Introduction
Redis NoSQL is a database based on a key (Key-Value) of, Redis may be made of Value String, hash, list, set, zset, Bitmaps, HyperLogLog data structures and algorithms, and other components. Redis also provides key expired, publish-subscribe, transaction, Lua script, Sentinel, Cluster and other functions. Redis command execution speed is very fast, according to the official performance can be achieved 10w + qps. In this paper, in the end so fast Redis where the following main points:
First, the development of language
and now we have a high-level programming language, such as Java, python and so on. You may find the C language is very old, but it is really useful, after all unix system is implemented in C, so C language is very close to the operating system language. Redis is using C language development, so the implementation will be faster.
Also say one more thing, college students a good learning C, will make you a better understanding of computer operating systems. Do not think learning a high-level language you can not focus on the bottom, always owe a debt to repay. Here recommend a book more difficult nut to "in-depth understanding of computing systems."
Second, pure memory access
Redis all data in memory, non-data synchronization to work in, is not required to read data from the disk, 0 times IO. Memory response time of about 100 nanoseconds, which is an important foundation of Redis fast speed. Take a look at CPU speed:
Face questions: single-threaded Redis why so fast?
Take my computers, clocked at 3.1G, which means you can perform 3.1 * 10 ^ 9 instructions per second. So the CPU to see the world is very, very slow, a hundred times slower than its memory, disk million times slower than him, you say fast unhappy?
Borrowed an "in-depth understanding of computer systems," the diagram shows a typical memory hierarchy, in the L0 layer, CPU can be accessed in a single clock cycle, based on the renewal of spring SRAM cache, you can in a few CPU clock cycle access to, and are based on DRAM main memory, you can have access to them in tens to hundreds of clock cycles.
三、单线程
第一，单线程简化算法的实现，并发的数据结构实现不但困难且测试也麻烦。第二，单线程避免了线程切换以及加锁释放锁带来的消耗，对于服务端开发来说，锁和线程切换通常是性能杀手。当然了，单线程也会有它的缺点，也是Redis的噩梦：阻塞。如果执行一个命令过长，那么会造成其他命令的阻塞，对于Redis是十分致命的，所以Redis是面向快速执行场景的数据库。
除了Redis之外，Node.js也是单线程，Nginx也是单线程，但他们都是服务器高性能的典范。
四、非阻塞多路I/O复用机制
在这之前先要说一下传统的阻塞I/O是如何工作的：当使用read或者write对某一文件描述符（File Descriptor FD）进行读写的时候，如果数据没有收到，那么该线程会被挂起，直到收到数据。阻塞模型虽然易于理解，但是在需要处理多个客户端任务的时候，不会使用阻塞模型。
I/O多路复用实际上是指多个连接的管理可以在同一进程。多路是指网络连接，复用只是同一个线程。在网络服务中，I/O多路复用起的作用是一次性把多个连接的事件通知业务代码处理，处理的方式由业务代码来决定。在I/O多路复用模型中，最重要的函数调用就是I/O 多路复用函数，该方法能同时监控多个文件描述符（fd）的读写情况，当其中的某些fd可读/写时，该方法就会返回可读/写的fd个数。
Redis使用epoll作为I/O多路复用技术的实现，再加上Redis自身的事件处理模型将epoll的read、write、close等都转换成事件，不在网络I/O上浪费过多的时间。实现对多个FD读写的监控，提高性能。
举个形象的例子吧。比如一个tcp服务器处理20个客户端socket。A方案：顺序处理，如果第一个socket因为网卡读数据处理慢了，一阻塞后面都玩蛋去。B方案：每个socket请求都创建一个分身子进程来处理，不说每个进程消耗大量系统资源，光是进程切换就够操作系统累的了。C方案（I/O复用模型，epoll）：将用户socket对应的fd注册进epoll（实际上服务器和操作系统之间传递的不是socket的fd而是fd_set的数据结构），然后epoll只告诉哪些需要读/写的socket，只需要处理那些活跃的、有变化的socket fd的就好了。这样，整个过程只在调用epoll的时候才会阻塞，收发客户消息是不会阻塞的。