一. 压测

你如果要对自己刚刚搭建好的redis做一个基准的压测，测一下你的redis的性能和QPS（query per second）。redis自己提供的redis-benchmark压测工具，是最快捷最方便的，当然啦，这个工具比较简单，用一些简单的操作和场景去压测。

1. 对redis读写分离架构进行压测，单实例写QPS+单实例读QPS

   redis-3.2.8/src./redis-benchmark -h 192.168.31.187-c <clients>       Number of parallel connections (default 50)
   -n <requests>      Total number of requests (default 100000)
   -d <size>          Data size of SET/GET value in bytes (default 2)
   

   根据你自己的高峰期的访问量，在高峰期，瞬时最大用户量会达到10万+，-c 100000，-n 10000000，-d 50。各种基准测试，直接出来

   1核1G，虚拟机====== PING_INLINE ======100000 requests completed in 1.28 seconds50 parallel clients3 bytes payloadkeep alive: 199.78% <= 1 milliseconds
   99.93% <= 2 milliseconds
   99.97% <= 3 milliseconds
   100.00% <= 3 milliseconds
   78308.54 requests per second====== PING_BULK ======100000 requests completed in 1.30 seconds50 parallel clients3 bytes payloadkeep alive: 199.87% <= 1 milliseconds
   100.00% <= 1 milliseconds
   76804.91 requests per second====== SET ======100000 requests completed in 2.50 seconds50 parallel clients3 bytes payloadkeep alive: 15.95% <= 1 milliseconds
   99.63% <= 2 milliseconds
   99.93% <= 3 milliseconds
   99.99% <= 4 milliseconds
   100.00% <= 4 milliseconds
   40032.03 requests per second====== GET ======100000 requests completed in 1.30 seconds50 parallel clients3 bytes payloadkeep alive: 199.73% <= 1 milliseconds
   100.00% <= 2 milliseconds
   100.00% <= 2 milliseconds
   76628.35 requests per second====== INCR ======100000 requests completed in 1.90 seconds50 parallel clients3 bytes payloadkeep alive: 180.92% <= 1 milliseconds
   99.81% <= 2 milliseconds
   99.95% <= 3 milliseconds
   99.96% <= 4 milliseconds
   99.97% <= 5 milliseconds
   100.00% <= 6 milliseconds
   52548.61 requests per second====== LPUSH ======100000 requests completed in 2.58 seconds50 parallel clients3 bytes payloadkeep alive: 13.76% <= 1 milliseconds
   99.61% <= 2 milliseconds
   99.93% <= 3 milliseconds
   100.00% <= 3 milliseconds
   38684.72 requests per second====== RPUSH ======100000 requests completed in 2.47 seconds50 parallel clients3 bytes payloadkeep alive: 16.87% <= 1 milliseconds
   99.69% <= 2 milliseconds
   99.87% <= 3 milliseconds
   99.99% <= 4 milliseconds
   100.00% <= 4 milliseconds
   40469.45 requests per second====== LPOP ======100000 requests completed in 2.26 seconds50 parallel clients3 bytes payloadkeep alive: 128.39% <= 1 milliseconds
   99.83% <= 2 milliseconds
   100.00% <= 2 milliseconds
   44306.60 requests per second====== RPOP ======100000 requests completed in 2.18 seconds50 parallel clients3 bytes payloadkeep alive: 136.08% <= 1 milliseconds
   99.75% <= 2 milliseconds
   100.00% <= 2 milliseconds
   45871.56 requests per second====== SADD ======100000 requests completed in 1.23 seconds50 parallel clients3 bytes payloadkeep alive: 199.94% <= 1 milliseconds
   100.00% <= 2 milliseconds
   100.00% <= 2 milliseconds
   81168.83 requests per second====== SPOP ======100000 requests completed in 1.28 seconds50 parallel clients3 bytes payloadkeep alive: 199.80% <= 1 milliseconds
   99.96% <= 2 milliseconds
   99.96% <= 3 milliseconds
   99.97% <= 5 milliseconds
   100.00% <= 5 milliseconds
   78369.91 requests per second====== LPUSH (needed to benchmark LRANGE) ======100000 requests completed in 2.47 seconds50 parallel clients3 bytes payloadkeep alive: 115.29% <= 1 milliseconds
   99.64% <= 2 milliseconds
   99.94% <= 3 milliseconds
   100.00% <= 3 milliseconds
   40420.37 requests per second====== LRANGE_100 (first 100 elements) ======100000 requests completed in 3.69 seconds50 parallel clients3 bytes payloadkeep alive: 130.86% <= 1 milliseconds
   96.99% <= 2 milliseconds
   99.94% <= 3 milliseconds
   99.99% <= 4 milliseconds
   100.00% <= 4 milliseconds
   27085.59 requests per second====== LRANGE_300 (first 300 elements) ======100000 requests completed in 10.22 seconds50 parallel clients3 bytes payloadkeep alive: 10.03% <= 1 milliseconds
   5.90% <= 2 milliseconds
   90.68% <= 3 milliseconds
   95.46% <= 4 milliseconds
   97.67% <= 5 milliseconds
   99.12% <= 6 milliseconds
   99.98% <= 7 milliseconds
   100.00% <= 7 milliseconds
   9784.74 requests per second====== LRANGE_500 (first 450 elements) ======100000 requests completed in 14.71 seconds50 parallel clients3 bytes payloadkeep alive: 10.00% <= 1 milliseconds
   0.07% <= 2 milliseconds
   1.59% <= 3 milliseconds
   89.26% <= 4 milliseconds
   97.90% <= 5 milliseconds
   99.24% <= 6 milliseconds
   99.73% <= 7 milliseconds
   99.89% <= 8 milliseconds
   99.96% <= 9 milliseconds
   99.99% <= 10 milliseconds
   100.00% <= 10 milliseconds
   6799.48 requests per second====== LRANGE_600 (first 600 elements) ======100000 requests completed in 18.56 seconds50 parallel clients3 bytes payloadkeep alive: 10.00% <= 2 milliseconds
   0.23% <= 3 milliseconds
   1.75% <= 4 milliseconds
   91.17% <= 5 milliseconds
   98.16% <= 6 milliseconds
   99.04% <= 7 milliseconds
   99.83% <= 8 milliseconds
   99.95% <= 9 milliseconds
   99.98% <= 10 milliseconds
   100.00% <= 10 milliseconds
   5387.35 requests per second====== MSET (10 keys) ======100000 requests completed in 4.02 seconds50 parallel clients3 bytes payloadkeep alive: 10.01% <= 1 milliseconds
   53.22% <= 2 milliseconds
   99.12% <= 3 milliseconds
   99.55% <= 4 milliseconds
   99.70% <= 5 milliseconds
   99.90% <= 6 milliseconds
   99.95% <= 7 milliseconds
   100.00% <= 8 milliseconds
   24869.44 requests per second
   

   (1) redis性能一般根据服务器的机器性能和配置，机器越牛逼，配置越高单机上十几万，单机上二十万。
   (2) 但在很多公司里，一般是一些低配置的服务器，业务操作又复杂度。如在大公司里，公司会提供统一的云平台，比如京东、腾讯、BAT、其他的一些、小米、美团虚拟机，低配。搭建一些集群，专门为某个项目，搭建的专用集群，4核4G内存，比较复杂的操作，数据比较大，几万，单机做到，差不多了。redis提供的高并发，至少到上万，没问题

   (3) 一般redisf支持几万~十几万/二十万不等QPS，自己不同公司，不同服务器，自己去测试，跟生产环境还有区别生产环境，大量的网络请求的调用，网络本身就有开销，你的redis的吞吐量就不一定那么高了

   (4) QPS的两个杀手：一个是复杂操作，lrange，挺多的; value很大，2 byte
   如：缓存做商品详情页的cache，可能是需要把大串数据，拼接在一起，作为一个json串，大小可能都几k，几个byte

二. 水平扩容redis读节点，提升度吞吐量

使用Master+多slave节点，单个从节点读请QPS在5万左右，两个redis从节点，所有的读请求打到两台机器上去，承载整个集群读QPS在10万+。