性能测试
Redis自带了一个叫 redis-benchmark的工具来模拟N个客户端同时发出M个请求，（类似于Apache ab程序），你可以使用redis-benchmark -h来查看基准参数。
Usage: redis-benchmark [-h ] [-p ] [-c ] [-n [-k ]-h #指定服务器名称(default 127.0.0.1);-p #指定服务器端口(default 6379);-s #指定服务器Socket(overrides host and port);-a #指定Redis密码;-c #指定并行客户端数量 (default 50);-n #指定总的请求数量(default 100000);-d #指定SET/GET一次数据大小 (default 2 Bytes);-dbnum #选择指定的数据库(default 0);-k #保持一个连接，一台服务器来处理这些请求 (default 1);-r #设置随机Key;-P #Pipeline requests. Default 1 (no pipeline).-q #显示每秒钟能处理多少请求数结果;--csv #输出为CSV格式;-l #Loop. Run the tests forever.-I #Idle mode. Just open N idle connections and wait.
这里用redis自带的benchmark工具测试，由于twemproxy不支持ping命令，所以对于twemproxy只测试set, get, incr, lpush, lpop, sadd, spop, lpush, lrange_100, lrange_300, lrange_500, lrange_600,mset命令。
Redis单实例简单测试
1）客户端分别为1/1000/5000，总请求数为100000，Key大小为1k，针对set/get命令测试QPS和完成时间（服务器：CPU 64核，内存 64G）
# redis-benchmark -h 0.0.0.0 -p 6500 -c 1 -t set,get -d 1000====== SET ====== 100000 requests completed in 2.65 seconds #完成时间 1 parallel clients 1000 bytes payload keep alive: 1100.00% < = 0 milliseconds37764.35 requests per second #每秒请求数====== GET ====== 100000 requests completed in 1.70 seconds 1 parallel clients 1000 bytes payload keep alive: 1100.00% <= 0 milliseconds58962.27 requests per second
# redis-benchmark -h 0.0.0.0 -p 6500 -c 1000 -t set,get -d 1000====== SET ====== 100000 requests completed in 0.75 seconds 1000 parallel clients 1000 bytes payload keep alive: 10.00% < = 4 milliseconds....................100.00% <= 14 milliseconds132450.33 requests per second====== GET ====== 100000 requests completed in 0.78 seconds 1000 parallel clients 1000 bytes payload keep alive: 10.00% <= 3 milliseconds..................100.00% <= 8 milliseconds128205.13 requests per second
# redis-benchmark -h 0.0.0.0 -p 6500 -c 5000 -t set,get -d 1000====== SET ====== 100000 requests completed in 1.18 seconds 5000 parallel clients 1000 bytes payload keep alive: 10.00% < = 28 milliseconds..........................100.00% <= 105 milliseconds84817.64 requests per second====== GET ====== 100000 requests completed in 1.24 seconds 5000 parallel clients 1000 bytes payload keep alive: 10.00% <= 35 milliseconds.......................100.00% <= 55 milliseconds80580.17 requests per second
下面提供一个CPU 8核，内存8G的压测结果。
root@shd-ops-mng1:~ # redis-benchmark -h 0.0.0.0 -p 6380 -c 1 -t set,get -d 1000====== SET ====== 100000 requests completed in 6.50 seconds 1 parallel clients 1000 bytes payload keep alive: 198.95% < = 1 milliseconds...................100.00% <= 6 milliseconds15379.88 requests per second====== GET ====== 100000 requests completed in 6.68 seconds 1 parallel clients 1000 bytes payload keep alive: 198.91% <= 1 milliseconds..................100.00% <= 4 milliseconds14965.58 requests per second
# redis-benchmark -h 0.0.0.0 -p 6380 -c 1000 -t set,get -d 1000====== SET ====== 100000 requests completed in 0.96 seconds 1000 parallel clients 1000 bytes payload keep alive: 10.00% < = 4 milliseconds....................103734.44 requests per second====== GET ====== 100000 requests completed in 1.00 seconds 1000 parallel clients 1000 bytes payload keep alive: 10.00% <= 3 milliseconds...................100.00% <= 15 milliseconds100300.91 requests per second
默认情况下面，基准测试使用单一的key。在一个基于内存的数据库里， 单一key测试和真实情况下面不会有巨大变化。当然，使用一个大的key范围空间， 可以模拟现实情况下面的缓存不命中情况。
这时候我们可以使用-r命令。比如，假设我们想设置10万随机key连续SET 100万次，连接客户端分别为1/5/1000，我们可以使用下列的命令：
# redis-benchmark -h 0.0.0.0 -p 6500 -c 1 -r 100000 -q 1000000 -t set -d 1000 -q1000000 -t set -d 1000 -q: 63051.70 requests per second# redis-benchmark -h 0.0.0.0 -p 6500 -c 1000 -r 100000 -q 1000000 -t set -d 1000 -q1000000 -t set -d 1000 -q: 94966.77 requests per second# redis-benchmark -h 0.0.0.0 -p 6500 -c 5000 -r 100000 -q 1000000 -t set -d 1000 -q1000000 -t set -d 1000 -q: 83542.19 requests per second
测试twemproxy
# redis-benchmark -h 0.0.0.0 -p 36379 -c 1 -t set,get -d 1000 ====== SET ====== 10000 requests completed in 1.08 seconds 1 parallel clients 1000 bytes payload keep alive: 1100.00% < = 0 milliseconds9267.84 requests per second====== GET ====== 10000 requests completed in 1.08 seconds 1 parallel clients 1000 bytes payload keep alive: 1100.00% <= 0 milliseconds9293.68 requests per second
# redis-benchmark -h 0.0.0.0 -p 36379 -c 1000 -t set,get -d 1000 ====== SET ====== 10000 requests completed in 0.18 seconds 1000 parallel clients 1000 bytes payload keep alive: 10.01% < = 3 milliseconds................100.00% <= 20 milliseconds55555.55 requests per second====== GET ====== 10000 requests completed in 0.21 seconds 1000 parallel clients 1000 bytes payload keep alive: 10.01% <= 5 milliseconds..............100.00% <= 23 milliseconds47393.37 requests per second
# redis-benchmark -h 0.0.0.0 -p 36379 -c 5000 -t set,get -d 1000 ====== SET ====== 10000 requests completed in 0.28 seconds 5000 parallel clients 1000 bytes payload keep alive: 10.01% < = 28 milliseconds.......................100.00% <= 87 milliseconds35587.19 requests per second====== GET ====== 10000 requests completed in 0.29 seconds 5000 parallel clients 1000 bytes payload keep alive: 10.01% <= 33 milliseconds....................100.00% <= 85 milliseconds34364.26 requests per second
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