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。
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Usage: redis-benchmark [-h <host>] [-p <port>] [-c <clients>] [-n <requests]> [-k <boolean>] -h <hostname> #指定服务器名称(default 127.0.0.1); -p <port> #指定服务器端口(default 6379); -s <socket> #指定服务器Socket(overrides host and port); -a <password> #指定Redis密码; -c <clients> #指定并行客户端数量 (default 50); -n <requests> #指定总的请求数量(default 100000); -d <size> #指定SET/GET一次数据大小 (default 2 Bytes); -dbnum <db> #选择指定的数据库(default 0); -k <boolean> #保持一个连接，一台服务器来处理这些请求 (default 1); -r <keyspacelen> #设置随机Key; -P <numreq> #Pipeline <numreq> 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）
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# 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: 1 100.00% <= 0 milliseconds 37764.35 requests per second #每秒请求数 ====== GET ====== 100000 requests completed in 1.70 seconds 1 parallel clients 1000 bytes payload keep alive: 1 100.00% <= 0 milliseconds 58962.27 requests per second |
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# 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: 1 0.00% <= 4 milliseconds .................... 100.00% <= 14 milliseconds 132450.33 requests per second ====== GET ====== 100000 requests completed in 0.78 seconds 1000 parallel clients 1000 bytes payload keep alive: 1 0.00% <= 3 milliseconds .................. 100.00% <= 8 milliseconds 128205.13 requests per second |
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# 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: 1 0.00% <= 28 milliseconds .......................... 100.00% <= 105 milliseconds 84817.64 requests per second ====== GET ====== 100000 requests completed in 1.24 seconds 5000 parallel clients 1000 bytes payload keep alive: 1 0.00% <= 35 milliseconds ....................... 100.00% <= 55 milliseconds 80580.17 requests per second |
下面提供一个CPU 8核，内存8G的压测结果。
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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: 1 98.95% <= 1 milliseconds ................... 100.00% <= 6 milliseconds 15379.88 requests per second ====== GET ====== 100000 requests completed in 6.68 seconds 1 parallel clients 1000 bytes payload keep alive: 1 98.91% <= 1 milliseconds .................. 100.00% <= 4 milliseconds 14965.58 requests per second |
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# 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: 1 0.00% <= 4 milliseconds .................... 103734.44 requests per second ====== GET ====== 100000 requests completed in 1.00 seconds 1000 parallel clients 1000 bytes payload keep alive: 1 0.00% <= 3 milliseconds ................... 100.00% <= 15 milliseconds 100300.91 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：
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# redis-benchmark -h 0.0.0.0 -p 6500 -c 1 -r 100000 -q 1000000 -t set -d 1000 -q 1000000 -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 -q 1000000 -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 -q 1000000 -t set -d 1000 -q: 83542.19 requests per second |
测试twemproxy
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# 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: 1 100.00% <= 0 milliseconds 9267.84 requests per second ====== GET ====== 10000 requests completed in 1.08 seconds 1 parallel clients 1000 bytes payload keep alive: 1 100.00% <= 0 milliseconds 9293.68 requests per second |
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# 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: 1 0.01% <= 3 milliseconds ................ 100.00% <= 20 milliseconds 55555.55 requests per second ====== GET ====== 10000 requests completed in 0.21 seconds 1000 parallel clients 1000 bytes payload keep alive: 1 0.01% <= 5 milliseconds .............. 100.00% <= 23 milliseconds 47393.37 requests per second |
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# 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: 1 0.01% <= 28 milliseconds ....................... 100.00% <= 87 milliseconds 35587.19 requests per second ====== GET ====== 10000 requests completed in 0.29 seconds 5000 parallel clients 1000 bytes payload keep alive: 1 0.01% <= 33 milliseconds .................... 100.00% <= 85 milliseconds 34364.26 requests per second |
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