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 #Pipelinerequests. 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: 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

# 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

# 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。

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

# 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：

# 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

# 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

# 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

# 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