Redis自己提供了一个性能测试工具redis-benchmark。redis-benchmark可以模拟N个机器，同时发送M个请求。
用法：redis-benchmark [-h
-h <hostname> Server hostname (default 127.0.0.1)
-p <port> Server port (default 6379)
-s <socket> Server socket (overrides host and port)
-c <clients> Number of parallel connections (default 50) 并发客户端数
-n <requests> Total number of requests (default 10000) 请求数量
-d <size> Data size of SET/GET value in bytes (default 2) set 数据大小
-k <boolean> 1=keep alive 0=reconnect (default 1) 是否采用keep alive模式
-r <keyspacelen> Use random keys for SET/GET/INCR, random values for SADD
Using this option the benchmark will get/set keys
in the form mykey_rand:000000012456 instead of constant
keys, the <keyspacelen> argument determines the max
number of values for the random number. For instance
if set to 10 only rand:000000000000 - rand:000000000009
range will be allowed.
-P <numreq> Pipeline <numreq> requests. Default 1 (no pipeline). 是否采用Pipeline模式请求，默认不采用
-q Quiet. Just show query/sec values 仅仅显示查询时间
--csv Output in CSV format 导出为CSV格式
-l Loop. Run the tests forever 循环测试
-t <tests> Only run the comma separated list of tests. The test
names are the same as the ones produced as output.
-I Idle mode. Just open N idle connections and wait.常用的办法
redis-benchmark -q -n 1000 PING_INLINE: 20408.16 requests per second PING_BULK: 25000.00 requests per second SET: 18181.82 requests per second GET: 21739.13 requests per second INCR: 27027.03 requests per second LPUSH: 27027.03 requests per second LPOP: 27027.03 requests per second SADD: 27027.03 requests per second SPOP: 22222.22 requests per second LPUSH (needed to benchmark LRANGE): 27777.78 requests per second LRANGE_100 (first 100 elements): 10989.01 requests per second LRANGE_300 (first 300 elements): 5434.78 requests per second LRANGE_500 (first 450 elements): 4444.44 requests per second LRANGE_600 (first 600 elements): 3164.56 requests per second MSET (10 keys): 18518.52 requests per second
可以看出在我的笔记本上，redis每秒可以处理上万条请求。
如果要显示详细资料的方式
redis-benchmark -n 1000
redis-benchmark -n 1000 ====== PING_INLINE ====== 1000 requests completed in 0.04 seconds 50 parallel clients 3 bytes payload keep alive: 1 7.30% <= 1 milliseconds 85.80% <= 2 milliseconds 95.10% <= 4 milliseconds 96.90% <= 5 milliseconds 100.00% <= 5 milliseconds 23255.81 requests per second ====== PING_BULK ====== 1000 requests completed in 0.05 seconds 50 parallel clients 3 bytes payload keep alive: 1 11.30% <= 1 milliseconds 77.00% <= 2 milliseconds 92.10% <= 3 milliseconds 95.10% <= 5 milliseconds 100.00% <= 5 milliseconds 22222.22 requests per second ====== SET ====== 1000 requests completed in 0.04 seconds 50 parallel clients 3 bytes payload keep alive: 1 11.20% <= 1 milliseconds 88.40% <= 2 milliseconds 93.30% <= 3 milliseconds 94.00% <= 4 milliseconds 94.60% <= 5 milliseconds 98.20% <= 6 milliseconds 98.60% <= 8 milliseconds 100.00% <= 8 milliseconds 22727.27 requests per second ====== GET ====== 1000 requests completed in 0.04 seconds 50 parallel clients 3 bytes payload keep alive: 1 6.30% <= 1 milliseconds 86.00% <= 2 milliseconds 100.00% <= 2 milliseconds 25641.03 requests per second ====== INCR ====== 1000 requests completed in 0.05 seconds 50 parallel clients 3 bytes payload keep alive: 1 7.30% <= 1 milliseconds 77.30% <= 2 milliseconds 83.40% <= 3 milliseconds 95.10% <= 6 milliseconds 98.20% <= 7 milliseconds 100.00% <= 7 milliseconds 20408.16 requests per second ====== LPUSH ====== 1000 requests completed in 0.04 seconds 50 parallel clients 3 bytes payload keep alive: 1 10.00% <= 1 milliseconds 75.00% <= 2 milliseconds 97.20% <= 3 milliseconds 100.00% <= 3 milliseconds 23809.52 requests per second ====== LPOP ====== 1000 requests completed in 0.05 seconds 50 parallel clients 3 bytes payload keep alive: 1 7.00% <= 1 milliseconds 79.30% <= 2 milliseconds 88.50% <= 3 milliseconds 90.60% <= 4 milliseconds 97.40% <= 5 milliseconds 100.00% <= 5 milliseconds 21276.60 requests per second ====== SADD ====== 1000 requests completed in 0.04 seconds 50 parallel clients 3 bytes payload keep alive: 1 11.10% <= 1 milliseconds 83.40% <= 2 milliseconds 91.70% <= 3 milliseconds 97.80% <= 4 milliseconds 99.60% <= 5 milliseconds 100.00% <= 5 milliseconds 23809.52 requests per second ====== SPOP ====== 1000 requests completed in 0.04 seconds 50 parallel clients 3 bytes payload keep alive: 1 7.90% <= 1 milliseconds 77.90% <= 2 milliseconds 90.60% <= 3 milliseconds 95.10% <= 5 milliseconds 100.00% <= 5 milliseconds 23255.81 requests per second ====== LPUSH (needed to benchmark LRANGE) ====== 1000 requests completed in 0.04 seconds 50 parallel clients 3 bytes payload keep alive: 1 10.10% <= 1 milliseconds 95.40% <= 4 milliseconds 97.60% <= 6 milliseconds 100.00% <= 6 milliseconds 22727.27 requests per second ====== LRANGE_100 (first 100 elements) ====== 1000 requests completed in 0.09 seconds 50 parallel clients 3 bytes payload keep alive: 1 1.20% <= 1 milliseconds 10.00% <= 2 milliseconds 50.90% <= 3 milliseconds 87.90% <= 4 milliseconds 99.60% <= 5 milliseconds 100.00% <= 5 milliseconds 10869.57 requests per second ====== LRANGE_300 (first 300 elements) ====== 1000 requests completed in 0.18 seconds 50 parallel clients 3 bytes payload keep alive: 1 0.90% <= 1 milliseconds 6.70% <= 2 milliseconds 13.70% <= 3 milliseconds 26.40% <= 4 milliseconds 41.00% <= 5 milliseconds 60.20% <= 6 milliseconds 76.40% <= 7 milliseconds 88.20% <= 8 milliseconds 95.80% <= 9 milliseconds 98.50% <= 10 milliseconds 99.60% <= 11 milliseconds 100.00% <= 11 milliseconds 5494.51 requests per second ====== LRANGE_500 (first 450 elements) ====== 1000 requests completed in 0.24 seconds 50 parallel clients 3 bytes payload keep alive: 1 0.10% <= 1 milliseconds 1.90% <= 2 milliseconds 5.60% <= 3 milliseconds 13.10% <= 4 milliseconds 26.80% <= 5 milliseconds 40.00% <= 6 milliseconds 53.90% <= 7 milliseconds 63.60% <= 8 milliseconds 74.70% <= 9 milliseconds 82.90% <= 10 milliseconds 90.00% <= 11 milliseconds 95.90% <= 12 milliseconds 99.30% <= 13 milliseconds 99.80% <= 14 milliseconds 100.00% <= 14 milliseconds 4132.23 requests per second ====== LRANGE_600 (first 600 elements) ====== 1000 requests completed in 0.28 seconds 50 parallel clients 3 bytes payload keep alive: 1 0.10% <= 1 milliseconds 0.40% <= 2 milliseconds 2.30% <= 3 milliseconds 9.10% <= 4 milliseconds 20.90% <= 5 milliseconds 32.50% <= 6 milliseconds 42.70% <= 7 milliseconds 56.10% <= 8 milliseconds 69.20% <= 9 milliseconds 83.10% <= 10 milliseconds 90.40% <= 11 milliseconds 95.90% <= 12 milliseconds 97.00% <= 13 milliseconds 97.70% <= 14 milliseconds 97.90% <= 15 milliseconds 98.20% <= 16 milliseconds 98.60% <= 17 milliseconds 98.90% <= 18 milliseconds 99.30% <= 19 milliseconds 99.60% <= 20 milliseconds 100.00% <= 21 milliseconds 3558.72 requests per second ====== MSET (10 keys) ====== 1000 requests completed in 0.06 seconds 50 parallel clients 3 bytes payload keep alive: 1 5.60% <= 1 milliseconds 47.20% <= 2 milliseconds 89.40% <= 3 milliseconds 95.80% <= 8 milliseconds 95.90% <= 10 milliseconds 99.50% <= 11 milliseconds 100.00% <= 11 milliseconds 16666.67 requests per second
很多时候，我们在局域网会调用redis，比如我有10台机器，可能同时产生大量的数据，然后这些数据同时存储在1台redis上。那么我们可以分别在10台机器上测试
redis-benchmark -h 192.168.1.124 -p 6379 -n 100000