Redis-benchmark是官方自带的Redis性能测试工具,可以有效的测试Redis服务的性能。

使用说明如下:

Usage: redis-benchmark [-h <host>] [-p <port>] [-c <clients>] [-n <requests]> [-k <boolean>]

 -h <hostname>      Server hostname (default 127.0.0.1)
-p <port> Server port (default )
-s <socket> Server socket (overrides host and port)
-c <clients> Number of parallel connections (default )
-n <requests> Total number of requests (default )
-d <size> Data size of SET/GET value in bytes (default )
-k <boolean> =keep alive =reconnect (default )
-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: instead of constant
keys, the <keyspacelen> argument determines the max
number of values for the random number. For instance
if set to only rand: - rand:
range will be allowed.
-P <numreq> Pipeline <numreq> requests. Default (no pipeline).
-q Quiet. Just show query/sec values
--csv Output in CSV format
-l Loop. Run the tests forever
-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.

测试命令事例:

1、redis-benchmark -h 192.168.1.201 -p 6379 -c 100 -n 100000 
100个并发连接,100000个请求,检测host为localhost 端口为6379的redis服务器性能

2、redis-benchmark -h 192.168.1.201 -p 6379 -q -d 100

测试存取大小为100字节的数据包的性能

3、redis-benchmark -t set,lpush -n 100000 -q

只测试某些操作的性能

4、redis-benchmark -n 100000 -q script load "redis.call('set','foo','bar')"

只测试某些数值存取的性能

测试结果分析:

   requests completed in 0.30 seconds
parallel clients
bytes payload
keep alive: 0.11% <= milliseconds
86.00% <= milliseconds
90.12% <= milliseconds
96.68% <= milliseconds
99.27% <= milliseconds
99.54% <= milliseconds
99.69% <= milliseconds
99.78% <= milliseconds
99.89% <= milliseconds
100.00% <= milliseconds
33222.59 requests per second ====== PING_BULK ======
requests completed in 0.27 seconds
parallel clients
bytes payload
keep alive: 0.93% <= milliseconds
97.66% <= milliseconds
100.00% <= milliseconds
37174.72 requests per second ====== SET ======
requests completed in 0.32 seconds
parallel clients
bytes payload
keep alive: 0.22% <= milliseconds
91.68% <= milliseconds
97.78% <= milliseconds
98.80% <= milliseconds
99.38% <= milliseconds
99.61% <= milliseconds
99.72% <= milliseconds
99.83% <= milliseconds
99.94% <= milliseconds
100.00% <= milliseconds
30959.75 requests per second ====== GET ======
requests completed in 0.28 seconds
parallel clients
bytes payload
keep alive: 0.55% <= milliseconds
98.86% <= milliseconds
100.00% <= milliseconds
35971.22 requests per second ====== INCR ======
requests completed in 0.14 seconds
parallel clients
bytes payload
keep alive: 95.61% <= milliseconds
100.00% <= milliseconds
69444.45 requests per second ====== LPUSH ======
requests completed in 0.21 seconds
parallel clients
bytes payload
keep alive: 18.33% <= milliseconds
100.00% <= milliseconds
48309.18 requests per second ====== LPOP ======
requests completed in 0.23 seconds
parallel clients
bytes payload
keep alive: 0.29% <= milliseconds
99.76% <= milliseconds
100.00% <= milliseconds
44052.86 requests per second ====== SADD ======
requests completed in 0.22 seconds
parallel clients
bytes payload
keep alive: 2.37% <= milliseconds
99.81% <= milliseconds
100.00% <= milliseconds
44444.45 requests per second ====== SPOP ======
requests completed in 0.22 seconds
parallel clients
bytes payload
keep alive: 4.27% <= milliseconds
99.84% <= milliseconds
100.00% <= milliseconds
44642.86 requests per second ====== LPUSH (needed to benchmark LRANGE) ======
requests completed in 0.22 seconds
parallel clients
bytes payload
keep alive: 12.35% <= milliseconds
99.62% <= milliseconds
100.00% <= milliseconds
46082.95 requests per second ====== LRANGE_100 (first elements) ======
requests completed in 0.48 seconds
parallel clients
bytes payload
keep alive: 0.01% <= milliseconds
3.27% <= milliseconds
98.71% <= milliseconds
99.93% <= milliseconds
100.00% <= milliseconds
20964.36 requests per second ====== LRANGE_300 (first elements) ======
requests completed in 1.26 seconds
parallel clients
bytes payload
keep alive: 0.01% <= milliseconds
0.14% <= milliseconds
0.90% <= milliseconds
7.03% <= milliseconds
31.68% <= milliseconds
78.93% <= milliseconds
98.88% <= milliseconds
99.56% <= milliseconds
99.72% <= milliseconds
99.95% <= milliseconds
100.00% <= milliseconds
7961.78 requests per second ====== LRANGE_500 (first elements) ======
requests completed in 1.82 seconds
parallel clients
bytes payload
keep alive: 0.01% <= milliseconds
0.06% <= milliseconds
0.14% <= milliseconds
0.30% <= milliseconds
0.99% <= milliseconds
2.91% <= milliseconds
8.11% <= milliseconds
43.15% <= milliseconds
88.38% <= milliseconds
97.25% <= milliseconds
98.61% <= milliseconds
99.26% <= milliseconds
99.30% <= milliseconds
99.44% <= milliseconds
99.48% <= milliseconds
99.64% <= milliseconds
99.85% <= milliseconds
99.92% <= milliseconds
99.95% <= milliseconds
99.96% <= milliseconds
99.97% <= milliseconds
100.00% <= milliseconds
5491.49 requests per second ====== LRANGE_600 (first elements) ======
requests completed in 2.29 seconds
parallel clients
bytes payload
keep alive: 0.01% <= milliseconds
0.05% <= milliseconds
0.10% <= milliseconds
0.19% <= milliseconds
0.34% <= milliseconds
0.46% <= milliseconds
0.58% <= milliseconds
4.46% <= milliseconds
21.80% <= milliseconds
40.48% <= milliseconds
60.14% <= milliseconds
79.81% <= milliseconds
93.77% <= milliseconds
97.14% <= milliseconds
98.67% <= milliseconds
99.08% <= milliseconds
99.30% <= milliseconds
99.41% <= milliseconds
99.52% <= milliseconds
99.61% <= milliseconds
99.79% <= milliseconds
99.88% <= milliseconds
99.89% <= milliseconds
99.95% <= milliseconds
99.96% <= milliseconds
99.97% <= milliseconds
99.98% <= milliseconds
100.00% <= milliseconds
4359.20 requests per second ====== MSET ( keys) ======
requests completed in 0.37 seconds
parallel clients
bytes payload
keep alive: 0.01% <= milliseconds
2.00% <= milliseconds
18.41% <= milliseconds
88.55% <= milliseconds
96.09% <= milliseconds
99.50% <= milliseconds
99.65% <= milliseconds
99.75% <= milliseconds
99.77% <= milliseconds
99.78% <= milliseconds
99.79% <= milliseconds
99.80% <= milliseconds
99.81% <= milliseconds
99.82% <= milliseconds
99.83% <= milliseconds
99.84% <= milliseconds
99.85% <= milliseconds
99.86% <= milliseconds
99.87% <= milliseconds
99.88% <= milliseconds
99.89% <= milliseconds
99.90% <= milliseconds
99.91% <= milliseconds
99.92% <= milliseconds
99.93% <= milliseconds
99.95% <= milliseconds
99.96% <= milliseconds
99.97% <= milliseconds
99.98% <= milliseconds
99.99% <= milliseconds
100.00% <= milliseconds
27173.91 requests per second

Redis-benchmark测试Redis性能的更多相关文章

  1. YCSB benchmark测试mongodb性能——和web服务器测试性能结果类似

    转自:http://blog.sina.com.cn/s/blog_48c95a190102v9kg.html         YCSB(Yahoo! Cloud Serving Benchmark) ...

  2. YCSB benchmark测试cassandra性能——和web服务器测试性能结果类似

    转自:http://www.itdadao.com/articles/c15a531189p0.html http://www.cnblogs.com/bettersky/p/6158172.html ...

  3. 【Redis】Redis-benchmark测试Redis性能

    Redis-benchmark是官方自带的Redis性能测试工具,可以有效的测试Redis服务的性能. 使用说明如下: Usage: redis-benchmark [-h <host>] ...

  4. Redis(十九):Redis压力测试工具benchmark

    redis-benchmark使用参数介绍 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 ...

  5. 【Azure Redis 缓存 Azure Cache For Redis】使用Redis自带redis-benchmark.exe命令测试Azure Redis的性能

    问题描述 关于Azure Redis的性能问题,在官方文档中,可以查看到不同层级Redis的最大连接数,每秒处理请求的性能. 基本缓存和标准缓存 C0 (250 MB) 缓存 - 最多支持 256 个 ...

  6. Azure Redis Cache (3) 在Windows 环境下使用Redis Benchmark

    <Windows Azure Platform 系列文章目录> 熟悉Redis环境的读者都知道,我们可以在Linux环境里,使用Redis Benchmark,测试Redis的性能. ht ...

  7. 搭建和测试 Redis 主备和集群

    本文章只是自我学习用,不适宜转载. 1. Redis主备集群 1.1 搭建步骤 机器:海航云虚机(2核4GB内存),使用 Centos 7.2 64bit 操作系统,IP 分别是 192.168.10 ...

  8. Redis QPS测试

    1.计算qps: 1)redis发布版本中自带了redis-benchmark性能测试工具,可以使用它计算qps.示例:使用50个并发连接,发出100000个请求,每个请求的数据为2kb,测试host ...

  9. 『性能』ServiceStack.Redis 和 StackExchange.Redis 性能比较

    背景 近来,需要用到 Redis 这类缓存技术 —— MongoDB 和 Redis 没有进行过比较. 我也懒得在这些细节上 纠结那么多 —— 按照网友给出的文章,听从网友建议,选择 Redis. R ...

随机推荐

  1. Tomcat性能调优方案

    一.操作系统调优 对于操作系统优化来说,是尽可能的增大可使用的内存容量.提高CPU的频率,保证文件系统的读写速率等.经过压力测试验证,在并发连接很多的情况下,CPU的处理能力越强,系统运行速度越快.. ...

  2. CMS

    一.任务简介: 开发简单的CMS.在数据库中创建新闻数据库表news,包含(题目.作者.日期.正文等字段):创建HTML模板文件:读取数据库所有数据的信息,并使用新闻信息 替换模板文件中的占位符,从而 ...

  3. Nuget很慢,我们该怎么办

    在VS中给项目添加程序已经采用NuGet 十分方便 不过很多时候速度很慢,一直显示“正在检索信息” 其实直接使用程序包管理控制台,速度就会好很多 如果命令不太会写,安装包名不是确认,可以先登录 htt ...

  4. Validating HTTP data with Play

    Validations ensure that the data has certain values or meets specific requirements. You can use vali ...

  5. Select-or-Die演示11种美化下拉框select方法

    在线预览 下载地址 在线实例 <div class="main"> <div class="mianc"> <h1>默认&l ...

  6. Kickoff - 创造可扩展的,响应式的网站

    Kickoff 是一个轻量级的前端框架,用于创建可扩展的,响应式的网站.作为前端开发人员,我们工作的类型越来越多样化.Kickoff 旨在帮助您在所有项目保持一致的结构和风格,无需添加其他框架. 在线 ...

  7. 向 Web 开发人员推荐35款 JavaScript 图形图表库

    图表是数据图形化的表示,通过形象的图表来展示数据,比如条形图,折线图,饼图等等.可视化图表可以帮助开发者更容易理解复杂的数据,提高生产的效率和 Web 应用和项目的可靠性. 在这篇文章中,我们收集了3 ...

  8. Office 365 – SharePoint 2013 Online 之WebPart开发、部署教程

    1.打开Visual Studio,新建一个项目,选择SharePoint空项目,如下图: 2.选择调试站点和沙盒解决方案,如下图: 3.在项目中,添加一个WebPart,如下图: 4.添加完毕的项目 ...

  9. 系统补丁对sharepoint很重要

    系统补丁对sharepoint很重要,会提高sharepoint运行效率,加载速度明显变快.

  10. iis7.5安装配置php环境

    前言 iis7.5是安装在win7.win8里的web服务器,win2003.win2000的web服务器使用的是iis6.0,由于win7.win8系统相比win2003.win2000有了改新革面 ...