标签：test

redis analyst (6)- simple performance test for mini cluster

其实测试这种分布式系统意义不是非常大，因为通过监控metric发现性能瓶时，直接增加节点即可，在很大范围内，节点数不是非常多的话，基本上处理能力呈线形增长，直接引用源作者的话：

“High performance and linear scalability up to 1000 nodes. There are no proxies, asynchronous replication is used, and no merge operations are performed on values.”

但是为什么要做一个简单的性能测试，因为第一次部署redis cluster，到底部署什么样的规模才能满足需求是无法回避的问题。所以还是简单测试下，为什么称为简单测试，因为实际环境中的软硬件配置、实际应用操作的读写比例、读写内容大小、读写波动范围、读写的机器数、线程数等实际场景，远不是本地可以简单真实模拟的。所以这里只是简单测试下(关注点在速度)，以有个感性的认识，以回答部署需要什么样的规模等问题。


127.0.0.1:7001>cluster nodes
87903653548352f6c3fdc0fa1ad9fc68de147fcd 10.224.2.142:7001 myself,slave 798f74b21c15120517d44bacfc7b5319b484244b 0 0 2 connected
3892d1dfa68d9976ce44b19e532d9c0e80a0357d 10.224.2.141:7001 slave b2b98976dfbc9f85bf714b385e508b3441c51338 0 1517983027812 17 connected
798f74b21c15120517d44bacfc7b5319b484244b 10.224.2.145:7001 master - 0 1517983028313 5 connected 5461-10922
b2b98976dfbc9f85bf714b385e508b3441c51338 10.224.2.144:7001 master - 0 1517983027813 17 connected 10923-16383
b71b412857c43e05a32a796fbc0de2e7d667cb67 10.224.2.143:7001 slave 912a1efa1f4085b4b7333706e546f64d16580761 0 1517983026306 6 connected
912a1efa1f4085b4b7333706e546f64d16580761 10.224.2.146:7001 master - 0 1517983026809 6 connected 0-5460

 

Redis Cluster  Node number Mini Redis cluster (6 nodes:  3*2 )
 Configure  Hardware  Cpu: 2 * Intel(R) Xeon(R) CPU E5-2650 v2 @ 2.60GHz

Memory:  4G(3924392)
 Software  #disable save cache content to disk
save “”
appendonly no# memory limit
maxmemory 1G
maxmemory-policy allkeys-lru		  make sure never reach max memroy
 Test Machine   Node number  15
 Configure Hardware configures Cpu: 2 * Intel(R) Xeon(R) CPU E5-2650 v2 @ 2.60GHz

Memory:  8G(8180636)
Software configures Jedis connection pool :

DEFAULT_MAX_TOTAL = 8
 Test method  Operation  write Test1: 10(machine) * 50(thread per machine) * 20K(write operation)= 10000K

Test2: 15(machine) * 50(thread per machine) * 20K(write operation)= 15000K

  String set(final String key, final String value)(1) key size: about 30

(2) value: size:

about 30
read  Test1: 10(machine) * 50(thread per machine) * 20K( read operation)= 10000K. data base existed 10000K records

Test2: 15(machine) * 50(thread per machine) * 20K( read operation)= 15000K,  data base exixted 15000K records

 String get(final String key)

(1) no hit

(2) key size:about 30
  Test result  OPS  Read  100K
 Write  50K
 Success Ratio Read  100%
 Write  100%

通过下图可知：测试中的key分布比较均匀，所有的压力平坦到3个master中，虽然测试的总tps很高，但是由于三个人干活，导致每个节点其实也还好，凸显分布式优点。

operation per second

测试结论： redis cluster的最小集（3*2），单纯考虑速度，不考虑容量限制，已经能支持很高TPS的需求了，另外需要注意的事，这是理想的测试，所以实际评估中仅供参考。

题外： 将读写测试1:1混合，会怎样，将两种测试同时并发执行，还能达到10万/S读，5万每S写么？测试结果如下：

总的OPS，只能达到45Kops, 然后读写吞吐量基本差不多1:1。这种数据比单纯只测一种更具有实际参考价值。

concurrent write/read

Open source: server-test-toolkit

SST is an open source project which is designed for test automation of server applications.

 Code

Code SVN: https://server-test-toolkit.googlecode.com/svn/trunk/

Apache Maven: http://search.maven.org/#browse%7C779006397

<dependency>
   <groupId>com.googlecode.server-test-toolkit</groupId>
   <artifactId>server-test-toolkit</artifactId>
   <version>2.2.6</version>
</dependency>

Release Version: http://code.google.com/p/server-test-toolkit/wiki/ReleaseVersion?ts=1398301402&updated=ReleaseVersion

 Features

– Remote Shell Tool

  • Feature; shell commands’ execute and results retrieve based on remote linux server;
  • Use: grep server logs, modify config, block connection, get cpu/io/memory/swap performance data etc.

– Remote Storage Tool

  • Feature: download/upload file with remote ftp/sftp server;
  • Use: prepare and use test data in one centra ftp/sftp server.

– Random File Tool

  • Feature: generate several kinds of file: doc/txt/jpg/pdf for test data
  • Use: test data prepare, used for storage applications.

– General DB Access Tool

  • Feature: access db and do operations.
  • Use: check records in database

– Job Schedule Tool

  • Feature: encapsulate quartz to supported job config/execute and register mbean for monitor support
  • Use: define some jobs to do some tasks.

– Popular Services Access Tool

  • Feature: provide the access interfaces for popular services such as memcached/zookeeper
  • Use: server applications often contain popular open source services, so this tool provide the common access methods for popular ones.

– Effetive Util tool

  • Feature: disk/io/memory/trackid/sleep/validation/performance etc
  • Use: util tool will help coder code more effectivly

 Feedback

Welcome to contact me with email:fujian1115@gmail.com if you has followed cases:

– Bugs or Issues

– Design improve advices

– Other uncovered requirements

Thanks for your sharing!