elasticsearch性能测试工具rally深入详解

elasticsearch性能测试工具rally深入详解点此链接

题记

elasticsearch性能测试研究了很久,自己想过通过批量导入数据,然后记录时间,统计CPU、内存等变化,计算得出某个性能指标。但显然,数据量起伏不定,非常不准确。

研究发现,github上提供了rally作为elasticsearch的性能测试工具,较好的解决了es性能测试问题。


1、esrally功能:es的性能测试工具。

esrally不支持windows版本,目前只支持Linux和Mac OS。

esrally的运行基于以下两点假设:

1)所有运行在同一台机器完成。(未来改假设条件可能会去掉)

2)你需要向Elasticsearch索引中添加特定的数据集,然后在其上进行基准查询(benchmarking queries).


2、esrally安装:

前提:验证是否安装了以下内容(注意版本)

Python 3.4+ available as python3 on the path (verify with: python3 --version which should print Python 3.4.0 or higher)

pip3 available on the path (verify with pip3 --version)

JDK 8

git


如下所示:


[root@laoyang git-2.4.0]# python

Python 3.5.1 (default, Aug 2 2016, 09:53:20)

[GCC 4.4.7 20120313 (Red Hat 4.4.7-17)] on linux

Type "help", "copyright", "credits" or "license" for more information.


[root@laoyang git-2.4.0]# git --version

git version 2.4.0


[root@laoyang git-2.4.0]# java -version

java version "1.8.0_91"

Java(TM) SE Runtime Environment (build 1.8.0_91-b14)

Java HotSpot(TM) 64-Bit Server VM (build 25.91-b14, mixed mode)


[root@laoyang git-2.4.0]# find / -name "pip3"

/usr/bin/pip3

/usr/local/python3/bin/pip3

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步骤1:安装 Rally

pip3 install esrally


步骤2:配置 Rally

调用: esrally configure 会提示让你输入 java8.home(也就是JAVA_HOME设定的环境变量路径)。

仅java8.home使用自己本机的JAVA_HOME环境变量路径,其他采用默认值即可。


[root@laoyang .rally]# cat /root/.rally/rally.ini

[meta]

config.version = 5


[system]

root.dir = /root/.rally/benchmarks

log.root.dir = logs

env.name = local


[source]

local.src.dir=/root/.rally/src   #注意,此路径并非elaticsearch安装路径。

remote.repo.url=https://github.com/elastic/elasticsearch.git


[provisioning]

local.install.dir = install


[runtime]

java8.home = /opt/jdk1.8.0_91  #注意,JAVA_HOME 路径为:/opt/jdk1.8.0_91


[benchmarks]

local.dataset.cache = ${system:root.dir}/data


[reporting]

datastore.type = elaticsearch

datastore.host = 10.0.1.30

datastore.port = 9200

datastore.secure = False

datastore.user =

datastore.password =


[tracks]

default.url = https://github.com/elastic/rally-tracks

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步骤3:运行esrally

由于elasticsearch的运行必须非root账户。esrally建议用非root账户执行。


3、esrally执行常见问题及解决方案

问题1:版本用哪个版本?

目前用最新版本 Rally 0.3.2(2016-8-7发行)。


问题2:注意gradle需要2.13版本,高版本会不兼容。

[root@laoyang caches]# ll /usr/bin/gradle

lrwxrwxrwx 1 root root 27 Aug 5 17:13 /usr/bin/gradle -> /opt/gradle-2.13/bin/gradle


问题3:安装时候提示 documents.json.bz2 无法下载成功。

1)手动下载: http://benchmarks.elasticsearch.org.s3.amazonaws.com/corpora/geonames/documents.json.bz2

2)移动到 /root/.rally/benchmarks/data/geonames/(对于root用户)

对于非root用户,elaticsearch用户,移动路径为:/home/elasticsearch/benchmarks/data/geonames/


问题4: esrally单独运行和加参数运行区别?

esrally单独运行:非常方便的指令,等价于 :esrally --pipeline=from-sources --version=current. Rally 将要通过Gradle从源码编译elasticsearch。

esrally --pipline=from-distribution --distribution-version=2.3.4, Rally将要从 https://download.elasticsearch.org/elasticsearch/release/org/elasticsearch/distribution/tar/elasticsearch/2.3.4/elasticsearch-2.3.4.tar.gz


下载elaticsearch2.3.4版本运行。


问题5: Could not resolve all dependencies for configuration ‘:benchmarks:classpath’.

37 > Could not download shadow.jar (com.github.jengelman.gradle.plugins:shadow:1.2.3)如何解决?

root账户下:


cd /home/elasticsearch/.rally/benchmarks/src

gradle :distribution:tar:assemble


正确提示信息为:


deprecated API.

Note: Recompile with -Xlint:deprecation for details.

:modules:transport-netty4:processResources UP-TO-DATE

:modules:transport-netty4:classes

:modules:transport-netty4:jar

:modules:transport-netty4:copyPluginPropertiesTemplate

:modules:transport-netty4:pluginProperties

:modules:transport-netty4:bundlePlugin

:distribution:buildModules

:distribution:tar:buildTar

:distribution:tar:generatePomFileForNebulaPublication

:distribution:tar:signArchives SKIPPED

:distribution:tar:assemble


BUILD SUCCESSFUL

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4、esrally最终运行结果:

Preparing for race (might take a few moments) ...

 Building from sources ...

/home/elasticsearch/.rally/benchmarks/races/2016-08-08-07-29-59/local/logs/rally_out.logRacing on track [geonames] and challenge [append-no-conflicts] with car [defaults]

 Benchmarking indexing at 12183.1 docs/s [100% done]

 Benchmarking stats (warmup iteration 100/100) [100% done]

 Benchmarking stats (iteration 100/100) [100% done]

 Benchmarking search (warmup iteration 100/100) [100% done]

 Benchmarking search (iteration 100/100) [100% done]

------------------------------------------------------

 _______ __ _____

 / ____(_)___ ____ _/ / / ___/_________ ________

 / /_ / / __ \/ __ `/ / \__ \/ ___/ __ \/ ___/ _ \

/ __/ / / / / / /_/ / / ___/ / /__/ /_/ / / / __/

/_/ /_/_/ /_/\__,_/_/ /____/\___/\____/_/ \___/

------------------------------------------------------

| Metric | Value |

|----------------------------------------------------------:|----------:|

| Min Indexing Throughput [docs/s] | 11949 |

| Median Indexing Throughput [docs/s] | 12307 |

| Max Indexing Throughput [docs/s] | 13349 |

| Indexing time [min] | 164.045 |

| Merge time [min] | 32.3815 |

| Refresh time [min] | 8.82333 |

| Flush time [min] | 1.63852 |

| Merge throttle time [min] | 1.45482 |

| Query latency default (90.0 percentile) [ms] | 68.8676 |

| Query latency default (99.0 percentile) [ms] | 77.6009 |

| Query latency default (100 percentile) [ms] | 78.8328 |

| Query latency term (90.0 percentile) [ms] | 4.63227 |

| Query latency term (99.0 percentile) [ms] | 10.9506 |

| Query latency term (100 percentile) [ms] | 13.0573 |

| Query latency phrase (90.0 percentile) [ms] | 6.35018 |

| Query latency phrase (99.0 percentile) [ms] | 13.1745 |

| Query latency phrase (100 percentile) [ms] | 14.2399 |

| Query latency country_agg_uncached (90.0 percentile) [ms] | 361.913 |

| Query latency country_agg_uncached (99.0 percentile) [ms] | 384.75 |

| Query latency country_agg_uncached (100 percentile) [ms] | 392.645 |

| Query latency country_agg_cached (90.0 percentile) [ms] | 7.71451 |

| Query latency country_agg_cached (99.0 percentile) [ms] | 17.4704 |

| Query latency country_agg_cached (100 percentile) [ms] | 18.4851 |

| Query latency scroll (90.0 percentile) [ms] | 50.4234 |

| Query latency scroll (99.0 percentile) [ms] | 50.9866 |

| Query latency scroll (100 percentile) [ms] | 51.2115 |

| Query latency expression (90.0 percentile) [ms] | 482.02 |

| Query latency expression (99.0 percentile) [ms] | 485.951 |

| Query latency expression (100 percentile) [ms] | 491.999 |

| Query latency painless_static (90.0 percentile) [ms] | 890.382 |

| Query latency painless_static (99.0 percentile) [ms] | 918.354 |

| Query latency painless_static (100 percentile) [ms] | 927.282 |

| Query latency painless_dynamic (90.0 percentile) [ms] | 968.908 |

| Query latency painless_dynamic (99.0 percentile) [ms] | 1019.14 |

| Query latency painless_dynamic (100 percentile) [ms] | 1021.97 |

| Median CPU usage (index) [%] | 887.7 |

| Median CPU usage (stats) [%] | 94.9 |

| Median CPU usage (search) [%] | 445.05 |

| Total Young Gen GC [s] | 89.121 |

| Total Old Gen GC [s] | 12.274 |

| Index size [GB] | 3.30111 |

| Totally written [GB] | 20.2123 |

| Heap used for segments [MB] | 21.6794 |

| Heap used for doc values [MB] | 0.113129 |

| Heap used for terms [MB] | 20.0574 |

| Heap used for norms [MB] | 0.0761719 |

| Heap used for points [MB] | 0.770404 |

| Heap used for stored fields [MB] | 0.6623 |

| Segment count | 96 |

| Indices Stats(90.0 percentile) [ms] | 11.5116 |

| Indices Stats(99.0 percentile) [ms] | 14.1724 |

| Indices Stats(100 percentile) [ms] | 36.8348 |

| Nodes Stats(90.0 percentile) [ms] | 11.342 |

| Nodes Stats(99.0 percentile) [ms] | 13.435 |

| Nodes Stats(100 percentile) [ms] | 16.4768 |

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Logs for this race are archived in /home/elasticsearch/.rally/benchmarks/races/2016-08-08-07-29-59/local/logs-geonames-append-no-conflicts-defaults.zip

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5、问题大讨论

https://discuss.elastic.co/t/the-below-bugs-appers-when-running-esrally/57063/25


源码 作者danielmitterdorfer一一回复, 最终作者回复:

I am very happy too and I am glad you had so much persistence. You also uncovered a few usability problems that I need to tackle.

帮作者提了一些建议,促使他升级了一个版本0.3.2。


参考:https://github.com/elastic/rally


小结

前面的确费劲周折,花费了接近3整天实践,期间甚至告诉原作者工具太难用,给作者反复沟通,最终问题解决。看到输出结果的那一刻,整个人很兴奋。坚持到底,相信付出的力量!不断思考、反思中前行!

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