安装Scala

使用spark-shell命令进入shell模式,查看spark版本和Scala版本:

下载Scala2.10.5

wget https://downloads.lightbend.com/scala/2.10.5/scala-2.10.5.tgz

解压

tar -xzvf scala-2.10.5.tgz

创建文件夹

mkdir -p /usr/local/scalacp -r scala-2.10.5 /usr/local/scala

配置环境

vim /etc/profile

添加内容

export SCALA_HOME=/usr/local/scala/scala-
export PATH=$PATH:$JAVA_HOME/bin:$PHOENIX_PATH/bin:$M2_HOME/bin:$SCALA_HOME/bin

生效

source /etc/profile

验证安装成功

安装Maven

参考:https://www.cnblogs.com/ratels/p/10874379.html

只是默认使用Maven中央仓库,不用另外添加Maven中央仓库的镜像;中央仓库虽然慢,但是内容全;镜像虽然速度快,但是内容有欠缺。

安装HiBench

获取源码

wget https://codeload.github.com/Intel-bigdata/HiBench/zip/master

进入文件夹下,执行以下命令进行安装

(参考:https://github.com/Intel-bigdata/HiBench  ;  https://github.com/Intel-bigdata/HiBench/blob/master/docs/build-hibench.md

mvn -Phadoopbench -Psparkbench -Dspark=1.6 -Dscala=2.10 clean package

报错:

Plugin org.apache.maven.plugins:maven-clean-plugin:2.5 or one of its dependencies could not be
The POM for org.apache.maven.plugins:maven-clean-plugin:jar:2.5 is invalid, transitive dependencies (if any) will not be available

解决方法(参考:https://blog.csdn.net/expect521/article/details/75663221):

(1)删除plugin目录下的文件夹,重新生成;

(2)设置Maven中央仓库为源;

编译后返回如下信息:

[INFO] ------------------------------------------------------------------------
[INFO] Reactor Summary:
[INFO]
[INFO] hibench 7.1-SNAPSHOT ............................... SUCCESS [ 40.848 s]
[INFO] hibench-common : min]
[INFO] HiBench data generation tools : min]
[INFO] sparkbench 7.1-SNAPSHOT ............................ SUCCESS [  0.014 s]
[INFO] sparkbench-common : min]
[INFO] sparkbench micro benchmark 7.1-SNAPSHOT ............ SUCCESS [  6.316 s]
[INFO] sparkbench machine learning benchmark : min]
[INFO] sparkbench-websearch 7.1-SNAPSHOT .................. SUCCESS [  3.217 s]
[INFO] sparkbench-graph 7.1-SNAPSHOT ...................... SUCCESS [ 43.669 s]
[INFO] sparkbench-sql 7.1-SNAPSHOT ........................ SUCCESS [ 50.434 s]
[INFO] sparkbench-streaming 7.1-SNAPSHOT .................. SUCCESS [ 11.003 s]
[INFO] sparkbench project assembly 7.1-SNAPSHOT ........... SUCCESS [ 28.359 s]
[INFO] hadoopbench 7.1-SNAPSHOT ........................... SUCCESS [  0.005 s]
[INFO] hadoopbench-sql : min]
[INFO] mahout 7.1-SNAPSHOT ................................ SKIPPED
[INFO] PEGASUS: A Peta-Scale Graph Mining System 2.0-SNAPSHOT SKIPPED
[INFO] nutchindexing 7.1-SNAPSHOT ......................... SKIPPED
[INFO] ------------------------------------------------------------------------
[INFO] BUILD FAILURE
[INFO] ------------------------------------------------------------------------
[INFO] Total : h
[INFO] Finished at: --03T17::+:
[INFO] ------------------------------------------------------------------------
[ERROR] Failed to execute goal com.googlecode.maven-download-plugin:download-maven-plugin::]
[ERROR]
[ERROR] To see the full stack trace of the errors, re-run Maven with the -e switch.
[ERROR] Re-run Maven using the -X switch to enable full debug logging.
[ERROR]
[ERROR] For more information about the errors and possible solutions, please read the following articles:
[ERROR] [Help ] http://cwiki.apache.org/confluence/display/MAVEN/MojoExecutionException
[ERROR]
[ERROR] After correcting the problems, you can resume the build with the command
[ERROR]   mvn <goals> -rf :hadoopbench-sql

错误原因是:

[WARNING] Could not get content
org.apache.maven.wagon.TransferFailedException: Connect to archive.apache.org: [archive.apache.org/163.172.17.199] failed: Connection timed out (Connection timed out)

Caused by: java.net.ConnectException: Connection timed out (Connection timed out)

[WARNING] Retrying ( more)
Downloading: http://archive.apache.org/dist/hive/hive-0.14.0//apache-hive-0.14.0-bin.tar.gz
java.net.SocketTimeoutException: Read timed out

本人手动去下载文件:http://archive.apache.org/dist/hive/hive-0.14.0//apache-hive-0.14.0-bin.tar.gz ,依然无法下载,说明是文件地址问题!

已经构建的模块暂时能够满足需求,先略过该问题。

创建并修改配置文件hadoop.conf

cp conf/hadoop.conf.template conf/hadoop.conf

然后修改配置文件: vim hadoop.conf

参考:https://github.com/Intel-bigdata/HiBench/blob/master/docs/run-hadoopbench.md  ;https://www.cnblogs.com/PJQOOO/p/6899988.html  ;https://blog.csdn.net/xiaoxiaojavacsdn/article/details/80235078

   # Hadoop home
   hibench.hadoop.home     /opt/cloudera/parcels/CDH--.cdh5./lib/hadoop

   # The path of hadoop executable
   hibench.hadoop.executable     /opt/cloudera/parcels/CDH--.cdh5./bin/hadoop

   # Hadoop configraution directory
   hibench.hadoop.configure.dir  /etc/hadoop/conf.cloudera.yarn

  # The root HDFS path to store HiBench data
  hibench.hdfs.master       hdfs://node1:8020

  #hdfs://localhost:8020
  #hdfs://localhost:9000

  # Hadoop release provider. Supported value: apache, cdh5, hdp
  hibench.hadoop.release    cdh5

注意:

1.hibench.hadoop.home是你本机上hadoop的安装路径。

2.在配置hibench.hdfs.master的时候我傻傻地写了hdfs://localhost:8020,导致后来运行脚本一直不成功。

首先localhost是你的机器的IP,后面的端口号可能是8020也可能是9000,要根据本机的具体情况,在命令行输入vim /etc/hadoop/conf.cloudera.yarn/core-site.xml,可以观察到

   <?xml version="1.0" encoding="UTF-8"?>

   <!--Autogenerated by Cloudera Manager-->
   <configuration>
     <property>
       <name>fs.defaultFS</name>
       <value>hdfs://node1:8020</value>
     </property>

接下来就是在HiBench下运行脚本,比如:

bin/workloads/micro/wordcount/prepare/prepare.sh

在HDFS中创建好目录

su hdfs
hadoop dfs -mkdir /HiBench/Wordcount
hadoop dfs -mkdir /HiBench/Wordcount/Input

目录创建好以后执行脚本,报错:

rm: Permission denied: user=root, access=WRITE, inode="/HiBench/Wordcount":hdfs:supergroup:drwxr-xr-x

原因:

root对hdfs创建的文件目录没有访问权限!

bash-4.2$ hadoop fs -ls /
Found  items
drwxr-xr-x   - hdfs  supergroup           -- : /HiBench
drwxr-xr-x   - hdfs  supergroup           -- : /benchmarks
drwxr-xr-x   - hbase hbase                -- : /hbase
drwxrwxrwt   - hdfs  supergroup           -- : /tmp
drwxr-xr-x   - hdfs  supergroup           -- : /user

解决方法:

(1 可选)参考:https://blog.csdn.net/dingding_ting/article/details/84955325

hadoop dfsadmin -safemode leave

(2)参考:https://blog.csdn.net/xianjie0318/article/details/75453758

hdfs dfs -chown -R root /HiBench

权限修正:

bash-4.2$ hadoop fs -ls /
Found  items
drwxr-xr-x   - root  supergroup           -- : /HiBench
drwxr-xr-x   - hdfs  supergroup           -- : /benchmarks
drwxr-xr-x   - hbase hbase                -- : /hbase
drwxrwxrwt   - hdfs  supergroup           -- : /tmp
drwxr-xr-x   - hdfs  supergroup           -- : /user

再次执行脚本,返回结果信息:

[root@node1 prepare]# ./prepare.sh
patching args=
Parsing conf: /home/cf/app/HiBench-master/conf/hadoop.conf
Parsing conf: /home/cf/app/HiBench-master/conf/hibench.conf
Parsing conf: /home/cf/app/HiBench-master/conf/workloads/micro/wordcount.conf
probe -.cdh5./lib/hadoop/../../jars/hadoop-mapreduce-client-jobclient--cdh5.14.2-tests.jar
start HadoopPrepareWordcount bench
hdfs -.cdh5./bin/hadoop --config /etc/hadoop/conf.cloudera.yarn fs -rm -r -skipTrash hdfs://node1:8020/HiBench/Wordcount/Input
Deleted hdfs://node1:8020/HiBench/Wordcount/Input
Submit MapReduce Job: /opt/cloudera/parcels/CDH--.cdh5./bin/hadoop --config /etc/hadoop/conf.cloudera.yarn jar /opt/cloudera/parcels/CDH--.cdh5./lib/hadoop/../../jars/hadoop-mapreduce-examples--cdh5. -D mapreduce.randomtextwriter.bytespermap= -D mapreduce.job.maps= -D mapreduce.job.reduces= hdfs://node1:8020/HiBench/Wordcount/Input
The job took  seconds.
finish HadoopPrepareWordcount bench

在 /home/cf/app/HiBench-master 目录下,执行脚本

bin/workloads/micro/wordcount/hadoop/run.sh

返回结果信息

[root@node1 hadoop]# ./run.sh
patching args=
Parsing conf: /home/cf/app/HiBench-master/conf/hadoop.conf
Parsing conf: /home/cf/app/HiBench-master/conf/hibench.conf
Parsing conf: /home/cf/app/HiBench-master/conf/workloads/micro/wordcount.conf
probe -.cdh5./lib/hadoop/../../jars/hadoop-mapreduce-client-jobclient--cdh5.14.2-tests.jar
start HadoopWordcount bench
hdfs -.cdh5./bin/hadoop --config /etc/hadoop/conf.cloudera.yarn fs -rm -r -skipTrash hdfs://node1:8020/HiBench/Wordcount/Output
rm: `hdfs://node1:8020/HiBench/Wordcount/Output': No such file or directory
hdfs -.cdh5./bin/hadoop --config /etc/hadoop/conf.cloudera.yarn fs -du -s hdfs://node1:8020/HiBench/Wordcount/Input
Submit MapReduce Job: /opt/cloudera/parcels/CDH--.cdh5./bin/hadoop --config /etc/hadoop/conf.cloudera.yarn jar /opt/cloudera/parcels/CDH--.cdh5./lib/hadoop/../../jars/hadoop-mapreduce-examples--cdh5. -D mapreduce.job.reduces= -D mapreduce.inputformat.class=org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat -D mapreduce.outputformat.class=org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat -D mapreduce.job.inputformat.class=org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat -D mapreduce.job.outputformat.class=org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat hdfs://node1:8020/HiBench/Wordcount/Input hdfs://node1:8020/HiBench/Wordcount/Output
         Bytes Written=
finish HadoopWordcount bench

执行结束以后可以查看分析结果

/report/hibench.report

Type         Date       Time     Input_data_size      Duration(s)          Throughput(bytes/s)  Throughput/node
HadoopWordcount 2019-06-04 16:59:04 37055                20.226               1832                 610                 

\report\wordcount路径下有两个文件夹,分别对应执行了脚本/prepare/prepare.sh和/hadoop/run.sh所产生的信息

\report\wordcount\prepare下有多个文件:monitor.log是原始日志,bench.log是Map-Reduce信息,monitor.html可视化了系统的性能信息,\conf\wordcount.conf本次任务的环境变量

\report\wordcount\hadoop下有多个文件:monitor.log是原始日志,bench.log是Map-Reduce信息,monitor.html可视化了系统的性能信息,\conf\wordcount.conf本次任务的环境变量

monitor.html中包含了Memory usage heatmap等统计图:

根据官方文档 https://github.com/Intel-bigdata/HiBench/blob/master/docs/run-hadoopbench.md ,还可以修改 hibench.scale.profile 调整测试的数据规模,修改 hibench.default.map.parallelism 和 hibench.default.shuffle.parallelism 调整并行化

HiBench成长笔记——(2) CentOS部署安装HiBench的更多相关文章

  1. HiBench成长笔记——(9) Centos安装Maven

    Maven的下载地址是:http://maven.apache.org/download.cgi 安装Maven非常简单,只需要将下载的压缩文件解压就可以了. cd /home/cf/app wget ...

  2. HiBench成长笔记——(7) 阅读《The HiBench Benchmark Suite: Characterization of the MapReduce-Based Data Analysis》

    <The HiBench Benchmark Suite: Characterization of the MapReduce-Based Data Analysis>内容精选 We th ...

  3. HiBench成长笔记——(4) HiBench测试Spark SQL

    很多内容之前的博客已经提过,这里不再赘述,详细内容参照本系列前面的博客:https://www.cnblogs.com/ratels/p/10970905.html 和 https://www.cnb ...

  4. HiBench成长笔记——(3) HiBench测试Spark

    很多内容之前的博客已经提过,这里不再赘述,详细内容参照本系列前面的博客:https://www.cnblogs.com/ratels/p/10970905.html 创建并修改配置文件conf/spa ...

  5. HiBench成长笔记——(5) HiBench-Spark-SQL-Scan源码分析

    run.sh #!/bin/bash # Licensed to the Apache Software Foundation (ASF) under one or more # contributo ...

  6. HiBench成长笔记——(1) HiBench概述

    测试分类 HiBench共计19个测试方向,可大致分为6个测试类别:分别是micro,ml(机器学习),sql,graph,websearch和streaming. 2.1 micro Benchma ...

  7. HiBench成长笔记——(11) 分析源码run.sh

    #!/bin/bash # Licensed to the Apache Software Foundation (ASF) under one or more # contributor licen ...

  8. HiBench成长笔记——(10) 分析源码execute_with_log.py

    #!/usr/bin/env python2 # Licensed to the Apache Software Foundation (ASF) under one or more # contri ...

  9. HiBench成长笔记——(9) 分析源码monitor.py

    monitor.py 是主监控程序,将监控数据写入日志,并统计监控数据生成HTML统计展示页面: #!/usr/bin/env python2 # Licensed to the Apache Sof ...

随机推荐

  1. python集合操作方法详解

    前言 说集合之前,我们先说一个小例子,假设某公司有五个人喜欢打篮球,五个人喜欢打游戏,问即打游戏有打篮球的人都有哪些? play_basketball = ['a','b','c','d','e'] ...

  2. RestTemplate post请求使用map传参 Controller 接收不到值的解决方案 postForObject方法源码解析.md

    结论 post方法中如果使用map传参,需要使用MultiValueMap来传递 RestTemplate 的 postForObject 方法有四个参数 String url => 顾名思义 ...

  3. 「JSOI2014」歌剧表演

    「JSOI2014」歌剧表演 传送门 没想到吧我半夜切的 这道题应该算是 \(\text{JSOI2014}\) 里面比较简单的吧... 考虑用集合关系来表示分辨关系,具体地说就是我们把所有演员分成若 ...

  4. 设计模式01 创建型模式 - 单例模式(Singleton Pattern)

    参考 [1] 设计模式之:创建型设计模式(6种) | 博客园 [2] 单例模式的八种写法比较 | 博客园 单例模式(Singleton  Pattern) 确保一个类有且仅有一个实例,并且为客户提供一 ...

  5. 吴裕雄--天生自然ORACLE数据库学习笔记:其它数据对象

    create index emp_deptno_index on emp(deptno) pctfree tablespace users; create bitmap index emp_salar ...

  6. xshell编码设置-----支持中文

    1. 点击 设置 图标 2. 选择 UTF-8 3. 重启xshell即可

  7. Java1.7已经舍弃substr了

    网上一堆在写substring和substr区别的文章,都是过时的. 起码在官方6.0的api文档中已经找不到了,只有substring()

  8. Python学习第十六课——静态属性(property, classmethod, staticmethod)

    计算所居住房子的面积 普通写法 class Room: def __init__(self,name,owner,width,length,heigh): self.name=name self.ow ...

  9. bootloader与启动地址偏移

    如果项目工程是IAP+APP,则在keil的APP中要么在修改IROM/IRAM的开始地址和大小,并在MAP中勾选设置. 在NVIC中修改system_stm32f10x.c修改 这个在void Sy ...

  10. Linux命令:iostat命令

    Linux系统中的 iostat是I/O statistics(输入/输出统计)的缩写,iostat工具将对系统的磁盘操作活动进行监视.它的特点是汇报磁盘活动统计情况,同时也会汇报出CPU使用情况.同 ...