Hadoop2.x源码-编译剖析详解大数据

1.概述

  最近,有小伙伴涉及到源码编译。然而,在编译期间也是遇到各种坑,在求助于搜索引擎,技术博客,也是难以解决自身所遇到的问题。笔者在被询问多次的情况下,今天打算为大家来写一篇文章来剖析下编译的细节,以及遇到编译问题后,应该如何去解决这样类似的问题。因为,编译的问题,对于后期业务拓展,二次开发,编译打包是一个基本需要面临的问题。

2.编译准备

  在编译源码之前,我们需要准备编译所需要的基本环境。下面给大家列举本次编译的基础环境,如下所示:

  • 硬件环境
操作系统 CentOS6.6
CPU

I7

内存 16G
硬盘 闪存
核数 4核
  • 软件环境
JDK 1.7
Maven 3.2.3
ANT 1.9.6
Protobuf 2.5.0

  在准备好这些环境之后,我们需要去将这些环境安装到操作系统当中。步骤如下:

2.1 基础环境安装

  关于JDK,Maven,ANT的安装较为简单,这里就不多做赘述了,将其对应的压缩包解压,然后在/etc/profile文件当中添加对应的路径到PATH中即可。下面笔者给大家介绍安装Protobuf,其安装需要对Protobuf进行编译,故我们需要编译的依赖环境gcc、gcc-c++、cmake、openssl-devel、ncurses-devel,安装命令如下所示:

yum -y install gcc    
yum -y install gcc-c++ 
yum -y install cmake 
yum -y install openssl-devel 
yum -y install ncurses-devel

  验证GCC是否安装成功,命令如下所示:

Hadoop2.x源码-编译剖析详解大数据

  验证Make核CMake是否安装成功,命令如下所示:

Hadoop2.x源码-编译剖析详解大数据

  在准备完这些环境之后,开始去编译Protobuf,编译命令如下所示:

[[email protected] ~]$ cd protobuf-2.5.0/ 
[[email protected] protobuf-2.5.0]$ ./configure --prefix=/usr/local/protoc 
[[email protected] protobuf-2.5.0]$ make 
[[email protected] protobuf-2.5.0]$ make install

  PS:这里安装的时候有可能提示权限不足,若出现该类问题,使用sudo进行安装。

  验证Protobuf安装是否成功,命令如下所示:

Hadoop2.x源码-编译剖析详解大数据

  下面,我们开始进入编译环境,在编译的过程当中会遇到很多问题,大家遇到问题的时候,要认真的去分析这些问题产生的原因,这里先给大家列举一些可以避免的问题,在使用Maven进行编译的时候,若使用默认的JVM参数,在编译到hadoop-hdfs模块的时候,会出现溢出现象。异常信息如下所示:

java.lang.OutOfMemoryError: Java heap space 

  这里,我们在编译Hadoop源码之前,可以先去环境变量中设置其参数即可,内容修改如下:

export MAVEN_OPTS="-Xms256m -Xmx512m"

  接下来,我们进入到Hadoop的源码,这里笔者使用的是Hadoop2.6的源码进行编译,更高版本的源码进行编译,估计会有些许差异,编译命令如下所示:

[[email protected] tar]$ cd hadoop-2.6.0-src 
[[email protected] tar]$ mvn package -DskipTests -Pdist,native

  PS:这里笔者是直接将其编译为文件夹,若需要编译成tar包,可以在后面加上tar的参数,命令为 mvn package -DskipTests -Pdist,native -Dtar

  笔者在编译过程当中,出现过在编译KMS模块时,下载tomcat不完全的问题,Hadoop采用的tomcat是apache-tomcat-6.0.41.tar.gz,若是在此模块下出现异常,可以使用一下命令查看tomcat的文件大小,该文件正常大小为6.9M左右。查看命令如下所示:

[[email protected] downloads]$ du -sh *

  若出现只有几K的tomcat安装包,表示tomcat下载失败,我们将其手动下载到/home/hadoop/tar/hadoop-2.6.0-src/hadoop-common-project/hadoop-kms/downloads目录下即可。在编译成功后,会出现以下信息:

[INFO] ------------------------------------------------------------------------ 
[INFO] Reactor Summary: 
[INFO]  
[INFO] Apache Hadoop Main ................................. SUCCESS [  1.162 s] 
[INFO] Apache Hadoop Project POM .......................... SUCCESS [  0.690 s] 
[INFO] Apache Hadoop Annotations .......................... SUCCESS [  1.589 s] 
[INFO] Apache Hadoop Assemblies ........................... SUCCESS [  0.164 s] 
[INFO] Apache Hadoop Project Dist POM ..................... SUCCESS [  1.064 s] 
[INFO] Apache Hadoop Maven Plugins ........................ SUCCESS [  2.260 s] 
[INFO] Apache Hadoop MiniKDC .............................. SUCCESS [  1.492 s] 
[INFO] Apache Hadoop Auth ................................. SUCCESS [  2.233 s] 
[INFO] Apache Hadoop Auth Examples ........................ SUCCESS [  2.102 s] 
[INFO] Apache Hadoop Common ............................... SUCCESS [01:00 min] 
[INFO] Apache Hadoop NFS .................................. SUCCESS [  3.891 s] 
[INFO] Apache Hadoop KMS .................................. SUCCESS [  5.872 s] 
[INFO] Apache Hadoop Common Project ....................... SUCCESS [  0.019 s] 
[INFO] Apache Hadoop HDFS ................................. SUCCESS [04:04 min] 
[INFO] Apache Hadoop HttpFS ............................... SUCCESS [01:47 min] 
[INFO] Apache Hadoop HDFS BookKeeper Journal .............. SUCCESS [04:58 min] 
[INFO] Apache Hadoop HDFS-NFS ............................. SUCCESS [  2.492 s] 
[INFO] Apache Hadoop HDFS Project ......................... SUCCESS [  0.020 s] 
[INFO] hadoop-yarn ........................................ SUCCESS [  0.018 s] 
[INFO] hadoop-yarn-api .................................... SUCCESS [01:05 min] 
[INFO] hadoop-yarn-common ................................. SUCCESS [01:00 min] 
[INFO] hadoop-yarn-server ................................. SUCCESS [  0.029 s] 
[INFO] hadoop-yarn-server-common .......................... SUCCESS [01:03 min] 
[INFO] hadoop-yarn-server-nodemanager ..................... SUCCESS [01:10 min] 
[INFO] hadoop-yarn-server-web-proxy ....................... SUCCESS [  1.810 s] 
[INFO] hadoop-yarn-server-applicationhistoryservice ....... SUCCESS [  4.041 s] 
[INFO] hadoop-yarn-server-resourcemanager ................. SUCCESS [ 11.739 s] 
[INFO] hadoop-yarn-server-tests ........................... SUCCESS [  3.332 s] 
[INFO] hadoop-yarn-client ................................. SUCCESS [  4.762 s] 
[INFO] hadoop-yarn-applications ........................... SUCCESS [  0.017 s] 
[INFO] hadoop-yarn-applications-distributedshell .......... SUCCESS [  1.586 s] 
[INFO] hadoop-yarn-applications-unmanaged-am-launcher ..... SUCCESS [  1.233 s] 
[INFO] hadoop-yarn-site ................................... SUCCESS [  0.018 s] 
[INFO] hadoop-yarn-registry ............................... SUCCESS [  3.270 s] 
[INFO] hadoop-yarn-project ................................ SUCCESS [  2.164 s] 
[INFO] hadoop-mapreduce-client ............................ SUCCESS [  0.032 s] 
[INFO] hadoop-mapreduce-client-core ....................... SUCCESS [ 13.047 s] 
[INFO] hadoop-mapreduce-client-common ..................... SUCCESS [ 10.890 s] 
[INFO] hadoop-mapreduce-client-shuffle .................... SUCCESS [  2.534 s] 
[INFO] hadoop-mapreduce-client-app ........................ SUCCESS [  6.429 s] 
[INFO] hadoop-mapreduce-client-hs ......................... SUCCESS [  4.866 s] 
[INFO] hadoop-mapreduce-client-jobclient .................. SUCCESS [02:04 min] 
[INFO] hadoop-mapreduce-client-hs-plugins ................. SUCCESS [  1.183 s] 
[INFO] Apache Hadoop MapReduce Examples ................... SUCCESS [  3.655 s] 
[INFO] hadoop-mapreduce ................................... SUCCESS [  1.775 s] 
[INFO] Apache Hadoop MapReduce Streaming .................. SUCCESS [ 11.478 s] 
[INFO] Apache Hadoop Distributed Copy ..................... SUCCESS [ 15.399 s] 
[INFO] Apache Hadoop Archives ............................. SUCCESS [  1.359 s] 
[INFO] Apache Hadoop Rumen ................................ SUCCESS [  3.736 s] 
[INFO] Apache Hadoop Gridmix .............................. SUCCESS [  2.822 s] 
[INFO] Apache Hadoop Data Join ............................ SUCCESS [  1.791 s] 
[INFO] Apache Hadoop Ant Tasks ............................ SUCCESS [  1.350 s] 
[INFO] Apache Hadoop Extras ............................... SUCCESS [  1.858 s] 
[INFO] Apache Hadoop Pipes ................................ SUCCESS [  5.805 s] 
[INFO] Apache Hadoop OpenStack support .................... SUCCESS [  3.061 s] 
[INFO] Apache Hadoop Amazon Web Services support .......... SUCCESS [07:14 min] 
[INFO] Apache Hadoop Client ............................... SUCCESS [  2.986 s] 
[INFO] Apache Hadoop Mini-Cluster ......................... SUCCESS [  0.053 s] 
[INFO] Apache Hadoop Scheduler Load Simulator ............. SUCCESS [  2.917 s] 
[INFO] Apache Hadoop Tools Dist ........................... SUCCESS [  5.702 s] 
[INFO] Apache Hadoop Tools ................................ SUCCESS [  0.015 s] 
[INFO] Apache Hadoop Distribution ......................... SUCCESS [  8.587 s] 
[INFO] ------------------------------------------------------------------------ 
[INFO] BUILD SUCCESS 
[INFO] ------------------------------------------------------------------------ 
[INFO] Total time: 28:25 min 
[INFO] Finished at: 2015-10-22T15:12:10+08:00 
[INFO] Final Memory: 89M/451M 
[INFO] ------------------------------------------------------------------------

  在编译完成之后,会在Hadoop源码的dist目录下生成编译好的文件,如下图所示:

Hadoop2.x源码-编译剖析详解大数据

  图中hadoop-2.6.0即表示编译好的文件。

3.总结

  在编译的过程当中,会出现各种各样的问题,有些问题可以借助搜索引擎去帮助我们解决,有些问题搜索引擎却难以直接的给出解决方案,这时,我们需要冷静的分析编译错误信息,大胆的去猜测,然后去求证我们的想法。简而言之,解决问题的方法是有很多的。当然,大家也可以在把遇到的编译问题,贴在评论下方,供后来者参考或借鉴。

4.结束语

  这篇文章就和大家分享到这里,如果大家在研究和学习的过程中有什么疑问,可以加群进行讨论或发送邮件给我,我会尽我所能为您解答,与君共勉!

原创文章,作者:Maggie-Hunter,如若转载,请注明出处:https://blog.ytso.com/9911.html

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