Hadoop 修改源码以及将修改后的源码应用到部署好的Hadoop中

　　我的Hadoop版本是hadoop-2.7.3, 我们可以去hadoop官网下载源码hadoop-2.7.3-src,以及编译好的工程文件hadoop-2.7.3, 后者可以直接部署. 前者hadoop-2.7.3-src必须mvn之后才能部署. 我们修改代码必须是在hadoop-2.7.3-src源码中进行, 而源码mvn之后才能部署或使用. 所以我们要先了解Maven.     mvn hadoop-2.7.3-src的时候会出现各种问题. (最好用jdk1.7)

　　其中hadoop-2.7.3-src源码文件中有个BUILDING.txt文件,要重点看. 教你如何构建hadoop. 如下所示:

Build instructions for Hadoop

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Requirements:

* Unix System
* JDK 1.7+
* Maven 3.0 or later
* Findbugs 1.3.9 (if running findbugs)
* ProtocolBuffer 2.5.0
* CMake 2.6 or newer (if compiling native code), must be 3.0 or newer on Mac
* Zlib devel (if compiling native code)
* openssl devel ( if compiling native hadoop-pipes and to get the best HDFS encryption performance )
* Linux FUSE (Filesystem in Userspace) version 2.6 or above ( if compiling fuse_dfs )
* Internet connection for first build (to fetch all Maven and Hadoop dependencies)

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Installing required packages for clean install of Ubuntu 14.04 LTS Desktop:

* Oracle JDK 1.7 (preferred)
  $ sudo apt-get purge openjdk*
  $ sudo apt-get install software-properties-common
  $ sudo add-apt-repository ppa:webupd8team/java
  $ sudo apt-get update
  $ sudo apt-get install oracle-java7-installer
* Maven
  $ sudo apt-get -y install maven
* Native libraries
  $ sudo apt-get -y install build-essential autoconf automake libtool cmake zlib1g-dev pkg-config libssl-dev
* ProtocolBuffer 2.5.0 (required)
  $ sudo apt-get -y install libprotobuf-dev protobuf-compiler

Optional packages:

* Snappy compression
  $ sudo apt-get install snappy libsnappy-dev
* Bzip2
  $ sudo apt-get install bzip2 libbz2-dev
* Jansson (C Library for JSON)
  $ sudo apt-get install libjansson-dev
* Linux FUSE
  $ sudo apt-get install fuse libfuse-dev

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Maven main modules:

  hadoop                            (Main Hadoop project)
         - hadoop-project           (Parent POM for all Hadoop Maven modules.             )
                                    (All plugins & dependencies versions are defined here.)
         - hadoop-project-dist      (Parent POM for modules that generate distributions.)
         - hadoop-annotations       (Generates the Hadoop doclet used to generated the Javadocs)
         - hadoop-assemblies        (Maven assemblies used by the different modules)
         - hadoop-common-project    (Hadoop Common)
         - hadoop-hdfs-project      (Hadoop HDFS)
         - hadoop-mapreduce-project (Hadoop MapReduce)
         - hadoop-tools             (Hadoop tools like Streaming, Distcp, etc.)
         - hadoop-dist              (Hadoop distribution assembler)

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Where to run Maven from?

  It can be run from any module. The only catch is that if not run from utrunk
  all modules that are not part of the build run must be installed in the local
  Maven cache or available in a Maven repository.

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Maven build goals:

 * Clean                     : mvn clean
 * Compile                   : mvn compile [-Pnative]
 * Run tests                 : mvn test [-Pnative]
 * Create JAR                : mvn package
 * Run findbugs              : mvn compile findbugs:findbugs
 * Run checkstyle            : mvn compile checkstyle:checkstyle
 * Install JAR in M2 cache   : mvn install
 * Deploy JAR to Maven repo  : mvn deploy
 * Run clover                : mvn test -Pclover [-DcloverLicenseLocation=${user.name}/.clover.license]
 * Run Rat                   : mvn apache-rat:check
 * Build javadocs            : mvn javadoc:javadoc
 * Build distribution        : mvn package [-Pdist][-Pdocs][-Psrc][-Pnative][-Dtar]
 * Change Hadoop version     : mvn versions:set -DnewVersion=NEWVERSION

 Build options:

  * Use -Pnative to compile/bundle native code
  * Use -Pdocs to generate & bundle the documentation in the distribution (using -Pdist)
  * Use -Psrc to create a project source TAR.GZ
  * Use -Dtar to create a TAR with the distribution (using -Pdist)

 Snappy build options:

   Snappy is a compression library that can be utilized by the native code.
   It is currently an optional component, meaning that Hadoop can be built with
   or without this dependency.

  * Use -Drequire.snappy to fail the build if libsnappy.so is not found.
    If this option is not specified and the snappy library is missing,
    we silently build a version of libhadoop.so that cannot make use of snappy.
    This option is recommended if you plan on making use of snappy and want
    to get more repeatable builds.

  * Use -Dsnappy.prefix to specify a nonstandard location for the libsnappy
    header files and library files. You do not need this option if you have
    installed snappy using a package manager.
  * Use -Dsnappy.lib to specify a nonstandard location for the libsnappy library
    files.  Similarly to snappy.prefix, you do not need this option if you have
    installed snappy using a package manager.
  * Use -Dbundle.snappy to copy the contents of the snappy.lib directory into
    the final tar file. This option requires that -Dsnappy.lib is also given,
    and it ignores the -Dsnappy.prefix option.

 OpenSSL build options:

   OpenSSL includes a crypto library that can be utilized by the native code.
   It is currently an optional component, meaning that Hadoop can be built with
   or without this dependency.

  * Use -Drequire.openssl to fail the build if libcrypto.so is not found.
    If this option is not specified and the openssl library is missing,
    we silently build a version of libhadoop.so that cannot make use of
    openssl. This option is recommended if you plan on making use of openssl
    and want to get more repeatable builds.
  * Use -Dopenssl.prefix to specify a nonstandard location for the libcrypto
    header files and library files. You do not need this option if you have
    installed openssl using a package manager.
  * Use -Dopenssl.lib to specify a nonstandard location for the libcrypto library
    files. Similarly to openssl.prefix, you do not need this option if you have
    installed openssl using a package manager.
  * Use -Dbundle.openssl to copy the contents of the openssl.lib directory into
    the final tar file. This option requires that -Dopenssl.lib is also given,
    and it ignores the -Dopenssl.prefix option.

   Tests options:

  * Use -DskipTests to skip tests when running the following Maven goals:
    'package',  'install', 'deploy' or 'verify'
  * -Dtest=<TESTCLASSNAME>,<TESTCLASSNAME#METHODNAME>,....
  * -Dtest.exclude=<TESTCLASSNAME>
  * -Dtest.exclude.pattern=**/<TESTCLASSNAME1>.java,**/<TESTCLASSNAME2>.java

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Building components separately

If you are building a submodule directory, all the hadoop dependencies this
submodule has will be resolved as all other 3rd party dependencies. This is,
from the Maven cache or from a Maven repository (if not available in the cache
or the SNAPSHOT 'timed out').
An alternative is to run 'mvn install -DskipTests' from Hadoop source top
level once; and then work from the submodule. Keep in mind that SNAPSHOTs
time out after a while, using the Maven '-nsu' will stop Maven from trying
to update SNAPSHOTs from external repos.

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Protocol Buffer compiler

The version of Protocol Buffer compiler, protoc, must match the version of the
protobuf JAR.

If you have multiple versions of protoc in your system, you can set in your
build shell the HADOOP_PROTOC_PATH environment variable to point to the one you
want to use for the Hadoop build. If you don't define this environment variable,
protoc is looked up in the PATH.
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Importing projects to eclipse

When you import the project to eclipse, install hadoop-maven-plugins at first.

  $ cd hadoop-maven-plugins
  $ mvn install

Then, generate eclipse project files.

  $ mvn eclipse:eclipse -DskipTests

At last, import to eclipse by specifying the root directory of the project via
[File] > [Import] > [Existing Projects into Workspace].

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Building distributions:

Create binary distribution without native code and without documentation:

  $ mvn package -Pdist -DskipTests -Dtar

Create binary distribution with native code and with documentation:

  $ mvn package -Pdist,native,docs -DskipTests -Dtar

Create source distribution:

  $ mvn package -Psrc -DskipTests

Create source and binary distributions with native code and documentation:

  $ mvn package -Pdist,native,docs,src -DskipTests -Dtar

Create a local staging version of the website (in /tmp/hadoop-site)

  $ mvn clean site; mvn site:stage -DstagingDirectory=/tmp/hadoop-site

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Installing Hadoop

Look for these HTML files after you build the document by the above commands.

  * Single Node Setup:
    hadoop-project-dist/hadoop-common/SingleCluster.html

  * Cluster Setup:
    hadoop-project-dist/hadoop-common/ClusterSetup.html

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Handling out of memory errors in builds

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If the build process fails with an out of memory error, you should be able to fix
it by increasing the memory used by maven -which can be done via the environment
variable MAVEN_OPTS.

Here is an example setting to allocate between 256 and 512 MB of heap space to
Maven

export MAVEN_OPTS="-Xms256m -Xmx512m"

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Building on Windows

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Requirements:

* Windows System
* JDK 1.7+
* Maven 3.0 or later
* Findbugs 1.3.9 (if running findbugs)
* ProtocolBuffer 2.5.0
* CMake 2.6 or newer
* Windows SDK 7.1 or Visual Studio 2010 Professional
* Windows SDK 8.1 (if building CPU rate control for the container executor)
* zlib headers (if building native code bindings for zlib)
* Internet connection for first build (to fetch all Maven and Hadoop dependencies)
* Unix command-line tools from GnuWin32: sh, mkdir, rm, cp, tar, gzip. These
  tools must be present on your PATH.

Unix command-line tools are also included with the Windows Git package which
can be downloaded from http://git-scm.com/download/win.

If using Visual Studio, it must be Visual Studio 2010 Professional (not 2012).
Do not use Visual Studio Express.  It does not support compiling for 64-bit,
which is problematic if running a 64-bit system.  The Windows SDK 7.1 is free to
download here:

http://www.microsoft.com/en-us/download/details.aspx?id=8279

The Windows SDK 8.1 is available to download at:

http://msdn.microsoft.com/en-us/windows/bg162891.aspx

Cygwin is neither required nor supported.

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Building:

Keep the source code tree in a short path to avoid running into problems related
to Windows maximum path length limitation.  (For example, C:\hdc).

Run builds from a Windows SDK Command Prompt.  (Start, All Programs,
Microsoft Windows SDK v7.1, Windows SDK 7.1 Command Prompt.)

JAVA_HOME must be set, and the path must not contain spaces.  If the full path
would contain spaces, then use the Windows short path instead.

You must set the Platform environment variable to either x64 or Win32 depending
on whether you're running a 64-bit or 32-bit system.  Note that this is
case-sensitive.  It must be "Platform", not "PLATFORM" or "platform".
Environment variables on Windows are usually case-insensitive, but Maven treats
them as case-sensitive.  Failure to set this environment variable correctly will
cause msbuild to fail while building the native code in hadoop-common.

set Platform=x64 (when building on a 64-bit system)
set Platform=Win32 (when building on a 32-bit system)

Several tests require that the user must have the Create Symbolic Links
privilege.

All Maven goals are the same as described above with the exception that
native code is built by enabling the 'native-win' Maven profile. -Pnative-win
is enabled by default when building on Windows since the native components
are required (not optional) on Windows.

If native code bindings for zlib are required, then the zlib headers must be
deployed on the build machine.  Set the ZLIB_HOME environment variable to the
directory containing the headers.

set ZLIB_HOME=C:\zlib-1.2.7

At runtime, zlib1.dll must be accessible on the PATH.  Hadoop has been tested
with zlib 1.2.7, built using Visual Studio 2010 out of contrib\vstudio\vc10 in
the zlib 1.2.7 source tree.

http://www.zlib.net/

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Building distributions:

 * Build distribution with native code    : mvn package [-Pdist][-Pdocs][-Psrc][-Dtar]

BULIDING.txt

　　每个子模块编译后生成的jar包放到了与源代码目录平级的target目录中.

　　其实mvn是根据pom.xml进行的. 所以只要有pom.xml文件,我们就可以进行mvn.  我们以修改NameNode.java的main()函数为例. 如下所示:

// NameNode.java
 public static void main(String argv[]) throws Exception {
    System.out.println("Hello NameNode!");   //这是我添加的,当执行start-all.sh时,会启动NameNode类的main()函数,进一步打印
    if (DFSUtil.parseHelpArgument(argv, NameNode.USAGE, System.out, true)) {
      System.exit(0);
    }

    try {
      StringUtils.startupShutdownMessage(NameNode.class, argv, LOG);
      NameNode namenode = createNameNode(argv, null);
      if (namenode != null) {
        namenode.join();
      }
    } catch (Throwable e) {
      LOG.error("Failed to start namenode.", e);
      terminate(1, e);
    }
  }

当我们修改hadoop-2.7.3-src的NameNode.java的源码后,

比如我们修改的NameNode.java在hadoop-2.7.3-src/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/NameNode.java中. 而NameNode.java在hadoop-2.7.3的hadoop-2.7.3/share/hadoop/hdfs/hadoop-hdfs-2.7.3.jar中,( 我们可以通过(解)压缩软件打开 hadoop-hdfs-2.7.3.jar, 会发现org/apache/hadoop/hdfs/server/namenode/NameNode.class , 也就是将 .class 文件打成 jia 包 ). mvn好之后的hadoop-hdfs-2.7.3.jar在对应的hadoop-2.7.3-src/hadoop-hdfs-project/hadoop-hdfs/target文件夹目录下, 我们只要用这个mvn好之后的hadoop-hdfs-2.7.3.jar替换部署好的hadoop的对应jar包即可. mvn方法如下:

(1) 我们可以对修改源码的项目整个进行mvn , 然后再部署. 这个缺点是每次都要对整个项目进行mvn , 还要重新进行部署. 所以不要用这种方法.

(2) 我们可以对修改源码的项目整个进行mvn ,然后替换掉我们修改的部分的哪一个jar包即可. 这样做比上面好的地方是,我们不要重新部署hadoop. 只需要替换我们修改的文件所在的jar包即可,不用每次都部署(已经部署好).

(3) NameNode.java在hadoop-hdfs-project里, 该文件夹有pom.xml文件,所以我们可以只对该文件进行mvn, 然后用生成的hadoop-hdfs-2.7.3.jar替换部署好的hadoop的对应jar包即可.( 这样可以节省时间, 因为hadoop-2.7.3-src文件夹下有很多其他文件夹要mvn.)

(4) NameNode.java在hadoop-hdfs-project/hadoop-hdfs里, hadoop-hdfs里也有pom.xml文件, 相比(3),我们只对hadoop-hdfs-project文件夹下的hadoop-hdfs进行mvn,而不管hadoop-hdfs-project文件夹下的其他文件,这样进一步节省时间. 之后然后用生成的hadoop-hdfs-2.7.3.jar替换部署好的hadoop的对应jar包即可. 这里生成的jar包在hadoop-hdfs文件的target文件里.

　　所以我们采用第(4)种, 但是源代码第一次mvn时都是很慢的,需要下载很多东西( 主要是jar包和 .pom 文件等).  我们可以用如下命令:

$ su root         # 先切换到root用户,否则很可能会出问题
$ mvn package -Pdist -DskipTests -Dtar     #在哪个目录下,就对哪个目录进行编译

　　成功的话, 会显示 BUILD SUCCESS .

最后的结果,是在启动NameNode的时候,会打印Hello NameNode! . 结果如下:

另外: 上面是我们修改了hadoop-2.7.3-src的源码. 所以要mvn.  如果我们只是使用Hadoop提供的一些接口来实现我们的功能,就不用mvn, 可以用eclipse来实现. 参考我的博客编写hadoop程序并打成jar包上传到hadoop集群运行  .