相信各位读者们在运行Hadoop时或多或少的都会遇到一些很让人费解的警告，举个栗子：
WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
大家应该不陌生。之所以会出现这个问题是因为没有使用本地编译的Hadoop二进制文件运行Hadoop，而是使用了官网下载的预编译的Hadoop。虽然运行起来没有什么问题，但是每次启动的时候都显示这一句警告很不爽有木有？
废话不多说，我们现在开始。
本人是用的 CentOS 6.8 64bit 版本的Linux系统来运行Hadoop集群的。
首先，下载编译所需要的软件包：
apache-ant-1.9.4-bin.tar.gz
findbugs-3.0.0.tar.gz
protobuf-2.5.0.tar.gz
apache-maven-3.0.5-bin.tar.gz
安装编译所需软件：
解压apache-maven-3.0.5-bin.tar.gz
把Maven的环境变量配到/etc/profile中，随后source /etc/profile使修改生效。使用mvn -v命令检查Maven是否安装成功。
解压apache-ant-1.9.4-bin.tar.gz
与Maven相同的步骤，随后使用ant-version命令验证是否安装成功。
解压findbugs-3.0.0.tar.gz
同样需要配置环境变量，使用findbugs-version验证是否安装成功。
解压protobuf-2.5.0.tar.gz（注意：protobuf的版本必须是2.5.0及以上）
cd到protobuf目录，依次执行以下命令：
./configure
make
make check
make install
使用protoc --version命令验证是否安装成功。
安装cmake、openssl-devel、ncurses-devel（注意：必须是root用户，并且要能连上网）
执行以下命令：
yum install cmake
yum install openssl-devel
yum install ncurses-devel
编译Hadoop源码：
cd到先前已解压的Hadoop源码目录
执行 mvn clean install -DskipTests 命令
等待完成(会自动联网下载很多东西)
执行 mvn package -Pdist,native -DskipTests -Dtar 命令，开始编译，等待完成
过程大概是这样的：
[INFO] ------------------------------------------------------------------------
[INFO] Reactor Summary:
[INFO]
[INFO] Apache Hadoop Main ................................ SUCCESS[6.304s]
[INFO] Apache Hadoop Project POM ......................... SUCCESS [26.555s]
[INFO] Apache Hadoop Annotations ......................... SUCCESS[2.757s]
[INFO] Apache Hadoop Assemblies .......................... SUCCESS [0.216s]
[INFO] Apache Hadoop Project Dist POM .................... SUCCESS [19.592s]
[INFO] Apache Hadoop Maven Plugins ....................... SUCCESS [2.715s]
[INFO] Apache Hadoop MiniKDC ............................. SUCCESS [2.360s]
[INFO] Apache Hadoop Auth ................................ SUCCESS [2.950s]
[INFO] Apache Hadoop Auth Examples ....................... SUCCESS[2.119s]
[INFO] Apache Hadoop Common .............................. SUCCESS [1:22.302s]
[INFO] Apache Hadoop NFS ................................. SUCCESS [5.095s]
[INFO] Apache Hadoop Common Project...................... SUCCESS [0.026s]
[INFO] Apache Hadoop HDFS ................................ SUCCESS [2:06.178s]
[INFO] Apache Hadoop HttpFS .............................. SUCCESS [1:09.142s]
[INFO] Apache Hadoop HDFS BookKeeper Journal ............. SUCCESS [14.457s]
[INFO] Apache Hadoop HDFS-NFS ............................SUCCESS [2.859s]
[INFO] Apache Hadoop HDFS Project ........................ SUCCESS [0.030s]
[INFO] hadoop-yarn ....................................... SUCCESS [0.029s]
[INFO] hadoop-yarn-api ................................... SUCCESS [59.010s]
[INFO] hadoop-yarn-common ................................ SUCCESS [20.743s]
[INFO] hadoop-yarn-server ................................ SUCCESS[0.026s]
[INFO] hadoop-yarn-server-common ......................... SUCCESS [7.344s]
[INFO] hadoop-yarn-server-nodemanager .................... SUCCESS [11.726s]
[INFO] hadoop-yarn-server-web-proxy ...................... SUCCESS [2.508s]
[INFO] hadoop-yarn-server-applicationhistoryservice ...... SUCCESS [4.041s]
[INFO] hadoop-yarn-server-resourcemanager ................ SUCCESS [10.370s]
[INFO] hadoop-yarn-server-tests .......................... SUCCESS [0.374s]
[INFO] hadoop-yarn-client ................................ SUCCESS [4.791s]
[INFO] hadoop-yarn-applications .......................... SUCCESS [0.025s]
[INFO] hadoop-yarn-applications-distributedshell ......... SUCCESS [2.242s]
[INFO] hadoop-yarn-applications-unmanaged-am-launcher .... SUCCESS [1.553s]
[INFO] hadoop-yarn-site .................................. SUCCESS [0.024s]
[INFO] hadoop-yarn-project ............................... SUCCESS [3.261s]
[INFO] hadoop-mapreduce-client ........................... SUCCESS [0.082s]
[INFO] hadoop-mapreduce-client-core ...................... SUCCESS [18.549s]
[INFO] hadoop-mapreduce-client-common .................... SUCCESS [13.772s]
[INFO] hadoop-mapreduce-client-shuffle ................... SUCCESS [2.441s]
[INFO] hadoop-mapreduce-client-app ....................... SUCCESS [6.866s]
[INFO] hadoop-mapreduce-client-hs ........................ SUCCESS [6.280s]
[INFO] hadoop-mapreduce-client-jobclient .................SUCCESS [3.510s]
[INFO] hadoop-mapreduce-client-hs-plugins ................ SUCCESS [1.725s]
[INFO] Apache Hadoop MapReduce Examples .................. SUCCESS [4.641s]
[INFO] hadoop-mapreduce .................................. SUCCESS[3.002s]
[INFO] Apache Hadoop MapReduce Streaming ................. SUCCESS [3.497s]
[INFO] Apache Hadoop Distributed Copy .................... SUCCESS [5.847s]
[INFO] Apache Hadoop Archives ............................ SUCCESS [1.791s]
[INFO] Apache Hadoop Rumen ............................... SUCCESS [4.693s]
[INFO] Apache Hadoop Gridmix ............................. SUCCESS [3.235s]
[INFO] Apache Hadoop Data Join........................... SUCCESS [2.349s]
[INFO] Apache Hadoop Extras .............................. SUCCESS [2.488s]
[INFO] Apache Hadoop Pipes ............................... SUCCESS [5.863s]
[INFO] Apache Hadoop OpenStack support ................... SUCCESS [3.776s]
[INFO] Apache Hadoop Client .............................. SUCCESS [5.235s]
[INFO] Apache Hadoop Mini-Cluster ........................ SUCCESS [0.070s]
[INFO] Apache Hadoop Scheduler Load Simulator ............ SUCCESS [3.935s]
[INFO] Apache Hadoop Tools Dist .......................... SUCCESS [4.392s]
[INFO] Apache Hadoop Tools ............................... SUCCESS [0.022s]
[INFO] Apache Hadoop Distribution ........................ SUCCESS [21.274s]
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 10:25.147s
[INFO] Finished at: Mon Jul 28 16:09:56 CST 2014
[INFO] Final Memory: 75M/241M
[INFO] ------------------------------------------------------------------------
表示编译成功
cd到hadoop-2.4.0-src/hadoop-dist/target/hadoop-2.4.0/lib/native中，将 64 位的 native 文件夹替换原 32 位的文件夹即可
大功告成！