Cloudera（CDH）的hadoop和Hortonworks（HDP）的的hadoop编译
版本使用范围，大致 与Apache Hadoop编译步骤一致大同小异，因为CDH的Hadoop的本来就是从社区版迁过来的，所以，这篇文章同样适合所有的以Apache Hadoop为原型的其他商业版本的hadoop编译，例如，Cloudera（CDH）的hadoop和Hortonworks（HDP）的的hadoop编译，下面开工：
1，环境准备（Cenots6.x，其他的大同小异）
（1）yum安装 sudo yum install -y autoconf automake libtool git gcc gcc-c++ make cmake openssl-devel,ncurses-devel bzip2-devel
（2）安装JDK1.7+
（3）安装Maven3.0+
（4）安装Ant1.8+
（5）安装 protobuf-2.5.0.tar.gz
安装例子：
cd /home/search
tar -zxvf protobuf-2.5.0.tar.gz
cd /home/search/protobuf-2.5.0
./configure --prefix=/home/search/protobuf（指定的一个安装目录，默认是根目录）
make && make install
（6）安装snappy1.1.0.tar.gz（可选选项，如果需要编译完的Hadoop支持Snappy压缩，需要此步骤）
安装例子：
cd /home/search
tar -zxvf snappy1.1.0.tar.gz
cd /home/search/snappy1.1.0
./configure --prefix=/home/search/snappy（指定的一个安装目录，默认是根目录）
make && make install
（7）安装hadoop-snappy
git下载地址
git clone https://github.com/electrum/hadoop-snappy.git
安装例子：
下载完成后
cd hadoop-snappy
执行maven打包命令
mvn package -Dsnappy.prefix=/home/search/snappy （需要6步骤）
构建成功后
这个目录就是编译后的snappy的本地库，在hadoop-snappy/target/hadoop-snappy-0.0.1-SNAPSHOT-tar/hadoop-snappy-0.0.1-SNAPSHOT/lib目录下，有个hadoop-snappy-0.0.1-SNAPSHOT.jar，在hadoop编译后，需要拷贝到$HADOOP_HOME/lib目录下
上面使用到的包，可到百度网盘：http://pan.baidu.com/s/1mBjZ4下载
2，下载编译hadoop2.6.0
下载cdh-hadoop2.6.0源码：
wget http://archive-primary.cloudera.com/cdh5/cdh/5/hadoop-2.6.0-cdh5.4.1-src.tar.gz
解压
tar -zxvf hadoop-2.6.0-cdh5.4.1-src.tar.gz
解压后进入根目录
执行下面这个编译命令，就能把snappy库绑定到hadoop的本地库里面，这样就可以在所有的机器上跑了
mvn clean package -DskipTests -Pdist,native -Dtar -Dsnappy.lib=(hadoop-snappy里面编译后的库地址) -Dbundle.snappy
中间会报一些异常，无须关心，如果报异常退出了，就继续执行上面这个命令，直到成功为止，一般速度会跟你的网速有关系，大概40分钟左右，最后会编译成功。 
3，搭建Hadoop集群
（1）拷贝编译完成后在hadoop-2.6.0-cdh5.4.1/hadoop-dist/target/hadoop-2.6.0-cdh5.4.1.tar.gz位置的tar包，至安装目录
（2）解压执行mv hadoop-2.6.0-cdh5.4.1 hadoop重命名为hadoop
（3）进入hadoop目录下，执行bin/hadoop checknative -a查看本地库，支持情况 
（4）配置Hadoop相关的环境变量
#hadoop
export HADOOP_HOME=/home/search/hadoop
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
export HADOOP_MAPRED_HOME=$HADOOP_HOME
export HADOOP_COMMON_HOME=$HADOOP_HOME
export HADOOP_HDFS_HOME=$HADOOP_HOME
export YARN_HOME=$HADOOP_HOME
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export YARN_CONF_DIR=$HADOOP_HOME/etc/hadoop
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
export CLASSPATH=.:$CLASSPATH:$HADOOP_COMMON_HOME:$HADOOP_COMMON_HOMEi/lib:$HADOOP_MAPRED_HOME:$HADOOP_HDFS_HOME:$HADOOP_HDFS_HOME
（5）选择一个数据目录/data/
新建三个目录
hadooptmp（存放hadoop的一些临时数据）
nd（存放hadoop的namenode数据）
dd（存放hadoop的datanode数据）
（6）进入hadoop/etc/hadoop目录
依次配置
slaves内容如下：
hadoop1 hadoop2 hadoop3
hadoop1 hadoop2 hadoop3
core-site.xml内容如下:
<configuration> <property> <name>fs.default.name</name> <value>hdfs://hadoop1:8020</value> </property> <property> <name>hadoop.tmp.dir</name> <value>/ROOT/tmp/data/hadooptmp</value> </property> <property> <name>io.compression.codecs</name> <value>org.apache.hadoop.io.compress.GzipCodec,org.apache.hadoop.io.compress.DefaultCodec,org.apache.hadoop.io.compress.BZip2Codec,org.apache.hadoop.io.compress.SnappyCodec</value> </property> <property> <name>fs.trash.interval</name> <value>1440</value> <description>Number of minutes between trash checkpoints. If zero, the trash feature is disabled. </description> </property> </configuration>
<configuration>
<property>
<name>fs.default.name</name>
<value>hdfs://hadoop1:8020</value>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>/ROOT/tmp/data/hadooptmp</value>
</property>
<property>
<name>io.compression.codecs</name>
<value>org.apache.hadoop.io.compress.GzipCodec,org.apache.hadoop.io.compress.DefaultCodec,org.apache.hadoop.io.compress.BZip2Codec,org.apache.hadoop.io.compress.SnappyCodec</value>
</property>
<property>
<name>fs.trash.interval</name>
<value>1440</value>
<description>Number of minutes between trash checkpoints.
If zero, the trash feature is disabled.
</description>
</property>
</configuration>
hdfs-site.xml内容如下：
<configuration> <property> <name>dfs.replication</name> <value>1</value> </property> <property> <name>dfs.namenode.name.dir</name> <value>file:///ROOT/tmp/data/nd</value> </property> <property> <name>dfs.datanode.data.dir</name> <value>/ROOT/tmp/data/dd</value> </property> <property> <name>dfs.permissions</name> <value>false</value> </property> <property> <name>dfs.webhdfs.enabled</name> <value>true</value> </property> <property> <name>dfs.blocksize</name> <value>134217728</value> </property> <property> <name>dfs.namenode.handler.count</name> <value>20</value> </property> <property> <name>dfs.datanode.max.xcievers</name> <value>65535</value> </property> </configuration>
<configuration>
<property>
<name>dfs.replication</name>
<value>1</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>file:///ROOT/tmp/data/nd</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>/ROOT/tmp/data/dd</value>
</property>
<property>
<name>dfs.permissions</name>
<value>false</value>
</property>
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.blocksize</name>
<value>134217728</value>
</property>
<property>
<name>dfs.namenode.handler.count</name>
<value>20</value>
</property>
<property>
<name>dfs.datanode.max.xcievers</name>
<value>65535</value>
</property>
</configuration>
mapred-site.xml内容如下：
<configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <property> <name>mapreduce.jobtracker.address</name> <value>hadoop1:8021</value> </property> <property> <name>mapreduce.jobhistory.address</name> <value>hadoop1:10020</value> </property> <property> <name>mapreduce.jobhistory.webapp.address</name> <value>hadoop1:19888</value> </property> <property> <name>mapred.max.maps.per.node</name> <value>4</value> </property> <property> <name>mapred.max.reduces.per.node</name> <value>2</value> </property> <property> <name>mapreduce.map.memory.mb</name> <value>1408</value> </property> <property> <name>mapreduce.map.java.opts</name> <value>-Xmx1126M</value> </property> <property> <name>mapreduce.reduce.memory.mb</name> <value>2816</value> </property> <property> <name>mapreduce.reduce.java.opts</name> <value>-Xmx2252M</value> </property> <property> <name>mapreduce.task.io.sort.mb</name> <value>512</value> </property> <property> <name>mapreduce.task.io.sort.factor</name> <value>100</value> </property> </configuration>
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.jobtracker.address</name>
<value>hadoop1:8021</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>hadoop1:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>hadoop1:19888</value>
</property>
<property>
<name>mapred.max.maps.per.node</name>
<value>4</value>
</property>
<property>
<name>mapred.max.reduces.per.node</name>
<value>2</value>
</property>
<property>
<name>mapreduce.map.memory.mb</name>
<value>1408</value>
</property>
<property>
<name>mapreduce.map.java.opts</name>
<value>-Xmx1126M</value>
</property>
<property>
<name>mapreduce.reduce.memory.mb</name>
<value>2816</value>
</property>
<property>
<name>mapreduce.reduce.java.opts</name>
<value>-Xmx2252M</value>
</property>
<property>
<name>mapreduce.task.io.sort.mb</name>
<value>512</value>
</property>
<property>
<name>mapreduce.task.io.sort.factor</name>
<value>100</value>
</property>
</configuration>
yarn-site.xml内容如下：
<configuration> <property> <name>mapreduce.jobhistory.address</name> <value>hadoop1:10020</value> </property> <property> <name>mapreduce.jobhistory.webapp.address</name> <value>hadoop1:19888</value> </property> <property> <name>yarn.resourcemanager.address</name> <value>hadoop1:8032</value> </property> <property> <name>yarn.resourcemanager.scheduler.address</name> <value>hadoop1:8030</value> </property> <property> <name>yarn.resourcemanager.scheduler.class</name> <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler</value> </property> <property> <name>yarn.resourcemanager.resource-tracker.address</name> <value>hadoop1:8031</value> </property> <property> <name>yarn.resourcemanager.admin.address</name> <value>hadoop1:8033</value> </property> <property> <name>yarn.resourcemanager.webapp.address</name> <value>hadoop1:8088</value> </property> <property> <name>yarn.nodemanager.aux-services</name> <value>mapreduce_shuffle</value> </property> <property> <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name> <value>org.apache.hadoop.mapred.ShuffleHandler</value> </property> <property> <description>Classpath for typical applications.</description> <name>yarn.application.classpath</name> <value>$HADOOP_CONF_DIR ,$HADOOP_COMMON_HOME/share/hadoop/common/* ,$HADOOP_COMMON_HOME/share/hadoop/common/lib/* ,$HADOOP_HDFS_HOME/share/hadoop/hdfs/* ,$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/* ,$YARN_HOME/share/hadoop/yarn/*</value> </property> <!-- Configurations for NodeManager --> <property> <name>yarn.nodemanager.resource.memory-mb</name> <value>5632</value> </property> <property> <name>yarn.scheduler.minimum-allocation-mb</name> <value>1408</value> </property> <property> <name>yarn.scheduler.maximum-allocation-mb</name> <value>5632</value> </property> </configuration>
<configuration>
<property>
<name>mapreduce.jobhistory.address</name>
<value>hadoop1:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>hadoop1:19888</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>hadoop1:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>hadoop1:8030</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>hadoop1:8031</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>hadoop1:8033</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>hadoop1:8088</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<description>Classpath for typical applications.</description>
<name>yarn.application.classpath</name>
<value>$HADOOP_CONF_DIR
,$HADOOP_COMMON_HOME/share/hadoop/common/*
,$HADOOP_COMMON_HOME/share/hadoop/common/lib/*
,$HADOOP_HDFS_HOME/share/hadoop/hdfs/*
,$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/*
,$YARN_HOME/share/hadoop/yarn/*</value>
</property>
<!-- Configurations for NodeManager -->
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>5632</value>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>1408</value>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>5632</value>
</property>
</configuration>
（6）将整个hadoop目录和/data数据目录，scp分发到各个节点上
（7）格式化HDFS
执行命令bin/hadoop namenode -format
（8）启动集群
sbin/start-dfs.sh 启动hdfs
sbin/start-yarn.sh启动yarn
sbin/mr-jobhistory-daemon.sh start historyserver 启动日志进程
（9）检验集群状态
jps监测： 
web页面监测：
http://hadoop1:50070
http://hadoop1:8088
（10）基准测试
测试map
bin/hadoop jar ./share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0-cdh5.4.1.jar randomwriter rand
测试reduce
bin/hadoop jar ./share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0-cdh5.4.1.jar sort rand sort-rand
Hadoop官方文档链接：http://hadoop.apache.org/docs/r2.7.0/hadoop-project-dist/hadoop-hdfs/HdfsUserGuide.html