hadoop搭建部署

HDFS(Hadoop Distributed File System)和Mapreduce是hadoop的两大核心：

HDFS(文件系统)实现分布式存储的底层支持

Mapreduce(编程模型)实现分布式并行任务处理的程序支持

JobTracker   对应于 NameNode

TaskTracker 对应于 DataNode

DataNode和NameNode   是针对数据存放来而言的

JobTracker和TaskTracker是对于MapReduce执行而言的

从官网下载安装包：

wget  http://mirrors.cnnic.cn/apache/hadoop/common/hadoop-2.7.1/hadoop-2.7.1.tar.gz

JDK安装和ssh免密码等此处不再讲述

hadoop环境变量配置：

vim /etc/profile.d/hadoop.sh

HADOOP_HOME=/usr/local/hadoop
HADOOP_HEAPSIZE=
HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
PATH=$HADOOP_HOME/bin:$PATH
HADOOP_OPTS=-Djava.library.path=$HADOOP_HOME/lib/native

然后主要配置下面5个配置文件：

core-site.xml

hdfs-site.xml

mapred-site.xml

yarn-site.xml

slave

以上各配置文件的各项参数默认值：

http://hadoop.apache.org/docs/r2.7.1/hadoop-project-dist/hadoop-common/core-default.xml

http://hadoop.apache.org/docs/r2.7.1/hadoop-project-dist/hadoop-hdfs/hdfs-default.xml

http://hadoop.apache.org/docs/r2.7.1/hadoop-mapreduce-client/hadoop-mapreduce-client-core/mapred-default.xml

http://hadoop.apache.org/docs/r2.7.1/hadoop-yarn/hadoop-yarn-common/yarn-default.xml

vim core-site.xml 在<configuration>处添加以下部分

<configuration>
     <property>
         <name>fs.defaultFS</name>
         <value>hdfs://dataMaster30:9000</value>
     </property>
     <property>
         <name>hadoop.tmp.dir</name>
         <value>file:/usr/local/hadoop/tmp</value>
        <description>Abase for other temporary directories.</description>
     </property>
     <property>
         <name>io.file.buffer.size</name>
         <value></value>
     </property>
</configuration>

vim hdfs-site.xml

<configuration>
       <property>
                <name>dfs.namenode.secondary.http-address</name>
                <value>dataMaster30:9001</value>
        </property>
        <property>
               <name>dfs.replication</name>
               <value></value>
        </property>
        <property>
               <name>dfs.blocksize</name>
               <value>512m</value>
        </property>
        <property>
              <name>dfs.namenode.name.dir</name>
              <value>file:/data/hadoop/name</value>
        </property>
        <property>
             <name>dfs.datanode.data.dir</name>
             <value>file:/data/hadoop/hdfs</value>
       </property>
       <property>
             <name>dfs.webhdfs.enabled</name>
             <value>true</value>
       </property>  
       <property>
             <name>dfs.permissions</name>
             <value>false</value>
       </property>
</configuration>

vim mapred-site.xml

<configuration>
        <property>
                <name>mapreduce.framework.name</name>
                <value>yarn</value>
        </property>
        <property>
                <name>mapreduce.jobhistory.address</name>
                <value>dataMaster30:10020</value>
        </property>
        <property>
                <name>mapreduce.jobhistory.webapp.address</name>
                <value>dataMaster30:19888</value>
        </property>

        <property>
                <name>mapreduce.map.memory.mb</name>
                <value></value>
                <description>每个Map任务的物理内存限制</description>
        </property>

        <property>
                <name>mapreduce.reduce.memory.mb</name>
                <value></value>
                <description>每个Reduce任务的物理内存限制</description>
        </property>
</configuration>

vim yarn-site.xml

<configuration>
        <property>
                 <name>yarn.resourcemanager.hostname</name>
                 <value>dataMaster30</value>
        </property>
        <property>
                 <name>yarn.nodemanager.aux-services</name>
                 <value>mapreduce_shuffle</value>
        </property>
        <property>
                <name>yarn.nodemanager.resource.memory-mb</name>
                <value></value>
                <discription>每个节点可用内存,单位MB</discription>
        </property>

        <property>
                <name>yarn.scheduler.minimum-allocation-mb</name>
                <value></value>
                <discription>单个任务可申请最少内存，默认1024MB</discription>
        </property>

        <property>
                <name>yarn.scheduler.maximum-allocation-mb</name>
                <value></value>
                <discription>单个任务可申请最大内存，默认8192MB</discription>
        </property>
         <property>
                <name>yarn.nodemanager.resource.cpu-vcores</name>
                <value></value>
                <discription>cpu</discription>
        </property>
</configuration>

vim slave

#localhost
dataSlave31
dataSlave32
dataSlave33
dataSlave34
dataSlave35

完成后，将配置好的Hadoop目录分发到各个slave节点对应位置上。

在Master节点服务器启动hadoop集群，从节点会自动启动，进入hadoop目录
(1)初始化，格式化Hadoop。输入命令，bin/hdfs namenode -format
(2)全部启动sbin/start-all.sh，也可以分开sbin/start-dfs.sh、sbin/start-yarn.sh
(3)停止的话，输入命令，sbin/stop-all.sh
(4)输入命令，jps，可以看到相关进程信息，从而进行验证是否启动成功。

如果输入jps出现process information unavailable提示时，这时可以进于是/tmp目录下，删除名称为hsperfdata_{username}的文件夹，然后重新启动Hadoop即可。

# jps (主节点)

1701 SecondaryNameNode
1459 NameNode
2242 Jps
1907 ResourceManager

# jps (从节点)

4520 Jps
9677 NodeManager
9526 DataNode

这时可以浏览器打开 IP:8088 和 IP:50070 就可以查看集群状态和NameNode信息了

Hadoop Shell命令：

http://blog.csdn.net/wuwenxiang91322/article/details/22166423

http://hadoop.apache.org/docs/r1.0.4/cn/hdfs_shell.html