【Hadoop学习】CDH5.2安装部署
【时间】2014年11月19日
【平台】Centos 6.5
【工具】scp
【软件】jdk-7u67-linux-x64.rpm
CDH5.2.0-hadoop2.5.0
【步骤】
1. 准备条件
(1)集群规划
| 主机类型 | IP地址 | 域名 |
| master | 192.168.50.10 | master.hadoop.com |
| slave1 | 192.168.50.11 | slave1.hadoop.com |
| slave2 | 192.168.50.12 | slave2.hadoop.com |
| slave3 | 192.168.50.13 | slave3.hadoop.com |
(2)以root身份登录操作系统
(3)在集群中的每台主机上执行如下命令,设置主机名。
hostname *.hadoop.com
编辑文件/etc/sysconfig/network如下
HOSTNAME=*.hadoop.com
(4)修改文件/etc/hosts如下
192.168.86.10 master.hadoop.com
192.168.86.11 slave1.hadoop.com
192.168.86.12 slave2.hadoop.com
192.168.86.13 slave3.hadoop.com
执行如下命令,将hosts文件复制到集群中每台主机上
scp /etc/hosts 192.168.50.*:/etc/hosts
(5)安装jdk
rpm -ivh jdk-7u67-linux-x64.rpm
创建文件
echo -e "JAVA_HOME=/usr/java/default\nexport PATH=\$JAVA_HOME/bin:\$PATH" > /etc/profile.d/java-env.sh
. /etc/profile.d/java-env.sh
(6)关闭iptables
service iptables stop
chkconfig iptables off
(7)关闭selinux。修改文件/etc/selinux/config,然后重启操作系统
SELINUX=disabled
2. 安装 (with YARN)
(1)在master.hadoop.com主机上执行
yum install hadoop-yarn-resourcemanager hadoop-mapreduce-historyserver hadoop-yarn-proxyserver hadoop-hdfs-namenode
yum install hadoop-hdfs-secondarynamenode 可选,如果使用HA,就不要安装此包
(2)在所有的slave*.hadoop.com主机上执行
yum install hadoop-yarn-nodemanager hadoop-mapreduce hadoop-hdfs-datanode
3. 配置。将以下文件修改完毕后,用scp命令复制到集群中的所有主机上
(1)创建配置文件
cp -r /etc/hadoop/conf.empty /etc/hadoop/conf.my_cluster
alternatives --install /etc/hadoop/conf hadoop-conf /etc/hadoop/conf.my_cluster
alternatives --set hadoop-conf /etc/hadoop/conf.my_cluster
(2)创建必要的本地文件夹
sudo -u hdfs hadoop fs -mkdir -p /tmp && sudo -u hdfs hadoop fs -chmod -R /tmp
sudo -u hdfs hadoop fs -mkdir -p /tmp/hadoop-yarn && sudo -u hdfs hadoop fs -chown -R mapred:mapred /tmp/hadoop-yarn
sudo -u hdfs hadoop fs -mkdir -p /tmp/hadoop-yarn/staging/history/done_intermediate && sudo -u hdfs hadoop fs -chown -R mapred:mapred /tmp/hadoop-yarn/staging && sudo -u hdfs hadoop fs -chmod -R /tmp
sudo -u hdfs hadoop fs -mkdir -p /var
sudo -u hdfs hadoop fs -mkdir -p /var/log && sudo -u hdfs hadoop fs -chmod -R /var/log && sudo -u hdfs hadoop fs -chown yarn:mapred /var/log
sudo -u hdfs hadoop fs -mkdir -p /var/log/hadoop-yarn/apps && sudo -u hdfs hadoop fs -chmod -R /var/log/hadoop-yarn/apps && sudo -u hdfs hadoop fs -chown yarn:mapred /var/log/hadoop-yarn/apps
sudo -u hdfs hadoop fs -mkdir -p /user
sudo -u hdfs hadoop fs -mkdir -p /user/history && sudo -u hdfs hadoop fs -chown mapred /user/history
sudo -u hdfs hadoop fs -mkdir -p /user/test && sudo -u hdfs hadoop fs -chmod -R /user/test && sudo -u hdfs hadoop fs -chown test /user/test
sudo -u hdfs hadoop fs -mkdir -p /user/root && sudo -u hdfs hadoop fs -chmod -R /user/root && sudo -u hdfs hadoop fs -chown root /user/root
(3)修改配置文件
1)core-site.xml
<property>
<name>fs.defaultFS</name>
<value>hdfs://master.hadoop.com:8020</value>
</property> <property>
<name>fs.trash.interval</name>
<value>1440</value>
</property> <property>
<name>fs.trash.checkpoint.interval</name>
<value>720</value>
</property> <property>
<name>hadoop.proxyuser.mapred.groups</name>
<value>*</value>
</property> <property>
<name>hadoop.proxyuser.mapred.hosts</name>
<value>*</value>
</property> <property>
<name>io.compression.codecs</name>
<value>org.apache.hadoop.io.compress.DefaultCodec,org.apache.hadoop.io.compress.GzipCodec,org.apache.hadoop.io.compress.BZip2Codec,com.hadoop.compression.lzo.LzoCodec,com.hadoop.compression.lzo.LzopCodec,org.apache.hadoop.io.compress.SnappyCodec</value>
</property>
2)hdfs-site.xml
<property>
<name>dfs.permissions.superusergroup</name>
<value>hadoop</value>
</property> <property>
<name>dfs.namenode.name.dir</name>
<value>file:///data/1/dfs/nn</value>
</property> <property>
<name>dfs.datanode.data.dir</name>
<value>file:///data/1/dfs/dn,file:///data/2/dfs/dn,file:///data/3/dfs/dn,file:///data/4/dfs/dn</value>
</property> <property>
<name>dfs.datanode.failed.volumes.tolerated</name>
<value>3</value>
</property> <property>
<name>dfs.datanode.fsdataset.volume.choosing.policy</name>
<value>org.apache.hadoop.hdfs.server.datanode.fsdataset.AvailableSpaceVolumeChoosingPolicy</value>
</property> <property>
<name>dfs.datanode.available-space-volume-choosing-policy.balanced-space-threshold</name>
<value>10737418240</value>
</property> <property>
<name>dfs.datanode.available-space-volume-choosing-policy.balanced-space-preference-fraction</name>
<value>0.75</value>
</property> <property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property> <property>
<name>dfs.webhdfs.user.provider.user.pattern</name>
<value>^[A-Za-z0-9_][A-Za-z0-9._-]*[$]?$</value>
</property>
3)yarn-site.xml
<property>
<name>yarn.resourcemanager.hostname</name>
<value>master.hadoop.com</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>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property> <property>
<description>List of directories to store localized files in.</description>
<name>yarn.nodemanager.local-dirs</name>
<value>/data/1/yarn/local,/data/2/yarn/local,/data/3/yarn/local,/data/4/yarn/local</value>
</property> <property>
<description>Where to store container logs.</description>
<name>yarn.nodemanager.log-dirs</name>
<value>/data/1/yarn/logs,/data/2/yarn/logs,/data/3/yarn/logs,/data/4/yarn/logs</value>
</property> <property>
<description>Where to aggregate logs to.</description>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>hdfs://master.hadoop.com:8020/var/log/hadoop-yarn/apps</value>
</property> <property>
<description>Classpath for typical applications.</description>
<name>yarn.application.classpath</name>
<value>
$HADOOP_CONF_DIR,
$HADOOP_COMMON_HOME/*,$HADOOP_COMMON_HOME/lib/*,
$HADOOP_HDFS_HOME/*,$HADOOP_HDFS_HOME/lib/*,
$HADOOP_MAPRED_HOME/*,$HADOOP_MAPRED_HOME/lib/*,
$HADOOP_YARN_HOME/*,$HADOOP_YARN_HOME/lib/*
</value>
</property> <property>
<name>yarn.web-proxy.address</name>
<value>master.hadoop.com</value>
</property> <property>
<description>It's not the memory the physical machine totally has, but that allocated to containers</description>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>5120</value>
</property> <property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>512</value>
</property> <property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>10240</value>
</property>
<property>
<name>yarn.app.mapreduce.am.resource.mb</name>
<value>512</value>
</property> <property>
<name>yarn.app.mapreduce.am.command-opts</name>
<value>-Xmx512m</value>
</property> <property>
<name>yarn.nodemanager.vmem-pmem-ratio</name>
<value>2.1</value>
</property> <property>
<name>yarn.nodemanager.resource.cpu-vcores</name>
<value>4</value>
</property> <property>
<name>yarn.scheduler.minimum-allocation-vcores</name>
<value>1</value>
</property> <property>
<name>yarn.scheduler.maximum-allocation-vcores</name>
<value>10</value>
</property> <property>
<name>yarn.scheduler.increment-allocation-mb</name>
<value>512</value>
</property> <property>
<name>yarn.scheduler.increment-allocation-vcores</name>
<value>1</value>
</property>
4)mapred-site.xml
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property> <property>
<name>mapreduce.jobhistory.address</name>
<value>master.hadoop.com:10020</value>
</property> <property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>master.hadoop.com:19888</value>
</property> <property>
<name>yarn.app.mapreduce.am.staging-dir</name>
<value>/user/history</value>
</property> <property>
<name>mapreduce.jobhistory.intermediate-done-dir</name>
<value>/user/history/intermediate-done-dir</value>
</property> <property>
<name>mapreduce.jobhistory.done-dir</name>
<value>/user/history/done-dir</value>
</property>
(4)复制配置文件到集群中的所有主机上
scp /etc/hadoop/conf.my_cluster/*-site.xml 192.168.50.*:/etc/hadoop/conf.my_cluster/
4. 格式化HDFS
sudo -u hdfs hdfs namenode -format
5. 启动HDFS
for x in `cd /etc/init.d ; ls hadoop-hdfs-*`; do service $x start; done
6. 在HDFS上创建必要的文件夹
sudo -u hdfs hadoop fs -mkdir -p /tmp && sudo -u hdfs hadoop fs -chmod -R /tmp
sudo -u hdfs hadoop fs -mkdir -p /tmp/hadoop-yarn && sudo -u hdfs hadoop fs -chown -R mapred:mapred /tmp/hadoop-yarn
sudo -u hdfs hadoop fs -mkdir -p /tmp/hadoop-yarn/staging/history/done_intermediate && sudo -u hdfs hadoop fs -chown -R mapred:mapred /tmp/hadoop-yarn/staging && sudo -u hdfs hadoop fs -chmod -R /tmp
sudo -u hdfs hadoop fs -mkdir -p /var
sudo -u hdfs hadoop fs -mkdir -p /var/log && sudo -u hdfs hadoop fs -chmod -R /var/log && sudo -u hdfs hadoop fs -chown yarn:mapred /var/log
sudo -u hdfs hadoop fs -mkdir -p /var/log/hadoop-yarn/apps && sudo -u hdfs hadoop fs -chmod -R /var/log/hadoop-yarn/apps && sudo -u hdfs hadoop fs -chown yarn:mapred /var/log/hadoop-yarn/apps
sudo -u hdfs hadoop fs -mkdir -p /user
sudo -u hdfs hadoop fs -mkdir -p /user/history && sudo -u hdfs hadoop fs -chown mapred /user/history
sudo -u hdfs hadoop fs -mkdir -p /user/test && sudo -u hdfs hadoop fs -chmod -R /user/test && sudo -u hdfs hadoop fs -chown test /user/test
sudo -u hdfs hadoop fs -mkdir -p /user/root && sudo -u hdfs hadoop fs -chmod -R /user/root && sudo -u hdfs hadoop fs -chown root /user/root
7. 操作YARN
在集群中每台机器上执行如下命令:
(1)启动
service hadoop-yarn-resourcemanager start;service hadoop-mapreduce-historyserver start;service hadoop-yarn-proxyserver start;service hadoop-yarn-nodemanager start
(2)查看
service hadoop-yarn-resourcemanager status;service hadoop-mapreduce-historyserver status;service hadoop-yarn-proxyserver status;service hadoop-yarn-nodemanager status
(3)停止
service hadoop-yarn-resourcemanager stop;service hadoop-mapreduce-historyserver stop;service hadoop-yarn-proxyserver stop;service hadoop-yarn-nodemanager stop
(4)重启
service hadoop-yarn-resourcemanager restart;service hadoop-mapreduce-historyserver restart;service hadoop-yarn-proxyserver restart;service hadoop-yarn-nodemanager restart
8. 安装Hadoop客户端
(1)安装CentOS 6.5
(2)以root身份登录,执行以下命令:
rpm -ivh jdk-7u67-linux-x64.rpm yum install hadoop-client cp -r /etc/hadoop/conf.empty /etc/hadoop/conf.my_cluster
alternatives --install /etc/hadoop/conf hadoop-conf /etc/hadoop/conf.my_cluster
alternatives --set hadoop-conf /etc/hadoop/conf.my_cluster scp 192.168.50.10:/etc/hadoop/conf.my_cluster/*-site.xml /etc/hadoop/conf.my_cluster/
scp 192.168.50.10:/etc/hosts /etc/
scp 192.168.50.10:/etc/profile.d/hadoop-env.sh /etc/profile.d/
. /etc/profile useradd -u 700 -g hadoop test
passwd test <test用户密码>
9. 测试Hadoop with YARN
su - test #计算Pi
hadoop fs -mkdir input
hadoop fs -put /etc/hadoop/conf/*.xml input
hadoop jar /usr/lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar wordcount input output
hadoop jar /usr/lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar pi 2 100 #执行grep任务
hadoop jar /usr/lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar grep input output 'dfs[a-z.]+'
hadoop fs -ls output
hadoop fs -cat output/part-r-00000 | head
【参考】
1)Cloudera 官方安装文档 http://www.cloudera.com/content/cloudera/en/documentation/core/latest/topics/cdh_ig_command_line.html
【Hadoop学习】CDH5.2安装部署的更多相关文章
- Ganglia监控Hadoop集群的安装部署[转]
Ganglia监控Hadoop集群的安装部署 一. 安装环境 Ubuntu server 12.04 安装gmetad的机器:192.168.52.105 安装gmond的机 器:192.168.52 ...
- Hadoop分布式HA的安装部署
Hadoop分布式HA的安装部署 前言 单机版的Hadoop环境只有一个namenode,一般namenode出现问题,整个系统也就无法使用,所以高可用主要指的是namenode的高可用,即存在两个n ...
- Apache Hadoop集群离线安装部署(三)——Hbase安装
Apache Hadoop集群离线安装部署(一)——Hadoop(HDFS.YARN.MR)安装:http://www.cnblogs.com/pojishou/p/6366542.html Apac ...
- Apache Hadoop集群离线安装部署(二)——Spark-2.1.0 on Yarn安装
Apache Hadoop集群离线安装部署(一)——Hadoop(HDFS.YARN.MR)安装:http://www.cnblogs.com/pojishou/p/6366542.html Apac ...
- Apache Hadoop集群离线安装部署(一)——Hadoop(HDFS、YARN、MR)安装
虽然我已经装了个Cloudera的CDH集群(教程详见:http://www.cnblogs.com/pojishou/p/6267616.html),但实在太吃内存了,而且给定的组件版本是不可选的, ...
- 【Spark学习】Spark 1.1.0 with CDH5.2 安装部署
[时间]2014年11月18日 [平台]Centos 6.5 [工具]scp [软件]jdk-7u67-linux-x64.rpm spark-worker-1.1.0+cdh5.2.0+56-1.c ...
- 高可用Hadoop平台-Ganglia安装部署
1.概述 最近,有朋友私密我,Hadoop有什么好的监控工具,其实,Hadoop的监控工具还是蛮多的.今天给大家分享一个老牌监控工具Ganglia,这个在企业用的也算是比较多的,Hadoop对它的兼容 ...
- Hadoop+Hbas完全分布式安装部署
Hadoop安装部署基本步骤: 1.安装jdk,配置环境变量. jdk可以去网上自行下载,环境变量如下: 编辑 vim /etc/profile 文件,添加如下内容: export JAVA_HO ...
- hadoop学习通过虚拟机安装hadoop完全分布式集群
要想深入的学习hadoop数据分析技术,首要的任务是必须要将hadoop集群环境搭建起来,可以将hadoop简化地想象成一个小软件,通过在各个物理节点上安装这个小软件,然后将其运行起来,就是一个had ...
- Hadoop完全分布式模式安装部署
在Linux上搭建Hadoop系列:1.Hadoop环境搭建流程图2.搭建Hadoop单机模式3.搭建Hadoop伪分布式模式4.搭建Hadoop完全分布式模式 注:此教程皆是以范例讲述的,当然你可以 ...
随机推荐
- SGU 180
求逆序数对 归并排序 #include <cstdio> #include <cstring> #include <cmath> #include <a ...
- python中unicode、utf8、gbk等编码问题
转自:http://luchanghong.com/python/2012/07/06/python-encoding-with-unicode-and-gbk-and-utf8.html 概要:编码 ...
- C++11 生产者消费者
下面是一个生产者消费者问题,来介绍condition_variable的用法.当线程间的共享数据发生变化的时候,可以通过condition_variable来通知其他的线程.消费者wait 直到生产者 ...
- URAL 1146 Maximum Sum & HDU 1081 To The Max (DP)
点我看题目 题意 : 给你一个n*n的矩阵,让你找一个子矩阵要求和最大. 思路 : 这个题都看了好多天了,一直不会做,今天娅楠美女给讲了,要转化成一维的,也就是说每一列存的是前几列的和,也就是说 0 ...
- POJ 1797 Heavy Transportation(Dijkstra)
http://poj.org/problem?id=1797 题意 :给出N个城市M条边,每条边都有容量值,求一条运输路线使城市1到N的运输量最大. 思路 :用dijkstra对松弛条件进行变形.解释 ...
- struts2总结六: Struts2的拦截器
一.Struts2的系统结构图
- altium designer 13 学习之添加汉字
在altium desginer中如果你是想添加英文还是比较方便的,基本直接就可以输入了,但是添加中文就不是那么简单了,下面不介绍下如何在altium designer中快速的添加自己想要的中文 工具 ...
- editplus的配置文件来支持sql语法高亮【转】
editplus默认是没有sql语法高亮的,原因是它的内部没有sql.stx的这样一个语法文件 我们自己在 EditPlus 的安装目录下面新建一个文件名为sql.stx,然后打开editplus ...
- LoadImage 和 BitBlt
#include <windows.h> #define WINDOWCLASS TEXT("Test") #define WNDTITLE TEXT("Te ...
- javeWeb常用快捷键 Junit for changeableargs enumn reflect
*1 工具常用的快捷键 1) Eclipse和MyEclipse,IBM,2001,Java编写,开源,跨平台跨语言 2)Alt+/快速内容提示 3)Ctrl+1快速修补错误 4)Syso ...