Hadoop2 namenode HA+聯(lián)邦+Resource Manager HA實(shí)驗(yàn)分析

本篇內(nèi)容介紹了“Hadoop2 namenode HA+聯(lián)邦+Resource Manager HA實(shí)驗(yàn)分析”的有關(guān)知識(shí)，在實(shí)際案例的操作過程中，不少人都會(huì)遇到這樣的困境，接下來就讓小編帶領(lǐng)大家學(xué)習(xí)一下如何處理這些情況吧！希望大家仔細(xì)閱讀，能夠?qū)W有所成！

實(shí)驗(yàn)的Hadoop版本為2.5.2，硬件環(huán)境是5臺(tái)虛擬機(jī)，使用的均是CentOS6.6操作系統(tǒng)，虛擬機(jī)IP和hostname分別為：
192.168.63.171    node1.zhch
192.168.63.172    node2.zhch
192.168.63.173    node3.zhch
192.168.63.174    node4.zhch
192.168.63.175    node5.zhch

ssh免密碼、防火墻、JDK這里就不在贅述了。虛擬機(jī)的角色分配是：
 node1為主namenode1、主resource manager、zookeeper、journalnode
 node2為備namendoe1、zookeeper、journalnode
 node3為主namenode2、備resource manager、zookeeper、journalnode、datanode
 node4為備namenode2、datanode
 node5為datanode

步驟和 Namenode HA的安裝配置基本相同，需要先 安裝zookeeper集群，主要的不同在于core-site.xml、hdfs-site.xml、yarn-site.xml配置文件，其余文件的配置和Namenode HA安裝配置基本一致。

一、配置Hadoop

## 解壓
[yyl@node1 program]$ tar -zxf hadoop-2.5.2.tar.gz
## 創(chuàng)建文件夾
[yyl@node1 program]$ mkdir hadoop-2.5.2/name
[yyl@node1 program]$ mkdir hadoop-2.5.2/data
[yyl@node1 program]$ mkdir hadoop-2.5.2/journal
[yyl@node1 program]$ mkdir hadoop-2.5.2/tmp
## 配置hadoop-env.sh
[yyl@node1 program]$ cd hadoop-2.5.2/etc/hadoop/
[yyl@node1 hadoop]$ vim hadoop-env.sh
export JAVA_HOME=/usr/lib/java/jdk1.7.0_80
## 配置yarn-env.sh
[yyl@node1 hadoop]$ vim yarn-env.sh
export JAVA_HOME=/usr/lib/java/jdk1.7.0_80
## 配置slaves
[yyl@node1 hadoop]$ vim slaves
node3.zhch
node4.zhch
node5.zhch
## 配置mapred-site.xml
[yyl@node1 hadoop]$ cp mapred-site.xml.template mapred-site.xml
[yyl@node1 hadoop]$ vim mapred-site.xml
<configuration>
<property>
  <name>mapreduce.framework.name</name>
  <value>yarn</value>
</property>
<property> 
  <name>mapreduce.jobhistory.address</name> 
  <value>node2.zhch:10020</value> 
</property> 
<property> 
  <name>mapreduce.jobhistory.webapp.address</name> 
  <value>node2.zhch:19888</value> 
</property>
</configuration>

## 配置core-site.xml
[yyl@node1 hadoop]$ vim core-site.xml
<configuration>
<property>
  <name>fs.defaultFS</name>
  <value>hdfs://mycluster</value>
</property>
<property>
  <name>io.file.buffer.size</name>
  <value>131072</value>
</property>
<property>
  <name>hadoop.tmp.dir</name>
  <value>file:/home/yyl/program/hadoop-2.5.2/tmp</value>
</property>
<property>
  <name>hadoop.proxyuser.hduser.hosts</name>
  <value>*</value>
</property>
<property>
  <name>hadoop.proxyuser.hduser.groups</name>
  <value>*</value>
</property>
<property>
  <name>ha.zookeeper.quorum</name>
  <value>node1.zhch:2181,node2.zhch:2181,node3.zhch:2181</value>
</property>
<property>
  <name>ha.zookeeper.session-timeout.ms</name>
  <value>1000</value>
</property>
</configuration>

## 配置hdfs-site.xml
[yyl@node1 hadoop]$ vim hdfs-site.xml
<configuration>
<property>
  <name>dfs.namenode.name.dir</name>
  <value>file:/home/yyl/program/hadoop-2.5.2/name</value>
</property>
<property>
  <name>dfs.datanode.data.dir</name>
  <value>file:/home/yyl/program/hadoop-2.5.2/data</value>
</property>
<property>
  <name>dfs.replication</name>
  <value>1</value>
</property>
<property>
  <name>dfs.webhdfs.enabled</name>
  <value>true</value>
</property>
<property>
  <name>dfs.permissions</name>
  <value>false</value>
</property>
<property>
  <name>dfs.permissions.enabled</name>
  <value>false</value>
</property>
<property>
  <name>dfs.nameservices</name>
  <value>mycluster,yourcluster</value>
</property>
<property>
  <name>dfs.ha.namenodes.mycluster</name>
  <value>nn1,nn2</value>
</property>
<property>
  <name>dfs.namenode.rpc-address.mycluster.nn1</name>
  <value>node1.zhch:9000</value>
</property>
<property>
  <name>dfs.namenode.rpc-address.mycluster.nn2</name>
  <value>node2.zhch:9000</value>
</property>
<property>
  <name>dfs.namenode.servicerpc-address.mycluster.nn1</name>
  <value>node1.zhch:53310</value>
</property>
<property>
  <name>dfs.namenode.servicerpc-address.mycluster.nn2</name>
  <value>node2.zhch:53310</value>
</property>
<property>
  <name>dfs.namenode.http-address.mycluster.nn1</name>
  <value>node1.zhch:50070</value>
</property>
<property>
  <name>dfs.namenode.http-address.mycluster.nn2</name>
  <value>node2.zhch:50070</value>
</property>
<property>
  <name>dfs.ha.namenodes.yourcluster</name>
  <value>nn1,nn2</value>
</property>
<property>
  <name>dfs.namenode.rpc-address.yourcluster.nn1</name>
  <value>node3.zhch:9000</value>
</property>
<property>
  <name>dfs.namenode.rpc-address.yourcluster.nn2</name>
  <value>node4.zhch:9000</value>
</property>
<property>
  <name>dfs.namenode.servicerpc-address.yourcluster.nn1</name>
  <value>node3.zhch:53310</value>
</property>
<property>
  <name>dfs.namenode.servicerpc-address.yourcluster.nn2</name>
  <value>node4.zhch:53310</value>
</property>
<property>
  <name>dfs.namenode.http-address.yourcluster.nn1</name>
  <value>node3.zhch:50070</value>
</property>
<property>
  <name>dfs.namenode.http-address.yourcluster.nn2</name>
  <value>node4.zhch:50070</value>
</property>
<property>
  <name>dfs.namenode.shared.edits.dir</name>
  <value>qjournal://node1.zhch:8485;node2.zhch:8485;node3.zhch:8485/mycluster</value>
</property>
<property>
  <name>dfs.client.failover.proxy.provider.mycluster</name>
  <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<property>
  <name>dfs.client.failover.proxy.provider.yourcluster</name>
  <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<property>
  <name>dfs.ha.fencing.methods</name>
  <value>sshfence</value>
</property>
<property>
  <name>dfs.ha.fencing.ssh.private-key-files</name>
  <value>/home/yyl/.ssh/id_rsa</value>
</property>
<property>
  <name>dfs.ha.fencing.ssh.connect-timeout</name>
  <value>30000</value>
</property>
<property>
  <name>dfs.journalnode.edits.dir</name>
  <value>/home/yyl/program/hadoop-2.5.2/journal</value>
</property>
<property>
  <name>dfs.ha.automatic-failover.enabled.mycluster</name>
  <value>true</value>
</property>
<property>
  <name>dfs.ha.automatic-failover.enabled.yourcluster</name>
  <value>true</value>
</property>
<property>
  <name>ha.failover-controller.cli-check.rpc-timeout.ms</name>
  <value>60000</value>
</property>
<property>
  <name>ipc.client.connect.timeout</name>
  <value>60000</value>
</property>
<property>
  <name>dfs.image.transfer.bandwidthPerSec</name>
  <value>4194304</value>
</property>
</configuration>

## 配置yarn-site.xml
[yyl@node1 hadoop]$ vim yarn-site.xml
<configuration>
<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.resourcemanager.connect.retry-interval.ms</name>
  <value>2000</value>
</property>
<property>
  <name>yarn.resourcemanager.ha.enabled</name>
  <value>true</value>
</property>
<property>
  <name>yarn.resourcemanager.ha.automatic-failover.enabled</name>
  <value>true</value>
</property>
<property>
  <name>yarn.resourcemanager.ha.automatic-failover.embedded</name>
  <value>true</value>
</property>
<property>
  <name>yarn.resourcemanager.cluster-id</name>
  <value>yarn-cluster</value>
</property>
<property>
  <name>yarn.resourcemanager.ha.rm-ids</name>
  <value>rm1,rm2</value>
</property>
<property>
  <name>yarn.resourcemanager.ha.id</name>
  <value>rm1</value>
</property>
<property>
  <name>yarn.resourcemanager.scheduler.class</name>
  <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value>
</property>
<property>
  <name>yarn.resourcemanager.recovery.enabled</name>
  <value>true</value>
</property>
<property>
  <name>yarn.app.mapreduce.am.scheduler.connection.wait.interval-ms</name>
  <value>5000</value>
</property>
<property>
  <name>yarn.resourcemanager.store.class</name>
  <value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
</property>
<property>
  <name>yarn.resourcemanager.zk-address</name>
  <value>node1.zhch:2181,node2.zhch:2181,node3.zhch:2181</value>
</property>
<property>
  <name>yarn.resourcemanager.zk.state-store.address</name>
  <value>node1.zhch:2181,node2.zhch:2181,node3.zhch:2181</value>
</property>
<property>
  <name>yarn.resourcemanager.address.rm1</name>
  <value>node1.zhch:23140</value>
</property>
<property>
  <name>yarn.resourcemanager.address.rm2</name>
  <value>node3.zhch:23140</value>
</property>
<property>
  <name>yarn.resourcemanager.scheduler.address.rm1</name>
  <value>node1.zhch:23130</value>
</property>
<property>
  <name>yarn.resourcemanager.scheduler.address.rm2</name>
  <value>node3.zhch:23130</value>
</property>
<property>
  <name>yarn.resourcemanager.admin.address.rm1</name>
  <value>node1.zhch:23141</value>
</property>
<property>
  <name>yarn.resourcemanager.admin.address.rm2</name>
  <value>node3.zhch:23141</value>
</property>
<property>
  <name>yarn.resourcemanager.resource-tracker.address.rm1</name>
  <value>node1.zhch:23125</value>
</property>
<property>
  <name>yarn.resourcemanager.resource-tracker.address.rm2</name>
  <value>node3.zhch:23125</value>
</property>
<property>
  <name>yarn.resourcemanager.webapp.address.rm1</name>
  <value>node1.zhch:23188</value>
</property>
<property>
  <name>yarn.resourcemanager.webapp.address.rm2</name>
  <value>node3.zhch:23188</value>
</property>
<property>
  <name>yarn.resourcemanager.webapp.https.address.rm1</name>
  <value>node1.zhch:23189</value>
</property>
<property>
  <name>yarn.resourcemanager.webapp.https.address.rm2</name>
  <value>node3.zhch:23189</value>
</property>
</configuration>

## 分發(fā)到各個(gè)節(jié)點(diǎn)
[yyl@node1 hadoop]$ cd /home/yyl/program/
[yyl@node1 program]$ scp -rp hadoop-2.5.2 yyl@node2.zhch:/home/yyl/program/
[yyl@node1 program]$ scp -rp hadoop-2.5.2 yyl@node3.zhch:/home/yyl/program/
[yyl@node1 program]$ scp -rp hadoop-2.5.2 yyl@node4.zhch:/home/yyl/program/
[yyl@node1 program]$ scp -rp hadoop-2.5.2 yyl@node5.zhch:/home/yyl/program/
## 修改主namenode2(node3.zhch)和備namenode2(node4.zhch)的 hdfs-site.xml 配置文件中 dfs.namenode.shared.edits.dir 的值為 qjournal://node1.zhch:8485;node2.zhch:8485;node3.zhch:8485/yourcluster ，其余屬性值不變。
## 修改備resource manager(node3.zhch)的 yarn-site.xml 配置文件中 yarn.resourcemanager.ha.id 的值為 rm2 ，其余屬性值不變。

## 在各個(gè)節(jié)點(diǎn)上設(shè)置hadoop環(huán)境變量
[yyl@node1 ~]$ vim .bash_profile 
export HADOOP_PREFIX=/home/yyl/program/hadoop-2.5.2
export HADOOP_COMMON_HOME=$HADOOP_PREFIX
export HADOOP_HDFS_HOME=$HADOOP_PREFIX
export HADOOP_MAPRED_HOME=$HADOOP_PREFIX
export HADOOP_YARN_HOME=$HADOOP_PREFIX
export HADOOP_CONF_DIR=$HADOOP_PREFIX/etc/hadoop
export PATH=$PATH:$HADOOP_PREFIX/bin:$HADOOP_PREFIX/sbin

二、格式化與啟動(dòng) 

## 啟動(dòng)Zookeeper集群
## 在主namenode1(node1.zhch)、主namenode2(node3.zhch)上執(zhí)行命令： $HADOOP_HOME/bin/hdfs zkfc -formatZK
[yyl@node1 ~]$ hdfs zkfc -formatZK
[yyl@node3 ~]$ hdfs zkfc -formatZK
[yyl@node2 ~]$ zkCli.sh
[zk: localhost:2181(CONNECTED) 0] ls /
[hadoop-ha, zookeeper]
[zk: localhost:2181(CONNECTED) 1] ls /hadoop-ha
[mycluster, yourcluster]
## 在node1.zhch node2.zhch node3.zhch上啟動(dòng)journalnode：
[yyl@node1 ~]$ hadoop-daemon.sh start journalnode
starting journalnode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-journalnode-node1.zhch.out
[yyl@node1 ~]$ jps
1985 QuorumPeerMain
2222 Jps
2176 JournalNode
[yyl@node2 ~]$ hadoop-daemon.sh start journalnode
starting journalnode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-journalnode-node2.zhch.out
[yyl@node2 ~]$ jps
1783 Jps
1737 JournalNode
1638 QuorumPeerMain
[yyl@node3 ~]$ hadoop-daemon.sh start journalnode
starting journalnode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-journalnode-node3.zhch.out
[yyl@node3 ~]$ jps
1658 JournalNode
1495 QuorumPeerMain
1704 Jps

## 在主namenode1(node1.zhch)上格式化namenode
[yyl@node1 ~]$ hdfs namenode -format -clusterId c1
## 在主namenode1(node1.zhch)上啟動(dòng)namenode進(jìn)程
[yyl@node1 ~]$ hadoop-daemon.sh start namenode
starting namenode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-namenode-node1.zhch.out
[yyl@node1 ~]$ jps
2286 NameNode
1985 QuorumPeerMain
2369 Jps
2176 JournalNode
## 在備namenode1(node2.zhch)上同步元數(shù)據(jù)
[yyl@node2 ~]$ hdfs namenode -bootstrapStandby
## 在備namenode1(node2.zhch)上啟動(dòng)namenode進(jìn)程
[yyl@node2 ~]$ hadoop-daemon.sh start namenode
starting namenode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-namenode-node2.zhch.out
[yyl@node2 ~]$ jps
1923 Jps
1737 JournalNode
1638 QuorumPeerMain
1840 NameNode

## 在主namenode2(node3.zhch)上格式化namenode
[yyl@node3 ~]$ hdfs namenode -format -clusterId c1
## 在主namenode2(node3.zhch)上啟動(dòng)namenode進(jìn)程
[yyl@node3 ~]$ hadoop-daemon.sh start namenode
starting namenode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-namenode-node3.zhch.out
[yyl@node3 ~]$ jps
1658 JournalNode
1495 QuorumPeerMain
1767 NameNode
1850 Jps
## 在備namenode2(node4.zhch)上同步元數(shù)據(jù)
[yyl@node4 ~]$ hdfs namenode -bootstrapStandby
## 在備namenode2(node4.zhch)上啟動(dòng)namenode進(jìn)程
[yyl@node4 ~]$ hadoop-daemon.sh start namenode
starting namenode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-namenode-node4.zhch.out
[yyl@node4 ~]$ jps
1602 Jps
1519 NameNode

## 在所有的namenode上啟動(dòng)ZooKeeperFailoverController
[yyl@node1 ~]$ hadoop-daemon.sh start zkfc
starting zkfc, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-zkfc-node1.zhch.out
[yyl@node2 ~]$ hadoop-daemon.sh start zkfc
starting zkfc, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-zkfc-node2.zhch.out
[yyl@node3 ~]$ hadoop-daemon.sh start zkfc
starting zkfc, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-zkfc-node3.zhch.out
[yyl@node4 ~]$ hadoop-daemon.sh start zkfc
starting zkfc, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-zkfc-node4.zhch.out

## 啟動(dòng)DataNode
[yyl@node1 ~]$ hadoop-daemons.sh start datanode
node4.zhch: starting datanode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-datanode-node4.zhch.out
node5.zhch: starting datanode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-datanode-node5.zhch.out
node3.zhch: starting datanode, logging to /home/yyl/program/hadoop-2.5.2/logs/hadoop-yyl-datanode-node3.zhch.out
## 啟動(dòng)Yarn
[yyl@node1 ~]$ start-yarn.sh
starting yarn daemons
starting resourcemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-resourcemanager-node1.zhch.out
node3.zhch: starting nodemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-nodemanager-node3.zhch.out
node4.zhch: starting nodemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-nodemanager-node4.zhch.out
node5.zhch: starting nodemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-nodemanager-node5.zhch.out
## 在備resource manager(node3.zhch)上啟動(dòng)resource manager
[yyl@node3 ~]$ yarn-daemon.sh start resourcemanager
starting resourcemanager, logging to /home/yyl/program/hadoop-2.5.2/logs/yarn-yyl-resourcemanager-node3.zhch.out
## 查看resource manager狀態(tài)
[yyl@node1 ~]$ yarn rmadmin -getServiceState rm1
active
[yyl@node1 ~]$ yarn rmadmin -getServiceState rm2
standby

三、驗(yàn)證 

開兩個(gè)終端，都連接到主resource manager，在終端A中運(yùn)行jps命令查看resource manager進(jìn)程ID，在終端B中運(yùn)行MapReduce程序；然后再到終端A中kill掉resource manager進(jìn)程；最后觀察在主resource manager進(jìn)程掛掉后，MapReduce任務(wù)是否還能正常執(zhí)行完畢。

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