Hadoop HA on Yarn——集群配置

本文转载自 captainlucky 查看原文 2015/07/20 5129 oop/ 配置/ hadoop/ 集群

集群搭建

因为服务器数量有限，这里服务器开启的进程有点多：

机器名	安装软件	运行进程
hadoop001	Hadoop,Zookeeper	NameNode, DFSZKFailoverController, ResourceManager DataNode, NodeManager QuorumPeerMain JournalNode
hadoop002	Hadoop,Zookeeper	NameNode, DFSZKFailoverController, ResourceManager DataNode, NodeManager QuorumPeerMain JournalNode
hadoop003	Hadoop,Zookeeper	DataNode, NodeManager QuorumPeerMain

说明[2]：

在hadoop2.X中通常由两个NameNode组成，一个处于active状态，另一个处于standby状态。Active NameNode对外提供服务，而Standby NameNode则不对外提供服务，仅同步active namenode的状态，以便能够在它失败时快速进行切换。

hadoop2.0官方提供了两种HDFS HA的解决方案，一种是NFS，另一种是QJM（由cloudra提出，原理类似zookeeper）。这里我使用QJM完成。主备NameNode之间通过一组JournalNode同步元数据信息，一条数据只要成功写入多数JournalNode即认为写入成功。通常配置奇数个JournalNode

这里略去jdk，Hadoop，Zookeeper的安装过程和环境变量配置。

无密码登陆

这里要非常注意无密码登陆的配置：

ssh-keygen -t rsa

在~/.ssh/目录中生成两个文件id_rsa和id_rsa.pub

如果想从hadoop001免密码登录到hadoop002中要在hadoop001中执行

ssh-copy-id -i ~/.ssh/id_rsa.pub [用户名]@hadoop002

这里为了实现任何机器之间都可以免密码登陆，所以在hadoop001中再执行两遍上面的操作（把@后面的机器名分别改成hadoop001和hadoop003），最后把生成的authorized_keys复制所有的节点上

Hadoop配置

core-site.xml

<configuration>
<!--   -->
<property>
<name>fs.defaultFS</name>
<value>hdfs://appcluster</value>
</property>

<!-- 指定hadoop临时目录 -->
<property>
<name>hadoop.tmp.dir</name>
<value>/data/hadoop/storage/tmp</value>
</property>

<!-- 指定zookeeper地址 -->
<property>
<name>ha.zookeeper.quorum</name>
<value>hadoop001:2181,hadoop002:2181,hadoop003:2181</value>
</property>

<property>
<name>ha.zookeeper.session-timeout.ms</name>
<value>2000</value>
</property>
</configuration>

hdfs-site.xml

<configuration>
<!--指定namenode名称空间的存储地址-->
<property>
<name>dfs.namenode.name.dir</name>
<value>file:///data/hadoop/storage/hdfs/name</value>
</property>

<!--指定datanode数据存储地址-->
<property>
<name>dfs.datanode.data.dir</name>
<value>file:///data/hadoop/storage/hdfs/data</value>
</property>

<!--指定数据冗余份数-->
<property>
<name>dfs.replication</name>
<value>2</value>
</property>

<!--指定hdfs的nameservice为appcluster，需要和core-site.xml中的保持一致 -->
<property> 
<name>dfs.nameservices</name> 
<value>appcluster</value> 
</property>

<!-- appcluster下面有两个NameNode，分别是nn1，nn2 -->
<property> 
<name>dfs.ha.namenodes.appcluster</name> 
<value>nn1,nn2</value> 
</property> 

<!-- nn1的RPC通信地址 -->
<property> 
<name>dfs.namenode.rpc-address.appcluster.nn1</name> 
<value>hadoop001:8020</value> 
</property> 

<!-- nn2的RPC通信地址 -->
<property> 
<name>dfs.namenode.rpc-address.appcluster.nn2</name> 
<value>hadoop002:8020</value> 
</property> 

<!-- nn1的http通信地址 -->
<property> 
<name>dfs.namenode.http-address.appcluster.nn1</name> 
<value>hadoop001:50070</value> 
</property> 

<!-- nn2的http通信地址 -->
<property> 
<name>dfs.namenode.http-address.appcluster.nn2</name> 
<value>hadoop002:50070</value> 
</property> 

<!-- 指定NameNode的元数据在JournalNode上的存放位置 -->
<property> 
<name>dfs.namenode.shared.edits.dir</name> 
<value>qjournal://hadoop001:8485;hadoop002:8485;hadoop003:8485/appcluster</value> 
</property> 

<property> 
<name>dfs.ha.automatic-failover.enabled.appcluster</name> 
<value>true</value> 
</property> 

<!-- 配置失败自动切换实现方式 -->
<property> 
<name>dfs.client.failover.proxy.provider.appcluster</name> 
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value> 
</property> 

<!-- 配置隔离机制 -->
<property> 
<name>dfs.ha.fencing.methods</name> 
<value>sshfence</value> 
</property>

<!-- 使用隔离机制时需要ssh免密码登陆 -->
<property> 
<name>dfs.ha.fencing.ssh.private-key-files</name> 
<value>/home/[用户名]/.ssh/id_rsa</value> 
</property> 

<!-- -->
<property>
<name>dfs.journalnode.edits.dir</name>
<value>/data/hadoop/tmp/journal</value>
</property>
</configuration>

mapred-site.xml

<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>

<!-- 配置 MapReduce JobHistory Server 地址 ，默认端口10020 -->
<property>
<name>mapreduce.jobhistory.address</name>
<value>0.0.0.0:10020</value>
</property>

<!-- 配置 MapReduce JobHistory Server web ui 地址， 默认端口19888 -->
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>0.0.0.0:19888</value>
</property>
</configuration>

yarn-site.xml

<?xml version="1.0"?>
<configuration>
<!--rm失联后重新链接的时间-->
<property>
<name>yarn.resourcemanager.connect.retry-interval.ms</name>
<value>2000</value>
</property>

<!--开启resourcemanagerHA,默认为false-->
<property>
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>

<!--配置resourcemanager-->
<property>
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2</value>
</property>

<property>
<name>ha.zookeeper.quorum</name>
<value>hadoop001:2181,hadoop002:2181,hadoop003:2181</value>
</property>

<!--开启故障自动切换-->
<property>
<name>yarn.resourcemanager.ha.automatic-failover.enabled</name>
<value>true</value>
</property>

<property>
<name>yarn.resourcemanager.hostname.rm1</name>
<value>hadoop001</value>
</property>

<property>
<name>yarn.resourcemanager.hostname.rm2</name>
<value>hadoop002</value>
</property>

<!--
在hadoop001上配置rm1,在hadoop002上配置rm2,
注意：一般都喜欢把配置好的文件远程复制到其它机器上，但这个在YARN的另一个机器上一定要修改
-->
<property>
<name>yarn.resourcemanager.ha.id</name>
<value>rm1</value>
<description>If we want to launch more than one RM in single node,we need this configuration</description>
</property>

<!--开启自动恢复功能-->
<property>
<name>yarn.resourcemanager.recovery.enabled</name>
<value>true</value>
</property>

<!--配置与zookeeper的连接地址-->
<property>
<name>yarn.resourcemanager.zk-state-store.address</name>
<value>hadoop001:2181,hadoop002:2181,hadoop003:2181</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>hadoop001:2181,hadoop002:2181,hadoop003:2181</value>
</property>

<property>
<name>yarn.resourcemanager.cluster-id</name>
<value>appcluster-yarn</value>
</property>

<!--schelduler失联等待连接时间-->
<property>
<name>yarn.app.mapreduce.am.scheduler.connection.wait.interval-ms</name>
<value>5000</value>
</property>

<!--配置rm1-->
<property>
<name>yarn.resourcemanager.address.rm1</name>
<value>hadoop001:8032</value>
</property>

<property>
<name>yarn.resourcemanager.scheduler.address.rm1</name>
<value>hadoop001:8030</value>
</property>

<property>
<name>yarn.resourcemanager.webapp.address.rm1</name>
<value>hadoop001:8088</value>
</property>

<property>
<name>yarn.resourcemanager.resource-tracker.address.rm1</name>
<value>hadoop001:8031</value>
</property>

<property>
<name>yarn.resourcemanager.admin.address.rm1</name>
<value>hadoop001:8033</value>
</property>

<property>
<name>yarn.resourcemanager.ha.admin.address.rm1</name>
<value>hadoop001:23142</value>
</property>

<!--配置rm2-->
<property>
<name>yarn.resourcemanager.address.rm2</name>
<value>hadoop002:8032</value>
</property>

<property>
<name>yarn.resourcemanager.scheduler.address.rm2</name>
<value>hadoop002:8030</value>
</property>

<property>
<name>yarn.resourcemanager.webapp.address.rm2</name>
<value>hadoop002:8088</value>
</property>

<property>
<name>yarn.resourcemanager.resource-tracker.address.rm2</name>
<value>hadoop002:8031</value>
</property>

<property>
<name>yarn.resourcemanager.admin.address.rm2</name>
<value>hadoop002:8033</value>
</property>

<property>
<name>yarn.resourcemanager.ha.admin.address.rm2</name>
<value>hadoop002:23142</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.nodemanager.local-dirs</name>
<value>/data/hadoop/yarn/local</value>
</property>

<property>
<name>yarn.nodemanager.log-dirs</name>
<value>/data/hadoop/yarn/log</value>
</property>

<property>
<name>mapreduce.shuffle.port</name>
<value>23080</value>
</property>

<!--故障处理类-->
<property>
<name>yarn.client.failover-proxy-provider</name>
<value>org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider</value>
</property>

<property>
<name>yarn.resourcemanager.ha.automatic-failover.zk-base-path</name>
<value>/yarn-leader-election</value>
<description>Optionalsetting.Thedefaultvalueis/yarn-leader-election</description>
</property>
</configuration>

hadoop-env.sh & mapred-env.sh & yarn-env.sh

export JAVA_HOME=/usr/java/jdk1.7.0_60 
export CLASS_PATH=$JAVA_HOME/lib:$JAVA_HOME/jre/lib 
  
export HADOOP_HOME=/data/hadoop-2.6.0
export HADOOP_PID_DIR=/data/hadoop/pids 
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native 
export HADOOP_OPTS="$HADOOP_OPTS-Djava.library.path=$HADOOP_HOME/lib/native" 
  
export HADOOP_PREFIX=$HADOOP_HOME 
  
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=$HADOOP_HOME/etc/hadoop 
export HDFS_CONF_DIR=$HADOOP_HOME/etc/hadoop 
export YARN_CONF_DIR=$HADOOP_HOME/etc/hadoop 
  
export JAVA_LIBRARY_PATH=$HADOOP_HOME/lib/native 
  
export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin

参考文献

[1] hdfs-site.xml:http://www.21ops.com/front-tech/10744.html

[2] yarn-site.xml: http://www.aboutyun.com/thread-10572-1-1.html 评论也值得参考

仅参考这两篇配置后报错：

15/07/17 13:58:55 FATAL ha.ZKFailoverController: Automatic failover is not enabled for NameNode at hadoop001/**.**.**.**:8020. Please ensure that automatic failover is enabled in the configuration before running the ZK failover controller.

再参考

[3]http://www.cnblogs.com/meiyuanbao/p/3545929.html (没有做到Yarn的HA)

发现需要在hdfs-site.xml添加配置：

<property> 
<name>dfs.ha.automatic-failover.enabled.appcluster</name> 
<value>true</value> 
</property>

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Hadoop HA on Yarn——集群启动 hadoop集群搭建HDFS、HA、 YARN hadoop集群之YARN`s ResourceManager HA（三） Hadoop 及 YARN 的高可用（HA）配置 hadoop2.6.5 ha配置与yarn ha配置