简介: 最新的Cloudera CDH5.0.0 beta版本已经支持RM的HA, 笔者为此简单验证了RM HA的功能. 后续将继续分析其HA的原理,以及其与社区RM HA的区别.

集群部属与RM failover功能性验证

1. 硬件准备

   四台机器, bj1, bj3, bj4, bj5 准备好相应的环境(包括ssh互通, java环境).

   角色说明, bj1为rm1, bj3为rm2, bj4和bj4为slave.

   Zookeeper部属在bj1上.

2. Hadoop版本准备http://archive.cloudera.com/cdh5/cdh/5/ 下载相应的CDH5版本hadoop-2.2.0-cdh5.0.0-beta-1.tar.gz(包括部属包和原代码),然后部属到每台slave中.
3. Zookeeper安装在bj1, 下载最新Zookeeper, 解压后配置 conf/zoo.cfg文件, 然后启动.

   [yuling.sh@v125050024 ~]$ cd zookeeper-3.4.3/

   [yuling.sh@v125050024 zookeeper-3.4.3]$ cp conf/zoo_sample.cfg conf/zoo.cfg

   [yuling.sh@v125050024 zookeeper-3.4.3]$ bin/zkServer.sh start

4. 配置文件准备,见附录, 也可以参考(https://www.cloudera.com/content/cloudera-content/cloudera-docs/CDH5/latest/CDH5-High-Availability-Guide/cdh5hag_cfg_RM_HA.html).
5. 首先启动HDFS

   bin/hadoop namenode –format

   sbin/start-dfs.sh

   网页上查看Namenode:　 http://bj1:50070/dfshealth.jsp

6. 启动Yarn

   rm1上启动resourcemanager

   sbin/yarn-daemon.sh start resourcemanager

   rm2上启动resourcemanager

   sbin/yarn-daemon.sh start resourcemanager

   slave启动NodeManager

   sbin/yarn-daemons.sh start nodemanager

   查看rm1和mr2的网页. http://bj1:23188/cluster 和 http://bj3:23188/cluster 其中active RM的网页可以查看, stanby的RM无法查看网页.

   注: 如果yarn.resourcemanager.ha.automatic-failover.enabled设置为false, 则需要手动设置其中一个RM为active,负责两个RM都为standby.

7. 提交一个sleep作业测试

   bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.2.0-cdh5.0.0-beta-1.jar sleep -m 1000

   然后可以到网页上查看作业运行情况

8. 在作业运行过程中kill掉active的RM进程, 这时候打开standby RM的网页,可以看到刚才提交的作业继续运行.

   [yuling.sh@v125050024 hadoop-2.2.0-cdh5.0.0-beta-1]$ jps

   31333 ResourceManager

   31671 Jps

   29502 NameNode

   25375 QuorumPeerMain

   [yuling.sh@v125050024 hadoop-2.2.0-cdh5.0.0-beta-1]$ kill 31333

结论: 上述几步简单验证了Cloudera RM Auto Failover的功能。

附录1

配置参考

1. etc/hadoop/slaves

   bj4

   bj5

2. etc/hadoop/hdfs-site.xml

<property>

<name>fs.default.name</name>

<value>hdfs://bj1:9000</value>

</property>

1. etc/hadoop/mapred-site.xml

   <property>

   <name>mapreduce.framework.name</name>

   <value>yarn</value>

   </property>

2. etc/hadoop/yarn-site.xml配置如下

除了yarn.resourcemanager.ha.id需要稍作修改外, 其它配置都可以一样.

<!-- Resource Manager Configs -->

<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.rm-ids</name>

<value>rm1,rm2</value>

</property>

<property>

<name>yarn.resourcemanager.ha.id</name>

<value>rm2</value> <!—注释, rm1上配置为rm1, rm2上配置rm2-->

</property>

<property>

<name>yarn.resourcemanager.store.class</name>

<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>

</property>

<property>

<name>yarn.resourcemanager.zk.state-store.address</name>

<value>bj1:2181</value>

</property>

<property>

<name>ha.zookeeper.quorum</name>

<value>bj1:2181</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>

<!-- RM1 configs -->

<property>

<name>yarn.resourcemanager.address.rm1</name>

<value>bj1:23140</value>

</property>

<property>

<name>yarn.resourcemanager.scheduler.address.rm1</name>

<value>bj1:23130</value>

</property>

<property>

<name>yarn.resourcemanager.webapp.address.rm1</name>

<value>bj1:23188</value>

</property>

<property>

<name>yarn.resourcemanager.resource-tracker.address.rm1</name>

<value>bj1:23125</value>

</property>

<property>

<name>yarn.resourcemanager.admin.address.rm1</name>

<value>bj1:23141</value>

</property>

<property>

<name>yarn.resourcemanager.ha.admin.address.rm1</name>

<value>bj1:23142</value>

</property>

<!-- RM2 configs -->

<property>

<name>yarn.resourcemanager.address.rm2</name>

<value>bj3:23140</value>

</property>

<property>

<name>yarn.resourcemanager.scheduler.address.rm2</name>

<value>bj3:23130</value>

</property>

<property>

<name>yarn.resourcemanager.webapp.address.rm2</name>

<value>bj3:23188</value>

</property>

<property>

<name>yarn.resourcemanager.resource-tracker.address.rm2</name>

<value>bj3:23125</value>

</property>

<property>

<name>yarn.resourcemanager.admin.address.rm2</name>

<value>bj3:23141</value>

</property>

<property>

<name>yarn.resourcemanager.ha.admin.address.rm2</name>

<value>bj3:23142</value>

</property>

<!-- Node Manager Configs -->

<property>

<description>Address where the localizer IPC is.</description>

<name>yarn.nodemanager.localizer.address</name>

<value>0.0.0.0:23344</value>

</property>

<property>

<description>NM Webapp address.</description>

<name>yarn.nodemanager.webapp.address</name>

<value>0.0.0.0:23999</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>/tmp/pseudo-dist/yarn/local</value>

</property>

<property>

<name>yarn.nodemanager.log-dirs</name>

<value>/tmp/pseudo-dist/yarn/log</value>

</property>

<property>

<name>mapreduce.shuffle.port</name>

<value>23080</value>

</property>