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Resource Manager HA配置详解

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Release: 2016-06-07 16:39:21
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YARN中的资源管理器(Resource Manager)负责整个系统的资源管理和调度,并内部维护了各个应用程序的ApplictionMaster信息,NodeManager信息,资源使用信息等。在2.4版本之后,Hadoop Common同样提供了HA的功能,解决了这样一个基础服务的可靠性和容错性问题

YARN中的资源管理器(Resource Manager)负责整个系统的资源管理和调度,并内部维护了各个应用程序的ApplictionMaster信息,NodeManager信息,资源使用信息等。在2.4版本之后,Hadoop Common同样提供了HA的功能,解决了这样一个基础服务的可靠性和容错性问题。其架构如下:
rm-ha-overview
Overview of ResourceManager High Availability
RM HA与NN HA有诸多相同之处(NameNode HA配置详解 ):
(1). Active/Standby架构,同一时间只有一个RM处于活动状态(如上图所示)。
(2). 依赖zooKeeper实现。手动切换使用yarn rmadmin命令(类似hdfs haadmin命令),而自动故障转移使用ZKFailoverController。但不同的是,zkfc只作为RM中一个线程而非独立的守护进程来启动。
(3). 当存在多个RM时,客户端使用的yarn-site.xml需要指定RM的列表。 客户端, ApplicationMasters (AMs)和NodeManagers (NMs) 会以轮训的方式寻找活动状态的RM,也就是说AM
s和NMs需要自己提供容错机制。如果当前活动状态的RM挂掉了,那么会继续使用轮训的方式找到新的RM。这种逻辑的实现需要在yarn.client.failover-proxy-provider中指定使用的类:org.apache.hadoop.yarn.client.RMFailoverProxyProvider
此外,新的RM可以恢复之前RM的状态(详见ResourceManger Restart )。当启动RM Restart,重启后的RM就加载之前活动RM的状态信息并继续之前RM的操作,这样应用程序定期执行检查点操作,就可以避免工作内容的丢失。在Active/standby的RM中,活动RM的状态数据需要active和standby都能访问,使用共享文件系统方法(FileSystemRMStateStore )或者zooKeeper方法(ZKRMStateStore)。后者在同一时间只允许一个RM有写入权限。

一个常见的YARN RM HA配置如下:

	yarn.resourcemanager.ha.enabled
	true
	yarn.resourcemanager.ha.rm-ids
	rm1,rm2
	yarn.resourcemanager.hostname.rm1
	debugo01
	yarn.resourcemanager.hostname.rm2
	debugo02
	yarn.resourcemanager.recovery.enabled
	true
	yarn.resourcemanager.store.class
        org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore
	yarn.resourcemanager.zk-address
        debugo01:2181,debugo02:2181,debugo03:2181
        For multiple zk services, separate them with comma
	yarn.resourcemanager.cluster-id
	yarn-ha
	yarn.resourcemanager.ha.automatic-failover.enabled
	true
	Enable automatic failover; By default, it is enabled only when HA is enabled.
  yarn.resourcemanager.ha.automatic-failover.zk-base-path
  /yarn-leader-election
Optional setting. The default value is /yarn-leader-election
	yarn.client.failover-proxy-provider
	org.apache.hadoop.yarn.client.RMFailoverProxyProvider
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同时,yarn RM服务监听地址的设置要修改成下面的方式:

yarn.resourcemanager.address.rm1
debugo01:8132
yarn.resourcemanager.address.rm2
debugo02:8132
yarn.resourcemanager.scheduler.address.rm1
debugo01:8130
yarn.resourcemanager.scheduler.address.rm2
debugo02:8130
yarn.resourcemanager.resource-tracker.address.rm1
debugo01:8131
yarn.resourcemanager.resource-tracker.address.rm2
debugo02:8131 yarn.resourcemanager.webapp.address.rm1
debugo01:8188
yarn.resourcemanager.webapp.address.rm2
debugo02:8188

启动RM

start-yarn.sh
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在standby的节点单独启动RM(也可使用start-yarn.sh脚本)

检查状态:

$ yarn rmadmin -getServiceState rm1
active
$ yarn rmadmin -getServiceState rm2
standby
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访问rm2节点的nodemanager会提示
This is standby RM. Redirecting to the current active RM: http://debugo01:8188/cluster/apps
下面KILL掉rm1的resourcemanager

$ yarn rmadmin -getServiceState rm2
active
?$  yarn rmadmin -getServiceState rm1
14/09/14 03:08:23 INFO ipc.Client: Retrying connect to server: debugo01/192.168.46.201:8033. Already tried 0 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=1, sleepTime=1000 MILLISECONDS)
Operation failed: Call From debugo01/192.168.46.201 to debugo01:8033 failed on connection exception: java.net.ConnectException: Connection refused; For more details see:  http://wiki.apache.org/hadoop/ConnectionRefused
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参考

http://hadoop.apache.org/docs/r2.4.1/hadoop-yarn/hadoop-yarn-site/ResourceManagerHA.html

http://dongxicheng.org/mapreduce-nextgen/hadoop-yarn-ha-in-cdh5/

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