Hadoop之YARN命令
本帖最后由 丫丫 于 2015-8-25 20:51 编辑问题导读
1.对于Hadoop集群用户有哪些有用的命令？
2.打印需要得到Hadoop的jar和所需要的lib包路径使用的什么命令？
3.对hadoop集群的管理员有哪些很有用的命令？
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概述
YARN命令是调用bin/yarn脚本文件，如果运行yarn脚本没有带任何参数，则会打印yarn所有命令的描述。
使用: yarn [--config confdir] COMMAND [--loglevel loglevel]
YARN有一个参数解析框架，采用解析泛型参数以及运行类。
命令参数 描述
--config confdir 指定一个默认的配置文件目录，默认值是： ${HADOOP_PREFIX}/conf.
--loglevel loglevel 重载Log级别。有效的日志级别包含：FATAL, ERROR, WARN, INFO, DEBUG, and TRACE。默认是INFO。
GENERIC_OPTIONS YARN支持表A的通用命令项。
COMMAND COMMAND_OPTIONS YARN分为用户命令和管理员命令。
表A：
通用项Description
-archives <comma separated list of archives>用逗号分隔计算中未归档的文件。 仅仅针对JOB。
-conf <configuration file>制定应用程序的配置文件。
-D <property>=<value>使用给定的属性值。
-files <comma separated list of files>用逗号分隔的文件,拷贝到Map reduce机器，仅仅针对JOB
-jt <local> or <resourcemanager:port>指定一个ResourceManager. 仅仅针对JOB。
-libjars <comma seperated list of jars>将用逗号分隔的jar路径包含到classpath中去，仅仅针对JOB。
用户命令：
对于Hadoop集群用户很有用的命令：
application
使用: yarn application
命令选项描述
-appStates <States>使用-list命令，基于应用程序的状态来过滤应用程序。如果应用程序的状态有多个，用逗号分隔。 有效的应用程序状态包含
如下： ALL, NEW, NEW_SAVING, SUBMITTED, ACCEPTED, RUNNING, FINISHED, FAILED, KILLED
-appTypes <Types>使用-list命令，基于应用程序类型来过滤应用程序。如果应用程序的类型有多个，用逗号分隔。
-list从RM返回的应用程序列表，使用-appTypes参数，支持基于应用程序类型的过滤，使用-appStates参数，支持对应用程序状态的过滤。
-kill <ApplicationId>kill掉指定的应用程序。
-status <ApplicationId>打印应用程序的状态。
示例1：
[*]
$ ./yarn application -list -appStates ACCEPTED
15/08/10 11:48:43 INFO client.RMProxy: Connecting to ResourceManager at hadoop1/10.0.1.41:8032
Total number of applications (application-types: [] and states: ):1
Application-Id Application-Name Application-Type User Queue State Final-State Progress Tracking-URL
application_1438998625140_1703MAC_STATUS MAPREDUCE hduser default ACCEPTED UNDEFINED 0% N/A
示例2：
[*]
$ ./yarn application -list
15/08/10 11:43:01 INFO client.RMProxy: Connecting to ResourceManager at hadoop1/10.0.1.41:8032
Total number of applications (application-types: [] and states: ):1
Application-Id Application-Name Application-TypeUser Queue State Final-State Progress Tracking-URL
application_1438998625140_1701 MAC_STATUS MAPREDUCE hduser default ACCEPTED UNDEFINED 0% N/A
示例3：
[*]
$ ./yarn application -kill application_1438998625140_1705
15/08/10 11:57:41 INFO client.RMProxy: Connecting to ResourceManager at hadoop1/10.0.1.41:8032
Killing application application_1438998625140_1705
15/08/10 11:57:42 INFO impl.YarnClientImpl: Killed application application_1438998625140_1705
applicationattempt
使用: yarn applicationattempt
命令选项描述
-help帮助
-list <ApplicationId>获取到应用程序尝试的列表，其返回值ApplicationAttempt-Id 等于 <Application Attempt Id>
-status <Application Attempt Id>打印应用程序尝试的状态。
打印应用程序尝试的报告。
示例1：
[*]
$ yarn applicationattempt -list application_1437364567082_0106
15/08/10 20:58:28 INFO client.RMProxy: Connecting to ResourceManager at hadoopcluster79/10.0.1.79:8032
Total number of application attempts :1
ApplicationAttempt-Id State AM-Container-Id Tracking-URL
appattempt_1437364567082_0106_000001 RUNNINGcontainer_1437364567082_0106_01_000001 http://hadoopcluster79:8088/proxy/application_1437364567082_0106/
示例2：
[*]
$ yarn applicationattempt -list application_1437364567082_0106
15/08/10 20:58:28 INFO client.RMProxy: Connecting to ResourceManager at hadoopcluster79/10.0.1.79:8032
Total number of application attempts :1
ApplicationAttempt-Id State AM-Container-Id Tracking-URL
appattempt_1437364567082_0106_000001 RUNNINGcontainer_1437364567082_0106_01_000001 http://hadoopcluster79:8088/proxy/application_1437364567082_0106/
classpath使用: yarn classpath
打印需要得到Hadoop的jar和所需要的lib包路径
[*]
$ yarn classpath
/home/hadoop/apache/hadoop-2.4.1/etc/hadoop:/home/hadoop/apache/hadoop-2.4.1/etc/hadoop:/home/hadoop/apache/hadoop-2.4.1/etc/hadoop:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/common/lib/*:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/common/*:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/hdfs:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/hdfs/lib/*:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/hdfs/*:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/yarn/lib/*:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/yarn/*:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/mapreduce/lib/*:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/mapreduce/*:/home/hadoop/apache/hadoop-2.4.1/contrib/capacity-scheduler/*.jar:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/yarn/*:/home/hadoop/apache/hadoop-2.4.1/share/hadoop/yarn/lib/*
container
使用: yarn container
命令选项描述
-help帮助
-list <Application Attempt Id>应用程序尝试的Containers列表
-status <ContainerId>打印Container的状态
打印container(s)的报告
示例1：
$ yarn container -list appattempt_1437364567082_0106_01
15/08/10 20:45:45 INFO client.RMProxy: Connecting to ResourceManager at hadoopcluster79/10.0.1.79:8032
Total number of containers :25
Container-Id Start Time Finish Time State Host LOG-URL
container_1437364567082_0106_01_000028 1439210458659 0 RUNNING hadoopcluster83:37140 //hadoopcluster83:8042/node/containerlogs/container_1437364567082_0106_01_000028/hadoop
container_1437364567082_0106_01_000016 1439210314436 0 RUNNING hadoopcluster84:43818 //hadoopcluster84:8042/node/containerlogs/container_1437364567082_0106_01_000016/hadoop
container_1437364567082_0106_01_000019 1439210338598 0 RUNNING hadoopcluster83:37140 //hadoopcluster83:8042/node/containerlogs/container_1437364567082_0106_01_000019/hadoop
container_1437364567082_0106_01_000004 1439210314130 0 RUNNING hadoopcluster82:48622 //hadoopcluster82:8042/node/containerlogs/container_1437364567082_0106_01_000004/hadoop
container_1437364567082_0106_01_000008 1439210314130 0 RUNNING hadoopcluster82:48622 //hadoopcluster82:8042/node/containerlogs/container_1437364567082_0106_01_000008/hadoop
container_1437364567082_0106_01_000031 1439210718604 0 RUNNING hadoopcluster83:37140 //hadoopcluster83:8042/node/containerlogs/container_1437364567082_0106_01_000031/hadoop
container_1437364567082_0106_01_000020 1439210339601 0 RUNNING hadoopcluster83:37140 //hadoopcluster83:8042/node/containerlogs/container_1437364567082_0106_01_000020/hadoop
container_1437364567082_0106_01_000005 1439210314130 0 RUNNING hadoopcluster82:48622 //hadoopcluster82:8042/node/containerlogs/container_1437364567082_0106_01_000005/hadoop
container_1437364567082_0106_01_000013 1439210314435 0 RUNNING hadoopcluster84:43818 //hadoopcluster84:8042/node/containerlogs/container_1437364567082_0106_01_000013/hadoop
container_1437364567082_0106_01_000022 1439210368679 0 RUNNING hadoopcluster84:43818 //hadoopcluster84:8042/node/containerlogs/container_1437364567082_0106_01_000022/hadoop
container_1437364567082_0106_01_000021 1439210353626 0 RUNNING hadoopcluster83:37140 //hadoopcluster83:8042/node/containerlogs/container_1437364567082_0106_01_000021/hadoop
container_1437364567082_0106_01_000014 1439210314435 0 RUNNING hadoopcluster84:43818 //hadoopcluster84:8042/node/containerlogs/container_1437364567082_0106_01_000014/hadoop
container_1437364567082_0106_01_000029 1439210473726 0 RUNNING hadoopcluster80:42366 //hadoopcluster80:8042/node/containerlogs/container_1437364567082_0106_01_000029/hadoop
container_1437364567082_0106_01_000006 1439210314130 0 RUNNING hadoopcluster82:48622 //hadoopcluster82:8042/node/containerlogs/container_1437364567082_0106_01_000006/hadoop
container_1437364567082_0106_01_000003 1439210314129 0 RUNNING hadoopcluster82:48622 //hadoopcluster82:8042/node/containerlogs/container_1437364567082_0106_01_000003/hadoop
container_1437364567082_0106_01_000015 1439210314436 0 RUNNING hadoopcluster84:43818 //hadoopcluster84:8042/node/containerlogs/container_1437364567082_0106_01_000015/hadoop
container_1437364567082_0106_01_000009 1439210314130 0 RUNNING hadoopcluster82:48622 //hadoopcluster82:8042/node/containerlogs/container_1437364567082_0106_01_000009/hadoop
container_1437364567082_0106_01_000030 1439210708467 0 RUNNING hadoopcluster83:37140 //hadoopcluster83:8042/node/containerlogs/container_1437364567082_0106_01_000030/hadoop
container_1437364567082_0106_01_000012 1439210314435 0 RUNNING hadoopcluster84:43818 //hadoopcluster84:8042/node/containerlogs/container_1437364567082_0106_01_000012/hadoop
container_1437364567082_0106_01_000027 1439210444354 0 RUNNING hadoopcluster84:43818 //hadoopcluster84:8042/node/containerlogs/container_1437364567082_0106_01_000027/hadoop
container_1437364567082_0106_01_000026 1439210428514 0 RUNNING hadoopcluster83:37140 //hadoopcluster83:8042/node/containerlogs/container_1437364567082_0106_01_000026/hadoop
container_1437364567082_0106_01_000017 1439210314436 0 RUNNING hadoopcluster84:43818 //hadoopcluster84:8042/node/containerlogs/container_1437364567082_0106_01_000017/hadoop
container_1437364567082_0106_01_000001 1439210306902 0 RUNNING hadoopcluster80:42366 //hadoopcluster80:8042/node/containerlogs/container_1437364567082_0106_01_000001/hadoop
container_1437364567082_0106_01_000002 1439210314129 0 RUNNING hadoopcluster82:48622 //hadoopcluster82:8042/node/containerlogs/container_1437364567082_0106_01_000002/hadoop
container_1437364567082_0106_01_000025 1439210414171 0 RUNNING hadoopcluster83:37140 //hadoopcluster83:8042/node/containerlogs/container_1437364567082_0106_01_000025/hadoop
示例2：
$ yarn container -status container_1437364567082_0105_01_000020
15/08/10 20:28:00 INFO client.RMProxy: Connecting to ResourceManager at hadoopcluster79/10.0.1.79:8032
Container Report :
Container-Id : container_1437364567082_0105_01_000020
Start-Time : 1439208779842
Finish-Time : 0
State : RUNNING
LOG-URL : //hadoopcluster83:8042/node/containerlogs/container_1437364567082_0105_01_000020/hadoop
Host : hadoopcluster83:37140
Diagnostics : null
jar使用: yarn jar <jar> args...
运行jar文件，用户可以将写好的YARN代码打包成jar文件，用这个命令去运行它。
logs
使用: yarn logs -applicationId <application ID>
注：应用程序没有完成，该命令是不能打印日志的。
命令选项描述
-applicationId <application ID>指定应用程序ID，应用程序的ID可以在yarn.resourcemanager.webapp.address配置的路径查看（即：ID）
-appOwner <AppOwner>应用的所有者（如果没有指定就是当前用户）应用程序的ID可以在yarn.resourcemanager.webapp.address配置的路径查看（即：User）
-containerId <ContainerId>Container Id
-help帮助
-nodeAddress <NodeAddress>节点地址的格式：nodename:port （端口是配置文件中:yarn.nodemanager.webapp.address参数指定）
转存container的日志。
示例：
$ yarn logs -applicationId application_1437364567082_0104-appOwner hadoop
15/08/10 17:59:19 INFO client.RMProxy: Connecting to ResourceManager at hadoopcluster79/10.0.1.79:8032
Container: container_1437364567082_0104_01_000003 on hadoopcluster82_48622
============================================================================
LogType: stderr
LogLength: 0
Log Contents:
LogType: stdout
LogLength: 0
Log Contents:
LogType: syslog
LogLength: 3673
Log Contents:
2015-08-10 17:24:01,565 WARN org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;Ignoring.
2015-08-10 17:24:01,580 WARN org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;Ignoring.
。。。。。。此处省略N万个字符
// 下面的命令，根据APP的所有者查看LOG日志，因为application_1437364567082_0104任务我是用hadoop用户启动的，所以打印的是如下信息：
$ yarn logs -applicationId application_1437364567082_0104-appOwner root
15/08/10 17:59:25 INFO client.RMProxy: Connecting to ResourceManager at hadoopcluster79/10.0.1.79:8032
Logs not available at /tmp/logs/root/logs/application_1437364567082_0104
Log aggregation has not completed or is not enabled.
node
使用: yarn node
命令选项描述
-all所有的节点，不管是什么状态的。
-list列出所有RUNNING状态的节点。支持-states选项过滤指定的状态，节点的状态包
含：NEW，RUNNING，UNHEALTHY，DECOMMISSIONED，LOST，REBOOTED。支持--all显示所有的节点。
-states <States>和-list配合使用，用逗号分隔节点状态，只显示这些状态的节点信息。
-status <NodeId>打印指定节点的状态。
示例1：
$ ./yarn node -list -all
15/08/10 17:34:17 INFO client.RMProxy: Connecting to ResourceManager at hadoopcluster79/10.0.1.79:8032
Total Nodes:4
Node-Id Node-State Node-Http-Address Number-of-Running-Containers
hadoopcluster82:48622 RUNNING hadoopcluster82:8042 0
hadoopcluster84:43818 RUNNING hadoopcluster84:8042 0
hadoopcluster83:37140 RUNNING hadoopcluster83:8042 0
hadoopcluster80:42366 RUNNING hadoopcluster80:8042 0
示例2：
[*]
$ ./yarn node -list -states RUNNING
15/08/10 17:39:55 INFO client.RMProxy: Connecting to ResourceManager at hadoopcluster79/10.0.1.79:8032
Total Nodes:4
Node-Id Node-State Node-Http-Address Number-of-Running-Containers
hadoopcluster82:48622 RUNNING hadoopcluster82:8042 0
hadoopcluster84:43818 RUNNING hadoopcluster84:8042 0
hadoopcluster83:37140 RUNNING hadoopcluster83:8042 0
hadoopcluster80:42366 RUNNING hadoopcluster80:8042 0
示例3：
$ ./yarn node -status hadoopcluster82:48622
15/08/10 17:52:52 INFO client.RMProxy: Connecting to ResourceManager at hadoopcluster79/10.0.1.79:8032
Node Report :
Node-Id : hadoopcluster82:48622
Rack : /default-rack
Node-State : RUNNING
Node-Http-Address : hadoopcluster82:8042
Last-Health-Update : 星期一 10/八月/15 05:52:09:601CST
Health-Report :
Containers : 0
Memory-Used : 0MB
Memory-Capacity : 10240MB
CPU-Used : 0 vcores
CPU-Capacity : 8 vcores
打印节点的报告。
queue
使用: yarn queue
命令选项描述
-help帮助
-status <QueueName>打印队列的状态
打印队列信息。
version
使用: yarn version
打印hadoop的版本。
管理员命令：
下列这些命令对hadoop集群的管理员是非常有用的。
daemonlog使用:
yarn daemonlog -getlevel <host:httpport> <classname> yarn daemonlog -setlevel <host:httpport> <classname> <level>
参数选项描述
-getlevel <host:httpport> <classname>打印运行在<host:port>的守护进程的日志级别。这个命令内部会连接http://<host:port>/logLevel?log=<name>
-setlevel <host:httpport> <classname> <level>设置运行在<host:port>的守护进程的日志级别。这个命令内部会连接http://<host:port>/logLevel?log=<name>
针对指定的守护进程，获取/设置日志级别.
示例1：
# hadoop daemonlog -getlevel hadoopcluster82:50075 org.apache.hadoop.hdfs.server.datanode.DataNode
Connecting to http://hadoopcluster82:50075/logLevel?log=org.apache.hadoop.hdfs.server.datanode.DataNode
Submitted Log Name: org.apache.hadoop.hdfs.server.datanode.DataNode
Log Class: org.apache.commons.logging.impl.Log4JLogger
Effective level: INFO
# yarn daemonlog -getlevel hadoopcluster79:8088 org.apache.hadoop.yarn.server.resourcemanager.rmapp.RMAppImpl
Connecting to http://hadoopcluster79:8088/logLevel?log=org.apache.hadoop.yarn.server.resourcemanager.rmapp.RMAppImpl
Submitted Log Name: org.apache.hadoop.yarn.server.resourcemanager.rmapp.RMAppImpl
Log Class: org.apache.commons.logging.impl.Log4JLogger
Effective level: INFO
# yarn daemonlog -getlevel hadoopcluster78:19888 org.apache.hadoop.mapreduce.v2.hs.JobHistory
Connecting to http://hadoopcluster78:19888/logLevel?log=org.apache.hadoop.mapreduce.v2.hs.JobHistory
Submitted Log Name: org.apache.hadoop.mapreduce.v2.hs.JobHistory
Log Class: org.apache.commons.logging.impl.Log4JLogger
Effective level: INFO
nodemanager
使用: yarn nodemanager
启动NodeManager
proxyserver
使用: yarn proxyserver
启动web proxy server
resourcemanager
使用: yarn resourcemanager [-format-state-store]
参数选项描述
-format-state-storeRMStateStore的格式. 如果过去的应用程序不再需要，则清理RMStateStore， RMStateStore仅仅在ResourceManager没有运行的时候，才运行RMStateStore
启动ResourceManager
rmadmin
使用:
yarn rmadmin [-refreshQueues] [-refreshNodes] [-refreshUserToGroupsMapping] [-refreshSuperUserGroupsConfiguration] [-refreshAdminAcls] [-refreshServiceAcl] [-getGroups ] [-transitionToActive [--forceactive] [--forcemanual] <serviceId>] [-transitionToStandby [--forcemanual] <serviceId>] [-failover [--forcefence] [--forceactive] <serviceId1> <serviceId2>] [-getServiceState <serviceId>] [-checkHealth <serviceId>] [-help ]
参数选项描述
-refreshQueues重载队列的ACL，状态和调度器特定的属性，ResourceManager将重载mapred-queues配置文件
-refreshNodes动态刷新dfs.hosts和dfs.hosts.exclude配置，无需重启NameNode。
dfs.hosts：列出了允许连入NameNode的datanode清单（IP或者机器名）
dfs.hosts.exclude：列出了禁止连入NameNode的datanode清单（IP或者机器名）
重新读取hosts和exclude文件，更新允许连到Namenode的或那些需要退出或入编的Datanode的集合。
-refreshUserToGroupsMappings刷新用户到组的映射。
-refreshSuperUserGroupsConfiguration刷新用户组的配置
-refreshAdminAcls刷新ResourceManager的ACL管理
-refreshServiceAclResourceManager重载服务级别的授权文件。
-getGroups 获取指定用户所属的组。
-transitionToActive [–forceactive] [–forcemanual] <serviceId>尝试将目标服务转为 Active 状态。如果使用了–forceactive选项，不需要核对非Active节点。如果采用了自动故障转移，这个命令不能使用。虽然你可以重写–forcemanual选项，你需要谨慎。
-transitionToStandby [–forcemanual] <serviceId>将服务转为 Standby 状态. 如果采用了自动故障转移，这个命令不能使用。虽然你可以重写–forcemanual选项，你需要谨慎。
-failover [–forceactive] <serviceId1> <serviceId2>启动从serviceId1 到 serviceId2的故障转移。如果使用了-forceactive选项，即使服务没有准备，也会尝试故障转移到目标服务。如果采用了自动故障转移，这个命令不能使用。
-getServiceState <serviceId>返回服务的状态。（注：ResourceManager不是HA的时候，时不能运行该命令的）
-checkHealth <serviceId>请求服务器执行健康检查，如果检查失败，RMAdmin将用一个非零标示退出。（注：ResourceManager不是HA的时候，时不能运行该命令的）
-help 显示指定命令的帮助，如果没有指定，则显示命令的帮助。
scmadmin使用: yarn scmadmin
参数选项描述
-helpHelp
-runCleanerTaskRuns the cleaner task
Runs Shared Cache Manager admin client
sharedcachemanager
使用: yarn sharedcachemanager
启动Shared Cache Manager
timelineserver
之前yarn运行框架只有Job history server，这是hadoop2.4版本之后加的通用Job History Server，命令为Application Timeline Server，详情请看：The YARN Timeline Server
使用: yarn timelineserver
启动TimeLineServer
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