hadoop job yarn 命令

hadoop命令行 与job相关的：
命令行工具 • 
1.查看 Job 信息：
hadoop job -list 
2.杀掉 Job： 
hadoop  job –kill  job_id
3.指定路径下查看历史日志汇总：
hadoop job -history output-dir 
4.作业的更多细节： 
hadoop job -history all output-dir 
5.打印map和reduce完成百分比和所有计数器：
hadoop job –status job_id 
6.杀死任务。被杀死的任务不会不利于失败尝试：
hadoop jab -kill-task  
7.使任务失败。被失败的任务会对失败尝试不利：

Hadoop job  -fail-task

YARN命令行：

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] [GENERIC_OPTIONS] [COMMAND_OPTIONS]
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	用逗号分隔计算中未归档的文件。 仅仅针对JOB。
-conf	制定应用程序的配置文件。
-D =	使用给定的属性值。
-files	用逗号分隔的文件,拷贝到Map reduce机器，仅仅针对JOB
-jt or	指定一个ResourceManager. 仅仅针对JOB。
-libjars	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 [options]

命令选项	描述
-appStates	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	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	kill掉指定的应用程序。
-status	打印应用程序的状态。

示例1：

 [hduser@hadoop0 bin]$ ./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: [ACCEPTED]):1
 Application-Id                  Application-Name Application-Type User   Queue   State    Final-State Progress Tracking-URL
 application_1438998625140_1703  MAC_STATUS   MAPREDUCE    hduser default ACCEPTED UNDEFINED   0%       N/A

示例2：

 [hduser@hadoop0 bin]$ ./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: [SUBMITTED, ACCEPTED, RUNNING]):1
 Application-Id                 Application-Name Application-Type  User   Queue   State    Final-State   Progress Tracking-URL
 application_1438998625140_1701 MAC_STATUS   MAPREDUCE     hduser default ACCEPTED UNDEFINED 0%   N/A

示例3：

 [hduser@hadoop0 bin]$ ./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 [options]

命令选项	描述
-help	帮助
-list	获取到应用程序尝试的列表，其返回值ApplicationAttempt-Id 等于
-status	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：

 [hadoop@hadoopcluster78 bin]$ 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   RUNNING  container_1437364567082_0106_01_000001 http://hadoopcluster79:8088/proxy/application_1437364567082_0106/

示例2：

 [hadoop@hadoopcluster78 bin]$ 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   RUNNING  container_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

 [hadoop@hadoopcluster78 bin]$ 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 [options]

命令选项	描述
-help	帮助
-list	应用程序尝试的Containers列表
-status	打印Container的状态

打印container(s)的报告
示例1：

 [hadoop@hadoopcluster78 bin]$ 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：

 [hadoop@hadoopcluster78 bin]$ 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 [mainClass] 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 [options]
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	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	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	Container Id
-help	帮助
-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：

 [hadoop@hadoopcluster78 bin]$ 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 [main] 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 [main] 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：
 [hadoop@hadoopcluster78 bin]$ 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 [options]

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	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	打印指定节点的状态。

示例1：

 [hadoop@hadoopcluster78 bin]$ ./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：

 [hadoop@hadoopcluster78 bin]$ ./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：

 [hadoop@hadoopcluster78 bin]$ ./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 [options]

命令选项	描述
-help	帮助
-status	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     yarn daemonlog -setlevel

参数选项	描述
-getlevel	打印运行在的守护进程的日志级别。这个命令内部会连接http:///logLevel?log=
-setlevel	设置运行在的守护进程的日志级别。这个命令内部会连接http:///logLevel?log=

针对指定的守护进程，获取/设置日志级别.
示例1：

 [root@hadoopcluster78 ~]# 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
 [root@hadoopcluster78 ~]# 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
 [root@hadoopcluster78 ~]# 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-store	RMStateStore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 [username]]               [-transitionToActive [--forceactive] [--forcemanual] ]               [-transitionToStandby [--forcemanual] ]               [-failover [--forcefence] [--forceactive] ]               [-getServiceState ]               [-checkHealth ]               [-help [cmd]]

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
-refreshServiceAcl	ResourceManager重载服务级别的授权文件。
-getGroups [username]	获取指定用户所属的组。
-transitionToActive [–forceactive] [–forcemanual]	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]	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]	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	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	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 [cmd]	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 [options]

参数选项	描述
-help	Help
-runCleanerTask	Runs 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