hadoop job yarn 命令
2017-06-13 10:46
148 查看
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 <task-id>
7.使任务失败。被失败的任务会对失败尝试不利：
Hadoop job
-fail-task <task-id>
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。
表A：
用户命令：
对于hadoop集群用户很有用的命令：
application
使用: yarn application [options]
示例1：
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[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：
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[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：
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[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]
打印应用程序尝试的报告。
示例1：
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[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：
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[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
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[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]
打印container(s)的报告
示例1：
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[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：
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[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 <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 <application ID> [options]
注：应用程序没有完成，该命令是不能打印日志的。
转存container的日志。
示例：
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[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]
示例1：
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[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：
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[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：
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[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]
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>
针对指定的守护进程，获取/设置日志级别.
示例1：
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[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]
启动ResourceManager
rmadmin
使用:
yarn rmadmin [-refreshQueues] [-refreshNodes] [-refreshUserToGroupsMapping] [-refreshSuperUserGroupsConfiguration]
[-refreshAdminAcls] [-refreshServiceAcl] [-getGroups [username]] [-transitionToActive [--forceactive] [--forcemanual] <serviceId>] [-transitionToStandby [--forcemanual] <serviceId>]
[-failover [--forcefence] [--forceactive] <serviceId1> <serviceId2>] [-getServiceState <serviceId>] [-checkHealth <serviceId>] [-help [cmd]]
scmadmin使用:
yarn scmadmin [options]
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
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 <task-id>
7.使任务失败。被失败的任务会对失败尝试不利：
Hadoop job
-fail-task <task-id>
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： ${HADOOP_PREFIX}/conf. |
| --loglevel loglevel | 重载Log级别。有效的日志级别包含：FATAL, ERROR, WARN, INFO, DEBUG, and TRACE。默认是INFO。 |
| GENERIC_OPTIONS | YARN支持表A的通用命令项。 |
| COMMAND COMMAND_OPTIONS | YARN分为用户命令和管理员命令。 |
| 通用项 | Description |
| -archives <comma separated list of archives> | 用逗号分隔计算中未归档的文件。 仅仅针对JOB。 |
| -conf <configuration file> | 制定应用程序的配置文件。 |
| -D <property>=<value> | 使用给定的属性值。 |
| -files <comma separated list of files> | 用逗号分隔的文件,拷贝到Map reduce机器，仅仅针对JOB |
| -jt <local> or <resourcemanager:port> | 指定一个ResourceManager. 仅仅针对JOB。 |
| -libjars <comma seperated list of jars> | 将用逗号分隔的jar路径包含到classpath中去，仅仅针对JOB。 |
对于hadoop集群用户很有用的命令：
application
使用: yarn application [options]
| 命令选项 | 描述 |
| -appStates <States> | 使用-list命令，基于应用程序的状态来过滤应用程序。如果应用程序的状态有多个，用逗号分隔。 有效的应用程序状态包含 如下： ALL, NEW, NEW_SAVING, SUBMITTED, ACCEPTED, RUNNING, FINISHED, FAILED, KILLED |
| -appTypes <Types> | 使用-list命令，基于应用程序类型来过滤应用程序。如果应用程序的类型有多个，用逗号分隔。 |
| -list | 从RM返回的应用程序列表，使用-appTypes参数，支持基于应用程序类型的过滤，使用-appStates参数，支持对应用程序状态的过滤。 |
| -kill <ApplicationId> | kill掉指定的应用程序。 |
| -status <ApplicationId> | 打印应用程序的状态。 |
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[hduser@hadoop0 bin]$ ./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：
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[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：
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[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 <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。 |
示例1：
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[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：
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[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
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[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]
| [align=left]命令选项[/align] | [align=left]描述[/align] |
| [align=left]-help[/align] | [align=left]帮助[/align] |
| [align=left]-list <Application Attempt Id>[/align] | [align=left]应用程序尝试的Containers列表[/align] |
| [align=left]-status <ContainerId>[/align] | [align=left]打印Container的状态[/align] |
示例1：
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[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：
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[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 <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 <application ID> [options]
注：应用程序没有完成，该命令是不能打印日志的。
| [align=left]命令选项[/align] | [align=left]描述[/align] |
| [align=left]-applicationId <application ID>[/align] | [align=left]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）[/align] |
| [align=left]-appOwner <AppOwner>[/align] | [align=left]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）[/align] |
| [align=left]-containerId <ContainerId>[/align] | [align=left]Container Id[/align] |
| [align=left]-help[/align] | [align=left]帮助[/align] |
| [align=left]-nodeAddress <NodeAddress>[/align] | [align=left]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）[/align] |
示例：
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[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]
| [align=left]命令选项[/align] | [align=left]描述[/align] |
| [align=left]-all[/align] | [align=left]所有的节点，不管是什么状态的。[/align] |
| [align=left]-list[/align] | 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。 |
| [align=left]-states <States>[/align] | [align=left]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。[/align] |
| [align=left]-status <NodeId>[/align] | [align=left]打印指定节点的状态。[/align] |
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[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：
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[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：
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[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]
| [align=left]命令选项[/align] | [align=left]描述[/align] |
| [align=left]-help[/align] | [align=left]帮助[/align] |
| [align=left]-status <QueueName>[/align] | [align=left]打印队列的状态[/align] |
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>
| [align=left]参数选项[/align] | [align=left]描述[/align] |
| [align=left]-getlevel <host:httpport> <classname>[/align] | [align=left]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>[/align] |
| [align=left]-setlevel <host:httpport> <classname> <level>[/align] | [align=left]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>[/align] |
示例1：
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[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]
| [align=left]参数选项[/align] | [align=left]描述[/align] |
| [align=left]-format-state-store[/align] | [align=left]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[/align] |
rmadmin
使用:
yarn rmadmin [-refreshQueues] [-refreshNodes] [-refreshUserToGroupsMapping] [-refreshSuperUserGroupsConfiguration]
[-refreshAdminAcls] [-refreshServiceAcl] [-getGroups [username]] [-transitionToActive [--forceactive] [--forcemanual] <serviceId>] [-transitionToStandby [--forcemanual] <serviceId>]
[-failover [--forcefence] [--forceactive] <serviceId1> <serviceId2>] [-getServiceState <serviceId>] [-checkHealth <serviceId>] [-help [cmd]]
| [align=left]参数选项[/align] | [align=left]描述[/align] |
| [align=left]-refreshQueues[/align] | [align=left]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[/align] |
| [align=left]-refreshNodes[/align] | 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。 |
| [align=left]-refreshUserToGroupsMappings[/align] | [align=left]刷新用户到组的映射。[/align] |
| [align=left]-refreshSuperUserGroupsConfiguration[/align] | [align=left]刷新用户组的配置[/align] |
| [align=left]-refreshAdminAcls[/align] | [align=left]刷新ResourceManager的ACL管理[/align] |
| [align=left]-refreshServiceAcl[/align] | [align=left]ResourceManager重载服务级别的授权文件。[/align] |
| [align=left]-getGroups [username][/align] | [align=left]获取指定用户所属的组。[/align] |
| [align=left]-transitionToActive [–forceactive] [–forcemanual] <serviceId>[/align] | [align=left]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。[/align] |
| [align=left]-transitionToStandby [–forcemanual] <serviceId>[/align] | [align=left]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。[/align] |
| [align=left]-failover [–forceactive] <serviceId1> <serviceId2>[/align] | [align=left]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。[/align] |
| [align=left]-getServiceState <serviceId>[/align] | [align=left]返回服务的状态。（注：ResourceManager不是HA的时候，时不能运行该命令的）[/align] |
| [align=left]-checkHealth <serviceId>[/align] | [align=left]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）[/align] |
| [align=left]-help [cmd][/align] | [align=left]显示指定命令的帮助，如果没有指定，则显示命令的帮助。[/align] |
yarn scmadmin [options]
| [align=left]参数选项[/align] | [align=left]描述[/align] |
| [align=left]-help[/align] | [align=left]Help[/align] |
| [align=left]-runCleanerTask[/align] | [align=left]Runs the cleaner task[/align] |
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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