MapReduce 历史服务器 REST API

概述

历史服务器 REST API 允许用户获取已完成应用程序的状态。

历史服务器信息 API

历史服务器信息资源提供有关历史服务器的总体信息。

URI

以下两个 URI 均可提供历史服务器信息，其中 appid 值标识应用程序 ID。

支持的 HTTP 操作

  • GET

支持的查询参数

  None

historyInfo 对象的元素

项目 数据类型 说明
startedOn long 历史服务器启动时间（自纪元以来的毫秒数）
hadoopVersion string Hadoop 通用版本
hadoopBuildVersion string Hadoop 通用构建字符串，包含构建版本、用户和校验和
hadoopVersionBuiltOn string Hadoop 通用构建时间戳

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/info

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

{
   "historyInfo" : {
      "startedOn":1353512830963,
      "hadoopVersionBuiltOn" : "Wed Jan 11 21:18:36 UTC 2012",
      "hadoopBuildVersion" : "0.23.1-SNAPSHOT from 1230253 by user1 source checksum bb6e554c6d50b0397d826081017437a7",
      "hadoopVersion" : "0.23.1-SNAPSHOT"
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/info
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 330
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<historyInfo>
  <startedOn>1353512830963</startedOn>
  <hadoopVersion>0.23.1-SNAPSHOT</hadoopVersion>
  <hadoopBuildVersion>0.23.1-SNAPSHOT from 1230253 by user1 source checksum bb6e554c6d50b0397d826081017437a7</hadoopBuildVersion>
  <hadoopVersionBuiltOn>Wed Jan 11 21:18:36 UTC 2012</hadoopVersionBuiltOn>
</historyInfo>

MapReduce API

以下资源列表适用于 MapReduce。

作业 API

作业资源提供已完成 MapReduce 作业的列表。目前，它不会返回参数的完整列表

URI

支持的 HTTP 操作

  • GET

支持的查询参数

可以指定多个参数。开始时间和结束时间具有开始和结束参数，以便您指定范围。例如，可以请求 2011 年 12 月 19 日上午 1:00 至下午 2:00 之间启动的所有作业，方法是 startedTimeBegin=1324256400&startedTimeEnd=1324303200。如果未指定开始参数，则默认为 0，如果未指定结束参数，则默认为无穷大。

  • user - 用户名
    • state - 作业状态
    • queue - 队列名称
    • limit - 要返回的 app 对象的总数
    • startedTimeBegin - 开始时间以该时间开始的作业，以自纪元以来的毫秒数指定
    • startedTimeEnd - 开始时间以该时间结束的作业，以自纪元以来的毫秒数指定
    • finishedTimeBegin - 结束时间以该时间开始的作业，以自纪元以来的毫秒数指定
    • finishedTimeEnd - 结束时间以该时间结束的作业，以自纪元以来的毫秒数指定

jobs 对象的元素

当您请求作业列表时，信息将作为作业对象数组返回。另请参阅 作业 API，了解作业对象的语法。不过，这是完整作业的子集。仅返回 startTime、finishTime、id、name、queue、user、state、mapsTotal、mapsCompleted、reducesTotal 和 reducesCompleted。

项目 数据类型 说明
作业 作业对象数组（json）/零个或多个作业对象（XML） 作业对象集合

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

{
   "jobs" : {
      "job" : [
         {
            "submitTime" : 1326381344449,
            "state" : "SUCCEEDED",
            "user" : "user1",
            "reducesTotal" : 1,
            "mapsCompleted" : 1,
            "startTime" : 1326381344489,
            "id" : "job_1326381300833_1_1",
            "name" : "word count",
            "reducesCompleted" : 1,
            "mapsTotal" : 1,
            "queue" : "default",
            "finishTime" : 1326381356010
         },
         {
            "submitTime" : 1326381446500
            "state" : "SUCCEEDED",
            "user" : "user1",
            "reducesTotal" : 1,
            "mapsCompleted" : 1,
            "startTime" : 1326381446529,
            "id" : "job_1326381300833_2_2",
            "name" : "Sleep job",
            "reducesCompleted" : 1,
            "mapsTotal" : 1,
            "queue" : "default",
            "finishTime" : 1326381582106
         }
      ]
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 1922
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<jobs>
  <job>
    <submitTime>1326381344449</submitTime>
    <startTime>1326381344489</startTime>
    <finishTime>1326381356010</finishTime>
    <id>job_1326381300833_1_1</id>
    <name>word count</name>
    <queue>default</queue>
    <user>user1</user>
    <state>SUCCEEDED</state>
    <mapsTotal>1</mapsTotal>
    <mapsCompleted>1</mapsCompleted>
    <reducesTotal>1</reducesTotal>
    <reducesCompleted>1</reducesCompleted>
  </job>
  <job>
    <submitTime>1326381446500</submitTime>
    <startTime>1326381446529</startTime>
    <finishTime>1326381582106</finishTime>
    <id>job_1326381300833_2_2</id>
    <name>Sleep job</name>
    <queue>default</queue>
    <user>user1</user>
    <state>SUCCEEDED</state>
    <mapsTotal>1</mapsTotal>
    <mapsCompleted>1</mapsCompleted>
    <reducesTotal>1</reducesTotal>
    <reducesCompleted>1</reducesCompleted>
  </job>
</jobs>

作业 API

作业资源包含由作业 ID 标识的特定作业的信息。

URI

支持的 HTTP 操作

  • GET

支持的查询参数

  None

作业 对象的元素

项目 数据类型 说明
id string 作业 ID
name string 作业名称
queue string 作业提交到的队列
user string 用户名
state string 作业状态 - 有效值：NEW、INITED、RUNNING、SUCCEEDED、FAILED、KILL_WAIT、KILLED、ERROR
diagnostics string 诊断消息
submitTime long 作业提交时间（自纪元以来的毫秒数）
startTime long 作业开始时间（自纪元以来的毫秒数）
finishTime long 作业完成时间（自纪元以来的毫秒数）
mapsTotal int 映射总数
mapsCompleted int 已完成的映射数
reducesTotal int 还原总数
reducesCompleted int 已完成的还原数
uberized boolean 指示作业是否是 uber 作业 - 完全在应用程序主控中运行
avgMapTime long 映射任务的平均时间（毫秒）
avgReduceTime long 还原的平均时间（毫秒）
avgShuffleTime long 洗牌的平均时间（毫秒）
avgMergeTime long 合并的平均时间（毫秒）
failedReduceAttempts int 失败的还原尝试次数
killedReduceAttempts int 已终止的还原尝试次数
successfulReduceAttempts int 成功的还原尝试次数
failedMapAttempts int 失败的映射尝试次数
killedMapAttempts int 已终止映射尝试数
successfulMapAttempts int 成功映射尝试数
acls acls 数组（json）/零个或多个 acls 对象（xml） acls 对象集合

acls 对象的元素

项目 数据类型 说明
value string acl 值
name string acl 名称

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Server: Jetty(6.1.26)
  Content-Length: 720

响应正文

{
   "job" : {
      "submitTime":  1326381446500,
      "avgReduceTime" : 124961,
      "failedReduceAttempts" : 0,
      "state" : "SUCCEEDED",
      "successfulReduceAttempts" : 1,
      "acls" : [
         {
            "value" : " ",
            "name" : "mapreduce.job.acl-modify-job"
         },
         {
            "value" : " ",
            "name" : "mapreduce.job.acl-view-job"
         }
      ],
      "user" : "user1",
      "reducesTotal" : 1,
      "mapsCompleted" : 1,
      "startTime" : 1326381446529,
      "id" : "job_1326381300833_2_2",
      "avgMapTime" : 2638,
      "successfulMapAttempts" : 1,
      "name" : "Sleep job",
      "avgShuffleTime" : 2540,
      "reducesCompleted" : 1,
      "diagnostics" : "",
      "failedMapAttempts" : 0,
      "avgMergeTime" : 2589,
      "killedReduceAttempts" : 0,
      "mapsTotal" : 1,
      "queue" : "default",
      "uberized" : false,
      "killedMapAttempts" : 0,
      "finishTime" : 1326381582106
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 983
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<job>
  <submitTime>1326381446500</submitTime>
  <startTime>1326381446529</startTime>
  <finishTime>1326381582106</finishTime>
  <id>job_1326381300833_2_2</id>
  <name>Sleep job</name>
  <queue>default</queue>
  <user>user1</user>
  <state>SUCCEEDED</state>
  <mapsTotal>1</mapsTotal>
  <mapsCompleted>1</mapsCompleted>
  <reducesTotal>1</reducesTotal>
  <reducesCompleted>1</reducesCompleted>
  <uberized>false</uberized>
  <diagnostics/>
  <avgMapTime>2638</avgMapTime>
  <avgReduceTime>124961</avgReduceTime>
  <avgShuffleTime>2540</avgShuffleTime>
  <avgMergeTime>2589</avgMergeTime>
  <failedReduceAttempts>0</failedReduceAttempts>
  <killedReduceAttempts>0</killedReduceAttempts>
  <successfulReduceAttempts>1</successfulReduceAttempts>
  <failedMapAttempts>0</failedMapAttempts>
  <killedMapAttempts>0</killedMapAttempts>
  <successfulMapAttempts>1</successfulMapAttempts>
  <acls>
    <name>mapreduce.job.acl-modify-job</name>
    <value> </value>
  </acls>
  <acls>
    <name>mapreduce.job.acl-view-job</name>
    <value> </value>
  </acls>
</job>

作业尝试 API

使用作业尝试 API，您可以获取表示作业尝试的资源集合。当您对该资源运行 GET 操作时，您将获取作业尝试对象集合。

URI

支持的 HTTP 操作

  • GET

支持的查询参数

  None

jobAttempts 对象的元素

当您请求作业尝试列表时，信息将作为作业尝试对象数组返回。

jobAttempts

项目 数据类型 说明
jobAttempt 作业尝试对象数组（JSON）/零个或多个作业尝试对象（XML） 作业尝试对象集合

jobAttempt 对象的元素

项目 数据类型 说明
id int 作业尝试 ID
nodeId string 尝试运行的节点的节点 ID
nodeHttpAddress string 尝试运行的节点的节点 http 地址
logsLink string 作业尝试日志的 http 链接
containerId string 作业尝试的容器 ID
startTime long 尝试的开始时间（自纪元以来的毫秒数）

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/jobattempts

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

{
   "jobAttempts" : {
      "jobAttempt" : [
         {
            "nodeId" : "host.domain.com:8041",
            "nodeHttpAddress" : "host.domain.com:8042",
            "startTime" : 1326381444693,
            "id" : 1,
            "logsLink" : "http://host.domain.com:19888/jobhistory/logs/host.domain.com:8041/container_1326381300833_0002_01_000001/job_1326381300833_2_2/user1",
            "containerId" : "container_1326381300833_0002_01_000001"
         }
      ]
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/jobattmpts
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 575
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<jobAttempts>
  <jobAttempt>
    <nodeHttpAddress>host.domain.com:8042</nodeHttpAddress>
    <nodeId>host.domain.com:8041</nodeId>
    <id>1</id>
    <startTime>1326381444693</startTime>
    <containerId>container_1326381300833_0002_01_000001</containerId>
    <logsLink>http://host.domain.com:19888/jobhistory/logs/host.domain.com:8041/container_1326381300833_0002_01_000001/job_1326381300833_2_2/user1</logsLink>
  </jobAttempt>
</jobAttempts>

作业计数器 API

使用作业计数器 API，您可以获取表示该作业所有计数器的资源集合。

URI

支持的 HTTP 操作

  • GET

支持的查询参数

  None

jobCounters 对象的元素

项目 数据类型 说明
id string 作业 ID
counterGroup counterGroup 对象数组（JSON）/零个或多个 counterGroup 对象（XML） 计数器组对象集合

counterGroup 对象的元素

项目 数据类型 说明
counterGroupName string 计数器组名称
counter counter 对象数组（JSON）/零个或多个 counter 对象（XML） 计数器对象集合

counter 对象的元素

项目 数据类型 说明
name string 计数器名称
reduceCounterValue long 归约任务的计数器值
mapCounterValue long 映射任务的计数器值
totalCounterValue long 所有任务的计数器值

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/counters

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

{
   "jobCounters" : {
      "id" : "job_1326381300833_2_2",
      "counterGroup" : [
         {
            "counterGroupName" : "Shuffle Errors",
            "counter" : [
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "BAD_ID"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "CONNECTION"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "IO_ERROR"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "WRONG_LENGTH"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "WRONG_MAP"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "WRONG_REDUCE"
               }
            ]
          },
         {
            "counterGroupName" : "org.apache.hadoop.mapreduce.FileSystemCounter",
            "counter" : [
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 2483,
                  "name" : "FILE_BYTES_READ"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 108525,
                  "name" : "FILE_BYTES_WRITTEN"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "FILE_READ_OPS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "FILE_LARGE_READ_OPS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "FILE_WRITE_OPS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 48,
                  "name" : "HDFS_BYTES_READ"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "HDFS_BYTES_WRITTEN"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 1,
                  "name" : "HDFS_READ_OPS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "HDFS_LARGE_READ_OPS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "HDFS_WRITE_OPS"
               }
            ]
         },
         {
            "counterGroupName" : "org.apache.hadoop.mapreduce.TaskCounter",
            "counter" : [
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 1,
                  "name" : "MAP_INPUT_RECORDS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 1200,
                  "name" : "MAP_OUTPUT_RECORDS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 4800,
                  "name" : "MAP_OUTPUT_BYTES"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 2235,
                  "name" : "MAP_OUTPUT_MATERIALIZED_BYTES"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 48,
                  "name" : "SPLIT_RAW_BYTES"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "COMBINE_INPUT_RECORDS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "COMBINE_OUTPUT_RECORDS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 1200,
                  "name" : "REDUCE_INPUT_GROUPS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 2235,
                  "name" : "REDUCE_SHUFFLE_BYTES"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 1200,
                  "name" : "REDUCE_INPUT_RECORDS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "REDUCE_OUTPUT_RECORDS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 2400,
                  "name" : "SPILLED_RECORDS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 1,
                  "name" : "SHUFFLED_MAPS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "FAILED_SHUFFLE"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 1,
                  "name" : "MERGED_MAP_OUTPUTS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 113,
                  "name" : "GC_TIME_MILLIS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 1830,
                  "name" : "CPU_MILLISECONDS"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 478068736,
                  "name" : "PHYSICAL_MEMORY_BYTES"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 2159284224,
                  "name" : "VIRTUAL_MEMORY_BYTES"
               },
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 378863616,
                  "name" : "COMMITTED_HEAP_BYTES"
               }
            ]
         },
         {
            "counterGroupName" : "org.apache.hadoop.mapreduce.lib.input.FileInputFormatCounter",
            "counter" : [
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "BYTES_READ"
               }
            ]
         },
         {
            "counterGroupName" : "org.apache.hadoop.mapreduce.lib.output.FileOutputFormatCounter",
            "counter" : [
               {
                  "reduceCounterValue" : 0,
                  "mapCounterValue" : 0,
                  "totalCounterValue" : 0,
                  "name" : "BYTES_WRITTEN"
               }
            ]
         }
      ]
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/counters
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 7030
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<jobCounters>
  <id>job_1326381300833_2_2</id>
  <counterGroup>
    <counterGroupName>Shuffle Errors</counterGroupName>
    <counter>
      <name>BAD_ID</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>CONNECTION</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>IO_ERROR</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>WRONG_LENGTH</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>WRONG_MAP</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>WRONG_REDUCE</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
  </counterGroup>
  <counterGroup>
    <counterGroupName>org.apache.hadoop.mapreduce.FileSystemCounter</counterGroupName>
    <counter>
      <name>FILE_BYTES_READ</name>
      <totalCounterValue>2483</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>FILE_BYTES_WRITTEN</name>
      <totalCounterValue>108525</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>FILE_READ_OPS</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>FILE_LARGE_READ_OPS</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>FILE_WRITE_OPS</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>HDFS_BYTES_READ</name>
      <totalCounterValue>48</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>HDFS_BYTES_WRITTEN</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>HDFS_READ_OPS</name>
      <totalCounterValue>1</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>HDFS_LARGE_READ_OPS</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>HDFS_WRITE_OPS</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
  </counterGroup>
  <counterGroup>
    <counterGroupName>org.apache.hadoop.mapreduce.TaskCounter</counterGroupName>
    <counter>
      <name>MAP_INPUT_RECORDS</name>
      <totalCounterValue>1</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>MAP_OUTPUT_RECORDS</name>
      <totalCounterValue>1200</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>MAP_OUTPUT_BYTES</name>
      <totalCounterValue>4800</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>MAP_OUTPUT_MATERIALIZED_BYTES</name>
      <totalCounterValue>2235</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>SPLIT_RAW_BYTES</name>
      <totalCounterValue>48</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>COMBINE_INPUT_RECORDS</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>COMBINE_OUTPUT_RECORDS</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>REDUCE_INPUT_GROUPS</name>
      <totalCounterValue>1200</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>REDUCE_SHUFFLE_BYTES</name>
      <totalCounterValue>2235</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>REDUCE_INPUT_RECORDS</name>
      <totalCounterValue>1200</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>REDUCE_OUTPUT_RECORDS</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>SPILLED_RECORDS</name>
      <totalCounterValue>2400</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>SHUFFLED_MAPS</name>
      <totalCounterValue>1</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>FAILED_SHUFFLE</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>MERGED_MAP_OUTPUTS</name>
      <totalCounterValue>1</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>GC_TIME_MILLIS</name>
      <totalCounterValue>113</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>CPU_MILLISECONDS</name>
      <totalCounterValue>1830</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>PHYSICAL_MEMORY_BYTES</name>
      <totalCounterValue>478068736</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>VIRTUAL_MEMORY_BYTES</name>
      <totalCounterValue>2159284224</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
    <counter>
      <name>COMMITTED_HEAP_BYTES</name>
      <totalCounterValue>378863616</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
  </counterGroup>
  <counterGroup>
    <counterGroupName>org.apache.hadoop.mapreduce.lib.input.FileInputFormatCounter</counterGroupName>
    <counter>
      <name>BYTES_READ</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
  </counterGroup>
  <counterGroup>
    <counterGroupName>org.apache.hadoop.mapreduce.lib.output.FileOutputFormatCounter</counterGroupName>
    <counter>
      <name>BYTES_WRITTEN</name>
      <totalCounterValue>0</totalCounterValue>
      <mapCounterValue>0</mapCounterValue>
      <reduceCounterValue>0</reduceCounterValue>
    </counter>
  </counterGroup>
</jobCounters>

作业配置 API

作业配置资源包含有关此作业的作业配置的信息。

URI

使用以下 URI 从由 jobid 值标识的作业中获取作业配置信息。

支持的 HTTP 操作

  • GET

支持的查询参数

  None

conf 对象的元素

项目 数据类型 说明
path string 作业配置文件的路径
property 配置属性数组（JSON）/零个或多个配置属性（XML） 配置属性对象的集合

property 对象的元素

项目 数据类型 说明
name string 配置属性的名称
value string 配置属性的值
source string 此配置对象来自的位置。如果有多个，则显示历史记录，列表末尾为最新来源。

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/conf

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

这是输出的一个小片段，因为输出非常大。实际输出包含作业配置文件中的每个属性。

{
   "conf" : {
      "path" : "hdfs://host.domain.com:9000/user/user1/.staging/job_1326381300833_0002/job.xml",
      "property" : [
         {
            "value" : "/home/hadoop/hdfs/data",
            "name" : "dfs.datanode.data.dir"
            "source" : ["hdfs-site.xml", "job.xml"]
         },
         {
            "value" : "org.apache.hadoop.yarn.server.webproxy.amfilter.AmFilterInitializer",
            "name" : "hadoop.http.filter.initializers"
            "source" : ["programmatically", "job.xml"]
         },
         {
            "value" : "/home/hadoop/tmp",
            "name" : "mapreduce.cluster.temp.dir"
            "source" : ["mapred-site.xml"]
         },
         ...
      ]
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/conf
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 552
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<conf>
  <path>hdfs://host.domain.com:9000/user/user1/.staging/job_1326381300833_0002/job.xml</path>
  <property>
    <name>dfs.datanode.data.dir</name>
    <value>/home/hadoop/hdfs/data</value>
    <source>hdfs-site.xml</source>
    <source>job.xml</source>
  </property>
  <property>
    <name>hadoop.http.filter.initializers</name>
    <value>org.apache.hadoop.yarn.server.webproxy.amfilter.AmFilterInitializer</value>
    <source>programmatically</source>
    <source>job.xml</source>
  </property>
  <property>
    <name>mapreduce.cluster.temp.dir</name>
    <value>/home/hadoop/tmp</value>
    <source>mapred-site.xml</source>
  </property>
  ...
</conf>

任务 API

使用任务 API，您可以获取表示作业中任务的资源集合。当您对该资源运行 GET 操作时，您将获得任务对象集合。

URI

支持的 HTTP 操作

  • GET

支持的查询参数

  • type - 任务类型，有效值为 m 或 r。m 表示映射任务，r 表示归约任务。

tasks 对象的元素

当您请求任务列表时，信息将作为任务对象数组返回。有关任务对象的语法，另请参见 任务 API。

项目 数据类型 说明
task 任务对象数组（JSON）/零个或多个任务对象（XML） 任务对象集合。

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

{
   "tasks" : {
      "task" : [
         {
            "progress" : 100,
            "elapsedTime" : 6777,
            "state" : "SUCCEEDED",
            "startTime" : 1326381446541,
            "id" : "task_1326381300833_2_2_m_0",
            "type" : "MAP",
            "successfulAttempt" : "attempt_1326381300833_2_2_m_0_0",
            "finishTime" : 1326381453318
         },
         {
            "progress" : 100,
            "elapsedTime" : 135559,
            "state" : "SUCCEEDED",
            "startTime" : 1326381446544,
            "id" : "task_1326381300833_2_2_r_0",
            "type" : "REDUCE",
            "successfulAttempt" : "attempt_1326381300833_2_2_r_0_0",
            "finishTime" : 1326381582103
         }
      ]
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 653
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<tasks>
  <task>
    <startTime>1326381446541</startTime>
    <finishTime>1326381453318</finishTime>
    <elapsedTime>6777</elapsedTime>
    <progress>100.0</progress>
    <id>task_1326381300833_2_2_m_0</id>
    <state>SUCCEEDED</state>
    <type>MAP</type>
    <successfulAttempt>attempt_1326381300833_2_2_m_0_0</successfulAttempt>
  </task>
  <task>
    <startTime>1326381446544</startTime>
    <finishTime>1326381582103</finishTime>
    <elapsedTime>135559</elapsedTime>
    <progress>100.0</progress>
    <id>task_1326381300833_2_2_r_0</id>
    <state>SUCCEEDED</state>
    <type>REDUCE</type>
    <successfulAttempt>attempt_1326381300833_2_2_r_0_0</successfulAttempt>
  </task>
</tasks>

任务 API

任务资源包含有关作业中特定任务的信息。

URI

使用以下 URI 从由 taskid 值标识的任务中获取任务对象。

支持的 HTTP 操作

  • GET

支持的查询参数

  None

task 对象的元素

项目 数据类型 说明
id string 任务 ID
state string 任务状态 - 有效值为：NEW、SCHEDULED、RUNNING、SUCCEEDED、FAILED、KILL_WAIT、KILLED
type string 任务类型 - MAP 或 REDUCE
successfulAttempt string 最后一次成功尝试的 ID
progress float 任务进度（百分比）
startTime long 任务开始时间（自纪元以来的毫秒数），如果从未开始，则为 -1
finishTime long 任务完成时间（自纪元以来的毫秒数）
elapsedTime long 应用程序启动以来的经过时间（以毫秒为单位）

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks/task_1326381300833_2_2_m_0

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

{
   "task" : {
      "progress" : 100,
      "elapsedTime" : 6777,
      "state" : "SUCCEEDED",
      "startTime" : 1326381446541,
      "id" : "task_1326381300833_2_2_m_0",
      "type" : "MAP",
      "successfulAttempt" : "attempt_1326381300833_2_2_m_0_0",
      "finishTime" : 1326381453318
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks/task_1326381300833_2_2_m_0
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 299
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<task>
  <startTime>1326381446541</startTime>
  <finishTime>1326381453318</finishTime>
  <elapsedTime>6777</elapsedTime>
  <progress>100.0</progress>
  <id>task_1326381300833_2_2_m_0</id>
  <state>SUCCEEDED</state>
  <type>MAP</type>
  <successfulAttempt>attempt_1326381300833_2_2_m_0_0</successfulAttempt>
</task>

任务计数器 API

使用任务计数器 API，您可以将资源集合对象化，这些资源集合表示该任务的所有计数器。

URI

支持的 HTTP 操作

  • GET

支持的查询参数

  None

jobTaskCounters 对象的元素

项目 数据类型 说明
id string 任务 ID
taskCounterGroup counterGroup 对象数组（JSON）/零个或多个 counterGroup 对象（XML） 计数器组对象集合

counterGroup 对象的元素

项目 数据类型 说明
counterGroupName string 计数器组名称
counter counter 对象数组（JSON）/零个或多个 counter 对象（XML） 计数器对象集合

counter 对象的元素

项目 数据类型 说明
name string 计数器名称
value long 计数器的值

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks/task_1326381300833_2_2_m_0/counters

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

{
   "jobTaskCounters" : {
      "id" : "task_1326381300833_2_2_m_0",
      "taskCounterGroup" : [
         {
            "counterGroupName" : "org.apache.hadoop.mapreduce.FileSystemCounter",
            "counter" : [
               {
                  "value" : 2363,
                  "name" : "FILE_BYTES_READ"
               },
               {
                  "value" : 54372,
                  "name" : "FILE_BYTES_WRITTEN"
               },
               {
                  "value" : 0,
                  "name" : "FILE_READ_OPS"
               },
               {
                  "value" : 0,
                  "name" : "FILE_LARGE_READ_OPS"
               },
               {
                  "value" : 0,
                  "name" : "FILE_WRITE_OPS"
               },
               {
                  "value" : 0,
                  "name" : "HDFS_BYTES_READ"
               },
               {
                  "value" : 0,
                  "name" : "HDFS_BYTES_WRITTEN"
               },
               {
                  "value" : 0,
                  "name" : "HDFS_READ_OPS"
               },
               {
                  "value" : 0,
                  "name" : "HDFS_LARGE_READ_OPS"
               },
               {
                  "value" : 0,
                  "name" : "HDFS_WRITE_OPS"
               }
            ]
         },
         {
            "counterGroupName" : "org.apache.hadoop.mapreduce.TaskCounter",
            "counter" : [
               {
                  "value" : 0,
                  "name" : "COMBINE_INPUT_RECORDS"
               },
               {
                  "value" : 0,
                  "name" : "COMBINE_OUTPUT_RECORDS"
               },
               {
                  "value" : 460,
                  "name" : "REDUCE_INPUT_GROUPS"
               },
               {
                  "value" : 2235,
                  "name" : "REDUCE_SHUFFLE_BYTES"
               },
               {
                  "value" : 460,
                  "name" : "REDUCE_INPUT_RECORDS"
               },
               {
                  "value" : 0,
                  "name" : "REDUCE_OUTPUT_RECORDS"
               },
               {
                  "value" : 0,
                  "name" : "SPILLED_RECORDS"
               },
               {
                  "value" : 1,
                  "name" : "SHUFFLED_MAPS"
               },
               {
                  "value" : 0,
                  "name" : "FAILED_SHUFFLE"
               },
               {
                  "value" : 1,
                  "name" : "MERGED_MAP_OUTPUTS"
               },
               {
                  "value" : 26,
                  "name" : "GC_TIME_MILLIS"
               },
               {
                  "value" : 860,
                  "name" : "CPU_MILLISECONDS"
               },
               {
                  "value" : 107839488,
                  "name" : "PHYSICAL_MEMORY_BYTES"
               },
               {
                  "value" : 1123147776,
                  "name" : "VIRTUAL_MEMORY_BYTES"
               },
               {
                  "value" : 57475072,
                  "name" : "COMMITTED_HEAP_BYTES"
               }
            ]
         },
         {
            "counterGroupName" : "Shuffle Errors",
            "counter" : [
               {
                  "value" : 0,
                  "name" : "BAD_ID"
               },
               {
                  "value" : 0,
                  "name" : "CONNECTION"
               },
               {
                  "value" : 0,
                  "name" : "IO_ERROR"
               },
               {
                  "value" : 0,
                  "name" : "WRONG_LENGTH"
               },
               {
                  "value" : 0,
                  "name" : "WRONG_MAP"
               },
               {
                  "value" : 0,
                  "name" : "WRONG_REDUCE"
               }
            ]
         },
         {
            "counterGroupName" : "org.apache.hadoop.mapreduce.lib.output.FileOutputFormatCounter",
            "counter" : [
               {
                  "value" : 0,
                  "name" : "BYTES_WRITTEN"
               }
            ]
         }
      ]
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks/task_1326381300833_2_2_m_0/counters
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 2660
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<jobTaskCounters>
  <id>task_1326381300833_2_2_m_0</id>
  <taskCounterGroup>
    <counterGroupName>org.apache.hadoop.mapreduce.FileSystemCounter</counterGroupName>
    <counter>
      <name>FILE_BYTES_READ</name>
      <value>2363</value>
    </counter>
    <counter>
      <name>FILE_BYTES_WRITTEN</name>
      <value>54372</value>
    </counter>
    <counter>
      <name>FILE_READ_OPS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>FILE_LARGE_READ_OPS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>FILE_WRITE_OPS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>HDFS_BYTES_READ</name>
      <value>0</value>
    </counter>
    <counter>
      <name>HDFS_BYTES_WRITTEN</name>
      <value>0</value>
    </counter>
    <counter>
      <name>HDFS_READ_OPS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>HDFS_LARGE_READ_OPS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>HDFS_WRITE_OPS</name>
      <value>0</value>
    </counter>
  </taskCounterGroup>
  <taskCounterGroup>
    <counterGroupName>org.apache.hadoop.mapreduce.TaskCounter</counterGroupName>
    <counter>
      <name>COMBINE_INPUT_RECORDS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>COMBINE_OUTPUT_RECORDS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>REDUCE_INPUT_GROUPS</name>
      <value>460</value>
    </counter>
    <counter>
      <name>REDUCE_SHUFFLE_BYTES</name>
      <value>2235</value>
    </counter>
    <counter>
      <name>REDUCE_INPUT_RECORDS</name>
      <value>460</value>
    </counter>
    <counter>
      <name>REDUCE_OUTPUT_RECORDS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>SPILLED_RECORDS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>SHUFFLED_MAPS</name>
      <value>1</value>
    </counter>
    <counter>
      <name>FAILED_SHUFFLE</name>
      <value>0</value>
    </counter>
    <counter>
      <name>MERGED_MAP_OUTPUTS</name>
      <value>1</value>
    </counter>
    <counter>
      <name>GC_TIME_MILLIS</name>
      <value>26</value>
    </counter>
    <counter>
      <name>CPU_MILLISECONDS</name>
      <value>860</value>
    </counter>
    <counter>
      <name>PHYSICAL_MEMORY_BYTES</name>
      <value>107839488</value>
    </counter>
    <counter>
      <name>VIRTUAL_MEMORY_BYTES</name>
      <value>1123147776</value>
    </counter>
    <counter>
      <name>COMMITTED_HEAP_BYTES</name>
      <value>57475072</value>
    </counter>
  </taskCounterGroup>
  <taskCounterGroup>
    <counterGroupName>Shuffle Errors</counterGroupName>
    <counter>
      <name>BAD_ID</name>
      <value>0</value>
    </counter>
    <counter>
      <name>CONNECTION</name>
      <value>0</value>
    </counter>
    <counter>
      <name>IO_ERROR</name>
      <value>0</value>
    </counter>
    <counter>
      <name>WRONG_LENGTH</name>
      <value>0</value>
    </counter>
    <counter>
      <name>WRONG_MAP</name>
      <value>0</value>
    </counter>
    <counter>
      <name>WRONG_REDUCE</name>
      <value>0</value>
    </counter>
  </taskCounterGroup>
  <taskCounterGroup>
    <counterGroupName>org.apache.hadoop.mapreduce.lib.output.FileOutputFormatCounter</counterGroupName>
    <counter>
      <name>BYTES_WRITTEN</name>
      <value>0</value>
    </counter>
  </taskCounterGroup>
</jobTaskCounters>

任务尝试 API

使用任务尝试 API，您可以获取资源集合，这些资源集合表示作业中的任务尝试。当您对该资源运行 GET 操作时，您将获取任务尝试对象集合。

URI

支持的 HTTP 操作

  • GET

支持的查询参数

  None

taskAttempts 对象的元素

当您请求任务尝试列表时，信息将作为任务尝试对象数组返回。另请参阅 任务尝试 API，了解任务对象的语法。

项目 数据类型 说明
taskAttempt 任务尝试对象数组（JSON）/零个或多个任务尝试对象（XML） 任务尝试对象集合

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks/task_1326381300833_2_2_m_0/attempts

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

{
   "taskAttempts" : {
      "taskAttempt" : [
         {
            "assignedContainerId" : "container_1326381300833_0002_01_000002",
            "progress" : 100,
            "elapsedTime" : 2638,
            "state" : "SUCCEEDED",
            "diagnostics" : "",
            "rack" : "/98.139.92.0",
            "nodeHttpAddress" : "host.domain.com:8042",
            "startTime" : 1326381450680,
            "id" : "attempt_1326381300833_2_2_m_0_0",
            "type" : "MAP",
            "finishTime" : 1326381453318
         }
      ]
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks/task_1326381300833_2_2_m_0/attempts
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 537
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<taskAttempts>
  <taskAttempt>
    <startTime>1326381450680</startTime>
    <finishTime>1326381453318</finishTime>
    <elapsedTime>2638</elapsedTime>
    <progress>100.0</progress>
    <id>attempt_1326381300833_2_2_m_0_0</id>
    <rack>/98.139.92.0</rack>
    <state>SUCCEEDED</state>
    <nodeHttpAddress>host.domain.com:8042</nodeHttpAddress>
    <diagnostics/>
    <type>MAP</type>
    <assignedContainerId>container_1326381300833_0002_01_000002</assignedContainerId>
  </taskAttempt>
</taskAttempts>

任务尝试 API

任务尝试资源包含作业中特定任务尝试的信息。

URI

使用以下 URI 从由 attemptid 值标识的任务中获取任务尝试对象。

支持的 HTTP 操作

  • GET

支持的查询参数

  None

taskAttempt 对象的元素

项目 数据类型 说明
id string 任务 ID
rack string 机架
state string 任务尝试的状态 - 有效值为：NEW、UNASSIGNED、ASSIGNED、RUNNING、COMMIT_PENDING、SUCCESS_CONTAINER_CLEANUP、SUCCEEDED、FAIL_CONTAINER_CLEANUP、FAIL_TASK_CLEANUP、FAILED、KILL_CONTAINER_CLEANUP、KILL_TASK_CLEANUP、KILLED
type string 任务类型
assignedContainerId string 此尝试分配到的容器 ID
nodeHttpAddress string 此任务尝试运行所在的节点的 HTTP 地址
diagnostics string 诊断消息
progress float 任务尝试的进度（以百分比表示）
startTime long 任务尝试开始的时间（以自纪元以来的毫秒数表示）
finishTime long 任务尝试完成的时间（自纪元以来的毫秒数）
elapsedTime long 自任务尝试开始以来经过的时间（毫秒数）

对于 reduce 任务尝试，您还有以下字段

项目 数据类型 说明
shuffleFinishTime long shuffle 完成的时间（自纪元以来的毫秒数）
mergeFinishTime long merge 完成的时间（自纪元以来的毫秒数）
elapsedShuffleTime long shuffle 阶段完成所需的时间（reduce 任务开始和 shuffle 完成之间的时间，以毫秒为单位）
elapsedMergeTime long merge 阶段完成所需的时间（shuffle 完成和 merge 完成之间的时间，以毫秒为单位）
elapsedReduceTime long reduce 阶段完成所需的时间（merge 完成到 reduce 任务结束之间的时间，以毫秒为单位）

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks/task_1326381300833_2_2_m_0/attempts/attempt_1326381300833_2_2_m_0_0

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

{
   "taskAttempt" : {
      "assignedContainerId" : "container_1326381300833_0002_01_000002",
      "progress" : 100,
      "elapsedTime" : 2638,
      "state" : "SUCCEEDED",
      "diagnostics" : "",
      "rack" : "/98.139.92.0",
      "nodeHttpAddress" : "host.domain.com:8042",
      "startTime" : 1326381450680,
      "id" : "attempt_1326381300833_2_2_m_0_0",
      "type" : "MAP",
      "finishTime" : 1326381453318
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks/task_1326381300833_2_2_m_0/attempts/attempt_1326381300833_2_2_m_0_0
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 691
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<taskAttempt>
  <startTime>1326381450680</startTime>
  <finishTime>1326381453318</finishTime>
  <elapsedTime>2638</elapsedTime>
  <progress>100.0</progress>
  <id>attempt_1326381300833_2_2_m_0_0</id>
  <rack>/98.139.92.0</rack>
  <state>SUCCEEDED</state>
  <nodeHttpAddress>host.domain.com:8042</nodeHttpAddress>
  <diagnostics/>
  <type>MAP</type>
  <assignedContainerId>container_1326381300833_0002_01_000002</assignedContainerId>
</taskAttempt>

任务尝试计数器 API

使用任务尝试计数器 API，您可以对象一个资源集合，这些资源表示该任务尝试的所有计数器。

URI

支持的 HTTP 操作

  • GET

支持的查询参数

  None

jobTaskAttemptCounters 对象的元素

项目 数据类型 说明
id string 任务尝试 ID
taskAttemptcounterGroup 任务尝试计数器组对象数组（JSON）/零个或多个任务尝试计数器组对象（XML） 任务尝试计数器组对象的集合

taskAttemptCounterGroup 对象的元素

项目 数据类型 说明
counterGroupName string 计数器组名称
counter counter 对象数组（JSON）/零个或多个 counter 对象（XML） 计数器对象集合

counter 对象的元素

项目 数据类型 说明
name string 计数器名称
value long 计数器的值

响应示例

JSON 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks/task_1326381300833_2_2_m_0/attempts/attempt_1326381300833_2_2_m_0_0/counters

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/json
  Transfer-Encoding: chunked
  Server: Jetty(6.1.26)

响应正文

{
   "jobTaskAttemptCounters" : {
      "taskAttemptCounterGroup" : [
         {
            "counterGroupName" : "org.apache.hadoop.mapreduce.FileSystemCounter",
            "counter" : [
               {
                  "value" : 2363,
                  "name" : "FILE_BYTES_READ"
               },
               {
                  "value" : 54372,
                  "name" : "FILE_BYTES_WRITTEN"
               },
               {
                  "value" : 0,
                  "name" : "FILE_READ_OPS"
               },
               {
                  "value" : 0,
                  "name" : "FILE_LARGE_READ_OPS"
               },
               {
                  "value" : 0,
                  "name" : "FILE_WRITE_OPS"
               },
               {
                  "value" : 0,
                  "name" : "HDFS_BYTES_READ"
               },
               {
                  "value" : 0,
                  "name" : "HDFS_BYTES_WRITTEN"
               },
              {
                  "value" : 0,
                  "name" : "HDFS_READ_OPS"
               },
               {
                  "value" : 0,
                  "name" : "HDFS_LARGE_READ_OPS"
               },
               {
                  "value" : 0,
                  "name" : "HDFS_WRITE_OPS"
               }
            ]
         },
         {
            "counterGroupName" : "org.apache.hadoop.mapreduce.TaskCounter",
            "counter" : [
               {
                  "value" : 0,
                  "name" : "COMBINE_INPUT_RECORDS"
               },
               {
                  "value" : 0,
                  "name" : "COMBINE_OUTPUT_RECORDS"
               },
               {
                  "value" : 460,
                  "name" : "REDUCE_INPUT_GROUPS"
               },
               {
                  "value" : 2235,
                  "name" : "REDUCE_SHUFFLE_BYTES"
               },
               {
                  "value" : 460,
                  "name" : "REDUCE_INPUT_RECORDS"
               },
               {
                  "value" : 0,
                  "name" : "REDUCE_OUTPUT_RECORDS"
               },
               {
                  "value" : 0,
                  "name" : "SPILLED_RECORDS"
               },
               {
                  "value" : 1,
                  "name" : "SHUFFLED_MAPS"
               },
               {
                  "value" : 0,
                  "name" : "FAILED_SHUFFLE"
               },
               {
                  "value" : 1,
                  "name" : "MERGED_MAP_OUTPUTS"
               },
               {
                  "value" : 26,
                  "name" : "GC_TIME_MILLIS"
               },
               {
                  "value" : 860,
                  "name" : "CPU_MILLISECONDS"
               },
               {
                  "value" : 107839488,
                  "name" : "PHYSICAL_MEMORY_BYTES"
               },
               {
                  "value" : 1123147776,
                  "name" : "VIRTUAL_MEMORY_BYTES"
               },
               {
                  "value" : 57475072,
                  "name" : "COMMITTED_HEAP_BYTES"
               }
            ]
         },
         {
            "counterGroupName" : "Shuffle Errors",
            "counter" : [
               {
                  "value" : 0,
                  "name" : "BAD_ID"
               },
               {
                  "value" : 0,
                  "name" : "CONNECTION"
               },
               {
                  "value" : 0,
                  "name" : "IO_ERROR"
               },
               {
                  "value" : 0,
                  "name" : "WRONG_LENGTH"
               },
               {
                  "value" : 0,
                  "name" : "WRONG_MAP"
               },
               {
                  "value" : 0,
                  "name" : "WRONG_REDUCE"
               }
            ]
         },
         {
            "counterGroupName" : "org.apache.hadoop.mapreduce.lib.output.FileOutputFormatCounter",
            "counter" : [
               {
                  "value" : 0,
                  "name" : "BYTES_WRITTEN"
               }
            ]
         }
      ],
      "id" : "attempt_1326381300833_2_2_m_0_0"
   }
}

XML 响应

HTTP 请求

  GET http://history-server-http-address:port/ws/v1/history/mapreduce/jobs/job_1326381300833_2_2/tasks/task_1326381300833_2_2_m_0/attempts/attempt_1326381300833_2_2_m_0_0/counters
  Accept: application/xml

响应标头

  HTTP/1.1 200 OK
  Content-Type: application/xml
  Content-Length: 2735
  Server: Jetty(6.1.26)

响应正文

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<jobTaskAttemptCounters>
  <id>attempt_1326381300833_2_2_m_0_0</id>
  <taskAttemptCounterGroup>
    <counterGroupName>org.apache.hadoop.mapreduce.FileSystemCounter</counterGroupName>
    <counter>
      <name>FILE_BYTES_READ</name>
      <value>2363</value>
    </counter>
    <counter>
      <name>FILE_BYTES_WRITTEN</name>
      <value>54372</value>
    </counter>
    <counter>
      <name>FILE_READ_OPS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>FILE_LARGE_READ_OPS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>FILE_WRITE_OPS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>HDFS_BYTES_READ</name>
      <value>0</value>
    </counter>
    <counter>
      <name>HDFS_BYTES_WRITTEN</name>
      <value>0</value>
    </counter>
    <counter>
      <name>HDFS_READ_OPS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>HDFS_LARGE_READ_OPS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>HDFS_WRITE_OPS</name>
      <value>0</value>
    </counter>
  </taskAttemptCounterGroup>
  <taskAttemptCounterGroup>
    <counterGroupName>org.apache.hadoop.mapreduce.TaskCounter</counterGroupName>
    <counter>
      <name>COMBINE_INPUT_RECORDS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>COMBINE_OUTPUT_RECORDS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>REDUCE_INPUT_GROUPS</name>
      <value>460</value>
    </counter>
    <counter>
      <name>REDUCE_SHUFFLE_BYTES</name>
      <value>2235</value>
    </counter>
    <counter>
      <name>REDUCE_INPUT_RECORDS</name>
      <value>460</value>
    </counter>
    <counter>
      <name>REDUCE_OUTPUT_RECORDS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>SPILLED_RECORDS</name>
      <value>0</value>
    </counter>
    <counter>
      <name>SHUFFLED_MAPS</name>
      <value>1</value>
    </counter>
    <counter>
      <name>FAILED_SHUFFLE</name>
      <value>0</value>
    </counter>
    <counter>
      <name>MERGED_MAP_OUTPUTS</name>
      <value>1</value>
    </counter>
    <counter>
      <name>GC_TIME_MILLIS</name>
      <value>26</value>
    </counter>
    <counter>
      <name>CPU_MILLISECONDS</name>
      <value>860</value>
    </counter>
    <counter>
      <name>PHYSICAL_MEMORY_BYTES</name>
      <value>107839488</value>
    </counter>
    <counter>
      <name>VIRTUAL_MEMORY_BYTES</name>
      <value>1123147776</value>
    </counter>
    <counter>
      <name>COMMITTED_HEAP_BYTES</name>
      <value>57475072</value>
    </counter>
  </taskAttemptCounterGroup>
  <taskAttemptCounterGroup>
    <counterGroupName>Shuffle Errors</counterGroupName>
    <counter>
      <name>BAD_ID</name>
      <value>0</value>
    </counter>
    <counter>
      <name>CONNECTION</name>
      <value>0</value>
    </counter>
    <counter>
      <name>IO_ERROR</name>
      <value>0</value>
    </counter>
    <counter>
      <name>WRONG_LENGTH</name>
      <value>0</value>
    </counter>
    <counter>
      <name>WRONG_MAP</name>
      <value>0</value>
    </counter>
    <counter>
      <name>WRONG_REDUCE</name>
      <value>0</value>
    </counter>
  </taskAttemptCounterGroup>
  <taskAttemptCounterGroup>
    <counterGroupName>org.apache.hadoop.mapreduce.lib.output.FileOutputFormatCounter</counterGroupName>
    <counter>
      <name>BYTES_WRITTEN</name>
      <value>0</value>
    </counter>
  </taskAttemptCounterGroup>
</jobTaskAttemptCounters>