hive跑mapreduce报java.lang.RuntimeException: Error in configuring object

Posted 2022-04-16 yueweimian

写于2016.7月

最近项目需要在hbase上做统计分析，在本机上装了hive，结果跑小批量数据sum时报错：

hive> select count(*) from page_view;
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
  set mapreduce.job.reduces=<number>
Starting Job = job_1468481753104_0014, Tracking URL = http://wangkai8:8088/proxy/application_1468481753104_0014/
Kill Command = /Users/wangkai8/app/hadoop-2.3.0-cdh5/bin/hadoop job  -kill job_1468481753104_0014
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2016-07-14 18:38:11,888 Stage-1 map = 100%,  reduce = 100%
Ended Job = job_1468481753104_0014 with errors
Error during job, obtaining debugging information...
Examining task ID: task_1468481753104_0014_m_000000 (and more) from job job_1468481753104_0014

Task with the most failures(1):
-----
Task ID:
  task_1468481753104_0014_r_000000

URL:
  http://0.0.0.0:8088/taskdetails.jsp?jobid=job_1468481753104_0014&tipid=task_1468481753104_0014_r_000000
-----
Diagnostic Messages for this Task:
java.lang.RuntimeException: Error in configuring object
    at org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:109)
    at org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:75)
    at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:133)
    at org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:409)
    at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:392)
    at org.apache.hadoop.mapred.LocalContainerLauncher$SubtaskRunner.runSubtask(LocalContainerLauncher.java:351)
    at org.apache.hadoop.mapred.LocalContainerLauncher$SubtaskRunner.run(LocalContainerLauncher.java:232)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.reflect.InvocationTargetException
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:106)
    ... 7 more
Caused by: java.lang.NullPointerException
    at org.apache.hadoop.hive.ql.exec.mr.ExecReducer.configure(ExecReducer.java:135)
    ... 12 more


FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask
MapReduce Jobs Launched:
Job 0: Map: 1  Reduce: 1   HDFS Read: 499 HDFS Write: 218201 FAIL
Total MapReduce CPU Time Spent: 0 msec
hive>

查看yarn日志，一样也是空指针异常，还有个提示是No plan file found: hdfs://...

2016-07-14 15:37:15,211 INFO [uber-SubtaskRunner] org.apache.hadoop.hive.ql.exec.mr.ObjectCache: Ignoring retrieval request: __REDUCE_PLAN__
2016-07-14 15:37:15,211 INFO [uber-SubtaskRunner] org.apache.hadoop.hive.ql.exec.Utilities: No plan file found: hdfs://wangkai8/tmp/hive-wangkai8/hive_2016-07-14_15-37-06_635_5512340937878595139-1/-mr-10004/1e60df26-2b73-4384-adbc-651342dd48f8/reduce.xml
2016-07-14 15:37:15,211 INFO [uber-SubtaskRunner] org.apache.hadoop.hive.ql.exec.mr.ObjectCache: Ignoring cache key: __REDUCE_PLAN__
2016-07-14 15:37:15,212 WARN [uber-SubtaskRunner] org.apache.hadoop.mapred.LocalContainerLauncher: Exception running local (uberized) ‘child‘ : java.lang.RuntimeException: Error in configuring object
    at org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:109)
    at org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:75)
    at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:133)
    at org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:409)
    at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:392)
    at org.apache.hadoop.mapred.LocalContainerLauncher$SubtaskRunner.runSubtask(LocalContainerLauncher.java:351)
    at org.apache.hadoop.mapred.LocalContainerLauncher$SubtaskRunner.run(LocalContainerLauncher.java:232)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.reflect.InvocationTargetException
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:106)
    ... 7 more
Caused by: java.lang.NullPointerException
    at org.apache.hadoop.hive.ql.exec.mr.ExecReducer.configure(ExecReducer.java:132)
    ... 12 more

2016-07-14 15:37:15,212 INFO [uber-SubtaskRunner] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Status update from attempt_1468481753104_0002_r_000000_0
2016-07-14 15:37:15,212 INFO [uber-SubtaskRunner] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Progress of TaskAttempt attempt_1468481753104_0002_r_000000_0 is : 0.0
2016-07-14 15:37:15,212 INFO [uber-SubtaskRunner] org.apache.hadoop.mapred.Task: Runnning cleanup for the task
2016-07-14 15:37:15,212 INFO [uber-SubtaskRunner] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Diagnostics report from attempt_1468481753104_0002_r_000000_0: java.lang.RuntimeException: Error in configuring object
    at org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:109)
    at org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:75)
    at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:133)
    at org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:409)
    at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:392)
    at org.apache.hadoop.mapred.LocalContainerLauncher$SubtaskRunner.runSubtask(LocalContainerLauncher.java:351)
    at org.apache.hadoop.mapred.LocalContainerLauncher$SubtaskRunner.run(LocalContainerLauncher.java:232)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.reflect.InvocationTargetException
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:106)
    ... 7 more
Caused by: java.lang.NullPointerException
    at org.apache.hadoop.hive.ql.exec.mr.ExecReducer.configure(ExecReducer.java:132)
    ... 12 more

2016-07-14 15:37:15,213 INFO [uber-SubtaskRunner] org.apache.hadoop.mapred.LocalContainerLauncher: Processing the event EventType: CONTAINER_REMOTE_CLEANUP for container container_1468481753104_0002_01_000001 taskAttempt attempt_1468481753104_0002_m_000000_0
2016-07-14 15:37:15,213 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1468481753104_0002_r_000000_0: java.lang.RuntimeException: Error in configuring object
    at org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:109)
    at org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:75)
    at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:133)
    at org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:409)
    at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:392)
    at org.apache.hadoop.mapred.LocalContainerLauncher$SubtaskRunner.runSubtask(LocalContainerLauncher.java:351)
    at org.apache.hadoop.mapred.LocalContainerLauncher$SubtaskRunner.run(LocalContainerLauncher.java:232)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.reflect.InvocationTargetException
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:106)
    ... 7 more
Caused by: java.lang.NullPointerException
    at org.apache.hadoop.hive.ql.exec.mr.ExecReducer.configure(ExecReducer.java:132)
    ... 12 more

 

查看hive源码，发现gWork为null，导致空指针异常

    //src: org.apache.hadoop.hive.ql.exec.mr.ExecReducer#configure

    ObjectCache cache = ObjectCacheFactory.getCache(jc);
    ReduceWork gWork = (ReduceWork) cache.retrieve(PLAN_KEY);
    if (gWork == null) 
      gWork = Utilities.getReduceWork(job);
      cache.cache(PLAN_KEY, gWork);
     else 
      Utilities.setReduceWork(job, gWork);
    
    reducer = gWork.getReducer(); //gWork为null，导致空指针

接着查看Utilities.getReduceWork(job)方法，最后跟到org.apache.hadoop.hive.ql.exec.Utilities#getBaseWork：

  /**
   * Returns the Map or Reduce plan
   * Side effect: the BaseWork returned is also placed in the gWorkMap
   * @param conf
   * @param name
   * @return BaseWork based on the name supplied will return null if name is null
   * @throws RuntimeException if the configuration files are not proper or if plan can not be loaded
   */
  private static BaseWork getBaseWork(Configuration conf, String name) 
    BaseWork gWork = null;
    Path path = null;
    InputStream in = null;
    try 
      path = getPlanPath(conf, name);
      assert path != null;
      if (!gWorkMap.containsKey(path)) 
        Path localPath;
        if (ShimLoader.getHadoopShims().isLocalMode(conf)) 
          localPath = path;
         else 
          localPath = new Path(name);
        

        if (HiveConf.getBoolVar(conf, ConfVars.HIVE_RPC_QUERY_PLAN)) 
          LOG.debug("Loading plan from string: "+path.toUri().getPath());
          String planString = conf.get(path.toUri().getPath());
          if (planString == null) 
            LOG.info("Could not find plan string in conf");
            return null;
          
          byte[] planBytes = Base64.decodeBase64(planString);
          in = new ByteArrayInputStream(planBytes);
          in = new InflaterInputStream(in);
         else 
          in = new FileInputStream(localPath.toUri().getPath());
        

        if(MAP_PLAN_NAME.equals(name))
          if (ExecMapper.class.getName().equals(conf.get(MAPRED_MAPPER_CLASS)))
            gWork = deserializePlan(in, MapWork.class, conf);
           else if(RCFileMergeMapper.class.getName().equals(conf.get(MAPRED_MAPPER_CLASS))) 
            gWork = deserializePlan(in, MergeWork.class, conf);
           else if(ColumnTruncateMapper.class.getName().equals(conf.get(MAPRED_MAPPER_CLASS))) 
            gWork = deserializePlan(in, ColumnTruncateWork.class, conf);
           else if(PartialScanMapper.class.getName().equals(conf.get(MAPRED_MAPPER_CLASS))) 
            gWork = deserializePlan(in, PartialScanWork.class,conf);
           else 
            throw new RuntimeException("unable to determine work from configuration ."
                + MAPRED_MAPPER_CLASS + " was "+ conf.get(MAPRED_MAPPER_CLASS)) ;
          
         else if (REDUCE_PLAN_NAME.equals(name)) 
          if(ExecReducer.class.getName().equals(conf.get(MAPRED_REDUCER_CLASS))) 
            gWork = deserializePlan(in, ReduceWork.class, conf);
           else 
            throw new RuntimeException("unable to determine work from configuration ."
                + MAPRED_REDUCER_CLASS +" was "+ conf.get(MAPRED_REDUCER_CLASS)) ;
          
        
        gWorkMap.put(path, gWork);
       else 
        LOG.debug("Found plan in cache.");
        gWork = gWorkMap.get(path);
      
      return gWork;
     catch (FileNotFoundException fnf) 
      // happens. e.g.: no reduce work.
      LOG.info("No plan file found: "+path);
      return null;
     catch (Exception e) 
      LOG.error("Failed to load plan: "+path, e);
      throw new RuntimeException(e);
     finally 
      if (in != null) 
        try 
          in.close();
         catch (IOException cantBlameMeForTrying)  
      
    
  

 再结合yarn报错信息：2016-07-14 15:37:15,211 INFO [uber-SubtaskRunner] org.apache.hadoop.hive.ql.exec.Utilities: No plan file found: hdfs://wangkai8/tmp/hive-wangkai8/hive_2016-07-14_15-37-06_635_5512340937878595139-1/-mr-10004/1e60df26-2b73-4384-adbc-651342dd48f8/reduce.xml

很明显reduce.xml找不到，报FileNotFoundException：No plan file found，但通过dfs fs -ls hdfs://wangkai8/tmp/hive-wangkai8/hive_2016-07-14_15-37-06_635_5512340937878595139-1/-mr-10004/1e60df26-2b73-4384-adbc-651342dd48f8/reduce.xml查看文件，文件的确是存在的，文件存在还报这个错，那这个问题就很诡异了。

 接着在hive中映射一张hbase表，此表记录较多，大概50万条，同样执行select count操作：

hive> select count(*) from qry_ins_user;
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
  set mapreduce.job.reduces=<number>
Starting Job = job_1468481753104_0016, Tracking URL = http://wangkai8:8088/proxy/application_1468481753104_0016/
Kill Command = /Users/wangkai8/app/hadoop-2.3.0-cdh5/bin/hadoop job  -kill job_1468481753104_0016
Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 1
2016-07-14 19:42:16,196 Stage-1 map = 0%,  reduce = 0%
2016-07-14 19:42:30,570 Stage-1 map = 50%,  reduce = 0%
2016-07-14 19:42:32,627 Stage-1 map = 100%,  reduce = 0%
2016-07-14 19:42:38,792 Stage-1 map = 100%,  reduce = 100%
Ended Job = job_1468481753104_0016
MapReduce Jobs Launched:
Job 0: Map: 2  Reduce: 1   HDFS Read: 566 HDFS Write: 7 SUCCESS
Total MapReduce CPU Time Spent: 0 msec
OK
509844
Time taken: 34.023 seconds, Fetched: 1 row(s)
hive>

 这个居然能执行成功，3条记录执行就报错？这个问题不能不说更诡异了。后面各种调试，最后从AppMaster日志中得到关键信息：

Log Type: syslog
Log Length: 155414
2016-07-14 18:40:17,962 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: Created MRAppMaster for application appattempt_1468481753104_0015_000001
2016-07-14 18:40:18,211 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
2016-07-14 18:40:18,230 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
2016-07-14 18:40:18,327 WARN [main] org.apache.hadoop.util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2016-07-14 18:40:18,340 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: Executing with tokens:
2016-07-14 18:40:18,340 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: Kind: YARN_AM_RM_TOKEN, Service: , Ident: ([email protected])
2016-07-14 18:40:18,363 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: The specific max attempts: 2 for application: 15. Attempt num: 1 is last retry: false
2016-07-14 18:40:18,452 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: dfs.datanode.data.dir;  Ignoring.
2016-07-14 18:40:18,454 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
2016-07-14 18:40:18,460 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: dfs.namenode.name.dir;  Ignoring.
2016-07-14 18:40:18,464 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
2016-07-14 18:40:18,837 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: OutputCommitter set in config org.apache.hadoop.hive.shims.HadoopShimsSecure$NullOutputCommitter
2016-07-14 18:40:18,839 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: OutputCommitter is org.apache.hadoop.hive.shims.HadoopShimsSecure$NullOutputCommitter
2016-07-14 18:40:18,876 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.jobhistory.EventType for class org.apache.hadoop.mapreduce.jobhistory.JobHistoryEventHandler
2016-07-14 18:40:18,877 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.job.event.JobEventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$JobEventDispatcher
2016-07-14 18:40:18,877 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.job.event.TaskEventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$TaskEventDispatcher
2016-07-14 18:40:18,878 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$TaskAttemptEventDispatcher
2016-07-14 18:40:18,878 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.commit.CommitterEventType for class org.apache.hadoop.mapreduce.v2.app.commit.CommitterEventHandler
2016-07-14 18:40:18,882 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.speculate.Speculator$EventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$SpeculatorEventDispatcher
2016-07-14 18:40:18,882 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.rm.ContainerAllocator$EventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$ContainerAllocatorRouter
2016-07-14 18:40:18,883 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncher$EventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$ContainerLauncherRouter
2016-07-14 18:40:18,940 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.job.event.JobFinishEvent$Type for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$JobFinishEventHandler
2016-07-14 18:40:19,105 INFO [main] org.apache.hadoop.metrics2.impl.MetricsConfig: loaded properties from hadoop-metrics2.properties
2016-07-14 18:40:19,147 INFO [main] org.apache.hadoop.metrics2.impl.MetricsSystemImpl: Scheduled snapshot period at 10 second(s).
2016-07-14 18:40:19,147 INFO [main] org.apache.hadoop.metrics2.impl.MetricsSystemImpl: MRAppMaster metrics system started
2016-07-14 18:40:19,153 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Adding job token for job_1468481753104_0015 to jobTokenSecretManager
2016-07-14 18:40:19,239 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Uberizing job job_1468481753104_0015: 1m+1r tasks (132 input bytes) will run sequentially on single node.
2016-07-14 18:40:19,257 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Input size for job job_1468481753104_0015 = 132. Number of splits = 1
2016-07-14 18:40:19,258 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Number of reduces for job job_1468481753104_0015 = 1
2016-07-14 18:40:19,258 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: job_1468481753104_0015Job Transitioned from NEW to INITED
2016-07-14 18:40:19,258 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: MRAppMaster uberizing job job_1468481753104_0015 in local container ("uber-AM") on node wangkai8:59734.
2016-07-14 18:40:19,280 INFO [main] org.apache.hadoop.ipc.CallQueueManager: Using callQueue class java.util.concurrent.LinkedBlockingQueue
2016-07-14 18:40:19,286 INFO [Socket Reader #1 for port 57486] org.apache.hadoop.ipc.Server: Starting Socket Reader #1 for port 57486
2016-07-14 18:40:19,301 INFO [main] org.apache.hadoop.yarn.factories.impl.pb.RpcServerFactoryPBImpl: Adding protocol org.apache.hadoop.mapreduce.v2.api.MRClientProtocolPB to the server

2016-07-14 18:40:19,258 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: MRAppMaster uberizing job job_1468481753104_0015 in local container ("uber-AM") on node wangkai8:59734.
reduce跑在local模式，难道50万记录的表跑在集群模式？查看50万条记录对应AppMaster日志：

Log Type: syslog
Log Length: 47618
2016-07-14 19:42:13,007 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: Created MRAppMaster for application appattempt_1468481753104_0016_000001
2016-07-14 19:42:13,254 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
2016-07-14 19:42:13,277 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
2016-07-14 19:42:13,366 WARN [main] org.apache.hadoop.util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2016-07-14 19:42:13,380 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: Executing with tokens:
2016-07-14 19:42:13,380 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: Kind: YARN_AM_RM_TOKEN, Service: , Ident: ([email protected])
2016-07-14 19:42:13,407 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: The specific max attempts: 2 for application: 16. Attempt num: 1 is last retry: false
2016-07-14 19:42:13,499 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: dfs.datanode.data.dir;  Ignoring.
2016-07-14 19:42:13,502 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
2016-07-14 19:42:13,508 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: dfs.namenode.name.dir;  Ignoring.
2016-07-14 19:42:13,511 WARN [main] org.apache.hadoop.conf.Configuration: job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
2016-07-14 19:42:14,025 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: OutputCommitter set in config org.apache.hadoop.hive.shims.HadoopShimsSecure$NullOutputCommitter
2016-07-14 19:42:14,027 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: OutputCommitter is org.apache.hadoop.hive.shims.HadoopShimsSecure$NullOutputCommitter
2016-07-14 19:42:14,071 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.jobhistory.EventType for class org.apache.hadoop.mapreduce.jobhistory.JobHistoryEventHandler
2016-07-14 19:42:14,072 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.job.event.JobEventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$JobEventDispatcher
2016-07-14 19:42:14,073 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.job.event.TaskEventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$TaskEventDispatcher
2016-07-14 19:42:14,073 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$TaskAttemptEventDispatcher
2016-07-14 19:42:14,074 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.commit.CommitterEventType for class org.apache.hadoop.mapreduce.v2.app.commit.CommitterEventHandler
2016-07-14 19:42:14,080 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.speculate.Speculator$EventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$SpeculatorEventDispatcher
2016-07-14 19:42:14,081 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.rm.ContainerAllocator$EventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$ContainerAllocatorRouter
2016-07-14 19:42:14,082 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncher$EventType for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$ContainerLauncherRouter
2016-07-14 19:42:14,159 INFO [main] org.apache.hadoop.yarn.event.AsyncDispatcher: Registering class org.apache.hadoop.mapreduce.v2.app.job.event.JobFinishEvent$Type for class org.apache.hadoop.mapreduce.v2.app.MRAppMaster$JobFinishEventHandler
2016-07-14 19:42:14,409 INFO [main] org.apache.hadoop.metrics2.impl.MetricsConfig: loaded properties from hadoop-metrics2.properties
2016-07-14 19:42:14,480 INFO [main] org.apache.hadoop.metrics2.impl.MetricsSystemImpl: Scheduled snapshot period at 10 second(s).
2016-07-14 19:42:14,480 INFO [main] org.apache.hadoop.metrics2.impl.MetricsSystemImpl: MRAppMaster metrics system started
2016-07-14 19:42:14,487 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Adding job token for job_1468481753104_0016 to jobTokenSecretManager
2016-07-14 19:42:14,603 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Not uberizing job_1468481753104_0016 because: too much input;
2016-07-14 19:42:14,628 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Input size for job job_1468481753104_0016 = 446693376. Number of splits = 2
2016-07-14 19:42:14,630 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Number of reduces for job job_1468481753104_0016 = 1
2016-07-14 19:42:14,630 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: job_1468481753104_0016Job Transitioned from NEW to INITED
2016-07-14 19:42:14,631 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: MRAppMaster launching normal, non-uberized, multi-container job job_1468481753104_0016.
2016-07-14 19:42:14,666 INFO [main] org.apache.hadoop.ipc.CallQueueManager: Using callQueue class java.util.concurrent.LinkedBlockingQueue
2016-07-14 19:42:14,676 INFO [Socket Reader #1 for port 59418] org.apache.hadoop.ipc.Server: Starting Socket Reader #1 for port 59418
2016-07-14 19:42:14,698 INFO [main] org.apache.hadoop.yarn.factories.impl.pb.RpcServerFactoryPBImpl: Adding protocol org.apache.hadoop.mapreduce.v2.api.MRClientProtocolPB to the server

2016-07-14 19:42:14,603 INFO [main] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Not uberizing job_1468481753104_0016 because: too much input;
好吧，果然是集群模式，那就查看org.apache.hadoop.mapreduce.v2.app.job.impl.JobImp源码，看看local、集群模式是怎么决定的：

  /**
   * Decide whether job can be run in uber mode based on various criteria.
   * @param dataInputLength Total length for all splits
   */
  private void makeUberDecision(long dataInputLength) 
    //FIXME:  need new memory criterion for uber-decision (oops, too late here;
    // until AM-resizing supported,
    // must depend on job client to pass fat-slot needs)
    // these are no longer "system" settings, necessarily; user may override
    int sysMaxMaps = conf.getInt(MRJobConfig.JOB_UBERTASK_MAXMAPS, 9);

    int sysMaxReduces = conf.getInt(MRJobConfig.JOB_UBERTASK_MAXREDUCES, 1);

    long sysMaxBytes = conf.getLong(MRJobConfig.JOB_UBERTASK_MAXBYTES,
        fs.getDefaultBlockSize(this.remoteJobSubmitDir)); // FIXME: this is wrong; get FS from
                                   // [File?]InputFormat and default block size
                                   // from that

    long sysMemSizeForUberSlot =
        conf.getInt(MRJobConfig.MR_AM_VMEM_MB,
            MRJobConfig.DEFAULT_MR_AM_VMEM_MB);

    long sysCPUSizeForUberSlot =
        conf.getInt(MRJobConfig.MR_AM_CPU_VCORES,
            MRJobConfig.DEFAULT_MR_AM_CPU_VCORES);

    boolean uberEnabled =
        conf.getBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
    boolean smallNumMapTasks = (numMapTasks <= sysMaxMaps);
    boolean smallNumReduceTasks = (numReduceTasks <= sysMaxReduces);
    boolean smallInput = (dataInputLength <= sysMaxBytes);
    // ignoring overhead due to UberAM and statics as negligible here:
    boolean smallMemory =
        ( (Math.max(conf.getLong(MRJobConfig.MAP_MEMORY_MB, 0),
            conf.getLong(MRJobConfig.REDUCE_MEMORY_MB, 0))
            <= sysMemSizeForUberSlot)
            || (sysMemSizeForUberSlot == JobConf.DISABLED_MEMORY_LIMIT));
    boolean smallCpu =
        (
            Math.max(
                conf.getInt(
                    MRJobConfig.MAP_CPU_VCORES, 
                    MRJobConfig.DEFAULT_MAP_CPU_VCORES), 
                conf.getInt(
                    MRJobConfig.REDUCE_CPU_VCORES, 
                    MRJobConfig.DEFAULT_REDUCE_CPU_VCORES)) 
             <= sysCPUSizeForUberSlot
        );
    boolean notChainJob = !isChainJob(conf);

    // User has overall veto power over uberization, or user can modify
    // limits (overriding system settings and potentially shooting
    // themselves in the head).  Note that ChainMapper/Reducer are
    // fundamentally incompatible with MR-1220; they employ a blocking
    // queue between the maps/reduces and thus require parallel execution,
    // while "uber-AM" (MR AM + LocalContainerLauncher) loops over tasks
    // and thus requires sequential execution.
    isUber = uberEnabled && smallNumMapTasks && smallNumReduceTasks
        && smallInput && smallMemory && smallCpu 
        && notChainJob;

    if (isUber) 
      LOG.info("Uberizing job " + jobId + ": " + numMapTasks + "m+"
          + numReduceTasks + "r tasks (" + dataInputLength
          + " input bytes) will run sequentially on single node.");

      // make sure reduces are scheduled only after all map are completed
      conf.setFloat(MRJobConfig.COMPLETED_MAPS_FOR_REDUCE_SLOWSTART,
                        1.0f);
      // uber-subtask attempts all get launched on same node; if one fails,
      // probably should retry elsewhere, i.e., move entire uber-AM:  ergo,
      // limit attempts to 1 (or at most 2?  probably not...)
      conf.setInt(MRJobConfig.MAP_MAX_ATTEMPTS, 1);
      conf.setInt(MRJobConfig.REDUCE_MAX_ATTEMPTS, 1);

      // disable speculation
      conf.setBoolean(MRJobConfig.MAP_SPECULATIVE, false);
      conf.setBoolean(MRJobConfig.REDUCE_SPECULATIVE, false);
     else 
      StringBuilder msg = new StringBuilder();
      msg.append("Not uberizing ").append(jobId).append(" because:");
      if (!uberEnabled)
        msg.append(" not enabled;");
      if (!smallNumMapTasks)
        msg.append(" too many maps;");
      if (!smallNumReduceTasks)
        msg.append(" too many reduces;");
      if (!smallInput)
        msg.append(" too much input;");
      if (!smallMemory)
        msg.append(" too much RAM;");
      if (!notChainJob)
        msg.append(" chainjob;");
      LOG.info(msg.toString());
    
  

mapreduce是否跑在local模式由7个变量决定：uberEnabled && smallNumMapTasks && smallNumReduceTasks&& smallInput && smallMemory && smallCpu && notChainJob，只有这7个变量同时满足才能跑在local模式。

首先要满足uberEnabled为true，看看uberEnable定义：uberEnabled = conf.getBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false)，MRJobConfig.JOB_UBERTASK_ENABLE对应配置项为mapreduce.job.ubertask.enable（mapred-site.xml）,说明mapreduce.job.ubertask.enable配置为true，查看mapred-site.xml配置文件，果然是true

<property>
  <name>mapreduce.job.ubertask.enable</name>
  <value>true</value>
  <description>Whether to enable the small-jobs "ubertask" optimization,
  which runs "sufficiently small" jobs sequentially within a single JVM.
  "Small" is defined by the following maxmaps, maxreduces, and maxbytes
  settings.  Users may override this value.
  </description>
</property>

问题找到了就好办，第一种办法直接把mapreduce.job.ubertask.enable改为false，都走集群模式；

第二种办法是mapreduce.job.ubertask.enable还是为true，继续分析reduce.xml文件找不到的原因，还是查看读取reduce.xml那块：org.apache.hadoop.hive.ql.exec.Utilities#getBaseWork

        if (HiveConf.getBoolVar(conf, ConfVars.HIVE_RPC_QUERY_PLAN)) 
          LOG.debug("Loading plan from string: "+path.toUri().getPath());
          String planString = conf.get(path.toUri().getPath());
          if (planString == null) 
            LOG.info("Could not find plan string in conf");
            return null;
          
          byte[] planBytes = Base64.decodeBase64(planString);
          in = new ByteArrayInputStream(planBytes);
          in = new InflaterInputStream(in);
         else 
          in = new FileInputStream(localPath.toUri().getPath());
        

可见hive执行计划文件由ConfVars.HIVE_RPC_QUERY_PLAN决定是通过rpc读集群上的文件还是读本地文件，默认为本地文件。