Hive
  1. Hive
  2. HIVE-7782

tez default engine not overridden by hive.execution.engine=mr in hive cli session

    Details

    • Type: Bug Bug
    • Status: Open
    • Priority: Minor Minor
    • Resolution: Unresolved
    • Affects Version/s: None
    • Fix Version/s: None
    • Component/s: CLI, Tez
    • Labels:
    • Environment:

      HDP2.1

      Description

      I've deployed hive.execution.engine=tez as the default on my secondary HDP cluster I find that hive cli interactive sessions where I do

      set hive.execution.engine=mr
      

      still execute with Tez as shown in the Resource Manager applications view. Now this may make sense since it's connected a Tez session by that point but it's also misleading because the job progress output in the cli changes to look like MapReduce rather than Tez and the query time is increased from 8 to to 15-16 secs but still less than the 25-30+ secs I usually see with MR. The Resource Manager shows both of these jobs as TEZ application type regardless of setting hive.execution.engine=mr. Is this a bug in the way Hive is submitting the job (Tez vs MR) or a bug in the way the RM is reporting it?

      hive
      
      Logging initialized using configuration in file:/etc/hive/conf.dist/hive-log4j.properties
      hive> select count(*) from sample_07;
      Query ID = hari_20140819164848_c03824c7-0e76-4507-b619-6a22cb0fbc4c
      Total jobs = 1
      Launching Job 1 out of 1
      
      
      Status: Running (application id: application_1408444369445_0031)
      
      Map 1: -/-      Reducer 2: 0/1
      Map 1: 0/1      Reducer 2: 0/1
      Map 1: 0/1      Reducer 2: 0/1
      Map 1: 1/1      Reducer 2: 0/1
      Map 1: 1/1      Reducer 2: 1/1
      Status: Finished successfully
      OK
      823
      Time taken: 8.492 seconds, Fetched: 1 row(s)
      hive> set hive.execution.engine=mr;
      hive> select count(*) from sample_07;
      Query ID = hari_20140819164848_b620d990-b405-479c-be5b-d9616527cefe
      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_1408444369445_0032, Tracking URL = http://lonsl1101827-data.uk.net.intra:8088/proxy/application_1408444369445_0032/
      Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1408444369445_0032
      Hadoop job information for Stage-1: number of mappers: 0; number of reducers: 0
      2014-08-19 16:48:35,242 Stage-1 map = 0%,  reduce = 0%
      2014-08-19 16:48:40,539 Stage-1 map = 100%,  reduce = 0%
      2014-08-19 16:48:44,676 Stage-1 map = 100%,  reduce = 100%
      Ended Job = job_1408444369445_0032
      MapReduce Jobs Launched:
      Job 0:  HDFS Read: 0 HDFS Write: 0 SUCCESS
      Total MapReduce CPU Time Spent: 0 msec
      OK
      823
      Time taken: 16.579 seconds, Fetched: 1 row(s)
      

      If I exit hive shell and restart it instead using

      --hiveconf hive.execution.engine=mr

      to set before session is established then it does a proper MapReduce job according to RM and it also takes the longer expected 25 secs instead of the 8 in Tez or 15 in trying to do MR instead Tez session.

        Activity

        Hide
        Pala M Muthaia added a comment -

        I am investigating this.

        In a hive session, when the first Tez job is executed, internally the mapreduce.framework.name property is set to "yarn-tez" (See TezSessionState.open() method). This setting causes all native MR jobs in this session to be sent to Tez for execution.

        When the execution engine is changed to MR (i.e. set hive.execution.engine=mr), this setting change is not reverted. So, the subsequent query, which used to go to native MR, now goes to Tez instead (as MR on Tez). That's why its faster than native MR, but slower than native Tez.

        Show
        Pala M Muthaia added a comment - I am investigating this. In a hive session, when the first Tez job is executed, internally the mapreduce.framework.name property is set to "yarn-tez" (See TezSessionState.open() method). This setting causes all native MR jobs in this session to be sent to Tez for execution. When the execution engine is changed to MR (i.e. set hive.execution.engine=mr), this setting change is not reverted. So, the subsequent query, which used to go to native MR, now goes to Tez instead (as MR on Tez). That's why its faster than native MR, but slower than native Tez.

          People

          • Assignee:
            Unassigned
            Reporter:
            Hari Sekhon
          • Votes:
            0 Vote for this issue
            Watchers:
            2 Start watching this issue

            Dates

            • Created:
              Updated:

              Development