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Posted to issues@hive.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2022/09/07 11:02:00 UTC

[jira] [Work logged] (HIVE-26437) dump unpartitioned Tables in parallel

     [ https://issues.apache.org/jira/browse/HIVE-26437?focusedWorklogId=806654&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-806654 ]

ASF GitHub Bot logged work on HIVE-26437:
-----------------------------------------

                Author: ASF GitHub Bot
            Created on: 07/Sep/22 11:01
            Start Date: 07/Sep/22 11:01
    Worklog Time Spent: 10m 
      Work Description: atsaonerk commented on PR #3444:
URL: https://github.com/apache/hive/pull/3444#issuecomment-1239240003

   Results of jmh performance benchmark test indicates an improvement in TableExport operation. If table is dumped in parallel manner instead of serial , the operation completes much faster giving. Below is the result seen when 500 tablexport operations are done both in serial and parallel manner.
   
   Result "org.apache.hive.benchmark.ql.exec.TableAndPartitionExportBench.BaseBench.parallel":
     N = 5
     mean =    640.862 ?(99.9%) 113.354 ms/op
   
   Result "org.apache.hive.benchmark.ql.exec.TableAndPartitionExportBench.BaseBench.serial":
     N = 5
     mean =  51697.322 ?(99.9%) 322.747 ms/op
   
   Benchmark                                                                     Mode  Cnt      Score             Error   Units
   TableAndPartitionExportBench.BaseBench.parallel    ss         5         640.862        ?         113.354  ms/op
   TableAndPartitionExportBench.BaseBench.serial       ss          5        51697.322     ?          322.747  ms/op




Issue Time Tracking
-------------------

            Worklog Id:     (was: 806654)
    Remaining Estimate: 0h
            Time Spent: 10m

> dump unpartitioned Tables in parallel
> -------------------------------------
>
>                 Key: HIVE-26437
>                 URL: https://issues.apache.org/jira/browse/HIVE-26437
>             Project: Hive
>          Issue Type: Improvement
>          Components: Hive
>            Reporter: Amit Saonerkar
>            Assignee: Amit Saonerkar
>            Priority: Major
>          Time Spent: 10m
>  Remaining Estimate: 0h
>




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