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From "Ferdinand Xu (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-15682) Eliminate per-row based dummy iterator creation
Date Wed, 08 Feb 2017 00:37:41 GMT

    [ https://issues.apache.org/jira/browse/HIVE-15682?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15857110#comment-15857110
] 

Ferdinand Xu commented on HIVE-15682:
-------------------------------------

Hi [~xuefuz]
{noformat}
select count(*) from (select request_lat from dwh.fact_trip where datestr > '2017-01-27'
order by request_lat) x;
Origin: 246.56, 342.78, 216.40, 216.587, 270.805, 449.232, 233.406 AVG: 282.25
patch: 125.21, 123.22, 166.31, 168.30, 120.428, 119.21, 120.385    AVG: 134.72
{noformat}
What kind of data scales do you use to evaluate the performance? We can evaluate this patch
using TPC-DS and TPCx-BB.

> Eliminate per-row based dummy iterator creation
> -----------------------------------------------
>
>                 Key: HIVE-15682
>                 URL: https://issues.apache.org/jira/browse/HIVE-15682
>             Project: Hive
>          Issue Type: Improvement
>          Components: Spark
>    Affects Versions: 2.2.0
>            Reporter: Xuefu Zhang
>            Assignee: Xuefu Zhang
>             Fix For: 2.2.0
>
>         Attachments: HIVE-15682.patch
>
>
> HIVE-15580 introduced a dummy iterator per input row which can be eliminated. This is
because {{SparkReduceRecordHandler}} is able to handle single key value pairs. We can refactor
this part of code 1. to remove the need for a iterator and 2. to optimize the code path for
per (key, value) based (instead of (key, value iterator)) processing. It would be also great
if we can measure the performance after the optimizations and compare to performance prior
to HIVE-15580.



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