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From "Rui Li (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-9153) Evaluate CombineHiveInputFormat versus HiveInputFormat [Spark Branch]
Date Thu, 18 Dec 2014 12:45:13 GMT

    [ https://issues.apache.org/jira/browse/HIVE-9153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14251597#comment-14251597
] 

Rui Li commented on HIVE-9153:
------------------------------

Judging from the results, I think fewer mappers can improve overall performance, which is
true for both spark and tez. Problem is that, why spark is 60s slower than tez with same #
of mappers.
One possible reason is that we don't have data locality with CombineHiveInputFormat, which
is tracked by HIVE-8722.
I also noticed that the parallelism drops during execution (attach a screenshot later). This
may be due to the delay schedule mechanism of spark, which attempts to schedule tasks with
some locality first.

> Evaluate CombineHiveInputFormat versus HiveInputFormat [Spark Branch]
> ---------------------------------------------------------------------
>
>                 Key: HIVE-9153
>                 URL: https://issues.apache.org/jira/browse/HIVE-9153
>             Project: Hive
>          Issue Type: Sub-task
>          Components: Spark
>    Affects Versions: spark-branch
>            Reporter: Brock Noland
>            Assignee: Rui Li
>         Attachments: screenshot.PNG
>
>
> The default InputFormat is {{CombineHiveInputFormat}} and thus HOS uses this. However,
Tez uses {{HiveInputFormat}}. Since tasks are relatively cheap in Spark, it might make sense
for us to use {{HiveInputFormat}} as well. We should evaluate this on a query which has many
input splits such as {{select count(\*) from store_sales where something is not null}}.



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