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https://issues.apache.org/jira/browse/HIVE-9153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14251407#comment-14251407
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Rui Li commented on HIVE-9153:
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I used our cluster B to test this. Results show that CombineHiveInputFormat
still performs much better than HiveInputFormat for spark. The test query is
{code}select count(*) from store_sales where ss_sold_date_sk is not null;{code}
With CombineHiveInputFormat spark spawns 1252 mappers and the query finishes in
about 180s, while HiveInputFormat requires 13559 mappers and the query finishes
in about 700s.
I didn't find why Tez uses HiveInputFormat as default. But for Tez,
HiveInputFormat spawns 332 mappers while CombineHiveInputFormat spawns 1252. So
I think Tez has its own way to combine the splits. With 332 mappers, Tez
finishes the query in about 90s, and with 1252 mappers, it took about 120s.
> 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
>
> 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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