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From "Gopal V (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-17287) HoS can not deal with skewed data group by
Date Thu, 10 Aug 2017 03:43:00 GMT

    [ https://issues.apache.org/jira/browse/HIVE-17287?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16121004#comment-16121004
] 

Gopal V commented on HIVE-17287:
--------------------------------

[~ liyunzhang_intel]: I suspect HoS is loading each partition as an independent RDD, which
removes the effect of SemanticAnalyzer::genNotNullFilterForJoinSourcePlan()?

As little as I know about Hive-on-Spark, Query67 does not read any row from the default partition
in MR or Tez.

> HoS can not deal with skewed data group by
> ------------------------------------------
>
>                 Key: HIVE-17287
>                 URL: https://issues.apache.org/jira/browse/HIVE-17287
>             Project: Hive
>          Issue Type: Bug
>            Reporter: liyunzhang_intel
>
> In [tpcds/query67.sql|https://github.com/kellyzly/hive-testbench/blob/hive14/sample-queries-tpcds/query67.sql],
fact table {{store_sales}} joins with small tables {{date_dim}}, {{item}},{{store}}. After
join, groupby the intermediate data.
> Here the data of {{store_sales}} on 3TB tpcds is skewed:  there are 1824 partitions.
The biggest partition is 25.7G and others are 715M.
> {code}
> hadoop fs -du -h /user/hive/warehouse/tpcds_bin_partitioned_parquet_3000.db/store_sales
> ....
> 715.0 M  /user/hive/warehouse/tpcds_bin_partitioned_parquet_3000.db/store_sales/ss_sold_date_sk=2452639
> 713.9 M  /user/hive/warehouse/tpcds_bin_partitioned_parquet_3000.db/store_sales/ss_sold_date_sk=2452640
> 714.1 M  /user/hive/warehouse/tpcds_bin_partitioned_parquet_3000.db/store_sales/ss_sold_date_sk=2452641
> 712.9 M  /user/hive/warehouse/tpcds_bin_partitioned_parquet_3000.db/store_sales/ss_sold_date_sk=2452642
> 25.7 G   /user/hive/warehouse/tpcds_bin_partitioned_parquet_3000.db/store_sales/ss_sold_date_sk=__HIVE_DEFAULT_PARTITION__
> {code}
> The skewed table {{store_sales}} caused the failed job. Is there any way to solve the
groupby problem of skewed table?  I tried to enable {{hive.groupby.skewindata}} to first divide
the data more evenly then start do group by. But the job still hangs. 



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