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From "liyunzhang_intel (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-17287) HoS can not deal with skewed data group by
Date Tue, 15 Aug 2017 08:58:01 GMT

    [ https://issues.apache.org/jira/browse/HIVE-17287?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16126964#comment-16126964
] 

liyunzhang_intel commented on HIVE-17287:
-----------------------------------------

[~lirui] ,[~gopalv]: some update about skewed data group by.
the problem happens when using group by with rollup. in [attached pic|https://issues.apache.org/jira/secure/attachment/12881892/compare_groupby_groupby_rollup.png],
you can see the difference, if using group by with roll up, the shuffle read data is 96.8g
while using group by, the shuffle read data is 68.1g.  when i only using group by, the shuffle
read metrics is very even.

> 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
>            Assignee: liyunzhang_intel
>         Attachments: compare_groupby_groupby_rollup.png, not_stages_completed_but_job_completed.PNG,
query67-fail-at-groupby.png, query67-groupby_shuffle_metric.png
>
>
> 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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