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https://issues.apache.org/jira/browse/HIVE-17287?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16121026#comment-16121026
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Gopal V commented on HIVE-17287:
--------------------------------

{code}
store_sales.ss_sold_date_sk=date_dim.d_date_sk
{code}

Implies ss_sold_date_sk is not null.

There's another optimizer in Hive called PCR, which removes any Filter which is 
no-op.

So there's some possibility that "explain extended <query>" won't list the 
default partition at all.

> 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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