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https://issues.apache.org/jira/browse/HIVE-17287?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16121023#comment-16121023
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liyunzhang_intel edited comment on HIVE-17287 at 8/10/17 4:02 AM:
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[~gopalv]: thanks for your comments
{quote}
As little as I know about Hive-on-Spark, Query67 does not read any row from the
default partition in MR or Tez.
{quote}
the default_partition stores the data(25.7G) which ss_sold_date_sk is null. In
MR/Tez, these part of data will not be load because there is no match data in
join?
{quote}
I suspect HoS is loading each partition as an independent RDD, which removes
the effect of SemanticAnalyzer::genNotNullFilterForJoinSourcePlan()?
{quote}
I also see the filter to filter null data in the explain, although HOS load
partition as an independent RDD, i think the filter should work after loading
data in theory.
part of explain of query67
{code}
Map 1
Map Operator Tree:
TableScan
alias: store_sales
filterExpr: (ss_store_sk is not null and ss_item_sk is not
null) (type: boolean)
Statistics: Num rows: 8251124389 Data size: 181524736558
Basic stats: COMPLETE Column stats: NONE
Filter Operator
predicate: (ss_store_sk is not null and ss_item_sk is not
null) (type: boolean)
Statistics: Num rows: 8251124389 Data size: 181524736558
Basic stats: COMPLETE Column stats: NONE
Select Operator
expressions: ss_item_sk (type: bigint), ss_store_sk
(type: bigint), ss_quantity (type: int), ss_sales_price (type: double),
ss_sold_date_sk (type: bigint)
outputColumnNames: _col0, _col1, _col2, _col3, _col4
Statistics: Num rows: 8251124389 Data size: 181524736558
Basic stats: COMPLETE Column stats: NONE
Map Join Operator
{code}
was (Author: kellyzly):
[~gopalv]: thanks for your comments
{quote}
As little as I know about Hive-on-Spark, Query67 does not read any row from the
default partition in MR or Tez.
{quote}
the default_partition stores the data(25.7G) which ss_sold_date_sk is null. In
MR/Tez, these part of data will not be load because there is no match data in
join?
{quote}
I suspect HoS is loading each partition as an independent RDD, which removes
the effect of SemanticAnalyzer::genNotNullFilterForJoinSourcePlan()?
{quote}
I also see the filter to filter null data in the explain, although hos load
partition as an independent RDD, i think the filter should work in theory.
part of explain of query67
{code}
Map 1
Map Operator Tree:
TableScan
alias: store_sales
filterExpr: (ss_store_sk is not null and ss_item_sk is not
null) (type: boolean)
Statistics: Num rows: 8251124389 Data size: 181524736558
Basic stats: COMPLETE Column stats: NONE
Filter Operator
predicate: (ss_store_sk is not null and ss_item_sk is not
null) (type: boolean)
Statistics: Num rows: 8251124389 Data size: 181524736558
Basic stats: COMPLETE Column stats: NONE
Select Operator
expressions: ss_item_sk (type: bigint), ss_store_sk
(type: bigint), ss_quantity (type: int), ss_sales_price (type: double),
ss_sold_date_sk (type: bigint)
outputColumnNames: _col0, _col1, _col2, _col3, _col4
Statistics: Num rows: 8251124389 Data size: 181524736558
Basic stats: COMPLETE Column stats: NONE
Map Join Operator
{code}
> 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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