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Rui Li commented on HIVE-17287: ------------------------------- OK that seems a skewed shuffle to me. You can run some statistics on the group key to confirm, in case there's some issue like HIVE-17114. Besides, what will the metrics look like if you enable {{hive.groupby.skewindata}}? That optimization will shuffle twice for the group by. The 1st shuffle is partitioned randomly. You can verify it in the explain: {noformat} Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: rand() (type: double) Statistics: Num rows: 58 Data size: 5812 Basic stats: COMPLETE Column stats: NONE {noformat} > 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: 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. -- This message was sent by Atlassian JIRA (v6.4.14#64029)