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From "ASF GitHub Bot (Jira)" <>
Subject [jira] [Work logged] (HIVE-23716) Support Anti Join in Hive
Date Sun, 26 Jul 2020 12:00:00 GMT


ASF GitHub Bot logged work on HIVE-23716:

                Author: ASF GitHub Bot
            Created on: 26/Jul/20 11:59
            Start Date: 26/Jul/20 11:59
    Worklog Time Spent: 10m 
      Work Description: maheshk114 commented on a change in pull request #1147:

File path: ql/src/java/org/apache/hadoop/hive/ql/optimizer/calcite/stats/
@@ -118,6 +119,15 @@ public Double getRowCount(HiveJoin join, RelMetadataQuery mq) {
   public Double getRowCount(HiveSemiJoin rel, RelMetadataQuery mq) {
+    return getRowCountInt(rel, mq);
+  }
+  public Double getRowCount(HiveAntiJoin rel, RelMetadataQuery mq) {
+    return getRowCountInt(rel, mq);
+  }
+  private Double getRowCountInt(Join rel, RelMetadataQuery mq) {

Review comment:
       super.getRowCount(rel, mq) does not support Anti join. I think we need to handle it.

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Issue Time Tracking

    Worklog Id:     (was: 463335)
    Time Spent: 10.5h  (was: 10h 20m)

> Support Anti Join in Hive 
> --------------------------
>                 Key: HIVE-23716
>                 URL:
>             Project: Hive
>          Issue Type: Bug
>            Reporter: mahesh kumar behera
>            Assignee: mahesh kumar behera
>            Priority: Major
>              Labels: pull-request-available
>         Attachments: HIVE-23716.01.patch
>          Time Spent: 10.5h
>  Remaining Estimate: 0h
> Currently hive does not support Anti join. The query for anti join is converted to left
outer join and null filter on right side join key is added to get the desired result. This
is causing
>  # Extra computation — The left outer join projects the redundant columns from right
side. Along with that, filtering is done to remove the redundant rows. This is can be avoided
in case of anti join as anti join will project only the required columns and rows from the
left side table.
>  # Extra shuffle — In case of anti join the duplicate records moved to join node can
be avoided from the child node. This can reduce significant amount of data movement if the
number of distinct rows( join keys) is significant.
>  # Extra Memory Usage - In case of map based anti join , hash set is sufficient as just
the key is required to check  if the records matches the join condition. In case of left
join, we need the key and the non key columns also and thus a hash table will be required.
> For a query like
> {code:java}
>  select wr_order_number FROM web_returns LEFT JOIN web_sales  ON wr_order_number = ws_order_number
WHERE ws_order_number IS NULL;{code}
> The number of distinct ws_order_number in web_sales table in a typical 10TB TPCDS set
up is just 10% of total records. So when we convert this query to anti join, instead of 7
billion rows, only 600 million rows are moved to join node.
> In the current patch, just one conversion is done. The pattern of project->filter->left-join
is converted to project->anti-join. This will take care of sub queries with “not exists”
clause. The queries with “not exists” are converted first to filter + left-join and then
its converted to anti join. The queries with “not in” are not handled in the current patch.
> From execution side, both merge join and map join with vectorized execution  is supported
for anti join.

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