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https://issues.apache.org/jira/browse/HIVE-23716?focusedWorklogId=462384&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-462384
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ASF GitHub Bot logged work on HIVE-23716:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 23/Jul/20 05:01
Start Date: 23/Jul/20 05:01
Worklog Time Spent: 10m
Work Description: maheshk114 commented on a change in pull request #1147:
URL: https://github.com/apache/hive/pull/1147#discussion_r459215352
##########
File path:
ql/src/java/org/apache/hadoop/hive/ql/optimizer/calcite/rules/HiveJoinAddNotNullRule.java
##########
@@ -74,7 +78,14 @@ public HiveJoinAddNotNullRule(Class<? extends Join> clazz,
@Override
public void onMatch(RelOptRuleCall call) {
Join join = call.rel(0);
- if (join.getJoinType() == JoinRelType.FULL ||
join.getCondition().isAlwaysTrue()) {
+
+ // For anti join case add the not null on right side if the condition is
Review comment:
For the case when we have. join condition which gets evaluated, it will
return false while comparing with a null on the right side. But for always true
join condition, we will not do a match for right side assuming it's always
true. So for anti join, the left side records will not be emitted. To avoid
this we put a null check on right side table and for all null entry, no records
will be projected from right side and thus all records from left side will be
emitted. So the comment is not very accurate. It's like even if the condition
is always true, we add a null check on right side for anti join. I will update
it.
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Issue Time Tracking
-------------------
Worklog Id: (was: 462384)
Time Spent: 6h 20m (was: 6h 10m)
> Support Anti Join in Hive
> --------------------------
>
> Key: HIVE-23716
> URL: https://issues.apache.org/jira/browse/HIVE-23716
> 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: 6h 20m
> 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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