[jira] [Work logged] (HIVE-26184) COLLECT_SET with GROUP BY is very slow when some keys are highly skewed

["ASF GitHub Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HIVE-26184?focusedWorklogId=765792&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-765792 ]

ASF GitHub Bot logged work on HIVE-26184:
-----------------------------------------

                Author: ASF GitHub Bot
            Created on: 04/May/22 01:29
            Start Date: 04/May/22 01:29
    Worklog Time Spent: 10m 
      Work Description: dengzhhu653 commented on code in PR #3253:
URL: https://github.com/apache/hive/pull/3253#discussion_r864405523


##########
ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDAFMkCollectionEvaluator.java:
##########
@@ -95,11 +95,27 @@ public MkArrayAggregationBuffer() {
         throw new RuntimeException("Buffer type unknown");
       }
     }
+
+    private void reset() {
+      if (bufferType == BufferType.LIST) {
+        container.clear();

Review Comment:
   If I understand it, the `clear()` of ArrayList should have the same problem, right?





Issue Time Tracking
-------------------

    Worklog Id:     (was: 765792)
    Time Spent: 50m  (was: 40m)

> COLLECT_SET with GROUP BY is very slow when some keys are highly skewed
> -----------------------------------------------------------------------
>
>                 Key: HIVE-26184
>                 URL: https://issues.apache.org/jira/browse/HIVE-26184
>             Project: Hive
>          Issue Type: Bug
>          Components: Hive
>    Affects Versions: 2.3.8, 3.1.3
>            Reporter: okumin
>            Assignee: okumin
>            Priority: Major
>              Labels: pull-request-available
>          Time Spent: 50m
>  Remaining Estimate: 0h
>
> I observed some reducers spend 98% of CPU time in invoking `java.util.HashMap#clear`.
> Looking the detail, I found COLLECT_SET reuses a LinkedHashSet and its `clear` can be quite heavy when a relation has a small number of highly skewed keys.
>  
> To reproduce the issue, first, we will create rows with a skewed key.
> {code:java}
> INSERT INTO test_collect_set
> SELECT '00000000-0000-0000-0000-000000000000' AS key, CAST(UUID() AS VARCHAR) AS value
> FROM table_with_many_rows
> LIMIT 100000;{code}
> Then, we will create many non-skewed rows.
> {code:java}
> INSERT INTO test_collect_set
> SELECT UUID() AS key, UUID() AS value
> FROM table_with_many_rows
> LIMIT 5000000;{code}
> We can observe the issue when we aggregate values by `key`.
> {code:java}
> SELECT key, COLLECT_SET(value) FROM group_by_skew GROUP BY key{code}



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