[GitHub] [spark] anishshri-db commented on a change in pull request #36002: [SPARK-38684][SS] Fix correctness issue on stream-stream outer join with RocksDB state store provider

[GitBox <gi...@apache.org>]

anishshri-db commented on a change in pull request #36002:
URL: https://github.com/apache/spark/pull/36002#discussion_r840105969



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
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@@ -324,17 +324,21 @@ case class StreamingSymmetricHashJoinExec(
           }
         }
 
+        val initIterFn = { () =>
+          val removedRowIter = leftSideJoiner.removeOldState()
+          removedRowIter.filterNot { kv =>
+            stateFormatVersion match {
+              case 1 => matchesWithRightSideState(new UnsafeRowPair(kv.key, kv.value))
+              case 2 => kv.matched
+              case _ => throwBadStateFormatVersionException()
+            }
+          }.map(pair => joinedRow.withLeft(pair.value).withRight(nullRight))
+        }
+
         // NOTE: we need to make sure `outerOutputIter` is evaluated "after" exhausting all of
-        // elements in `innerOutputIter`, because evaluation of `innerOutputIter` may update
+        // elements in `hashJoinOutputIter`, because evaluation of `hashJoinOutputIter` may update

Review comment:
       Nit: Do you think we should tag the spark JIRA ticket (https://issues.apache.org/jira/browse/SPARK-38684) in the comment here and below? Also, should we mention some of the PR description you added here, to elaborate the issue further? :
   
   ```
   More specifically, if updates are performed during processing input rows and somehow updates the number of values for grouping key, the update is not seen in SymmetricHashJoinStateManager.removeByValueCondition, and the method does the eviction with the number of values in out of sync.
   
   Making it more worse, if the method performs the eviction and updates the number of values for grouping key, it "overwrites" the number of value, effectively drop all rows being inserted in the same batch.
   ```




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