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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2020/09/11 05:41:36 UTC

[GitHub] [spark] c21 opened a new pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

c21 opened a new pull request #29724:
URL: https://github.com/apache/spark/pull/29724


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   Several minor code and documentation improvement for stream-stream join. Specifically:
   
   * Remove extending from `SparkPlan`, as extending from `BinaryExecNode` is enough.
   * Return `left/right.outputPartitioning` for `Left/RightOuter` in `outputPartitioning`, as the `PartitioningCollection` wrapper is unnecessary (similar to batch joins `ShuffledHashJoinExec`, `SortMergeJoinExec`).
   *  Avoid per-row check for join type (https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala#L486-L492), by creating the method before the loop of reading rows (`generateFilteredJoinedRow` in `storeAndJoinWithOtherSide`). Similar optimization (i.e. create auxiliary method/variable per different join type before the iterator of input rows) has been done in batch join world (`SortMergeJoinExec`, `ShuffledHashJoinExec`).
   * Minor fix for comment/indentation for better readability.
   
   ### Why are the changes needed?
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     1. If you propose a new API, clarify the use case for a new API.
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   Minor optimization to avoid per-row unnecessary work (this probably can be optimized away by compiler, but we can do a better join to avoid it at the first place). And other comment/indentation fix to have better code readability for future developers.
   
   ### Does this PR introduce _any_ user-facing change?
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   No.
   
   ### How was this patch tested?
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   Existing tests in `StreamingJoinSuite.scala` as no new logic is introduced.


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[GitHub] [spark] xuanyuanking commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
xuanyuanking commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r487250765



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Yes, have a string val for the same error message.




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[GitHub] [spark] c21 commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
c21 commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r487206481



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       @cloud-fan - updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       @cloud-fan , @HeartSaVioR - yes, this is just updating the comment, because there's no `leftJoiner`/`rightJoiner`/`joinWith` in the file, and the original author (https://github.com/apache/spark/pull/19271) should mean to refer to `leftSideJoiner`/`rightSideJoiner`/`storeAndJoinWithOtherSide`. I think it would make sense to be consistent  between code and comment here. This is anyway a minor change for comment only.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sorry that I don't get how to change, are you suggesting to have a string val for error message to be used in `throwBadJoinTypeException ` and `require(...)`: `val errorMessageForJoinType = s"${getClass.getSimpleName} should not take $joinType as the JoinType")`, or something else?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sure, updated.




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[GitHub] [spark] cloud-fan commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r486837991



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?




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[GitHub] [spark] xuanyuanking commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
xuanyuanking commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r487229420



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Nich catch,
   nit: let's remove the duplicate error string in https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR168 and https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR162

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I think the original PR just wants to use pseudocode to explain, either way is ok to me.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Yes, have a string val for the same error message.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Nich catch,
   nit: let's remove the duplicate error string in https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR168 and https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR162

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I think the original PR just wants to use pseudocode to explain, either way is ok to me.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Yes, have a string val for the same error message.




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[GitHub] [spark] c21 commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
c21 commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r487255626



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sure, updated.




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[GitHub] [spark] AmplabJenkins commented on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
AmplabJenkins commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-691066506






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[GitHub] [spark] AmplabJenkins commented on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
AmplabJenkins commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-690889562






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[GitHub] [spark] xuanyuanking commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
xuanyuanking commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r487229420



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Nich catch,
   nit: let's remove the duplicate error string in https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR168 and https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR162

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I think the original PR just wants to use pseudocode to explain, either way is ok to me.




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[GitHub] [spark] SparkQA removed a comment on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
SparkQA removed a comment on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-690889136






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[GitHub] [spark] HeartSaVioR commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r486993687



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       The comment seems to be just modified for replacing `leftJoiner.joinWith(rightJoiner)` with `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` and vice versa for right side. Other parts aren't modified.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       The comment seems to be just modified for replacing `leftJoiner.joinWith(rightJoiner)` with `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` and vice versa for right side. Other parts aren't modified.




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[GitHub] [spark] cloud-fan commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r486837991



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`




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[GitHub] [spark] c21 commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
c21 commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r487206481



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       @cloud-fan - updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       @cloud-fan , @HeartSaVioR - yes, this is just updating the comment, because there's no `leftJoiner`/`rightJoiner`/`joinWith` in the file, and the original author (https://github.com/apache/spark/pull/19271) should mean to refer to `leftSideJoiner`/`rightSideJoiner`/`storeAndJoinWithOtherSide`. I think it would make sense to be consistent  between code and comment here. This is anyway a minor change for comment only.




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[GitHub] [spark] cloud-fan commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r486840286



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 




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Posted by GitBox <gi...@apache.org>.
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[GitHub] [spark] cloud-fan commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r486837991



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 




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[GitHub] [spark] HeartSaVioR commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r486993687



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       The comment seems to be just modified for replacing `leftJoiner.joinWith(rightJoiner)` with `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` and vice versa for right side. Other parts aren't modified.




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Posted by GitBox <gi...@apache.org>.
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[GitHub] [spark] cloud-fan closed pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
cloud-fan closed pull request #29724:
URL: https://github.com/apache/spark/pull/29724


   


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[GitHub] [spark] SparkQA commented on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-691065454


   **[Test build #128556 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/128556/testReport)** for PR 29724 at commit [`069ad73`](https://github.com/apache/spark/commit/069ad73da7197a5db82b3d2d3fbf515f11bae6f6).
    * This patch passes all tests.
    * This patch merges cleanly.
    * This patch adds no public classes.


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[GitHub] [spark] SparkQA commented on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-691349096


   **[Test build #128578 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/128578/testReport)** for PR 29724 at commit [`cfd9cc0`](https://github.com/apache/spark/commit/cfd9cc0cdc0c319da6bf10e95e5dc74d7dbb6266).
    * This patch passes all tests.
    * This patch merges cleanly.
    * This patch adds no public classes.


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[GitHub] [spark] c21 commented on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
c21 commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-692184842


   Thank you @cloud-fan , @HeartSaVioR and @xuanyuanking for review!


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URL: https://github.com/apache/spark/pull/29724#issuecomment-690889136






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[GitHub] [spark] HeartSaVioR commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r486993687



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       The comment seems to be just modified for replacing `leftJoiner.joinWith(rightJoiner)` with `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` and vice versa for right side. Other parts aren't modified.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       The comment seems to be just modified for replacing `leftJoiner.joinWith(rightJoiner)` with `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` and vice versa for right side. Other parts aren't modified.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       The comment seems to be just modified for replacing `leftJoiner.joinWith(rightJoiner)` with `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` and vice versa for right side. Other parts aren't modified.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       The comment seems to be just modified for replacing `leftJoiner.joinWith(rightJoiner)` with `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` and vice versa for right side. Other parts aren't modified.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       The comment seems to be just modified for replacing `leftJoiner.joinWith(rightJoiner)` with `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` and vice versa for right side. Other parts aren't modified.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       The comment seems to be just modified for replacing `leftJoiner.joinWith(rightJoiner)` with `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` and vice versa for right side. Other parts aren't modified.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       The comment seems to be just modified for replacing `leftJoiner.joinWith(rightJoiner)` with `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` and vice versa for right side. Other parts aren't modified.




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Posted by GitBox <gi...@apache.org>.
c21 commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-690917366


   retest this please


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Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-690916887


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    * This patch **fails due to an unknown error code, -9**.
    * This patch merges cleanly.
    * This patch adds no public classes.


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Posted by GitBox <gi...@apache.org>.
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    * This patch passes all tests.
    * This patch merges cleanly.
    * This patch adds no public classes.


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[GitHub] [spark] cloud-fan commented on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
cloud-fan commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-691915645


   thanks, merging to master!


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[GitHub] [spark] c21 commented on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
c21 commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-690887740


   cc @cloud-fan and @sameeragarwal if you have time to take a look, thanks.


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[GitHub] [spark] c21 commented on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
c21 commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-691785756


   Addressed all comments and tests are passed. Let me know if anything needs to be changed, thanks, @cloud-fan .


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[GitHub] [spark] cloud-fan commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r486837991



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       `uses the watermark to figure out`

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I'm not familiar with this part, cc @zsxwing  @HeartSaVioR @xuanyuanking 




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[GitHub] [spark] xuanyuanking commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
xuanyuanking commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r487229420



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Nich catch,
   nit: let's remove the duplicate error string in https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR168 and https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR162

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I think the original PR just wants to use pseudocode to explain, either way is ok to me.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Yes, have a string val for the same error message.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Nich catch,
   nit: let's remove the duplicate error string in https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR168 and https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR162

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I think the original PR just wants to use pseudocode to explain, either way is ok to me.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Yes, have a string val for the same error message.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Nich catch,
   nit: let's remove the duplicate error string in https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR168 and https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR162

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I think the original PR just wants to use pseudocode to explain, either way is ok to me.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Yes, have a string val for the same error message.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Nich catch,
   nit: let's remove the duplicate error string in https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR168 and https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR162

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I think the original PR just wants to use pseudocode to explain, either way is ok to me.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Yes, have a string val for the same error message.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Nich catch,
   nit: let's remove the duplicate error string in https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR168 and https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR162

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I think the original PR just wants to use pseudocode to explain, either way is ok to me.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Yes, have a string val for the same error message.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Nich catch,
   nit: let's remove the duplicate error string in https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR168 and https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR162

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I think the original PR just wants to use pseudocode to explain, either way is ok to me.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Yes, have a string val for the same error message.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Nich catch,
   nit: let's remove the duplicate error string in https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR168 and https://github.com/apache/spark/pull/29724/files#diff-e9db271d8593f070ba7096e758c8b89dR162

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       I think the original PR just wants to use pseudocode to explain, either way is ok to me.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       Yes, have a string val for the same error message.




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Posted by GitBox <gi...@apache.org>.
AmplabJenkins commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-691349550






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[GitHub] [spark] SparkQA removed a comment on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
SparkQA removed a comment on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-691283703


   **[Test build #128580 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/128580/testReport)** for PR 29724 at commit [`ed800ee`](https://github.com/apache/spark/commit/ed800ee41814eabf9fb1f00ee79092ff2c2fa34b).


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[GitHub] [spark] SparkQA commented on pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #29724:
URL: https://github.com/apache/spark/pull/29724#issuecomment-690889136






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[GitHub] [spark] c21 commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
c21 commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r487249765



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sorry that I don't get how to change, are you suggesting to have a string val for error message to be used in `throwBadJoinTypeException ` and `require(...)`: `val errorMessageForJoinType = s"${getClass.getSimpleName} should not take $joinType as the JoinType")`, or something else?




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[GitHub] [spark] c21 commented on a change in pull request #29724: [SPARK-32854][SS] Minor code and doc improvement for stream-stream join

Posted by GitBox <gi...@apache.org>.
c21 commented on a change in pull request #29724:
URL: https://github.com/apache/spark/pull/29724#discussion_r487206481



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       @cloud-fan - updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       @cloud-fan , @HeartSaVioR - yes, this is just updating the comment, because there's no `leftJoiner`/`rightJoiner`/`joinWith` in the file, and the original author (https://github.com/apache/spark/pull/19271) should mean to refer to `leftSideJoiner`/`rightSideJoiner`/`storeAndJoinWithOtherSide`. I think it would make sense to be consistent  between code and comment here. This is anyway a minor change for comment only.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sorry that I don't get how to change, are you suggesting to have a string val for error message to be used in `throwBadJoinTypeException ` and `require(...)`: `val errorMessageForJoinType = s"${getClass.getSimpleName} should not take $joinType as the JoinType")`, or something else?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sure, updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       @cloud-fan - updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       @cloud-fan , @HeartSaVioR - yes, this is just updating the comment, because there's no `leftJoiner`/`rightJoiner`/`joinWith` in the file, and the original author (https://github.com/apache/spark/pull/19271) should mean to refer to `leftSideJoiner`/`rightSideJoiner`/`storeAndJoinWithOtherSide`. I think it would make sense to be consistent  between code and comment here. This is anyway a minor change for comment only.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sorry that I don't get how to change, are you suggesting to have a string val for error message to be used in `throwBadJoinTypeException ` and `require(...)`: `val errorMessageForJoinType = s"${getClass.getSimpleName} should not take $joinType as the JoinType")`, or something else?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sure, updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       @cloud-fan - updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       @cloud-fan , @HeartSaVioR - yes, this is just updating the comment, because there's no `leftJoiner`/`rightJoiner`/`joinWith` in the file, and the original author (https://github.com/apache/spark/pull/19271) should mean to refer to `leftSideJoiner`/`rightSideJoiner`/`storeAndJoinWithOtherSide`. I think it would make sense to be consistent  between code and comment here. This is anyway a minor change for comment only.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sorry that I don't get how to change, are you suggesting to have a string val for error message to be used in `throwBadJoinTypeException ` and `require(...)`: `val errorMessageForJoinType = s"${getClass.getSimpleName} should not take $joinType as the JoinType")`, or something else?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sure, updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       @cloud-fan - updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       @cloud-fan , @HeartSaVioR - yes, this is just updating the comment, because there's no `leftJoiner`/`rightJoiner`/`joinWith` in the file, and the original author (https://github.com/apache/spark/pull/19271) should mean to refer to `leftSideJoiner`/`rightSideJoiner`/`storeAndJoinWithOtherSide`. I think it would make sense to be consistent  between code and comment here. This is anyway a minor change for comment only.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sorry that I don't get how to change, are you suggesting to have a string val for error message to be used in `throwBadJoinTypeException ` and `require(...)`: `val errorMessageForJoinType = s"${getClass.getSimpleName} should not take $joinType as the JoinType")`, or something else?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sure, updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       @cloud-fan - updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       @cloud-fan , @HeartSaVioR - yes, this is just updating the comment, because there's no `leftJoiner`/`rightJoiner`/`joinWith` in the file, and the original author (https://github.com/apache/spark/pull/19271) should mean to refer to `leftSideJoiner`/`rightSideJoiner`/`storeAndJoinWithOtherSide`. I think it would make sense to be consistent  between code and comment here. This is anyway a minor change for comment only.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sorry that I don't get how to change, are you suggesting to have a string val for error message to be used in `throwBadJoinTypeException ` and `require(...)`: `val errorMessageForJoinType = s"${getClass.getSimpleName} should not take $joinType as the JoinType")`, or something else?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sure, updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       @cloud-fan - updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       @cloud-fan , @HeartSaVioR - yes, this is just updating the comment, because there's no `leftJoiner`/`rightJoiner`/`joinWith` in the file, and the original author (https://github.com/apache/spark/pull/19271) should mean to refer to `leftSideJoiner`/`rightSideJoiner`/`storeAndJoinWithOtherSide`. I think it would make sense to be consistent  between code and comment here. This is anyway a minor change for comment only.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sorry that I don't get how to change, are you suggesting to have a string val for error message to be used in `throwBadJoinTypeException ` and `require(...)`: `val errorMessageForJoinType = s"${getClass.getSimpleName} should not take $joinType as the JoinType")`, or something else?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sure, updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       @cloud-fan - updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       @cloud-fan , @HeartSaVioR - yes, this is just updating the comment, because there's no `leftJoiner`/`rightJoiner`/`joinWith` in the file, and the original author (https://github.com/apache/spark/pull/19271) should mean to refer to `leftSideJoiner`/`rightSideJoiner`/`storeAndJoinWithOtherSide`. I think it would make sense to be consistent  between code and comment here. This is anyway a minor change for comment only.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sorry that I don't get how to change, are you suggesting to have a string val for error message to be used in `throwBadJoinTypeException ` and `require(...)`: `val errorMessageForJoinType = s"${getClass.getSimpleName} should not take $joinType as the JoinType")`, or something else?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sure, updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark figure out which rows in the buffer will not join with

Review comment:
       @cloud-fan - updated.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -246,13 +244,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with

Review comment:
       @cloud-fan , @HeartSaVioR - yes, this is just updating the comment, because there's no `leftJoiner`/`rightJoiner`/`joinWith` in the file, and the original author (https://github.com/apache/spark/pull/19271) should mean to refer to `leftSideJoiner`/`rightSideJoiner`/`storeAndJoinWithOtherSide`. I think it would make sense to be consistent  between code and comment here. This is anyway a minor change for comment only.

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sorry that I don't get how to change, are you suggesting to have a string val for error message to be used in `throwBadJoinTypeException ` and `require(...)`: `val errorMessageForJoinType = s"${getClass.getSimpleName} should not take $joinType as the JoinType")`, or something else?

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
##########
@@ -189,11 +189,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()

Review comment:
       @xuanyuanking - sure, updated.




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