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[GitHub] [spark] sunchao opened a new pull request, #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

sunchao opened a new pull request, #38196:
URL: https://github.com/apache/spark/pull/38196

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   This PR fixes a performance regression issue when one side of a join uses `HashPartitioning` with `ShuffleExchange` while the other side uses `SinglePartition`. In this case, Spark will re-shuffle the side with `HashPartitioning` and both sides will end up with only a single partition. This could hurt query performance a lot if the side with `HashPartitioning` contains a lot of input data.
   
   ### Why are the changes needed?
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   After SPARK-35703, when Spark sees that one side of the join has `ShuffleExchange` (meaning it needs to be shuffled anyways), and the other side doesn't, it'll try to avoid shuffling the side without `ShuffleExchange`. For instance:
   
   ```
   ShuffleExchange(HashPartition(200)) <-> HashPartition(150)
   ```
   
   will be converted into
   ```
   ShuffleExchange(HashPartition(150)) <-> HashPartition(150)
   ```
   
   However, when the side without `ShuffleExchange` is `SinglePartition`, like the following:
   ```
   ShuffleExchange(HashPartition(150)) <-> SinglePartition
   ```
   
   Spark will also do the same which causes the left-hand side to only use one partition. This can hurt job parallelism dramatically, especially when using DataSource V2, since `SinglePartition` is used by the V2 scan. On the other hand, it seems DataSource V1 won't be impacted much as it always report `UnknownPartitioning` in this situation.
   
   ### Does this PR introduce _any_ user-facing change?
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   Note that it means *any* user-facing change including all aspects such as the documentation fix.
   If yes, please clarify the previous behavior and the change this PR proposes - provide the console output, description and/or an example to show the behavior difference if possible.
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   No.
   
   ### How was this patch tested?
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   Added new unit tests in `EnsureRequirementsSuite`.


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[GitHub] [spark] wangyum commented on pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

Posted by GitBox <gi...@apache.org>.
wangyum commented on PR #38196:
URL: https://github.com/apache/spark/pull/38196#issuecomment-1279636319

   Merged to master and branch-3.3


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[GitHub] [spark] sunchao commented on pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

Posted by GitBox <gi...@apache.org>.
sunchao commented on PR #38196:
URL: https://github.com/apache/spark/pull/38196#issuecomment-1274853785

   cc @cloud-fan @c21 @viirya @dongjoon-hyun @huaxingao 


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[GitHub] [spark] c21 commented on pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

Posted by GitBox <gi...@apache.org>.
c21 commented on PR #38196:
URL: https://github.com/apache/spark/pull/38196#issuecomment-1275742743

   LGTM, thanks for the fix.


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[GitHub] [spark] dongjoon-hyun commented on pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on PR #38196:
URL: https://github.com/apache/spark/pull/38196#issuecomment-1275295888

   Also, cc @mridulm and @tgravescs , too


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[GitHub] [spark] wangyum closed pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

Posted by GitBox <gi...@apache.org>.
wangyum closed pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism
URL: https://github.com/apache/spark/pull/38196


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[GitHub] [spark] sunchao commented on pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

Posted by GitBox <gi...@apache.org>.
sunchao commented on PR #38196:
URL: https://github.com/apache/spark/pull/38196#issuecomment-1279764239

   Thanks @wangyum @bryanck @zhengruifeng @dongjoon-hyun @huaxingao @viirya @c21 !


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[GitHub] [spark] wangyum commented on pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

Posted by GitBox <gi...@apache.org>.
wangyum commented on PR #38196:
URL: https://github.com/apache/spark/pull/38196#issuecomment-1276199767

   cc @cloud-fan 


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[GitHub] [spark] sunchao commented on a diff in pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

Posted by GitBox <gi...@apache.org>.
sunchao commented on code in PR #38196:
URL: https://github.com/apache/spark/pull/38196#discussion_r992455054


##########
sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala:
##########
@@ -277,7 +277,7 @@ class PlannerSuite extends SharedSparkSession with AdaptiveSparkPlanHelper {
           val numExchanges = collect(plan) {
             case exchange: ShuffleExchangeExec => exchange
           }.length
-          assert(numExchanges === 3)
+          assert(numExchanges === 5)

Review Comment:
   Restored the test to the previous state as in Spark 3.2. Query plan:
   
   After this PR:
   ```
   AdaptiveSparkPlan isFinalPlan=false
   +- SortMergeJoin [key#220], [key#222], Inner
      :- SortMergeJoin [key#13], [key#220], Inner
      :  :- Sort [key#13 ASC NULLS FIRST], false, 0
      :  :  +- Exchange hashpartitioning(key#13, 5), ENSURE_REQUIREMENTS, [plan_id=133]
      :  :     +- SerializeFromObject [knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).key AS key#13, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).value, true, false, true) AS value#14]
      :  :        +- Scan[obj#12]
      :  +- Sort [key#220 ASC NULLS FIRST], false, 0
      :     +- Exchange hashpartitioning(key#220, 5), ENSURE_REQUIREMENTS, [plan_id=134]
      :        +- GlobalLimit 10, 0
      :           +- Exchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=129]
      :              +- LocalLimit 10
      :                 +- SerializeFromObject [knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).key AS key#220, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).value, true, false, true) AS value#221]
      :                    +- Scan[obj#218]
      +- Sort [key#222 ASC NULLS FIRST], false, 0
         +- Exchange hashpartitioning(key#222, 5), ENSURE_REQUIREMENTS, [plan_id=142]
            +- GlobalLimit 3, 0
               +- Exchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=138]
                  +- LocalLimit 3
                     +- SerializeFromObject [knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).key AS key#222, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).value, true, false, true) AS value#223]
                        +- Scan[obj#219]
   ```
   
   Before this PR:
   ```
   AdaptiveSparkPlan isFinalPlan=false
   +- SortMergeJoin [key#220], [key#222], Inner
      :- SortMergeJoin [key#13], [key#220], Inner
      :  :- Sort [key#13 ASC NULLS FIRST], false, 0
      :  :  +- Exchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=134]
      :  :     +- SerializeFromObject [knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).key AS key#13, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).value, true, false, true) AS value#14]
      :  :        +- Scan[obj#12]
      :  +- Sort [key#220 ASC NULLS FIRST], false, 0
      :     +- GlobalLimit 10, 0
      :        +- Exchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=129]
      :           +- LocalLimit 10
      :              +- SerializeFromObject [knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).key AS key#220, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).value, true, false, true) AS value#221]
      :                 +- Scan[obj#218]
      +- Sort [key#222 ASC NULLS FIRST], false, 0
         +- GlobalLimit 3, 0
            +- Exchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=138]
               +- LocalLimit 3
                  +- SerializeFromObject [knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).key AS key#222, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, knownnotnull(assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData, true])).value, true, false, true) AS value#223]
                     +- Scan[obj#219]
   ```



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[GitHub] [spark] zhengruifeng commented on pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

Posted by GitBox <gi...@apache.org>.
zhengruifeng commented on PR #38196:
URL: https://github.com/apache/spark/pull/38196#issuecomment-1274061615

   Looks reasonable to me


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[GitHub] [spark] cloud-fan commented on pull request #38196: [SPARK-40703][SQL] Introduce shuffle on SinglePartition to improve parallelism

Posted by GitBox <gi...@apache.org>.
cloud-fan commented on PR #38196:
URL: https://github.com/apache/spark/pull/38196#issuecomment-1283252896

   late LGTM. I think this is good to fix the perf regression, but we probably need a better design to fix similar problems. What if the other side is `HashPartitioning(2)`? The parallelism can still be too low. We need some heuristic or cost model to make a better decision here.


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