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[SPARK-32282][SQL] Improve EnsureRquirement.reorderJoinKeys to handle more scenarios such as PartitioningCollection #29074

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Original file line number Diff line number Diff line change
Expand Up @@ -135,9 +135,14 @@ case class EnsureRequirements(conf: SQLConf) extends Rule[SparkPlan] {
leftKeys: IndexedSeq[Expression],
rightKeys: IndexedSeq[Expression],
expectedOrderOfKeys: Seq[Expression],
currentOrderOfKeys: Seq[Expression]): (Seq[Expression], Seq[Expression]) = {
currentOrderOfKeys: Seq[Expression]): Option[(Seq[Expression], Seq[Expression])] = {
if (expectedOrderOfKeys.size != currentOrderOfKeys.size) {
return (leftKeys, rightKeys)
return None
}

// Check if the current order already satisfies the expected order.
if (expectedOrderOfKeys.zip(currentOrderOfKeys).forall(p => p._1.semanticEquals(p._2))) {
return Some(leftKeys, rightKeys)
}

// Build a lookup between an expression and the positions its holds in the current key seq.
Expand All @@ -164,10 +169,10 @@ case class EnsureRequirements(conf: SQLConf) extends Rule[SparkPlan] {
rightKeysBuffer += rightKeys(index)
case _ =>
// The expression cannot be found, or we have exhausted all indices for that expression.
return (leftKeys, rightKeys)
return None
}
}
(leftKeysBuffer.toSeq, rightKeysBuffer.toSeq)
Some(leftKeysBuffer.toSeq, rightKeysBuffer.toSeq)
}

private def reorderJoinKeys(
Expand All @@ -176,19 +181,51 @@ case class EnsureRequirements(conf: SQLConf) extends Rule[SparkPlan] {
leftPartitioning: Partitioning,
rightPartitioning: Partitioning): (Seq[Expression], Seq[Expression]) = {
if (leftKeys.forall(_.deterministic) && rightKeys.forall(_.deterministic)) {
(leftPartitioning, rightPartitioning) match {
case (HashPartitioning(leftExpressions, _), _) =>
reorder(leftKeys.toIndexedSeq, rightKeys.toIndexedSeq, leftExpressions, leftKeys)
case (_, HashPartitioning(rightExpressions, _)) =>
reorder(leftKeys.toIndexedSeq, rightKeys.toIndexedSeq, rightExpressions, rightKeys)
case _ =>
(leftKeys, rightKeys)
}
reorderJoinKeysRecursively(
leftKeys,
rightKeys,
Some(leftPartitioning),
Some(rightPartitioning))
.getOrElse((leftKeys, rightKeys))
} else {
(leftKeys, rightKeys)
}
}

/**
* Recursively reorders the join keys based on partitioning. It starts reordering the
* join keys to match HashPartitioning on either side, followed by PartitioningCollection.
*/
private def reorderJoinKeysRecursively(
leftKeys: Seq[Expression],
rightKeys: Seq[Expression],
leftPartitioning: Option[Partitioning],
rightPartitioning: Option[Partitioning]): Option[(Seq[Expression], Seq[Expression])] = {
(leftPartitioning, rightPartitioning) match {
case (Some(HashPartitioning(leftExpressions, _)), _) =>
reorder(leftKeys.toIndexedSeq, rightKeys.toIndexedSeq, leftExpressions, leftKeys)
.orElse(reorderJoinKeysRecursively(
leftKeys, rightKeys, None, rightPartitioning))
case (_, Some(HashPartitioning(rightExpressions, _))) =>
reorder(leftKeys.toIndexedSeq, rightKeys.toIndexedSeq, rightExpressions, rightKeys)
.orElse(reorderJoinKeysRecursively(
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This can be also implemented by looking at left partitioning first then move to the right partitionoing:

    (leftPartitioning, rightPartitioning) match {
      case (HashPartitioning(leftExpressions, _), _) =>
        reorder(leftKeys.toIndexedSeq, rightKeys.toIndexedSeq, leftExpressions, leftKeys)
          .orElse(reorderJoinKeysRecursively(
            leftKeys, rightKeys, UnknownPartitioning(0), rightPartitioning))
      case (PartitioningCollection(partitionings), _) =>
        partitionings.foreach { p =>
          reorderJoinKeysRecursively(leftKeys, rightKeys, p, rightPartitioning).map { k =>
            return Some(k)
          }
        }
        reorderJoinKeysRecursively(leftKeys, rightKeys, UnknownPartitioning(0), rightPartitioning)
      case (_, HashPartitioning(rightExpressions, _)) =>
        reorder(leftKeys.toIndexedSeq, rightKeys.toIndexedSeq, rightExpressions, rightKeys)
      case (_, PartitioningCollection(partitionings)) =>
        partitionings.foreach { p =>
          reorderJoinKeysRecursively(leftKeys, rightKeys, leftPartitioning, p).map { k =>
            return Some(k)
          }
        }
        None
      case _ =>
        None
    }

However, I chose this way so that the behavior remains the same. If you have leftPartitioning = PartitioningCollection and rightPartitioning = HashPartitioning, it will match the rightPartitioning first, which is the existing behavior.

leftKeys, rightKeys, leftPartitioning, None))
case (Some(PartitioningCollection(partitionings)), _) =>
partitionings.foldLeft(Option.empty[(Seq[Expression], Seq[Expression])]) { (res, p) =>
res.orElse(reorderJoinKeysRecursively(leftKeys, rightKeys, Some(p), rightPartitioning))
}.orElse(reorderJoinKeysRecursively(leftKeys, rightKeys, None, rightPartitioning))
case (_, Some(PartitioningCollection(partitionings))) =>
partitionings.foreach { p =>
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can you do the same refactor here?

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Fixed.

reorderJoinKeysRecursively(leftKeys, rightKeys, leftPartitioning, Some(p)).map { k =>
return Some(k)
}
}
None
case _ =>
None
}
}

/**
* When the physical operators are created for JOIN, the ordering of join keys is based on order
* in which the join keys appear in the user query. That might not match with the output
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,134 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package org.apache.spark.sql.execution.exchange

import org.apache.spark.sql.catalyst.expressions.Literal
import org.apache.spark.sql.catalyst.plans.Inner
import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioning, PartitioningCollection}
import org.apache.spark.sql.execution.{DummySparkPlan, SortExec}
import org.apache.spark.sql.execution.joins.SortMergeJoinExec
import org.apache.spark.sql.test.SharedSparkSession

class EnsureRequirementsSuite extends SharedSparkSession {
private val exprA = Literal(1)
private val exprB = Literal(2)
private val exprC = Literal(3)

test("reorder should handle PartitioningCollection") {
val plan1 = DummySparkPlan(
outputPartitioning = PartitioningCollection(Seq(
HashPartitioning(exprA :: exprB :: Nil, 5),
HashPartitioning(exprA :: Nil, 5))))
val plan2 = DummySparkPlan()

// Test PartitioningCollection on the left side of join.
val smjExec1 = SortMergeJoinExec(
exprB :: exprA :: Nil, exprA :: exprB :: Nil, Inner, None, plan1, plan2)
EnsureRequirements(spark.sessionState.conf).apply(smjExec1) match {
case SortMergeJoinExec(leftKeys, rightKeys, _, _,
SortExec(_, _, DummySparkPlan(_, _, _: PartitioningCollection, _, _), _),
SortExec(_, _, ShuffleExchangeExec(_: HashPartitioning, _, _), _), _) =>
assert(leftKeys !== smjExec1.leftKeys)
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is this check needed? We already check leftKeys === Seq(exprA, exprB) and it's obvious that leftKeys !== smjExec1.leftKeys

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Removed, thanks!

assert(rightKeys !== smjExec1.rightKeys)
assert(leftKeys === Seq(exprA, exprB))
assert(rightKeys === Seq(exprB, exprA))
case other => fail(other.toString)
}

// Test PartitioningCollection on the right side of join.
val smjExec2 = SortMergeJoinExec(
exprA :: exprB :: Nil, exprB :: exprA :: Nil, Inner, None, plan2, plan1)
EnsureRequirements(spark.sessionState.conf).apply(smjExec2) match {
case SortMergeJoinExec(leftKeys, rightKeys, _, _,
SortExec(_, _, ShuffleExchangeExec(_: HashPartitioning, _, _), _),
SortExec(_, _, DummySparkPlan(_, _, _: PartitioningCollection, _, _), _), _) =>
assert(leftKeys !== smjExec2.leftKeys)
assert(rightKeys !== smjExec2.rightKeys)
assert(leftKeys === Seq(exprB, exprA))
assert(rightKeys === Seq(exprA, exprB))
case other => fail(other.toString)
}

// Both sides are PartitioningCollection, but left side cannot be reorderd to match
// and it should fall back to the right side.
val smjExec3 = SortMergeJoinExec(
exprA :: exprC :: Nil, exprB :: exprA :: Nil, Inner, None, plan1, plan1)
EnsureRequirements(spark.sessionState.conf).apply(smjExec3) match {
case SortMergeJoinExec(leftKeys, rightKeys, _, _,
SortExec(_, _, ShuffleExchangeExec(_: HashPartitioning, _, _), _),
SortExec(_, _, DummySparkPlan(_, _, _: PartitioningCollection, _, _), _), _) =>
assert(leftKeys !== smjExec3.leftKeys)
assert(rightKeys !== smjExec3.rightKeys)
assert(leftKeys === Seq(exprC, exprA))
assert(rightKeys === Seq(exprA, exprB))
case other => fail(other.toString)
}
}

test("reorder should fallback to the other side partitioning") {
val plan1 = DummySparkPlan(
outputPartitioning = HashPartitioning(exprA :: exprB :: exprC :: Nil, 5))
val plan2 = DummySparkPlan(
outputPartitioning = HashPartitioning(exprB :: exprC :: Nil, 5))

// Test fallback to the right side, which has HashPartitioning.
val smjExec1 = SortMergeJoinExec(
exprA :: exprB :: Nil, exprC :: exprB :: Nil, Inner, None, plan1, plan2)
EnsureRequirements(spark.sessionState.conf).apply(smjExec1) match {
case SortMergeJoinExec(leftKeys, rightKeys, _, _,
SortExec(_, _, ShuffleExchangeExec(_: HashPartitioning, _, _), _),
SortExec(_, _, DummySparkPlan(_, _, _: HashPartitioning, _, _), _), _) =>
assert(leftKeys !== smjExec1.leftKeys)
assert(rightKeys !== smjExec1.rightKeys)
assert(leftKeys === Seq(exprB, exprA))
assert(rightKeys === Seq(exprB, exprC))
case other => fail(other.toString)
}

// Test fallback to the right side, which has PartitioningCollection.
val plan3 = DummySparkPlan(
outputPartitioning = PartitioningCollection(Seq(HashPartitioning(exprB :: exprC :: Nil, 5))))
val smjExec2 = SortMergeJoinExec(
exprA :: exprB :: Nil, exprC :: exprB :: Nil, Inner, None, plan1, plan3)
EnsureRequirements(spark.sessionState.conf).apply(smjExec2) match {
case SortMergeJoinExec(leftKeys, rightKeys, _, _,
SortExec(_, _, ShuffleExchangeExec(_: HashPartitioning, _, _), _),
SortExec(_, _, DummySparkPlan(_, _, _: PartitioningCollection, _, _), _), _) =>
assert(leftKeys !== smjExec2.leftKeys)
assert(rightKeys !== smjExec2.rightKeys)
assert(leftKeys === Seq(exprB, exprA))
assert(rightKeys === Seq(exprB, exprC))
case other => fail(other.toString)
}

// The right side has HashPartitioning, so it is matched first, but no reordering match is
// found, and it should fall back to the left side, which has a PartitioningCollection.
val smjExec3 = SortMergeJoinExec(
exprC :: exprB :: Nil, exprA :: exprB :: Nil, Inner, None, plan3, plan1)
EnsureRequirements(spark.sessionState.conf).apply(smjExec3) match {
case SortMergeJoinExec(leftKeys, rightKeys, _, _,
SortExec(_, _, DummySparkPlan(_, _, _: PartitioningCollection, _, _), _),
SortExec(_, _, ShuffleExchangeExec(_: HashPartitioning, _, _), _), _) =>
assert(leftKeys !== smjExec3.leftKeys)
assert(rightKeys !== smjExec3.rightKeys)
assert(leftKeys === Seq(exprB, exprC))
assert(rightKeys === Seq(exprB, exprA))
case other => fail(other.toString)
}
}
}