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[SPARK-23973][SQL] Remove consecutive Sorts #21072

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[SPARK-23973][SQL] Remove consecutive Sorts #21072

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[SPARK-23973][SQL] Remove consecutive Sorts
mgaido91 Apr 14, 2018
ff7d412
remove Sort operator separated by 0...n Project/Filter operators
mgaido91 Apr 16, 2018
ac03bed
fix test
mgaido91 Apr 16, 2018
1d6ca1e
add test cases + fix typo
mgaido91 Apr 17, 2018
e7391f3
address comments
mgaido91 Apr 23, 2018
e2f4d4d
address comment
mgaido91 Apr 23, 2018
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12 changes: 11 additions & 1 deletion sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -736,12 +736,22 @@ object EliminateSorts extends Rule[LogicalPlan] {
}

/**
* Removes Sort operation if the child is already sorted
* Removes redundant Sort operation. This can happen:
* 1) if the child is already sorted
* 2) if there is another Sort operator separated by 0...n Project/Filter operators
*/
object RemoveRedundantSorts extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
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nit: now it's more efficient to do transformDown

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isn't it the same?

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@cloud-fan cloud-fan Apr 23, 2018 •
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assume the plan is

Sort
  Filter
    Sort
      Filter
        Sort
          OtherPlan

If we do transformUp, we hit the rule 3 times, which has some unnecessary transformation(OtherPlan is transformed 3 times). If it's transformDown, it's one-shot.

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yes, but I saw that transfrom actually does transformDown. Anyway, I see that this might change and here we best have transformDown

case Sort(orders, true, child) if SortOrder.orderingSatisfies(child.outputOrdering, orders) =>
child
case s @ Sort(_, _, child) => s.copy(child = recursiveRemoveSort(child))
}

def recursiveRemoveSort(plan: LogicalPlan): LogicalPlan = plan match {
case Project(fields, child) => Project(fields, recursiveRemoveSort(child))
case Filter(condition, child) => Filter(condition, recursiveRemoveSort(child))
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we should at least add ResolvedHint. To easily expand the white list in the future, I'd like to change the code style to

def recursiveRemoveSort(plan: LogicalPlan): LogicalPlan = plan match {
  case s: Sort => recursiveRemoveSort(s.child)
  case other if canEliminateSort(other) => other.withNewChildren(other.children.map(recursiveRemoveSort))
  case _ => plan
}

def canEliminateSort(plan: LogicalPlan): Boolean = plan match {
  case p: Project => p.projectList.forall(_.deterministic)
  case f: Filter => f.condition.deterministic
  case _: ResolvedHint => true
  ...
  case _ => false
}

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why do you think we should check for the filter condition and the projected items to be deterministic?

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by the definition of deterministic, the entire input is the stats of the expression. It's very likely we will get a different result if we remove sort before filter, e.g. rowId() < 10 will get the first 10 rows, if you sort the input, the first 10 rows changed.

I think we should be conservative about deterministic expressions.

case Sort(_, _, child) => recursiveRemoveSort(child)
case _ => plan
}
}

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51 changes: 44 additions & 7 deletions ...st/src/test/scala/org/apache/spark/sql/catalyst/optimizer/RemoveRedundantSortsSuite.scala
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Expand Up @@ -17,16 +17,12 @@

package org.apache.spark.sql.catalyst.optimizer

import org.apache.spark.sql.catalyst.analysis.{Analyzer, EmptyFunctionRegistry}
import org.apache.spark.sql.catalyst.catalog.{InMemoryCatalog, SessionCatalog}
import org.apache.spark.sql.catalyst.dsl.expressions._
import org.apache.spark.sql.catalyst.dsl.plans._
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.plans._
import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.rules._
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.internal.SQLConf.{CASE_SENSITIVE, ORDER_BY_ORDINAL}

class RemoveRedundantSortsSuite extends PlanTest {

Expand All @@ -42,15 +38,15 @@ class RemoveRedundantSortsSuite extends PlanTest {

test("remove redundant order by") {
val orderedPlan = testRelation.select('a, 'b).orderBy('a.asc, 'b.desc_nullsFirst)
val unnecessaryReordered = orderedPlan.select('a).orderBy('a.asc, 'b.desc_nullsFirst)
val unnecessaryReordered = orderedPlan.limit(2).select('a).orderBy('a.asc, 'b.desc_nullsFirst)
val optimized = Optimize.execute(unnecessaryReordered.analyze)
val correctAnswer = orderedPlan.select('a).analyze
val correctAnswer = orderedPlan.limit(2).select('a).analyze
comparePlans(Optimize.execute(optimized), correctAnswer)
}

test("do not remove sort if the order is different") {
val orderedPlan = testRelation.select('a, 'b).orderBy('a.asc, 'b.desc_nullsFirst)
val reorderedDifferently = orderedPlan.select('a).orderBy('a.asc, 'b.desc)
val reorderedDifferently = orderedPlan.limit(2).select('a).orderBy('a.asc, 'b.desc)
val optimized = Optimize.execute(reorderedDifferently.analyze)
val correctAnswer = reorderedDifferently.analyze
comparePlans(optimized, correctAnswer)
Expand All @@ -72,6 +68,14 @@ class RemoveRedundantSortsSuite extends PlanTest {
comparePlans(optimized, correctAnswer)
}

test("different sorts are not simplified if limit is in between") {
val orderedPlan = testRelation.select('a, 'b).orderBy('b.desc).limit(Literal(10))
.orderBy('a.asc)
val optimized = Optimize.execute(orderedPlan.analyze)
val correctAnswer = orderedPlan.analyze
comparePlans(optimized, correctAnswer)
}

test("range is already sorted") {
val inputPlan = Range(1L, 1000L, 1, 10)
val orderedPlan = inputPlan.orderBy('id.asc)
Expand All @@ -98,4 +102,37 @@ class RemoveRedundantSortsSuite extends PlanTest {
val correctAnswer = groupedAndResorted.analyze
comparePlans(optimized, correctAnswer)
}

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Could you add a test which explicitly confirms that sort.limit.sort is not simplified? I know the above two tests cover that case, but it's good to have one dedicated to testing this important property.

test("remove two consecutive sorts") {
val orderedTwice = testRelation.orderBy('a.asc).orderBy('b.desc)
val optimized = Optimize.execute(orderedTwice.analyze)
val correctAnswer = testRelation.orderBy('b.desc).analyze
comparePlans(optimized, correctAnswer)
}
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Can you add a test for three consecutive sorts? Two is the base case, three will help us show the inductive case :)


test("remove sorts separated by Filter/Project operators") {
val orderedTwiceWithProject = testRelation.orderBy('a.asc).select('b).orderBy('b.desc)
val optimizedWithProject = Optimize.execute(orderedTwiceWithProject.analyze)
val correctAnswerWithProject = testRelation.select('b).orderBy('b.desc).analyze
comparePlans(optimizedWithProject, correctAnswerWithProject)

val orderedTwiceWithFilter =
testRelation.orderBy('a.asc).where('b > Literal(0)).orderBy('b.desc)
val optimizedWithFilter = Optimize.execute(orderedTwiceWithFilter.analyze)
val correctAnswerWithFilter = testRelation.where('b > Literal(0)).orderBy('b.desc).analyze
comparePlans(optimizedWithFilter, correctAnswerWithFilter)

val orderedTwiceWithBoth =
testRelation.orderBy('a.asc).select('b).where('b > Literal(0)).orderBy('b.desc)
val optimizedWithBoth = Optimize.execute(orderedTwiceWithBoth.analyze)
val correctAnswerWithBoth =
testRelation.select('b).where('b > Literal(0)).orderBy('b.desc).analyze
comparePlans(optimizedWithBoth, correctAnswerWithBoth)

val orderedThrice = orderedTwiceWithBoth.select(('b + 1).as('c)).orderBy('c.asc)
val optimizedThrice = Optimize.execute(orderedThrice.analyze)
val correctAnswerThrice = testRelation.select('b).where('b > Literal(0))
.select(('b + 1).as('c)).orderBy('c.asc).analyze
comparePlans(optimizedThrice, correctAnswerThrice)
}
}