beliefer commented on code in PR #38799:
URL: https://github.com/apache/spark/pull/38799#discussion_r1036961597
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala:
##########
@@ -627,6 +627,87 @@ abstract class SparkStrategies extends
QueryPlanner[SparkPlan] {
}
}
+ /**
+ * Optimize the filter based on rank-like window function by reduce not
required rows.
+ * This rule optimizes the following cases:
+ * {{{
+ * SELECT *, ROW_NUMBER() OVER(PARTITION BY k ORDER BY a) AS rn FROM Tab1
WHERE rn = 5
+ * SELECT *, ROW_NUMBER() OVER(PARTITION BY k ORDER BY a) AS rn FROM Tab1
WHERE 5 = rn
+ * SELECT *, ROW_NUMBER() OVER(PARTITION BY k ORDER BY a) AS rn FROM Tab1
WHERE rn < 5
+ * SELECT *, ROW_NUMBER() OVER(PARTITION BY k ORDER BY a) AS rn FROM Tab1
WHERE 5 > rn
+ * SELECT *, ROW_NUMBER() OVER(PARTITION BY k ORDER BY a) AS rn FROM Tab1
WHERE rn <= 5
+ * SELECT *, ROW_NUMBER() OVER(PARTITION BY k ORDER BY a) AS rn FROM Tab1
WHERE 5 >= rn
+ * }}}
+ */
+ object WindowGroupLimit extends Strategy with PredicateHelper {
+
+ /**
+ * Extract all the limit values from predicates.
+ */
+ def extractLimits(condition: Expression, attr: Attribute): Option[Int] = {
+ val limits = splitConjunctivePredicates(condition).collect {
+ case EqualTo(IntegerLiteral(limit), e) if e.semanticEquals(attr) =>
limit
+ case EqualTo(e, IntegerLiteral(limit)) if e.semanticEquals(attr) =>
limit
+ case LessThan(e, IntegerLiteral(limit)) if e.semanticEquals(attr) =>
limit - 1
+ case GreaterThan(IntegerLiteral(limit), e) if e.semanticEquals(attr)
=> limit - 1
+ case LessThanOrEqual(e, IntegerLiteral(limit)) if
e.semanticEquals(attr) => limit
+ case GreaterThanOrEqual(IntegerLiteral(limit), e) if
e.semanticEquals(attr) => limit
+ }
+
+ if (limits.nonEmpty) Some(limits.min) else None
+ }
+
+ private def supports(
+ windowExpressions: Seq[NamedExpression]): Boolean =
windowExpressions.exists {
+ case Alias(WindowExpression(_: Rank | _: DenseRank | _: RowNumber,
WindowSpecDefinition(_, _,
+ SpecifiedWindowFrame(RowFrame, UnboundedPreceding, CurrentRow))), _) =>
true
+ case _ => false
+ }
+
+ def apply(plan: LogicalPlan): Seq[SparkPlan] = {
+ if (conf.windowGroupLimitThreshold == -1) return Nil
+
+ plan match {
+ case filter @ Filter(condition,
+ window @ logical.Window(windowExpressions, partitionSpec, orderSpec,
child))
+ if !child.isInstanceOf[logical.Window] &&
+ supports(windowExpressions) && orderSpec.nonEmpty =>
+ val limits = windowExpressions.collect {
+ case alias @ Alias(WindowExpression(rankLikeFunction, _), _) =>
+ extractLimits(condition, alias.toAttribute).map((_,
rankLikeFunction))
+ }.filter(_.isDefined)
+
+ // non rank-like functions or multiple different rank-like functions
unsupported.
+ if (limits.isEmpty || limits.groupBy(_.get._2).size > 1) {
+ return Nil
+ }
+ val minLimit = limits.minBy(_.get._1)
+ minLimit match {
+ case Some((limit, rankLikeFunction)) if limit <=
conf.windowGroupLimitThreshold =>
+ if (limit > 0) {
+ // TODO: [SPARK-41337] Add a physical rule to remove the
partialLimitExec node,
+ // if there is no shuffle between the two nodes
(partialLimitExec's
+ // outputPartitioning satisfies the finalLimitExec's
requiredChildDistribution)
+ val partialLimitExec =
execution.window.WindowGroupLimitExec(partitionSpec,
+ orderSpec, rankLikeFunction, limit,
execution.window.Partial, planLater(child))
+ val finalLimitExec =
execution.window.WindowGroupLimitExec(partitionSpec,
+ orderSpec, rankLikeFunction, limit, execution.window.Final,
partialLimitExec)
+ val windowExec = execution.window.WindowExec(
+ windowExpressions, partitionSpec, orderSpec, finalLimitExec)
+ windowExec.setLogicalLink(window)
+ val filterExec = execution.FilterExec(condition, windowExec)
+ filterExec :: Nil
+ } else {
+ val localTableScanExec = LocalTableScanExec(filter.output,
Seq.empty)
Review Comment:
> maybe we can put it in other empty-relation related rules.
Maybe we can move it into `PruneFilters`.
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