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[SPARK-12503][SPARK-12505] Limit pushdown in UNION ALL and OUTER JOIN
This patch adds a new optimizer rule for performing limit pushdown. Limits will now be pushed down in two cases: - If a limit is on top of a `UNION ALL` operator, then a partition-local limit operator will be pushed to each of the union operator's children. - If a limit is on top of an `OUTER JOIN` then a partition-local limit will be pushed to one side of the join. For `LEFT OUTER` and `RIGHT OUTER` joins, the limit will be pushed to the left and right side, respectively. For `FULL OUTER` join, we will only push limits when at most one of the inputs is already limited: if one input is limited we will push a smaller limit on top of it and if neither input is limited then we will limit the input which is estimated to be larger. These optimizations were proposed previously by gatorsmile in #10451 and #10454, but those earlier PRs were closed and deferred for later because at that time Spark's physical `Limit` operator would trigger a full shuffle to perform global limits so there was a chance that pushdowns could actually harm performance by causing additional shuffles/stages. In #7334, we split the `Limit` operator into separate `LocalLimit` and `GlobalLimit` operators, so we can now push down only local limits (which don't require extra shuffles). This patch is based on both of gatorsmile's patches, with changes and simplifications due to partition-local-limiting. When we push down the limit, we still keep the original limit in place, so we need a mechanism to ensure that the optimizer rule doesn't keep pattern-matching once the limit has been pushed down. In order to handle this, this patch adds a `maxRows` method to `SparkPlan` which returns the maximum number of rows that the plan can compute, then defines the pushdown rules to only push limits to children if the children's maxRows are greater than the limit's maxRows. This idea is carried over from #10451; see that patch for additional discussion. Author: Josh Rosen <joshrosen@databricks.com> Closes #11121 from JoshRosen/limit-pushdown-2.
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sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/LimitPushdownSuite.scala
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| /* | ||
| * 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. | ||
| */ | ||
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| package org.apache.spark.sql.catalyst.optimizer | ||
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| import org.apache.spark.sql.catalyst.analysis.EliminateSubQueries | ||
| import org.apache.spark.sql.catalyst.dsl.expressions._ | ||
| import org.apache.spark.sql.catalyst.dsl.plans._ | ||
| import org.apache.spark.sql.catalyst.expressions.Add | ||
| import org.apache.spark.sql.catalyst.plans.{FullOuter, LeftOuter, PlanTest, RightOuter} | ||
| import org.apache.spark.sql.catalyst.plans.logical._ | ||
| import org.apache.spark.sql.catalyst.rules._ | ||
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| class LimitPushdownSuite extends PlanTest { | ||
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| private object Optimize extends RuleExecutor[LogicalPlan] { | ||
| val batches = | ||
| Batch("Subqueries", Once, | ||
| EliminateSubQueries) :: | ||
| Batch("Limit pushdown", FixedPoint(100), | ||
| LimitPushDown, | ||
| CombineLimits, | ||
| ConstantFolding, | ||
| BooleanSimplification) :: Nil | ||
| } | ||
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| private val testRelation = LocalRelation('a.int, 'b.int, 'c.int) | ||
| private val testRelation2 = LocalRelation('d.int, 'e.int, 'f.int) | ||
| private val x = testRelation.subquery('x) | ||
| private val y = testRelation.subquery('y) | ||
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| // Union --------------------------------------------------------------------------------------- | ||
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| test("Union: limit to each side") { | ||
| val unionQuery = Union(testRelation, testRelation2).limit(1) | ||
| val unionOptimized = Optimize.execute(unionQuery.analyze) | ||
| val unionCorrectAnswer = | ||
| Limit(1, Union(LocalLimit(1, testRelation), LocalLimit(1, testRelation2))).analyze | ||
| comparePlans(unionOptimized, unionCorrectAnswer) | ||
| } | ||
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| test("Union: limit to each side with constant-foldable limit expressions") { | ||
| val unionQuery = Union(testRelation, testRelation2).limit(Add(1, 1)) | ||
| val unionOptimized = Optimize.execute(unionQuery.analyze) | ||
| val unionCorrectAnswer = | ||
| Limit(2, Union(LocalLimit(2, testRelation), LocalLimit(2, testRelation2))).analyze | ||
| comparePlans(unionOptimized, unionCorrectAnswer) | ||
| } | ||
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| test("Union: limit to each side with the new limit number") { | ||
| val unionQuery = Union(testRelation, testRelation2.limit(3)).limit(1) | ||
| val unionOptimized = Optimize.execute(unionQuery.analyze) | ||
| val unionCorrectAnswer = | ||
| Limit(1, Union(LocalLimit(1, testRelation), LocalLimit(1, testRelation2))).analyze | ||
| comparePlans(unionOptimized, unionCorrectAnswer) | ||
| } | ||
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| test("Union: no limit to both sides if children having smaller limit values") { | ||
| val unionQuery = Union(testRelation.limit(1), testRelation2.select('d).limit(1)).limit(2) | ||
| val unionOptimized = Optimize.execute(unionQuery.analyze) | ||
| val unionCorrectAnswer = | ||
| Limit(2, Union(testRelation.limit(1), testRelation2.select('d).limit(1))).analyze | ||
| comparePlans(unionOptimized, unionCorrectAnswer) | ||
| } | ||
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| test("Union: limit to each sides if children having larger limit values") { | ||
| val testLimitUnion = Union(testRelation.limit(3), testRelation2.select('d).limit(4)) | ||
| val unionQuery = testLimitUnion.limit(2) | ||
| val unionOptimized = Optimize.execute(unionQuery.analyze) | ||
| val unionCorrectAnswer = | ||
| Limit(2, Union(LocalLimit(2, testRelation), LocalLimit(2, testRelation2.select('d)))).analyze | ||
| comparePlans(unionOptimized, unionCorrectAnswer) | ||
| } | ||
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| // Outer join ---------------------------------------------------------------------------------- | ||
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| test("left outer join") { | ||
| val originalQuery = x.join(y, LeftOuter).limit(1) | ||
| val optimized = Optimize.execute(originalQuery.analyze) | ||
| val correctAnswer = Limit(1, LocalLimit(1, y).join(y, LeftOuter)).analyze | ||
| comparePlans(optimized, correctAnswer) | ||
| } | ||
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| test("right outer join") { | ||
| val originalQuery = x.join(y, RightOuter).limit(1) | ||
| val optimized = Optimize.execute(originalQuery.analyze) | ||
| val correctAnswer = Limit(1, x.join(LocalLimit(1, y), RightOuter)).analyze | ||
| comparePlans(optimized, correctAnswer) | ||
| } | ||
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| test("larger limits are not pushed on top of smaller ones in right outer join") { | ||
| val originalQuery = x.join(y.limit(5), RightOuter).limit(10) | ||
| val optimized = Optimize.execute(originalQuery.analyze) | ||
| val correctAnswer = Limit(10, x.join(Limit(5, y), RightOuter)).analyze | ||
| comparePlans(optimized, correctAnswer) | ||
| } | ||
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| test("full outer join where neither side is limited and both sides have same statistics") { | ||
| assert(x.statistics.sizeInBytes === y.statistics.sizeInBytes) | ||
| val originalQuery = x.join(y, FullOuter).limit(1) | ||
| val optimized = Optimize.execute(originalQuery.analyze) | ||
| val correctAnswer = Limit(1, LocalLimit(1, x).join(y, FullOuter)).analyze | ||
| comparePlans(optimized, correctAnswer) | ||
| } | ||
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| test("full outer join where neither side is limited and left side has larger statistics") { | ||
| val xBig = testRelation.copy(data = Seq.fill(2)(null)).subquery('x) | ||
| assert(xBig.statistics.sizeInBytes > y.statistics.sizeInBytes) | ||
| val originalQuery = xBig.join(y, FullOuter).limit(1) | ||
| val optimized = Optimize.execute(originalQuery.analyze) | ||
| val correctAnswer = Limit(1, LocalLimit(1, xBig).join(y, FullOuter)).analyze | ||
| comparePlans(optimized, correctAnswer) | ||
| } | ||
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| test("full outer join where neither side is limited and right side has larger statistics") { | ||
| val yBig = testRelation.copy(data = Seq.fill(2)(null)).subquery('y) | ||
| assert(x.statistics.sizeInBytes < yBig.statistics.sizeInBytes) | ||
| val originalQuery = x.join(yBig, FullOuter).limit(1) | ||
| val optimized = Optimize.execute(originalQuery.analyze) | ||
| val correctAnswer = Limit(1, x.join(LocalLimit(1, yBig), FullOuter)).analyze | ||
| comparePlans(optimized, correctAnswer) | ||
| } | ||
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| test("full outer join where both sides are limited") { | ||
| val originalQuery = x.limit(2).join(y.limit(2), FullOuter).limit(1) | ||
| val optimized = Optimize.execute(originalQuery.analyze) | ||
| val correctAnswer = Limit(1, Limit(2, x).join(Limit(2, y), FullOuter)).analyze | ||
| comparePlans(optimized, correctAnswer) | ||
| } | ||
| } | ||
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