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author | Liang-Chi Hsieh <simonh@tw.ibm.com> | 2016-07-26 12:00:01 +0800 |
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committer | Wenchen Fan <wenchen@databricks.com> | 2016-07-26 12:00:01 +0800 |
commit | 7b06a8948fc16d3c14e240fdd632b79ce1651008 (patch) | |
tree | 8c70ae844421475b518091754ec7b986b5f52e3c /sql | |
parent | 815f3eece5f095919a329af8cbd762b9ed71c7a8 (diff) | |
download | spark-7b06a8948fc16d3c14e240fdd632b79ce1651008.tar.gz spark-7b06a8948fc16d3c14e240fdd632b79ce1651008.tar.bz2 spark-7b06a8948fc16d3c14e240fdd632b79ce1651008.zip |
[SPARK-16686][SQL] Remove PushProjectThroughSample since it is handled by ColumnPruning
## What changes were proposed in this pull request?
We push down `Project` through `Sample` in `Optimizer` by the rule `PushProjectThroughSample`. However, if the projected columns produce new output, they will encounter whole data instead of sampled data. It will bring some inconsistency between original plan (Sample then Project) and optimized plan (Project then Sample). In the extreme case such as attached in the JIRA, if the projected column is an UDF which is supposed to not see the sampled out data, the result of UDF will be incorrect.
Since the rule `ColumnPruning` already handles general `Project` pushdown. We don't need `PushProjectThroughSample` anymore. The rule `ColumnPruning` also avoids the described issue.
## How was this patch tested?
Jenkins tests.
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Closes #14327 from viirya/fix-sample-pushdown.
Diffstat (limited to 'sql')
4 files changed, 40 insertions, 29 deletions
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala index c8e9d8e2f9..fe328fd598 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala @@ -76,7 +76,6 @@ abstract class Optimizer(sessionCatalog: SessionCatalog, conf: CatalystConf) Batch("Operator Optimizations", fixedPoint, // Operator push down PushThroughSetOperations, - PushProjectThroughSample, ReorderJoin, EliminateOuterJoin, PushPredicateThroughJoin, @@ -149,17 +148,6 @@ class SimpleTestOptimizer extends Optimizer( new SimpleCatalystConf(caseSensitiveAnalysis = true)) /** - * Pushes projects down beneath Sample to enable column pruning with sampling. - */ -object PushProjectThroughSample extends Rule[LogicalPlan] { - def apply(plan: LogicalPlan): LogicalPlan = plan transform { - // Push down projection into sample - case Project(projectList, Sample(lb, up, replace, seed, child)) => - Sample(lb, up, replace, seed, Project(projectList, child))() - } -} - -/** * Removes the Project only conducting Alias of its child node. * It is created mainly for removing extra Project added in EliminateSerialization rule, * but can also benefit other operators. diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ColumnPruningSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ColumnPruningSuite.scala index b5664a5e69..589607e3ad 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ColumnPruningSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ColumnPruningSuite.scala @@ -346,5 +346,20 @@ class ColumnPruningSuite extends PlanTest { comparePlans(Optimize.execute(plan1.analyze), correctAnswer1) } + test("push project down into sample") { + val testRelation = LocalRelation('a.int, 'b.int, 'c.int) + val x = testRelation.subquery('x) + + val query1 = Sample(0.0, 0.6, false, 11L, x)().select('a) + val optimized1 = Optimize.execute(query1.analyze) + val expected1 = Sample(0.0, 0.6, false, 11L, x.select('a))() + comparePlans(optimized1, expected1.analyze) + + val query2 = Sample(0.0, 0.6, false, 11L, x)().select('a as 'aa) + val optimized2 = Optimize.execute(query2.analyze) + val expected2 = Sample(0.0, 0.6, false, 11L, x.select('a))().select('a as 'aa) + comparePlans(optimized2, expected2.analyze) + } + // todo: add more tests for column pruning } diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala index 780e78ed1c..596b8fcea1 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala @@ -34,7 +34,6 @@ class FilterPushdownSuite extends PlanTest { Batch("Subqueries", Once, EliminateSubqueryAliases) :: Batch("Filter Pushdown", FixedPoint(10), - PushProjectThroughSample, CombineFilters, PushDownPredicate, BooleanSimplification, @@ -585,22 +584,6 @@ class FilterPushdownSuite extends PlanTest { comparePlans(optimized, originalQuery) } - test("push project and filter down into sample") { - val x = testRelation.subquery('x) - val originalQuery = - Sample(0.0, 0.6, false, 11L, x)().select('a) - - val originalQueryAnalyzed = - EliminateSubqueryAliases(analysis.SimpleAnalyzer.execute(originalQuery)) - - val optimized = Optimize.execute(originalQueryAnalyzed) - - val correctAnswer = - Sample(0.0, 0.6, false, 11L, x.select('a))() - - comparePlans(optimized, correctAnswer.analyze) - } - test("aggregate: push down filter when filter on group by expression") { val originalQuery = testRelation .groupBy('a)('a, count('b) as 'c) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala index 0b6f40872f..7e3b7b63d8 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala @@ -422,6 +422,31 @@ class DatasetSuite extends QueryTest with SharedSQLContext { 3, 17, 27, 58, 62) } + test("SPARK-16686: Dataset.sample with seed results shouldn't depend on downstream usage") { + val simpleUdf = udf((n: Int) => { + require(n != 1, "simpleUdf shouldn't see id=1!") + 1 + }) + + val df = Seq( + (0, "string0"), + (1, "string1"), + (2, "string2"), + (3, "string3"), + (4, "string4"), + (5, "string5"), + (6, "string6"), + (7, "string7"), + (8, "string8"), + (9, "string9") + ).toDF("id", "stringData") + val sampleDF = df.sample(false, 0.7, 50) + // After sampling, sampleDF doesn't contain id=1. + assert(!sampleDF.select("id").collect.contains(1)) + // simpleUdf should not encounter id=1. + checkAnswer(sampleDF.select(simpleUdf($"id")), List.fill(sampleDF.count.toInt)(Row(1))) + } + test("SPARK-11436: we should rebind right encoder when join 2 datasets") { val ds1 = Seq("1", "2").toDS().as("a") val ds2 = Seq(2, 3).toDS().as("b") |