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author | Cheng Lian <lian@databricks.com> | 2015-11-06 11:11:36 -0800 |
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committer | Yin Huai <yhuai@databricks.com> | 2015-11-06 11:11:36 -0800 |
commit | c048929c6a9f7ce57f384037cd6c0bf5751c447a (patch) | |
tree | 3a6ebf534b99a868df2fc6d51d4266422fc77eec /sql | |
parent | 574141a29835ce78d68c97bb54336cf4fd3c39d3 (diff) | |
download | spark-c048929c6a9f7ce57f384037cd6c0bf5751c447a.tar.gz spark-c048929c6a9f7ce57f384037cd6c0bf5751c447a.tar.bz2 spark-c048929c6a9f7ce57f384037cd6c0bf5751c447a.zip |
[SPARK-10978][SQL][FOLLOW-UP] More comprehensive tests for PR #9399
This PR adds test cases that test various column pruning and filter push-down cases.
Author: Cheng Lian <lian@databricks.com>
Closes #9468 from liancheng/spark-10978.follow-up.
Diffstat (limited to 'sql')
3 files changed, 321 insertions, 46 deletions
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala index 7541e72302..2cad964e55 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala @@ -17,16 +17,15 @@ package org.apache.spark.sql.sources -import org.apache.spark.sql.execution.datasources.LogicalRelation - import scala.language.existentials import org.apache.spark.rdd.RDD -import org.apache.spark.unsafe.types.UTF8String import org.apache.spark.sql._ +import org.apache.spark.sql.catalyst.expressions.PredicateHelper +import org.apache.spark.sql.execution.datasources.LogicalRelation import org.apache.spark.sql.test.SharedSQLContext import org.apache.spark.sql.types._ - +import org.apache.spark.unsafe.types.UTF8String class FilteredScanSource extends RelationProvider { override def createRelation( @@ -130,7 +129,7 @@ object ColumnsRequired { var set: Set[String] = Set.empty } -class FilteredScanSuite extends DataSourceTest with SharedSQLContext { +class FilteredScanSuite extends DataSourceTest with SharedSQLContext with PredicateHelper { protected override lazy val sql = caseInsensitiveContext.sql _ override def beforeAll(): Unit = { @@ -144,9 +143,6 @@ class FilteredScanSuite extends DataSourceTest with SharedSQLContext { | to '10' |) """.stripMargin) - - // UDF for testing filter push-down - caseInsensitiveContext.udf.register("udf_gt3", (_: Int) > 3) } sqlTest( @@ -276,14 +272,15 @@ class FilteredScanSuite extends DataSourceTest with SharedSQLContext { testPushDown("SELECT c FROM oneToTenFiltered WHERE c = 'aaaaaAAAAA'", 1, Set("c")) testPushDown("SELECT c FROM oneToTenFiltered WHERE c IN ('aaaaaAAAAA', 'foo')", 1, Set("c")) - // Columns only referenced by UDF filter must be required, as UDF filters can't be pushed down. - testPushDown("SELECT c FROM oneToTenFiltered WHERE udf_gt3(A)", 10, Set("a", "c")) + // Filters referencing multiple columns are not convertible, all referenced columns must be + // required. + testPushDown("SELECT c FROM oneToTenFiltered WHERE A + b > 9", 10, Set("a", "b", "c")) - // A query with an unconvertible filter, an unhandled filter, and a handled filter. + // A query with an inconvertible filter, an unhandled filter, and a handled filter. testPushDown( """SELECT a | FROM oneToTenFiltered - | WHERE udf_gt3(b) + | WHERE a + b > 9 | AND b < 16 | AND c IN ('bbbbbBBBBB', 'cccccCCCCC', 'dddddDDDDD', 'foo') """.stripMargin.split("\n").map(_.trim).mkString(" "), 3, Set("a", "b")) diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/sources/SimpleTextHadoopFsRelationSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/sources/SimpleTextHadoopFsRelationSuite.scala index d945408341..9251a69f31 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/sources/SimpleTextHadoopFsRelationSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/sources/SimpleTextHadoopFsRelationSuite.scala @@ -17,15 +17,21 @@ package org.apache.spark.sql.sources +import java.io.File + import org.apache.hadoop.fs.Path + +import org.apache.spark.sql.catalyst.expressions.Expression import org.apache.spark.deploy.SparkHadoopUtil -import org.apache.spark.sql.Row -import org.apache.spark.sql.catalyst.CatalystTypeConverters -import org.apache.spark.sql.execution.PhysicalRDD +import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute +import org.apache.spark.sql.catalyst.expressions.{AttributeReference, PredicateHelper} +import org.apache.spark.sql.execution.{LogicalRDD, PhysicalRDD} import org.apache.spark.sql.functions._ import org.apache.spark.sql.types._ +import org.apache.spark.sql.{Column, DataFrame, Row, execution} +import org.apache.spark.util.Utils -class SimpleTextHadoopFsRelationSuite extends HadoopFsRelationTest { +class SimpleTextHadoopFsRelationSuite extends HadoopFsRelationTest with PredicateHelper { import testImplicits._ override val dataSourceName: String = classOf[SimpleTextSource].getCanonicalName @@ -70,43 +76,304 @@ class SimpleTextHadoopFsRelationSuite extends HadoopFsRelationTest { } } - private val writer = testDF.write.option("dataSchema", dataSchema.json).format(dataSourceName) - private val reader = sqlContext.read.option("dataSchema", dataSchema.json).format(dataSourceName) - - test("unhandledFilters") { - withTempPath { dir => - - val path = dir.getCanonicalPath - writer.save(s"$path/p=0") - writer.save(s"$path/p=1") - - val isOdd = udf((_: Int) % 2 == 1) - val df = reader.load(path) - .filter( - // This filter is inconvertible - isOdd('a) && - // This filter is convertible but unhandled - 'a > 1 && - // This filter is convertible and handled - 'b > "val_1" && - // This filter references a partiiton column, won't be pushed down - 'p === 1 - ).select('a, 'p) - val rawScan = df.queryExecution.executedPlan collect { + private var tempPath: File = _ + + private var partitionedDF: DataFrame = _ + + private val partitionedDataSchema: StructType = StructType('a.int :: 'b.int :: 'c.string :: Nil) + + protected override def beforeAll(): Unit = { + this.tempPath = Utils.createTempDir() + + val df = sqlContext.range(10).select( + 'id cast IntegerType as 'a, + ('id cast IntegerType) * 2 as 'b, + concat(lit("val_"), 'id) as 'c + ) + + partitionedWriter(df).save(s"${tempPath.getCanonicalPath}/p=0") + partitionedWriter(df).save(s"${tempPath.getCanonicalPath}/p=1") + + partitionedDF = partitionedReader.load(tempPath.getCanonicalPath) + } + + override protected def afterAll(): Unit = { + Utils.deleteRecursively(tempPath) + } + + private def partitionedWriter(df: DataFrame) = + df.write.option("dataSchema", partitionedDataSchema.json).format(dataSourceName) + + private def partitionedReader = + sqlContext.read.option("dataSchema", partitionedDataSchema.json).format(dataSourceName) + + /** + * Constructs test cases that test column pruning and filter push-down. + * + * For filter push-down, the following filters are not pushed-down. + * + * 1. Partitioning filters don't participate filter push-down, they are handled separately in + * `DataSourceStrategy` + * + * 2. Catalyst filter `Expression`s that cannot be converted to data source `Filter`s are not + * pushed down (e.g. UDF and filters referencing multiple columns). + * + * 3. Catalyst filter `Expression`s that can be converted to data source `Filter`s but cannot be + * handled by the underlying data source are not pushed down (e.g. returned from + * `BaseRelation.unhandledFilters()`). + * + * Note that for [[SimpleTextRelation]], all data source [[Filter]]s other than [[GreaterThan]] + * are unhandled. We made this assumption in [[SimpleTextRelation.unhandledFilters()]] only + * for testing purposes. + * + * @param projections Projection list of the query + * @param filter Filter condition of the query + * @param requiredColumns Expected names of required columns + * @param pushedFilters Expected data source [[Filter]]s that are pushed down + * @param inconvertibleFilters Expected Catalyst filter [[Expression]]s that cannot be converted + * to data source [[Filter]]s + * @param unhandledFilters Expected Catalyst flter [[Expression]]s that can be converted to data + * source [[Filter]]s but cannot be handled by the data source relation + * @param partitioningFilters Expected Catalyst filter [[Expression]]s that reference partition + * columns + * @param expectedRawScanAnswer Expected query result of the raw table scan returned by the data + * source relation + * @param expectedAnswer Expected query result of the full query + */ + def testPruningAndFiltering( + projections: Seq[Column], + filter: Column, + requiredColumns: Seq[String], + pushedFilters: Seq[Filter], + inconvertibleFilters: Seq[Column], + unhandledFilters: Seq[Column], + partitioningFilters: Seq[Column])( + expectedRawScanAnswer: => Seq[Row])( + expectedAnswer: => Seq[Row]): Unit = { + test(s"pruning and filtering: df.select(${projections.mkString(", ")}).where($filter)") { + val df = partitionedDF.where(filter).select(projections: _*) + val queryExecution = df.queryExecution + val executedPlan = queryExecution.executedPlan + + val rawScan = executedPlan.collect { case p: PhysicalRDD => p } match { - case Seq(p) => p + case Seq(scan) => scan + case _ => fail(s"More than one PhysicalRDD found\n$queryExecution") } - val outputSchema = new StructType().add("a", IntegerType).add("p", IntegerType) + markup("Checking raw scan answer") + checkAnswer( + DataFrame(sqlContext, LogicalRDD(rawScan.output, rawScan.rdd)(sqlContext)), + expectedRawScanAnswer) - assertResult(Set((2, 1), (3, 1))) { - rawScan.execute().collect() - .map { CatalystTypeConverters.convertToScala(_, outputSchema) } - .map { case Row(a, p) => (a, p) }.toSet + markup("Checking full query answer") + checkAnswer(df, expectedAnswer) + + markup("Checking required columns") + assert(requiredColumns === SimpleTextRelation.requiredColumns) + + val nonPushedFilters = { + val boundFilters = executedPlan.collect { + case f: execution.Filter => f + } match { + case Nil => Nil + case Seq(f) => splitConjunctivePredicates(f.condition) + case _ => fail(s"More than one PhysicalRDD found\n$queryExecution") + } + + // Unbound these bound filters so that we can easily compare them with expected results. + boundFilters.map { + _.transform { case a: AttributeReference => UnresolvedAttribute(a.name) } + }.toSet } - checkAnswer(df, Row(3, 1)) + markup("Checking pushed filters") + assert(SimpleTextRelation.pushedFilters === pushedFilters.toSet) + + val expectedInconvertibleFilters = inconvertibleFilters.map(_.expr).toSet + val expectedUnhandledFilters = unhandledFilters.map(_.expr).toSet + val expectedPartitioningFilters = partitioningFilters.map(_.expr).toSet + + markup("Checking unhandled and inconvertible filters") + assert(expectedInconvertibleFilters ++ expectedUnhandledFilters === nonPushedFilters) + + markup("Checking partitioning filters") + val actualPartitioningFilters = splitConjunctivePredicates(filter.expr).filter { + _.references.contains(UnresolvedAttribute("p")) + }.toSet + + // Partitioning filters are handled separately and don't participate filter push-down. So they + // shouldn't be part of non-pushed filters. + assert(expectedPartitioningFilters.intersect(nonPushedFilters).isEmpty) + assert(expectedPartitioningFilters === actualPartitioningFilters) } } + + testPruningAndFiltering( + projections = Seq('*), + filter = 'p > 0, + requiredColumns = Seq("a", "b", "c"), + pushedFilters = Nil, + inconvertibleFilters = Nil, + unhandledFilters = Nil, + partitioningFilters = Seq('p > 0) + ) { + Seq( + Row(0, 0, "val_0", 1), + Row(1, 2, "val_1", 1), + Row(2, 4, "val_2", 1), + Row(3, 6, "val_3", 1), + Row(4, 8, "val_4", 1), + Row(5, 10, "val_5", 1), + Row(6, 12, "val_6", 1), + Row(7, 14, "val_7", 1), + Row(8, 16, "val_8", 1), + Row(9, 18, "val_9", 1)) + } { + Seq( + Row(0, 0, "val_0", 1), + Row(1, 2, "val_1", 1), + Row(2, 4, "val_2", 1), + Row(3, 6, "val_3", 1), + Row(4, 8, "val_4", 1), + Row(5, 10, "val_5", 1), + Row(6, 12, "val_6", 1), + Row(7, 14, "val_7", 1), + Row(8, 16, "val_8", 1), + Row(9, 18, "val_9", 1)) + } + + testPruningAndFiltering( + projections = Seq('c, 'p), + filter = 'a < 3 && 'p > 0, + requiredColumns = Seq("c", "a"), + pushedFilters = Nil, + inconvertibleFilters = Nil, + unhandledFilters = Seq('a < 3), + partitioningFilters = Seq('p > 0) + ) { + Seq( + Row("val_0", 1, 0), + Row("val_1", 1, 1), + Row("val_2", 1, 2), + Row("val_3", 1, 3), + Row("val_4", 1, 4), + Row("val_5", 1, 5), + Row("val_6", 1, 6), + Row("val_7", 1, 7), + Row("val_8", 1, 8), + Row("val_9", 1, 9)) + } { + Seq( + Row("val_0", 1), + Row("val_1", 1), + Row("val_2", 1)) + } + + testPruningAndFiltering( + projections = Seq('*), + filter = 'a > 8, + requiredColumns = Seq("a", "b", "c"), + pushedFilters = Seq(GreaterThan("a", 8)), + inconvertibleFilters = Nil, + unhandledFilters = Nil, + partitioningFilters = Nil + ) { + Seq( + Row(9, 18, "val_9", 0), + Row(9, 18, "val_9", 1)) + } { + Seq( + Row(9, 18, "val_9", 0), + Row(9, 18, "val_9", 1)) + } + + testPruningAndFiltering( + projections = Seq('b, 'p), + filter = 'a > 8, + requiredColumns = Seq("b"), + pushedFilters = Seq(GreaterThan("a", 8)), + inconvertibleFilters = Nil, + unhandledFilters = Nil, + partitioningFilters = Nil + ) { + Seq( + Row(18, 0), + Row(18, 1)) + } { + Seq( + Row(18, 0), + Row(18, 1)) + } + + testPruningAndFiltering( + projections = Seq('b, 'p), + filter = 'a > 8 && 'p > 0, + requiredColumns = Seq("b"), + pushedFilters = Seq(GreaterThan("a", 8)), + inconvertibleFilters = Nil, + unhandledFilters = Nil, + partitioningFilters = Seq('p > 0) + ) { + Seq( + Row(18, 1)) + } { + Seq( + Row(18, 1)) + } + + testPruningAndFiltering( + projections = Seq('b, 'p), + filter = 'c > "val_7" && 'b < 18 && 'p > 0, + requiredColumns = Seq("b"), + pushedFilters = Seq(GreaterThan("c", "val_7")), + inconvertibleFilters = Nil, + unhandledFilters = Seq('b < 18), + partitioningFilters = Seq('p > 0) + ) { + Seq( + Row(16, 1), + Row(18, 1)) + } { + Seq( + Row(16, 1)) + } + + testPruningAndFiltering( + projections = Seq('b, 'p), + filter = 'a % 2 === 0 && 'c > "val_7" && 'b < 18 && 'p > 0, + requiredColumns = Seq("b", "a"), + pushedFilters = Seq(GreaterThan("c", "val_7")), + inconvertibleFilters = Seq('a % 2 === 0), + unhandledFilters = Seq('b < 18), + partitioningFilters = Seq('p > 0) + ) { + Seq( + Row(16, 1, 8), + Row(18, 1, 9)) + } { + Seq( + Row(16, 1)) + } + + testPruningAndFiltering( + projections = Seq('b, 'p), + filter = 'a > 7 && 'a < 9, + requiredColumns = Seq("b", "a"), + pushedFilters = Seq(GreaterThan("a", 7)), + inconvertibleFilters = Nil, + unhandledFilters = Seq('a < 9), + partitioningFilters = Nil + ) { + Seq( + Row(16, 0, 8), + Row(16, 1, 8), + Row(18, 0, 9), + Row(18, 1, 9)) + } { + Seq( + Row(16, 0), + Row(16, 1)) + } } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/sources/SimpleTextRelation.scala b/sql/hive/src/test/scala/org/apache/spark/sql/sources/SimpleTextRelation.scala index da09e1b00a..bdc48a383b 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/sources/SimpleTextRelation.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/sources/SimpleTextRelation.scala @@ -128,6 +128,9 @@ class SimpleTextRelation( filters: Array[Filter], inputFiles: Array[FileStatus]): RDD[Row] = { + SimpleTextRelation.requiredColumns = requiredColumns + SimpleTextRelation.pushedFilters = filters.toSet + val fields = this.dataSchema.map(_.dataType) val inputAttributes = this.dataSchema.toAttributes val outputAttributes = requiredColumns.flatMap(name => inputAttributes.find(_.name == name)) @@ -191,6 +194,14 @@ class SimpleTextRelation( } } +object SimpleTextRelation { + // Used to test column pruning + var requiredColumns: Seq[String] = Nil + + // Used to test filter push-down + var pushedFilters: Set[Filter] = Set.empty +} + /** * A simple example [[HadoopFsRelationProvider]]. */ |