diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala index 917b346086dcb..b88ec96bc5abc 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala @@ -107,7 +107,9 @@ case class GetField(child: Expression, fieldName: String) extends UnaryExpressio */ case class CreateArray(children: Seq[Expression]) extends Expression { override type EvaluatedType = Any - + + override def foldable = !children.exists(!_.foldable) + lazy val childTypes = children.map(_.dataType).distinct override lazy val resolved = diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala index b255a2ebb9778..7fece4b20f52d 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala @@ -164,6 +164,11 @@ private[hive] case class HiveGenericUdf(functionClassName: String, children: Seq override def foldable = isUDFDeterministic && returnInspector.isInstanceOf[ConstantObjectInspector] + @transient + protected def constantReturnValue = unwrap( + returnInspector.asInstanceOf[ConstantObjectInspector].getWritableConstantValue(), + returnInspector) + @transient protected lazy val deferedObjects = argumentInspectors.map(new DeferredObjectAdapter(_)).toArray[DeferredObject] @@ -172,6 +177,8 @@ private[hive] case class HiveGenericUdf(functionClassName: String, children: Seq override def eval(input: Row): Any = { returnInspector // Make sure initialized. + if(foldable) return constantReturnValue + var i = 0 while (i < children.length) { val idx = i @@ -198,12 +205,13 @@ private[hive] case class HiveGenericUdaf( @transient protected lazy val objectInspector = { - resolver.getEvaluator(children.map(_.dataType.toTypeInfo).toArray) + val parameterInfo = new SimpleGenericUDAFParameterInfo(inspectors.toArray, false, false) + resolver.getEvaluator(parameterInfo) .init(GenericUDAFEvaluator.Mode.COMPLETE, inspectors.toArray) } @transient - protected lazy val inspectors = children.map(_.dataType).map(toInspector) + protected lazy val inspectors = children.map(toInspector) def dataType: DataType = inspectorToDataType(objectInspector) @@ -228,12 +236,13 @@ private[hive] case class HiveUdaf( @transient protected lazy val objectInspector = { - resolver.getEvaluator(children.map(_.dataType.toTypeInfo).toArray) + val parameterInfo = new SimpleGenericUDAFParameterInfo(inspectors.toArray, false, false) + resolver.getEvaluator(parameterInfo) .init(GenericUDAFEvaluator.Mode.COMPLETE, inspectors.toArray) } @transient - protected lazy val inspectors = children.map(_.dataType).map(toInspector) + protected lazy val inspectors = children.map(toInspector) def dataType: DataType = inspectorToDataType(objectInspector) @@ -266,7 +275,7 @@ private[hive] case class HiveGenericUdtf( protected lazy val function: GenericUDTF = createFunction() @transient - protected lazy val inputInspectors = children.map(_.dataType).map(toInspector) + protected lazy val inputInspectors = children.map(toInspector) @transient protected lazy val outputInspector = function.initialize(inputInspectors.toArray) @@ -340,10 +349,13 @@ private[hive] case class HiveUdafFunction( } else { createFunction[AbstractGenericUDAFResolver]() } - - private val inspectors = exprs.map(_.dataType).map(toInspector).toArray - - private val function = resolver.getEvaluator(exprs.map(_.dataType.toTypeInfo).toArray) + + private val inspectors = exprs.map(toInspector).toArray + + private val function = { + val parameterInfo = new SimpleGenericUDAFParameterInfo(inspectors, false, false) + resolver.getEvaluator(parameterInfo) + } private val returnInspector = function.init(GenericUDAFEvaluator.Mode.COMPLETE, inspectors) @@ -356,8 +368,11 @@ private[hive] case class HiveUdafFunction( @transient val inputProjection = new InterpretedProjection(exprs) + @transient + protected lazy val cached = new Array[AnyRef](exprs.length) + def update(input: Row): Unit = { val inputs = inputProjection(input).asInstanceOf[Seq[AnyRef]].toArray - function.iterate(buffer, inputs) + function.iterate(buffer, wrap(inputs, inspectors, cached)) } } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala index 872f28d514efe..ff9385a591d6a 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala @@ -85,10 +85,21 @@ class HiveUdfSuite extends QueryTest { } test("SPARK-2693 udaf aggregates test") { - checkAnswer(sql("SELECT percentile(key,1) FROM src LIMIT 1"), + checkAnswer(sql("SELECT percentile(key, 1) FROM src LIMIT 1"), sql("SELECT max(key) FROM src").collect().toSeq) + + checkAnswer(sql("SELECT percentile(key, array(1, 1)) FROM src LIMIT 1"), + sql("SELECT array(max(key), max(key)) FROM src").collect().toSeq) } + test("Generic UDAF aggregates") { + checkAnswer(sql("SELECT ceiling(percentile_approx(key, 0.99999)) FROM src LIMIT 1"), + sql("SELECT max(key) FROM src LIMIT 1").collect().toSeq) + + checkAnswer(sql("SELECT percentile_approx(100.0, array(0.9, 0.9)) FROM src LIMIT 1"), + sql("SELECT array(100, 100) FROM src LIMIT 1").collect().toSeq) + } + test("UDFIntegerToString") { val testData = TestHive.sparkContext.parallelize( IntegerCaseClass(1) :: IntegerCaseClass(2) :: Nil)