diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
index 5e42b409dcc59645d9c96b2a8126b70c06ad923e..7b543b6c2aa42316084c36bd854648f01c32070e 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
@@ -17,6 +17,8 @@
package org.apache.spark.sql.catalyst.analysis
+import scala.collection.mutable.ArrayBuffer
+
import org.apache.spark.util.collection.OpenHashSet
import org.apache.spark.sql.AnalysisException
import org.apache.spark.sql.catalyst.expressions._
@@ -61,6 +63,7 @@ class Analyzer(
ResolveGenerate ::
ImplicitGenerate ::
ResolveFunctions ::
+ ExtractWindowExpressions ::
GlobalAggregates ::
UnresolvedHavingClauseAttributes ::
TrimGroupingAliases ::
@@ -529,6 +532,203 @@ class Analyzer(
makeGeneratorOutput(p.generator, p.generatorOutput), p.child)
}
}
+
+ /**
+ * Extracts [[WindowExpression]]s from the projectList of a [[Project]] operator and
+ * aggregateExpressions of an [[Aggregate]] operator and creates individual [[Window]]
+ * operators for every distinct [[WindowSpecDefinition]].
+ *
+ * This rule handles three cases:
+ * - A [[Project]] having [[WindowExpression]]s in its projectList;
+ * - An [[Aggregate]] having [[WindowExpression]]s in its aggregateExpressions.
+ * - An [[Filter]]->[[Aggregate]] pattern representing GROUP BY with a HAVING
+ * clause and the [[Aggregate]] has [[WindowExpression]]s in its aggregateExpressions.
+ * Note: If there is a GROUP BY clause in the query, aggregations and corresponding
+ * filters (expressions in the HAVING clause) should be evaluated before any
+ * [[WindowExpression]]. If a query has SELECT DISTINCT, the DISTINCT part should be
+ * evaluated after all [[WindowExpression]]s.
+ *
+ * For every case, the transformation works as follows:
+ * 1. For a list of [[Expression]]s (a projectList or an aggregateExpressions), partitions
+ * it two lists of [[Expression]]s, one for all [[WindowExpression]]s and another for
+ * all regular expressions.
+ * 2. For all [[WindowExpression]]s, groups them based on their [[WindowSpecDefinition]]s.
+ * 3. For every distinct [[WindowSpecDefinition]], creates a [[Window]] operator and inserts
+ * it into the plan tree.
+ */
+ object ExtractWindowExpressions extends Rule[LogicalPlan] {
+ def hasWindowFunction(projectList: Seq[NamedExpression]): Boolean =
+ projectList.exists(hasWindowFunction)
+
+ def hasWindowFunction(expr: NamedExpression): Boolean = {
+ expr.find {
+ case window: WindowExpression => true
+ case _ => false
+ }.isDefined
+ }
+
+ /**
+ * From a Seq of [[NamedExpression]]s, extract window expressions and
+ * other regular expressions.
+ */
+ def extract(
+ expressions: Seq[NamedExpression]): (Seq[NamedExpression], Seq[NamedExpression]) = {
+ // First, we simple partition the input expressions to two part, one having
+ // WindowExpressions and another one without WindowExpressions.
+ val (windowExpressions, regularExpressions) = expressions.partition(hasWindowFunction)
+
+ // Then, we need to extract those regular expressions used in the WindowExpression.
+ // For example, when we have col1 - Sum(col2 + col3) OVER (PARTITION BY col4 ORDER BY col5),
+ // we need to make sure that col1 to col5 are all projected from the child of the Window
+ // operator.
+ val extractedExprBuffer = new ArrayBuffer[NamedExpression]()
+ def extractExpr(expr: Expression): Expression = expr match {
+ case ne: NamedExpression =>
+ // If a named expression is not in regularExpressions, add extract it and replace it
+ // with an AttributeReference.
+ val missingExpr =
+ AttributeSet(Seq(expr)) -- (regularExpressions ++ extractedExprBuffer)
+ if (missingExpr.nonEmpty) {
+ extractedExprBuffer += ne
+ }
+ ne.toAttribute
+ case e: Expression if e.foldable =>
+ e // No need to create an attribute reference if it will be evaluated as a Literal.
+ case e: Expression =>
+ // For other expressions, we extract it and replace it with an AttributeReference (with
+ // an interal column name, e.g. "_w0").
+ val withName = Alias(e, s"_w${extractedExprBuffer.length}")()
+ extractedExprBuffer += withName
+ withName.toAttribute
+ }
+
+ // Now, we extract expressions from windowExpressions by using extractExpr.
+ val newWindowExpressions = windowExpressions.map {
+ _.transform {
+ // Extracts children expressions of a WindowFunction (input parameters of
+ // a WindowFunction).
+ case wf : WindowFunction =>
+ val newChildren = wf.children.map(extractExpr(_))
+ wf.withNewChildren(newChildren)
+
+ // Extracts expressions from the partition spec and order spec.
+ case wsc @ WindowSpecDefinition(partitionSpec, orderSpec, _) =>
+ val newPartitionSpec = partitionSpec.map(extractExpr(_))
+ val newOrderSpec = orderSpec.map { so =>
+ val newChild = extractExpr(so.child)
+ so.copy(child = newChild)
+ }
+ wsc.copy(partitionSpec = newPartitionSpec, orderSpec = newOrderSpec)
+
+ // Extracts AggregateExpression. For example, for SUM(x) - Sum(y) OVER (...),
+ // we need to extract SUM(x).
+ case agg: AggregateExpression =>
+ val withName = Alias(agg, s"_w${extractedExprBuffer.length}")()
+ extractedExprBuffer += withName
+ withName.toAttribute
+ }.asInstanceOf[NamedExpression]
+ }
+
+ (newWindowExpressions, regularExpressions ++ extractedExprBuffer)
+ }
+
+ /**
+ * Adds operators for Window Expressions. Every Window operator handles a single Window Spec.
+ */
+ def addWindow(windowExpressions: Seq[NamedExpression], child: LogicalPlan): LogicalPlan = {
+ // First, we group window expressions based on their Window Spec.
+ val groupedWindowExpression = windowExpressions.groupBy { expr =>
+ val windowExpression = expr.find {
+ case window: WindowExpression => true
+ case other => false
+ }.map(_.asInstanceOf[WindowExpression].windowSpec)
+ windowExpression.getOrElse(
+ failAnalysis(s"$windowExpressions does not have any WindowExpression."))
+ }.toSeq
+
+ // For every Window Spec, we add a Window operator and set currentChild as the child of it.
+ var currentChild = child
+ var i = 0
+ while (i < groupedWindowExpression.size) {
+ val (windowSpec, windowExpressions) = groupedWindowExpression(i)
+ // Set currentChild to the newly created Window operator.
+ currentChild = Window(currentChild.output, windowExpressions, windowSpec, currentChild)
+
+ // Move to next WindowExpression.
+ i += 1
+ }
+
+ // We return the top operator.
+ currentChild
+ }
+
+ // We have to use transformDown at here to make sure the rule of
+ // "Aggregate with Having clause" will be triggered.
+ def apply(plan: LogicalPlan): LogicalPlan = plan transformDown {
+ // Lookup WindowSpecDefinitions. This rule works with unresolved children.
+ case WithWindowDefinition(windowDefinitions, child) =>
+ child.transform {
+ case plan => plan.transformExpressions {
+ case UnresolvedWindowExpression(c, WindowSpecReference(windowName)) =>
+ val errorMessage =
+ s"Window specification $windowName is not defined in the WINDOW clause."
+ val windowSpecDefinition =
+ windowDefinitions
+ .get(windowName)
+ .getOrElse(failAnalysis(errorMessage))
+ WindowExpression(c, windowSpecDefinition)
+ }
+ }
+
+ // Aggregate with Having clause. This rule works with an unresolved Aggregate because
+ // a resolved Aggregate will not have Window Functions.
+ case f @ Filter(condition, a @ Aggregate(groupingExprs, aggregateExprs, child))
+ if child.resolved &&
+ hasWindowFunction(aggregateExprs) &&
+ !a.expressions.exists(!_.resolved) =>
+ val (windowExpressions, aggregateExpressions) = extract(aggregateExprs)
+ // Create an Aggregate operator to evaluate aggregation functions.
+ val withAggregate = Aggregate(groupingExprs, aggregateExpressions, child)
+ // Add a Filter operator for conditions in the Having clause.
+ val withFilter = Filter(condition, withAggregate)
+ val withWindow = addWindow(windowExpressions, withFilter)
+
+ // Finally, generate output columns according to the original projectList.
+ val finalProjectList = aggregateExprs.map (_.toAttribute)
+ Project(finalProjectList, withWindow)
+
+ case p: LogicalPlan if !p.childrenResolved => p
+
+ // Aggregate without Having clause.
+ case a @ Aggregate(groupingExprs, aggregateExprs, child)
+ if hasWindowFunction(aggregateExprs) &&
+ !a.expressions.exists(!_.resolved) =>
+ val (windowExpressions, aggregateExpressions) = extract(aggregateExprs)
+ // Create an Aggregate operator to evaluate aggregation functions.
+ val withAggregate = Aggregate(groupingExprs, aggregateExpressions, child)
+ // Add Window operators.
+ val withWindow = addWindow(windowExpressions, withAggregate)
+
+ // Finally, generate output columns according to the original projectList.
+ val finalProjectList = aggregateExprs.map (_.toAttribute)
+ Project(finalProjectList, withWindow)
+
+ // We only extract Window Expressions after all expressions of the Project
+ // have been resolved.
+ case p @ Project(projectList, child)
+ if hasWindowFunction(projectList) && !p.expressions.exists(!_.resolved) =>
+ val (windowExpressions, regularExpressions) = extract(projectList)
+ // We add a project to get all needed expressions for window expressions from the child
+ // of the original Project operator.
+ val withProject = Project(regularExpressions, child)
+ // Add Window operators.
+ val withWindow = addWindow(windowExpressions, withProject)
+
+ // Finally, generate output columns according to the original projectList.
+ val finalProjectList = projectList.map (_.toAttribute)
+ Project(finalProjectList, withWindow)
+ }
+ }
}
/**
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
index 2381689e17525c4f75bf6c03780508e217239804..c8288c6767004a6f165a70a1b4ffe5b3748936c4 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
@@ -70,6 +70,11 @@ trait CheckAnalysis {
failAnalysis(
s"invalid expression ${b.prettyString} " +
s"between ${b.left.simpleString} and ${b.right.simpleString}")
+
+ case w @ WindowExpression(windowFunction, windowSpec) if windowSpec.validate.nonEmpty =>
+ // The window spec is not valid.
+ val reason = windowSpec.validate.get
+ failAnalysis(s"Window specification $windowSpec is not valid because $reason")
}
operator match {
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Projection.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Projection.scala
index c2866cd955409379501abfdf33c1eccb62a87b9d..8cae548279eb166c5884998eed90e5116fb0659f 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Projection.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Projection.scala
@@ -548,3 +548,97 @@ class JoinedRow5 extends Row {
}
}
}
+
+/**
+ * JIT HACK: Replace with macros
+ */
+class JoinedRow6 extends Row {
+ private[this] var row1: Row = _
+ private[this] var row2: Row = _
+
+ def this(left: Row, right: Row) = {
+ this()
+ row1 = left
+ row2 = right
+ }
+
+ /** Updates this JoinedRow to used point at two new base rows. Returns itself. */
+ def apply(r1: Row, r2: Row): Row = {
+ row1 = r1
+ row2 = r2
+ this
+ }
+
+ /** Updates this JoinedRow by updating its left base row. Returns itself. */
+ def withLeft(newLeft: Row): Row = {
+ row1 = newLeft
+ this
+ }
+
+ /** Updates this JoinedRow by updating its right base row. Returns itself. */
+ def withRight(newRight: Row): Row = {
+ row2 = newRight
+ this
+ }
+
+ override def toSeq: Seq[Any] = row1.toSeq ++ row2.toSeq
+
+ override def length: Int = row1.length + row2.length
+
+ override def apply(i: Int): Any =
+ if (i < row1.length) row1(i) else row2(i - row1.length)
+
+ override def isNullAt(i: Int): Boolean =
+ if (i < row1.length) row1.isNullAt(i) else row2.isNullAt(i - row1.length)
+
+ override def getInt(i: Int): Int =
+ if (i < row1.length) row1.getInt(i) else row2.getInt(i - row1.length)
+
+ override def getLong(i: Int): Long =
+ if (i < row1.length) row1.getLong(i) else row2.getLong(i - row1.length)
+
+ override def getDouble(i: Int): Double =
+ if (i < row1.length) row1.getDouble(i) else row2.getDouble(i - row1.length)
+
+ override def getBoolean(i: Int): Boolean =
+ if (i < row1.length) row1.getBoolean(i) else row2.getBoolean(i - row1.length)
+
+ override def getShort(i: Int): Short =
+ if (i < row1.length) row1.getShort(i) else row2.getShort(i - row1.length)
+
+ override def getByte(i: Int): Byte =
+ if (i < row1.length) row1.getByte(i) else row2.getByte(i - row1.length)
+
+ override def getFloat(i: Int): Float =
+ if (i < row1.length) row1.getFloat(i) else row2.getFloat(i - row1.length)
+
+ override def getString(i: Int): String =
+ if (i < row1.length) row1.getString(i) else row2.getString(i - row1.length)
+
+ override def getAs[T](i: Int): T =
+ if (i < row1.length) row1.getAs[T](i) else row2.getAs[T](i - row1.length)
+
+ override def copy(): Row = {
+ val totalSize = row1.length + row2.length
+ val copiedValues = new Array[Any](totalSize)
+ var i = 0
+ while(i < totalSize) {
+ copiedValues(i) = apply(i)
+ i += 1
+ }
+ new GenericRow(copiedValues)
+ }
+
+ override def toString: String = {
+ // Make sure toString never throws NullPointerException.
+ if ((row1 eq null) && (row2 eq null)) {
+ "[ empty row ]"
+ } else if (row1 eq null) {
+ row2.mkString("[", ",", "]")
+ } else if (row2 eq null) {
+ row1.mkString("[", ",", "]")
+ } else {
+ mkString("[", ",", "]")
+ }
+ }
+}
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala
new file mode 100644
index 0000000000000000000000000000000000000000..099d67ca7fee3a3d0ae09ed0795c7715f726cef5
--- /dev/null
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala
@@ -0,0 +1,340 @@
+/*
+ * 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.
+ */
+
+package org.apache.spark.sql.catalyst.expressions
+
+import org.apache.spark.sql.catalyst.analysis.UnresolvedException
+import org.apache.spark.sql.catalyst.errors.TreeNodeException
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.types.{NumericType, DataType}
+
+/**
+ * The trait of the Window Specification (specified in the OVER clause or WINDOW clause) for
+ * Window Functions.
+ */
+sealed trait WindowSpec
+
+/**
+ * The specification for a window function.
+ * @param partitionSpec It defines the way that input rows are partitioned.
+ * @param orderSpec It defines the ordering of rows in a partition.
+ * @param frameSpecification It defines the window frame in a partition.
+ */
+case class WindowSpecDefinition(
+ partitionSpec: Seq[Expression],
+ orderSpec: Seq[SortOrder],
+ frameSpecification: WindowFrame) extends Expression with WindowSpec {
+
+ def validate: Option[String] = frameSpecification match {
+ case UnspecifiedFrame =>
+ Some("Found a UnspecifiedFrame. It should be converted to a SpecifiedWindowFrame " +
+ "during analysis. Please file a bug report.")
+ case frame: SpecifiedWindowFrame => frame.validate.orElse {
+ def checkValueBasedBoundaryForRangeFrame(): Option[String] = {
+ if (orderSpec.length > 1) {
+ // It is not allowed to have a value-based PRECEDING and FOLLOWING
+ // as the boundary of a Range Window Frame.
+ Some("This Range Window Frame only accepts at most one ORDER BY expression.")
+ } else if (orderSpec.nonEmpty && !orderSpec.head.dataType.isInstanceOf[NumericType]) {
+ Some("The data type of the expression in the ORDER BY clause should be a numeric type.")
+ } else {
+ None
+ }
+ }
+
+ (frame.frameType, frame.frameStart, frame.frameEnd) match {
+ case (RangeFrame, vp: ValuePreceding, _) => checkValueBasedBoundaryForRangeFrame()
+ case (RangeFrame, vf: ValueFollowing, _) => checkValueBasedBoundaryForRangeFrame()
+ case (RangeFrame, _, vp: ValuePreceding) => checkValueBasedBoundaryForRangeFrame()
+ case (RangeFrame, _, vf: ValueFollowing) => checkValueBasedBoundaryForRangeFrame()
+ case (_, _, _) => None
+ }
+ }
+ }
+
+ type EvaluatedType = Any
+
+ override def children: Seq[Expression] = partitionSpec ++ orderSpec
+
+ override lazy val resolved: Boolean =
+ childrenResolved && frameSpecification.isInstanceOf[SpecifiedWindowFrame]
+
+
+ override def toString: String = simpleString
+
+ override def eval(input: Row): EvaluatedType = throw new UnsupportedOperationException
+ override def nullable: Boolean = true
+ override def foldable: Boolean = false
+ override def dataType: DataType = throw new UnsupportedOperationException
+}
+
+/**
+ * A Window specification reference that refers to the [[WindowSpecDefinition]] defined
+ * under the name `name`.
+ */
+case class WindowSpecReference(name: String) extends WindowSpec
+
+/**
+ * The trait used to represent the type of a Window Frame.
+ */
+sealed trait FrameType
+
+/**
+ * RowFrame treats rows in a partition individually. When a [[ValuePreceding]]
+ * or a [[ValueFollowing]] is used as its [[FrameBoundary]], the value is considered
+ * as a physical offset.
+ * For example, `ROW BETWEEN 1 PRECEDING AND 1 FOLLOWING` represents a 3-row frame,
+ * from the row precedes the current row to the row follows the current row.
+ */
+case object RowFrame extends FrameType
+
+/**
+ * RangeFrame treats rows in a partition as groups of peers.
+ * All rows having the same `ORDER BY` ordering are considered as peers.
+ * When a [[ValuePreceding]] or a [[ValueFollowing]] is used as its [[FrameBoundary]],
+ * the value is considered as a logical offset.
+ * For example, assuming the value of the current row's `ORDER BY` expression `expr` is `v`,
+ * `RANGE BETWEEN 1 PRECEDING AND 1 FOLLOWING` represents a frame containing rows whose values
+ * `expr` are in the range of [v-1, v+1].
+ *
+ * If `ORDER BY` clause is not defined, all rows in the partition is considered as peers
+ * of the current row.
+ */
+case object RangeFrame extends FrameType
+
+/**
+ * The trait used to represent the type of a Window Frame Boundary.
+ */
+sealed trait FrameBoundary {
+ def notFollows(other: FrameBoundary): Boolean
+}
+
+/** UNBOUNDED PRECEDING boundary. */
+case object UnboundedPreceding extends FrameBoundary {
+ def notFollows(other: FrameBoundary): Boolean = other match {
+ case UnboundedPreceding => true
+ case vp: ValuePreceding => true
+ case CurrentRow => true
+ case vf: ValueFollowing => true
+ case UnboundedFollowing => true
+ }
+
+ override def toString: String = "UNBOUNDED PRECEDING"
+}
+
+/** <value> PRECEDING boundary. */
+case class ValuePreceding(value: Int) extends FrameBoundary {
+ def notFollows(other: FrameBoundary): Boolean = other match {
+ case UnboundedPreceding => false
+ case ValuePreceding(anotherValue) => value >= anotherValue
+ case CurrentRow => true
+ case vf: ValueFollowing => true
+ case UnboundedFollowing => true
+ }
+
+ override def toString: String = s"$value PRECEDING"
+}
+
+/** CURRENT ROW boundary. */
+case object CurrentRow extends FrameBoundary {
+ def notFollows(other: FrameBoundary): Boolean = other match {
+ case UnboundedPreceding => false
+ case vp: ValuePreceding => false
+ case CurrentRow => true
+ case vf: ValueFollowing => true
+ case UnboundedFollowing => true
+ }
+
+ override def toString: String = "CURRENT ROW"
+}
+
+/** <value> FOLLOWING boundary. */
+case class ValueFollowing(value: Int) extends FrameBoundary {
+ def notFollows(other: FrameBoundary): Boolean = other match {
+ case UnboundedPreceding => false
+ case vp: ValuePreceding => false
+ case CurrentRow => false
+ case ValueFollowing(anotherValue) => value <= anotherValue
+ case UnboundedFollowing => true
+ }
+
+ override def toString: String = s"$value FOLLOWING"
+}
+
+/** UNBOUNDED FOLLOWING boundary. */
+case object UnboundedFollowing extends FrameBoundary {
+ def notFollows(other: FrameBoundary): Boolean = other match {
+ case UnboundedPreceding => false
+ case vp: ValuePreceding => false
+ case CurrentRow => false
+ case vf: ValueFollowing => false
+ case UnboundedFollowing => true
+ }
+
+ override def toString: String = "UNBOUNDED FOLLOWING"
+}
+
+/**
+ * The trait used to represent the a Window Frame.
+ */
+sealed trait WindowFrame
+
+/** Used as a place holder when a frame specification is not defined. */
+case object UnspecifiedFrame extends WindowFrame
+
+/** A specified Window Frame. */
+case class SpecifiedWindowFrame(
+ frameType: FrameType,
+ frameStart: FrameBoundary,
+ frameEnd: FrameBoundary) extends WindowFrame {
+
+ /** If this WindowFrame is valid or not. */
+ def validate: Option[String] = (frameType, frameStart, frameEnd) match {
+ case (_, UnboundedFollowing, _) =>
+ Some(s"$UnboundedFollowing is not allowed as the start of a Window Frame.")
+ case (_, _, UnboundedPreceding) =>
+ Some(s"$UnboundedPreceding is not allowed as the end of a Window Frame.")
+ // case (RowFrame, start, end) => ??? RowFrame specific rule
+ // case (RangeFrame, start, end) => ??? RangeFrame specific rule
+ case (_, start, end) =>
+ if (start.notFollows(end)) {
+ None
+ } else {
+ val reason =
+ s"The end of this Window Frame $end is smaller than the start of " +
+ s"this Window Frame $start."
+ Some(reason)
+ }
+ }
+
+ override def toString: String = frameType match {
+ case RowFrame => s"ROWS BETWEEN $frameStart AND $frameEnd"
+ case RangeFrame => s"RANGE BETWEEN $frameStart AND $frameEnd"
+ }
+}
+
+object SpecifiedWindowFrame {
+ /**
+ *
+ * @param hasOrderSpecification If the window spec has order by expressions.
+ * @param acceptWindowFrame If the window function accepts user-specified frame.
+ * @return
+ */
+ def defaultWindowFrame(
+ hasOrderSpecification: Boolean,
+ acceptWindowFrame: Boolean): SpecifiedWindowFrame = {
+ if (hasOrderSpecification && acceptWindowFrame) {
+ // If order spec is defined and the window function supports user specified window frames,
+ // the default frame is RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW.
+ SpecifiedWindowFrame(RangeFrame, UnboundedPreceding, CurrentRow)
+ } else {
+ // Otherwise, the default frame is
+ // ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING.
+ SpecifiedWindowFrame(RowFrame, UnboundedPreceding, UnboundedFollowing)
+ }
+ }
+}
+
+/**
+ * Every window function needs to maintain a output buffer for its output.
+ * It should expect that for a n-row window frame, it will be called n times
+ * to retrieve value corresponding with these n rows.
+ */
+trait WindowFunction extends Expression {
+ self: Product =>
+
+ def init(): Unit
+
+ def reset(): Unit
+
+ def prepareInputParameters(input: Row): AnyRef
+
+ def update(input: AnyRef): Unit
+
+ def batchUpdate(inputs: Array[AnyRef]): Unit
+
+ def evaluate(): Unit
+
+ def get(index: Int): Any
+
+ def newInstance(): WindowFunction
+}
+
+case class UnresolvedWindowFunction(
+ name: String,
+ children: Seq[Expression])
+ extends Expression with WindowFunction {
+
+ override def dataType: DataType = throw new UnresolvedException(this, "dataType")
+ override def foldable: Boolean = throw new UnresolvedException(this, "foldable")
+ override def nullable: Boolean = throw new UnresolvedException(this, "nullable")
+ override lazy val resolved = false
+
+ override def init(): Unit =
+ throw new UnresolvedException(this, "init")
+ override def reset(): Unit =
+ throw new UnresolvedException(this, "reset")
+ override def prepareInputParameters(input: Row): AnyRef =
+ throw new UnresolvedException(this, "prepareInputParameters")
+ override def update(input: AnyRef): Unit =
+ throw new UnresolvedException(this, "update")
+ override def batchUpdate(inputs: Array[AnyRef]): Unit =
+ throw new UnresolvedException(this, "batchUpdate")
+ override def evaluate(): Unit =
+ throw new UnresolvedException(this, "evaluate")
+ override def get(index: Int): Any =
+ throw new UnresolvedException(this, "get")
+ // Unresolved functions are transient at compile time and don't get evaluated during execution.
+ override def eval(input: Row = null): EvaluatedType =
+ throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}")
+
+ override def toString: String = s"'$name(${children.mkString(",")})"
+
+ override def newInstance(): WindowFunction =
+ throw new UnresolvedException(this, "newInstance")
+}
+
+case class UnresolvedWindowExpression(
+ child: UnresolvedWindowFunction,
+ windowSpec: WindowSpecReference) extends UnaryExpression {
+ override def dataType: DataType = throw new UnresolvedException(this, "dataType")
+ override def foldable: Boolean = throw new UnresolvedException(this, "foldable")
+ override def nullable: Boolean = throw new UnresolvedException(this, "nullable")
+ override lazy val resolved = false
+
+ // Unresolved functions are transient at compile time and don't get evaluated during execution.
+ override def eval(input: Row = null): EvaluatedType =
+ throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}")
+}
+
+case class WindowExpression(
+ windowFunction: WindowFunction,
+ windowSpec: WindowSpecDefinition) extends Expression {
+ override type EvaluatedType = Any
+
+ override def children: Seq[Expression] =
+ windowFunction :: windowSpec :: Nil
+
+ override def eval(input: Row): EvaluatedType =
+ throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}")
+
+ override def dataType: DataType = windowFunction.dataType
+ override def foldable: Boolean = windowFunction.foldable
+ override def nullable: Boolean = windowFunction.nullable
+
+ override def toString: String = s"$windowFunction $windowSpec"
+}
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
index 21208c8a5c281df31735bb095beb57ffacbf1209..ba0abb2df596c03d7ad8455a365965ebbd03ead3 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala
@@ -25,13 +25,14 @@ case class Project(projectList: Seq[NamedExpression], child: LogicalPlan) extend
override def output: Seq[Attribute] = projectList.map(_.toAttribute)
override lazy val resolved: Boolean = {
- val containsAggregatesOrGenerators = projectList.exists ( _.collect {
+ val hasSpecialExpressions = projectList.exists ( _.collect {
case agg: AggregateExpression => agg
case generator: Generator => generator
+ case window: WindowExpression => window
}.nonEmpty
)
- !expressions.exists(!_.resolved) && childrenResolved && !containsAggregatesOrGenerators
+ !expressions.exists(!_.resolved) && childrenResolved && !hasSpecialExpressions
}
}
@@ -170,6 +171,12 @@ case class With(child: LogicalPlan, cteRelations: Map[String, Subquery]) extends
override def output: Seq[Attribute] = child.output
}
+case class WithWindowDefinition(
+ windowDefinitions: Map[String, WindowSpecDefinition],
+ child: LogicalPlan) extends UnaryNode {
+ override def output: Seq[Attribute] = child.output
+}
+
case class WriteToFile(
path: String,
child: LogicalPlan) extends UnaryNode {
@@ -195,9 +202,28 @@ case class Aggregate(
child: LogicalPlan)
extends UnaryNode {
+ override lazy val resolved: Boolean = {
+ val hasWindowExpressions = aggregateExpressions.exists ( _.collect {
+ case window: WindowExpression => window
+ }.nonEmpty
+ )
+
+ !expressions.exists(!_.resolved) && childrenResolved && !hasWindowExpressions
+ }
+
override def output: Seq[Attribute] = aggregateExpressions.map(_.toAttribute)
}
+case class Window(
+ projectList: Seq[Attribute],
+ windowExpressions: Seq[NamedExpression],
+ windowSpec: WindowSpecDefinition,
+ child: LogicalPlan) extends UnaryNode {
+
+ override def output: Seq[Attribute] =
+ (projectList ++ windowExpressions).map(_.toAttribute)
+}
+
/**
* Apply the all of the GroupExpressions to every input row, hence we will get
* multiple output rows for a input row.
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala
index 97502ed3afe72af3c829a1ba1741e9b894b834c1..4b93f7d31b8089f9fa5643029f8985f6d0b0330c 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala
@@ -71,6 +71,15 @@ abstract class TreeNode[BaseType <: TreeNode[BaseType]] {
this.eq(other) || this == other
}
+ /**
+ * Find the first [[TreeNode]] that satisfies the condition specified by `f`.
+ * The condition is recursively applied to this node and all of its children (pre-order).
+ */
+ def find(f: BaseType => Boolean): Option[BaseType] = f(this) match {
+ case true => Some(this)
+ case false => children.foldLeft(None: Option[BaseType]) { (l, r) => l.orElse(r.find(f)) }
+ }
+
/**
* Runs the given function on this node and then recursively on [[children]].
* @param f the function to be applied to each node in the tree.
@@ -151,6 +160,20 @@ abstract class TreeNode[BaseType <: TreeNode[BaseType]] {
val remainingNewChildren = newChildren.toBuffer
val remainingOldChildren = children.toBuffer
val newArgs = productIterator.map {
+ // This rule is used to handle children is a input argument.
+ case s: Seq[_] => s.map {
+ case arg: TreeNode[_] if children contains arg =>
+ val newChild = remainingNewChildren.remove(0)
+ val oldChild = remainingOldChildren.remove(0)
+ if (newChild fastEquals oldChild) {
+ oldChild
+ } else {
+ changed = true
+ newChild
+ }
+ case nonChild: AnyRef => nonChild
+ case null => null
+ }
case arg: TreeNode[_] if children contains arg =>
val newChild = remainingNewChildren.remove(0)
val oldChild = remainingOldChildren.remove(0)
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala
index 6b393327cc97afc70588491b766225eb395c9b87..786ddba403f2c28e33ed634421d88dce69784313 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala
@@ -22,7 +22,7 @@ import scala.collection.mutable.ArrayBuffer
import org.scalatest.FunSuite
import org.apache.spark.sql.catalyst.expressions._
-import org.apache.spark.sql.types.{StringType, NullType}
+import org.apache.spark.sql.types.{IntegerType, StringType, NullType}
case class Dummy(optKey: Option[Expression]) extends Expression {
def children: Seq[Expression] = optKey.toSeq
@@ -129,5 +129,47 @@ class TreeNodeSuite extends FunSuite {
assert(expected === actual)
}
+ test("find") {
+ val expression = Add(Literal(1), Multiply(Literal(2), Subtract(Literal(3), Literal(4))))
+ // Find the top node.
+ var actual: Option[Expression] = expression.find {
+ case add: Add => true
+ case other => false
+ }
+ var expected: Option[Expression] =
+ Some(Add(Literal(1), Multiply(Literal(2), Subtract(Literal(3), Literal(4)))))
+ assert(expected === actual)
+
+ // Find the first children.
+ actual = expression.find {
+ case Literal(1, IntegerType) => true
+ case other => false
+ }
+ expected = Some(Literal(1))
+ assert(expected === actual)
+ // Find an internal node (Subtract).
+ actual = expression.find {
+ case sub: Subtract => true
+ case other => false
+ }
+ expected = Some(Subtract(Literal(3), Literal(4)))
+ assert(expected === actual)
+
+ // Find a leaf node.
+ actual = expression.find {
+ case Literal(3, IntegerType) => true
+ case other => false
+ }
+ expected = Some(Literal(3))
+ assert(expected === actual)
+
+ // Find nothing.
+ actual = expression.find {
+ case Literal(100, IntegerType) => true
+ case other => false
+ }
+ expected = None
+ assert(expected === actual)
+ }
}
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
index 326e8ce4ca524e47e76e6960842f83b7eb8756cc..56a4689eb58f0210a62a754ccd4e11599d8ae99b 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
@@ -303,6 +303,8 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
execution.Expand(projections, output, planLater(child)) :: Nil
case logical.Aggregate(group, agg, child) =>
execution.Aggregate(partial = false, group, agg, planLater(child)) :: Nil
+ case logical.Window(projectList, windowExpressions, spec, child) =>
+ execution.Window(projectList, windowExpressions, spec, planLater(child)) :: Nil
case logical.Sample(lb, ub, withReplacement, seed, child) =>
execution.Sample(lb, ub, withReplacement, seed, planLater(child)) :: Nil
case logical.LocalRelation(output, data) =>
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala
new file mode 100644
index 0000000000000000000000000000000000000000..217b559def5124aec1c2e3e03a68142af1db11f4
--- /dev/null
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala
@@ -0,0 +1,480 @@
+/*
+ * 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.
+ */
+
+package org.apache.spark.sql.execution
+
+import java.util
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.Row
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans.physical.{AllTuples, Distribution, ClusteredDistribution, Partitioning}
+import org.apache.spark.util.collection.CompactBuffer
+
+/**
+ * :: DeveloperApi ::
+ * For every row, evaluates `windowExpression` containing Window Functions and attaches
+ * the results with other regular expressions (presented by `projectList`).
+ * Evert operator handles a single Window Specification, `windowSpec`.
+ */
+case class Window(
+ projectList: Seq[Attribute],
+ windowExpression: Seq[NamedExpression],
+ windowSpec: WindowSpecDefinition,
+ child: SparkPlan)
+ extends UnaryNode {
+
+ override def output: Seq[Attribute] =
+ (projectList ++ windowExpression).map(_.toAttribute)
+
+ override def requiredChildDistribution: Seq[Distribution] =
+ if (windowSpec.partitionSpec.isEmpty) {
+ // This operator will be very expensive.
+ AllTuples :: Nil
+ } else {
+ ClusteredDistribution(windowSpec.partitionSpec) :: Nil
+ }
+
+ // Since window functions are adding columns to the input rows, the child's outputPartitioning
+ // is preserved.
+ override def outputPartitioning: Partitioning = child.outputPartitioning
+
+ override def requiredChildOrdering: Seq[Seq[SortOrder]] = {
+ // The required child ordering has two parts.
+ // The first part is the expressions in the partition specification.
+ // We add these expressions to the required ordering to make sure input rows are grouped
+ // based on the partition specification. So, we only need to process a single partition
+ // at a time.
+ // The second part is the expressions specified in the ORDER BY cluase.
+ // Basically, we first use sort to group rows based on partition specifications and then sort
+ // Rows in a group based on the order specification.
+ (windowSpec.partitionSpec.map(SortOrder(_, Ascending)) ++ windowSpec.orderSpec) :: Nil
+ }
+
+ // Since window functions basically add columns to input rows, this operator
+ // will not change the ordering of input rows.
+ override def outputOrdering: Seq[SortOrder] = child.outputOrdering
+
+ case class ComputedWindow(
+ unbound: WindowExpression,
+ windowFunction: WindowFunction,
+ resultAttribute: AttributeReference)
+
+ // A list of window functions that need to be computed for each group.
+ private[this] val computedWindowExpressions = windowExpression.flatMap { window =>
+ window.collect {
+ case w: WindowExpression =>
+ ComputedWindow(
+ w,
+ BindReferences.bindReference(w.windowFunction, child.output),
+ AttributeReference(s"windowResult:$w", w.dataType, w.nullable)())
+ }
+ }.toArray
+
+ private[this] val windowFrame =
+ windowSpec.frameSpecification.asInstanceOf[SpecifiedWindowFrame]
+
+ // Create window functions.
+ private[this] def windowFunctions(): Array[WindowFunction] = {
+ val functions = new Array[WindowFunction](computedWindowExpressions.length)
+ var i = 0
+ while (i < computedWindowExpressions.length) {
+ functions(i) = computedWindowExpressions(i).windowFunction.newInstance()
+ functions(i).init()
+ i += 1
+ }
+ functions
+ }
+
+ // The schema of the result of all window function evaluations
+ private[this] val computedSchema = computedWindowExpressions.map(_.resultAttribute)
+
+ private[this] val computedResultMap =
+ computedWindowExpressions.map { w => w.unbound -> w.resultAttribute }.toMap
+
+ private[this] val windowExpressionResult = windowExpression.map { window =>
+ window.transform {
+ case w: WindowExpression if computedResultMap.contains(w) => computedResultMap(w)
+ }
+ }
+
+ def execute(): RDD[Row] = {
+ child.execute().mapPartitions { iter =>
+ new Iterator[Row] {
+
+ // Although input rows are grouped based on windowSpec.partitionSpec, we need to
+ // know when we have a new partition.
+ // This is to manually construct an ordering that can be used to compare rows.
+ // TODO: We may want to have a newOrdering that takes BoundReferences.
+ // So, we can take advantave of code gen.
+ private val partitionOrdering: Ordering[Row] =
+ RowOrdering.forSchema(windowSpec.partitionSpec.map(_.dataType))
+
+ // This is used to project expressions for the partition specification.
+ protected val partitionGenerator =
+ newMutableProjection(windowSpec.partitionSpec, child.output)()
+
+ // This is ued to project expressions for the order specification.
+ protected val rowOrderGenerator =
+ newMutableProjection(windowSpec.orderSpec.map(_.child), child.output)()
+
+ // The position of next output row in the inputRowBuffer.
+ var rowPosition: Int = 0
+ // The number of buffered rows in the inputRowBuffer (the size of the current partition).
+ var partitionSize: Int = 0
+ // The buffer used to buffer rows in a partition.
+ var inputRowBuffer: CompactBuffer[Row] = _
+ // The partition key of the current partition.
+ var currentPartitionKey: Row = _
+ // The partition key of next partition.
+ var nextPartitionKey: Row = _
+ // The first row of next partition.
+ var firstRowInNextPartition: Row = _
+ // Indicates if this partition is the last one in the iter.
+ var lastPartition: Boolean = false
+
+ def createBoundaryEvaluator(): () => Unit = {
+ def findPhysicalBoundary(
+ boundary: FrameBoundary): () => Int = boundary match {
+ case UnboundedPreceding => () => 0
+ case UnboundedFollowing => () => partitionSize - 1
+ case CurrentRow => () => rowPosition
+ case ValuePreceding(value) =>
+ () =>
+ val newPosition = rowPosition - value
+ if (newPosition > 0) newPosition else 0
+ case ValueFollowing(value) =>
+ () =>
+ val newPosition = rowPosition + value
+ if (newPosition < partitionSize) newPosition else partitionSize - 1
+ }
+
+ def findLogicalBoundary(
+ boundary: FrameBoundary,
+ searchDirection: Int,
+ evaluator: Expression,
+ joinedRow: JoinedRow): () => Int = boundary match {
+ case UnboundedPreceding => () => 0
+ case UnboundedFollowing => () => partitionSize - 1
+ case other =>
+ () => {
+ // CurrentRow, ValuePreceding, or ValueFollowing.
+ var newPosition = rowPosition + searchDirection
+ var stopSearch = false
+ // rowOrderGenerator is a mutable projection.
+ // We need to make a copy of the returned by rowOrderGenerator since we will
+ // compare searched row with this currentOrderByValue.
+ val currentOrderByValue = rowOrderGenerator(inputRowBuffer(rowPosition)).copy()
+ while (newPosition >= 0 && newPosition < partitionSize && !stopSearch) {
+ val r = rowOrderGenerator(inputRowBuffer(newPosition))
+ stopSearch =
+ !(evaluator.eval(joinedRow(currentOrderByValue, r)).asInstanceOf[Boolean])
+ if (!stopSearch) {
+ newPosition += searchDirection
+ }
+ }
+ newPosition -= searchDirection
+
+ if (newPosition < 0) {
+ 0
+ } else if (newPosition >= partitionSize) {
+ partitionSize - 1
+ } else {
+ newPosition
+ }
+ }
+ }
+
+ windowFrame.frameType match {
+ case RowFrame =>
+ val findStart = findPhysicalBoundary(windowFrame.frameStart)
+ val findEnd = findPhysicalBoundary(windowFrame.frameEnd)
+ () => {
+ frameStart = findStart()
+ frameEnd = findEnd()
+ }
+ case RangeFrame =>
+ val joinedRowForBoundaryEvaluation: JoinedRow = new JoinedRow()
+ val orderByExpr = windowSpec.orderSpec.head
+ val currentRowExpr =
+ BoundReference(0, orderByExpr.dataType, orderByExpr.nullable)
+ val examedRowExpr =
+ BoundReference(1, orderByExpr.dataType, orderByExpr.nullable)
+ val differenceExpr = Abs(Subtract(currentRowExpr, examedRowExpr))
+
+ val frameStartEvaluator = windowFrame.frameStart match {
+ case CurrentRow => EqualTo(currentRowExpr, examedRowExpr)
+ case ValuePreceding(value) =>
+ LessThanOrEqual(differenceExpr, Cast(Literal(value), orderByExpr.dataType))
+ case ValueFollowing(value) =>
+ GreaterThanOrEqual(differenceExpr, Cast(Literal(value), orderByExpr.dataType))
+ case o => Literal(true) // This is just a dummy expression, we will not use it.
+ }
+
+ val frameEndEvaluator = windowFrame.frameEnd match {
+ case CurrentRow => EqualTo(currentRowExpr, examedRowExpr)
+ case ValuePreceding(value) =>
+ GreaterThanOrEqual(differenceExpr, Cast(Literal(value), orderByExpr.dataType))
+ case ValueFollowing(value) =>
+ LessThanOrEqual(differenceExpr, Cast(Literal(value), orderByExpr.dataType))
+ case o => Literal(true) // This is just a dummy expression, we will not use it.
+ }
+
+ val findStart =
+ findLogicalBoundary(
+ boundary = windowFrame.frameStart,
+ searchDirection = -1,
+ evaluator = frameStartEvaluator,
+ joinedRow = joinedRowForBoundaryEvaluation)
+ val findEnd =
+ findLogicalBoundary(
+ boundary = windowFrame.frameEnd,
+ searchDirection = 1,
+ evaluator = frameEndEvaluator,
+ joinedRow = joinedRowForBoundaryEvaluation)
+ () => {
+ frameStart = findStart()
+ frameEnd = findEnd()
+ }
+ }
+ }
+
+ val boundaryEvaluator = createBoundaryEvaluator()
+ // Indicates if we the specified window frame requires us to maintain a sliding frame
+ // (e.g. RANGES BETWEEN 1 PRECEDING AND CURRENT ROW) or the window frame
+ // is the entire partition (e.g. ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING).
+ val requireUpdateFrame: Boolean = {
+ def requireUpdateBoundary(boundary: FrameBoundary): Boolean = boundary match {
+ case UnboundedPreceding => false
+ case UnboundedFollowing => false
+ case _ => true
+ }
+
+ requireUpdateBoundary(windowFrame.frameStart) ||
+ requireUpdateBoundary(windowFrame.frameEnd)
+ }
+ // The start position of the current frame in the partition.
+ var frameStart: Int = 0
+ // The end position of the current frame in the partition.
+ var frameEnd: Int = -1
+ // Window functions.
+ val functions: Array[WindowFunction] = windowFunctions()
+ // Buffers used to store input parameters for window functions. Because we may need to
+ // maintain a sliding frame, we use this buffer to avoid evaluate the parameters from
+ // the same row multiple times.
+ val windowFunctionParameterBuffers: Array[util.LinkedList[AnyRef]] =
+ functions.map(_ => new util.LinkedList[AnyRef]())
+
+ // The projection used to generate the final result rows of this operator.
+ private[this] val resultProjection =
+ newMutableProjection(
+ projectList ++ windowExpressionResult,
+ projectList ++ computedSchema)()
+
+ // The row used to hold results of window functions.
+ private[this] val windowExpressionResultRow =
+ new GenericMutableRow(computedSchema.length)
+
+ private[this] val joinedRow = new JoinedRow6
+
+ // Initialize this iterator.
+ initialize()
+
+ private def initialize(): Unit = {
+ if (iter.hasNext) {
+ val currentRow = iter.next().copy()
+ // partitionGenerator is a mutable projection. Since we need to track nextPartitionKey,
+ // we are making a copy of the returned partitionKey at here.
+ nextPartitionKey = partitionGenerator(currentRow).copy()
+ firstRowInNextPartition = currentRow
+ fetchNextPartition()
+ } else {
+ // The iter is an empty one. So, we set all of the following variables
+ // to make sure hasNext will return false.
+ lastPartition = true
+ rowPosition = 0
+ partitionSize = 0
+ }
+ }
+
+ // Indicates if we will have new output row.
+ override final def hasNext: Boolean = {
+ !lastPartition || (rowPosition < partitionSize)
+ }
+
+ override final def next(): Row = {
+ if (hasNext) {
+ if (rowPosition == partitionSize) {
+ // All rows of this buffer have been consumed.
+ // We will move to next partition.
+ fetchNextPartition()
+ }
+ // Get the input row for the current output row.
+ val inputRow = inputRowBuffer(rowPosition)
+ // Get all results of the window functions for this output row.
+ var i = 0
+ while (i < functions.length) {
+ windowExpressionResultRow.update(i, functions(i).get(rowPosition))
+ i += 1
+ }
+
+ // Construct the output row.
+ val outputRow = resultProjection(joinedRow(inputRow, windowExpressionResultRow))
+ // We will move to the next one.
+ rowPosition += 1
+ if (requireUpdateFrame && rowPosition < partitionSize) {
+ // If we need to maintain a sliding frame and
+ // we will still work on this partition when next is called next time, do the update.
+ updateFrame()
+ }
+
+ // Return the output row.
+ outputRow
+ } else {
+ // no more result
+ throw new NoSuchElementException
+ }
+ }
+
+ // Fetch the next partition.
+ private def fetchNextPartition(): Unit = {
+ // Create a new buffer for input rows.
+ inputRowBuffer = new CompactBuffer[Row]()
+ // We already have the first row for this partition
+ // (recorded in firstRowInNextPartition). Add it back.
+ inputRowBuffer += firstRowInNextPartition
+ // Set the current partition key.
+ currentPartitionKey = nextPartitionKey
+ // Now, we will start to find all rows belonging to this partition.
+ // Create a variable to track if we see the next partition.
+ var findNextPartition = false
+ // The search will stop when we see the next partition or there is no
+ // input row left in the iter.
+ while (iter.hasNext && !findNextPartition) {
+ // Make a copy of the input row since we will put it in the buffer.
+ val currentRow = iter.next().copy()
+ // Get the partition key based on the partition specification.
+ // For the below compare method, we do not need to make a copy of partitionKey.
+ val partitionKey = partitionGenerator(currentRow)
+ // Check if the current row belongs the current input row.
+ val comparing = partitionOrdering.compare(currentPartitionKey, partitionKey)
+ if (comparing == 0) {
+ // This row is still in the current partition.
+ inputRowBuffer += currentRow
+ } else {
+ // The current input row is in a different partition.
+ findNextPartition = true
+ // partitionGenerator is a mutable projection.
+ // Since we need to track nextPartitionKey and we determine that it should be set
+ // as partitionKey, we are making a copy of the partitionKey at here.
+ nextPartitionKey = partitionKey.copy()
+ firstRowInNextPartition = currentRow
+ }
+ }
+
+ // We have not seen a new partition. It means that there is no new row in the
+ // iter. The current partition is the last partition of the iter.
+ if (!findNextPartition) {
+ lastPartition = true
+ }
+
+ // We have got all rows for the current partition.
+ // Set rowPosition to 0 (the next output row will be based on the first
+ // input row of this partition).
+ rowPosition = 0
+ // The size of this partition.
+ partitionSize = inputRowBuffer.size
+ // Reset all parameter buffers of window functions.
+ var i = 0
+ while (i < windowFunctionParameterBuffers.length) {
+ windowFunctionParameterBuffers(i).clear()
+ i += 1
+ }
+ frameStart = 0
+ frameEnd = -1
+ // Create the first window frame for this partition.
+ // If we do not need to maintain a sliding frame, this frame will
+ // have the entire partition.
+ updateFrame()
+ }
+
+ /** The function used to maintain the sliding frame. */
+ private def updateFrame(): Unit = {
+ // Based on the difference between the new frame and old frame,
+ // updates the buffers holding input parameters of window functions.
+ // We will start to prepare input parameters starting from the row
+ // indicated by offset in the input row buffer.
+ def updateWindowFunctionParameterBuffers(
+ numToRemove: Int,
+ numToAdd: Int,
+ offset: Int): Unit = {
+ // First, remove unneeded entries from the head of every buffer.
+ var i = 0
+ while (i < numToRemove) {
+ var j = 0
+ while (j < windowFunctionParameterBuffers.length) {
+ windowFunctionParameterBuffers(j).remove()
+ j += 1
+ }
+ i += 1
+ }
+ // Then, add needed entries to the tail of every buffer.
+ i = 0
+ while (i < numToAdd) {
+ var j = 0
+ while (j < windowFunctionParameterBuffers.length) {
+ // Ask the function to prepare the input parameters.
+ val parameters = functions(j).prepareInputParameters(inputRowBuffer(i + offset))
+ windowFunctionParameterBuffers(j).add(parameters)
+ j += 1
+ }
+ i += 1
+ }
+ }
+
+ // Record the current frame start point and end point before
+ // we update them.
+ val previousFrameStart = frameStart
+ val previousFrameEnd = frameEnd
+ boundaryEvaluator()
+ updateWindowFunctionParameterBuffers(
+ frameStart - previousFrameStart,
+ frameEnd - previousFrameEnd,
+ previousFrameEnd + 1)
+ // Evaluate the current frame.
+ evaluateCurrentFrame()
+ }
+
+ /** Evaluate the current window frame. */
+ private def evaluateCurrentFrame(): Unit = {
+ var i = 0
+ while (i < functions.length) {
+ // Reset the state of the window function.
+ functions(i).reset()
+ // Get all buffered input parameters based on rows of this window frame.
+ val inputParameters = windowFunctionParameterBuffers(i).toArray()
+ // Send these input parameters to the window function.
+ functions(i).batchUpdate(inputParameters)
+ // Ask the function to evaluate based on this window frame.
+ functions(i).evaluate()
+ i += 1
+ }
+ }
+ }
+ }
+ }
+}
diff --git a/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala b/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala
index 81ee48ef4152f65be63e74fe332ffdff18b33a59..5e411c2fdba9df21d89db2c24dca026430928622 100644
--- a/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala
+++ b/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala
@@ -185,7 +185,7 @@ class HiveCompatibilitySuite extends HiveQueryFileTest with BeforeAndAfter {
// Hive does not support buckets.
".*bucket.*",
- // No window support yet
+ // We have our own tests based on these query files.
".*window.*",
// Fails in hive with authorization errors.
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala
index 1d8d0b5c322ad50ffd831e1ede49ef6edb66e304..f25723e53f07c3aabce36ef4b8c16c2dfac9842d 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala
@@ -252,6 +252,7 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) {
catalog.CreateTables ::
catalog.PreInsertionCasts ::
ExtractPythonUdfs ::
+ ResolveHiveWindowFunction ::
sources.PreInsertCastAndRename ::
Nil
}
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
index 63a8c05f775b8790805e159c9a107be90acaecf4..8a0686a2d81c9c81a358b7f2b6a2a33c1c0cd584 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala
@@ -421,16 +421,16 @@ private[hive] object HiveQl {
}
/**
- * SELECT MAX(value) FROM src GROUP BY k1, k2, k3 GROUPING SETS((k1, k2), (k2))
- * is equivalent to
+ * SELECT MAX(value) FROM src GROUP BY k1, k2, k3 GROUPING SETS((k1, k2), (k2))
+ * is equivalent to
* SELECT MAX(value) FROM src GROUP BY k1, k2 UNION SELECT MAX(value) FROM src GROUP BY k2
* Check the following link for details.
- *
+ *
https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C+Grouping+and+Rollup
*
* The bitmask denotes the grouping expressions validity for a grouping set,
* the bitmask also be called as grouping id (`GROUPING__ID`, the virtual column in Hive)
- * e.g. In superset (k1, k2, k3), (bit 0: k1, bit 1: k2, and bit 2: k3), the grouping id of
+ * e.g. In superset (k1, k2, k3), (bit 0: k1, bit 1: k2, and bit 2: k3), the grouping id of
* GROUPING SETS (k1, k2) and (k2) should be 3 and 2 respectively.
*/
protected def extractGroupingSet(children: Seq[ASTNode]): (Seq[Expression], Seq[Int]) = {
@@ -444,7 +444,7 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
val bitmasks: Seq[Int] = setASTs.map(set => set match {
case Token("TOK_GROUPING_SETS_EXPRESSION", null) => 0
- case Token("TOK_GROUPING_SETS_EXPRESSION", children) =>
+ case Token("TOK_GROUPING_SETS_EXPRESSION", children) =>
children.foldLeft(0)((bitmap, col) => {
val colString = col.asInstanceOf[ASTNode].toStringTree()
require(keyMap.contains(colString), s"$colString doens't show up in the GROUP BY list")
@@ -613,7 +613,8 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
clusterByClause ::
distributeByClause ::
limitClause ::
- lateralViewClause :: Nil) = {
+ lateralViewClause ::
+ windowClause :: Nil) = {
getClauses(
Seq(
"TOK_INSERT_INTO",
@@ -631,15 +632,16 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
"TOK_CLUSTERBY",
"TOK_DISTRIBUTEBY",
"TOK_LIMIT",
- "TOK_LATERAL_VIEW"),
+ "TOK_LATERAL_VIEW",
+ "WINDOW"),
singleInsert)
}
-
+
val relations = fromClause match {
case Some(f) => nodeToRelation(f)
case None => OneRowRelation
}
-
+
val withWhere = whereClause.map { whereNode =>
val Seq(whereExpr) = whereNode.getChildren.toSeq
Filter(nodeToExpr(whereExpr), relations)
@@ -691,7 +693,7 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
val serdeProps = propsClause.map {
case Token("TOK_TABLEPROPERTY", Token(name, Nil) :: Token(value, Nil) :: Nil) =>
(name, value)
- }
+ }
(Nil, serdeClass, serdeProps)
case Nil => (Nil, "", Nil)
@@ -736,7 +738,7 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
// The projection of the query can either be a normal projection, an aggregation
// (if there is a group by) or a script transformation.
val withProject: LogicalPlan = transformation.getOrElse {
- val selectExpressions =
+ val selectExpressions =
nameExpressions(select.getChildren.flatMap(selExprNodeToExpr).toSeq)
Seq(
groupByClause.map(e => e match {
@@ -764,31 +766,34 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
Some(Project(selectExpressions, withLateralView))).flatten.head
}
- val withDistinct =
- if (selectDistinctClause.isDefined) Distinct(withProject) else withProject
-
+ // Handle HAVING clause.
val withHaving = havingClause.map { h =>
val havingExpr = h.getChildren.toSeq match { case Seq(hexpr) => nodeToExpr(hexpr) }
// Note that we added a cast to boolean. If the expression itself is already boolean,
// the optimizer will get rid of the unnecessary cast.
- Filter(Cast(havingExpr, BooleanType), withDistinct)
- }.getOrElse(withDistinct)
+ Filter(Cast(havingExpr, BooleanType), withProject)
+ }.getOrElse(withProject)
+
+ // Handle SELECT DISTINCT
+ val withDistinct =
+ if (selectDistinctClause.isDefined) Distinct(withHaving) else withHaving
+ // Handle ORDER BY, SORT BY, DISTRIBETU BY, and CLUSTER BY clause.
val withSort =
(orderByClause, sortByClause, distributeByClause, clusterByClause) match {
case (Some(totalOrdering), None, None, None) =>
- Sort(totalOrdering.getChildren.map(nodeToSortOrder), true, withHaving)
+ Sort(totalOrdering.getChildren.map(nodeToSortOrder), true, withDistinct)
case (None, Some(perPartitionOrdering), None, None) =>
- Sort(perPartitionOrdering.getChildren.map(nodeToSortOrder), false, withHaving)
+ Sort(perPartitionOrdering.getChildren.map(nodeToSortOrder), false, withDistinct)
case (None, None, Some(partitionExprs), None) =>
- RepartitionByExpression(partitionExprs.getChildren.map(nodeToExpr), withHaving)
+ RepartitionByExpression(partitionExprs.getChildren.map(nodeToExpr), withDistinct)
case (None, Some(perPartitionOrdering), Some(partitionExprs), None) =>
Sort(perPartitionOrdering.getChildren.map(nodeToSortOrder), false,
- RepartitionByExpression(partitionExprs.getChildren.map(nodeToExpr), withHaving))
+ RepartitionByExpression(partitionExprs.getChildren.map(nodeToExpr), withDistinct))
case (None, None, None, Some(clusterExprs)) =>
Sort(clusterExprs.getChildren.map(nodeToExpr).map(SortOrder(_, Ascending)), false,
- RepartitionByExpression(clusterExprs.getChildren.map(nodeToExpr), withHaving))
- case (None, None, None, None) => withHaving
+ RepartitionByExpression(clusterExprs.getChildren.map(nodeToExpr), withDistinct))
+ case (None, None, None, None) => withDistinct
case _ => sys.error("Unsupported set of ordering / distribution clauses.")
}
@@ -797,6 +802,27 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
.map(Limit(_, withSort))
.getOrElse(withSort)
+ // Collect all window specifications defined in the WINDOW clause.
+ val windowDefinitions = windowClause.map(_.getChildren.toSeq.collect {
+ case Token("TOK_WINDOWDEF",
+ Token(windowName, Nil) :: Token("TOK_WINDOWSPEC", spec) :: Nil) =>
+ windowName -> nodesToWindowSpecification(spec)
+ }.toMap)
+ // Handle cases like
+ // window w1 as (partition by p_mfgr order by p_name
+ // range between 2 preceding and 2 following),
+ // w2 as w1
+ val resolvedCrossReference = windowDefinitions.map {
+ windowDefMap => windowDefMap.map {
+ case (windowName, WindowSpecReference(other)) =>
+ (windowName, windowDefMap(other).asInstanceOf[WindowSpecDefinition])
+ case o => o.asInstanceOf[(String, WindowSpecDefinition)]
+ }
+ }
+
+ val withWindowDefinitions =
+ resolvedCrossReference.map(WithWindowDefinition(_, withLimit)).getOrElse(withLimit)
+
// TOK_INSERT_INTO means to add files to the table.
// TOK_DESTINATION means to overwrite the table.
val resultDestination =
@@ -804,7 +830,7 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
val overwrite = intoClause.isEmpty
nodeToDest(
resultDestination,
- withLimit,
+ withWindowDefinitions,
overwrite)
}
@@ -1053,7 +1079,6 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
throw new NotImplementedError(s"No parse rules for:\n ${dumpTree(a).toString} ")
}
-
protected val escapedIdentifier = "`([^`]+)`".r
/** Strips backticks from ident if present */
protected def cleanIdentifier(ident: String): String = ident match {
@@ -1250,6 +1275,25 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
Substring(nodeToExpr(string), nodeToExpr(pos), nodeToExpr(length))
case Token("TOK_FUNCTION", Token(COALESCE(), Nil) :: list) => Coalesce(list.map(nodeToExpr))
+ /* Window Functions */
+ case Token("TOK_FUNCTION", Token(name, Nil) +: args :+ Token("TOK_WINDOWSPEC", spec)) =>
+ val function = UnresolvedWindowFunction(name, args.map(nodeToExpr))
+ nodesToWindowSpecification(spec) match {
+ case reference: WindowSpecReference =>
+ UnresolvedWindowExpression(function, reference)
+ case definition: WindowSpecDefinition =>
+ WindowExpression(function, definition)
+ }
+ case Token("TOK_FUNCTIONSTAR", Token(name, Nil) :: Token("TOK_WINDOWSPEC", spec) :: Nil) =>
+ // Safe to use Literal(1)?
+ val function = UnresolvedWindowFunction(name, Literal(1) :: Nil)
+ nodesToWindowSpecification(spec) match {
+ case reference: WindowSpecReference =>
+ UnresolvedWindowExpression(function, reference)
+ case definition: WindowSpecDefinition =>
+ WindowExpression(function, definition)
+ }
+
/* UDFs - Must be last otherwise will preempt built in functions */
case Token("TOK_FUNCTION", Token(name, Nil) :: args) =>
UnresolvedFunction(name, args.map(nodeToExpr))
@@ -1312,6 +1356,89 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C
""".stripMargin)
}
+ def nodesToWindowSpecification(nodes: Seq[ASTNode]): WindowSpec = nodes match {
+ case Token(windowName, Nil) :: Nil =>
+ // Refer to a window spec defined in the window clause.
+ WindowSpecReference(windowName)
+ case Nil =>
+ // OVER()
+ WindowSpecDefinition(
+ partitionSpec = Nil,
+ orderSpec = Nil,
+ frameSpecification = UnspecifiedFrame)
+ case spec =>
+ val (partitionClause :: rowFrame :: rangeFrame :: Nil) =
+ getClauses(
+ Seq(
+ "TOK_PARTITIONINGSPEC",
+ "TOK_WINDOWRANGE",
+ "TOK_WINDOWVALUES"),
+ spec)
+
+ // Handle Partition By and Order By.
+ val (partitionSpec, orderSpec) = partitionClause.map { partitionAndOrdering =>
+ val (partitionByClause :: orderByClause :: sortByClause :: clusterByClause :: Nil) =
+ getClauses(
+ Seq("TOK_DISTRIBUTEBY", "TOK_ORDERBY", "TOK_SORTBY", "TOK_CLUSTERBY"),
+ partitionAndOrdering.getChildren.toSeq.asInstanceOf[Seq[ASTNode]])
+
+ (partitionByClause, orderByClause.orElse(sortByClause), clusterByClause) match {
+ case (Some(partitionByExpr), Some(orderByExpr), None) =>
+ (partitionByExpr.getChildren.map(nodeToExpr),
+ orderByExpr.getChildren.map(nodeToSortOrder))
+ case (Some(partitionByExpr), None, None) =>
+ (partitionByExpr.getChildren.map(nodeToExpr), Nil)
+ case (None, Some(orderByExpr), None) =>
+ (Nil, orderByExpr.getChildren.map(nodeToSortOrder))
+ case (None, None, Some(clusterByExpr)) =>
+ val expressions = clusterByExpr.getChildren.map(nodeToExpr)
+ (expressions, expressions.map(SortOrder(_, Ascending)))
+ case _ =>
+ throw new NotImplementedError(
+ s"""No parse rules for Node ${partitionAndOrdering.getName}
+ """.stripMargin)
+ }
+ }.getOrElse {
+ (Nil, Nil)
+ }
+
+ // Handle Window Frame
+ val windowFrame =
+ if (rowFrame.isEmpty && rangeFrame.isEmpty) {
+ UnspecifiedFrame
+ } else {
+ val frameType = rowFrame.map(_ => RowFrame).getOrElse(RangeFrame)
+ def nodeToBoundary(node: Node): FrameBoundary = node match {
+ case Token("preceding", Token(count, Nil) :: Nil) =>
+ if (count == "unbounded") UnboundedPreceding else ValuePreceding(count.toInt)
+ case Token("following", Token(count, Nil) :: Nil) =>
+ if (count == "unbounded") UnboundedFollowing else ValueFollowing(count.toInt)
+ case Token("current", Nil) => CurrentRow
+ case _ =>
+ throw new NotImplementedError(
+ s"""No parse rules for the Window Frame Boundary based on Node ${node.getName}
+ """.stripMargin)
+ }
+
+ rowFrame.orElse(rangeFrame).map { frame =>
+ frame.getChildren.toList match {
+ case precedingNode :: followingNode :: Nil =>
+ SpecifiedWindowFrame(
+ frameType,
+ nodeToBoundary(precedingNode),
+ nodeToBoundary(followingNode))
+ case precedingNode :: Nil =>
+ SpecifiedWindowFrame(frameType, nodeToBoundary(precedingNode), CurrentRow)
+ case _ =>
+ throw new NotImplementedError(
+ s"""No parse rules for the Window Frame based on Node ${frame.getName}
+ """.stripMargin)
+ }
+ }.getOrElse(sys.error(s"If you see this, please file a bug report with your query."))
+ }
+
+ WindowSpecDefinition(partitionSpec, orderSpec, windowFrame)
+ }
val explode = "(?i)explode".r
def nodesToGenerator(nodes: Seq[Node]): (Generator, Seq[String]) = {
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 4b6f0ad75f54f9a8e5597f40a173d250cd938ad5..fd0b6f058595dca5bbe7c9c318652e43a1aaef74 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
@@ -17,27 +17,27 @@
package org.apache.spark.sql.hive
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator.AggregationBuffer
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils.ConversionHelper
+import org.apache.spark.sql.AnalysisException
import scala.collection.mutable.ArrayBuffer
import org.apache.hadoop.hive.serde2.objectinspector.{ObjectInspector, ConstantObjectInspector}
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory.ObjectInspectorOptions
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory
-import org.apache.hadoop.hive.ql.exec.{UDF, UDAF}
-import org.apache.hadoop.hive.ql.exec.{FunctionInfo, FunctionRegistry}
+import org.apache.hadoop.hive.ql.exec._
import org.apache.hadoop.hive.ql.udf.{UDFType => HiveUDFType}
import org.apache.hadoop.hive.ql.udf.generic._
import org.apache.hadoop.hive.ql.udf.generic.GenericUDF._
import org.apache.spark.Logging
import org.apache.spark.sql.catalyst.analysis
+import org.apache.spark.sql.catalyst.errors.TreeNodeException
import org.apache.spark.sql.catalyst.expressions._
-import org.apache.spark.sql.catalyst.plans.logical.{Generate, Project, LogicalPlan}
+import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.types._
-import org.apache.spark.sql.catalyst.analysis.MultiAlias
-import org.apache.spark.sql.catalyst.errors.TreeNodeException
/* Implicit conversions */
import scala.collection.JavaConversions._
@@ -189,6 +189,219 @@ private[hive] case class HiveGenericUdf(funcWrapper: HiveFunctionWrapper, childr
}
}
+/**
+ * Resolves [[UnresolvedWindowFunction]] to [[HiveWindowFunction]].
+ */
+private[spark] object ResolveHiveWindowFunction extends Rule[LogicalPlan] {
+ def apply(plan: LogicalPlan): LogicalPlan = plan transformUp {
+ case p: LogicalPlan if !p.childrenResolved => p
+
+ // We are resolving WindowExpressions at here. When we get here, we have already
+ // replaced those WindowSpecReferences.
+ case p: LogicalPlan =>
+ p transformExpressions {
+ case WindowExpression(
+ UnresolvedWindowFunction(name, children),
+ windowSpec: WindowSpecDefinition) =>
+ // First, let's find the window function info.
+ val windowFunctionInfo: WindowFunctionInfo =
+ Option(FunctionRegistry.getWindowFunctionInfo(name.toLowerCase)).getOrElse(
+ throw new AnalysisException(s"Couldn't find window function $name"))
+
+ // Get the class of this function.
+ // In Hive 0.12, there is no windowFunctionInfo.getFunctionClass. So, we use
+ // windowFunctionInfo.getfInfo().getFunctionClass for both Hive 0.13 and Hive 0.13.1.
+ val functionClass = windowFunctionInfo.getfInfo().getFunctionClass
+ val newChildren =
+ // Rank(), DENSE_RANK(), CUME_DIST(), and PERCENT_RANK() do not take explicit
+ // input parameters and requires implicit parameters, which
+ // are expressions in Order By clause.
+ if (classOf[GenericUDAFRank].isAssignableFrom(functionClass)) {
+ if (children.nonEmpty) {
+ throw new AnalysisException(s"$name does not take input parameters.")
+ }
+ windowSpec.orderSpec.map(_.child)
+ } else {
+ children
+ }
+
+ // If the class is UDAF, we need to use UDAFBridge.
+ val isUDAFBridgeRequired =
+ if (classOf[UDAF].isAssignableFrom(functionClass)) {
+ true
+ } else {
+ false
+ }
+
+ // Create the HiveWindowFunction. For the meaning of isPivotResult, see the doc of
+ // HiveWindowFunction.
+ val windowFunction =
+ HiveWindowFunction(
+ new HiveFunctionWrapper(functionClass.getName),
+ windowFunctionInfo.isPivotResult,
+ isUDAFBridgeRequired,
+ newChildren)
+
+ // Second, check if the specified window function can accept window definition.
+ windowSpec.frameSpecification match {
+ case frame: SpecifiedWindowFrame if !windowFunctionInfo.isSupportsWindow =>
+ // This Hive window function does not support user-speficied window frame.
+ throw new AnalysisException(
+ s"Window function $name does not take a frame specification.")
+ case frame: SpecifiedWindowFrame if windowFunctionInfo.isSupportsWindow &&
+ windowFunctionInfo.isPivotResult =>
+ // These two should not be true at the same time when a window frame is defined.
+ // If so, throw an exception.
+ throw new AnalysisException(s"Could not handle Hive window function $name because " +
+ s"it supports both a user specified window frame and pivot result.")
+ case _ => // OK
+ }
+ // Resolve those UnspecifiedWindowFrame because the physical Window operator still needs
+ // a window frame specification to work.
+ val newWindowSpec = windowSpec.frameSpecification match {
+ case UnspecifiedFrame =>
+ val newWindowFrame =
+ SpecifiedWindowFrame.defaultWindowFrame(
+ windowSpec.orderSpec.nonEmpty,
+ windowFunctionInfo.isSupportsWindow)
+ WindowSpecDefinition(windowSpec.partitionSpec, windowSpec.orderSpec, newWindowFrame)
+ case _ => windowSpec
+ }
+
+ // Finally, we create a WindowExpression with the resolved window function and
+ // specified window spec.
+ WindowExpression(windowFunction, newWindowSpec)
+ }
+ }
+}
+
+/**
+ * A [[WindowFunction]] implementation wrapping Hive's window function.
+ * @param funcWrapper The wrapper for the Hive Window Function.
+ * @param pivotResult If it is true, the Hive function will return a list of values representing
+ * the values of the added columns. Otherwise, a single value is returned for
+ * current row.
+ * @param isUDAFBridgeRequired If it is true, the function returned by functionWrapper's
+ * createFunction is UDAF, we need to use GenericUDAFBridge to wrap
+ * it as a GenericUDAFResolver2.
+ * @param children Input parameters.
+ */
+private[hive] case class HiveWindowFunction(
+ funcWrapper: HiveFunctionWrapper,
+ pivotResult: Boolean,
+ isUDAFBridgeRequired: Boolean,
+ children: Seq[Expression]) extends WindowFunction
+ with HiveInspectors {
+
+ // Hive window functions are based on GenericUDAFResolver2.
+ type UDFType = GenericUDAFResolver2
+
+ @transient
+ protected lazy val resolver: GenericUDAFResolver2 =
+ if (isUDAFBridgeRequired) {
+ new GenericUDAFBridge(funcWrapper.createFunction[UDAF]())
+ } else {
+ funcWrapper.createFunction[GenericUDAFResolver2]()
+ }
+
+ @transient
+ protected lazy val inputInspectors = children.map(toInspector).toArray
+
+ // The GenericUDAFEvaluator used to evaluate the window function.
+ @transient
+ protected lazy val evaluator: GenericUDAFEvaluator = {
+ val parameterInfo = new SimpleGenericUDAFParameterInfo(inputInspectors, false, false)
+ resolver.getEvaluator(parameterInfo)
+ }
+
+ // The object inspector of values returned from the Hive window function.
+ @transient
+ protected lazy val returnInspector = {
+ evaluator.init(GenericUDAFEvaluator.Mode.COMPLETE, inputInspectors)
+ }
+
+ def dataType: DataType =
+ if (!pivotResult) {
+ inspectorToDataType(returnInspector)
+ } else {
+ // If pivotResult is true, we should take the element type out as the data type of this
+ // function.
+ inspectorToDataType(returnInspector) match {
+ case ArrayType(dt, _) => dt
+ case _ =>
+ sys.error(
+ s"error resolve the data type of window function ${funcWrapper.functionClassName}")
+ }
+ }
+
+ def nullable: Boolean = true
+
+ override type EvaluatedType = Any
+
+ override def eval(input: Row): Any =
+ throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}")
+
+ @transient
+ lazy val inputProjection = new InterpretedProjection(children)
+
+ @transient
+ private var hiveEvaluatorBuffer: AggregationBuffer = _
+ // Output buffer.
+ private var outputBuffer: Any = _
+
+ override def init(): Unit = {
+ evaluator.init(GenericUDAFEvaluator.Mode.COMPLETE, inputInspectors)
+ }
+
+ // Reset the hiveEvaluatorBuffer and outputPosition
+ override def reset(): Unit = {
+ // We create a new aggregation buffer to workaround the bug in GenericUDAFRowNumber.
+ // Basically, GenericUDAFRowNumberEvaluator.reset calls RowNumberBuffer.init.
+ // However, RowNumberBuffer.init does not really reset this buffer.
+ hiveEvaluatorBuffer = evaluator.getNewAggregationBuffer
+ evaluator.reset(hiveEvaluatorBuffer)
+ }
+
+ override def prepareInputParameters(input: Row): AnyRef = {
+ wrap(inputProjection(input), inputInspectors, new Array[AnyRef](children.length))
+ }
+ // Add input parameters for a single row.
+ override def update(input: AnyRef): Unit = {
+ evaluator.iterate(hiveEvaluatorBuffer, input.asInstanceOf[Array[AnyRef]])
+ }
+
+ override def batchUpdate(inputs: Array[AnyRef]): Unit = {
+ var i = 0
+ while (i < inputs.length) {
+ evaluator.iterate(hiveEvaluatorBuffer, inputs(i).asInstanceOf[Array[AnyRef]])
+ i += 1
+ }
+ }
+
+ override def evaluate(): Unit = {
+ outputBuffer = unwrap(evaluator.evaluate(hiveEvaluatorBuffer), returnInspector)
+ }
+
+ override def get(index: Int): Any = {
+ if (!pivotResult) {
+ // if pivotResult is false, we will get a single value for all rows in the frame.
+ outputBuffer
+ } else {
+ // if pivotResult is true, we will get a Seq having the same size with the size
+ // of the window frame. At here, we will return the result at the position of
+ // index in the output buffer.
+ outputBuffer.asInstanceOf[Seq[Any]].get(index)
+ }
+ }
+
+ override def toString: String = {
+ s"$nodeName#${funcWrapper.functionClassName}(${children.mkString(",")})"
+ }
+
+ override def newInstance: WindowFunction =
+ new HiveWindowFunction(funcWrapper, pivotResult, isUDAFBridgeRequired, children)
+}
+
private[hive] case class HiveGenericUdaf(
funcWrapper: HiveFunctionWrapper,
children: Seq[Expression]) extends AggregateExpression
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 1. testWindowing-0-327a8cd39fe30255ff492ee86f660522 b/sql/hive/src/test/resources/golden/windowing.q -- 1. testWindowing-0-327a8cd39fe30255ff492ee86f660522
new file mode 100644
index 0000000000000000000000000000000000000000..850c41c8115d6f4ee3c712324d68fc2a9b5ac3c7
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 1. testWindowing-0-327a8cd39fe30255ff492ee86f660522
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 1173.15
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 2346.3
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3 2 4100.06
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4 3 5702.650000000001
+Manufacturer#1 almond aquamarine burnished black steel 28 5 4 7117.070000000001
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 6 5 8749.730000000001
+Manufacturer#2 almond antique violet chocolate turquoise 14 1 1 1690.68
+Manufacturer#2 almond antique violet turquoise frosted 40 2 2 3491.38
+Manufacturer#2 almond aquamarine midnight light salmon 2 3 3 5523.360000000001
+Manufacturer#2 almond aquamarine rose maroon antique 25 4 4 7222.02
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5 5 8923.62
+Manufacturer#3 almond antique chartreuse khaki white 17 1 1 1671.68
+Manufacturer#3 almond antique forest lavender goldenrod 14 2 2 2861.95
+Manufacturer#3 almond antique metallic orange dim 19 3 3 4272.34
+Manufacturer#3 almond antique misty red olive 1 4 4 6195.32
+Manufacturer#3 almond antique olive coral navajo 45 5 5 7532.61
+Manufacturer#4 almond antique gainsboro frosted violet 10 1 1 1620.67
+Manufacturer#4 almond antique violet mint lemon 39 2 2 2996.09
+Manufacturer#4 almond aquamarine floral ivory bisque 27 3 3 4202.35
+Manufacturer#4 almond aquamarine yellow dodger mint 7 4 4 6047.27
+Manufacturer#4 almond azure aquamarine papaya violet 12 5 5 7337.620000000001
+Manufacturer#5 almond antique blue firebrick mint 31 1 1 1789.69
+Manufacturer#5 almond antique medium spring khaki 6 2 2 3401.3500000000004
+Manufacturer#5 almond antique sky peru orange 2 3 3 5190.08
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 4 4 6208.18
+Manufacturer#5 almond azure blanched chiffon midnight 23 5 5 7672.66
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 10. testHavingWithWindowingCondRankNoGBY-0-fef4bf638d52a9a601845347010602fd b/sql/hive/src/test/resources/golden/windowing.q -- 10. testHavingWithWindowingCondRankNoGBY-0-fef4bf638d52a9a601845347010602fd
new file mode 100644
index 0000000000000000000000000000000000000000..850c41c8115d6f4ee3c712324d68fc2a9b5ac3c7
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 10. testHavingWithWindowingCondRankNoGBY-0-fef4bf638d52a9a601845347010602fd
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 1173.15
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 2346.3
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3 2 4100.06
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4 3 5702.650000000001
+Manufacturer#1 almond aquamarine burnished black steel 28 5 4 7117.070000000001
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 6 5 8749.730000000001
+Manufacturer#2 almond antique violet chocolate turquoise 14 1 1 1690.68
+Manufacturer#2 almond antique violet turquoise frosted 40 2 2 3491.38
+Manufacturer#2 almond aquamarine midnight light salmon 2 3 3 5523.360000000001
+Manufacturer#2 almond aquamarine rose maroon antique 25 4 4 7222.02
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5 5 8923.62
+Manufacturer#3 almond antique chartreuse khaki white 17 1 1 1671.68
+Manufacturer#3 almond antique forest lavender goldenrod 14 2 2 2861.95
+Manufacturer#3 almond antique metallic orange dim 19 3 3 4272.34
+Manufacturer#3 almond antique misty red olive 1 4 4 6195.32
+Manufacturer#3 almond antique olive coral navajo 45 5 5 7532.61
+Manufacturer#4 almond antique gainsboro frosted violet 10 1 1 1620.67
+Manufacturer#4 almond antique violet mint lemon 39 2 2 2996.09
+Manufacturer#4 almond aquamarine floral ivory bisque 27 3 3 4202.35
+Manufacturer#4 almond aquamarine yellow dodger mint 7 4 4 6047.27
+Manufacturer#4 almond azure aquamarine papaya violet 12 5 5 7337.620000000001
+Manufacturer#5 almond antique blue firebrick mint 31 1 1 1789.69
+Manufacturer#5 almond antique medium spring khaki 6 2 2 3401.3500000000004
+Manufacturer#5 almond antique sky peru orange 2 3 3 5190.08
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 4 4 6208.18
+Manufacturer#5 almond azure blanched chiffon midnight 23 5 5 7672.66
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 11. testFirstLast-0-86bb9c97d92fdcd941bcb5143513e2e6 b/sql/hive/src/test/resources/golden/windowing.q -- 11. testFirstLast-0-86bb9c97d92fdcd941bcb5143513e2e6
new file mode 100644
index 0000000000000000000000000000000000000000..921679cdcf569bcabc8a6d767f3548a77e72cd66
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 11. testFirstLast-0-86bb9c97d92fdcd941bcb5143513e2e6
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 2 2 34
+Manufacturer#1 almond antique burnished rose metallic 2 2 2 6
+Manufacturer#1 almond antique chartreuse lavender yellow 34 34 2 28
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 6 2 42
+Manufacturer#1 almond aquamarine burnished black steel 28 28 34 42
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 42 6 42
+Manufacturer#2 almond antique violet chocolate turquoise 14 14 14 2
+Manufacturer#2 almond antique violet turquoise frosted 40 40 14 25
+Manufacturer#2 almond aquamarine midnight light salmon 2 2 14 18
+Manufacturer#2 almond aquamarine rose maroon antique 25 25 40 18
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 18 2 18
+Manufacturer#3 almond antique chartreuse khaki white 17 17 17 19
+Manufacturer#3 almond antique forest lavender goldenrod 14 14 17 1
+Manufacturer#3 almond antique metallic orange dim 19 19 17 45
+Manufacturer#3 almond antique misty red olive 1 1 14 45
+Manufacturer#3 almond antique olive coral navajo 45 45 19 45
+Manufacturer#4 almond antique gainsboro frosted violet 10 10 10 27
+Manufacturer#4 almond antique violet mint lemon 39 39 10 7
+Manufacturer#4 almond aquamarine floral ivory bisque 27 27 10 12
+Manufacturer#4 almond aquamarine yellow dodger mint 7 7 39 12
+Manufacturer#4 almond azure aquamarine papaya violet 12 12 27 12
+Manufacturer#5 almond antique blue firebrick mint 31 31 31 2
+Manufacturer#5 almond antique medium spring khaki 6 6 31 46
+Manufacturer#5 almond antique sky peru orange 2 2 31 23
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 46 6 23
+Manufacturer#5 almond azure blanched chiffon midnight 23 23 2 23
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 12. testFirstLastWithWhere-0-84345a9f685ba63b87caa4bb16b122b5 b/sql/hive/src/test/resources/golden/windowing.q -- 12. testFirstLastWithWhere-0-84345a9f685ba63b87caa4bb16b122b5
new file mode 100644
index 0000000000000000000000000000000000000000..09e30c7c57349e41c0c4f99b9d4a8141c9cc5aca
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 12. testFirstLastWithWhere-0-84345a9f685ba63b87caa4bb16b122b5
@@ -0,0 +1,5 @@
+Manufacturer#3 almond antique chartreuse khaki white 17 1 17 17 19
+Manufacturer#3 almond antique forest lavender goldenrod 14 2 14 17 1
+Manufacturer#3 almond antique metallic orange dim 19 3 19 17 45
+Manufacturer#3 almond antique misty red olive 1 4 1 14 45
+Manufacturer#3 almond antique olive coral navajo 45 5 45 19 45
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 13. testSumWindow-0-6cfc8840d3a4469b0fe11d63182cb59f b/sql/hive/src/test/resources/golden/windowing.q -- 13. testSumWindow-0-6cfc8840d3a4469b0fe11d63182cb59f
new file mode 100644
index 0000000000000000000000000000000000000000..01ee88ff233029c665ef24ac310f09ec4b27e163
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 13. testSumWindow-0-6cfc8840d3a4469b0fe11d63182cb59f
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 38 2
+Manufacturer#1 almond antique burnished rose metallic 2 44 2
+Manufacturer#1 almond antique chartreuse lavender yellow 34 72 34
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 112 6
+Manufacturer#1 almond aquamarine burnished black steel 28 110 28
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 76 42
+Manufacturer#2 almond antique violet chocolate turquoise 14 56 14
+Manufacturer#2 almond antique violet turquoise frosted 40 81 40
+Manufacturer#2 almond aquamarine midnight light salmon 2 99 2
+Manufacturer#2 almond aquamarine rose maroon antique 25 85 25
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 45 18
+Manufacturer#3 almond antique chartreuse khaki white 17 50 17
+Manufacturer#3 almond antique forest lavender goldenrod 14 51 14
+Manufacturer#3 almond antique metallic orange dim 19 96 19
+Manufacturer#3 almond antique misty red olive 1 79 1
+Manufacturer#3 almond antique olive coral navajo 45 65 45
+Manufacturer#4 almond antique gainsboro frosted violet 10 76 10
+Manufacturer#4 almond antique violet mint lemon 39 83 39
+Manufacturer#4 almond aquamarine floral ivory bisque 27 95 27
+Manufacturer#4 almond aquamarine yellow dodger mint 7 85 7
+Manufacturer#4 almond azure aquamarine papaya violet 12 46 12
+Manufacturer#5 almond antique blue firebrick mint 31 39 31
+Manufacturer#5 almond antique medium spring khaki 6 85 6
+Manufacturer#5 almond antique sky peru orange 2 108 2
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 77 46
+Manufacturer#5 almond azure blanched chiffon midnight 23 71 23
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 14. testNoSortClause-0-88d96a526d3cae6ed8168c5b228974d1 b/sql/hive/src/test/resources/golden/windowing.q -- 14. testNoSortClause-0-88d96a526d3cae6ed8168c5b228974d1
new file mode 100644
index 0000000000000000000000000000000000000000..c78eb640c9c2744724a97c63a30dfd687de69cec
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 14. testNoSortClause-0-88d96a526d3cae6ed8168c5b228974d1
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1 1
+Manufacturer#1 almond antique burnished rose metallic 2 1 1
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3 2
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4 3
+Manufacturer#1 almond aquamarine burnished black steel 28 5 4
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 6 5
+Manufacturer#2 almond antique violet chocolate turquoise 14 1 1
+Manufacturer#2 almond antique violet turquoise frosted 40 2 2
+Manufacturer#2 almond aquamarine midnight light salmon 2 3 3
+Manufacturer#2 almond aquamarine rose maroon antique 25 4 4
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5 5
+Manufacturer#3 almond antique chartreuse khaki white 17 1 1
+Manufacturer#3 almond antique forest lavender goldenrod 14 2 2
+Manufacturer#3 almond antique metallic orange dim 19 3 3
+Manufacturer#3 almond antique misty red olive 1 4 4
+Manufacturer#3 almond antique olive coral navajo 45 5 5
+Manufacturer#4 almond antique gainsboro frosted violet 10 1 1
+Manufacturer#4 almond antique violet mint lemon 39 2 2
+Manufacturer#4 almond aquamarine floral ivory bisque 27 3 3
+Manufacturer#4 almond aquamarine yellow dodger mint 7 4 4
+Manufacturer#4 almond azure aquamarine papaya violet 12 5 5
+Manufacturer#5 almond antique blue firebrick mint 31 1 1
+Manufacturer#5 almond antique medium spring khaki 6 2 2
+Manufacturer#5 almond antique sky peru orange 2 3 3
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 4 4
+Manufacturer#5 almond azure blanched chiffon midnight 23 5 5
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 15. testExpressions-0-11f6c13cf2710ce7054654cca136e73e b/sql/hive/src/test/resources/golden/windowing.q -- 15. testExpressions-0-11f6c13cf2710ce7054654cca136e73e
new file mode 100644
index 0000000000000000000000000000000000000000..050138ccf04ce2c34ed96daf1fdbf9349c925048
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 15. testExpressions-0-11f6c13cf2710ce7054654cca136e73e
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 0.3333333333333333 0.0 1 2 2.0 0.0 2 2 2
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 0.3333333333333333 0.0 1 2 2.0 0.0 2 2 2
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3 2 0.5 0.4 2 3 12.666666666666666 15.084944665313014 2 34 2
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4 3 0.6666666666666666 0.6 2 4 11.0 13.379088160259652 2 6 2
+Manufacturer#1 almond aquamarine burnished black steel 28 5 4 0.8333333333333334 0.8 3 5 14.4 13.763720427268202 2 28 34
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 6 5 1.0 1.0 3 6 19.0 16.237815945091466 2 42 6
+Manufacturer#2 almond antique violet chocolate turquoise 14 1 1 0.2 0.0 1 1 14.0 0.0 4 14 14
+Manufacturer#2 almond antique violet turquoise frosted 40 2 2 0.4 0.25 1 2 27.0 13.0 4 40 14
+Manufacturer#2 almond aquamarine midnight light salmon 2 3 3 0.6 0.5 2 3 18.666666666666668 15.86050300449376 4 2 14
+Manufacturer#2 almond aquamarine rose maroon antique 25 4 4 0.8 0.75 2 4 20.25 14.00669482783144 4 25 40
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5 5 1.0 1.0 3 5 19.8 12.560254774486067 4 18 2
+Manufacturer#3 almond antique chartreuse khaki white 17 1 1 0.2 0.0 1 1 17.0 0.0 2 17 17
+Manufacturer#3 almond antique forest lavender goldenrod 14 2 2 0.4 0.25 1 2 15.5 1.5 2 14 17
+Manufacturer#3 almond antique metallic orange dim 19 3 3 0.6 0.5 2 3 16.666666666666668 2.0548046676563256 2 19 17
+Manufacturer#3 almond antique misty red olive 1 4 4 0.8 0.75 2 4 12.75 7.013380069552769 2 1 14
+Manufacturer#3 almond antique olive coral navajo 45 5 5 1.0 1.0 3 5 19.2 14.344336861632886 2 45 19
+Manufacturer#4 almond antique gainsboro frosted violet 10 1 1 0.2 0.0 1 1 10.0 0.0 0 10 10
+Manufacturer#4 almond antique violet mint lemon 39 2 2 0.4 0.25 1 2 24.5 14.5 0 39 10
+Manufacturer#4 almond aquamarine floral ivory bisque 27 3 3 0.6 0.5 2 3 25.333333333333332 11.897712198383164 0 27 10
+Manufacturer#4 almond aquamarine yellow dodger mint 7 4 4 0.8 0.75 2 4 20.75 13.007209539328564 0 7 39
+Manufacturer#4 almond azure aquamarine papaya violet 12 5 5 1.0 1.0 3 5 19.0 12.149074038789951 0 12 27
+Manufacturer#5 almond antique blue firebrick mint 31 1 1 0.2 0.0 1 1 31.0 0.0 1 31 31
+Manufacturer#5 almond antique medium spring khaki 6 2 2 0.4 0.25 1 2 18.5 12.5 1 6 31
+Manufacturer#5 almond antique sky peru orange 2 3 3 0.6 0.5 2 3 13.0 12.832251036613439 1 2 31
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 4 4 0.8 0.75 2 4 21.25 18.102140757380052 1 46 6
+Manufacturer#5 almond azure blanched chiffon midnight 23 5 5 1.0 1.0 3 5 21.6 16.206171663906314 1 23 2
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 16. testMultipleWindows-0-efd1476255eeb1b1961149144f574b7a b/sql/hive/src/test/resources/golden/windowing.q -- 16. testMultipleWindows-0-efd1476255eeb1b1961149144f574b7a
new file mode 100644
index 0000000000000000000000000000000000000000..c10888852b504389a0acf97e19363885e62acf40
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 16. testMultipleWindows-0-efd1476255eeb1b1961149144f574b7a
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 0.3333333333333333 4 4 2
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 0.3333333333333333 4 4 2
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3 2 0.5 38 34 2
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4 3 0.6666666666666666 44 10 2
+Manufacturer#1 almond aquamarine burnished black steel 28 5 4 0.8333333333333334 72 28 34
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 6 5 1.0 114 42 6
+Manufacturer#2 almond antique violet chocolate turquoise 14 1 1 0.2 14 14 14
+Manufacturer#2 almond antique violet turquoise frosted 40 2 2 0.4 54 40 14
+Manufacturer#2 almond aquamarine midnight light salmon 2 3 3 0.6 56 2 14
+Manufacturer#2 almond aquamarine rose maroon antique 25 4 4 0.8 81 25 40
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5 5 1.0 99 32 2
+Manufacturer#3 almond antique chartreuse khaki white 17 1 1 0.2 17 31 17
+Manufacturer#3 almond antique forest lavender goldenrod 14 2 2 0.4 31 14 17
+Manufacturer#3 almond antique metallic orange dim 19 3 3 0.6 50 50 17
+Manufacturer#3 almond antique misty red olive 1 4 4 0.8 51 1 14
+Manufacturer#3 almond antique olive coral navajo 45 5 5 1.0 96 45 19
+Manufacturer#4 almond antique gainsboro frosted violet 10 1 1 0.2 10 17 10
+Manufacturer#4 almond antique violet mint lemon 39 2 2 0.4 49 39 10
+Manufacturer#4 almond aquamarine floral ivory bisque 27 3 3 0.6 76 27 10
+Manufacturer#4 almond aquamarine yellow dodger mint 7 4 4 0.8 83 7 39
+Manufacturer#4 almond azure aquamarine papaya violet 12 5 5 1.0 95 29 27
+Manufacturer#5 almond antique blue firebrick mint 31 1 1 0.2 31 31 31
+Manufacturer#5 almond antique medium spring khaki 6 2 2 0.4 37 8 31
+Manufacturer#5 almond antique sky peru orange 2 3 3 0.6 39 2 31
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 4 4 0.8 85 46 6
+Manufacturer#5 almond azure blanched chiffon midnight 23 5 5 1.0 108 23 2
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 17. testCountStar-0-1b1fc185c8fddf68e58e92f29052ab2d b/sql/hive/src/test/resources/golden/windowing.q -- 17. testCountStar-0-1b1fc185c8fddf68e58e92f29052ab2d
new file mode 100644
index 0000000000000000000000000000000000000000..b1309a497d68ec2669e811c36c5b5773da329dcd
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 17. testCountStar-0-1b1fc185c8fddf68e58e92f29052ab2d
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 2 2 2
+Manufacturer#1 almond antique burnished rose metallic 2 2 2 2
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3 3 2
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4 4 2
+Manufacturer#1 almond aquamarine burnished black steel 28 5 5 34
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 6 6 6
+Manufacturer#2 almond antique violet chocolate turquoise 14 1 1 14
+Manufacturer#2 almond antique violet turquoise frosted 40 2 2 14
+Manufacturer#2 almond aquamarine midnight light salmon 2 3 3 14
+Manufacturer#2 almond aquamarine rose maroon antique 25 4 4 40
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5 5 2
+Manufacturer#3 almond antique chartreuse khaki white 17 1 1 17
+Manufacturer#3 almond antique forest lavender goldenrod 14 2 2 17
+Manufacturer#3 almond antique metallic orange dim 19 3 3 17
+Manufacturer#3 almond antique misty red olive 1 4 4 14
+Manufacturer#3 almond antique olive coral navajo 45 5 5 19
+Manufacturer#4 almond antique gainsboro frosted violet 10 1 1 10
+Manufacturer#4 almond antique violet mint lemon 39 2 2 10
+Manufacturer#4 almond aquamarine floral ivory bisque 27 3 3 10
+Manufacturer#4 almond aquamarine yellow dodger mint 7 4 4 39
+Manufacturer#4 almond azure aquamarine papaya violet 12 5 5 27
+Manufacturer#5 almond antique blue firebrick mint 31 1 1 31
+Manufacturer#5 almond antique medium spring khaki 6 2 2 31
+Manufacturer#5 almond antique sky peru orange 2 3 3 31
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 4 4 6
+Manufacturer#5 almond azure blanched chiffon midnight 23 5 5 2
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 18. testUDAFs-0-6974e5959e41a661e09db18547fef58a b/sql/hive/src/test/resources/golden/windowing.q -- 18. testUDAFs-0-6974e5959e41a661e09db18547fef58a
new file mode 100644
index 0000000000000000000000000000000000000000..52d2ee8d0cd3f3e44cedc93a41cccb90ec9fcfd4
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 18. testUDAFs-0-6974e5959e41a661e09db18547fef58a
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 4100.06 1173.15 1753.76 1366.6866666666667
+Manufacturer#1 almond antique burnished rose metallic 2 5702.650000000001 1173.15 1753.76 1425.6625000000001
+Manufacturer#1 almond antique chartreuse lavender yellow 34 7117.070000000001 1173.15 1753.76 1423.4140000000002
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 7576.58 1173.15 1753.76 1515.316
+Manufacturer#1 almond aquamarine burnished black steel 28 6403.43 1414.42 1753.76 1600.8575
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 4649.67 1414.42 1632.66 1549.89
+Manufacturer#2 almond antique violet chocolate turquoise 14 5523.360000000001 1690.68 2031.98 1841.1200000000001
+Manufacturer#2 almond antique violet turquoise frosted 40 7222.02 1690.68 2031.98 1805.505
+Manufacturer#2 almond aquamarine midnight light salmon 2 8923.62 1690.68 2031.98 1784.7240000000002
+Manufacturer#2 almond aquamarine rose maroon antique 25 7232.9400000000005 1698.66 2031.98 1808.2350000000001
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5432.24 1698.66 2031.98 1810.7466666666667
+Manufacturer#3 almond antique chartreuse khaki white 17 4272.34 1190.27 1671.68 1424.1133333333335
+Manufacturer#3 almond antique forest lavender goldenrod 14 6195.32 1190.27 1922.98 1548.83
+Manufacturer#3 almond antique metallic orange dim 19 7532.61 1190.27 1922.98 1506.522
+Manufacturer#3 almond antique misty red olive 1 5860.929999999999 1190.27 1922.98 1465.2324999999998
+Manufacturer#3 almond antique olive coral navajo 45 4670.66 1337.29 1922.98 1556.8866666666665
+Manufacturer#4 almond antique gainsboro frosted violet 10 4202.35 1206.26 1620.67 1400.7833333333335
+Manufacturer#4 almond antique violet mint lemon 39 6047.27 1206.26 1844.92 1511.8175
+Manufacturer#4 almond aquamarine floral ivory bisque 27 7337.620000000001 1206.26 1844.92 1467.5240000000001
+Manufacturer#4 almond aquamarine yellow dodger mint 7 5716.950000000001 1206.26 1844.92 1429.2375000000002
+Manufacturer#4 almond azure aquamarine papaya violet 12 4341.530000000001 1206.26 1844.92 1447.176666666667
+Manufacturer#5 almond antique blue firebrick mint 31 5190.08 1611.66 1789.69 1730.0266666666666
+Manufacturer#5 almond antique medium spring khaki 6 6208.18 1018.1 1789.69 1552.045
+Manufacturer#5 almond antique sky peru orange 2 7672.66 1018.1 1789.69 1534.532
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 5882.970000000001 1018.1 1788.73 1470.7425000000003
+Manufacturer#5 almond azure blanched chiffon midnight 23 4271.3099999999995 1018.1 1788.73 1423.7699999999998
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 19. testUDAFsWithGBY-0-67d15ee5915ac64a738fd4b60d75eb35 b/sql/hive/src/test/resources/golden/windowing.q -- 19. testUDAFsWithGBY-0-67d15ee5915ac64a738fd4b60d75eb35
new file mode 100644
index 0000000000000000000000000000000000000000..6461642d34a21171a3f10673a3aa4755374ec7f5
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 19. testUDAFsWithGBY-0-67d15ee5915ac64a738fd4b60d75eb35
@@ -0,0 +1,25 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1173.15 4529.5 1173.15 1173.15 1509.8333333333333
+Manufacturer#1 almond antique chartreuse lavender yellow 34 1753.76 5943.92 1753.76 1753.76 1485.98
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 1602.59 7576.58 1602.59 1602.59 1515.316
+Manufacturer#1 almond aquamarine burnished black steel 28 1414.42 6403.43 1414.42 1414.42 1600.8575
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 1632.66 4649.67 1632.66 1632.66 1549.89
+Manufacturer#2 almond antique violet chocolate turquoise 14 1690.68 5523.360000000001 1690.68 1690.68 1841.1200000000001
+Manufacturer#2 almond antique violet turquoise frosted 40 1800.7 7222.02 1800.7 1800.7 1805.505
+Manufacturer#2 almond aquamarine midnight light salmon 2 2031.98 8923.62 2031.98 2031.98 1784.7240000000002
+Manufacturer#2 almond aquamarine rose maroon antique 25 1698.66 7232.9400000000005 1698.66 1698.66 1808.2350000000001
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 1701.6 5432.24 1701.6 1701.6 1810.7466666666667
+Manufacturer#3 almond antique chartreuse khaki white 17 1671.68 4272.34 1671.68 1671.68 1424.1133333333335
+Manufacturer#3 almond antique forest lavender goldenrod 14 1190.27 6195.32 1190.27 1190.27 1548.83
+Manufacturer#3 almond antique metallic orange dim 19 1410.39 7532.61 1410.39 1410.39 1506.522
+Manufacturer#3 almond antique misty red olive 1 1922.98 5860.929999999999 1922.98 1922.98 1465.2324999999998
+Manufacturer#3 almond antique olive coral navajo 45 1337.29 4670.66 1337.29 1337.29 1556.8866666666665
+Manufacturer#4 almond antique gainsboro frosted violet 10 1620.67 4202.35 1620.67 1620.67 1400.7833333333335
+Manufacturer#4 almond antique violet mint lemon 39 1375.42 6047.27 1375.42 1375.42 1511.8175
+Manufacturer#4 almond aquamarine floral ivory bisque 27 1206.26 7337.620000000001 1206.26 1206.26 1467.5240000000001
+Manufacturer#4 almond aquamarine yellow dodger mint 7 1844.92 5716.950000000001 1844.92 1844.92 1429.2375000000002
+Manufacturer#4 almond azure aquamarine papaya violet 12 1290.35 4341.530000000001 1290.35 1290.35 1447.176666666667
+Manufacturer#5 almond antique blue firebrick mint 31 1789.69 5190.08 1789.69 1789.69 1730.0266666666666
+Manufacturer#5 almond antique medium spring khaki 6 1611.66 6208.18 1611.66 1611.66 1552.045
+Manufacturer#5 almond antique sky peru orange 2 1788.73 7672.66 1788.73 1788.73 1534.532
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 1018.1 5882.970000000001 1018.1 1018.1 1470.7425000000003
+Manufacturer#5 almond azure blanched chiffon midnight 23 1464.48 4271.3099999999995 1464.48 1464.48 1423.7699999999998
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 2. testGroupByWithPartitioning-0-cb5618b1e626f3a9d4a030b508b5d251 b/sql/hive/src/test/resources/golden/windowing.q -- 2. testGroupByWithPartitioning-0-cb5618b1e626f3a9d4a030b508b5d251
new file mode 100644
index 0000000000000000000000000000000000000000..2c30e652aa26d6baac06f06ebab3fd7ac12f010e
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 2. testGroupByWithPartitioning-0-cb5618b1e626f3a9d4a030b508b5d251
@@ -0,0 +1,25 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1173.15 1 1 2 0
+Manufacturer#1 almond antique chartreuse lavender yellow 34 1753.76 2 2 34 32
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 1602.59 3 3 6 -28
+Manufacturer#1 almond aquamarine burnished black steel 28 1414.42 4 4 28 22
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 1632.66 5 5 42 14
+Manufacturer#2 almond antique violet chocolate turquoise 14 1690.68 1 1 14 0
+Manufacturer#2 almond antique violet turquoise frosted 40 1800.7 2 2 40 26
+Manufacturer#2 almond aquamarine midnight light salmon 2 2031.98 3 3 2 -38
+Manufacturer#2 almond aquamarine rose maroon antique 25 1698.66 4 4 25 23
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 1701.6 5 5 18 -7
+Manufacturer#3 almond antique chartreuse khaki white 17 1671.68 1 1 17 0
+Manufacturer#3 almond antique forest lavender goldenrod 14 1190.27 2 2 14 -3
+Manufacturer#3 almond antique metallic orange dim 19 1410.39 3 3 19 5
+Manufacturer#3 almond antique misty red olive 1 1922.98 4 4 1 -18
+Manufacturer#3 almond antique olive coral navajo 45 1337.29 5 5 45 44
+Manufacturer#4 almond antique gainsboro frosted violet 10 1620.67 1 1 10 0
+Manufacturer#4 almond antique violet mint lemon 39 1375.42 2 2 39 29
+Manufacturer#4 almond aquamarine floral ivory bisque 27 1206.26 3 3 27 -12
+Manufacturer#4 almond aquamarine yellow dodger mint 7 1844.92 4 4 7 -20
+Manufacturer#4 almond azure aquamarine papaya violet 12 1290.35 5 5 12 5
+Manufacturer#5 almond antique blue firebrick mint 31 1789.69 1 1 31 0
+Manufacturer#5 almond antique medium spring khaki 6 1611.66 2 2 6 -25
+Manufacturer#5 almond antique sky peru orange 2 1788.73 3 3 2 -4
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 1018.1 4 4 46 44
+Manufacturer#5 almond azure blanched chiffon midnight 23 1464.48 5 5 23 -23
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 20. testSTATs-0-da0e0cca69e42118a96b8609b8fa5838 b/sql/hive/src/test/resources/golden/windowing.q -- 20. testSTATs-0-da0e0cca69e42118a96b8609b8fa5838
new file mode 100644
index 0000000000000000000000000000000000000000..1f7e8a5d67036678c557542be33dc808198bdbba
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 20. testSTATs-0-da0e0cca69e42118a96b8609b8fa5838
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 273.70217881648074 273.70217881648074 [34,2] 74912.8826888888 1.0 4128.782222222221
+Manufacturer#1 almond antique burnished rose metallic 2 258.10677784349235 258.10677784349235 [34,2,6] 66619.10876874991 0.811328754177887 2801.7074999999995
+Manufacturer#1 almond antique chartreuse lavender yellow 34 230.90151585470358 230.90151585470358 [34,2,6,28] 53315.51002399992 0.695639377397664 2210.7864
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 202.73109328368946 202.73109328368946 [34,2,6,42,28] 41099.896184 0.630785977101214 2009.9536000000007
+Manufacturer#1 almond aquamarine burnished black steel 28 121.6064517973862 121.6064517973862 [34,6,42,28] 14788.129118750014 0.2036684720435979 331.1337500000004
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 96.5751586416853 96.5751586416853 [6,42,28] 9326.761266666683 -1.4442181184933883E-4 -0.20666666666708502
+Manufacturer#2 almond antique violet chocolate turquoise 14 142.2363169751898 142.2363169751898 [2,40,14] 20231.169866666663 -0.49369526554523185 -1113.7466666666658
+Manufacturer#2 almond antique violet turquoise frosted 40 137.76306498840682 137.76306498840682 [2,25,40,14] 18978.662075 -0.5205630897335946 -1004.4812499999995
+Manufacturer#2 almond aquamarine midnight light salmon 2 130.03972279269132 130.03972279269132 [2,18,25,40,14] 16910.329504000005 -0.46908967495720255 -766.1791999999995
+Manufacturer#2 almond aquamarine rose maroon antique 25 135.55100986344584 135.55100986344584 [2,18,25,40] 18374.07627499999 -0.6091405874714462 -1128.1787499999987
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 156.44019460768044 156.44019460768044 [2,18,25] 24473.534488888927 -0.9571686373491608 -1441.4466666666676
+Manufacturer#3 almond antique chartreuse khaki white 17 196.7742266885805 196.7742266885805 [17,19,14] 38720.09628888887 0.5557168646224995 224.6944444444446
+Manufacturer#3 almond antique forest lavender goldenrod 14 275.14144189852607 275.14144189852607 [17,1,19,14] 75702.81305 -0.6720833036576083 -1296.9000000000003
+Manufacturer#3 almond antique metallic orange dim 19 260.23473614412046 260.23473614412046 [17,1,19,14,45] 67722.117896 -0.5703526513979519 -2129.0664
+Manufacturer#3 almond antique misty red olive 1 275.9139962356932 275.9139962356932 [1,19,14,45] 76128.53331875012 -0.577476899644802 -2547.7868749999993
+Manufacturer#3 almond antique olive coral navajo 45 260.5815918713796 260.5815918713796 [1,19,45] 67902.76602222225 -0.8710736366736884 -4099.731111111111
+Manufacturer#4 almond antique gainsboro frosted violet 10 170.13011889596618 170.13011889596618 [39,27,10] 28944.25735555559 -0.6656975320098423 -1347.4777777777779
+Manufacturer#4 almond antique violet mint lemon 39 242.26834609323197 242.26834609323197 [39,7,27,10] 58693.95151875002 -0.8051852719193339 -2537.328125
+Manufacturer#4 almond aquamarine floral ivory bisque 27 234.10001662537326 234.10001662537326 [39,7,27,10,12] 54802.817784000035 -0.6046935574240581 -1719.8079999999995
+Manufacturer#4 almond aquamarine yellow dodger mint 7 247.3342714197732 247.3342714197732 [39,7,27,12] 61174.24181875003 -0.5508665654707869 -1719.0368749999975
+Manufacturer#4 almond azure aquamarine papaya violet 12 283.3344330566893 283.3344330566893 [7,27,12] 80278.40095555557 -0.7755740084632333 -1867.4888888888881
+Manufacturer#5 almond antique blue firebrick mint 31 83.69879024746363 83.69879024746363 [2,6,31] 7005.487488888913 0.39004303087285047 418.9233333333353
+Manufacturer#5 almond antique medium spring khaki 6 316.68049612345885 316.68049612345885 [2,6,46,31] 100286.53662500004 -0.713612911776183 -4090.853749999999
+Manufacturer#5 almond antique sky peru orange 2 285.40506298242155 285.40506298242155 [2,23,6,46,31] 81456.04997600002 -0.712858514567818 -3297.2011999999986
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 285.43749038756283 285.43749038756283 [2,23,6,46] 81474.56091875004 -0.984128787153391 -4871.028125000002
+Manufacturer#5 almond azure blanched chiffon midnight 23 315.9225931564038 315.9225931564038 [2,23,46] 99807.08486666664 -0.9978877469246936 -5664.856666666666
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 21. testDISTs-0-672d4cb385b7ced2e446f132474293ad b/sql/hive/src/test/resources/golden/windowing.q -- 21. testDISTs-0-672d4cb385b7ced2e446f132474293ad
new file mode 100644
index 0000000000000000000000000000000000000000..e7c39f454fb37cd3f2ee48b5fb044b7ff3797f03
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 21. testDISTs-0-672d4cb385b7ced2e446f132474293ad
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 [{"x":1173.15,"y":2.0},{"x":1753.76,"y":1.0}] 121152.0 1
+Manufacturer#1 almond antique burnished rose metallic 2 [{"x":1173.15,"y":2.0},{"x":1602.59,"y":1.0},{"x":1753.76,"y":1.0}] 115872.0 2
+Manufacturer#1 almond antique chartreuse lavender yellow 34 [{"x":1173.15,"y":2.0},{"x":1414.42,"y":1.0},{"x":1602.59,"y":1.0},{"x":1753.76,"y":1.0}] 110592.0 3
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 [{"x":1173.15,"y":1.0},{"x":1414.42,"y":1.0},{"x":1602.59,"y":1.0},{"x":1632.66,"y":1.0},{"x":1753.76,"y":1.0}] 86428.0 4
+Manufacturer#1 almond aquamarine burnished black steel 28 [{"x":1414.42,"y":1.0},{"x":1602.59,"y":1.0},{"x":1632.66,"y":1.0},{"x":1753.76,"y":1.0}] 86098.0 5
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 [{"x":1414.42,"y":1.0},{"x":1602.59,"y":1.0},{"x":1632.66,"y":1.0}] 86428.0 6
+Manufacturer#2 almond antique violet chocolate turquoise 14 [{"x":1690.68,"y":1.0},{"x":1800.7,"y":1.0},{"x":2031.98,"y":1.0}] 146985.0 1
+Manufacturer#2 almond antique violet turquoise frosted 40 [{"x":1690.68,"y":1.0},{"x":1698.66,"y":1.0},{"x":1800.7,"y":1.0},{"x":2031.98,"y":1.0}] 139825.5 2
+Manufacturer#2 almond aquamarine midnight light salmon 2 [{"x":1690.68,"y":1.0},{"x":1698.66,"y":1.0},{"x":1701.6,"y":1.0},{"x":1800.7,"y":1.0},{"x":2031.98,"y":1.0}] 146985.0 3
+Manufacturer#2 almond aquamarine rose maroon antique 25 [{"x":1698.66,"y":1.0},{"x":1701.6,"y":1.0},{"x":1800.7,"y":1.0},{"x":2031.98,"y":1.0}] 169347.0 4
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 [{"x":1698.66,"y":1.0},{"x":1701.6,"y":1.0},{"x":2031.98,"y":1.0}] 146985.0 5
+Manufacturer#3 almond antique chartreuse khaki white 17 [{"x":1190.27,"y":1.0},{"x":1410.39,"y":1.0},{"x":1671.68,"y":1.0}] 90681.0 1
+Manufacturer#3 almond antique forest lavender goldenrod 14 [{"x":1190.27,"y":1.0},{"x":1410.39,"y":1.0},{"x":1671.68,"y":1.0},{"x":1922.98,"y":1.0}] 65831.5 2
+Manufacturer#3 almond antique metallic orange dim 19 [{"x":1190.27,"y":1.0},{"x":1337.29,"y":1.0},{"x":1410.39,"y":1.0},{"x":1671.68,"y":1.0},{"x":1922.98,"y":1.0}] 90681.0 3
+Manufacturer#3 almond antique misty red olive 1 [{"x":1190.27,"y":1.0},{"x":1337.29,"y":1.0},{"x":1410.39,"y":1.0},{"x":1922.98,"y":1.0}] 76690.0 4
+Manufacturer#3 almond antique olive coral navajo 45 [{"x":1337.29,"y":1.0},{"x":1410.39,"y":1.0},{"x":1922.98,"y":1.0}] 112398.0 5
+Manufacturer#4 almond antique gainsboro frosted violet 10 [{"x":1206.26,"y":1.0},{"x":1375.42,"y":1.0},{"x":1620.67,"y":1.0}] 48427.0 1
+Manufacturer#4 almond antique violet mint lemon 39 [{"x":1206.26,"y":1.0},{"x":1375.42,"y":1.0},{"x":1620.67,"y":1.0},{"x":1844.92,"y":1.0}] 46844.0 2
+Manufacturer#4 almond aquamarine floral ivory bisque 27 [{"x":1206.26,"y":1.0},{"x":1290.35,"y":1.0},{"x":1375.42,"y":1.0},{"x":1620.67,"y":1.0},{"x":1844.92,"y":1.0}] 45261.0 3
+Manufacturer#4 almond aquamarine yellow dodger mint 7 [{"x":1206.26,"y":1.0},{"x":1290.35,"y":1.0},{"x":1375.42,"y":1.0},{"x":1844.92,"y":1.0}] 39309.0 4
+Manufacturer#4 almond azure aquamarine papaya violet 12 [{"x":1206.26,"y":1.0},{"x":1290.35,"y":1.0},{"x":1844.92,"y":1.0}] 33357.0 5
+Manufacturer#5 almond antique blue firebrick mint 31 [{"x":1611.66,"y":1.0},{"x":1788.73,"y":1.0},{"x":1789.69,"y":1.0}] 155733.0 1
+Manufacturer#5 almond antique medium spring khaki 6 [{"x":1018.1,"y":1.0},{"x":1611.66,"y":1.0},{"x":1788.73,"y":1.0},{"x":1789.69,"y":1.0}] 99201.0 2
+Manufacturer#5 almond antique sky peru orange 2 [{"x":1018.1,"y":1.0},{"x":1464.48,"y":1.0},{"x":1611.66,"y":1.0},{"x":1788.73,"y":1.0},{"x":1789.69,"y":1.0}] 78486.0 3
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 [{"x":1018.1,"y":1.0},{"x":1464.48,"y":1.0},{"x":1611.66,"y":1.0},{"x":1788.73,"y":1.0}] 60577.5 4
+Manufacturer#5 almond azure blanched chiffon midnight 23 [{"x":1018.1,"y":1.0},{"x":1464.48,"y":1.0},{"x":1788.73,"y":1.0}] 78486.0 5
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 24. testLateralViews-0-dea06072f0a64fe4537fae854944ed5a b/sql/hive/src/test/resources/golden/windowing.q -- 24. testLateralViews-0-dea06072f0a64fe4537fae854944ed5a
new file mode 100644
index 0000000000000000000000000000000000000000..dc83c9fffe9323b69d5e0c03bc59113687fcf71e
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 24. testLateralViews-0-dea06072f0a64fe4537fae854944ed5a
@@ -0,0 +1,78 @@
+Manufacturer#1 almond antique burnished rose metallic 1 2 2
+Manufacturer#1 almond antique burnished rose metallic 1 2 4
+Manufacturer#1 almond antique burnished rose metallic 2 2 6
+Manufacturer#1 almond antique burnished rose metallic 2 2 6
+Manufacturer#1 almond antique burnished rose metallic 3 2 6
+Manufacturer#1 almond antique burnished rose metallic 3 2 6
+Manufacturer#1 almond antique salmon chartreuse burlywood 1 6 10
+Manufacturer#1 almond antique salmon chartreuse burlywood 2 6 14
+Manufacturer#1 almond antique salmon chartreuse burlywood 3 6 18
+Manufacturer#1 almond aquamarine burnished black steel 1 28 40
+Manufacturer#1 almond aquamarine burnished black steel 2 28 62
+Manufacturer#1 almond aquamarine burnished black steel 3 28 84
+Manufacturer#1 almond antique chartreuse lavender yellow 1 34 90
+Manufacturer#1 almond antique chartreuse lavender yellow 2 34 96
+Manufacturer#1 almond antique chartreuse lavender yellow 3 34 102
+Manufacturer#1 almond aquamarine pink moccasin thistle 1 42 110
+Manufacturer#1 almond aquamarine pink moccasin thistle 2 42 118
+Manufacturer#1 almond aquamarine pink moccasin thistle 3 42 126
+Manufacturer#2 almond aquamarine midnight light salmon 1 2 2
+Manufacturer#2 almond aquamarine midnight light salmon 2 2 4
+Manufacturer#2 almond aquamarine midnight light salmon 3 2 6
+Manufacturer#2 almond antique violet chocolate turquoise 1 14 18
+Manufacturer#2 almond antique violet chocolate turquoise 2 14 30
+Manufacturer#2 almond antique violet chocolate turquoise 3 14 42
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 1 18 46
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 2 18 50
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 3 18 54
+Manufacturer#2 almond aquamarine rose maroon antique 1 25 61
+Manufacturer#2 almond aquamarine rose maroon antique 2 25 68
+Manufacturer#2 almond aquamarine rose maroon antique 3 25 75
+Manufacturer#2 almond antique violet turquoise frosted 1 40 90
+Manufacturer#2 almond antique violet turquoise frosted 2 40 105
+Manufacturer#2 almond antique violet turquoise frosted 3 40 120
+Manufacturer#3 almond antique misty red olive 1 1 1
+Manufacturer#3 almond antique misty red olive 2 1 2
+Manufacturer#3 almond antique misty red olive 3 1 3
+Manufacturer#3 almond antique forest lavender goldenrod 1 14 16
+Manufacturer#3 almond antique forest lavender goldenrod 2 14 29
+Manufacturer#3 almond antique forest lavender goldenrod 3 14 42
+Manufacturer#3 almond antique chartreuse khaki white 1 17 45
+Manufacturer#3 almond antique chartreuse khaki white 2 17 48
+Manufacturer#3 almond antique chartreuse khaki white 3 17 51
+Manufacturer#3 almond antique metallic orange dim 1 19 53
+Manufacturer#3 almond antique metallic orange dim 2 19 55
+Manufacturer#3 almond antique metallic orange dim 3 19 57
+Manufacturer#3 almond antique olive coral navajo 1 45 83
+Manufacturer#3 almond antique olive coral navajo 2 45 109
+Manufacturer#3 almond antique olive coral navajo 3 45 135
+Manufacturer#4 almond aquamarine yellow dodger mint 1 7 7
+Manufacturer#4 almond aquamarine yellow dodger mint 2 7 14
+Manufacturer#4 almond aquamarine yellow dodger mint 3 7 21
+Manufacturer#4 almond antique gainsboro frosted violet 1 10 24
+Manufacturer#4 almond antique gainsboro frosted violet 2 10 27
+Manufacturer#4 almond antique gainsboro frosted violet 3 10 30
+Manufacturer#4 almond azure aquamarine papaya violet 1 12 32
+Manufacturer#4 almond azure aquamarine papaya violet 2 12 34
+Manufacturer#4 almond azure aquamarine papaya violet 3 12 36
+Manufacturer#4 almond aquamarine floral ivory bisque 1 27 51
+Manufacturer#4 almond aquamarine floral ivory bisque 2 27 66
+Manufacturer#4 almond aquamarine floral ivory bisque 3 27 81
+Manufacturer#4 almond antique violet mint lemon 1 39 93
+Manufacturer#4 almond antique violet mint lemon 2 39 105
+Manufacturer#4 almond antique violet mint lemon 3 39 117
+Manufacturer#5 almond antique sky peru orange 1 2 2
+Manufacturer#5 almond antique sky peru orange 2 2 4
+Manufacturer#5 almond antique sky peru orange 3 2 6
+Manufacturer#5 almond antique medium spring khaki 1 6 10
+Manufacturer#5 almond antique medium spring khaki 2 6 14
+Manufacturer#5 almond antique medium spring khaki 3 6 18
+Manufacturer#5 almond azure blanched chiffon midnight 1 23 35
+Manufacturer#5 almond azure blanched chiffon midnight 2 23 52
+Manufacturer#5 almond azure blanched chiffon midnight 3 23 69
+Manufacturer#5 almond antique blue firebrick mint 1 31 77
+Manufacturer#5 almond antique blue firebrick mint 2 31 85
+Manufacturer#5 almond antique blue firebrick mint 3 31 93
+Manufacturer#5 almond aquamarine dodger light gainsboro 1 46 108
+Manufacturer#5 almond aquamarine dodger light gainsboro 2 46 123
+Manufacturer#5 almond aquamarine dodger light gainsboro 3 46 138
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 26. testGroupByHavingWithSWQAndAlias-0-b996a664b06e5741c08079d5c38241bc b/sql/hive/src/test/resources/golden/windowing.q -- 26. testGroupByHavingWithSWQAndAlias-0-b996a664b06e5741c08079d5c38241bc
new file mode 100644
index 0000000000000000000000000000000000000000..2c30e652aa26d6baac06f06ebab3fd7ac12f010e
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 26. testGroupByHavingWithSWQAndAlias-0-b996a664b06e5741c08079d5c38241bc
@@ -0,0 +1,25 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1173.15 1 1 2 0
+Manufacturer#1 almond antique chartreuse lavender yellow 34 1753.76 2 2 34 32
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 1602.59 3 3 6 -28
+Manufacturer#1 almond aquamarine burnished black steel 28 1414.42 4 4 28 22
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 1632.66 5 5 42 14
+Manufacturer#2 almond antique violet chocolate turquoise 14 1690.68 1 1 14 0
+Manufacturer#2 almond antique violet turquoise frosted 40 1800.7 2 2 40 26
+Manufacturer#2 almond aquamarine midnight light salmon 2 2031.98 3 3 2 -38
+Manufacturer#2 almond aquamarine rose maroon antique 25 1698.66 4 4 25 23
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 1701.6 5 5 18 -7
+Manufacturer#3 almond antique chartreuse khaki white 17 1671.68 1 1 17 0
+Manufacturer#3 almond antique forest lavender goldenrod 14 1190.27 2 2 14 -3
+Manufacturer#3 almond antique metallic orange dim 19 1410.39 3 3 19 5
+Manufacturer#3 almond antique misty red olive 1 1922.98 4 4 1 -18
+Manufacturer#3 almond antique olive coral navajo 45 1337.29 5 5 45 44
+Manufacturer#4 almond antique gainsboro frosted violet 10 1620.67 1 1 10 0
+Manufacturer#4 almond antique violet mint lemon 39 1375.42 2 2 39 29
+Manufacturer#4 almond aquamarine floral ivory bisque 27 1206.26 3 3 27 -12
+Manufacturer#4 almond aquamarine yellow dodger mint 7 1844.92 4 4 7 -20
+Manufacturer#4 almond azure aquamarine papaya violet 12 1290.35 5 5 12 5
+Manufacturer#5 almond antique blue firebrick mint 31 1789.69 1 1 31 0
+Manufacturer#5 almond antique medium spring khaki 6 1611.66 2 2 6 -25
+Manufacturer#5 almond antique sky peru orange 2 1788.73 3 3 2 -4
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 1018.1 4 4 46 44
+Manufacturer#5 almond azure blanched chiffon midnight 23 1464.48 5 5 23 -23
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 27. testMultipleRangeWindows-0-227e080e337d734dd88ff814b3b412e4 b/sql/hive/src/test/resources/golden/windowing.q -- 27. testMultipleRangeWindows-0-227e080e337d734dd88ff814b3b412e4
new file mode 100644
index 0000000000000000000000000000000000000000..b2a91ba727a726f08ba54c463613def82663fa9a
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 27. testMultipleRangeWindows-0-227e080e337d734dd88ff814b3b412e4
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 4 10
+Manufacturer#1 almond antique burnished rose metallic 2 4 10
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 10 6
+Manufacturer#1 almond aquamarine burnished black steel 28 28 62
+Manufacturer#1 almond antique chartreuse lavender yellow 34 62 76
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 76 42
+Manufacturer#2 almond aquamarine midnight light salmon 2 2 2
+Manufacturer#2 almond antique violet chocolate turquoise 14 14 32
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 32 43
+Manufacturer#2 almond aquamarine rose maroon antique 25 43 25
+Manufacturer#2 almond antique violet turquoise frosted 40 40 40
+Manufacturer#3 almond antique misty red olive 1 1 1
+Manufacturer#3 almond antique forest lavender goldenrod 14 14 50
+Manufacturer#3 almond antique chartreuse khaki white 17 31 36
+Manufacturer#3 almond antique metallic orange dim 19 50 19
+Manufacturer#3 almond antique olive coral navajo 45 45 45
+Manufacturer#4 almond aquamarine yellow dodger mint 7 7 29
+Manufacturer#4 almond antique gainsboro frosted violet 10 17 22
+Manufacturer#4 almond azure aquamarine papaya violet 12 29 12
+Manufacturer#4 almond aquamarine floral ivory bisque 27 27 27
+Manufacturer#4 almond antique violet mint lemon 39 39 39
+Manufacturer#5 almond antique sky peru orange 2 2 8
+Manufacturer#5 almond antique medium spring khaki 6 8 6
+Manufacturer#5 almond azure blanched chiffon midnight 23 23 54
+Manufacturer#5 almond antique blue firebrick mint 31 54 31
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 46 46
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 28. testPartOrderInUDAFInvoke-0-25912ae7d18c91cc09e17e57968fb5db b/sql/hive/src/test/resources/golden/windowing.q -- 28. testPartOrderInUDAFInvoke-0-25912ae7d18c91cc09e17e57968fb5db
new file mode 100644
index 0000000000000000000000000000000000000000..5bcb0fa941d65a0b26da9af9628d211eeecf5749
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 28. testPartOrderInUDAFInvoke-0-25912ae7d18c91cc09e17e57968fb5db
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 38
+Manufacturer#1 almond antique burnished rose metallic 2 44
+Manufacturer#1 almond antique chartreuse lavender yellow 34 72
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 112
+Manufacturer#1 almond aquamarine burnished black steel 28 110
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 76
+Manufacturer#2 almond antique violet chocolate turquoise 14 56
+Manufacturer#2 almond antique violet turquoise frosted 40 81
+Manufacturer#2 almond aquamarine midnight light salmon 2 99
+Manufacturer#2 almond aquamarine rose maroon antique 25 85
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 45
+Manufacturer#3 almond antique chartreuse khaki white 17 50
+Manufacturer#3 almond antique forest lavender goldenrod 14 51
+Manufacturer#3 almond antique metallic orange dim 19 96
+Manufacturer#3 almond antique misty red olive 1 79
+Manufacturer#3 almond antique olive coral navajo 45 65
+Manufacturer#4 almond antique gainsboro frosted violet 10 76
+Manufacturer#4 almond antique violet mint lemon 39 83
+Manufacturer#4 almond aquamarine floral ivory bisque 27 95
+Manufacturer#4 almond aquamarine yellow dodger mint 7 85
+Manufacturer#4 almond azure aquamarine papaya violet 12 46
+Manufacturer#5 almond antique blue firebrick mint 31 39
+Manufacturer#5 almond antique medium spring khaki 6 85
+Manufacturer#5 almond antique sky peru orange 2 108
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 77
+Manufacturer#5 almond azure blanched chiffon midnight 23 71
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 29. testPartOrderInWdwDef-0-88945892370ccbc1125a927a3d55342a b/sql/hive/src/test/resources/golden/windowing.q -- 29. testPartOrderInWdwDef-0-88945892370ccbc1125a927a3d55342a
new file mode 100644
index 0000000000000000000000000000000000000000..5bcb0fa941d65a0b26da9af9628d211eeecf5749
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 29. testPartOrderInWdwDef-0-88945892370ccbc1125a927a3d55342a
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 38
+Manufacturer#1 almond antique burnished rose metallic 2 44
+Manufacturer#1 almond antique chartreuse lavender yellow 34 72
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 112
+Manufacturer#1 almond aquamarine burnished black steel 28 110
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 76
+Manufacturer#2 almond antique violet chocolate turquoise 14 56
+Manufacturer#2 almond antique violet turquoise frosted 40 81
+Manufacturer#2 almond aquamarine midnight light salmon 2 99
+Manufacturer#2 almond aquamarine rose maroon antique 25 85
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 45
+Manufacturer#3 almond antique chartreuse khaki white 17 50
+Manufacturer#3 almond antique forest lavender goldenrod 14 51
+Manufacturer#3 almond antique metallic orange dim 19 96
+Manufacturer#3 almond antique misty red olive 1 79
+Manufacturer#3 almond antique olive coral navajo 45 65
+Manufacturer#4 almond antique gainsboro frosted violet 10 76
+Manufacturer#4 almond antique violet mint lemon 39 83
+Manufacturer#4 almond aquamarine floral ivory bisque 27 95
+Manufacturer#4 almond aquamarine yellow dodger mint 7 85
+Manufacturer#4 almond azure aquamarine papaya violet 12 46
+Manufacturer#5 almond antique blue firebrick mint 31 39
+Manufacturer#5 almond antique medium spring khaki 6 85
+Manufacturer#5 almond antique sky peru orange 2 108
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 77
+Manufacturer#5 almond azure blanched chiffon midnight 23 71
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 3. testGroupByHavingWithSWQ-0-a5a5339330a6a6660d32ccb0cc5d7100 b/sql/hive/src/test/resources/golden/windowing.q -- 3. testGroupByHavingWithSWQ-0-a5a5339330a6a6660d32ccb0cc5d7100
new file mode 100644
index 0000000000000000000000000000000000000000..2c30e652aa26d6baac06f06ebab3fd7ac12f010e
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 3. testGroupByHavingWithSWQ-0-a5a5339330a6a6660d32ccb0cc5d7100
@@ -0,0 +1,25 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1173.15 1 1 2 0
+Manufacturer#1 almond antique chartreuse lavender yellow 34 1753.76 2 2 34 32
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 1602.59 3 3 6 -28
+Manufacturer#1 almond aquamarine burnished black steel 28 1414.42 4 4 28 22
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 1632.66 5 5 42 14
+Manufacturer#2 almond antique violet chocolate turquoise 14 1690.68 1 1 14 0
+Manufacturer#2 almond antique violet turquoise frosted 40 1800.7 2 2 40 26
+Manufacturer#2 almond aquamarine midnight light salmon 2 2031.98 3 3 2 -38
+Manufacturer#2 almond aquamarine rose maroon antique 25 1698.66 4 4 25 23
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 1701.6 5 5 18 -7
+Manufacturer#3 almond antique chartreuse khaki white 17 1671.68 1 1 17 0
+Manufacturer#3 almond antique forest lavender goldenrod 14 1190.27 2 2 14 -3
+Manufacturer#3 almond antique metallic orange dim 19 1410.39 3 3 19 5
+Manufacturer#3 almond antique misty red olive 1 1922.98 4 4 1 -18
+Manufacturer#3 almond antique olive coral navajo 45 1337.29 5 5 45 44
+Manufacturer#4 almond antique gainsboro frosted violet 10 1620.67 1 1 10 0
+Manufacturer#4 almond antique violet mint lemon 39 1375.42 2 2 39 29
+Manufacturer#4 almond aquamarine floral ivory bisque 27 1206.26 3 3 27 -12
+Manufacturer#4 almond aquamarine yellow dodger mint 7 1844.92 4 4 7 -20
+Manufacturer#4 almond azure aquamarine papaya violet 12 1290.35 5 5 12 5
+Manufacturer#5 almond antique blue firebrick mint 31 1789.69 1 1 31 0
+Manufacturer#5 almond antique medium spring khaki 6 1611.66 2 2 6 -25
+Manufacturer#5 almond antique sky peru orange 2 1788.73 3 3 2 -4
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 1018.1 4 4 46 44
+Manufacturer#5 almond azure blanched chiffon midnight 23 1464.48 5 5 23 -23
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 30. testDefaultPartitioningSpecRules-0-fa80b09c99e3c1487de48ea71a88dada b/sql/hive/src/test/resources/golden/windowing.q -- 30. testDefaultPartitioningSpecRules-0-fa80b09c99e3c1487de48ea71a88dada
new file mode 100644
index 0000000000000000000000000000000000000000..698a44349d2a65cef205e553e199ae310995b0ea
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 30. testDefaultPartitioningSpecRules-0-fa80b09c99e3c1487de48ea71a88dada
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 38 4
+Manufacturer#1 almond antique burnished rose metallic 2 44 4
+Manufacturer#1 almond antique chartreuse lavender yellow 34 72 38
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 112 44
+Manufacturer#1 almond aquamarine burnished black steel 28 110 72
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 76 114
+Manufacturer#2 almond antique violet chocolate turquoise 14 56 14
+Manufacturer#2 almond antique violet turquoise frosted 40 81 54
+Manufacturer#2 almond aquamarine midnight light salmon 2 99 56
+Manufacturer#2 almond aquamarine rose maroon antique 25 85 81
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 45 99
+Manufacturer#3 almond antique chartreuse khaki white 17 50 17
+Manufacturer#3 almond antique forest lavender goldenrod 14 51 31
+Manufacturer#3 almond antique metallic orange dim 19 96 50
+Manufacturer#3 almond antique misty red olive 1 79 51
+Manufacturer#3 almond antique olive coral navajo 45 65 96
+Manufacturer#4 almond antique gainsboro frosted violet 10 76 10
+Manufacturer#4 almond antique violet mint lemon 39 83 49
+Manufacturer#4 almond aquamarine floral ivory bisque 27 95 76
+Manufacturer#4 almond aquamarine yellow dodger mint 7 85 83
+Manufacturer#4 almond azure aquamarine papaya violet 12 46 95
+Manufacturer#5 almond antique blue firebrick mint 31 39 31
+Manufacturer#5 almond antique medium spring khaki 6 85 37
+Manufacturer#5 almond antique sky peru orange 2 108 39
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 77 85
+Manufacturer#5 almond azure blanched chiffon midnight 23 71 108
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 36. testRankWithPartitioning-0-45ccbaf0ee083858f7661c66b11d4768 b/sql/hive/src/test/resources/golden/windowing.q -- 36. testRankWithPartitioning-0-45ccbaf0ee083858f7661c66b11d4768
new file mode 100644
index 0000000000000000000000000000000000000000..e35257d98382ee79f5a22375f8ee3be3266144e9
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 36. testRankWithPartitioning-0-45ccbaf0ee083858f7661c66b11d4768
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1
+Manufacturer#1 almond antique burnished rose metallic 2 1
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4
+Manufacturer#1 almond aquamarine burnished black steel 28 5
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 6
+Manufacturer#2 almond antique violet chocolate turquoise 14 1
+Manufacturer#2 almond antique violet turquoise frosted 40 2
+Manufacturer#2 almond aquamarine midnight light salmon 2 3
+Manufacturer#2 almond aquamarine rose maroon antique 25 4
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5
+Manufacturer#3 almond antique chartreuse khaki white 17 1
+Manufacturer#3 almond antique forest lavender goldenrod 14 2
+Manufacturer#3 almond antique metallic orange dim 19 3
+Manufacturer#3 almond antique misty red olive 1 4
+Manufacturer#3 almond antique olive coral navajo 45 5
+Manufacturer#4 almond antique gainsboro frosted violet 10 1
+Manufacturer#4 almond antique violet mint lemon 39 2
+Manufacturer#4 almond aquamarine floral ivory bisque 27 3
+Manufacturer#4 almond aquamarine yellow dodger mint 7 4
+Manufacturer#4 almond azure aquamarine papaya violet 12 5
+Manufacturer#5 almond antique blue firebrick mint 31 1
+Manufacturer#5 almond antique medium spring khaki 6 2
+Manufacturer#5 almond antique sky peru orange 2 3
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 4
+Manufacturer#5 almond azure blanched chiffon midnight 23 5
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 37. testPartitioningVariousForms-0-3436e50214f9afdec84334e10faa931a b/sql/hive/src/test/resources/golden/windowing.q -- 37. testPartitioningVariousForms-0-3436e50214f9afdec84334e10faa931a
new file mode 100644
index 0000000000000000000000000000000000000000..9c0ca6c7a00ba7e54b8f9a47d3fd332950d2bac1
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 37. testPartitioningVariousForms-0-3436e50214f9afdec84334e10faa931a
@@ -0,0 +1,26 @@
+Manufacturer#1 8749.73 1173.15 1753.76 1458.29 6
+Manufacturer#1 8749.73 1173.15 1753.76 1458.29 6
+Manufacturer#1 8749.73 1173.15 1753.76 1458.29 6
+Manufacturer#1 8749.73 1173.15 1753.76 1458.29 6
+Manufacturer#1 8749.73 1173.15 1753.76 1458.29 6
+Manufacturer#1 8749.73 1173.15 1753.76 1458.29 6
+Manufacturer#2 8923.62 1690.68 2031.98 1784.72 5
+Manufacturer#2 8923.62 1690.68 2031.98 1784.72 5
+Manufacturer#2 8923.62 1690.68 2031.98 1784.72 5
+Manufacturer#2 8923.62 1690.68 2031.98 1784.72 5
+Manufacturer#2 8923.62 1690.68 2031.98 1784.72 5
+Manufacturer#3 7532.61 1190.27 1922.98 1506.52 5
+Manufacturer#3 7532.61 1190.27 1922.98 1506.52 5
+Manufacturer#3 7532.61 1190.27 1922.98 1506.52 5
+Manufacturer#3 7532.61 1190.27 1922.98 1506.52 5
+Manufacturer#3 7532.61 1190.27 1922.98 1506.52 5
+Manufacturer#4 7337.62 1206.26 1844.92 1467.52 5
+Manufacturer#4 7337.62 1206.26 1844.92 1467.52 5
+Manufacturer#4 7337.62 1206.26 1844.92 1467.52 5
+Manufacturer#4 7337.62 1206.26 1844.92 1467.52 5
+Manufacturer#4 7337.62 1206.26 1844.92 1467.52 5
+Manufacturer#5 7672.66 1018.1 1789.69 1534.53 5
+Manufacturer#5 7672.66 1018.1 1789.69 1534.53 5
+Manufacturer#5 7672.66 1018.1 1789.69 1534.53 5
+Manufacturer#5 7672.66 1018.1 1789.69 1534.53 5
+Manufacturer#5 7672.66 1018.1 1789.69 1534.53 5
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 38. testPartitioningVariousForms2-0-cba9d84a6b1bb5e36595338d4602377e b/sql/hive/src/test/resources/golden/windowing.q -- 38. testPartitioningVariousForms2-0-cba9d84a6b1bb5e36595338d4602377e
new file mode 100644
index 0000000000000000000000000000000000000000..fc27df2f2b648574739571f20a558eb06d6d876f
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 38. testPartitioningVariousForms2-0-cba9d84a6b1bb5e36595338d4602377e
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1173.15 1173.15 1173.15
+Manufacturer#1 almond antique burnished rose metallic 2 2346.3 1173.15 1173.15
+Manufacturer#1 almond antique chartreuse lavender yellow 34 1753.76 1753.76 1753.76
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 1602.59 1602.59 1602.59
+Manufacturer#1 almond aquamarine burnished black steel 28 1414.42 1414.42 1414.42
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 1632.66 1632.66 1632.66
+Manufacturer#2 almond antique violet chocolate turquoise 14 1690.68 1690.68 1690.68
+Manufacturer#2 almond antique violet turquoise frosted 40 1800.7 1800.7 1800.7
+Manufacturer#2 almond aquamarine midnight light salmon 2 2031.98 2031.98 2031.98
+Manufacturer#2 almond aquamarine rose maroon antique 25 1698.66 1698.66 1698.66
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 1701.6 1701.6 1701.6
+Manufacturer#3 almond antique chartreuse khaki white 17 1671.68 1671.68 1671.68
+Manufacturer#3 almond antique forest lavender goldenrod 14 1190.27 1190.27 1190.27
+Manufacturer#3 almond antique metallic orange dim 19 1410.39 1410.39 1410.39
+Manufacturer#3 almond antique misty red olive 1 1922.98 1922.98 1922.98
+Manufacturer#3 almond antique olive coral navajo 45 1337.29 1337.29 1337.29
+Manufacturer#4 almond antique gainsboro frosted violet 10 1620.67 1620.67 1620.67
+Manufacturer#4 almond antique violet mint lemon 39 1375.42 1375.42 1375.42
+Manufacturer#4 almond aquamarine floral ivory bisque 27 1206.26 1206.26 1206.26
+Manufacturer#4 almond aquamarine yellow dodger mint 7 1844.92 1844.92 1844.92
+Manufacturer#4 almond azure aquamarine papaya violet 12 1290.35 1290.35 1290.35
+Manufacturer#5 almond antique blue firebrick mint 31 1789.69 1789.69 1789.69
+Manufacturer#5 almond antique medium spring khaki 6 1611.66 1611.66 1611.66
+Manufacturer#5 almond antique sky peru orange 2 1788.73 1788.73 1788.73
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 1018.1 1018.1 1018.1
+Manufacturer#5 almond azure blanched chiffon midnight 23 1464.48 1464.48 1464.48
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 39. testUDFOnOrderCols-0-7647562850dd367ef1e6c63117805423 b/sql/hive/src/test/resources/golden/windowing.q -- 39. testUDFOnOrderCols-0-7647562850dd367ef1e6c63117805423
new file mode 100644
index 0000000000000000000000000000000000000000..e5a541f56f6f33930707dc391344b867357f1cb7
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 39. testUDFOnOrderCols-0-7647562850dd367ef1e6c63117805423
@@ -0,0 +1,26 @@
+Manufacturer#1 LARGE BRUSHED STEEL ARGE BRUSHED STEEL 1
+Manufacturer#1 LARGE BURNISHED STEEL ARGE BURNISHED STEEL 2
+Manufacturer#1 PROMO BURNISHED NICKEL ROMO BURNISHED NICKEL 3
+Manufacturer#1 PROMO PLATED TIN ROMO PLATED TIN 4
+Manufacturer#1 PROMO PLATED TIN ROMO PLATED TIN 4
+Manufacturer#1 STANDARD ANODIZED STEEL TANDARD ANODIZED STEEL 6
+Manufacturer#2 ECONOMY POLISHED STEEL CONOMY POLISHED STEEL 1
+Manufacturer#2 MEDIUM ANODIZED COPPER EDIUM ANODIZED COPPER 2
+Manufacturer#2 MEDIUM BURNISHED COPPER EDIUM BURNISHED COPPER 3
+Manufacturer#2 SMALL POLISHED NICKEL MALL POLISHED NICKEL 4
+Manufacturer#2 STANDARD PLATED TIN TANDARD PLATED TIN 5
+Manufacturer#3 ECONOMY PLATED COPPER CONOMY PLATED COPPER 1
+Manufacturer#3 MEDIUM BURNISHED BRASS EDIUM BURNISHED BRASS 2
+Manufacturer#3 MEDIUM BURNISHED TIN EDIUM BURNISHED TIN 3
+Manufacturer#3 PROMO ANODIZED TIN ROMO ANODIZED TIN 4
+Manufacturer#3 STANDARD POLISHED STEEL TANDARD POLISHED STEEL 5
+Manufacturer#4 ECONOMY BRUSHED COPPER CONOMY BRUSHED COPPER 1
+Manufacturer#4 SMALL BRUSHED BRASS MALL BRUSHED BRASS 2
+Manufacturer#4 SMALL PLATED STEEL MALL PLATED STEEL 3
+Manufacturer#4 PROMO POLISHED STEEL ROMO POLISHED STEEL 4
+Manufacturer#4 STANDARD ANODIZED TIN TANDARD ANODIZED TIN 5
+Manufacturer#5 LARGE BRUSHED BRASS ARGE BRUSHED BRASS 1
+Manufacturer#5 ECONOMY BURNISHED STEEL CONOMY BURNISHED STEEL 2
+Manufacturer#5 MEDIUM BURNISHED TIN EDIUM BURNISHED TIN 3
+Manufacturer#5 SMALL PLATED BRASS MALL PLATED BRASS 4
+Manufacturer#5 STANDARD BURNISHED TIN TANDARD BURNISHED TIN 5
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 4. testCount-0-e6e97e884327df86f16b870527ec026c b/sql/hive/src/test/resources/golden/windowing.q -- 4. testCount-0-e6e97e884327df86f16b870527ec026c
new file mode 100644
index 0000000000000000000000000000000000000000..bf8e620a304afd4400001a8a0ae7c0b426440224
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 4. testCount-0-e6e97e884327df86f16b870527ec026c
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2
+Manufacturer#1 almond antique burnished rose metallic 2
+Manufacturer#1 almond antique chartreuse lavender yellow 3
+Manufacturer#1 almond antique salmon chartreuse burlywood 4
+Manufacturer#1 almond aquamarine burnished black steel 5
+Manufacturer#1 almond aquamarine pink moccasin thistle 6
+Manufacturer#2 almond antique violet chocolate turquoise 1
+Manufacturer#2 almond antique violet turquoise frosted 2
+Manufacturer#2 almond aquamarine midnight light salmon 3
+Manufacturer#2 almond aquamarine rose maroon antique 4
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 5
+Manufacturer#3 almond antique chartreuse khaki white 1
+Manufacturer#3 almond antique forest lavender goldenrod 2
+Manufacturer#3 almond antique metallic orange dim 3
+Manufacturer#3 almond antique misty red olive 4
+Manufacturer#3 almond antique olive coral navajo 5
+Manufacturer#4 almond antique gainsboro frosted violet 1
+Manufacturer#4 almond antique violet mint lemon 2
+Manufacturer#4 almond aquamarine floral ivory bisque 3
+Manufacturer#4 almond aquamarine yellow dodger mint 4
+Manufacturer#4 almond azure aquamarine papaya violet 5
+Manufacturer#5 almond antique blue firebrick mint 1
+Manufacturer#5 almond antique medium spring khaki 2
+Manufacturer#5 almond antique sky peru orange 3
+Manufacturer#5 almond aquamarine dodger light gainsboro 4
+Manufacturer#5 almond azure blanched chiffon midnight 5
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 40. testNoBetweenForRows-0-99007f45b6406869e048b0e4eb9213f1 b/sql/hive/src/test/resources/golden/windowing.q -- 40. testNoBetweenForRows-0-99007f45b6406869e048b0e4eb9213f1
new file mode 100644
index 0000000000000000000000000000000000000000..1e29df62901d0eedae90d06ee520317d100f7948
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 40. testNoBetweenForRows-0-99007f45b6406869e048b0e4eb9213f1
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1173.15
+Manufacturer#1 almond antique burnished rose metallic 2 2346.3
+Manufacturer#1 almond antique chartreuse lavender yellow 34 4100.06
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 5702.650000000001
+Manufacturer#1 almond aquamarine burnished black steel 28 7117.070000000001
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 8749.730000000001
+Manufacturer#2 almond antique violet chocolate turquoise 14 1690.68
+Manufacturer#2 almond antique violet turquoise frosted 40 3491.38
+Manufacturer#2 almond aquamarine midnight light salmon 2 5523.360000000001
+Manufacturer#2 almond aquamarine rose maroon antique 25 7222.02
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 8923.62
+Manufacturer#3 almond antique chartreuse khaki white 17 1671.68
+Manufacturer#3 almond antique forest lavender goldenrod 14 2861.95
+Manufacturer#3 almond antique metallic orange dim 19 4272.34
+Manufacturer#3 almond antique misty red olive 1 6195.32
+Manufacturer#3 almond antique olive coral navajo 45 7532.61
+Manufacturer#4 almond antique gainsboro frosted violet 10 1620.67
+Manufacturer#4 almond antique violet mint lemon 39 2996.09
+Manufacturer#4 almond aquamarine floral ivory bisque 27 4202.35
+Manufacturer#4 almond aquamarine yellow dodger mint 7 6047.27
+Manufacturer#4 almond azure aquamarine papaya violet 12 7337.620000000001
+Manufacturer#5 almond antique blue firebrick mint 31 1789.69
+Manufacturer#5 almond antique medium spring khaki 6 3401.3500000000004
+Manufacturer#5 almond antique sky peru orange 2 5190.08
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 6208.18
+Manufacturer#5 almond azure blanched chiffon midnight 23 7672.66
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 41. testNoBetweenForRange-0-d81a591e90950de291d2f133793e9283 b/sql/hive/src/test/resources/golden/windowing.q -- 41. testNoBetweenForRange-0-d81a591e90950de291d2f133793e9283
new file mode 100644
index 0000000000000000000000000000000000000000..a620479fe406408a31b35c5b759c58b5d428c984
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 41. testNoBetweenForRange-0-d81a591e90950de291d2f133793e9283
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 2346.3
+Manufacturer#1 almond antique burnished rose metallic 2 2346.3
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 3948.8900000000003
+Manufacturer#1 almond aquamarine burnished black steel 28 5363.31
+Manufacturer#1 almond antique chartreuse lavender yellow 34 7117.070000000001
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 8749.730000000001
+Manufacturer#2 almond aquamarine midnight light salmon 2 2031.98
+Manufacturer#2 almond antique violet chocolate turquoise 14 3722.66
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5424.26
+Manufacturer#2 almond aquamarine rose maroon antique 25 7122.92
+Manufacturer#2 almond antique violet turquoise frosted 40 8923.62
+Manufacturer#3 almond antique misty red olive 1 1922.98
+Manufacturer#3 almond antique forest lavender goldenrod 14 3113.25
+Manufacturer#3 almond antique chartreuse khaki white 17 4784.93
+Manufacturer#3 almond antique metallic orange dim 19 6195.320000000001
+Manufacturer#3 almond antique olive coral navajo 45 7532.610000000001
+Manufacturer#4 almond aquamarine yellow dodger mint 7 1844.92
+Manufacturer#4 almond antique gainsboro frosted violet 10 3465.59
+Manufacturer#4 almond azure aquamarine papaya violet 12 4755.9400000000005
+Manufacturer#4 almond aquamarine floral ivory bisque 27 5962.200000000001
+Manufacturer#4 almond antique violet mint lemon 39 7337.620000000001
+Manufacturer#5 almond antique sky peru orange 2 1788.73
+Manufacturer#5 almond antique medium spring khaki 6 3400.3900000000003
+Manufacturer#5 almond azure blanched chiffon midnight 23 4864.870000000001
+Manufacturer#5 almond antique blue firebrick mint 31 6654.560000000001
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 7672.660000000002
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 42. testUnboundedFollowingForRows-0-fb8648e82e4dd56d6bdcfd739dd1edf0 b/sql/hive/src/test/resources/golden/windowing.q -- 42. testUnboundedFollowingForRows-0-fb8648e82e4dd56d6bdcfd739dd1edf0
new file mode 100644
index 0000000000000000000000000000000000000000..74147d2571a1556eb4116a83dad7b9eee6156f7c
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 42. testUnboundedFollowingForRows-0-fb8648e82e4dd56d6bdcfd739dd1edf0
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 8749.730000000001
+Manufacturer#1 almond antique burnished rose metallic 2 7576.58
+Manufacturer#1 almond antique chartreuse lavender yellow 34 6403.43
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4649.67
+Manufacturer#1 almond aquamarine burnished black steel 28 3047.08
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 1632.66
+Manufacturer#2 almond antique violet chocolate turquoise 14 8923.62
+Manufacturer#2 almond antique violet turquoise frosted 40 7232.9400000000005
+Manufacturer#2 almond aquamarine midnight light salmon 2 5432.24
+Manufacturer#2 almond aquamarine rose maroon antique 25 3400.26
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 1701.6
+Manufacturer#3 almond antique chartreuse khaki white 17 7532.61
+Manufacturer#3 almond antique forest lavender goldenrod 14 5860.929999999999
+Manufacturer#3 almond antique metallic orange dim 19 4670.66
+Manufacturer#3 almond antique misty red olive 1 3260.27
+Manufacturer#3 almond antique olive coral navajo 45 1337.29
+Manufacturer#4 almond antique gainsboro frosted violet 10 7337.620000000001
+Manufacturer#4 almond antique violet mint lemon 39 5716.950000000001
+Manufacturer#4 almond aquamarine floral ivory bisque 27 4341.530000000001
+Manufacturer#4 almond aquamarine yellow dodger mint 7 3135.27
+Manufacturer#4 almond azure aquamarine papaya violet 12 1290.35
+Manufacturer#5 almond antique blue firebrick mint 31 7672.66
+Manufacturer#5 almond antique medium spring khaki 6 5882.970000000001
+Manufacturer#5 almond antique sky peru orange 2 4271.3099999999995
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 2482.58
+Manufacturer#5 almond azure blanched chiffon midnight 23 1464.48
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 43. testUnboundedFollowingForRange-0-3cd04e5f2398853c4850f4f86142bb39 b/sql/hive/src/test/resources/golden/windowing.q -- 43. testUnboundedFollowingForRange-0-3cd04e5f2398853c4850f4f86142bb39
new file mode 100644
index 0000000000000000000000000000000000000000..49d003b5de1391cdcd8d385d48fb3f5a78289328
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 43. testUnboundedFollowingForRange-0-3cd04e5f2398853c4850f4f86142bb39
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 8749.730000000001
+Manufacturer#1 almond antique burnished rose metallic 2 8749.730000000001
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 6403.43
+Manufacturer#1 almond aquamarine burnished black steel 28 4800.84
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3386.42
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 1632.66
+Manufacturer#2 almond aquamarine midnight light salmon 2 8923.62
+Manufacturer#2 almond antique violet chocolate turquoise 14 6891.639999999999
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5200.96
+Manufacturer#2 almond aquamarine rose maroon antique 25 3499.36
+Manufacturer#2 almond antique violet turquoise frosted 40 1800.7
+Manufacturer#3 almond antique misty red olive 1 7532.610000000001
+Manufacturer#3 almond antique forest lavender goldenrod 14 5609.63
+Manufacturer#3 almond antique chartreuse khaki white 17 4419.360000000001
+Manufacturer#3 almond antique metallic orange dim 19 2747.6800000000003
+Manufacturer#3 almond antique olive coral navajo 45 1337.29
+Manufacturer#4 almond aquamarine yellow dodger mint 7 7337.620000000001
+Manufacturer#4 almond antique gainsboro frosted violet 10 5492.7
+Manufacturer#4 almond azure aquamarine papaya violet 12 3872.0299999999997
+Manufacturer#4 almond aquamarine floral ivory bisque 27 2581.6800000000003
+Manufacturer#4 almond antique violet mint lemon 39 1375.42
+Manufacturer#5 almond antique sky peru orange 2 7672.660000000002
+Manufacturer#5 almond antique medium spring khaki 6 5883.93
+Manufacturer#5 almond azure blanched chiffon midnight 23 4272.27
+Manufacturer#5 almond antique blue firebrick mint 31 2807.79
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 1018.1
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 44. testOverNoPartitionSingleAggregate-0-cb3d2f8c1296044dc2658876bb6103ae b/sql/hive/src/test/resources/golden/windowing.q -- 44. testOverNoPartitionSingleAggregate-0-cb3d2f8c1296044dc2658876bb6103ae
new file mode 100644
index 0000000000000000000000000000000000000000..5982c9ee2a4d417ac18bedbc8cfdd38186351479
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 44. testOverNoPartitionSingleAggregate-0-cb3d2f8c1296044dc2658876bb6103ae
@@ -0,0 +1,26 @@
+almond antique blue firebrick mint 1789.69 1546.78
+almond antique burnished rose metallic 1173.15 1546.78
+almond antique burnished rose metallic 1173.15 1546.78
+almond antique chartreuse khaki white 1671.68 1546.78
+almond antique chartreuse lavender yellow 1753.76 1546.78
+almond antique forest lavender goldenrod 1190.27 1546.78
+almond antique gainsboro frosted violet 1620.67 1546.78
+almond antique medium spring khaki 1611.66 1546.78
+almond antique metallic orange dim 1410.39 1546.78
+almond antique misty red olive 1922.98 1546.78
+almond antique olive coral navajo 1337.29 1546.78
+almond antique salmon chartreuse burlywood 1602.59 1546.78
+almond antique sky peru orange 1788.73 1546.78
+almond antique violet chocolate turquoise 1690.68 1546.78
+almond antique violet mint lemon 1375.42 1546.78
+almond antique violet turquoise frosted 1800.7 1546.78
+almond aquamarine burnished black steel 1414.42 1546.78
+almond aquamarine dodger light gainsboro 1018.1 1546.78
+almond aquamarine floral ivory bisque 1206.26 1546.78
+almond aquamarine midnight light salmon 2031.98 1546.78
+almond aquamarine pink moccasin thistle 1632.66 1546.78
+almond aquamarine rose maroon antique 1698.66 1546.78
+almond aquamarine sandy cyan gainsboro 1701.6 1546.78
+almond aquamarine yellow dodger mint 1844.92 1546.78
+almond azure aquamarine papaya violet 1290.35 1546.78
+almond azure blanched chiffon midnight 1464.48 1546.78
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 5. testCountWithWindowingUDAF-0-3bde93728761b780a745c2ce0398aa0f b/sql/hive/src/test/resources/golden/windowing.q -- 5. testCountWithWindowingUDAF-0-3bde93728761b780a745c2ce0398aa0f
new file mode 100644
index 0000000000000000000000000000000000000000..00d41fc0bcd9ccf0b53c129f1cd8ed33555b14a5
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 5. testCountWithWindowingUDAF-0-3bde93728761b780a745c2ce0398aa0f
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 1 1 2 1173.15 1173.15 2 0
+Manufacturer#1 almond antique burnished rose metallic 1 1 2 1173.15 2346.3 2 0
+Manufacturer#1 almond antique chartreuse lavender yellow 3 2 3 1753.76 4100.06 34 32
+Manufacturer#1 almond antique salmon chartreuse burlywood 4 3 4 1602.59 5702.650000000001 6 -28
+Manufacturer#1 almond aquamarine burnished black steel 5 4 5 1414.42 7117.070000000001 28 22
+Manufacturer#1 almond aquamarine pink moccasin thistle 6 5 6 1632.66 8749.730000000001 42 14
+Manufacturer#2 almond antique violet chocolate turquoise 1 1 1 1690.68 1690.68 14 0
+Manufacturer#2 almond antique violet turquoise frosted 2 2 2 1800.7 3491.38 40 26
+Manufacturer#2 almond aquamarine midnight light salmon 3 3 3 2031.98 5523.360000000001 2 -38
+Manufacturer#2 almond aquamarine rose maroon antique 4 4 4 1698.66 7222.02 25 23
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 5 5 5 1701.6 8923.62 18 -7
+Manufacturer#3 almond antique chartreuse khaki white 1 1 1 1671.68 1671.68 17 0
+Manufacturer#3 almond antique forest lavender goldenrod 2 2 2 1190.27 2861.95 14 -3
+Manufacturer#3 almond antique metallic orange dim 3 3 3 1410.39 4272.34 19 5
+Manufacturer#3 almond antique misty red olive 4 4 4 1922.98 6195.32 1 -18
+Manufacturer#3 almond antique olive coral navajo 5 5 5 1337.29 7532.61 45 44
+Manufacturer#4 almond antique gainsboro frosted violet 1 1 1 1620.67 1620.67 10 0
+Manufacturer#4 almond antique violet mint lemon 2 2 2 1375.42 2996.09 39 29
+Manufacturer#4 almond aquamarine floral ivory bisque 3 3 3 1206.26 4202.35 27 -12
+Manufacturer#4 almond aquamarine yellow dodger mint 4 4 4 1844.92 6047.27 7 -20
+Manufacturer#4 almond azure aquamarine papaya violet 5 5 5 1290.35 7337.620000000001 12 5
+Manufacturer#5 almond antique blue firebrick mint 1 1 1 1789.69 1789.69 31 0
+Manufacturer#5 almond antique medium spring khaki 2 2 2 1611.66 3401.3500000000004 6 -25
+Manufacturer#5 almond antique sky peru orange 3 3 3 1788.73 5190.08 2 -4
+Manufacturer#5 almond aquamarine dodger light gainsboro 4 4 4 1018.1 6208.18 46 44
+Manufacturer#5 almond azure blanched chiffon midnight 5 5 5 1464.48 7672.66 23 -23
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 6. testCountInSubQ-0-73d5274a21d4f4fd51d2a0f1d98516ce b/sql/hive/src/test/resources/golden/windowing.q -- 6. testCountInSubQ-0-73d5274a21d4f4fd51d2a0f1d98516ce
new file mode 100644
index 0000000000000000000000000000000000000000..98c09e4fe15c38615859aae6989676a7e025ee92
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 6. testCountInSubQ-0-73d5274a21d4f4fd51d2a0f1d98516ce
@@ -0,0 +1,26 @@
+1 1 2 1173.15 0
+1 1 2 2346.3 0
+3 2 3 4100.06 32
+4 3 4 5702.650000000001 -28
+5 4 5 7117.070000000001 22
+6 5 6 8749.730000000001 14
+1 1 1 1690.68 0
+2 2 2 3491.38 26
+3 3 3 5523.360000000001 -38
+4 4 4 7222.02 23
+5 5 5 8923.62 -7
+1 1 1 1671.68 0
+2 2 2 2861.95 -3
+3 3 3 4272.34 5
+4 4 4 6195.32 -18
+5 5 5 7532.61 44
+1 1 1 1620.67 0
+2 2 2 2996.09 29
+3 3 3 4202.35 -12
+4 4 4 6047.27 -20
+5 5 5 7337.620000000001 5
+1 1 1 1789.69 0
+2 2 2 3401.3500000000004 -25
+3 3 3 5190.08 -4
+4 4 4 6208.18 44
+5 5 5 7672.66 -23
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 8. testMixedCaseAlias-0-4b1ad2515fb079012467e987f484a722 b/sql/hive/src/test/resources/golden/windowing.q -- 8. testMixedCaseAlias-0-4b1ad2515fb079012467e987f484a722
new file mode 100644
index 0000000000000000000000000000000000000000..e35257d98382ee79f5a22375f8ee3be3266144e9
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 8. testMixedCaseAlias-0-4b1ad2515fb079012467e987f484a722
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1
+Manufacturer#1 almond antique burnished rose metallic 2 1
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4
+Manufacturer#1 almond aquamarine burnished black steel 28 5
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 6
+Manufacturer#2 almond antique violet chocolate turquoise 14 1
+Manufacturer#2 almond antique violet turquoise frosted 40 2
+Manufacturer#2 almond aquamarine midnight light salmon 2 3
+Manufacturer#2 almond aquamarine rose maroon antique 25 4
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5
+Manufacturer#3 almond antique chartreuse khaki white 17 1
+Manufacturer#3 almond antique forest lavender goldenrod 14 2
+Manufacturer#3 almond antique metallic orange dim 19 3
+Manufacturer#3 almond antique misty red olive 1 4
+Manufacturer#3 almond antique olive coral navajo 45 5
+Manufacturer#4 almond antique gainsboro frosted violet 10 1
+Manufacturer#4 almond antique violet mint lemon 39 2
+Manufacturer#4 almond aquamarine floral ivory bisque 27 3
+Manufacturer#4 almond aquamarine yellow dodger mint 7 4
+Manufacturer#4 almond azure aquamarine papaya violet 12 5
+Manufacturer#5 almond antique blue firebrick mint 31 1
+Manufacturer#5 almond antique medium spring khaki 6 2
+Manufacturer#5 almond antique sky peru orange 2 3
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 4
+Manufacturer#5 almond azure blanched chiffon midnight 23 5
diff --git a/sql/hive/src/test/resources/golden/windowing.q -- 9. testHavingWithWindowingNoGBY-0-70cdc0555a61ef08534a9ebebb95ebbf b/sql/hive/src/test/resources/golden/windowing.q -- 9. testHavingWithWindowingNoGBY-0-70cdc0555a61ef08534a9ebebb95ebbf
new file mode 100644
index 0000000000000000000000000000000000000000..850c41c8115d6f4ee3c712324d68fc2a9b5ac3c7
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing.q -- 9. testHavingWithWindowingNoGBY-0-70cdc0555a61ef08534a9ebebb95ebbf
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 1173.15
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 2346.3
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3 2 4100.06
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4 3 5702.650000000001
+Manufacturer#1 almond aquamarine burnished black steel 28 5 4 7117.070000000001
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 6 5 8749.730000000001
+Manufacturer#2 almond antique violet chocolate turquoise 14 1 1 1690.68
+Manufacturer#2 almond antique violet turquoise frosted 40 2 2 3491.38
+Manufacturer#2 almond aquamarine midnight light salmon 2 3 3 5523.360000000001
+Manufacturer#2 almond aquamarine rose maroon antique 25 4 4 7222.02
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5 5 8923.62
+Manufacturer#3 almond antique chartreuse khaki white 17 1 1 1671.68
+Manufacturer#3 almond antique forest lavender goldenrod 14 2 2 2861.95
+Manufacturer#3 almond antique metallic orange dim 19 3 3 4272.34
+Manufacturer#3 almond antique misty red olive 1 4 4 6195.32
+Manufacturer#3 almond antique olive coral navajo 45 5 5 7532.61
+Manufacturer#4 almond antique gainsboro frosted violet 10 1 1 1620.67
+Manufacturer#4 almond antique violet mint lemon 39 2 2 2996.09
+Manufacturer#4 almond aquamarine floral ivory bisque 27 3 3 4202.35
+Manufacturer#4 almond aquamarine yellow dodger mint 7 4 4 6047.27
+Manufacturer#4 almond azure aquamarine papaya violet 12 5 5 7337.620000000001
+Manufacturer#5 almond antique blue firebrick mint 31 1 1 1789.69
+Manufacturer#5 almond antique medium spring khaki 6 2 2 3401.3500000000004
+Manufacturer#5 almond antique sky peru orange 2 3 3 5190.08
+Manufacturer#5 almond aquamarine dodger light gainsboro 46 4 4 6208.18
+Manufacturer#5 almond azure blanched chiffon midnight 23 5 5 7672.66
diff --git a/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-0-d3f50875bd5dff172cf813fdb7d738eb b/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-0-d3f50875bd5dff172cf813fdb7d738eb
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-1-dda16565b98926fc3587de937b9401c7 b/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-1-dda16565b98926fc3587de937b9401c7
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-2-374e39786feb745cd70f25be58bfa24 b/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-2-374e39786feb745cd70f25be58bfa24
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-3-d2b5e23edec42a62e61750b110ecbaac b/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-3-d2b5e23edec42a62e61750b110ecbaac
new file mode 100644
index 0000000000000000000000000000000000000000..573541ac9702dd3969c9bc859d2b91ec1f7e6e56
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-3-d2b5e23edec42a62e61750b110ecbaac
@@ -0,0 +1 @@
+0
diff --git a/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-4-50d0c630159068b5b8ccdeb76493f1f7 b/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-4-50d0c630159068b5b8ccdeb76493f1f7
new file mode 100644
index 0000000000000000000000000000000000000000..850c41c8115d6f4ee3c712324d68fc2a9b5ac3c7
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_adjust_rowcontainer_sz-4-50d0c630159068b5b8ccdeb76493f1f7
@@ -0,0 +1,26 @@
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 1173.15
+Manufacturer#1 almond antique burnished rose metallic 2 1 1 2346.3
+Manufacturer#1 almond antique chartreuse lavender yellow 34 3 2 4100.06
+Manufacturer#1 almond antique salmon chartreuse burlywood 6 4 3 5702.650000000001
+Manufacturer#1 almond aquamarine burnished black steel 28 5 4 7117.070000000001
+Manufacturer#1 almond aquamarine pink moccasin thistle 42 6 5 8749.730000000001
+Manufacturer#2 almond antique violet chocolate turquoise 14 1 1 1690.68
+Manufacturer#2 almond antique violet turquoise frosted 40 2 2 3491.38
+Manufacturer#2 almond aquamarine midnight light salmon 2 3 3 5523.360000000001
+Manufacturer#2 almond aquamarine rose maroon antique 25 4 4 7222.02
+Manufacturer#2 almond aquamarine sandy cyan gainsboro 18 5 5 8923.62
+Manufacturer#3 almond antique chartreuse khaki white 17 1 1 1671.68
+Manufacturer#3 almond antique forest lavender goldenrod 14 2 2 2861.95
+Manufacturer#3 almond antique metallic orange dim 19 3 3 4272.34
+Manufacturer#3 almond antique misty red olive 1 4 4 6195.32
+Manufacturer#3 almond antique olive coral navajo 45 5 5 7532.61
+Manufacturer#4 almond antique gainsboro frosted violet 10 1 1 1620.67
+Manufacturer#4 almond antique violet mint lemon 39 2 2 2996.09
+Manufacturer#4 almond aquamarine floral ivory bisque 27 3 3 4202.35
+Manufacturer#4 almond aquamarine yellow dodger mint 7 4 4 6047.27
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diff --git a/sql/hive/src/test/resources/golden/windowing_multipartitioning.q (deterministic) 3-0-455e41d9949a2d22bab634fd8e42f2b1 b/sql/hive/src/test/resources/golden/windowing_multipartitioning.q (deterministic) 3-0-455e41d9949a2d22bab634fd8e42f2b1
new file mode 100644
index 0000000000000000000000000000000000000000..f47923618a1aa0b5f509f751f6cbcfccd2eddaa4
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_multipartitioning.q (deterministic) 3-0-455e41d9949a2d22bab634fd8e42f2b1
@@ -0,0 +1 @@
+bob steinbeck 65637 9.699999809265137
diff --git a/sql/hive/src/test/resources/golden/windowing_multipartitioning.q (deterministic) 4-0-cfad06ae8eba6b047d32a6a61dd59392 b/sql/hive/src/test/resources/golden/windowing_multipartitioning.q (deterministic) 4-0-cfad06ae8eba6b047d32a6a61dd59392
new file mode 100644
index 0000000000000000000000000000000000000000..f41eaa259cec04de5242979983d01a49534059c5
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_multipartitioning.q (deterministic) 4-0-cfad06ae8eba6b047d32a6a61dd59392
@@ -0,0 +1 @@
+bob steinbeck 1 1
diff --git a/sql/hive/src/test/resources/golden/windowing_multipartitioning.q (deterministic) 5-0-d7ca7a61377cef3a9f721a28afdae012 b/sql/hive/src/test/resources/golden/windowing_multipartitioning.q (deterministic) 5-0-d7ca7a61377cef3a9f721a28afdae012
new file mode 100644
index 0000000000000000000000000000000000000000..5308b2eb457e776ab558341f540df6f19064ec66
--- /dev/null
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diff --git a/sql/hive/src/test/resources/golden/windowing_multipartitioning.q (deterministic) 6-0-287bcc7679822bc7b684532b267bf11f b/sql/hive/src/test/resources/golden/windowing_multipartitioning.q (deterministic) 6-0-287bcc7679822bc7b684532b267bf11f
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index 0000000000000000000000000000000000000000..f41eaa259cec04de5242979983d01a49534059c5
--- /dev/null
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index 0000000000000000000000000000000000000000..8150409e62d33a5813571880269de7a59d38ebe1
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diff --git a/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-1-9ee79e711248dd6e0a6ce27e439e55f4 b/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-1-9ee79e711248dd6e0a6ce27e439e55f4
new file mode 100644
index 0000000000000000000000000000000000000000..275772e1f643adcc0e4b71ab3941881ea91bb25f
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-1-9ee79e711248dd6e0a6ce27e439e55f4
@@ -0,0 +1,1049 @@
+65791 calvin nixon
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diff --git a/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-2-1e88e0ba414a00195f7ebf6b8600ac04 b/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-2-1e88e0ba414a00195f7ebf6b8600ac04
new file mode 100644
index 0000000000000000000000000000000000000000..62d71abc6fc7ddbcf84c3813842e22540cddd5e2
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-2-1e88e0ba414a00195f7ebf6b8600ac04
@@ -0,0 +1,1049 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-3-34d9ee4120f21d0d0ae914fba0acc60c b/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-3-34d9ee4120f21d0d0ae914fba0acc60c
new file mode 100644
index 0000000000000000000000000000000000000000..569c1d4e5f7b6df2a9605e5b4b2560a995991768
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-3-34d9ee4120f21d0d0ae914fba0acc60c
@@ -0,0 +1,1049 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-4-dfd39236756a3951bc1ec354799d69e4 b/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-4-dfd39236756a3951bc1ec354799d69e4
new file mode 100644
index 0000000000000000000000000000000000000000..86ca4e49d21bd44ab1fcf545390f06b32111ceb3
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-4-dfd39236756a3951bc1ec354799d69e4
@@ -0,0 +1,1049 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-5-8d0ee3e1605f38214bfad28a5ce897cc b/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-5-8d0ee3e1605f38214bfad28a5ce897cc
new file mode 100644
index 0000000000000000000000000000000000000000..ddb15e338263f45f956ef02504c3f6f58799bbe9
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_navfn.q (deterministic)-5-8d0ee3e1605f38214bfad28a5ce897cc
@@ -0,0 +1 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-0-b7cb25303831392a51cd996e758ac79a b/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-0-b7cb25303831392a51cd996e758ac79a
new file mode 100644
index 0000000000000000000000000000000000000000..42e5151fe211bd57cab35b137fcd3337b4ee68f6
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-0-b7cb25303831392a51cd996e758ac79a
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diff --git a/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-1-a3d352560ac835993001665db6954965 b/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-1-a3d352560ac835993001665db6954965
new file mode 100644
index 0000000000000000000000000000000000000000..dc72606a83db6f37694cdebbf744e2f0f1b91c8a
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-1-a3d352560ac835993001665db6954965
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diff --git a/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-2-fafa16c0f7697ca28aeb6f2698799562 b/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-2-fafa16c0f7697ca28aeb6f2698799562
new file mode 100644
index 0000000000000000000000000000000000000000..76cbeb254c0e96772e1091ee07c43b0727e3de40
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-2-fafa16c0f7697ca28aeb6f2698799562
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diff --git a/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-3-bda0e7c77d6f4712a03389cb5032bc6d b/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-3-bda0e7c77d6f4712a03389cb5032bc6d
new file mode 100644
index 0000000000000000000000000000000000000000..a9ec53c0cb21c9c3698706db0cac271c64fa0dfc
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_ntile.q (deterministic)-3-bda0e7c77d6f4712a03389cb5032bc6d
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diff --git a/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-0-2e0cbc2d7c5f16657edacd9e7209e6e7 b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-0-2e0cbc2d7c5f16657edacd9e7209e6e7
new file mode 100644
index 0000000000000000000000000000000000000000..612bdf44c0cdf4a72201b6fbdf231764a1643aa1
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-0-2e0cbc2d7c5f16657edacd9e7209e6e7
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diff --git a/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-1-5c5f373e325115d710a7a23fcb1626f1 b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-1-5c5f373e325115d710a7a23fcb1626f1
new file mode 100644
index 0000000000000000000000000000000000000000..22a6f27253dcf3302d53ed87a723bc5fb67854b3
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-1-5c5f373e325115d710a7a23fcb1626f1
@@ -0,0 +1,1049 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-2-ac487cc1b94130bf9ce00e07c7075f65 b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-2-ac487cc1b94130bf9ce00e07c7075f65
new file mode 100644
index 0000000000000000000000000000000000000000..c38e7bbabc21e78cc50f16b465ea552b44b98f50
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-2-ac487cc1b94130bf9ce00e07c7075f65
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diff --git a/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-3-b82dfa24123047be4b4e3c27c3997d34 b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-3-b82dfa24123047be4b4e3c27c3997d34
new file mode 100644
index 0000000000000000000000000000000000000000..1e0cf03db63a020c37426ffefa60ffe420a5f838
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 1-3-b82dfa24123047be4b4e3c27c3997d34
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diff --git a/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 2-0-81bb7f49a55385878637c8aac4d08e5 b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 2-0-81bb7f49a55385878637c8aac4d08e5
new file mode 100644
index 0000000000000000000000000000000000000000..9091a9156134c5e406ad805d82e6f3809542b2eb
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 2-0-81bb7f49a55385878637c8aac4d08e5
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diff --git a/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 4-0-12cc78f3953c3e6b5411ddc729541bf0 b/sql/hive/src/test/resources/golden/windowing_rank.q (deterministic) 4-0-12cc78f3953c3e6b5411ddc729541bf0
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diff --git a/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-0-6642a21d87e0401ba1a668ea8b244f0c b/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-0-6642a21d87e0401ba1a668ea8b244f0c
new file mode 100644
index 0000000000000000000000000000000000000000..119dd71df14263a26965fe39e79461dda538b0ee
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-0-6642a21d87e0401ba1a668ea8b244f0c
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diff --git a/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-1-2bf20f39e6ffef258858f7943a974e7e b/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-1-2bf20f39e6ffef258858f7943a974e7e
new file mode 100644
index 0000000000000000000000000000000000000000..657e81a94f4c5b1006e58307fa543f14952df902
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-1-2bf20f39e6ffef258858f7943a974e7e
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diff --git a/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-2-16239d2b069789ba99fbac50c4f0724f b/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-2-16239d2b069789ba99fbac50c4f0724f
new file mode 100644
index 0000000000000000000000000000000000000000..6cfa5ad413fa4b0afb21712257a1959319134ff6
--- /dev/null
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diff --git a/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-3-d90b27fca067b0b3c48d873b3ef32af7 b/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-3-d90b27fca067b0b3c48d873b3ef32af7
new file mode 100644
index 0000000000000000000000000000000000000000..072a8a891a836edb7072af8c22e829210a861e46
--- /dev/null
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diff --git a/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-4-f2e4d659b65a833e9281b6786d3d55c1 b/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-4-f2e4d659b65a833e9281b6786d3d55c1
new file mode 100644
index 0000000000000000000000000000000000000000..9cc7e7ea6c2b28c237132a04a1b425f36e5a9686
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_udaf.q (deterministic)-4-f2e4d659b65a833e9281b6786d3d55c1
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diff --git a/sql/hive/src/test/resources/golden/windowing_udaf2-0-96659fde37d7a38ea15b367b47f59ce2 b/sql/hive/src/test/resources/golden/windowing_udaf2-0-96659fde37d7a38ea15b367b47f59ce2
new file mode 100644
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diff --git a/sql/hive/src/test/resources/golden/windowing_udaf2-1-b4bdee4908b1cb8e240c549ae5cfe4c0 b/sql/hive/src/test/resources/golden/windowing_udaf2-1-b4bdee4908b1cb8e240c549ae5cfe4c0
new file mode 100644
index 0000000000000000000000000000000000000000..17c31c0f04592723f2c63800cc48bacc46b92340
--- /dev/null
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@@ -0,0 +1 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-0-f498cccf82480be03022d2a36f87651e b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-0-f498cccf82480be03022d2a36f87651e
new file mode 100644
index 0000000000000000000000000000000000000000..31b1f85a5eb5aa93dd90f2dbd09a2498a28ea159
--- /dev/null
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diff --git a/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-1-6378faf36ffd3f61e61cee6c0cb70e6 b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-1-6378faf36ffd3f61e61cee6c0cb70e6
new file mode 100644
index 0000000000000000000000000000000000000000..1436509e4ec17c2ed6854d8e75650d23a323c582
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-1-6378faf36ffd3f61e61cee6c0cb70e6
@@ -0,0 +1,1049 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-2-5f0eab306ea3c22b11ace9b542a7ee56 b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-2-5f0eab306ea3c22b11ace9b542a7ee56
new file mode 100644
index 0000000000000000000000000000000000000000..e55bede9242e58c3170ce3c7b1a370ca8deb1aa7
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-2-5f0eab306ea3c22b11ace9b542a7ee56
@@ -0,0 +1,1049 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-3-6f104992e0050576085064815de43194 b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-3-6f104992e0050576085064815de43194
new file mode 100644
index 0000000000000000000000000000000000000000..ae2a1e9dd7d3fdc41cbccd31ff4b06c98b8ec011
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-3-6f104992e0050576085064815de43194
@@ -0,0 +1,1049 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-4-cd2e3d2344810cb3ba843d4c01c81d7e b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-4-cd2e3d2344810cb3ba843d4c01c81d7e
new file mode 100644
index 0000000000000000000000000000000000000000..ee1c26e331a1e52098aa7fa9a3ee0ac39fca6389
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-4-cd2e3d2344810cb3ba843d4c01c81d7e
@@ -0,0 +1,1049 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-5-ee44c5cdc80e1c832b702f9fb76d8145 b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-5-ee44c5cdc80e1c832b702f9fb76d8145
new file mode 100644
index 0000000000000000000000000000000000000000..a9ae190825a0113f4e04c34599022e6b47c6b298
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-5-ee44c5cdc80e1c832b702f9fb76d8145
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diff --git a/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-6-4d78f7b1d172d20c91f5867bc13a42a0 b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-6-4d78f7b1d172d20c91f5867bc13a42a0
new file mode 100644
index 0000000000000000000000000000000000000000..b3f08818f491afedf0a0d52194ac2ec8cdea3059
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-6-4d78f7b1d172d20c91f5867bc13a42a0
@@ -0,0 +1,1049 @@
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diff --git a/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-7-20fdc99aa046b2c41d9b85ab338c749c b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-7-20fdc99aa046b2c41d9b85ab338c749c
new file mode 100644
index 0000000000000000000000000000000000000000..1a4528978b74f17db18fc6aa60a5c7396bdf2831
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-7-20fdc99aa046b2c41d9b85ab338c749c
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diff --git a/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-8-45a1d7c2aba45d761e19ff4dfdf5463e b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-8-45a1d7c2aba45d761e19ff4dfdf5463e
new file mode 100644
index 0000000000000000000000000000000000000000..84b934fad85b17b209410489fb7c58f7368a2fae
--- /dev/null
+++ b/sql/hive/src/test/resources/golden/windowing_windowspec.q (deterministic)-8-45a1d7c2aba45d761e19ff4dfdf5463e
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diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala
index 027056d4b865f07afbc7fe2d1313dbab11f2a491..5ead5f3c19908e947b411ea346066b1e3cae4afd 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala
@@ -300,7 +300,7 @@ abstract class HiveComparisonTest
val hiveQueries = queryList.map(new TestHive.HiveQLQueryExecution(_))
// Make sure we can at least parse everything before attempting hive execution.
- hiveQueries.foreach(_.analyzed)
+ hiveQueries.foreach(_.logical)
val computedResults = (queryList.zipWithIndex, hiveQueries, hiveCacheFiles).zipped.map {
case ((queryString, i), hiveQuery, cachedAnswerFile)=>
try {
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveWindowFunctionQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveWindowFunctionQuerySuite.scala
new file mode 100644
index 0000000000000000000000000000000000000000..934452fe579a1db085603c29ce5e6c4c8efaad40
--- /dev/null
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveWindowFunctionQuerySuite.scala
@@ -0,0 +1,845 @@
+/*
+ * 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.
+ */
+
+package org.apache.spark.sql.hive.execution
+
+import java.io.File
+import java.util.{Locale, TimeZone}
+
+import org.scalatest.BeforeAndAfter
+
+import org.apache.spark.sql.hive.test.TestHive
+import org.apache.spark.sql.hive.test.TestHive._
+import org.apache.spark.util.Utils
+
+/**
+ * The test suite for window functions. To actually compare results with Hive,
+ * every test should be created by `createQueryTest`. Because we are reusing tables
+ * for different tests and there are a few properties needed to let Hive generate golden
+ * files, every `createQueryTest` calls should explicitly set `reset` to `false`.
+ */
+abstract class HiveWindowFunctionQueryBaseSuite extends HiveComparisonTest with BeforeAndAfter {
+ private val originalTimeZone = TimeZone.getDefault
+ private val originalLocale = Locale.getDefault
+ private val testTempDir = Utils.createTempDir()
+
+ override def beforeAll() {
+ TestHive.cacheTables = true
+ // Timezone is fixed to America/Los_Angeles for those timezone sensitive tests (timestamp_*)
+ TimeZone.setDefault(TimeZone.getTimeZone("America/Los_Angeles"))
+ // Add Locale setting
+ Locale.setDefault(Locale.US)
+
+ // Create the table used in windowing.q
+ sql("DROP TABLE IF EXISTS part")
+ sql(
+ """
+ |CREATE TABLE part(
+ | p_partkey INT,
+ | p_name STRING,
+ | p_mfgr STRING,
+ | p_brand STRING,
+ | p_type STRING,
+ | p_size INT,
+ | p_container STRING,
+ | p_retailprice DOUBLE,
+ | p_comment STRING)
+ """.stripMargin)
+ val testData1 = TestHive.getHiveFile("data/files/part_tiny.txt").getCanonicalPath
+ sql(
+ s"""
+ |LOAD DATA LOCAL INPATH '$testData1' overwrite into table part
+ """.stripMargin)
+
+ sql("DROP TABLE IF EXISTS over1k")
+ sql(
+ """
+ |create table over1k(
+ | t tinyint,
+ | si smallint,
+ | i int,
+ | b bigint,
+ | f float,
+ | d double,
+ | bo boolean,
+ | s string,
+ | ts timestamp,
+ | dec decimal(4,2),
+ | bin binary)
+ |row format delimited
+ |fields terminated by '|'
+ """.stripMargin)
+ val testData2 = TestHive.getHiveFile("data/files/over1k").getCanonicalPath
+ sql(
+ s"""
+ |LOAD DATA LOCAL INPATH '$testData2' overwrite into table over1k
+ """.stripMargin)
+
+ // The following settings are used for generating golden files with Hive.
+ // We have to use kryo to correctly let Hive serialize plans with window functions.
+ // This is used to generate golden files.
+ sql("set hive.plan.serialization.format=kryo")
+ // Explicitly set fs to local fs.
+ sql(s"set fs.default.name=file://$testTempDir/")
+ // Ask Hive to run jobs in-process as a single map and reduce task.
+ sql("set mapred.job.tracker=local")
+ }
+
+ override def afterAll() {
+ TestHive.cacheTables = false
+ TimeZone.setDefault(originalTimeZone)
+ Locale.setDefault(originalLocale)
+ TestHive.reset()
+ }
+
+ /////////////////////////////////////////////////////////////////////////////
+ // Tests based on windowing_multipartitioning.q
+ // Results of the original query file are not deterministic.
+ /////////////////////////////////////////////////////////////////////////////
+ createQueryTest("windowing_multipartitioning.q (deterministic) 1",
+ s"""
+ |select s,
+ |rank() over (partition by s order by si) r,
+ |sum(b) over (partition by s order by si) sum
+ |from over1k
+ |order by s, r, sum;
+ """.stripMargin, reset = false)
+
+ /* timestamp comparison issue with Hive?
+ createQueryTest("windowing_multipartitioning.q (deterministic) 2",
+ s"""
+ |select s,
+ |rank() over (partition by s order by dec desc) r,
+ |sum(b) over (partition by s order by ts desc) as sum
+ |from over1k
+ |where s = 'tom allen' or s = 'bob steinbeck'
+ |order by s, r, sum;
+ """.stripMargin, reset = false)
+ */
+
+ createQueryTest("windowing_multipartitioning.q (deterministic) 3",
+ s"""
+ |select s, sum(i) over (partition by s), sum(f) over (partition by si)
+ |from over1k where s = 'tom allen' or s = 'bob steinbeck';
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing_multipartitioning.q (deterministic) 4",
+ s"""
+ |select s, rank() over (partition by s order by bo),
+ |rank() over (partition by si order by bin desc) from over1k
+ |where s = 'tom allen' or s = 'bob steinbeck';
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing_multipartitioning.q (deterministic) 5",
+ s"""
+ |select s, sum(f) over (partition by i), row_number() over (order by f)
+ |from over1k where s = 'tom allen' or s = 'bob steinbeck';
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing_multipartitioning.q (deterministic) 6",
+ s"""
+ |select s, rank() over w1,
+ |rank() over w2
+ |from over1k
+ |where s = 'tom allen' or s = 'bob steinbeck'
+ |window
+ |w1 as (partition by s order by dec),
+ |w2 as (partition by si order by f) ;
+ """.stripMargin, reset = false)
+
+ /////////////////////////////////////////////////////////////////////////////
+ // Tests based on windowing_navfn.q
+ // Results of the original query file are not deterministic.
+ // Also, the original query of
+ // select i, lead(s) over (partition by bin order by d,i desc) from over1k ;
+ /////////////////////////////////////////////////////////////////////////////
+ createQueryTest("windowing_navfn.q (deterministic)",
+ s"""
+ |select s, row_number() over (partition by d order by dec) rn from over1k
+ |order by s, rn desc;
+ |select i, lead(s) over (partition by cast(bin as string) order by d,i desc) as l
+ |from over1k
+ |order by i desc, l;
+ |select i, lag(dec) over (partition by i order by s,i,dec) l from over1k
+ |order by i, l;
+ |select s, last_value(t) over (partition by d order by f) l from over1k
+ |order by s, l;
+ |select s, first_value(s) over (partition by bo order by s) f from over1k
+ |order by s, f;
+ |select t, s, i, last_value(i) over (partition by t order by s)
+ |from over1k where (s = 'oscar allen' or s = 'oscar carson') and t = 10;
+ """.stripMargin, reset = false)
+
+ /////////////////////////////////////////////////////////////////////////////
+ // Tests based on windowing_ntile.q
+ // Results of the original query file are not deterministic.
+ /////////////////////////////////////////////////////////////////////////////
+ createQueryTest("windowing_ntile.q (deterministic)",
+ s"""
+ |select i, ntile(10) over (partition by s order by i) n from over1k
+ |order by i, n;
+ |select s, ntile(100) over (partition by i order by s) n from over1k
+ |order by s, n;
+ |select f, ntile(4) over (partition by d order by f) n from over1k
+ |order by f, n;
+ |select d, ntile(1000) over (partition by dec order by d) n from over1k
+ |order by d, n;
+ """.stripMargin, reset = false)
+
+ /////////////////////////////////////////////////////////////////////////////
+ // Tests based on windowing_udaf.q
+ // Results of the original query file are not deterministic.
+ /////////////////////////////////////////////////////////////////////////////
+ createQueryTest("windowing_udaf.q (deterministic)",
+ s"""
+ |select s, min(i) over (partition by s) m from over1k
+ |order by s, m;
+ |select s, avg(f) over (partition by si order by s) a from over1k
+ |order by s, a;
+ |select s, avg(i) over (partition by t, b order by s) a from over1k
+ |order by s, a;
+ |select max(i) over w m from over1k
+ |order by m window w as (partition by f) ;
+ |select s, avg(d) over (partition by t order by f) a from over1k
+ |order by s, a;
+ """.stripMargin, reset = false)
+
+ /////////////////////////////////////////////////////////////////////////////
+ // Tests based on windowing_windowspec.q
+ // Results of the original query file are not deterministic.
+ /////////////////////////////////////////////////////////////////////////////
+ createQueryTest("windowing_windowspec.q (deterministic)",
+ s"""
+ |select s, sum(b) over (partition by i order by s,b rows unbounded preceding) as sum
+ |from over1k order by s, sum;
+ |select s, sum(f) over (partition by d order by s,f rows unbounded preceding) as sum
+ |from over1k order by s, sum;
+ |select s, sum(f) over
+ |(partition by ts order by f range between current row and unbounded following) as sum
+ |from over1k order by s, sum;
+ |select s, avg(f)
+ |over (partition by ts order by s,f rows between current row and 5 following) avg
+ |from over1k order by s, avg;
+ |select s, avg(d) over
+ |(partition by t order by s,d desc rows between 5 preceding and 5 following) avg
+ |from over1k order by s, avg;
+ |select s, sum(i) over(partition by ts order by s) sum from over1k
+ |order by s, sum;
+ |select f, sum(f) over
+ |(partition by ts order by f range between unbounded preceding and current row) sum
+ |from over1k order by f, sum;
+ |select s, i, round(avg(d) over (partition by s order by i) / 10.0 , 2) avg
+ |from over1k order by s, i, avg;
+ |select s, i, round((avg(d) over w1 + 10.0) - (avg(d) over w1 - 10.0),2) avg
+ |from over1k
+ |order by s, i, avg window w1 as (partition by s order by i);
+ """.stripMargin, reset = false)
+
+ /////////////////////////////////////////////////////////////////////////////
+ // Tests based on windowing_rank.q
+ // Results of the original query file are not deterministic.
+ /////////////////////////////////////////////////////////////////////////////
+ createQueryTest("windowing_rank.q (deterministic) 1",
+ s"""
+ |select s, rank() over (partition by f order by t) r from over1k order by s, r;
+ |select s, dense_rank() over (partition by ts order by i,s desc) as r from over1k
+ |order by s desc, r desc;
+ |select s, cume_dist() over (partition by bo order by b,s) cd from over1k
+ |order by s, cd;
+ |select s, percent_rank() over (partition by dec order by f) r from over1k
+ |order by s desc, r desc;
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing_rank.q (deterministic) 2",
+ s"""
+ |select ts, dec, rnk
+ |from
+ | (select ts, dec,
+ | rank() over (partition by ts order by dec) as rnk
+ | from
+ | (select other.ts, other.dec
+ | from over1k other
+ | join over1k on (other.b = over1k.b)
+ | ) joined
+ | ) ranked
+ |where rnk = 1
+ |order by ts, dec, rnk;
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing_rank.q (deterministic) 3",
+ s"""
+ |select ts, dec, rnk
+ |from
+ | (select ts, dec,
+ | rank() over (partition by ts order by dec) as rnk
+ | from
+ | (select other.ts, other.dec
+ | from over1k other
+ | join over1k on (other.b = over1k.b)
+ | ) joined
+ | ) ranked
+ |where dec = 89.5
+ |order by ts, dec, rnk;
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing_rank.q (deterministic) 4",
+ s"""
+ |select ts, dec, rnk
+ |from
+ | (select ts, dec,
+ | rank() over (partition by ts order by dec) as rnk
+ | from
+ | (select other.ts, other.dec
+ | from over1k other
+ | join over1k on (other.b = over1k.b)
+ | where other.t < 10
+ | ) joined
+ | ) ranked
+ |where rnk = 1
+ |order by ts, dec, rnk;
+ """.stripMargin, reset = false)
+
+ /////////////////////////////////////////////////////////////////////////////
+ // Tests from windowing.q
+ // We port tests in windowing.q to here because this query file contains too
+ // many tests and the syntax of test "-- 7. testJoinWithWindowingAndPTF"
+ // is not supported right now.
+ /////////////////////////////////////////////////////////////////////////////
+ createQueryTest("windowing.q -- 1. testWindowing",
+ s"""
+ |select p_mfgr, p_name, p_size,
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr,
+ |sum(p_retailprice) over
+ |(distribute by p_mfgr sort by p_name rows between unbounded preceding and current row) as s1
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 2. testGroupByWithPartitioning",
+ s"""
+ |select p_mfgr, p_name, p_size,
+ |min(p_retailprice),
+ |rank() over(distribute by p_mfgr sort by p_name)as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr,
+ |p_size, p_size - lag(p_size,1,p_size) over(distribute by p_mfgr sort by p_name) as deltaSz
+ |from part
+ |group by p_mfgr, p_name, p_size
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 3. testGroupByHavingWithSWQ",
+ s"""
+ |select p_mfgr, p_name, p_size, min(p_retailprice),
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr,
+ |p_size, p_size - lag(p_size,1,p_size) over(distribute by p_mfgr sort by p_name) as deltaSz
+ |from part
+ |group by p_mfgr, p_name, p_size
+ |having p_size > 0
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 4. testCount",
+ s"""
+ |select p_mfgr, p_name,
+ |count(p_size) over(distribute by p_mfgr sort by p_name) as cd
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 5. testCountWithWindowingUDAF",
+ s"""
+ |select p_mfgr, p_name,
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr,
+ |count(p_size) over(distribute by p_mfgr sort by p_name) as cd,
+ |p_retailprice, sum(p_retailprice) over (distribute by p_mfgr sort by p_name
+ | rows between unbounded preceding and current row) as s1,
+ |p_size, p_size - lag(p_size,1,p_size) over(distribute by p_mfgr sort by p_name) as deltaSz
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 6. testCountInSubQ",
+ s"""
+ |select sub1.r, sub1.dr, sub1.cd, sub1.s1, sub1.deltaSz
+ |from (select p_mfgr, p_name,
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr,
+ |count(p_size) over(distribute by p_mfgr sort by p_name) as cd,
+ |p_retailprice, sum(p_retailprice) over (distribute by p_mfgr sort by p_name
+ | rows between unbounded preceding and current row) as s1,
+ |p_size, p_size - lag(p_size,1,p_size) over(distribute by p_mfgr sort by p_name) as deltaSz
+ |from part
+ |) sub1
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 8. testMixedCaseAlias",
+ s"""
+ |select p_mfgr, p_name, p_size,
+ |rank() over(distribute by p_mfgr sort by p_name, p_size desc) as R
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 9. testHavingWithWindowingNoGBY",
+ s"""
+ |select p_mfgr, p_name, p_size,
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr,
+ |sum(p_retailprice) over (distribute by p_mfgr sort by p_name
+ | rows between unbounded preceding and current row) as s1
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 10. testHavingWithWindowingCondRankNoGBY",
+ s"""
+ |select p_mfgr, p_name, p_size,
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr,
+ |sum(p_retailprice) over (distribute by p_mfgr sort by p_name
+ | rows between unbounded preceding and current row) as s1
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 11. testFirstLast",
+ s"""
+ |select p_mfgr,p_name, p_size,
+ |sum(p_size) over (distribute by p_mfgr sort by p_name
+ |rows between current row and current row) as s2,
+ |first_value(p_size) over w1 as f,
+ |last_value(p_size, false) over w1 as l
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_name rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 12. testFirstLastWithWhere",
+ s"""
+ |select p_mfgr,p_name, p_size,
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |sum(p_size) over (distribute by p_mfgr sort by p_name
+ |rows between current row and current row) as s2,
+ |first_value(p_size) over w1 as f,
+ |last_value(p_size, false) over w1 as l
+ |from part
+ |where p_mfgr = 'Manufacturer#3'
+ |window w1 as (distribute by p_mfgr sort by p_name rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 13. testSumWindow",
+ s"""
+ |select p_mfgr,p_name, p_size,
+ |sum(p_size) over w1 as s1,
+ |sum(p_size) over (distribute by p_mfgr sort by p_name
+ |rows between current row and current row) as s2
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_name rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 14. testNoSortClause",
+ s"""
+ |select p_mfgr,p_name, p_size,
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_name rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 15. testExpressions",
+ s"""
+ |select p_mfgr,p_name, p_size,
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr,
+ |cume_dist() over(distribute by p_mfgr sort by p_name) as cud,
+ |percent_rank() over(distribute by p_mfgr sort by p_name) as pr,
+ |ntile(3) over(distribute by p_mfgr sort by p_name) as nt,
+ |count(p_size) over(distribute by p_mfgr sort by p_name) as ca,
+ |avg(p_size) over(distribute by p_mfgr sort by p_name) as avg,
+ |stddev(p_size) over(distribute by p_mfgr sort by p_name) as st,
+ |first_value(p_size % 5) over(distribute by p_mfgr sort by p_name) as fv,
+ |last_value(p_size) over(distribute by p_mfgr sort by p_name) as lv,
+ |first_value(p_size) over w1 as fvW1
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_mfgr, p_name
+ | rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 16. testMultipleWindows",
+ s"""
+ |select p_mfgr,p_name, p_size,
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr,
+ |cume_dist() over(distribute by p_mfgr sort by p_name) as cud,
+ |sum(p_size) over (distribute by p_mfgr sort by p_name
+ |range between unbounded preceding and current row) as s1,
+ |sum(p_size) over (distribute by p_mfgr sort by p_size
+ |range between 5 preceding and current row) as s2,
+ |first_value(p_size) over w1 as fv1
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_mfgr, p_name
+ | rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+
+ createQueryTest("windowing.q -- 17. testCountStar",
+ s"""
+ |select p_mfgr,p_name, p_size,
+ |count(*) over(distribute by p_mfgr sort by p_name ) as c,
+ |count(p_size) over(distribute by p_mfgr sort by p_name) as ca,
+ |first_value(p_size) over w1 as fvW1
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_mfgr, p_name
+ | rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 18. testUDAFs",
+ s"""
+ |select p_mfgr,p_name, p_size,
+ |sum(p_retailprice) over w1 as s,
+ |min(p_retailprice) over w1 as mi,
+ |max(p_retailprice) over w1 as ma,
+ |avg(p_retailprice) over w1 as ag
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_mfgr, p_name
+ | rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 19. testUDAFsWithGBY",
+ """
+ |select p_mfgr,p_name, p_size, p_retailprice,
+ |sum(p_retailprice) over w1 as s,
+ |min(p_retailprice) as mi ,
+ |max(p_retailprice) as ma ,
+ |avg(p_retailprice) over w1 as ag
+ |from part
+ |group by p_mfgr,p_name, p_size, p_retailprice
+ |window w1 as (distribute by p_mfgr sort by p_mfgr, p_name
+ | rows between 2 preceding and 2 following);
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 20. testSTATs",
+ """
+ |select p_mfgr,p_name, p_size,
+ |stddev(p_retailprice) over w1 as sdev,
+ |stddev_pop(p_retailprice) over w1 as sdev_pop,
+ |collect_set(p_size) over w1 as uniq_size,
+ |variance(p_retailprice) over w1 as var,
+ |corr(p_size, p_retailprice) over w1 as cor,
+ |covar_pop(p_size, p_retailprice) over w1 as covarp
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_mfgr, p_name
+ | rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 21. testDISTs",
+ """
+ |select p_mfgr,p_name, p_size,
+ |histogram_numeric(p_retailprice, 5) over w1 as hist,
+ |percentile(p_partkey, 0.5) over w1 as per,
+ |row_number() over(distribute by p_mfgr sort by p_name) as rn
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_mfgr, p_name
+ | rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 24. testLateralViews",
+ """
+ |select p_mfgr, p_name,
+ |lv_col, p_size, sum(p_size) over w1 as s
+ |from (select p_mfgr, p_name, p_size, array(1,2,3) arr from part) p
+ |lateral view explode(arr) part_lv as lv_col
+ |window w1 as (distribute by p_mfgr sort by p_size, lv_col
+ | rows between 2 preceding and current row)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 26. testGroupByHavingWithSWQAndAlias",
+ """
+ |select p_mfgr, p_name, p_size, min(p_retailprice) as mi,
+ |rank() over(distribute by p_mfgr sort by p_name) as r,
+ |dense_rank() over(distribute by p_mfgr sort by p_name) as dr,
+ |p_size, p_size - lag(p_size,1,p_size) over(distribute by p_mfgr sort by p_name) as deltaSz
+ |from part
+ |group by p_mfgr, p_name, p_size
+ |having p_size > 0
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 27. testMultipleRangeWindows",
+ """
+ |select p_mfgr,p_name, p_size,
+ |sum(p_size) over (distribute by p_mfgr sort by p_size
+ |range between 10 preceding and current row) as s2,
+ |sum(p_size) over (distribute by p_mfgr sort by p_size
+ |range between current row and 10 following ) as s1
+ |from part
+ |window w1 as (rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 28. testPartOrderInUDAFInvoke",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_size) over (partition by p_mfgr order by p_name
+ |rows between 2 preceding and 2 following) as s
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 29. testPartOrderInWdwDef",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_size) over w1 as s
+ |from part
+ |window w1 as (partition by p_mfgr order by p_name
+ | rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 30. testDefaultPartitioningSpecRules",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_size) over w1 as s,
+ |sum(p_size) over w2 as s2
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_name rows between 2 preceding and 2 following),
+ | w2 as (partition by p_mfgr order by p_name)
+ """.stripMargin, reset = false)
+
+ /* p_name is not a numeric column. What is Hive's semantic?
+ createQueryTest("windowing.q -- 31. testWindowCrossReference",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_size) over w1 as s1,
+ |sum(p_size) over w2 as s2
+ |from part
+ |window w1 as (partition by p_mfgr order by p_name
+ | range between 2 preceding and 2 following),
+ | w2 as w1
+ """.stripMargin, reset = false)
+ */
+ /*
+ createQueryTest("windowing.q -- 32. testWindowInheritance",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_size) over w1 as s1,
+ |sum(p_size) over w2 as s2
+ |from part
+ |window w1 as (partition by p_mfgr order by p_name
+ | range between 2 preceding and 2 following),
+ | w2 as (w1 rows between unbounded preceding and current row)
+ """.stripMargin, reset = false)
+ */
+
+ /* p_name is not a numeric column. What is Hive's semantic?
+ createQueryTest("windowing.q -- 33. testWindowForwardReference",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_size) over w1 as s1,
+ |sum(p_size) over w2 as s2,
+ |sum(p_size) over w3 as s3
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_name
+ | range between 2 preceding and 2 following),
+ | w2 as w3,
+ | w3 as (distribute by p_mfgr sort by p_name
+ | range between unbounded preceding and current row)
+ """.stripMargin, reset = false)
+ */
+ /*
+ createQueryTest("windowing.q -- 34. testWindowDefinitionPropagation",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_size) over w1 as s1,
+ |sum(p_size) over w2 as s2,
+ |sum(p_size) over (w3 rows between 2 preceding and 2 following) as s3
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_name
+ | range between 2 preceding and 2 following),
+ | w2 as w3,
+ | w3 as (distribute by p_mfgr sort by p_name
+ | range between unbounded preceding and current row)
+ """.stripMargin, reset = false)
+ */
+
+ /* Seems Hive evaluate SELECT DISTINCT before window functions?
+ createQueryTest("windowing.q -- 35. testDistinctWithWindowing",
+ """
+ |select DISTINCT p_mfgr, p_name, p_size,
+ |sum(p_size) over w1 as s
+ |from part
+ |window w1 as (distribute by p_mfgr sort by p_name rows between 2 preceding and 2 following)
+ """.stripMargin, reset = false)
+ */
+
+ createQueryTest("windowing.q -- 36. testRankWithPartitioning",
+ """
+ |select p_mfgr, p_name, p_size,
+ |rank() over (partition by p_mfgr order by p_name ) as r
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 37. testPartitioningVariousForms",
+ """
+ |select p_mfgr,
+ |round(sum(p_retailprice) over (partition by p_mfgr order by p_mfgr),2) as s1,
+ |min(p_retailprice) over (partition by p_mfgr) as s2,
+ |max(p_retailprice) over (distribute by p_mfgr sort by p_mfgr) as s3,
+ |round(avg(p_retailprice) over (distribute by p_mfgr),2) as s4,
+ |count(p_retailprice) over (cluster by p_mfgr ) as s5
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 38. testPartitioningVariousForms2",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_retailprice) over (partition by p_mfgr, p_name order by p_mfgr, p_name
+ |rows between unbounded preceding and current row) as s1,
+ |min(p_retailprice) over (distribute by p_mfgr, p_name sort by p_mfgr, p_name
+ |rows between unbounded preceding and current row) as s2,
+ |max(p_retailprice) over (partition by p_mfgr, p_name order by p_name) as s3
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 39. testUDFOnOrderCols",
+ """
+ |select p_mfgr, p_type, substr(p_type, 2) as short_ptype,
+ |rank() over (partition by p_mfgr order by substr(p_type, 2)) as r
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 40. testNoBetweenForRows",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_retailprice) over (distribute by p_mfgr sort by p_name rows unbounded preceding) as s1
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 41. testNoBetweenForRange",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_retailprice) over (distribute by p_mfgr sort by p_size range unbounded preceding) as s1
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 42. testUnboundedFollowingForRows",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_retailprice) over (distribute by p_mfgr sort by p_name
+ |rows between current row and unbounded following) as s1
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 43. testUnboundedFollowingForRange",
+ """
+ |select p_mfgr, p_name, p_size,
+ |sum(p_retailprice) over (distribute by p_mfgr sort by p_size
+ |range between current row and unbounded following) as s1
+ |from part
+ """.stripMargin, reset = false)
+
+ createQueryTest("windowing.q -- 44. testOverNoPartitionSingleAggregate",
+ """
+ |select p_name, p_retailprice,
+ |round(avg(p_retailprice) over(),2)
+ |from part
+ |order by p_name
+ """.stripMargin, reset = false)
+}
+
+class HiveWindowFunctionQueryWithoutCodeGenSuite extends HiveWindowFunctionQueryBaseSuite {
+ var originalCodegenEnabled: Boolean = _
+ override def beforeAll(): Unit = {
+ super.beforeAll()
+ originalCodegenEnabled = conf.codegenEnabled
+ sql("set spark.sql.codegen=false")
+ }
+
+ override def afterAll(): Unit = {
+ sql(s"set spark.sql.codegen=$originalCodegenEnabled")
+ super.afterAll()
+ }
+}
+
+abstract class HiveWindowFunctionQueryFileBaseSuite
+ extends HiveCompatibilitySuite with BeforeAndAfter {
+ private val originalTimeZone = TimeZone.getDefault
+ private val originalLocale = Locale.getDefault
+ private val testTempDir = Utils.createTempDir()
+
+ override def beforeAll() {
+ TestHive.cacheTables = true
+ // Timezone is fixed to America/Los_Angeles for those timezone sensitive tests (timestamp_*)
+ TimeZone.setDefault(TimeZone.getTimeZone("America/Los_Angeles"))
+ // Add Locale setting
+ Locale.setDefault(Locale.US)
+
+ // The following settings are used for generating golden files with Hive.
+ // We have to use kryo to correctly let Hive serialize plans with window functions.
+ // This is used to generate golden files.
+ sql("set hive.plan.serialization.format=kryo")
+ // Explicitly set fs to local fs.
+ sql(s"set fs.default.name=file://$testTempDir/")
+ // Ask Hive to run jobs in-process as a single map and reduce task.
+ sql("set mapred.job.tracker=local")
+ }
+
+ override def afterAll() {
+ TestHive.cacheTables = false
+ TimeZone.setDefault(originalTimeZone)
+ Locale.setDefault(originalLocale)
+ TestHive.reset()
+ }
+
+ override def blackList: Seq[String] = Seq(
+ // Partitioned table functions are not supported.
+ "ptf*",
+ // tests of windowing.q are in HiveWindowFunctionQueryBaseSuite
+ "windowing.q",
+
+ // This one failed on the expression of
+ // sum(lag(p_retailprice,1,0.0)) over w1
+ // lag(p_retailprice,1,0.0) is a GenericUDF and the argument inspector of
+ // p_retailprice created by HiveInspectors is
+ // PrimitiveObjectInspectorFactory.javaDoubleObjectInspector.
+ // However, seems Hive assumes it is
+ // PrimitiveObjectInspectorFactory.writableDoubleObjectInspector, which introduces an error.
+ "windowing_expressions",
+
+ // Hive's results are not deterministic
+ "windowing_multipartitioning",
+ "windowing_navfn",
+ "windowing_ntile",
+ "windowing_udaf",
+ "windowing_windowspec",
+ "windowing_rank"
+ )
+
+ override def whiteList: Seq[String] = Seq(
+ "windowing_udaf2",
+ "windowing_columnPruning",
+ "windowing_adjust_rowcontainer_sz"
+ )
+
+ override def testCases: Seq[(String, File)] = super.testCases.filter {
+ case (name, _) => realWhiteList.contains(name)
+ }
+}
+
+class HiveWindowFunctionQueryFileWithoutCodeGenSuite extends HiveWindowFunctionQueryFileBaseSuite {
+ var originalCodegenEnabled: Boolean = _
+ override def beforeAll(): Unit = {
+ super.beforeAll()
+ originalCodegenEnabled = conf.codegenEnabled
+ sql("set spark.sql.codegen=false")
+ }
+
+ override def afterAll(): Unit = {
+ sql(s"set spark.sql.codegen=$originalCodegenEnabled")
+ super.afterAll()
+ }
+}
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
index 630dec8fa05a09571a4b6d03d782748b0dd7c98a..616352d223c5bf32e757b2c52fe074dd634e4297 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
@@ -48,6 +48,10 @@ case class Order(
state: String,
month: Int)
+case class WindowData(
+ month: Int,
+ area: String,
+ product: Int)
/** A SQL Dialect for testing purpose, and it can not be nested type */
class MyDialect extends DefaultDialect
@@ -604,4 +608,147 @@ class SQLQuerySuite extends QueryTest {
sql("SELECT TRANSFORM (d1, d2, d3) USING 'cat' AS (a,b,c) FROM script_trans")
.queryExecution.toRdd.count())
}
+
+ test("window function: udaf with aggregate expressin") {
+ val data = Seq(
+ WindowData(1, "a", 5),
+ WindowData(2, "a", 6),
+ WindowData(3, "b", 7),
+ WindowData(4, "b", 8),
+ WindowData(5, "c", 9),
+ WindowData(6, "c", 10)
+ )
+ sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+ checkAnswer(
+ sql(
+ """
+ |select area, sum(product), sum(sum(product)) over (partition by area)
+ |from windowData group by month, area
+ """.stripMargin),
+ Seq(
+ ("a", 5, 11),
+ ("a", 6, 11),
+ ("b", 7, 15),
+ ("b", 8, 15),
+ ("c", 9, 19),
+ ("c", 10, 19)
+ ).map(i => Row(i._1, i._2, i._3)))
+
+ checkAnswer(
+ sql(
+ """
+ |select area, sum(product) - 1, sum(sum(product)) over (partition by area)
+ |from windowData group by month, area
+ """.stripMargin),
+ Seq(
+ ("a", 4, 11),
+ ("a", 5, 11),
+ ("b", 6, 15),
+ ("b", 7, 15),
+ ("c", 8, 19),
+ ("c", 9, 19)
+ ).map(i => Row(i._1, i._2, i._3)))
+
+ checkAnswer(
+ sql(
+ """
+ |select area, sum(product), sum(product) / sum(sum(product)) over (partition by area)
+ |from windowData group by month, area
+ """.stripMargin),
+ Seq(
+ ("a", 5, 5d/11),
+ ("a", 6, 6d/11),
+ ("b", 7, 7d/15),
+ ("b", 8, 8d/15),
+ ("c", 10, 10d/19),
+ ("c", 9, 9d/19)
+ ).map(i => Row(i._1, i._2, i._3)))
+
+ checkAnswer(
+ sql(
+ """
+ |select area, sum(product), sum(product) / sum(sum(product) - 1) over (partition by area)
+ |from windowData group by month, area
+ """.stripMargin),
+ Seq(
+ ("a", 5, 5d/9),
+ ("a", 6, 6d/9),
+ ("b", 7, 7d/13),
+ ("b", 8, 8d/13),
+ ("c", 10, 10d/17),
+ ("c", 9, 9d/17)
+ ).map(i => Row(i._1, i._2, i._3)))
+ }
+
+ test("window function: partition and order expressions") {
+ val data = Seq(
+ WindowData(1, "a", 5),
+ WindowData(2, "a", 6),
+ WindowData(3, "b", 7),
+ WindowData(4, "b", 8),
+ WindowData(5, "c", 9),
+ WindowData(6, "c", 10)
+ )
+ sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+ checkAnswer(
+ sql(
+ """
+ |select month, area, product, sum(product + 1) over (partition by 1 order by 2)
+ |from windowData
+ """.stripMargin),
+ Seq(
+ (1, "a", 5, 51),
+ (2, "a", 6, 51),
+ (3, "b", 7, 51),
+ (4, "b", 8, 51),
+ (5, "c", 9, 51),
+ (6, "c", 10, 51)
+ ).map(i => Row(i._1, i._2, i._3, i._4)))
+
+ checkAnswer(
+ sql(
+ """
+ |select month, area, product, sum(product)
+ |over (partition by month % 2 order by 10 - product)
+ |from windowData
+ """.stripMargin),
+ Seq(
+ (1, "a", 5, 21),
+ (2, "a", 6, 24),
+ (3, "b", 7, 16),
+ (4, "b", 8, 18),
+ (5, "c", 9, 9),
+ (6, "c", 10, 10)
+ ).map(i => Row(i._1, i._2, i._3, i._4)))
+ }
+
+ test("window function: expressions in arguments of a window functions") {
+ val data = Seq(
+ WindowData(1, "a", 5),
+ WindowData(2, "a", 6),
+ WindowData(3, "b", 7),
+ WindowData(4, "b", 8),
+ WindowData(5, "c", 9),
+ WindowData(6, "c", 10)
+ )
+ sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+ checkAnswer(
+ sql(
+ """
+ |select month, area, month % 2,
+ |lag(product, 1 + 1, product) over (partition by month % 2 order by area)
+ |from windowData
+ """.stripMargin),
+ Seq(
+ (1, "a", 1, 5),
+ (2, "a", 0, 6),
+ (3, "b", 1, 7),
+ (4, "b", 0, 8),
+ (5, "c", 1, 5),
+ (6, "c", 0, 6)
+ ).map(i => Row(i._1, i._2, i._3, i._4)))
+ }
}