From be5dd881f1eff248224a92d57cfd1309cb3acf38 Mon Sep 17 00:00:00 2001 From: Davies Liu Date: Tue, 2 Feb 2016 11:50:14 -0800 Subject: [SPARK-12913] [SQL] Improve performance of stat functions As benchmarked and discussed here: https://github.com/apache/spark/pull/10786/files#r50038294, benefits from codegen, the declarative aggregate function could be much faster than imperative one. Author: Davies Liu Closes #10960 from davies/stddev. --- .../sql/catalyst/analysis/HiveTypeCoercion.scala | 18 +- .../expressions/aggregate/CentralMomentAgg.scala | 285 ++++++++++----------- .../sql/catalyst/expressions/aggregate/Corr.scala | 208 ++++----------- .../expressions/aggregate/Covariance.scala | 205 ++++----------- .../catalyst/expressions/aggregate/Kurtosis.scala | 54 ---- .../catalyst/expressions/aggregate/Skewness.scala | 53 ---- .../catalyst/expressions/aggregate/Stddev.scala | 81 ------ .../catalyst/expressions/aggregate/Variance.scala | 81 ------ .../spark/sql/catalyst/expressions/misc.scala | 18 ++ .../org/apache/spark/sql/execution/Window.scala | 6 +- .../execution/aggregate/TungstenAggregate.scala | 1 - .../sql/execution/BenchmarkWholeStageCodegen.scala | 55 +++- .../hive/execution/HiveCompatibilitySuite.scala | 4 +- .../sql/hive/execution/AggregationQuerySuite.scala | 17 +- 14 files changed, 331 insertions(+), 755 deletions(-) delete mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Kurtosis.scala delete mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Skewness.scala delete mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Stddev.scala delete mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Variance.scala diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala index 957ac89fa5..57bdb164e1 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala @@ -347,18 +347,12 @@ object HiveTypeCoercion { case Sum(e @ StringType()) => Sum(Cast(e, DoubleType)) case Average(e @ StringType()) => Average(Cast(e, DoubleType)) - case StddevPop(e @ StringType(), mutableAggBufferOffset, inputAggBufferOffset) => - StddevPop(Cast(e, DoubleType), mutableAggBufferOffset, inputAggBufferOffset) - case StddevSamp(e @ StringType(), mutableAggBufferOffset, inputAggBufferOffset) => - StddevSamp(Cast(e, DoubleType), mutableAggBufferOffset, inputAggBufferOffset) - case VariancePop(e @ StringType(), mutableAggBufferOffset, inputAggBufferOffset) => - VariancePop(Cast(e, DoubleType), mutableAggBufferOffset, inputAggBufferOffset) - case VarianceSamp(e @ StringType(), mutableAggBufferOffset, inputAggBufferOffset) => - VarianceSamp(Cast(e, DoubleType), mutableAggBufferOffset, inputAggBufferOffset) - case Skewness(e @ StringType(), mutableAggBufferOffset, inputAggBufferOffset) => - Skewness(Cast(e, DoubleType), mutableAggBufferOffset, inputAggBufferOffset) - case Kurtosis(e @ StringType(), mutableAggBufferOffset, inputAggBufferOffset) => - Kurtosis(Cast(e, DoubleType), mutableAggBufferOffset, inputAggBufferOffset) + case StddevPop(e @ StringType()) => StddevPop(Cast(e, DoubleType)) + case StddevSamp(e @ StringType()) => StddevSamp(Cast(e, DoubleType)) + case VariancePop(e @ StringType()) => VariancePop(Cast(e, DoubleType)) + case VarianceSamp(e @ StringType()) => VarianceSamp(Cast(e, DoubleType)) + case Skewness(e @ StringType()) => Skewness(Cast(e, DoubleType)) + case Kurtosis(e @ StringType()) => Kurtosis(Cast(e, DoubleType)) } } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/CentralMomentAgg.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/CentralMomentAgg.scala index 30f602227b..9d2db45144 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/CentralMomentAgg.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/CentralMomentAgg.scala @@ -17,10 +17,8 @@ package org.apache.spark.sql.catalyst.expressions.aggregate -import org.apache.spark.sql.catalyst.InternalRow -import org.apache.spark.sql.catalyst.analysis.TypeCheckResult +import org.apache.spark.sql.catalyst.dsl.expressions._ import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.util.TypeUtils import org.apache.spark.sql.types._ /** @@ -44,7 +42,7 @@ import org.apache.spark.sql.types._ * * @param child to compute central moments of. */ -abstract class CentralMomentAgg(child: Expression) extends ImperativeAggregate with Serializable { +abstract class CentralMomentAgg(child: Expression) extends DeclarativeAggregate { /** * The central moment order to be computed. @@ -52,178 +50,161 @@ abstract class CentralMomentAgg(child: Expression) extends ImperativeAggregate w protected def momentOrder: Int override def children: Seq[Expression] = Seq(child) - override def nullable: Boolean = true - override def dataType: DataType = DoubleType + override def inputTypes: Seq[AbstractDataType] = Seq(DoubleType) - override def inputTypes: Seq[AbstractDataType] = Seq(NumericType) + protected val n = AttributeReference("n", DoubleType, nullable = false)() + protected val avg = AttributeReference("avg", DoubleType, nullable = false)() + protected val m2 = AttributeReference("m2", DoubleType, nullable = false)() + protected val m3 = AttributeReference("m3", DoubleType, nullable = false)() + protected val m4 = AttributeReference("m4", DoubleType, nullable = false)() - override def checkInputDataTypes(): TypeCheckResult = - TypeUtils.checkForNumericExpr(child.dataType, s"function $prettyName") + private def trimHigherOrder[T](expressions: Seq[T]) = expressions.take(momentOrder + 1) - override def aggBufferSchema: StructType = StructType.fromAttributes(aggBufferAttributes) + override val aggBufferAttributes = trimHigherOrder(Seq(n, avg, m2, m3, m4)) - /** - * Size of aggregation buffer. - */ - private[this] val bufferSize = 5 + override val initialValues: Seq[Expression] = Array.fill(momentOrder + 1)(Literal(0.0)) - override val aggBufferAttributes: Seq[AttributeReference] = Seq.tabulate(bufferSize) { i => - AttributeReference(s"M$i", DoubleType)() + override val updateExpressions: Seq[Expression] = { + val newN = n + Literal(1.0) + val delta = child - avg + val deltaN = delta / newN + val newAvg = avg + deltaN + val newM2 = m2 + delta * (delta - deltaN) + + val delta2 = delta * delta + val deltaN2 = deltaN * deltaN + val newM3 = if (momentOrder >= 3) { + m3 - Literal(3.0) * deltaN * newM2 + delta * (delta2 - deltaN2) + } else { + Literal(0.0) + } + val newM4 = if (momentOrder >= 4) { + m4 - Literal(4.0) * deltaN * newM3 - Literal(6.0) * deltaN2 * newM2 + + delta * (delta * delta2 - deltaN * deltaN2) + } else { + Literal(0.0) + } + + trimHigherOrder(Seq( + If(IsNull(child), n, newN), + If(IsNull(child), avg, newAvg), + If(IsNull(child), m2, newM2), + If(IsNull(child), m3, newM3), + If(IsNull(child), m4, newM4) + )) } - // Note: although this simply copies aggBufferAttributes, this common code can not be placed - // in the superclass because that will lead to initialization ordering issues. - override val inputAggBufferAttributes: Seq[AttributeReference] = - aggBufferAttributes.map(_.newInstance()) - - // buffer offsets - private[this] val nOffset = mutableAggBufferOffset - private[this] val meanOffset = mutableAggBufferOffset + 1 - private[this] val secondMomentOffset = mutableAggBufferOffset + 2 - private[this] val thirdMomentOffset = mutableAggBufferOffset + 3 - private[this] val fourthMomentOffset = mutableAggBufferOffset + 4 - - // frequently used values for online updates - private[this] var delta = 0.0 - private[this] var deltaN = 0.0 - private[this] var delta2 = 0.0 - private[this] var deltaN2 = 0.0 - private[this] var n = 0.0 - private[this] var mean = 0.0 - private[this] var m2 = 0.0 - private[this] var m3 = 0.0 - private[this] var m4 = 0.0 + override val mergeExpressions: Seq[Expression] = { - /** - * Initialize all moments to zero. - */ - override def initialize(buffer: MutableRow): Unit = { - for (aggIndex <- 0 until bufferSize) { - buffer.setDouble(mutableAggBufferOffset + aggIndex, 0.0) + val n1 = n.left + val n2 = n.right + val newN = n1 + n2 + val delta = avg.right - avg.left + val deltaN = If(newN === Literal(0.0), Literal(0.0), delta / newN) + val newAvg = avg.left + deltaN * n2 + + // higher order moments computed according to: + // https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Higher-order_statistics + val newM2 = m2.left + m2.right + delta * deltaN * n1 * n2 + // `m3.right` is not available if momentOrder < 3 + val newM3 = if (momentOrder >= 3) { + m3.left + m3.right + deltaN * deltaN * delta * n1 * n2 * (n1 - n2) + + Literal(3.0) * deltaN * (n1 * m2.right - n2 * m2.left) + } else { + Literal(0.0) } + // `m4.right` is not available if momentOrder < 4 + val newM4 = if (momentOrder >= 4) { + m4.left + m4.right + + deltaN * deltaN * deltaN * delta * n1 * n2 * (n1 * n1 - n1 * n2 + n2 * n2) + + Literal(6.0) * deltaN * deltaN * (n1 * n1 * m2.right + n2 * n2 * m2.left) + + Literal(4.0) * deltaN * (n1 * m3.right - n2 * m3.left) + } else { + Literal(0.0) + } + + trimHigherOrder(Seq(newN, newAvg, newM2, newM3, newM4)) } +} - /** - * Update the central moments buffer. - */ - override def update(buffer: MutableRow, input: InternalRow): Unit = { - val v = Cast(child, DoubleType).eval(input) - if (v != null) { - val updateValue = v match { - case d: Double => d - } - - n = buffer.getDouble(nOffset) - mean = buffer.getDouble(meanOffset) - - n += 1.0 - buffer.setDouble(nOffset, n) - delta = updateValue - mean - deltaN = delta / n - mean += deltaN - buffer.setDouble(meanOffset, mean) - - if (momentOrder >= 2) { - m2 = buffer.getDouble(secondMomentOffset) - m2 += delta * (delta - deltaN) - buffer.setDouble(secondMomentOffset, m2) - } - - if (momentOrder >= 3) { - delta2 = delta * delta - deltaN2 = deltaN * deltaN - m3 = buffer.getDouble(thirdMomentOffset) - m3 += -3.0 * deltaN * m2 + delta * (delta2 - deltaN2) - buffer.setDouble(thirdMomentOffset, m3) - } - - if (momentOrder >= 4) { - m4 = buffer.getDouble(fourthMomentOffset) - m4 += -4.0 * deltaN * m3 - 6.0 * deltaN2 * m2 + - delta * (delta * delta2 - deltaN * deltaN2) - buffer.setDouble(fourthMomentOffset, m4) - } - } +// Compute the population standard deviation of a column +case class StddevPop(child: Expression) extends CentralMomentAgg(child) { + + override protected def momentOrder = 2 + + override val evaluateExpression: Expression = { + If(n === Literal(0.0), Literal.create(null, DoubleType), + Sqrt(m2 / n)) } - /** - * Merge two central moment buffers. - */ - override def merge(buffer1: MutableRow, buffer2: InternalRow): Unit = { - val n1 = buffer1.getDouble(nOffset) - val n2 = buffer2.getDouble(inputAggBufferOffset) - val mean1 = buffer1.getDouble(meanOffset) - val mean2 = buffer2.getDouble(inputAggBufferOffset + 1) + override def prettyName: String = "stddev_pop" +} + +// Compute the sample standard deviation of a column +case class StddevSamp(child: Expression) extends CentralMomentAgg(child) { + + override protected def momentOrder = 2 - var secondMoment1 = 0.0 - var secondMoment2 = 0.0 + override val evaluateExpression: Expression = { + If(n === Literal(0.0), Literal.create(null, DoubleType), + If(n === Literal(1.0), Literal(Double.NaN), + Sqrt(m2 / (n - Literal(1.0))))) + } - var thirdMoment1 = 0.0 - var thirdMoment2 = 0.0 + override def prettyName: String = "stddev_samp" +} - var fourthMoment1 = 0.0 - var fourthMoment2 = 0.0 +// Compute the population variance of a column +case class VariancePop(child: Expression) extends CentralMomentAgg(child) { - n = n1 + n2 - buffer1.setDouble(nOffset, n) - delta = mean2 - mean1 - deltaN = if (n == 0.0) 0.0 else delta / n - mean = mean1 + deltaN * n2 - buffer1.setDouble(mutableAggBufferOffset + 1, mean) + override protected def momentOrder = 2 - // higher order moments computed according to: - // https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Higher-order_statistics - if (momentOrder >= 2) { - secondMoment1 = buffer1.getDouble(secondMomentOffset) - secondMoment2 = buffer2.getDouble(inputAggBufferOffset + 2) - m2 = secondMoment1 + secondMoment2 + delta * deltaN * n1 * n2 - buffer1.setDouble(secondMomentOffset, m2) - } + override val evaluateExpression: Expression = { + If(n === Literal(0.0), Literal.create(null, DoubleType), + m2 / n) + } - if (momentOrder >= 3) { - thirdMoment1 = buffer1.getDouble(thirdMomentOffset) - thirdMoment2 = buffer2.getDouble(inputAggBufferOffset + 3) - m3 = thirdMoment1 + thirdMoment2 + deltaN * deltaN * delta * n1 * n2 * - (n1 - n2) + 3.0 * deltaN * (n1 * secondMoment2 - n2 * secondMoment1) - buffer1.setDouble(thirdMomentOffset, m3) - } + override def prettyName: String = "var_pop" +} - if (momentOrder >= 4) { - fourthMoment1 = buffer1.getDouble(fourthMomentOffset) - fourthMoment2 = buffer2.getDouble(inputAggBufferOffset + 4) - m4 = fourthMoment1 + fourthMoment2 + deltaN * deltaN * deltaN * delta * n1 * - n2 * (n1 * n1 - n1 * n2 + n2 * n2) + deltaN * deltaN * 6.0 * - (n1 * n1 * secondMoment2 + n2 * n2 * secondMoment1) + - 4.0 * deltaN * (n1 * thirdMoment2 - n2 * thirdMoment1) - buffer1.setDouble(fourthMomentOffset, m4) - } +// Compute the sample variance of a column +case class VarianceSamp(child: Expression) extends CentralMomentAgg(child) { + + override protected def momentOrder = 2 + + override val evaluateExpression: Expression = { + If(n === Literal(0.0), Literal.create(null, DoubleType), + If(n === Literal(1.0), Literal(Double.NaN), + m2 / (n - Literal(1.0)))) } - /** - * Compute aggregate statistic from sufficient moments. - * @param centralMoments Length `momentOrder + 1` array of central moments (un-normalized) - * needed to compute the aggregate stat. - */ - def getStatistic(n: Double, mean: Double, centralMoments: Array[Double]): Any - - override final def eval(buffer: InternalRow): Any = { - val n = buffer.getDouble(nOffset) - val mean = buffer.getDouble(meanOffset) - val moments = Array.ofDim[Double](momentOrder + 1) - moments(0) = 1.0 - moments(1) = 0.0 - if (momentOrder >= 2) { - moments(2) = buffer.getDouble(secondMomentOffset) - } - if (momentOrder >= 3) { - moments(3) = buffer.getDouble(thirdMomentOffset) - } - if (momentOrder >= 4) { - moments(4) = buffer.getDouble(fourthMomentOffset) - } + override def prettyName: String = "var_samp" +} + +case class Skewness(child: Expression) extends CentralMomentAgg(child) { + + override def prettyName: String = "skewness" + + override protected def momentOrder = 3 - getStatistic(n, mean, moments) + override val evaluateExpression: Expression = { + If(n === Literal(0.0), Literal.create(null, DoubleType), + If(m2 === Literal(0.0), Literal(Double.NaN), + Sqrt(n) * m3 / Sqrt(m2 * m2 * m2))) } } + +case class Kurtosis(child: Expression) extends CentralMomentAgg(child) { + + override protected def momentOrder = 4 + + override val evaluateExpression: Expression = { + If(n === Literal(0.0), Literal.create(null, DoubleType), + If(m2 === Literal(0.0), Literal(Double.NaN), + n * m4 / (m2 * m2) - Literal(3.0))) + } + + override def prettyName: String = "kurtosis" +} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Corr.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Corr.scala index d25f3335ff..e6b8214ef2 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Corr.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Corr.scala @@ -17,8 +17,7 @@ package org.apache.spark.sql.catalyst.expressions.aggregate -import org.apache.spark.sql.catalyst.InternalRow -import org.apache.spark.sql.catalyst.analysis.TypeCheckResult +import org.apache.spark.sql.catalyst.dsl.expressions._ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.types._ @@ -29,165 +28,70 @@ import org.apache.spark.sql.types._ * Definition of Pearson correlation can be found at * http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient */ -case class Corr( - left: Expression, - right: Expression, - mutableAggBufferOffset: Int = 0, - inputAggBufferOffset: Int = 0) - extends ImperativeAggregate { - - def this(left: Expression, right: Expression) = - this(left, right, mutableAggBufferOffset = 0, inputAggBufferOffset = 0) - - override def children: Seq[Expression] = Seq(left, right) +case class Corr(x: Expression, y: Expression) extends DeclarativeAggregate { + override def children: Seq[Expression] = Seq(x, y) override def nullable: Boolean = true - override def dataType: DataType = DoubleType - override def inputTypes: Seq[AbstractDataType] = Seq(DoubleType, DoubleType) - override def checkInputDataTypes(): TypeCheckResult = { - if (left.dataType.isInstanceOf[DoubleType] && right.dataType.isInstanceOf[DoubleType]) { - TypeCheckResult.TypeCheckSuccess - } else { - TypeCheckResult.TypeCheckFailure( - s"corr requires that both arguments are double type, " + - s"not (${left.dataType}, ${right.dataType}).") - } + protected val n = AttributeReference("n", DoubleType, nullable = false)() + protected val xAvg = AttributeReference("xAvg", DoubleType, nullable = false)() + protected val yAvg = AttributeReference("yAvg", DoubleType, nullable = false)() + protected val ck = AttributeReference("ck", DoubleType, nullable = false)() + protected val xMk = AttributeReference("xMk", DoubleType, nullable = false)() + protected val yMk = AttributeReference("yMk", DoubleType, nullable = false)() + + override val aggBufferAttributes: Seq[AttributeReference] = Seq(n, xAvg, yAvg, ck, xMk, yMk) + + override val initialValues: Seq[Expression] = Array.fill(6)(Literal(0.0)) + + override val updateExpressions: Seq[Expression] = { + val newN = n + Literal(1.0) + val dx = x - xAvg + val dxN = dx / newN + val dy = y - yAvg + val dyN = dy / newN + val newXAvg = xAvg + dxN + val newYAvg = yAvg + dyN + val newCk = ck + dx * (y - newYAvg) + val newXMk = xMk + dx * (x - newXAvg) + val newYMk = yMk + dy * (y - newYAvg) + + val isNull = IsNull(x) || IsNull(y) + Seq( + If(isNull, n, newN), + If(isNull, xAvg, newXAvg), + If(isNull, yAvg, newYAvg), + If(isNull, ck, newCk), + If(isNull, xMk, newXMk), + If(isNull, yMk, newYMk) + ) } - override def aggBufferSchema: StructType = StructType.fromAttributes(aggBufferAttributes) - - override def inputAggBufferAttributes: Seq[AttributeReference] = { - aggBufferAttributes.map(_.newInstance()) + override val mergeExpressions: Seq[Expression] = { + + val n1 = n.left + val n2 = n.right + val newN = n1 + n2 + val dx = xAvg.right - xAvg.left + val dxN = If(newN === Literal(0.0), Literal(0.0), dx / newN) + val dy = yAvg.right - yAvg.left + val dyN = If(newN === Literal(0.0), Literal(0.0), dy / newN) + val newXAvg = xAvg.left + dxN * n2 + val newYAvg = yAvg.left + dyN * n2 + val newCk = ck.left + ck.right + dx * dyN * n1 * n2 + val newXMk = xMk.left + xMk.right + dx * dxN * n1 * n2 + val newYMk = yMk.left + yMk.right + dy * dyN * n1 * n2 + + Seq(newN, newXAvg, newYAvg, newCk, newXMk, newYMk) } - override val aggBufferAttributes: Seq[AttributeReference] = Seq( - AttributeReference("xAvg", DoubleType)(), - AttributeReference("yAvg", DoubleType)(), - AttributeReference("Ck", DoubleType)(), - AttributeReference("MkX", DoubleType)(), - AttributeReference("MkY", DoubleType)(), - AttributeReference("count", LongType)()) - - // Local cache of mutableAggBufferOffset(s) that will be used in update and merge - private[this] val mutableAggBufferOffsetPlus1 = mutableAggBufferOffset + 1 - private[this] val mutableAggBufferOffsetPlus2 = mutableAggBufferOffset + 2 - private[this] val mutableAggBufferOffsetPlus3 = mutableAggBufferOffset + 3 - private[this] val mutableAggBufferOffsetPlus4 = mutableAggBufferOffset + 4 - private[this] val mutableAggBufferOffsetPlus5 = mutableAggBufferOffset + 5 - - // Local cache of inputAggBufferOffset(s) that will be used in update and merge - private[this] val inputAggBufferOffsetPlus1 = inputAggBufferOffset + 1 - private[this] val inputAggBufferOffsetPlus2 = inputAggBufferOffset + 2 - private[this] val inputAggBufferOffsetPlus3 = inputAggBufferOffset + 3 - private[this] val inputAggBufferOffsetPlus4 = inputAggBufferOffset + 4 - private[this] val inputAggBufferOffsetPlus5 = inputAggBufferOffset + 5 - - override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): ImperativeAggregate = - copy(mutableAggBufferOffset = newMutableAggBufferOffset) - - override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): ImperativeAggregate = - copy(inputAggBufferOffset = newInputAggBufferOffset) - - override def initialize(buffer: MutableRow): Unit = { - buffer.setDouble(mutableAggBufferOffset, 0.0) - buffer.setDouble(mutableAggBufferOffsetPlus1, 0.0) - buffer.setDouble(mutableAggBufferOffsetPlus2, 0.0) - buffer.setDouble(mutableAggBufferOffsetPlus3, 0.0) - buffer.setDouble(mutableAggBufferOffsetPlus4, 0.0) - buffer.setLong(mutableAggBufferOffsetPlus5, 0L) + override val evaluateExpression: Expression = { + If(n === Literal(0.0), Literal.create(null, DoubleType), + If(n === Literal(1.0), Literal(Double.NaN), + ck / Sqrt(xMk * yMk))) } - override def update(buffer: MutableRow, input: InternalRow): Unit = { - val leftEval = left.eval(input) - val rightEval = right.eval(input) - - if (leftEval != null && rightEval != null) { - val x = leftEval.asInstanceOf[Double] - val y = rightEval.asInstanceOf[Double] - - var xAvg = buffer.getDouble(mutableAggBufferOffset) - var yAvg = buffer.getDouble(mutableAggBufferOffsetPlus1) - var Ck = buffer.getDouble(mutableAggBufferOffsetPlus2) - var MkX = buffer.getDouble(mutableAggBufferOffsetPlus3) - var MkY = buffer.getDouble(mutableAggBufferOffsetPlus4) - var count = buffer.getLong(mutableAggBufferOffsetPlus5) - - val deltaX = x - xAvg - val deltaY = y - yAvg - count += 1 - xAvg += deltaX / count - yAvg += deltaY / count - Ck += deltaX * (y - yAvg) - MkX += deltaX * (x - xAvg) - MkY += deltaY * (y - yAvg) - - buffer.setDouble(mutableAggBufferOffset, xAvg) - buffer.setDouble(mutableAggBufferOffsetPlus1, yAvg) - buffer.setDouble(mutableAggBufferOffsetPlus2, Ck) - buffer.setDouble(mutableAggBufferOffsetPlus3, MkX) - buffer.setDouble(mutableAggBufferOffsetPlus4, MkY) - buffer.setLong(mutableAggBufferOffsetPlus5, count) - } - } - - // Merge counters from other partitions. Formula can be found at: - // http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance - override def merge(buffer1: MutableRow, buffer2: InternalRow): Unit = { - val count2 = buffer2.getLong(inputAggBufferOffsetPlus5) - - // We only go to merge two buffers if there is at least one record aggregated in buffer2. - // We don't need to check count in buffer1 because if count2 is more than zero, totalCount - // is more than zero too, then we won't get a divide by zero exception. - if (count2 > 0) { - var xAvg = buffer1.getDouble(mutableAggBufferOffset) - var yAvg = buffer1.getDouble(mutableAggBufferOffsetPlus1) - var Ck = buffer1.getDouble(mutableAggBufferOffsetPlus2) - var MkX = buffer1.getDouble(mutableAggBufferOffsetPlus3) - var MkY = buffer1.getDouble(mutableAggBufferOffsetPlus4) - var count = buffer1.getLong(mutableAggBufferOffsetPlus5) - - val xAvg2 = buffer2.getDouble(inputAggBufferOffset) - val yAvg2 = buffer2.getDouble(inputAggBufferOffsetPlus1) - val Ck2 = buffer2.getDouble(inputAggBufferOffsetPlus2) - val MkX2 = buffer2.getDouble(inputAggBufferOffsetPlus3) - val MkY2 = buffer2.getDouble(inputAggBufferOffsetPlus4) - - val totalCount = count + count2 - val deltaX = xAvg - xAvg2 - val deltaY = yAvg - yAvg2 - Ck += Ck2 + deltaX * deltaY * count / totalCount * count2 - xAvg = (xAvg * count + xAvg2 * count2) / totalCount - yAvg = (yAvg * count + yAvg2 * count2) / totalCount - MkX += MkX2 + deltaX * deltaX * count / totalCount * count2 - MkY += MkY2 + deltaY * deltaY * count / totalCount * count2 - count = totalCount - - buffer1.setDouble(mutableAggBufferOffset, xAvg) - buffer1.setDouble(mutableAggBufferOffsetPlus1, yAvg) - buffer1.setDouble(mutableAggBufferOffsetPlus2, Ck) - buffer1.setDouble(mutableAggBufferOffsetPlus3, MkX) - buffer1.setDouble(mutableAggBufferOffsetPlus4, MkY) - buffer1.setLong(mutableAggBufferOffsetPlus5, count) - } - } - - override def eval(buffer: InternalRow): Any = { - val count = buffer.getLong(mutableAggBufferOffsetPlus5) - if (count > 0) { - val Ck = buffer.getDouble(mutableAggBufferOffsetPlus2) - val MkX = buffer.getDouble(mutableAggBufferOffsetPlus3) - val MkY = buffer.getDouble(mutableAggBufferOffsetPlus4) - val corr = Ck / math.sqrt(MkX * MkY) - if (corr.isNaN) { - null - } else { - corr - } - } else { - null - } - } + override def prettyName: String = "corr" } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Covariance.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Covariance.scala index f53b01be2a..c175a8c4c7 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Covariance.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Covariance.scala @@ -17,182 +17,79 @@ package org.apache.spark.sql.catalyst.expressions.aggregate -import org.apache.spark.sql.catalyst.InternalRow -import org.apache.spark.sql.catalyst.analysis.TypeCheckResult +import org.apache.spark.sql.catalyst.dsl.expressions._ import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.util.TypeUtils import org.apache.spark.sql.types._ /** * Compute the covariance between two expressions. * When applied on empty data (i.e., count is zero), it returns NULL. - * */ -abstract class Covariance(left: Expression, right: Expression) extends ImperativeAggregate - with Serializable { - override def children: Seq[Expression] = Seq(left, right) +abstract class Covariance(x: Expression, y: Expression) extends DeclarativeAggregate { + override def children: Seq[Expression] = Seq(x, y) override def nullable: Boolean = true - override def dataType: DataType = DoubleType - override def inputTypes: Seq[AbstractDataType] = Seq(DoubleType, DoubleType) - override def checkInputDataTypes(): TypeCheckResult = { - if (left.dataType.isInstanceOf[DoubleType] && right.dataType.isInstanceOf[DoubleType]) { - TypeCheckResult.TypeCheckSuccess - } else { - TypeCheckResult.TypeCheckFailure( - s"covariance requires that both arguments are double type, " + - s"not (${left.dataType}, ${right.dataType}).") - } - } - - override def aggBufferSchema: StructType = StructType.fromAttributes(aggBufferAttributes) - - override def inputAggBufferAttributes: Seq[AttributeReference] = { - aggBufferAttributes.map(_.newInstance()) - } - - override val aggBufferAttributes: Seq[AttributeReference] = Seq( - AttributeReference("xAvg", DoubleType)(), - AttributeReference("yAvg", DoubleType)(), - AttributeReference("Ck", DoubleType)(), - AttributeReference("count", LongType)()) - - // Local cache of mutableAggBufferOffset(s) that will be used in update and merge - val xAvgOffset = mutableAggBufferOffset - val yAvgOffset = mutableAggBufferOffset + 1 - val CkOffset = mutableAggBufferOffset + 2 - val countOffset = mutableAggBufferOffset + 3 - - // Local cache of inputAggBufferOffset(s) that will be used in update and merge - val inputXAvgOffset = inputAggBufferOffset - val inputYAvgOffset = inputAggBufferOffset + 1 - val inputCkOffset = inputAggBufferOffset + 2 - val inputCountOffset = inputAggBufferOffset + 3 - - override def initialize(buffer: MutableRow): Unit = { - buffer.setDouble(xAvgOffset, 0.0) - buffer.setDouble(yAvgOffset, 0.0) - buffer.setDouble(CkOffset, 0.0) - buffer.setLong(countOffset, 0L) - } - - override def update(buffer: MutableRow, input: InternalRow): Unit = { - val leftEval = left.eval(input) - val rightEval = right.eval(input) - - if (leftEval != null && rightEval != null) { - val x = leftEval.asInstanceOf[Double] - val y = rightEval.asInstanceOf[Double] - - var xAvg = buffer.getDouble(xAvgOffset) - var yAvg = buffer.getDouble(yAvgOffset) - var Ck = buffer.getDouble(CkOffset) - var count = buffer.getLong(countOffset) - - val deltaX = x - xAvg - val deltaY = y - yAvg - count += 1 - xAvg += deltaX / count - yAvg += deltaY / count - Ck += deltaX * (y - yAvg) - - buffer.setDouble(xAvgOffset, xAvg) - buffer.setDouble(yAvgOffset, yAvg) - buffer.setDouble(CkOffset, Ck) - buffer.setLong(countOffset, count) - } + protected val n = AttributeReference("n", DoubleType, nullable = false)() + protected val xAvg = AttributeReference("xAvg", DoubleType, nullable = false)() + protected val yAvg = AttributeReference("yAvg", DoubleType, nullable = false)() + protected val ck = AttributeReference("ck", DoubleType, nullable = false)() + + override val aggBufferAttributes: Seq[AttributeReference] = Seq(n, xAvg, yAvg, ck) + + override val initialValues: Seq[Expression] = Array.fill(4)(Literal(0.0)) + + override lazy val updateExpressions: Seq[Expression] = { + val newN = n + Literal(1.0) + val dx = x - xAvg + val dy = y - yAvg + val dyN = dy / newN + val newXAvg = xAvg + dx / newN + val newYAvg = yAvg + dyN + val newCk = ck + dx * (y - newYAvg) + + val isNull = IsNull(x) || IsNull(y) + Seq( + If(isNull, n, newN), + If(isNull, xAvg, newXAvg), + If(isNull, yAvg, newYAvg), + If(isNull, ck, newCk) + ) } - // Merge counters from other partitions. Formula can be found at: - // http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance - override def merge(buffer1: MutableRow, buffer2: InternalRow): Unit = { - val count2 = buffer2.getLong(inputCountOffset) - - // We only go to merge two buffers if there is at least one record aggregated in buffer2. - // We don't need to check count in buffer1 because if count2 is more than zero, totalCount - // is more than zero too, then we won't get a divide by zero exception. - if (count2 > 0) { - var xAvg = buffer1.getDouble(xAvgOffset) - var yAvg = buffer1.getDouble(yAvgOffset) - var Ck = buffer1.getDouble(CkOffset) - var count = buffer1.getLong(countOffset) + override val mergeExpressions: Seq[Expression] = { - val xAvg2 = buffer2.getDouble(inputXAvgOffset) - val yAvg2 = buffer2.getDouble(inputYAvgOffset) - val Ck2 = buffer2.getDouble(inputCkOffset) + val n1 = n.left + val n2 = n.right + val newN = n1 + n2 + val dx = xAvg.right - xAvg.left + val dxN = If(newN === Literal(0.0), Literal(0.0), dx / newN) + val dy = yAvg.right - yAvg.left + val dyN = If(newN === Literal(0.0), Literal(0.0), dy / newN) + val newXAvg = xAvg.left + dxN * n2 + val newYAvg = yAvg.left + dyN * n2 + val newCk = ck.left + ck.right + dx * dyN * n1 * n2 - val totalCount = count + count2 - val deltaX = xAvg - xAvg2 - val deltaY = yAvg - yAvg2 - Ck += Ck2 + deltaX * deltaY * count / totalCount * count2 - xAvg = (xAvg * count + xAvg2 * count2) / totalCount - yAvg = (yAvg * count + yAvg2 * count2) / totalCount - count = totalCount - - buffer1.setDouble(xAvgOffset, xAvg) - buffer1.setDouble(yAvgOffset, yAvg) - buffer1.setDouble(CkOffset, Ck) - buffer1.setLong(countOffset, count) - } + Seq(newN, newXAvg, newYAvg, newCk) } } -case class CovSample( - left: Expression, - right: Expression, - mutableAggBufferOffset: Int = 0, - inputAggBufferOffset: Int = 0) - extends Covariance(left, right) { - - override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): ImperativeAggregate = - copy(mutableAggBufferOffset = newMutableAggBufferOffset) - - override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): ImperativeAggregate = - copy(inputAggBufferOffset = newInputAggBufferOffset) - - override def eval(buffer: InternalRow): Any = { - val count = buffer.getLong(countOffset) - if (count > 1) { - val Ck = buffer.getDouble(CkOffset) - val cov = Ck / (count - 1) - if (cov.isNaN) { - null - } else { - cov - } - } else { - null - } +case class CovPopulation(left: Expression, right: Expression) extends Covariance(left, right) { + override val evaluateExpression: Expression = { + If(n === Literal(0.0), Literal.create(null, DoubleType), + ck / n) } + override def prettyName: String = "covar_pop" } -case class CovPopulation( - left: Expression, - right: Expression, - mutableAggBufferOffset: Int = 0, - inputAggBufferOffset: Int = 0) - extends Covariance(left, right) { - - override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): ImperativeAggregate = - copy(mutableAggBufferOffset = newMutableAggBufferOffset) - - override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): ImperativeAggregate = - copy(inputAggBufferOffset = newInputAggBufferOffset) - override def eval(buffer: InternalRow): Any = { - val count = buffer.getLong(countOffset) - if (count > 0) { - val Ck = buffer.getDouble(CkOffset) - if (Ck.isNaN) { - null - } else { - Ck / count - } - } else { - null - } +case class CovSample(left: Expression, right: Expression) extends Covariance(left, right) { + override val evaluateExpression: Expression = { + If(n === Literal(0.0), Literal.create(null, DoubleType), + If(n === Literal(1.0), Literal(Double.NaN), + ck / (n - Literal(1.0)))) } + override def prettyName: String = "covar_samp" } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Kurtosis.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Kurtosis.scala deleted file mode 100644 index c2bf2cb941..0000000000 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Kurtosis.scala +++ /dev/null @@ -1,54 +0,0 @@ -/* - * 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.aggregate - -import org.apache.spark.sql.catalyst.expressions._ - -case class Kurtosis(child: Expression, - mutableAggBufferOffset: Int = 0, - inputAggBufferOffset: Int = 0) - extends CentralMomentAgg(child) { - - def this(child: Expression) = this(child, mutableAggBufferOffset = 0, inputAggBufferOffset = 0) - - override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): ImperativeAggregate = - copy(mutableAggBufferOffset = newMutableAggBufferOffset) - - override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): ImperativeAggregate = - copy(inputAggBufferOffset = newInputAggBufferOffset) - - override def prettyName: String = "kurtosis" - - override protected val momentOrder = 4 - - // NOTE: this is the formula for excess kurtosis, which is default for R and SciPy - override def getStatistic(n: Double, mean: Double, moments: Array[Double]): Any = { - require(moments.length == momentOrder + 1, - s"$prettyName requires ${momentOrder + 1} central moments, received: ${moments.length}") - val m2 = moments(2) - val m4 = moments(4) - - if (n == 0.0) { - null - } else if (m2 == 0.0) { - Double.NaN - } else { - n * m4 / (m2 * m2) - 3.0 - } - } -} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Skewness.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Skewness.scala deleted file mode 100644 index 9411bcea25..0000000000 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Skewness.scala +++ /dev/null @@ -1,53 +0,0 @@ -/* - * 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.aggregate - -import org.apache.spark.sql.catalyst.expressions._ - -case class Skewness(child: Expression, - mutableAggBufferOffset: Int = 0, - inputAggBufferOffset: Int = 0) - extends CentralMomentAgg(child) { - - def this(child: Expression) = this(child, mutableAggBufferOffset = 0, inputAggBufferOffset = 0) - - override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): ImperativeAggregate = - copy(mutableAggBufferOffset = newMutableAggBufferOffset) - - override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): ImperativeAggregate = - copy(inputAggBufferOffset = newInputAggBufferOffset) - - override def prettyName: String = "skewness" - - override protected val momentOrder = 3 - - override def getStatistic(n: Double, mean: Double, moments: Array[Double]): Any = { - require(moments.length == momentOrder + 1, - s"$prettyName requires ${momentOrder + 1} central moments, received: ${moments.length}") - val m2 = moments(2) - val m3 = moments(3) - - if (n == 0.0) { - null - } else if (m2 == 0.0) { - Double.NaN - } else { - math.sqrt(n) * m3 / math.sqrt(m2 * m2 * m2) - } - } -} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Stddev.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Stddev.scala deleted file mode 100644 index eec79a9033..0000000000 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Stddev.scala +++ /dev/null @@ -1,81 +0,0 @@ -/* - * 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.aggregate - -import org.apache.spark.sql.catalyst.expressions._ - -case class StddevSamp(child: Expression, - mutableAggBufferOffset: Int = 0, - inputAggBufferOffset: Int = 0) - extends CentralMomentAgg(child) { - - def this(child: Expression) = this(child, mutableAggBufferOffset = 0, inputAggBufferOffset = 0) - - override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): ImperativeAggregate = - copy(mutableAggBufferOffset = newMutableAggBufferOffset) - - override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): ImperativeAggregate = - copy(inputAggBufferOffset = newInputAggBufferOffset) - - override def prettyName: String = "stddev_samp" - - override protected val momentOrder = 2 - - override def getStatistic(n: Double, mean: Double, moments: Array[Double]): Any = { - require(moments.length == momentOrder + 1, - s"$prettyName requires ${momentOrder + 1} central moment, received: ${moments.length}") - - if (n == 0.0) { - null - } else if (n == 1.0) { - Double.NaN - } else { - math.sqrt(moments(2) / (n - 1.0)) - } - } -} - -case class StddevPop( - child: Expression, - mutableAggBufferOffset: Int = 0, - inputAggBufferOffset: Int = 0) - extends CentralMomentAgg(child) { - - def this(child: Expression) = this(child, mutableAggBufferOffset = 0, inputAggBufferOffset = 0) - - override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): ImperativeAggregate = - copy(mutableAggBufferOffset = newMutableAggBufferOffset) - - override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): ImperativeAggregate = - copy(inputAggBufferOffset = newInputAggBufferOffset) - - override def prettyName: String = "stddev_pop" - - override protected val momentOrder = 2 - - override def getStatistic(n: Double, mean: Double, moments: Array[Double]): Any = { - require(moments.length == momentOrder + 1, - s"$prettyName requires ${momentOrder + 1} central moment, received: ${moments.length}") - - if (n == 0.0) { - null - } else { - math.sqrt(moments(2) / n) - } - } -} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Variance.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Variance.scala deleted file mode 100644 index cf3a740305..0000000000 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Variance.scala +++ /dev/null @@ -1,81 +0,0 @@ -/* - * 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.aggregate - -import org.apache.spark.sql.catalyst.expressions._ - -case class VarianceSamp(child: Expression, - mutableAggBufferOffset: Int = 0, - inputAggBufferOffset: Int = 0) - extends CentralMomentAgg(child) { - - def this(child: Expression) = this(child, mutableAggBufferOffset = 0, inputAggBufferOffset = 0) - - override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): ImperativeAggregate = - copy(mutableAggBufferOffset = newMutableAggBufferOffset) - - override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): ImperativeAggregate = - copy(inputAggBufferOffset = newInputAggBufferOffset) - - override def prettyName: String = "var_samp" - - override protected val momentOrder = 2 - - override def getStatistic(n: Double, mean: Double, moments: Array[Double]): Any = { - require(moments.length == momentOrder + 1, - s"$prettyName requires ${momentOrder + 1} central moment, received: ${moments.length}") - - if (n == 0.0) { - null - } else if (n == 1.0) { - Double.NaN - } else { - moments(2) / (n - 1.0) - } - } -} - -case class VariancePop( - child: Expression, - mutableAggBufferOffset: Int = 0, - inputAggBufferOffset: Int = 0) - extends CentralMomentAgg(child) { - - def this(child: Expression) = this(child, mutableAggBufferOffset = 0, inputAggBufferOffset = 0) - - override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): ImperativeAggregate = - copy(mutableAggBufferOffset = newMutableAggBufferOffset) - - override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): ImperativeAggregate = - copy(inputAggBufferOffset = newInputAggBufferOffset) - - override def prettyName: String = "var_pop" - - override protected val momentOrder = 2 - - override def getStatistic(n: Double, mean: Double, moments: Array[Double]): Any = { - require(moments.length == momentOrder + 1, - s"$prettyName requires ${momentOrder + 1} central moment, received: ${moments.length}") - - if (n == 0.0) { - null - } else { - moments(2) / n - } - } -} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/misc.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/misc.scala index 36e1fa1176..f4ccadd9c5 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/misc.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/misc.scala @@ -424,3 +424,21 @@ case class Murmur3Hash(children: Seq[Expression], seed: Int) extends Expression } } } + +/** + * Print the result of an expression to stderr (used for debugging codegen). + */ +case class PrintToStderr(child: Expression) extends UnaryExpression { + + override def dataType: DataType = child.dataType + + protected override def nullSafeEval(input: Any): Any = input + + override def genCode(ctx: CodegenContext, ev: ExprCode): String = { + nullSafeCodeGen(ctx, ev, c => + s""" + | System.err.println("Result of ${child.simpleString} is " + $c); + | ${ev.value} = $c; + """.stripMargin) + } +} 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 index 26a7340f1a..84154a47de 100644 --- 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 @@ -198,7 +198,8 @@ case class Window( functions, ordinal, child.output, - (expressions, schema) => newMutableProjection(expressions, schema)) + (expressions, schema) => + newMutableProjection(expressions, schema, subexpressionEliminationEnabled)) // Create the factory val factory = key match { @@ -210,7 +211,8 @@ case class Window( ordinal, functions, child.output, - (expressions, schema) => newMutableProjection(expressions, schema), + (expressions, schema) => + newMutableProjection(expressions, schema, subexpressionEliminationEnabled), offset) // Growing Frame. diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TungstenAggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TungstenAggregate.scala index 57db7262fd..a8a81d6d65 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TungstenAggregate.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TungstenAggregate.scala @@ -240,7 +240,6 @@ case class TungstenAggregate( | ${bufVars(i).value} = ${ev.value}; """.stripMargin } - s""" | // do aggregate | ${aggVals.map(_.code).mkString("\n")} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/BenchmarkWholeStageCodegen.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/BenchmarkWholeStageCodegen.scala index 2f09c8a114..1ccf0e3d06 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/BenchmarkWholeStageCodegen.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/BenchmarkWholeStageCodegen.scala @@ -59,6 +59,55 @@ class BenchmarkWholeStageCodegen extends SparkFunSuite { benchmark.run() } + def testStatFunctions(values: Int): Unit = { + + val benchmark = new Benchmark("stat functions", values) + + benchmark.addCase("stddev w/o codegen") { iter => + sqlContext.setConf("spark.sql.codegen.wholeStage", "false") + sqlContext.range(values).groupBy().agg("id" -> "stddev").collect() + } + + benchmark.addCase("stddev w codegen") { iter => + sqlContext.setConf("spark.sql.codegen.wholeStage", "true") + sqlContext.range(values).groupBy().agg("id" -> "stddev").collect() + } + + benchmark.addCase("kurtosis w/o codegen") { iter => + sqlContext.setConf("spark.sql.codegen.wholeStage", "false") + sqlContext.range(values).groupBy().agg("id" -> "kurtosis").collect() + } + + benchmark.addCase("kurtosis w codegen") { iter => + sqlContext.setConf("spark.sql.codegen.wholeStage", "true") + sqlContext.range(values).groupBy().agg("id" -> "kurtosis").collect() + } + + + /** + Using ImperativeAggregate (as implemented in Spark 1.6): + + Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz + stddev: Avg Time(ms) Avg Rate(M/s) Relative Rate + ------------------------------------------------------------------------------- + stddev w/o codegen 2019.04 10.39 1.00 X + stddev w codegen 2097.29 10.00 0.96 X + kurtosis w/o codegen 2108.99 9.94 0.96 X + kurtosis w codegen 2090.69 10.03 0.97 X + + Using DeclarativeAggregate: + + Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz + stddev: Avg Time(ms) Avg Rate(M/s) Relative Rate + ------------------------------------------------------------------------------- + stddev w/o codegen 989.22 21.20 1.00 X + stddev w codegen 352.35 59.52 2.81 X + kurtosis w/o codegen 3636.91 5.77 0.27 X + kurtosis w codegen 369.25 56.79 2.68 X + */ + benchmark.run() + } + def testAggregateWithKey(values: Int): Unit = { val benchmark = new Benchmark("Aggregate with keys", values) @@ -147,8 +196,10 @@ class BenchmarkWholeStageCodegen extends SparkFunSuite { benchmark.run() } - test("benchmark") { - // testWholeStage(1024 * 1024 * 200) + // These benchmark are skipped in normal build + ignore("benchmark") { + // testWholeStage(200 << 20) + // testStddev(20 << 20) // testAggregateWithKey(20 << 20) // testBytesToBytesMap(1024 * 1024 * 50) } 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 554d47d651..61b73fa557 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 @@ -325,6 +325,9 @@ class HiveCompatibilitySuite extends HiveQueryFileTest with BeforeAndAfter { "drop_partitions_ignore_protection", "protectmode", + // Hive returns null rather than NaN when n = 1 + "udaf_covar_samp", + // Spark parser treats numerical literals differently: it creates decimals instead of doubles. "udf_abs", "udf_format_number", @@ -881,7 +884,6 @@ class HiveCompatibilitySuite extends HiveQueryFileTest with BeforeAndAfter { "type_widening", "udaf_collect_set", "udaf_covar_pop", - "udaf_covar_samp", "udaf_histogram_numeric", "udf2", "udf5", diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala index 7a9ed1eaf3..caf1db9ad0 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala @@ -798,7 +798,7 @@ abstract class AggregationQuerySuite extends QueryTest with SQLTestUtils with Te """ |SELECT corr(b, c) FROM covar_tab WHERE a = 3 """.stripMargin), - Row(null) :: Nil) + Row(Double.NaN) :: Nil) checkAnswer( sqlContext.sql( @@ -807,10 +807,10 @@ abstract class AggregationQuerySuite extends QueryTest with SQLTestUtils with Te """.stripMargin), Row(1, null) :: Row(2, null) :: - Row(3, null) :: - Row(4, null) :: - Row(5, null) :: - Row(6, null) :: Nil) + Row(3, Double.NaN) :: + Row(4, Double.NaN) :: + Row(5, Double.NaN) :: + Row(6, Double.NaN) :: Nil) val corr7 = sqlContext.sql("SELECT corr(b, c) FROM covar_tab").collect()(0).getDouble(0) assert(math.abs(corr7 - 0.6633880657639323) < 1e-12) @@ -841,11 +841,8 @@ abstract class AggregationQuerySuite extends QueryTest with SQLTestUtils with Te // one row test val df3 = Seq.tabulate(1)(x => (1 * x, x * x * x - 2)).toDF("a", "b") - val cov_samp3 = df3.groupBy().agg(covar_samp("a", "b")).collect()(0).get(0) - assert(cov_samp3 == null) - - val cov_pop3 = df3.groupBy().agg(covar_pop("a", "b")).collect()(0).getDouble(0) - assert(cov_pop3 == 0.0) + checkAnswer(df3.groupBy().agg(covar_samp("a", "b")), Row(Double.NaN)) + checkAnswer(df3.groupBy().agg(covar_pop("a", "b")), Row(0.0)) } test("no aggregation function (SPARK-11486)") { -- cgit v1.2.3