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[SPARK-8280][SPARK-8281][SQL]Handle NaN, null and Infinity in math
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JIRA:
https://issues.apache.org/jira/browse/SPARK-8280
https://issues.apache.org/jira/browse/SPARK-8281

Author: Yijie Shen <henry.yijieshen@gmail.com>

Closes apache#7451 from yijieshen/nan_null2 and squashes the following commits:

47a529d [Yijie Shen] style fix
63dee44 [Yijie Shen] handle log expressions similar to Hive
188be51 [Yijie Shen] null to nan in Math Expression
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yjshen authored and rxin committed Jul 18, 2015
1 parent 1707238 commit 529a2c2
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Showing 5 changed files with 157 additions and 63 deletions.
Original file line number Diff line number Diff line change
Expand Up @@ -112,9 +112,9 @@ object FunctionRegistry {
expression[Log]("ln"),
expression[Log10]("log10"),
expression[Log1p]("log1p"),
expression[Log2]("log2"),
expression[UnaryMinus]("negative"),
expression[Pi]("pi"),
expression[Log2]("log2"),
expression[Pow]("pow"),
expression[Pow]("power"),
expression[Pmod]("pmod"),
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -65,22 +65,38 @@ abstract class UnaryMathExpression(f: Double => Double, name: String)
override def toString: String = s"$name($child)"

protected override def nullSafeEval(input: Any): Any = {
val result = f(input.asInstanceOf[Double])
if (result.isNaN) null else result
f(input.asInstanceOf[Double])
}

// name of function in java.lang.Math
def funcName: String = name.toLowerCase

override def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): String = {
nullSafeCodeGen(ctx, ev, eval => {
defineCodeGen(ctx, ev, c => s"java.lang.Math.${funcName}($c)")
}
}

abstract class UnaryLogExpression(f: Double => Double, name: String)
extends UnaryMathExpression(f, name) { self: Product =>

// values less than or equal to yAsymptote eval to null in Hive, instead of NaN or -Infinity
protected val yAsymptote: Double = 0.0

protected override def nullSafeEval(input: Any): Any = {
val d = input.asInstanceOf[Double]
if (d <= yAsymptote) null else f(d)
}

override def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): String = {
nullSafeCodeGen(ctx, ev, c =>
s"""
${ev.primitive} = java.lang.Math.${funcName}($eval);
if (Double.valueOf(${ev.primitive}).isNaN()) {
if ($c <= $yAsymptote) {
${ev.isNull} = true;
} else {
${ev.primitive} = java.lang.Math.${funcName}($c);
}
"""
})
)
}
}

Expand All @@ -100,8 +116,7 @@ abstract class BinaryMathExpression(f: (Double, Double) => Double, name: String)
override def dataType: DataType = DoubleType

protected override def nullSafeEval(input1: Any, input2: Any): Any = {
val result = f(input1.asInstanceOf[Double], input2.asInstanceOf[Double])
if (result.isNaN) null else result
f(input1.asInstanceOf[Double], input2.asInstanceOf[Double])
}

override def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): String = {
Expand Down Expand Up @@ -398,25 +413,28 @@ case class Factorial(child: Expression) extends UnaryExpression with ImplicitCas
}
}

case class Log(child: Expression) extends UnaryMathExpression(math.log, "LOG")
case class Log(child: Expression) extends UnaryLogExpression(math.log, "LOG")

case class Log2(child: Expression)
extends UnaryMathExpression((x: Double) => math.log(x) / math.log(2), "LOG2") {
extends UnaryLogExpression((x: Double) => math.log(x) / math.log(2), "LOG2") {
override def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): String = {
nullSafeCodeGen(ctx, ev, eval => {
nullSafeCodeGen(ctx, ev, c =>
s"""
${ev.primitive} = java.lang.Math.log($eval) / java.lang.Math.log(2);
if (Double.valueOf(${ev.primitive}).isNaN()) {
if ($c <= $yAsymptote) {
${ev.isNull} = true;
} else {
${ev.primitive} = java.lang.Math.log($c) / java.lang.Math.log(2);
}
"""
})
)
}
}

case class Log10(child: Expression) extends UnaryMathExpression(math.log10, "LOG10")
case class Log10(child: Expression) extends UnaryLogExpression(math.log10, "LOG10")

case class Log1p(child: Expression) extends UnaryMathExpression(math.log1p, "LOG1P")
case class Log1p(child: Expression) extends UnaryLogExpression(math.log1p, "LOG1P") {
protected override val yAsymptote: Double = -1.0
}

case class Rint(child: Expression) extends UnaryMathExpression(math.rint, "ROUND") {
override def funcName: String = "rint"
Expand Down Expand Up @@ -577,27 +595,18 @@ case class Atan2(left: Expression, right: Expression)

protected override def nullSafeEval(input1: Any, input2: Any): Any = {
// With codegen, the values returned by -0.0 and 0.0 are different. Handled with +0.0
val result = math.atan2(input1.asInstanceOf[Double] + 0.0, input2.asInstanceOf[Double] + 0.0)
if (result.isNaN) null else result
math.atan2(input1.asInstanceOf[Double] + 0.0, input2.asInstanceOf[Double] + 0.0)
}

override def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): String = {
defineCodeGen(ctx, ev, (c1, c2) => s"java.lang.Math.atan2($c1 + 0.0, $c2 + 0.0)") + s"""
if (Double.valueOf(${ev.primitive}).isNaN()) {
${ev.isNull} = true;
}
"""
defineCodeGen(ctx, ev, (c1, c2) => s"java.lang.Math.atan2($c1 + 0.0, $c2 + 0.0)")
}
}

case class Pow(left: Expression, right: Expression)
extends BinaryMathExpression(math.pow, "POWER") {
override def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): String = {
defineCodeGen(ctx, ev, (c1, c2) => s"java.lang.Math.pow($c1, $c2)") + s"""
if (Double.valueOf(${ev.primitive}).isNaN()) {
${ev.isNull} = true;
}
"""
defineCodeGen(ctx, ev, (c1, c2) => s"java.lang.Math.pow($c1, $c2)")
}
}

Expand Down Expand Up @@ -699,17 +708,33 @@ case class Logarithm(left: Expression, right: Expression)
this(EulerNumber(), child)
}

protected override def nullSafeEval(input1: Any, input2: Any): Any = {
val dLeft = input1.asInstanceOf[Double]
val dRight = input2.asInstanceOf[Double]
// Unlike Hive, we support Log base in (0.0, 1.0]
if (dLeft <= 0.0 || dRight <= 0.0) null else math.log(dRight) / math.log(dLeft)
}

override def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): String = {
val logCode = if (left.isInstanceOf[EulerNumber]) {
defineCodeGen(ctx, ev, (c1, c2) => s"java.lang.Math.log($c2)")
if (left.isInstanceOf[EulerNumber]) {
nullSafeCodeGen(ctx, ev, (c1, c2) =>
s"""
if ($c2 <= 0.0) {
${ev.isNull} = true;
} else {
${ev.primitive} = java.lang.Math.log($c2);
}
""")
} else {
defineCodeGen(ctx, ev, (c1, c2) => s"java.lang.Math.log($c2) / java.lang.Math.log($c1)")
nullSafeCodeGen(ctx, ev, (c1, c2) =>
s"""
if ($c1 <= 0.0 || $c2 <= 0.0) {
${ev.isNull} = true;
} else {
${ev.primitive} = java.lang.Math.log($c2) / java.lang.Math.log($c1);
}
""")
}
logCode + s"""
if (Double.isNaN(${ev.primitive})) {
${ev.isNull} = true;
}
"""
}
}

Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,10 @@ import com.google.common.math.LongMath

import org.apache.spark.SparkFunSuite
import org.apache.spark.sql.catalyst.dsl.expressions._
import org.apache.spark.sql.catalyst.expressions.codegen.{GenerateProjection, GenerateMutableProjection}
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.optimizer.DefaultOptimizer
import org.apache.spark.sql.catalyst.plans.logical.{OneRowRelation, Project}
import org.apache.spark.sql.types._


Expand All @@ -47,6 +51,7 @@ class MathFunctionsSuite extends SparkFunSuite with ExpressionEvalHelper {
* @param f The functions in scala.math or elsewhere used to generate expected results
* @param domain The set of values to run the function with
* @param expectNull Whether the given values should return null or not
* @param expectNaN Whether the given values should eval to NaN or not
* @tparam T Generic type for primitives
* @tparam U Generic type for the output of the given function `f`
*/
Expand All @@ -55,11 +60,16 @@ class MathFunctionsSuite extends SparkFunSuite with ExpressionEvalHelper {
f: T => U,
domain: Iterable[T] = (-20 to 20).map(_ * 0.1),
expectNull: Boolean = false,
expectNaN: Boolean = false,
evalType: DataType = DoubleType): Unit = {
if (expectNull) {
domain.foreach { value =>
checkEvaluation(c(Literal(value)), null, EmptyRow)
}
} else if (expectNaN) {
domain.foreach { value =>
checkNaN(c(Literal(value)), EmptyRow)
}
} else {
domain.foreach { value =>
checkEvaluation(c(Literal(value)), f(value), EmptyRow)
Expand All @@ -74,16 +84,22 @@ class MathFunctionsSuite extends SparkFunSuite with ExpressionEvalHelper {
* @param c The DataFrame function
* @param f The functions in scala.math
* @param domain The set of values to run the function with
* @param expectNull Whether the given values should return null or not
* @param expectNaN Whether the given values should eval to NaN or not
*/
private def testBinary(
c: (Expression, Expression) => Expression,
f: (Double, Double) => Double,
domain: Iterable[(Double, Double)] = (-20 to 20).map(v => (v * 0.1, v * -0.1)),
expectNull: Boolean = false): Unit = {
expectNull: Boolean = false, expectNaN: Boolean = false): Unit = {
if (expectNull) {
domain.foreach { case (v1, v2) =>
checkEvaluation(c(Literal(v1), Literal(v2)), null, create_row(null))
}
} else if (expectNaN) {
domain.foreach { case (v1, v2) =>
checkNaN(c(Literal(v1), Literal(v2)), EmptyRow)
}
} else {
domain.foreach { case (v1, v2) =>
checkEvaluation(c(Literal(v1), Literal(v2)), f(v1 + 0.0, v2 + 0.0), EmptyRow)
Expand Down Expand Up @@ -112,6 +128,62 @@ class MathFunctionsSuite extends SparkFunSuite with ExpressionEvalHelper {
Conv(Literal("11abc"), Literal(10), Literal(16)), "B")
}

private def checkNaN(
expression: Expression, inputRow: InternalRow = EmptyRow): Unit = {
checkNaNWithoutCodegen(expression, inputRow)
checkNaNWithGeneratedProjection(expression, inputRow)
checkNaNWithOptimization(expression, inputRow)
}

private def checkNaNWithoutCodegen(
expression: Expression,
expected: Any,
inputRow: InternalRow = EmptyRow): Unit = {
val actual = try evaluate(expression, inputRow) catch {
case e: Exception => fail(s"Exception evaluating $expression", e)
}
if (!actual.asInstanceOf[Double].isNaN) {
val input = if (inputRow == EmptyRow) "" else s", input: $inputRow"
fail(s"Incorrect evaluation (codegen off): $expression, " +
s"actual: $actual, " +
s"expected: NaN")
}
}


private def checkNaNWithGeneratedProjection(
expression: Expression,
inputRow: InternalRow = EmptyRow): Unit = {

val plan = try {
GenerateMutableProjection.generate(Alias(expression, s"Optimized($expression)")() :: Nil)()
} catch {
case e: Throwable =>
val ctx = GenerateProjection.newCodeGenContext()
val evaluated = expression.gen(ctx)
fail(
s"""
|Code generation of $expression failed:
|${evaluated.code}
|$e
""".stripMargin)
}

val actual = plan(inputRow).apply(0)
if (!actual.asInstanceOf[Double].isNaN) {
val input = if (inputRow == EmptyRow) "" else s", input: $inputRow"
fail(s"Incorrect Evaluation: $expression, actual: $actual, expected: NaN")
}
}

private def checkNaNWithOptimization(
expression: Expression,
inputRow: InternalRow = EmptyRow): Unit = {
val plan = Project(Alias(expression, s"Optimized($expression)")() :: Nil, OneRowRelation)
val optimizedPlan = DefaultOptimizer.execute(plan)
checkNaNWithoutCodegen(optimizedPlan.expressions.head, inputRow)
}

test("e") {
testLeaf(EulerNumber, math.E)
}
Expand All @@ -126,7 +198,7 @@ class MathFunctionsSuite extends SparkFunSuite with ExpressionEvalHelper {

test("asin") {
testUnary(Asin, math.asin, (-10 to 10).map(_ * 0.1))
testUnary(Asin, math.asin, (11 to 20).map(_ * 0.1), expectNull = true)
testUnary(Asin, math.asin, (11 to 20).map(_ * 0.1), expectNaN = true)
}

test("sinh") {
Expand All @@ -139,7 +211,7 @@ class MathFunctionsSuite extends SparkFunSuite with ExpressionEvalHelper {

test("acos") {
testUnary(Acos, math.acos, (-10 to 10).map(_ * 0.1))
testUnary(Acos, math.acos, (11 to 20).map(_ * 0.1), expectNull = true)
testUnary(Acos, math.acos, (11 to 20).map(_ * 0.1), expectNaN = true)
}

test("cosh") {
Expand Down Expand Up @@ -204,18 +276,18 @@ class MathFunctionsSuite extends SparkFunSuite with ExpressionEvalHelper {
}

test("log") {
testUnary(Log, math.log, (0 to 20).map(_ * 0.1))
testUnary(Log, math.log, (-5 to -1).map(_ * 0.1), expectNull = true)
testUnary(Log, math.log, (1 to 20).map(_ * 0.1))
testUnary(Log, math.log, (-5 to 0).map(_ * 0.1), expectNull = true)
}

test("log10") {
testUnary(Log10, math.log10, (0 to 20).map(_ * 0.1))
testUnary(Log10, math.log10, (-5 to -1).map(_ * 0.1), expectNull = true)
testUnary(Log10, math.log10, (1 to 20).map(_ * 0.1))
testUnary(Log10, math.log10, (-5 to 0).map(_ * 0.1), expectNull = true)
}

test("log1p") {
testUnary(Log1p, math.log1p, (-1 to 20).map(_ * 0.1))
testUnary(Log1p, math.log1p, (-10 to -2).map(_ * 1.0), expectNull = true)
testUnary(Log1p, math.log1p, (0 to 20).map(_ * 0.1))
testUnary(Log1p, math.log1p, (-10 to -1).map(_ * 1.0), expectNull = true)
}

test("bin") {
Expand All @@ -237,22 +309,22 @@ class MathFunctionsSuite extends SparkFunSuite with ExpressionEvalHelper {

test("log2") {
def f: (Double) => Double = (x: Double) => math.log(x) / math.log(2)
testUnary(Log2, f, (0 to 20).map(_ * 0.1))
testUnary(Log2, f, (-5 to -1).map(_ * 1.0), expectNull = true)
testUnary(Log2, f, (1 to 20).map(_ * 0.1))
testUnary(Log2, f, (-5 to 0).map(_ * 1.0), expectNull = true)
}

test("sqrt") {
testUnary(Sqrt, math.sqrt, (0 to 20).map(_ * 0.1))
testUnary(Sqrt, math.sqrt, (-5 to -1).map(_ * 1.0), expectNull = true)
testUnary(Sqrt, math.sqrt, (-5 to -1).map(_ * 1.0), expectNaN = true)

checkEvaluation(Sqrt(Literal.create(null, DoubleType)), null, create_row(null))
checkEvaluation(Sqrt(Literal(-1.0)), null, EmptyRow)
checkEvaluation(Sqrt(Literal(-1.5)), null, EmptyRow)
checkNaN(Sqrt(Literal(-1.0)), EmptyRow)
checkNaN(Sqrt(Literal(-1.5)), EmptyRow)
}

test("pow") {
testBinary(Pow, math.pow, (-5 to 5).map(v => (v * 1.0, v * 1.0)))
testBinary(Pow, math.pow, Seq((-1.0, 0.9), (-2.2, 1.7), (-2.2, -1.7)), expectNull = true)
testBinary(Pow, math.pow, Seq((-1.0, 0.9), (-2.2, 1.7), (-2.2, -1.7)), expectNaN = true)
}

test("shift left") {
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -68,12 +68,7 @@ class MathExpressionsSuite extends QueryTest {
if (f(-1) === math.log1p(-1)) {
checkAnswer(
nnDoubleData.select(c('b)),
(1 to 9).map(n => Row(f(n * -0.1))) :+ Row(Double.NegativeInfinity)
)
} else {
checkAnswer(
nnDoubleData.select(c('b)),
(1 to 10).map(n => Row(null))
(1 to 9).map(n => Row(f(n * -0.1))) :+ Row(null)
)
}

Expand Down
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