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[SPARK-32688][SQL][TEST] Add special values to LiteralGenerator for float and double #29515

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[SPARK-32688][SQL][TEST] Add special values to LiteralGenerator for float and double #29515

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8c8313c
Add special values to LiteralGenerator for float and double
tanelk Aug 22, 2020
77d63ac
Add 'MaxValue' to LiteralGenerator for float and double
tanelk Aug 23, 2020
818abe2
Ensure -0.0 and 0.0 comparison consistency
tanelk Aug 23, 2020
1116d3d
Revert equality check
tanelk Aug 23, 2020
2dce36e
test -0.0 equality for complex types
tanelk Aug 23, 2020
9a3b983
Add -0.0 as special value to RandomDataGenerator
tanelk Aug 24, 2020
d20a2ed
revert test -0.0 equality for complex types
tanelk Sep 4, 2020
529aba8
revert test -0.0 equality for complex types
tanelk Sep 4, 2020
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6 changes: 4 additions & 2 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala
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Expand Up @@ -793,7 +793,9 @@ case class EqualTo(left: Expression, right: Expression)
// | FALSE | FALSE | TRUE | UNKNOWN |
// | UNKNOWN | UNKNOWN | UNKNOWN | UNKNOWN |
// +---------+---------+---------+---------+
protected override def nullSafeEval(left: Any, right: Any): Any = ordering.equiv(left, right)
protected override def nullSafeEval(left: Any, right: Any): Any = {
left == right || ordering.equiv(left, right)
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@maropu maropu Aug 23, 2020

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At least, we shoud fix the existing test failures that we found in this PR. But, this fix looks improper, so could we use NormalizeNaNAndZero instead? cc: @cloud-fan @viirya

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@tanelk tanelk Aug 23, 2020 •
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NormalizeNaNAndZero can't help here, because checkConsistencyBetweenInterpretedAndCodegen is done without optimizers.

Also it could introduce new correctness issues with atan2(-0.0, x) and 1.0 / -0.0.

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@tanelk tanelk Aug 23, 2020

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I assumed that 0.0 == -0.0 is the expected behavior, but if it is not, then we could leave this as it was change the code gen path.

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@maropu maropu Aug 23, 2020 •
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But, how about the case array(-0.0) == array(0.0)?

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@tanelk tanelk Aug 23, 2020

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You are 100% correct.

It is an interesting problem, where the same comparator is used for both sorting and equality check.
For sorting -0.0 should be smaller than 0.0, but in equality check they should be equal.

Just for reference, it seems that both hive and mysql consider them equal in the equality check:
https://issues.apache.org/jira/browse/HIVE-11174

}

override def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
defineCodeGen(ctx, ev, (c1, c2) => ctx.genEqual(left.dataType, c1, c2))
Expand Down Expand Up @@ -845,7 +847,7 @@ case class EqualNullSafe(left: Expression, right: Expression) extends BinaryComp
} else if (input1 == null || input2 == null) {
false
} else {
ordering.equiv(input1, input2)
input1 == input2 || ordering.equiv(input1, input2)
}
}

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19 changes: 15 additions & 4 deletions sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/LiteralGenerator.scala
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Expand Up @@ -68,16 +68,27 @@ object LiteralGenerator {
lazy val longLiteralGen: Gen[Literal] =
for { l <- Arbitrary.arbLong.arbitrary } yield Literal.create(l, LongType)

// The floatLiteralGen and doubleLiteralGen will 50% of the time yield arbitrary values
// and 50% of the time will yield some special values that are more likely to reveal
// corner cases. This behavior is similar to the integral value generators.
lazy val floatLiteralGen: Gen[Literal] =
for {
f <- Gen.chooseNum(Float.MinValue / 2, Float.MaxValue / 2,
Float.NaN, Float.PositiveInfinity, Float.NegativeInfinity)
f <- Gen.oneOf(
Gen.oneOf(
Float.NaN, Float.PositiveInfinity, Float.NegativeInfinity, Float.MinPositiveValue,
Float.MaxValue, -Float.MaxValue, 0.0f, -0.0f, 1.0f, -1.0f),
Arbitrary.arbFloat.arbitrary
)
} yield Literal.create(f, FloatType)

lazy val doubleLiteralGen: Gen[Literal] =
for {
f <- Gen.chooseNum(Double.MinValue / 2, Double.MaxValue / 2,
Double.NaN, Double.PositiveInfinity, Double.NegativeInfinity)
f <- Gen.oneOf(
Gen.oneOf(
Double.NaN, Double.PositiveInfinity, Double.NegativeInfinity, Double.MinPositiveValue,
Double.MaxValue, -Double.MaxValue, 0.0, -0.0, 1.0, -1.0),
Arbitrary.arbDouble.arbitrary
)
} yield Literal.create(f, DoubleType)

// TODO cache the generated data
Expand Down
7 changes: 7 additions & 0 deletions sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/PredicateSuite.scala
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Expand Up @@ -496,6 +496,13 @@ class PredicateSuite extends SparkFunSuite with ExpressionEvalHelper {
checkEvaluation(EqualTo(infinity, infinity), true)
}

test("SPARK-32688: 0.0 and -0.0 should be considered equal") {
checkEvaluation(EqualTo(Literal(0.0), Literal(-0.0)), true)
checkEvaluation(EqualNullSafe(Literal(0.0), Literal(-0.0)), true)
checkEvaluation(EqualTo(Literal(0.0f), Literal(-0.0f)), true)
checkEvaluation(EqualNullSafe(Literal(0.0f), Literal(-0.0f)), true)
}

test("SPARK-22693: InSet should not use global variables") {
val ctx = new CodegenContext
InSet(Literal(1), Set(1, 2, 3, 4)).genCode(ctx)
Expand Down