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Better float/double cases for casting tests #1781

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merged 8 commits into from
Feb 23, 2021
Merged

Better float/double cases for casting tests #1781

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ea3766a
enhance float/double cases for casting tests
sperlingxx Feb 21, 2021
5c11d5a
continue
sperlingxx Feb 21, 2021
6d308ef
code clean
sperlingxx Feb 21, 2021
ff2fa8d
code clean
sperlingxx Feb 21, 2021
e33e0c4
fix typo
sperlingxx Feb 21, 2021
1c569cc
fix typo
sperlingxx Feb 21, 2021
15c2fa5
some updates
sperlingxx Feb 23, 2021
d612e86
fix typo
sperlingxx Feb 23, 2021
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16 changes: 8 additions & 8 deletions tests/src/test/scala/com/nvidia/spark/rapids/AnsiCastOpSuite.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -338,31 +338,31 @@ class AnsiCastOpSuite extends GpuExpressionTestSuite {
frame => testCastTo(DataTypes.DoubleType)(frame)
}

testCastFailsForBadInputs("Test bad cast 1 from strings to floats", badFloatStringsDf,
testCastFailsForBadInputs("Test bad cast 1 from strings to floats", invalidFloatStringsDf,
msg = GpuCast.INVALID_FLOAT_CAST_MSG) {
frame =>frame.select(col("c0").cast(FloatType))
}

testCastFailsForBadInputs("Test bad cast 2 from strings to floats", badFloatStringsDf,
testCastFailsForBadInputs("Test bad cast 2 from strings to floats", invalidFloatStringsDf,
msg = GpuCast.INVALID_FLOAT_CAST_MSG) {
frame =>frame.select(col("c1").cast(FloatType))
}

testCastFailsForBadInputs("Test bad cast 1 from strings to double", badFloatStringsDf,
testCastFailsForBadInputs("Test bad cast 1 from strings to double", invalidFloatStringsDf,
msg = GpuCast.INVALID_FLOAT_CAST_MSG) {
frame =>frame.select(col("c0").cast(DoubleType))
}

testCastFailsForBadInputs("Test bad cast 2 from strings to double", badFloatStringsDf,
testCastFailsForBadInputs("Test bad cast 2 from strings to double", invalidFloatStringsDf,
msg = GpuCast.INVALID_FLOAT_CAST_MSG) {
frame =>frame.select(col("c1").cast(DoubleType))
}

//Currently there is a bug in cudf which doesn't convert one value correctly
// Currently there is a bug in cudf which doesn't convert some corner cases correctly
// The bug is documented here https://github.com/rapidsai/cudf/issues/5225
ignore("Test cast from strings to double that doesn't match") {
testSparkResultsAreEqual("Test cast from strings to double that doesn't match",
badDoubleStringsDf) {
badDoubleStringsDf, conf = sparkConf, maxFloatDiff = 0.0001) {
frame =>frame.select(
col("c0").cast(DoubleType))
}
Expand All @@ -372,12 +372,12 @@ class AnsiCastOpSuite extends GpuExpressionTestSuite {
// Ansi cast from floating point to string
///////////////////////////////////////////////////////////////////////////

ignore("ansi_cast float to string") {
test("ansi_cast float to string") {
testCastToString[Float](DataTypes.FloatType, ansiMode = true,
comparisonFunc = Some(compareStringifiedFloats))
}

ignore("ansi_cast double to string") {
test("ansi_cast double to string") {
testCastToString[Double](DataTypes.DoubleType, ansiMode = true,
comparisonFunc = Some(compareStringifiedFloats))
}
Expand Down
62 changes: 15 additions & 47 deletions tests/src/test/scala/com/nvidia/spark/rapids/CastOpSuite.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -203,16 +203,6 @@ class CastOpSuite extends GpuExpressionTestSuite {
}
}

private def testCastTo(castTo: DataType)(frame: DataFrame): DataFrame ={
frame.withColumn("c1", col("c0").cast(castTo))
}

private def stringDf(str: String)(session: SparkSession): DataFrame = {
import session.sqlContext.implicits._
// use more than one value otherwise spark optimizes it out as a literal
Seq(str, str).toDF("c0")
}

private def castToStringExpectedFun[T]: T => Option[String] = (d: T) => Some(String.valueOf(d))

test("cast byte to string") {
Expand All @@ -231,11 +221,11 @@ class CastOpSuite extends GpuExpressionTestSuite {
testCastToString[Long](DataTypes.LongType)
}

ignore("cast float to string") {
test("cast float to string") {
testCastToString[Float](DataTypes.FloatType, comparisonFunc = Some(compareStringifiedFloats))
}

ignore("cast double to string") {
test("cast double to string") {
testCastToString[Double](DataTypes.DoubleType, comparisonFunc = Some(compareStringifiedFloats))
}

Expand Down Expand Up @@ -298,30 +288,6 @@ class CastOpSuite extends GpuExpressionTestSuite {
col("doubles").cast(TimestampType))
}

ignore("Test cast from double to string") {

//NOTE that the testSparkResultsAreEqual method isn't adequate in this case because we
// need to use a specialized comparison function

val conf = new SparkConf()
.set(RapidsConf.ENABLE_CAST_FLOAT_TO_STRING.key, "true")

val (cpu, gpu) = runOnCpuAndGpu(doubleDf, frame => frame.select(
col("doubles").cast(StringType))
.orderBy(col("doubles")), conf)

val fromCpu = cpu.map(row => row.getAs[String](0))
val fromGpu = gpu.map(row => row.getAs[String](0))

fromCpu.zip(fromGpu).foreach {
case (c, g) =>
if (!compareStringifiedFloats(c, g)) {
fail(s"Running on the GPU and on the CPU did not match: CPU value: $c. " +
s"GPU value: $g.")
}
}
}

testSparkResultsAreEqual("Test cast from boolean", booleanDf) {
frame => frame.select(
col("bools").cast(IntegerType),
Expand Down Expand Up @@ -396,14 +362,6 @@ class CastOpSuite extends GpuExpressionTestSuite {
col("doubles").cast(TimestampType))
}

ignore("Test cast from strings to double that doesn't match") {
testSparkResultsAreEqual("Test cast from strings to double that doesn't match",
badDoubleStringsDf) {
frame =>frame.select(
col("doubles").cast(DoubleType))
}
}

testSparkResultsAreEqual("Test cast from strings to doubles", doublesAsStrings,
conf = sparkConf, maxFloatDiff = 0.0001) {
frame => frame.select(
Expand All @@ -416,7 +374,7 @@ class CastOpSuite extends GpuExpressionTestSuite {
col("c0").cast(FloatType))
}

testSparkResultsAreEqual("Test bad cast from strings to floats", badFloatStringsDf,
testSparkResultsAreEqual("Test bad cast from strings to floats", invalidFloatStringsDf,
conf = sparkConf, maxFloatDiff = 0.0001) {
frame =>frame.select(
col("c0").cast(DoubleType),
Expand All @@ -425,6 +383,16 @@ class CastOpSuite extends GpuExpressionTestSuite {
col("c1").cast(FloatType))
}

// Currently there is a bug in cudf which doesn't convert some corner cases correctly
// The bug is documented here https://github.com/rapidsai/cudf/issues/5225
ignore("Test cast from strings to double that doesn't match") {
testSparkResultsAreEqual("Test cast from strings to double that doesn't match",
badDoubleStringsDf, conf = sparkConf, maxFloatDiff = 0.0001) {
frame => frame.select(
col("c0").cast(DoubleType))
}
}

testSparkResultsAreEqual("ansi_cast string to double exp", exponentsAsStringsDf,
conf = sparkConf, maxFloatDiff = 0.0001) {
frame => frame.select(
Expand Down Expand Up @@ -720,13 +688,13 @@ object CastOpSuite {

def doublesAsStrings(session: SparkSession): DataFrame = {
val schema = FuzzerUtils.createSchema(Seq(DoubleType), false)
val df = FuzzerUtils.generateDataFrame(session, schema, 100)
val df = FuzzerUtils.generateDataFrame(session, schema, 2048)
df.withColumn("c0", col("c0").cast(StringType))
}

def floatsAsStrings(session: SparkSession): DataFrame = {
val schema = FuzzerUtils.createSchema(Seq(FloatType), false)
val df = FuzzerUtils.generateDataFrame(session, schema, 100)
val df = FuzzerUtils.generateDataFrame(session, schema, 2048)
df.withColumn("c0", col("c0").cast(StringType))
}

Expand Down
16 changes: 10 additions & 6 deletions tests/src/test/scala/com/nvidia/spark/rapids/FuzzerUtils.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -301,30 +301,34 @@ class EnhancedRandom(protected val r: Random, protected val options: FuzzerOptio
}

def nextFloat(): Float = {
r.nextInt(9) match {
r.nextInt(11) match {
case 0 => Float.NaN
case 1 => Float.PositiveInfinity
case 2 => Float.NegativeInfinity
case 3 => r.nextFloat() * Float.MinValue
case 4 => r.nextFloat() * Float.MaxValue
case 3 => Float.MinValue
case 4 => Float.MaxValue
case 5 => 0 - r.nextFloat()
case 6 => r.nextFloat()
case 7 => 0f
case 8 => -0f
case 9 => r.nextFloat() * Float.MinValue
case 10 => r.nextFloat() * Float.MaxValue
}
}

def nextDouble(): Double = {
r.nextInt(9) match {
r.nextInt(11) match {
case 0 => Double.NaN
case 1 => Double.PositiveInfinity
case 2 => Double.NegativeInfinity
case 3 => r.nextDouble() * Double.MinValue
case 4 => r.nextDouble() * Double.MaxValue
case 3 => Double.MaxValue
case 4 => Double.MinValue
case 5 => 0 - r.nextDouble()
case 6 => r.nextDouble()
case 7 => 0d
case 8 => -0d
case 9 => r.nextDouble() * Double.MinValue
case 10 => r.nextDouble() * Double.MaxValue
}
}

Expand Down
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