andygrove commented on code in PR #351:
URL: https://github.com/apache/datafusion-comet/pull/351#discussion_r1584966124
##########
spark/src/test/scala/org/apache/comet/CometCastSuite.scala:
##########
@@ -118,12 +474,68 @@ class CometCastSuite extends CometTestBase with
AdaptiveSparkPlanHelper {
private def generateFloats(): DataFrame = {
val r = new Random(0)
- Range(0, dataSize).map(_ => r.nextFloat()).toDF("a")
+ val values = Seq(
+ Float.MaxValue,
+ Float.MinPositiveValue,
+ Float.MinValue,
+ Float.NaN,
+ Float.PositiveInfinity,
+ Float.NegativeInfinity,
+ 0.0f,
+ -0.0f) ++
+ Range(0, dataSize).map(_ => r.nextFloat())
+ values.toDF("a")
Review Comment:
Thanks. I have pushed an update to add nulls to all generators except for
string. I will address this in a future PR when I change the string generator
to also return a DataFrame.
##########
spark/src/test/scala/org/apache/comet/CometCastSuite.scala:
##########
@@ -118,12 +474,68 @@ class CometCastSuite extends CometTestBase with
AdaptiveSparkPlanHelper {
private def generateFloats(): DataFrame = {
val r = new Random(0)
- Range(0, dataSize).map(_ => r.nextFloat()).toDF("a")
+ val values = Seq(
+ Float.MaxValue,
+ Float.MinPositiveValue,
+ Float.MinValue,
+ Float.NaN,
+ Float.PositiveInfinity,
+ Float.NegativeInfinity,
+ 0.0f,
+ -0.0f) ++
+ Range(0, dataSize).map(_ => r.nextFloat())
+ values.toDF("a")
+ }
+
+ private def generateDoubles(): DataFrame = {
+ val r = new Random(0)
+ val values = Seq(
+ Double.MaxValue,
+ Double.MinPositiveValue,
+ Double.MinValue,
+ Double.NaN,
+ Double.PositiveInfinity,
+ Double.NegativeInfinity,
+ 0.0d,
+ -0.0d) ++
+ Range(0, dataSize).map(_ => r.nextDouble())
+ values.toDF("a")
+ }
+
+ private def generateBools(): DataFrame = {
+ Seq(true, false).toDF("a")
+ }
+
+ private def generateBytes(): DataFrame = {
+ val r = new Random(0)
+ val values = Seq(Byte.MinValue, Byte.MaxValue) ++
+ Range(0, dataSize).map(_ => r.nextInt().toByte)
+ values.toDF("a")
+ }
+
+ private def generateShorts(): DataFrame = {
+ val r = new Random(0)
+ val values = Seq(Short.MinValue, Short.MaxValue) ++
+ Range(0, dataSize).map(_ => r.nextInt().toShort)
+ values.toDF("a")
+ }
+
+ private def generateInts(): DataFrame = {
+ val r = new Random(0)
+ val values = Seq(Int.MinValue, Int.MaxValue) ++
+ Range(0, dataSize).map(_ => r.nextInt())
+ values.toDF("a")
}
private def generateLongs(): DataFrame = {
val r = new Random(0)
- Range(0, dataSize).map(_ => r.nextLong()).toDF("a")
+ val values = Seq(Long.MinValue, Long.MaxValue) ++
+ Range(0, dataSize).map(_ => r.nextLong())
+ values.toDF("a")
+ }
+
+ private def generateDecimals(): DataFrame = {
+ Seq(BigDecimal("123456.789"), BigDecimal("-123456.789"),
BigDecimal("0.0")).toDF("a")
}
private def generateString(r: Random, chars: String, maxLen: Int): String = {
Review Comment:
Added a TODO for this
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