andygrove commented on issue #1238:
URL:
https://github.com/apache/datafusion-comet/issues/1238#issuecomment-2580003711
Here is a better repro:
```scala
test("SPARK-32038: NormalizeFloatingNumbers should work on distinct
aggregate") {
val nan1 = java.lang.Float.intBitsToFloat(0x7f800001)
val nan2 = java.lang.Float.intBitsToFloat(0x7fffffff)
withSQLConf(CometConf.COMET_SHUFFLE_MODE.key -> "auto") {
Seq(
("mithunr", Float.NaN),
("mithunr", nan1),
("mithunr", nan2),
("abellina", 1.0f),
("abellina", 2.0f)).toDF("uid",
"score").createOrReplaceTempView("view")
val df =
spark.sql("select uid, count(distinct score) from view group by 1
order by 1 asc")
checkSparkAnswer /*AndOperator*/ (df)
}
}
```
The test passes for shuffle mode `auto` or `native` and fails for `jvm`.
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