Github user yjshen commented on a diff in the pull request:
https://github.com/apache/spark/pull/7523#discussion_r34969931
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/nullFunctions.scala
---
@@ -198,14 +203,39 @@ case class AtLeastNNonNulls(n: Int, children:
Seq[Expression]) extends Predicate
val nonnull = ctx.freshName("nonnull")
val code = children.map { e =>
val eval = e.gen(ctx)
- s"""
- if ($nonnull < $n) {
- ${eval.code}
- if (!${eval.isNull}) {
- $nonnull += 1;
- }
- }
- """
+ e.dataType match {
+ case DoubleType =>
+ s"""
+ if ($nonnull < $n) {
+ ${eval.code}
+ if (!${eval.isNull}) {
+ if (!Double.isNaN(${eval.primitive})) {
--- End diff --
yes, actually there's a bunch of code could just be checked with
`Double.isNaN`, but use Float.isNaN and Double.isNaN separately, should I
simplify them all?
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