rednaxelafx commented on a change in pull request #25666: [SPARK-28962][SQL]
Provide index argument to filter lambda functions
URL: https://github.com/apache/spark/pull/25666#discussion_r330236082
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/higherOrderFunctions.scala
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@@ -369,6 +383,9 @@ case class ArrayFilter(
var i = 0
while (i < arr.numElements) {
elementVar.value.set(arr.get(i, elementVar.dataType))
+ if (indexVar.isDefined) {
Review comment:
@maropu @henrydavidge The best performing way to avoid the per-row check in
a non-codegen setting is to introduce a new expression type, say
`ArrayFilterWithIndex`.
The tradeoff between the inline per-row check and the lambda batch solution
is that on input arrays that are small (like the one @henrydavidge used in his
benchmark), the lambda invocation (which is not guaranteed to be
inlined+optimized) overhead *may* exceed the per-row check overhead. You'd need
a fairly large input array to amortize that.
If we want to make it stay simple for now, I'm okay with the inline per-row
check version.
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