Github user shivaram commented on a diff in the pull request:
https://github.com/apache/spark/pull/10037#discussion_r46765017
--- Diff: R/pkg/R/generics.R ---
@@ -623,6 +623,10 @@ setGeneric("getItem", function(x, ...) {
standardGeneric("getItem") })
#' @rdname column
#' @export
+setGeneric("isNaN", function(x) { standardGeneric("isNaN") })
--- End diff --
Ok I think I get it. Let me summarize the situation below and let know if I
am getting it right.
1. We have isNaN, isNull, isNotNull for `Column` as defined in `column.R`.
These mirror the scala functions.
2. We have added `isnan` and `is.nan` for `Column` in this PR. These call
`isnan` in Scala. And I presume their behavior is this the same as `isNaN` ?
3. In addition to this, we have some DataFrame operators called `isNaN` ? I
can't find that call in our unit test file, so I guess it doesn't exist in
SparkR ? Does this exist in Scala ?
4. We convert `NA` in R to `null` in the SparkSQL side.
I think the change looks fine to me, but I just want to understand the
different things going on here
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