Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/10037#discussion_r46246717
--- Diff: R/pkg/R/functions.R ---
@@ -488,19 +488,35 @@ setMethod("initcap",
column(jc)
})
-#' isNaN
+#' isnan
#'
-#' Return true iff the column is NaN.
+#' Return true if the column is NaN.
#'
-#' @rdname isNaN
-#' @name isNaN
+#' @rdname isnan
+#' @name isnan
#' @family normal_funcs
#' @export
-#' @examples \dontrun{isNaN(df$c)}
-setMethod("isNaN",
+#' @examples \dontrun{isnan(df$c)}
+setMethod("isnan",
signature(x = "Column"),
function(x) {
- jc <- callJStatic("org.apache.spark.sql.functions", "isNaN",
x@jc)
+ jc <- callJStatic("org.apache.spark.sql.functions", "isnan",
x@jc)
+ column(jc)
+ })
+
+#' isnull
+#'
+#' Return true if the column is NULL.
+#'
+#' @rdname isnull
+#' @name isnull
+#' @family normal_funcs
+#' @export
+#' @examples \dontrun{isnull(df$c)}
+setMethod("isnull",
--- End diff --
Our replies crossed - it would seem to me to say Scala/Python `isnull` == R
`is.na` is confusing.
In any case we could definitely use some explanations on NULL/NA in the
SPARKR programming guide, opened JIRA
https://issues.apache.org/jira/browse/SPARK-12071
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