Github user sun-rui commented on a diff in the pull request:
https://github.com/apache/spark/pull/10037#discussion_r46240622
--- 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 --
In the context of DataFrame column, "null" means missing value, which I
think NA in R means. When we read a column from a DataFrame to R side, null
will be converted to NA, see the code at
https://github.com/apache/spark/blob/master/R/pkg/R/deserialize.R#L115
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
