Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/12493#discussion_r61486517
--- Diff: R/pkg/R/DataFrame.R ---
@@ -1125,6 +1126,66 @@ setMethod("summarize",
agg(x, ...)
})
+#' dapply
+#'
+#' Apply a function to each partition of a DataFrame.
+#'
+#' @param x A SparkDataFrame
+#' @param func A function to be applied to each partition of the
SparkDataFrame.
+#' func should have only one parameter, to which a data.frame
corresponds
+#' to each partition will be passed.
+#' The output of func should be a data.frame.
+#' @param schema The schema of the resulting DataFrame after the function
is applied.
+#' It must match the output of func.
+#' @family SparkDataFrame functions
+#' @rdname dapply
+#' @name dapply
+#' @export
+#' @examples
+#' \dontrun{
+#' df <- createDataFrame (sqlContext, iris)
+#' df1 <- dapply(df, function(x) { x }, schema(df))
+#' collect(df1)
+#'
+#' # filter and add a column
+#' df <- createDataFrame (
+#' sqlContext,
+#' list(list(1L, 1, "1"), list(2L, 2, "2"), list(3L, 3, "3")),
+#' c("a", "b", "c"))
+#' schema <- structType(structField("a", "integer"), structField("b",
"double"),
--- End diff --
btw, we already have a simpler way (string based) to define a schema in
Scala and Python, we may also add that to R.
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