Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/18458#discussion_r124706483
--- Diff: R/pkg/R/functions.R ---
@@ -2156,28 +2178,23 @@ setMethod("date_format", signature(y = "Column", x
= "character"),
column(jc)
})
-#' from_json
-#'
-#' Parses a column containing a JSON string into a Column of
\code{structType} with the specified
-#' \code{schema} or array of \code{structType} if \code{as.json.array} is
set to \code{TRUE}.
-#' If the string is unparseable, the Column will contains the value NA.
+#' @details
+#' \code{from_json}: Parses a column containing a JSON string into a
Column of \code{structType}
+#' with the specified \code{schema} or array of \code{structType} if
\code{as.json.array} is set
+#' to \code{TRUE}. If the string is unparseable, the Column will contains
the value NA.
#'
-#' @param x Column containing the JSON string.
+#' @rdname column_collection_functions
#' @param schema a structType object to use as the schema to use when
parsing the JSON string.
#' @param as.json.array indicating if input string is JSON array of
objects or a single object.
-#' @param ... additional named properties to control how the json is
parsed, accepts the same
-#' options as the JSON data source.
-#'
-#' @family non-aggregate functions
-#' @rdname from_json
-#' @name from_json
-#' @aliases from_json,Column,structType-method
+#' @aliases from_json from_json,Column,structType-method
#' @export
#' @examples
+#'
#' \dontrun{
-#' schema <- structType(structField("name", "string"),
-#' select(df, from_json(df$value, schema, dateFormat = "dd/MM/yyyy"))
-#'}
+#' df2 <- sql("SELECT named_struct('name', 'Bob') as people")
+#' df2 <- mutate(df2, people_json = to_json(df2$people))
+#' schema <- structType(structField("name", "string"))
+#' head(select(df2, from_json(df2$people_json, schema)))}
--- End diff --
I think it's worthwhile to keep `dateFormat = "dd/MM/yyyy")` in the example
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