Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/23184#discussion_r238057238
--- Diff: R/pkg/R/functions.R ---
@@ -2254,40 +2255,48 @@ setMethod("date_format", signature(y = "Column", x
= "character"),
column(jc)
})
+setClassUnion("characterOrstructTypeOrColumn", c("character",
"structType", "Column"))
+
#' @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 contain
the value NA.
#'
#' @rdname column_collection_functions
#' @param as.json.array indicating if input string is JSON array of
objects or a single object.
-#' @aliases from_json from_json,Column,characterOrstructType-method
+#' @aliases from_json from_json,Column,characterOrstructTypeOrColumn-method
#' @examples
#'
#' \dontrun{
#' df2 <- sql("SELECT named_struct('date', cast('2000-01-01' as date)) as
d")
#' df2 <- mutate(df2, d2 = to_json(df2$d, dateFormat = 'dd/MM/yyyy'))
#' schema <- structType(structField("date", "string"))
#' head(select(df2, from_json(df2$d2, 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)))
-#' head(select(df2, from_json(df2$people_json, "name STRING")))}
+#' head(select(df2, from_json(df2$people_json, "name STRING")))
+#' head(select(df2, from_json(df2$people_json,
schema_of_json(head(df2)$people_json))))}
#' @note from_json since 2.2.0
-setMethod("from_json", signature(x = "Column", schema =
"characterOrstructType"),
+setMethod("from_json", signature(x = "Column", schema =
"characterOrstructTypeOrColumn"),
function(x, schema, as.json.array = FALSE, ...) {
if (is.character(schema)) {
- schema <- structType(schema)
+ jschema <- structType(schema)$jobj
+ } else if (class(schema) == "structType") {
+ jschema <- schema$jobj
+ } else {
+ jschema <- schema@jc
}
if (as.json.array) {
- jschema <-
callJStatic("org.apache.spark.sql.types.DataTypes",
- "createArrayType",
- schema$jobj)
- } else {
- jschema <- schema$jobj
+ # This case is R-specifically different. Unlike Scala and
Python side,
--- End diff --
If so, the provided schema is wrapped by Array. The test cases are ...
here
https://github.com/apache/spark/pull/23184/files#diff-d4011863c8b176830365b2f224a84bf2R1707
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