Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/17406#discussion_r108339957
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/functions.scala ---
@@ -3055,13 +3056,21 @@ object functions {
* with the specified schema. Returns `null`, in the case of an
unparseable string.
*
* @param e a string column containing JSON data.
- * @param schema the schema to use when parsing the json string as a
json string
+ * @param schema the schema to use when parsing the json string as a
json string. In Spark 2.1,
+ * the user-provided schema has to be in JSON format.
Since Spark 2.2, the DDL
+ * format is also supported for the schema.
*
* @group collection_funcs
* @since 2.1.0
*/
- def from_json(e: Column, schema: String, options: java.util.Map[String,
String]): Column =
- from_json(e, DataType.fromJson(schema), options)
+ def from_json(e: Column, schema: String, options: java.util.Map[String,
String]): Column = {
+ val dataType = try {
--- End diff --
That is fine, right? cc @cloud-fan
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