[GitHub] [spark] maropu commented on a change in pull request #17406: [SPARK-20009][SQL] Support DDL strings for defining schema in functions.from_json

[GitBox <gi...@apache.org>]

maropu commented on a change in pull request #17406:
URL: https://github.com/apache/spark/pull/17406#discussion_r514650459



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File path: sql/core/src/main/scala/org/apache/spark/sql/functions.scala
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@@ -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 {
+      DataType.fromJson(schema)
+    } catch {
+      case NonFatal(_) => StructType.fromDDL(schema)
+    }

Review comment:
       I think I just missed it, so making the code in common seems fine.




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