Move fromDDL to StructType

Author: maropu

sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataType.scala

@@ -24,7 +24,6 @@ import org.json4s.jackson.JsonMethods._
 
 import org.apache.spark.annotation.InterfaceStability
 import org.apache.spark.sql.catalyst.expressions.Expression
-import org.apache.spark.sql.catalyst.parser.CatalystSqlParser
 import org.apache.spark.util.Utils
 
 /**
@@ -104,12 +103,6 @@ object DataType {
 
   def fromJson(json: String): DataType = parseDataType(parse(json))
 
-  /**
-   * Creates StructType for a given DDL-formatted string, which is a comma separated list of field
-   * definitions, e.g., a INT, b STRING.
-   */
-  def fromDDL(ddl: String): StructType = CatalystSqlParser.parseTableSchema(ddl)
-
   private val nonDecimalNameToType = {
     Seq(NullType, DateType, TimestampType, BinaryType, IntegerType, BooleanType, LongType,
       DoubleType, FloatType, ShortType, ByteType, StringType, CalendarIntervalType)

sql/catalyst/src/main/scala/org/apache/spark/sql/types/StructType.scala

@@ -417,6 +417,12 @@ object StructType extends AbstractDataType {
     }
   }
 
+  /**
+   * Creates StructType for a given DDL-formatted string, which is a comma separated list of field
+   * definitions, e.g., a INT, b STRING.
+   */
+  def fromDDL(ddl: String): StructType = CatalystSqlParser.parseTableSchema(ddl)
+
   def apply(fields: Seq[StructField]): StructType = StructType(fields.toArray)
 
   def apply(fields: java.util.List[StructField]): StructType = {

sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeSuite.scala

@@ -177,7 +177,7 @@ class DataTypeSuite extends SparkFunSuite {
 
   def checkDataTypeFromDDL(dataType: DataType, ignoreNullability: Boolean = false): Unit = {
     test(s"from DDL - $dataType") {
-      val parsed = DataType.fromDDL(s"a ${dataType.sql}")
+      val parsed = StructType.fromDDL(s"a ${dataType.sql}")
       val expected = new StructType().add("a", dataType)
       if (!ignoreNullability) {
         assert(parsed === expected)

sql/core/src/main/scala/org/apache/spark/sql/functions.scala

@@ -3067,7 +3067,7 @@ object functions {
     val dataType = try {
       DataType.fromJson(schema)
     } catch {
-      case NonFatal(_) => DataType.fromDDL(schema)
+      case NonFatal(_) => StructType.fromDDL(schema)
     }
     from_json(e, dataType, options)
   }