def schema(self):
        """Returns the schema of this DataFrame (represented by
        a L{StructType}).

        >>> df.schema()
        StructType(List(StructField(age,IntegerType,true),StructField(name,StringType,true)))
        """
        return _parse_datatype_json_string(self._jdf.schema().json())

    def schema(self):
        """Returns the schema of this :class:`DataFrame` as a :class:`types.StructType`.

        >>> df.schema
        StructType(List(StructField(age,IntegerType,true),StructField(name,StringType,true)))
        """
        if self._schema is None:
            self._schema = _parse_datatype_json_string(self._jdf.schema().json())
        return self._schema

    def schema(self):
        """Returns the schema of this :class:`DataFrame` as a :class:`types.StructType`.

        >>> df.schema
        StructType(List(StructField(age,IntegerType,true),StructField(name,StringType,true)))
        """
        if self._schema is None:
            try:
                self._schema = _parse_datatype_json_string(self._jdf.schema().json())
            except AttributeError as e:
                raise Exception("Unable to parse datatype from schema. %s" % e)
        return self._schema

    def imageSchema(self):
        """
        Returns the image schema.

        :return: a :class:`StructType` with a single column of images
               named "image" (nullable).

        .. versionadded:: 2.3.0
        """

        if self._imageSchema is None:
            ctx = SparkContext._active_spark_context
            jschema = ctx._jvm.org.apache.spark.ml.image.ImageSchema.imageSchema()
            self._imageSchema = _parse_datatype_json_string(jschema.json())
        return self._imageSchema

    def columnSchema(self):
        """
        Returns the schema for the image column.

        :return: a :class:`StructType` for image column,
            ``struct<origin:string, height:int, width:int, nChannels:int, mode:int, data:binary>``.

        .. versionadded:: 2.4.0
        """

        if self._columnSchema is None:
            ctx = SparkContext._active_spark_context
            jschema = ctx._jvm.org.apache.spark.ml.image.ImageSchema.columnSchema()
            self._columnSchema = _parse_datatype_json_string(jschema.json())
        return self._columnSchema

 def check_datatype(datatype):
     pickled = pickle.loads(pickle.dumps(datatype))
     assert datatype == pickled
     scala_datatype = self.sqlCtx._ssql_ctx.parseDataType(datatype.json())
     python_datatype = _parse_datatype_json_string(scala_datatype.json())
     assert datatype == python_datatype

 def check_datatype(datatype):
     pickled = pickle.loads(pickle.dumps(datatype))
     assert datatype == pickled
     scala_datatype = self.spark._jsparkSession.parseDataType(datatype.json())
     python_datatype = _parse_datatype_json_string(scala_datatype.json())
     assert datatype == python_datatype