Vancior commented on code in PR #20499:
URL: https://github.com/apache/flink/pull/20499#discussion_r941101664


##########
flink-python/pyflink/datastream/formats/parquet.py:
##########
@@ -155,3 +158,54 @@ def for_generic_record(schema: 'AvroSchema') -> 
'BulkWriterFactory':
         jvm = get_gateway().jvm
         JAvroParquetWriters = 
jvm.org.apache.flink.formats.parquet.avro.AvroParquetWriters
         return 
BulkWriterFactory(JAvroParquetWriters.forGenericRecord(schema._j_schema))
+
+
+class ParquetRowDataWriter(object):
+    """
+    Convenient builder to create a :class:`BulkWriterFactory` that writes Rows 
with a defined
+    :class:`RowType` into Parquet files in a batch fashion.
+
+    .. versionadded:: 1.16.0
+    """
+
+    @staticmethod
+    def for_row_type(row_type: RowType, hadoop_config: Optional[Configuration] 
= None,
+                     utc_timestamp: bool = False) -> 'BulkWriterFactory':
+        """
+        Create a :class:`RowDataBulkWriterFactory` that writes Rows records 
with a defined
+        :class:`RowType` into Parquet files in a batch fashion.
+
+        Example:
+        ::
+
+            >>> row_type = DataTypes.ROW([
+            ...     DataTypes.FIELD('string', DataTypes.STRING()),
+            ...     DataTypes.FIELD('int_array', 
DataTypes.ARRAY(DataTypes.INT()))
+            ... ])
+            >>> row_type_info = Types.ROW_NAMED(
+            ...     ['string', 'int_array'],
+            ...     [Types.STRING(), Types.LIST(Types.INT())]
+            ... )
+            >>> sink = FileSink.for_bulk_format(
+            ...     OUTPUT_DIR, ParquetRowDataWriter.for_row_type(
+            ...         row_type,
+            ...         hadoop_config=Configuration(),
+            ...         utc_timestamp=True,
+            ...     )
+            ... ).build()

Review Comment:
   Why no `build` ?



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