[GitHub] [spark] HyukjinKwon commented on a diff in pull request #42715: [SPARK-45001][PYTHON][CONNECT] Implement DataFrame.foreachPartition

["HyukjinKwon (via GitHub)" <gi...@apache.org>]

HyukjinKwon commented on code in PR #42715:
URL: https://github.com/apache/spark/pull/42715#discussion_r1308196424


##########
python/pyspark/sql/connect/dataframe.py:
##########
@@ -2005,6 +2001,31 @@ def mapInArrow(
 
     mapInArrow.__doc__ = PySparkDataFrame.mapInArrow.__doc__
 
+    def foreachPartition(self, f: Callable[[Iterator[Row]], None]) -> None:
+        assert self._plan is not None
+
+        schema = self.schema
+        field_converters = [
+            ArrowTableToRowsConversion._create_converter(f.dataType) for f in schema.fields
+        ]
+
+        def foreach_partition_func(itr: Iterator[pa.ArrowBatch]) -> None:
+            def flatten() -> Iterator[Row]:
+                for table in itr:
+                    columnar_data = [column.to_pylist() for column in table.columns]
+                    for i in range(0, table.num_rows):
+                        values = [
+                            field_converters[j](columnar_data[j][i])
+                            for j in range(table.num_columns)
+                        ]
+                        yield _create_row(fields=schema.fieldNames(), values=values)
+
+            f(flatten())
+
+        self.mapInArrow(foreach_partition_func, schema=StructType())

Review Comment:
   yeah .. :-).



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