Kimahriman commented on code in PR #53035:
URL: https://github.com/apache/spark/pull/53035#discussion_r2561531946
##########
python/pyspark/sql/pandas/serializers.py:
##########
@@ -1222,53 +1222,31 @@ def __init__(
def load_stream(self, stream):
"""
- Yield column iterators instead of concatenating batches.
- Each group yields a structure where indexing by column offset gives an
iterator of arrays.
+ Yield an iterator that produces one list of column arrays per batch.
+ Each group yields Iterator[List[pa.Array]], allowing UDF to process
batches one by one
+ without consuming all batches upfront.
"""
+
+ def process_group(batches: "Iterator[pa.RecordBatch]"):
+ # Convert each Arrow batch to a list of column arrays on-demand,
yielding one list per batch
+ for batch in batches:
+ # Extract all columns from the batch as a list of arrays
+ column_arrays = [batch.column(col_idx) for col_idx in
range(batch.num_columns)]
+ yield column_arrays
Review Comment:
Is this effectively just
```suggestion
yield batch.columns
```
?
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