kevinjqliu commented on code in PR #1141:
URL: https://github.com/apache/iceberg-python/pull/1141#discussion_r1759604254
##########
pyiceberg/io/pyarrow.py:
##########
@@ -1251,10 +1253,17 @@ def _task_to_record_batches(
arrow_table = arrow_table.filter(pyarrow_filter)
if len(arrow_table) == 0:
continue
- batch = arrow_table.to_batches()[0]
- yield _to_requested_schema(
- projected_schema, file_project_schema, batch,
downcast_ns_timestamp_to_us=True, use_large_types=use_large_types
- )
+ output_batches = arrow_table.to_batches()
+ else:
+ output_batches = iter([batch])
+ for output_batch in output_batches:
Review Comment:
I'm a bit concerned about all the nested for-loops in this function. But
correctness comes first and we can always refactor later.
##########
pyiceberg/io/pyarrow.py:
##########
@@ -1251,10 +1253,17 @@ def _task_to_record_batches(
arrow_table = arrow_table.filter(pyarrow_filter)
if len(arrow_table) == 0:
continue
- batch = arrow_table.to_batches()[0]
- yield _to_requested_schema(
- projected_schema, file_project_schema, batch,
downcast_ns_timestamp_to_us=True, use_large_types=use_large_types
- )
+ output_batches = arrow_table.to_batches()
+ else:
+ output_batches = iter([batch])
Review Comment:
nit: redundant with `output_batches` already initialized to the same value
##########
pyiceberg/io/pyarrow.py:
##########
@@ -1238,10 +1238,12 @@ def _task_to_record_batches(
for batch in batches:
next_index = next_index + len(batch)
current_index = next_index - len(batch)
+ output_batches = iter([batch])
if positional_deletes:
# Create the mask of indices that we're interested in
indices = _combine_positional_deletes(positional_deletes,
current_index, current_index + len(batch))
batch = batch.take(indices)
+
# Apply the user filter
if pyarrow_filter is not None:
Review Comment:
a little unrelated to this PR, but I wonder if there's ever a case where we
need to filter (with `pyarrow_filter`) but `positional_deletes` is
None/empty/falsey.
I can see that as a potential issue
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