jorisvandenbossche commented on code in PR #12811:
URL: https://github.com/apache/arrow/pull/12811#discussion_r845311683
##########
python/pyarrow/tests/test_dataset.py:
##########
@@ -937,7 +937,7 @@ def _create_dataset_for_fragments(tempdir, chunk_size=None,
filesystem=None):
path = str(tempdir / "test_parquet_dataset")
# write_to_dataset currently requires pandas
- pq.write_to_dataset(table, path,
+ pq.write_to_dataset(table, path, use_legacy_dataset=True,
partition_cols=["part"], chunk_size=chunk_size)
Review Comment:
The dataset API now has a `max_rows_per_group`, but that doesn't necessarily
directly relate to Parquet row groups?
It's more generic about how many rows are written in one go, but so
effectively is therefore also a max parquet row group size? (since those need
to be written in one go)
##########
python/pyarrow/tests/test_dataset.py:
##########
@@ -937,7 +937,7 @@ def _create_dataset_for_fragments(tempdir, chunk_size=None,
filesystem=None):
path = str(tempdir / "test_parquet_dataset")
# write_to_dataset currently requires pandas
- pq.write_to_dataset(table, path,
+ pq.write_to_dataset(table, path, use_legacy_dataset=True,
partition_cols=["part"], chunk_size=chunk_size)
Review Comment:
The dataset API now has a `max_rows_per_group`, I see, but that doesn't
necessarily directly relate to Parquet row groups?
It's more generic about how many rows are written in one go, but so
effectively is therefore also a max parquet row group size? (since those need
to be written in one go)
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