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ARROW-16240: [Python] Support row_group_size/chunk_size keyword in pq.write_to_dataset with use_legacy_dataset=False #12955

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AlenkaF wants to merge 6 commits into from
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ARROW-16240: [Python] Support row_group_size/chunk_size keyword in pq.write_to_dataset with use_legacy_dataset=False #12955

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05a65c2
Support row_group_size/chunk_size keyword in pq.write_to_dataset
AlenkaF Apr 22, 2022
f69d9b9
Add row_group_size also
AlenkaF Apr 22, 2022
93141c1
Fix precedence
AlenkaF Apr 22, 2022
edf3e7a
Update python/pyarrow/parquet/__init__.py
jorisvandenbossche Apr 22, 2022
f370e9f
Flake8
kszucs Apr 22, 2022
15f0c39
Remove accidentally committed script
kszucs Apr 22, 2022
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9 changes: 8 additions & 1 deletion python/pyarrow/parquet/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3109,6 +3109,12 @@ def file_visitor(written_file):
# extract non-file format options
schema = kwargs.pop("schema", None)
use_threads = kwargs.pop("use_threads", True)
chunk_size = kwargs.pop("chunk_size", None)
row_group_size = kwargs.pop("row_group_size", None)

row_group_size = (
row_group_size if row_group_size is not None else chunk_size
)

# raise for unsupported keywords
msg = (
Expand Down Expand Up @@ -3147,7 +3153,8 @@ def file_visitor(written_file):
partitioning=partitioning, use_threads=use_threads,
file_visitor=file_visitor,
basename_template=basename_template,
existing_data_behavior=existing_data_behavior)
existing_data_behavior=existing_data_behavior,
max_rows_per_group=row_group_size)
return

# warnings and errors when using legecy implementation
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2 changes: 1 addition & 1 deletion python/pyarrow/tests/test_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -971,7 +971,7 @@ 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, use_legacy_dataset=True,
pq.write_to_dataset(table, path,
partition_cols=["part"], chunk_size=chunk_size)
dataset = ds.dataset(
path, format="parquet", partitioning="hive", filesystem=filesystem
Expand Down