westonpace commented on a change in pull request #10628:
URL: https://github.com/apache/arrow/pull/10628#discussion_r665252360
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File path: python/pyarrow/tests/test_dataset.py
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@@ -2672,47 +2672,56 @@ def test_feather_format(tempdir, dataset_reader):
dataset_reader.to_table(ds.dataset(basedir, format="feather"))
-def _create_parquet_dataset_simple(root_path):
+def _create_parquet_dataset_simple(root_path, use_legacy_dataset):
import pyarrow.parquet as pq
metadata_collector = []
- for i in range(4):
- table = pa.table({'f1': [i] * 10, 'f2': np.random.randn(10)})
- pq.write_to_dataset(
- table, str(root_path), metadata_collector=metadata_collector
- )
+ f1_vals = [item for chunk in range(4) for item in [chunk] * 10]
+
+ table = pa.table({'f1': f1_vals, 'f2': np.random.randn(40)})
+ pq.write_to_dataset(
+ table, str(root_path), partition_cols=['f1'],
+ use_legacy_dataset=use_legacy_dataset,
+ metadata_collector=metadata_collector
+ )
+
+ partitionless_schema = pa.schema([pa.field('f2', pa.float64())])
metadata_path = str(root_path / '_metadata')
# write _metadata file
pq.write_metadata(
- table.schema, metadata_path,
+ partitionless_schema, metadata_path,
Review comment:
See below comment. Ideally no, but will be addressed in ARROW-13269
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