AlenkaF commented on code in PR #12704:
URL: https://github.com/apache/arrow/pull/12704#discussion_r841541096
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python/pyarrow/parquet.py:
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@@ -2201,6 +3055,47 @@ def write_to_dataset(table, root_path,
partition_cols=None,
Using `metadata_collector` in kwargs allows one to collect the
file metadata instances of dataset pieces. The file paths in the
ColumnChunkMetaData will be set relative to `root_path`.
+
+ Examples
+ --------
+ Generate an example PyArrow Table:
+
+ >>> import pyarrow as pa
+ >>> import pandas as pd
+ >>> df = pd.DataFrame({'year': [2020, 2022, 2021, 2022, 2019, 2021],
+ ... 'month': [3, 5, 7, 9, 11, 12],
+ ... 'day': [1, 5, 9, 13, 17, 23],
+ ... 'n_legs': [2, 2, 4, 4, 5, 100],
+ ... 'animals': ["Flamingo", "Parrot", "Dog", "Horse",
+ ... "Brittle stars", "Centipede"]})
+ >>> table = pa.Table.from_pandas(df)
+
+ and write it to a partitioned dataset:
+
+ >>> import pyarrow.parquet as pq
+ >>> pq.write_to_dataset(table, root_path='dataset_name_3',
+ ... partition_cols=['year', 'month', 'day'],
+ ... use_legacy_dataset=False
+ ... )
+ >>> pq.ParquetDataset('dataset_name_3', use_legacy_dataset=False).files
+ ['dataset_name_3/year=2019/month=11/day=17/part-0.parquet', ...
+
+ Use old Arrow Dataset API and override the partition filename:
+
+ >>> pq.write_to_dataset(table, root_path='dataset_name_5',
+ ... partition_cols=['year', 'month', 'day'],
+ ... partition_filename_cb=lambda x:
+ ... str(x[0]) + str(x[1]) + str(x[2]) + '.parquet'
+ ... )
+ >>> pq.ParquetDataset('dataset_name_5/', use_legacy_dataset=False).files
+ ['dataset_name_5/year=2019/month=11/day=17/20191117.parquet', ...
+
+ Write to a single Parquet file:
Review Comment:
Yes, I should make this clearer.
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