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Tonnam Balankura edited comment on ARROW-9573 at 8/3/20, 6:07 AM: ------------------------------------------------------------------ Thank you [~bkietz] for taking a look. Seems like [legacy pq.read_table|https://github.com/apache/arrow/blob/master/python/pyarrow/parquet.py#L970] pushes filtered files if no filtered directories are found. If I understand correctly, with the new dataset API, [discovery.cc|https://github.com/apache/arrow/blob/master/cpp/src/arrow/dataset/discovery.cc#L184] handles the logic of ignoring directories that starts with "." and "_". I presume that modifying the C++ code to behave like the legacy {{pq.read_table}} is not the preferred approach. One partial solution I can think of is to add the {{ignore_prefixes}} option to {{read_table}} and {{_ParquetDatasetV2}} (and passing the option to {{ds.dataset}}) to allow users to set it when calling {{read_table}}. Maybe that would help users with the loading parquet with a partitioned column that starts with an underscore. Do you think that could work? was (Author: tonnamb): Thank you [~bkietz] for taking a look. Seems like [legacy pq.read_table|https://github.com/apache/arrow/blob/master/python/pyarrow/parquet.py#L970] pushes filtered files if no filtered directories are found. If I understand correctly, with the new dataset API, [discovery.cc|https://github.com/apache/arrow/blob/master/cpp/src/arrow/dataset/discovery.cc#L184] handles the logic of ignoring directories that starts with "." and "_". I presume that modifying the C++ code to behave like the legacy {{pq.read_table}} is not the preferred approach. One partial solution I can think of is to add the {{ignore_prefixes}} option to {{read_table}} and {{_ParquetDatasetV2}} to allow users to set it when calling {{read_table}}. Maybe that would help users with the loading parquet with a partitioned column that starts with an underscore. Do you think that could work? > [Python] Parquet doesn't load when partitioned column starts with '_' > --------------------------------------------------------------------- > > Key: ARROW-9573 > URL: https://issues.apache.org/jira/browse/ARROW-9573 > Project: Apache Arrow > Issue Type: Bug > Components: Python > Affects Versions: 1.0.0 > Reporter: Tonnam Balankura > Assignee: Ben Kietzman > Priority: Major > > When the loading parquet with partitioned column that starts with an > underscore '_', nothing is loaded. No exceptions are raised either. Loading > this parquet have worked for me in pyarrow 0.17.1, but not working anymore in > pyarrow 1.0.0. > On the other hand, loading parquet with a partitioned column starting with > '_' is possible by using the `use_legacy_dataset` option. Also, when the > column that starts with an underscore is not a partitioned column, loading > parquet seems to work as expected. > {code:python} > >>> import pyarrow as pa > >>> import pyarrow.parquet as pq > >>> import pandas as pd > >>> df1 = pd.DataFrame(data={'_COL_1': [1, 2], 'COL_2': [3, 4], 'COL_3': [5, > >>> 6]}) > >>> table1 = pa.Table.from_pandas(df1) > >>> pq.write_to_dataset(table1, partition_cols=['_COL_1', 'COL_2'], > >>> root_path='test_parquet1') > >>> df_pq1 = pq.read_table('test_parquet1') > >>> df_pq1 > pyarrow.Table > >>> len(df_pq1) > 0 > >>> df_pq1_legacy = pq.read_table('test_parquet1', use_legacy_dataset=True) > pyarrow.Table > COL_3: int64 > _COL_1: dictionary<values=int64, indices=int32, ordered=0> > COL_2: dictionary<values=int64, indices=int32, ordered=0> > >>> len(df_pq1_legacy) > 2 > >>> df2 = pd.DataFrame(data={'COL_1': [1, 2], 'COL_2': [3, 4], '_COL_3': [5, > >>> 6]}) > >>> table2 = pa.Table.from_pandas(df2) > >>> pq.write_to_dataset(table2, partition_cols=['COL_1', 'COL_2'], > >>> root_path='test_parquet2') > >>> df_pq2 = pq.read_table('test_parquet2') > >>> df_pq2 > pyarrow.Table > _COL_3: int64 > COL_1: int32 > COL_2: int32 > >>> len(df_pq2) > 2 > {code} -- This message was sent by Atlassian Jira (v8.3.4#803005)