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Posted to jira@arrow.apache.org by "Krisztian Szucs (Jira)" <ji...@apache.org> on 2022/01/25 09:31:00 UTC
[jira] [Commented] (ARROW-15438) [Python] Flaky test test_write_dataset_max_open_files
[ https://issues.apache.org/jira/browse/ARROW-15438?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17481678#comment-17481678 ]
Krisztian Szucs commented on ARROW-15438:
-----------------------------------------
cc [~jorisvandenbossche]
> [Python] Flaky test test_write_dataset_max_open_files
> -----------------------------------------------------
>
> Key: ARROW-15438
> URL: https://issues.apache.org/jira/browse/ARROW-15438
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Reporter: David Li
> Priority: Major
>
> Found during 7.0.0 verification
> {noformat}
> pyarrow/tests/test_dataset.py::test_write_dataset_max_open_files FAILED [ 30%]
> >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> traceback >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>tempdir = PosixPath('/tmp/pytest-of-root/pytest-1/test_write_dataset_max_open_fi0') def test_write_dataset_max_open_files(tempdir):
> directory = tempdir / 'ds'
> file_format = "parquet"
> partition_column_id = 1
> column_names = ['c1', 'c2']
> record_batch_1 = pa.record_batch(data=[[1, 2, 3, 4, 0, 10],
> ['a', 'b', 'c', 'd', 'e', 'a']],
> names=column_names)
> record_batch_2 = pa.record_batch(data=[[5, 6, 7, 8, 0, 1],
> ['a', 'b', 'c', 'd', 'e', 'c']],
> names=column_names)
> record_batch_3 = pa.record_batch(data=[[9, 10, 11, 12, 0, 1],
> ['a', 'b', 'c', 'd', 'e', 'd']],
> names=column_names)
> record_batch_4 = pa.record_batch(data=[[13, 14, 15, 16, 0, 1],
> ['a', 'b', 'c', 'd', 'e', 'b']],
> names=column_names)
>
> table = pa.Table.from_batches([record_batch_1, record_batch_2,
> record_batch_3, record_batch_4])
>
> partitioning = ds.partitioning(
> pa.schema([(column_names[partition_column_id], pa.string())]),
> flavor="hive")
>
> data_source_1 = directory / "default"
>
> ds.write_dataset(data=table, base_dir=data_source_1,
> partitioning=partitioning, format=file_format)
>
> # Here we consider the number of unique partitions created when
> # partitioning column contains duplicate records.
> # Returns: (number_of_files_generated, number_of_partitions)
> def _get_compare_pair(data_source, record_batch, file_format, col_id):
> num_of_files_generated = _get_num_of_files_generated(
> base_directory=data_source, file_format=file_format)
> number_of_partitions = len(pa.compute.unique(record_batch[col_id]))
> return num_of_files_generated, number_of_partitions
>
> # CASE 1: when max_open_files=default & max_open_files >= num_of_partitions
> # In case of a writing to disk via partitioning based on a
> # particular column (considering row labels in that column),
> # the number of unique rows must be equal
> # to the number of files generated
>
> num_of_files_generated, number_of_partitions \
> = _get_compare_pair(data_source_1, record_batch_1, file_format,
> partition_column_id)
> assert num_of_files_generated == number_of_partitions
>
> # CASE 2: when max_open_files > 0 & max_open_files < num_of_partitions
> # the number of files generated must be greater than the number of
> # partitions
>
> data_source_2 = directory / "max_1"
>
> max_open_files = 3
>
> ds.write_dataset(data=table, base_dir=data_source_2,
> partitioning=partitioning, format=file_format,
> max_open_files=max_open_files)
>
> num_of_files_generated, number_of_partitions \
> = _get_compare_pair(data_source_2, record_batch_1, file_format,
> partition_column_id)
> > assert num_of_files_generated > number_of_partitions
> E assert 5 > 5pyarrow/tests/test_dataset.py:3807: AssertionError
> {noformat}
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