Support barrier mode for mapInPandas/mapInArrow #10364
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Signed-off-by: Bobby Wang <wbo4958@gmail.com>
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| @@ -425,3 +426,41 @@ def test_func(spark): | |||
| lambda data: [pd.DataFrame([len(list(data))])], schema="ret:integer") | |||
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| assert_gpu_and_cpu_are_equal_collect(test_func, conf=arrow_udf_conf) | |||
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| @pytest.mark.skipif(is_before_spark_350(), | |||
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NIT: Better to ignore order for result comparison.
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no need to do that, since there is only 1 partition, the result will not be mess up.
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This reverts commit cca5955. Signed-off-by: Jason Lowe <jlowe@nvidia.com>
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Signed-off-by: Bobby Wang <wbo4958@gmail.com>
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* Support barrier mode for mapInPandas/mapInArrow (#10364) Signed-off-by: Bobby Wang <wbo4958@gmail.com> * support databricks * license --------- Signed-off-by: Bobby Wang <wbo4958@gmail.com>
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To fix #10344
Spark 3.5 has introduced a new feature supporting barrier mode for mapInPandas/mapInArrow, more detail can be found at https://issues.apache.org/jira/browse/SPARK-42896. However, spark-rapids missed this feature which resulted in unexpected behavior. For example
The same tasks of the above code will run on barrier mode on the CPU, while on
non-barriermode on the GPU with spark-rapids.