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Add a test for ORC write with more than one stripe #11743

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Add a test for ORC write with more than one stripe #11743

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5075d7d
Add a test for ORC write with more than one stripe
ustcfy Nov 21, 2024
d51c3ad
Mark the test case as xfail due to known issue #11736
ustcfy Nov 21, 2024
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14 changes: 14 additions & 0 deletions integration_tests/src/main/python/orc_write_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -91,6 +91,20 @@ def test_write_round_trip(spark_tmp_path, orc_gens, orc_impl):
data_path,
conf={'spark.sql.orc.impl': orc_impl, 'spark.rapids.sql.format.orc.write.enabled': True})

@pytest.mark.parametrize('orc_gen', [pytest.param(boolean_gen, marks=pytest.mark.xfail(reason='https://github.com/NVIDIA/spark-rapids/issues/11736'))], ids=idfn)
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In my understanding, we also need to test other kinds of data, not just the ones that failed?

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I would like to see more data types so that we are not concerned about what other errors we might be seeing. I would also like to see parquet tests with more that one row group. I am fine if that is a follow on issue too.

@pytest.mark.parametrize('orc_impl', ["native", "hive"])
@allow_non_gpu(*non_utc_allow)
def test_write_more_than_one_stripe_round_trip(spark_tmp_path, orc_gen, orc_impl):
gen_list = [('_c0', orc_gen)]
data_path = spark_tmp_path + '/ORC_DATA'
assert_gpu_and_cpu_writes_are_equal_collect(
# Generate a large enough dataframe to produce more than one stripe
# Preferably use only one partition to avoid splitting the data
lambda spark, path: gen_df(spark, gen_list, 12800, num_slices=1).write.orc(path),
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Question: Where does the 12800 number come from? Do we know it will be greater than 64m (orc stripe size) for all the datagens you tested?

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This number comes from my experiment.(

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In general CUDF will split the data by rows and by size.

https://github.com/rapidsai/cudf/blob/f54c1a5ad34133605d3b5b447d9717ce7eb6dba0/cpp/include/cudf/io/orc.hpp#L585-L587

https://github.com/rapidsai/cudf/blob/f54c1a5ad34133605d3b5b447d9717ce7eb6dba0/cpp/include/cudf/io/orc.hpp#L41-L42

In parquet the split rows in 20,000 but for ORC it is 1,000,000. I am not sure how 12,800 booelan values produces a more than one stripe. I would really like to understand this better because I would expect that to be no where close to the row group count we expect to cause multiple slices.

lambda spark, path: spark.read.orc(path),
data_path,
conf={'spark.sql.orc.impl': orc_impl, 'spark.rapids.sql.format.orc.write.enabled': True})

@pytest.mark.parametrize('orc_gen', orc_write_odd_empty_strings_gens_sample, ids=idfn)
@pytest.mark.parametrize('orc_impl', ["native", "hive"])
def test_write_round_trip_corner(spark_tmp_path, orc_gen, orc_impl):
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