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Temporarily disable integration test - test_hash_reduction_pivot_without_nans #4534

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merged 3 commits into from
Jan 14, 2022
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Temporarily disable integration test - test_hash_reduction_pivot_without_nans #4534

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37a8c83
disable test_hash_reduction_pivot_without_nans inegration test
nartal1 Jan 14, 2022
249ae12
addressed review comments
nartal1 Jan 14, 2022
3a73bba
fix typo
nartal1 Jan 14, 2022
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26 changes: 14 additions & 12 deletions integration_tests/src/main/python/hash_aggregate_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -533,18 +533,20 @@ def fetch_pivot_values(spark):
"PivotFirst",
conf=_nans_float_conf)

@approximate_float
@ignore_order(local=True)
@incompat
@pytest.mark.parametrize('data_gen', _init_list_no_nans, ids=idfn)
@pytest.mark.parametrize('conf', get_params(_confs_with_nans, params_markers_for_confs_nans), ids=idfn)
def test_hash_reduction_pivot_without_nans(data_gen, conf):
assert_gpu_and_cpu_are_equal_collect(
lambda spark: gen_df(spark, data_gen, length=100)
.groupby()
.pivot('b')
.agg(f.sum('c')),
conf=conf)
# https://github.com/NVIDIA/spark-rapids/issues/4514
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It would be better to skip the test rather than comment it out:

@pytest.mark.skip(reason='https://github.com/NVIDIA/spark-rapids/issues/4514')

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xfail seems appropriate here, as this is code we fully expect to pass but is failing due to known issues. skip should be used for tests that are never expected to pass if attempted, even after bugfixes (e.g.: tests for a feature that a particular Spark version does not support, etc.)

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It doesn't seem to be failing in github CI, so we probably want to skip?

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xfail is what we want. xfail is fine if the test actually passes (it reports it as an XPASS result).

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ah ok, sorry I thought xfail actually failed the tests when it passed. Thanks

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There is a config for that I wish we had done a good enough job with things that it would fail. But that is not how it is right now :(

# Disabling below test temporarily until we have a fix. Disabling fixes the CI pipeline failures.
#@approximate_float
#ignore_order(local=True)
#@incompat
#@pytest.mark.parametrize('data_gen', _init_list_no_nans, ids=idfn)
#@pytest.mark.parametrize('conf', get_params(_confs_with_nans, params_markers_for_confs_nans), ids=idfn)
#def test_hash_reduction_pivot_without_nans(data_gen, conf):
# assert_gpu_and_cpu_are_equal_collect(
# lambda spark: gen_df(spark, data_gen, length=100)
# .groupby()
# .pivot('b')
# .agg(f.sum('c')),
# conf=conf)

_repeat_agg_column_for_collect_op = [
RepeatSeqGen(BooleanGen(), length=15),
Expand Down