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Avoid "p2p" shuffle as a default when dask_cudf is imported #15469

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merged 9 commits into from
Apr 8, 2024
Merged

Avoid "p2p" shuffle as a default when dask_cudf is imported #15469

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36febfd
avoid p2p shuffle as a default
rjzamora Apr 5, 2024
7d9d2e8
Merge branch 'branch-24.06' into avoid-p2p-default
rjzamora Apr 5, 2024
68bafe5
Merge branch 'branch-24.06' into avoid-p2p-default
rjzamora Apr 5, 2024
bc39bfc
Merge branch 'branch-24.06' into avoid-p2p-default
rjzamora Apr 5, 2024
10fded0
rename helper to at_least_n_gpus
rjzamora Apr 5, 2024
609b936
update comment
rjzamora Apr 5, 2024
091b160
Merge branch 'branch-24.06' into avoid-p2p-default
rjzamora Apr 5, 2024
7563b54
Merge branch 'branch-24.06' into avoid-p2p-default
rjzamora Apr 8, 2024
836c485
Merge branch 'branch-24.06' into avoid-p2p-default
rjzamora Apr 8, 2024
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3 changes: 3 additions & 0 deletions python/dask_cudf/dask_cudf/expr/__init__.py
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Expand Up @@ -8,6 +8,9 @@

# Register custom expressions and collections
if QUERY_PLANNING_ON:
# Broadly avoid "p2p" and "disk" defaults for now
config.set({"dataframe.shuffle.method": "tasks"})

try:
import dask_cudf.expr._collection
import dask_cudf.expr._expr
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22 changes: 19 additions & 3 deletions python/dask_cudf/dask_cudf/tests/test_distributed.py
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Expand Up @@ -16,9 +16,9 @@
dask_cuda = pytest.importorskip("dask_cuda")


def more_than_two_gpus():
def more_than_n_gpus(n):
ngpus = len(numba.cuda.gpus)
return ngpus >= 2
return ngpus >= n


@pytest.mark.parametrize("delayed", [True, False])
Expand Down Expand Up @@ -54,7 +54,7 @@ def test_merge():


@pytest.mark.skipif(
not more_than_two_gpus(), reason="Machine does not have more than two GPUs"
not more_than_n_gpus(2), reason="Machine does not have more than two GPUs"
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Suggested change
not more_than_n_gpus(2), reason="Machine does not have more than two GPUs"
not more_than_n_gpus(2), reason="Machine does not at least two GPUs"

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Just like the message was misleading, I believe the function name is too and I would suggest renaming it to at_least_n_gpus or something more accurate.

)
def test_ucx_seriesgroupby():
pytest.importorskip("ucp")
Expand Down Expand Up @@ -97,3 +97,19 @@ def test_p2p_shuffle():
ddf.compute().sort_values("x"),
check_index=False,
)


@pytest.mark.skipif(
not more_than_n_gpus(3),
reason="Machine does not have more than three GPUs",
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Suggested change
reason="Machine does not have more than three GPUs",
reason="Machine does not have at least three GPUs",

)
def test_unique():
with dask_cuda.LocalCUDACluster(n_workers=3) as cluster:
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Needed >2 workers to reproduce the error locally. Not sure what the problem is yet, but the to-pyarrow dispatch is failing to register on one or more workers.

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So that means the error is not reproducible by disabling P2P shuffle and this test confirms that, right?

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This PR does something pretty simple, but the background is slightly confusing:

  • Using the latest release of dask, this test would fail without the global "tasks" config that is set in this PR
  • After Add lazy "cudf" registration for p2p-related dispatch functions dask/dask#11040, this test will also pass when the "p2p" shuffle is used
  • Even though "p2p" works for dask:main, I still think it makes sense to use the "tasks" default (at least for now). Although "p2p" should theoretically be more stable, I have not found this to be the case in practice for GPUs. Also, "tasks" is definitely faster.

with Client(cluster):
df = cudf.DataFrame({"x": ["a", "b", "c", "a", "a"]})
ddf = dask_cudf.from_cudf(df, npartitions=2)
dd.assert_eq(
df.x.unique(),
ddf.x.unique().compute(),
check_index=False,
)
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