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Handle null partitions in P2P shuffling #7922

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Merged
hendrikmakait merged 5 commits into from
Jun 20, 2023
Merged

Handle null partitions in P2P shuffling #7922

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32fe846
Promote null types during concat_tables (#7837).
detroyejr Jun 15, 2023
7ec002d
Test handling null partitions during p2p shuffle.
detroyejr Jun 15, 2023
be815d2
Move to shuffle/tests and add an assert.
detroyejr Jun 16, 2023
3635803
Reuse imported dask.datafame and drop assert.
detroyejr Jun 20, 2023
f8a46bc
Merge branch 'main' into pr/detroyejr/7922-1
hendrikmakait Jun 20, 2023
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2 changes: 1 addition & 1 deletion distributed/shuffle/_arrow.py
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Original file line number Diff line number Diff line change
Expand Up @@ -55,7 +55,7 @@ def convert_partition(data: bytes, meta: pd.DataFrame) -> pd.DataFrame:
while file.tell() < end:
sr = pa.RecordBatchStreamReader(file)
shards.append(sr.read_all())
table = pa.concat_tables(shards)
table = pa.concat_tables(shards, promote=True)
df = table.to_pandas(self_destruct=True)

def default_types_mapper(pyarrow_dtype: pa.DataType) -> object:
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19 changes: 19 additions & 0 deletions distributed/shuffle/tests/test_shuffle.py
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Expand Up @@ -1826,3 +1826,22 @@ async def test_closed_worker_returns_before_barrier(c, s):
await c.close()
await asyncio.gather(*[clean_worker(w) for w in workers])
await clean_scheduler(s)


@gen_cluster(client=True)
async def test_handle_null_partitions_p2p_shuffling(c, s, *workers):
data = [
{"companies": [], "id": "a", "x": None},
{"companies": [{"id": 3}, {"id": 5}], "id": "b", "x": None},
{"companies": [{"id": 3}, {"id": 4}, {"id": 5}], "id": "c", "x": "b"},
{"companies": [{"id": 9}], "id": "a", "x": "a"},
]
df = pd.DataFrame(data)
ddf = dd.from_pandas(df, npartitions=2)
ddf = ddf.shuffle(on="id", shuffle="p2p", ignore_index=True)
result = await c.compute(ddf)
dd.assert_eq(result, df)

await c.close()
await asyncio.gather(*[clean_worker(w) for w in workers])
await clean_scheduler(s)