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dont use take with arrow #2336

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dont use take with arrow #2336

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6a0d9a2
dont use take with arrow
Ben-Epstein Feb 9, 2023
5d7ea60
array_types take updated
Ben-Epstein Feb 13, 2023
4b21a64
in module already
Ben-Epstein Feb 13, 2023
0a47d13
more takes
maartenbreddels Feb 14, 2023
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15 changes: 12 additions & 3 deletions packages/vaex-core/vaex/column.py
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Original file line number Diff line number Diff line change
Expand Up @@ -382,8 +382,17 @@ def __getitem__(self, slice):
# arrow and numpy do not like the negative indices, so we set them to 0
take_indices = indices.copy()
take_indices[mask] = 0
if isinstance(ar_unfiltered, supported_arrow_array_types):
ar = ar_unfiltered.take(vaex.array_types.to_arrow(take_indices))
# Don't use .take in arrow anymore
# https://issues.apache.org/jira/browse/ARROW-9773
# slice is zero-copy
if isinstance(ar_unfiltered, pa.Array):
ar = pa.concat_arrays(
[ar_unfiltered.slice(i, 1) for i in take_indices]
)
elif isinstance(ar_unfiltered, pa.ChunkedArray):
ar = pa.concat_arrays(
[ar_unfiltered.slice(i, 1).combine_chunks() for i in take_indices]
)
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Suggested change
# Don't use .take in arrow anymore
# https://issues.apache.org/jira/browse/ARROW-9773
# slice is zero-copy
if isinstance(ar_unfiltered, pa.Array):
ar = pa.concat_arrays(
[ar_unfiltered.slice(i, 1) for i in take_indices]
)
elif isinstance(ar_unfiltered, pa.ChunkedArray):
ar = pa.concat_arrays(
[ar_unfiltered.slice(i, 1).combine_chunks() for i in take_indices]
)
if isinstance(ar_unfiltered, pa.Array):
ar = ar_unfiltered.take(vaex.array_types.to_arrow(take_indices))
elif isinstance(ar_unfiltered, pa.ChunkedArray):
# Don't use .take in arrow for chunked arrays
# https://issues.apache.org/jira/browse/ARROW-9773
# slice is zero-copy
ar = pa.concat_arrays(
[ar_unfiltered.slice(i, 1).combine_chunks() for i in take_indices]
)

it is only an issue for chunked arrays right?
Maybe the best place to put this is vaex.array_types.take ?
There is already a take function there, and if all places in vaex uses that function, we have a nice central place where we can solve this.

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@maartenbreddels i do not think this is only an issue for chunked_arrays, I think it's an issue with take broadly. I definitely like the idea of moving it down to a centralized place, but I think no matter the array type, you need to replace take with slice

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https://issues.apache.org/jira/browse/ARROW-9773 only talks about chunked arrays, and I also think it's only a problem for that (since it's more complex).

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Okay i'll take your word on this one, you certainly know more here. I'll move this into the vaex array_types.take

else:
ar = ar_unfiltered[take_indices]
assert not np.ma.isMaskedArray(indices)
Expand Down Expand Up @@ -825,4 +834,4 @@ def get_mask(self):
return self.string_sequence.mask()

def astype(self, type):
return self.to_numpy().astype(type)
return self.to_numpy().astype(type)