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WIP: Testing-only PR to check maint-19.0.0 status #45194

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@amoeba amoeba commented Jan 7, 2025

Caution

Do not merge this PR.

This PR is only to pre-check the first RC for 19.0.0 with crossbow and should not be merged.

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Thanks for opening a pull request!

If this is not a minor PR. Could you open an issue for this pull request on GitHub? https://github.com/apache/arrow/issues/new/choose

Opening GitHub issues ahead of time contributes to the Openness of the Apache Arrow project.

Then could you also rename the pull request title in the following format?

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amoeba commented Jan 7, 2025

@github-actions crossbow submit --group verify-rc-source

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amoeba commented Jan 7, 2025

@github-actions crossbow submit --group packaging

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Revision: 77b39d7

Submitted crossbow builds: ursacomputing/crossbow @ actions-37e1cb2f5f

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Revision: 77b39d7

Submitted crossbow builds: ursacomputing/crossbow @ actions-8d976c45f6

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amoeba commented Jan 8, 2025

@github-actions crossbow submit almalinux-9-arm64

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amoeba commented Jan 8, 2025

@github-actions crossbow submit debian-bookworm-arm64

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amoeba commented Jan 8, 2025

@github-actions crossbow submit wheel-manylinux-2014-cp313-cp313-arm64

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Revision: 77b39d7

Submitted crossbow builds: ursacomputing/crossbow @ actions-e6674a8807

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raulcd commented Jan 8, 2025

I think we might have some possible leaks on parquet encryption based on the valgrind failures that we should investigate.

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amoeba commented Jan 8, 2025

Thanks @kou

Hmm. verify-rc-source-python-macos-conda-amd64 isn't failed in nightly build with this error.

I also ran the job on my crossbow queue and it succeeds. It's strange.

I think we might have some possible leaks on parquet encryption based on the valgrind failures that we should investigate.

Good catch, I forgot to check that nightly group. I can look tomorrow.

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kou commented Jan 9, 2025

Hmm. verify-rc-source-python-macos-conda-amd64 isn't failed in nightly build with this error. This error may be transient or caused by a conda package problem. I re-run the job: https://github.com/ursacomputing/crossbow/actions/runs/12658197249

Passed. We can ignore this failure.

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raulcd commented Jan 9, 2025

I've opened #45212 to track the issue

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raulcd commented Jan 9, 2025

The valgrind issue has been fixed and merged. It is tagged as 19.0.0 to be cherry-picked.

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amoeba commented Jan 9, 2025

Thanks all. I'll re-run jobs here after #44195 is merged and then move on to creating an RC.

@amoeba amoeba requested a review from wgtmac as a code owner January 9, 2025 19:48
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amoeba commented Jan 9, 2025

@github-actions crossbow submit --group verify-rc-source

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amoeba commented Jan 9, 2025

@github-actions crossbow submit --group packaging

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Revision: acb2282

Submitted crossbow builds: ursacomputing/crossbow @ actions-b67986b35c

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Revision: acb2282

Submitted crossbow builds: ursacomputing/crossbow @ actions-6d471c9383

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amoeba commented Jan 10, 2025

@github-actions crossbow submit verify-rc-source-integration-linux-ubuntu-22.04-amd64

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amoeba commented Jan 10, 2025

@github-actions crossbow submit wheel-macos-monterey-cp313-cp313-arm64

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Revision: acb2282

Submitted crossbow builds: ursacomputing/crossbow @ actions-c341cea2ab

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jorisvandenbossche and others added 5 commits January 10, 2025 20:16
…das for string view type (#45176)

### Rationale for this change

Currently this keyword works for string or large string:

```python
>>> table = pa.table({"col": pa.array(["a", "b", "a"], pa.string())})
>>> table.to_pandas(strings_to_categorical=True).dtypes
col    category
dtype: object
>>> table = pa.table({"col": pa.array(["a", "b", "a"], pa.large_string())})
>>> table.to_pandas(strings_to_categorical=True).dtypes
col    category
dtype: object
```

but not for string view:

```python
>>> table = pa.table({"col": pa.array(["a", "b", "a"], pa.string_view())})
>>> table.to_pandas(strings_to_categorical=True).dtypes
col    object
dtype: object
```

For consistency we should make that keyword check for string view columns as well, I think

From https://github.com/apache/arrow/pull/44195/files#r1901831460

### Are these changes tested?

Yes

### Are there any user-facing changes?

Yes, when using the `strings_to_categorical=True` keyword and having a string_view type, this column will now be converted to a pandas Categorical

* GitHub Issue: #45175

Authored-by: Joris Van den Bossche <[email protected]>
Signed-off-by: Raúl Cumplido <[email protected]>
### What changes are included in this PR?

Updates to the release guide. Mostly changes to make the guide up to date with how release are being done currently.

### Are these changes tested?

Previewed locally.

### Are there any user-facing changes?

More accurate docs.

Fixes #45140 
* GitHub Issue: #45140

Lead-authored-by: Bryce Mecum <[email protected]>
Co-authored-by: Sutou Kouhei <[email protected]>
Signed-off-by: Bryce Mecum <[email protected]>
…/arrow-java (#45199)

### Rationale for this change

For apache/arrow-java#493.

### What changes are included in this PR?

Remove `java_` prefix.

### Are these changes tested?

Yes.

### Are there any user-facing changes?

No.
* GitHub Issue: #45164

Authored-by: Sutou Kouhei <[email protected]>
Signed-off-by: Sutou Kouhei <[email protected]>
…erty (#45213)

### Rationale for this change

The PR to introduce SizeStatistics has spanned several months, during which time WriterProperties::Builder(const WriterProperties& properties) was added.

### What changes are included in this PR?

This PR fixes WriterProperties::Builder(const WriterProperties& properties) function to initialize size_statistics_level_.

### Are these changes tested?

Pass CIs.

### Are there any user-facing changes?

No.
* GitHub Issue: #45212

Authored-by: Gang Wu <[email protected]>
Signed-off-by: Gang Wu <[email protected]>
…44195)

### Rationale for this change

With pandas' [PDEP-14](https://pandas.pydata.org/pdeps/0014-string-dtype.html) proposal, pandas is planning to introduce a default string dtype in pandas 3.0 (instead of the current object dtype).

This will become the default in pandas 3.0, and can be enabled with an option in the upcoming pandas 2.3 (`pd.options.future.infer_string = True`). To prepare for that, we should start using that string dtype in `to_pandas()` conversions when that option is enabled.

### What changes are included in this PR?

- If pandas >= 3.0 is used or the pandas option is enabled, ensure that `to_pandas()` calls use the default string dtype of pandas for string-like columns (string, large_string, string_view)

### Are these changes tested?

It is tested in the pandas-nightly crossbow build.

There is still one failure that is because of a bug on the pandas side (pandas-dev/pandas#59879)

### Are there any user-facing changes?

**This PR includes breaking changes to public APIs.** Depending on the version of pandas, `to_pandas()` will change to use pandas' string dtype instead of object dtype. This is a breaking user-facing change, but essentially just following the equivalent change in default dtype on the pandas side.

* GitHub Issue: #43683

Lead-authored-by: Joris Van den Bossche <[email protected]>
Co-authored-by: Raúl Cumplido <[email protected]>
Signed-off-by: Joris Van den Bossche <[email protected]>
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