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…#20562) ## Which issue does this PR close? <!-- We generally require a GitHub issue to be filed for all bug fixes and enhancements and this helps us generate change logs for our releases. You can link an issue to this PR using the GitHub syntax. For example `Closes #123` indicates that this PR will close issue #123. --> - Closes #20561 ## Rationale for this change Previously `create_physical_plan` consumed the `DataFrame`, making it impossible to inspect (e.g. log) the physical plan and then execute the same `DataFrame` (e.g. via `write_parquet` or `collect`) without first cloning it. Since the method only needs `&LogicalPlan` (which it forwards to `SessionState::create_physical_plan`), there is no reason to take ownership. Changing the signature to `&self` makes the common pattern of "get plan for logging, then write/collect" work naturally. Also removes the now-unnecessary `self.clone()` in `DataFrame::cache` that was introduced for the same reason. <!-- Why are you proposing this change? If this is already explained clearly in the issue then this section is not needed. Explaining clearly why changes are proposed helps reviewers understand your changes and offer better suggestions for fixes. --> ## What changes are included in this PR? Changing `self` to `&self` <!-- There is no need to duplicate the description in the issue here but it is sometimes worth providing a summary of the individual changes in this PR. --> ## Are these changes tested? Yes <!-- We typically require tests for all PRs in order to: 1. Prevent the code from being accidentally broken by subsequent changes 2. Serve as another way to document the expected behavior of the code If tests are not included in your PR, please explain why (for example, are they covered by existing tests)? --> ## Are there any user-facing changes? <!-- If there are user-facing changes then we may require documentation to be updated before approving the PR. --> <!-- If there are any breaking changes to public APIs, please add the `api change` label. --> --------- Co-authored-by: xanderbailey <xanderbailey@users.noreply.github.com>
- Closes #20989. ## Rationale for this change The planner should be consistent with the expected SQL behavior—swapping the names of tables that have identical structure in a SQL query should not affect the schema for that query. ## What changes are included in this PR? - A fix in the `exclude_using_columns` helper method in `datafusion/expr/src/utils.rs` that ensures that we don't retain columns from the projected side when deciding which USING columns to exclude and which to retain on top of semi- or antijoins. - Regression tests for the change in `test_using_join_wildcard_schema_semi_anti`. ## Are these changes tested? - Added a regression test. ## Are there any user-facing changes? Yes, the change is user facing, but I doubt that this behavior is expected and is documented anywhere. If existing docs need to be updated, please point me to the concrete places and I can take a look. Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org>
## Rationale for this change - closes #21110 Expose the new Content-Defined Chunking feature from parquet-rs apache/arrow-rs#9450 ## What changes are included in this PR? New parquet writer options for enabling CDC. ## Are these changes tested? In-progress. ## Are there any user-facing changes? New config options. Depends on the 58.1 arrow-rs release.
## Which issue does this PR close? - Closes #21204. ## Rationale for this change In practice, `split_part(string, delimiter, position)` is often invoked with constant values for `delimiter` and `position`. We can take advantage of that to hoist some conditional branches out of the per-row hot loop; more importantly, we can switch from using `str::split` to building a `memchr::memmem::Finder` and using it for each row. Building a `Finder` is relatively expensive but it's a clear win when we can amortize that one-time cost over an entire input batch. Benchmarks (M4 Max): - `scalar_utf8_single_char/pos_first`: 105 µs → 41 µs, -61% - `scalar_utf8_single_char/pos_middle`: 358 µs → 97 µs, -73% - `scalar_utf8_single_char/pos_negative`: 110 µs → 46 µs, -58% - `scalar_utf8_multi_char/pos_middle`: 355 µs → 132 µs, -63% - `scalar_utf8_long_strings/pos_middle`: 1.97 ms → 1.11 ms, -43% - `scalar_utf8view_long_parts/pos_middle`: 467 µs → 169 µs, -63% - `array_utf8_single_char/pos_middle`: 351 µs → 357 µs, no change - `array_utf8_multi_char/pos_middle`: 366 µs → 357 µs, -2.6% ## What changes are included in this PR? * Add benchmarks for `split_part` with scalar delimiter and position * Add new fast-path for `split_part` with scalar delimiter and position * Add SLT tests for `split_part` with scalar delimiter and position ## Are these changes tested? Yes. ## Are there any user-facing changes? No.
…unts (#21369) ## Which issue does this PR close? N/A — standalone API improvement, prerequisite for #21157. ## Rationale for this change `PruningStatistics::row_counts(&self, column: &Column)` takes a column parameter, but row counts are container-level (same for all columns). 8 of 11 implementations ignore the parameter with `_column`. The Parquet impl (`RowGroupPruningStatistics`) unnecessarily constructs a `StatisticsConverter` from the column just to call `row_group_row_counts()`, which doesn't use the column at all. The existing code even has a comment acknowledging this: > "row counts are the same for all columns in a row group" And a test comment: > "This is debatable, personally I think `row_count` should not take a `Column` as an argument at all since all columns should have the same number of rows." ## What changes are included in this PR? **Breaking change**: `fn row_counts(&self, column: &Column) -> Option<ArrayRef>` becomes `fn row_counts(&self) -> Option<ArrayRef>`. - Remove `column` parameter from trait definition and all 11 implementations - `RowGroupPruningStatistics`: read `num_rows()` directly from row group metadata instead of routing through `StatisticsConverter` - `PrunableStatistics`: remove column-exists validation (row count is container-level) - Update all call sites and tests ## Are these changes tested? Yes — all existing tests updated and passing. The behavior change is: - `row_counts()` on `PrunableStatistics` now returns data even for non-existent columns (correct, since row count is container-level) - `RowGroupPruningStatistics::row_counts()` always returns row counts (previously could fail if column wasn't in Parquet schema) ## Are there any user-facing changes? Yes — breaking change to `PruningStatistics` trait. Downstream implementations need to remove the `column` parameter from their `row_counts` method. 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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