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Move Regr_* functions to use UDAF #10898
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Closes apache#10883 and is part of apache#8708
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Thank you @eejbyfeldt -- this looks awesome
I took the liberty of running cargo fmt and regenerated the vendored data |
The macos failure https://github.com/apache/datafusion/actions/runs/9502875641/job/26191967199?pr=10898 appears to be related to #10904 (a flaky fuzz test) |
Merged up to get the fix for #10904 |
🎉 |
Thanks @eejbyfeldt and @alamb |
* Move Regr_* functions to use UDAF Closes apache#10883 and is part of apache#8708 * Format and regen * tweak error check --------- Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org>
* chore: update datafusion deps * feat: impl ExecutionPlan::static_name() for DatasetExec This required trait method was added upstream [0] and recommends to simply forward to `static_name`. [0]: apache/datafusion#10266 * feat: update first_value and last_value wrappers. Upstream signatures were changed for the new new `AggregateBuilder` api [0]. This simply gets the code to work. We should better incorporate that API into `datafusion-python`. [0] apache/datafusion#10560 * migrate count to UDAF Builtin Count was removed upstream. TBD whether we want to re-implement `count_star` with new API. Ref: apache/datafusion#10893 * migrate approx_percentile_cont, approx_distinct, and approx_median to UDAF Ref: approx_distinct apache/datafusion#10851 Ref: approx_median apache/datafusion#10840 Ref: approx_percentile_cont and _with_weight apache/datafusion#10917 * migrate avg to UDAF Ref: apache/datafusion#10964 * migrage corr to UDAF Ref: apache/datafusion#10884 * migrate grouping to UDAF Ref: apache/datafusion#10906 * add alias `mean` for UDAF `avg` * migrate stddev to UDAF Ref: apache/datafusion#10827 * remove rust alias for stddev The python wrapper now provides stddev_samp alias. * migrage var_pop to UDAF Ref: apache/datafusion#10836 * migrate regr_* functions to UDAF Ref: apache/datafusion#10898 * migrate bitwise functions to UDAF The functions now take a single expression instead of a Vec<_>. Ref: apache/datafusion#10930 * add missing variants for ScalarValue with todo * fix typo in approx_percentile_cont * add distinct arg to count * comment out failing test `approx_percentile_cont` is now returning a DoubleArray instead of an IntArray. This may be a bug upstream; it requires further investigation. * update tests to expect lowercase `sum` in query plans This was changed upstream. Ref: apache/datafusion#10831 * update ScalarType data_type map * add docs dependency pickleshare * re-implement count_star * lint: ruff python lint * lint: rust cargo fmt * include name of window function in error for find_window_fn * refactor `find_window_fn` for debug clarity * search default aggregate functions by both name and aliases The alias list no longer includes the name of the function. Ref: apache/datafusion#10658 * fix markdown in find_window_fn docs * parameterize test_window_functions `first_value` and `last_value` are currently failing and marked as xfail. * add test ids to test_simple_select tests marked xfail * update find_window_fn to search built-ins first The behavior of `first_value` and `last_value` UDAFs currently does not match the built-in behavior. This allowed me to remove `marks=pytest.xfail` from the window tests. * improve first_call and last_call use of the builder API * remove trailing todos * fix examples/substrait.py * chore: remove explicit aliases from functions.rs Ref: #779 * remove `array_fn!` aliases * remove alias rules for `expr_fn_vec!` * remove alias rules from `expr_fn!` macro * remove unnecessary pyo3 var-arg signatures in functions.rs * remove pyo3 signatures that provided defaults for first_value and last_value * parametrize test_string_functions * test regr_ function wrappers Closes #778
Which issue does this PR close?
Closes #10883 and is part of #8708
Rationale for this change
The motivation is in #8708
What changes are included in this PR?
This moves Regr to be implemented using UDAF as decided in #8708. To avoid duplicating to much code I had to modify an existing macros and add new one to avoid creating a lot of boilerplate for each one. Let me know if there is some better way of doing it.
Are these changes tested?
Existing tests cases.
Are there any user-facing changes?
I think so since we moved the implementations to a different package.