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Add experimental support for executing SQL with Polars and Pandas #190
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@jdye64 fyi |
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* changelog (#188) * Add Python wrapper for LogicalPlan::Sort (#196) * Add Python wrapper for LogicalPlan::Aggregate (#195) * Add Python wrapper for LogicalPlan::Limit (#193) * Add Python wrapper for LogicalPlan::Filter (#192) * Add Python wrapper for LogicalPlan::Filter * clippy * clippy * Update src/expr/filter.rs Co-authored-by: Liang-Chi Hsieh <viirya@gmail.com> --------- Co-authored-by: Liang-Chi Hsieh <viirya@gmail.com> * Add tests for recently added functionality (#199) * Add experimental support for executing SQL with Polars and Pandas (#190) * Run `maturin develop` instead of `cargo build` in verification script (#200) * Implement `to_pandas()` (#197) * Implement to_pandas() * Update documentation * Write unit test * Add support for cudf as a physical execution engine (#205) * Update README in preparation for 0.8 release (#206) * Analyze table bindings (#204) * method for getting the internal LogicalPlan instance * Add explain plan method * Add bindings for analyze table * Add to_variant * cargo fmt * blake and flake formatting * changelog (#209) --------- Co-authored-by: Liang-Chi Hsieh <viirya@gmail.com> Co-authored-by: Dejan Simic <10134699+simicd@users.noreply.github.com> Co-authored-by: Jeremy Dyer <jdye64@gmail.com>
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Which issue does this PR close?
Part of #191
Rationale for this change
Demonstrate how to use DataFusion as a SQL query planner and optimizer in Python and then translate the logical plan to another execution engine.
The examples added in this PR run trivial SQL queries against Polars and Pandas.
To support a wider range of queries we would need to expose all of the DataFusion operators and expressions (see #191).
Polars Example
Results:
Pandas Example
Results:
What changes are included in this PR?
Are there any user-facing changes?