fangchenli opened a new pull request, #23403:
URL: https://github.com/apache/datafusion/pull/23403
## Which issue does this PR close?
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- Closes #23401.
## Rationale for this change
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the issue then this section is not needed.
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The SingleDistinctToGroupBy optimizer rule fires for the SQL planner but not
for the logically-equivalent plan built by the DataFrame API, because the two
front-ends place the output alias differently:
- SQL (count(DISTINCT v) AS n) keeps Aggregate.aggr_expr bare and carries
the alias in an outer Projection.
- DataFrame API (count(col("v")).distinct().alias("n")) applies the alias
directly to the aggregate, so aggr_expr holds Expr::Alias(AggregateFunction).
is_single_distinct_agg only matched a bare Expr::AggregateFunction, so the
aliased shape fell through and the rule never fired. As a result the DataFrame
API path was materially slower than the identical SQL query.
## What changes are included in this PR?
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sometimes worth providing a summary of the individual changes in this PR.
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- is_single_distinct_agg: peel any top-level Expr::Alias wrapper(s) before
matching Expr::AggregateFunction, so aliased aggregates built by the DataFrame
API are recognized. Uses a small borrowed helper unalias_ref.
- Rewrite body: reuse the existing datafusion_expr::expr_rewriter::unalias
to strip the outer alias(es) before processing each aggregate. Output column
names are preserved automatically, since the rule already rebuilds the outer
Projection from the original aggregate's schema field names.
## Are these changes tested?
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Yes, unit tests added.
## Are there any user-facing changes?
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No behavior change, except performance improvement.
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