[jira] [Created] (CALCITE-7254) Add a rule for sharing trivially equivelent RelNodes within Combine

["TJ Banghart (Jira)" <ji...@apache.org>]

TJ Banghart created CALCITE-7254:
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             Summary: Add a rule for sharing trivially equivelent RelNodes within Combine
                 Key: CALCITE-7254
                 URL: https://issues.apache.org/jira/browse/CALCITE-7254
             Project: Calcite
          Issue Type: New Feature
    Affects Versions: 1.40.0
            Reporter: TJ Banghart
            Assignee: TJ Banghart


Introduce an optimization rule to identify and consolidate trivially equivalent {{RelNodes}} that appear within a {{Combine}} operator. Trivial equivalence is defined as two {{RelNodes}} having identical digests. When such equivalence is detected, the common subexpression should be lifted into a shared {{Spool}} reference, and each original occurrence should be replaced with a dependent on that {{{}Spool{}}}.

An implementation may be able to build on the existing {{{}RelCommonExpressionSuggester{}}}, which currently identifies common expressions within individual queries. It may need to be extended to consider multiple queries or multiple branches within a single {{{}Combine{}}}.

An important consideration will be how {{Combine}} handles cost estimation in the absence of optimization and how shared expressions might influence that model. We will likely need to evaluate how these lifted expressions interact with the cost model to ensure we aren’t over-rewarding shared subtrees or unintentionally skewing plan selection.

We'd have to take care when managing interactions with other optimization rules. Filter pushdown, projection trimming, join reordering, etc... can alter digests and preclude trivial equivalence. The new rule will need safeguards to prevent conflicts or premature firing relative to these other optimizations.

Some of the implementation details are likely to evolve as this develops. Initial focus would be on correctness and identifying the right insertion points in the optimization pipeline.



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