feat: prune unused dimension joins from queries#228
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hussainsultan merged 4 commits intomainfrom Apr 14, 2026
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When a query only references a subset of the joined tables (via dimension keys or measure names), joins to unreferenced tables are now skipped. This avoids expensive joins to dimension tables that contribute nothing to the result — e.g. a pure SUM() on a fact table no longer joins 4 dimension tables. The implementation extracts table prefixes from the query's keys and aggs, passes them as parent_requirements to SemanticJoinOp.to_untagged(), which recursively prunes right-side leaf tables not in the needed set. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The pre-agg path needs all tables for dimension bridges — passing parent_requirements=None ensures no pruning happens there. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Guard pruning by cardinality and join type: only prune join_one with how="left". Inner joins act as row filters and must not be removed. join_many/join_cross are never pruned (join_many is intercepted by the pre-agg path; join_cross changes row counts). Adds edge case tests: - Inner join with orphan rows: pruning correctly preserves inner join - Filter on dimension table: pruning correctly disabled - SQL verification: pruned tables absent from compiled SQL Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
model.aggregate("facts.total_sales")no longer joins unused dimension tablesCloses #227
How it works
SemanticAggregateOp.to_untagged()extracts table prefixes from query keys/aggs (e.g.stores.store_name→stores)parent_requirementstoSemanticJoinOp.to_untagged()to_untagged()checks if the right-side leaf table is in the needed set — if not, skips the join entirelyTest plan
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