Add SelectivityTracker adaptive filter cost model#22236
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Introduce `OptionalFilterPhysicalExpr`, a transparent `PhysicalExpr` wrapper that marks a filter as *optional* — droppable without affecting query correctness. It delegates every `PhysicalExpr` method to the inner expression, so it is behavior-neutral until a consumer explicitly checks for the marker. This is the foundation for adaptive filter scheduling: a scan can detect the wrapper and drop a performance-hint filter (e.g. a hash-join dynamic filter) when it is not cost-effective, knowing correctness is enforced elsewhere. Also adds proto serialization (`PhysicalOptionalFilterNode`) so physical plans containing the wrapper round-trip faithfully. No caller wraps anything yet — that arrives with the adaptive parquet scan later in the stack. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Add an opt-in way to learn, per individual conjunct, how effective each predicate was during pruning — without running any extra pruning passes. - `PruningPredicate::try_new_tagged_conjuncts` builds a predicate from AND-conjuncts, each carrying a caller-supplied tag. - `PruningPredicate::prune_per_conjunct` returns the usual prune mask plus per-conjunct `PerConjunctPruneStats` (rows/containers seen vs. skipped) as a side effect of the pruning iteration that already runs. - `RowGroupAccessPlanFilter::prune_by_statistics_with_per_conjunct_stats` and `PagePruningAccessPlanFilter::prune_plan_with_per_conjunct_stats` surface those stats for row-group and page-index pruning respectively. The existing untagged `prune` / `prune_by_statistics` / `prune_plan_with_page_index` paths are preserved and unchanged; the new methods return empty stats on the untagged path. No in-tree caller uses the tagged path yet — the adaptive parquet scan consumes it later in the stack as a selectivity prior. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Introduce `SelectivityTracker`, the cross-file cost model behind adaptive filter pushdown. It accumulates per-filter selectivity and throughput statistics and, given a confidence interval, decides whether each filter conjunct should be evaluated at row level, deferred to post-scan, or dropped entirely (for optional filters). This commit adds the module, its `total_compressed_bytes` helper in `row_filter`, a criterion benchmark, and ~45 unit tests covering the partitioning / promote / demote / drop logic. Nothing wires it into the parquet scan yet — that integration is the final commit in this stack. A couple of `pub(crate)` items (`count_skippable_bytes`, `skip_flag`, `is_filter_skipped`) are only exercised by that integration and carry a temporary `#[expect(dead_code)]` until then. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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This was referenced May 15, 2026
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Thank you for opening this pull request! Reviewer note: cargo-semver-checks reported the current version number is not SemVer-compatible with the changes in this pull request (compared against the base branch). Details |
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Which issue does this PR close?
Rationale for this change
The cost model that decides where each filter conjunct runs (row-level, post-scan, or dropped) is large enough to review on its own, separate from the scan plumbing that consumes it.
What changes are included in this PR?
SelectivityTracker: a cross-file cost model that accumulates per-filter selectivity and throughput statistics and, using a confidence interval, partitions filter conjuncts into row-level / post-scan / dropped buckets.total_compressed_byteshelper inrow_filter(column-byte sizing used by the tracker).Nothing wires the tracker into the parquet scan yet — that is the final PR in the stack. A few
pub(crate)items only exercised by that integration carry a temporary#[expect(dead_code)], removed in PR 4.Are these changes tested?
Yes — ~45 unit tests cover the partition / promote / demote / drop logic.
Are there any user-facing changes?
New
pubmoduledatafusion-datasource-parquet::selectivity. No behavior change — no production code path uses it yet.Stacked PR — diff is cumulative against
main. Review the top commit "feat: add SelectivityTracker adaptive filter cost model"; the commits below it are PRs #22234 and #22235.Stack (review/merge in order):