Switch the default serialized output of `sum` on empty / all-missing
buckets back to `"value": 0` to match Elasticsearch, and gate the
SQL-style `"value": null` behavior behind a new
`none_if_no_match: Option<bool>` flag on `SumAggregation`.
`IntermediateSum::finalize` still returns `Option<f64>` internally so
the Rust API stays parallel to min/max/avg, but the ES-vs-SQL choice is
made at the boundary in `IntermediateMetricResult::into_final_metric_result`:
`None` is coerced to `Some(0.0)` unless `none_if_no_match` is set on the
aggregation request.
Adds `AggregationVariants::as_sum()` accessor for that boundary check
and two end-to-end tests covering both the default ES behavior and the
opt-in null behavior on an empty index.
Surface the trade-off in the doc comment so future reviewers see why
this differs from ES (which returns "value": 0 for sum over
empty/all-missing buckets) and what consumers (ParadeDB SQL NULL) the
None variant is meant to serve.
IntermediateSum::finalize() returned Some(0.0) even when count==0
(all documents had missing/NULL values). This differs from MIN, MAX,
and AVG which all return None for count==0.
The 0.0 came from IntermediateStats' default sum initialization.
Consumers (like ParadeDB) that map None to SQL NULL were incorrectly
getting 0 for SUM on all-NULL groups.
Fixesparadedb/paradedb#4621
Add a public rank(target) method on BlockSegmentPostings that returns the
number of docs with a doc id strictly smaller than target. It jumps to the
candidate block through the skip list and decodes a single block, so the cost
is O(skip-list entries) + one block decode rather than O(doc_freq).
This is a useful primitive for range counting over a posting list (e.g. number
of matches in a [lo, hi) doc-id window) without iterating every matched doc.
To support it, expose SkipReader::remaining_docs() (pub(crate)). Like seek(),
rank() advances the cursor forward only and must be called with non-decreasing,
valid (<= TERMINATED) targets. Adds a unit test covering multi-block lists and
the below-first / above-last / empty edge cases.
The metric/cardinality/histogram _mut getters had no callers needing
mutation; their two uses already pass the resulting reference as &T.
simplify req_data ownership: clone into collectors, Rc only for filter BitSet
Replace Vec<Option<Box<T>>> + take/put-back round-trip with Vec<T> +
direct clone into collector. Collectors now own their per-segment
request data outright, removing the borrow-checker dance that the
take/put-back pattern existed to satisfy.
The structural clones are cheap (Column<u64> is Arc-internal) except
for the filter aggregation, whose DocumentQueryEvaluator carries a
precomputed per-segment BitSet sized by max_doc. Wrap that in
Rc<DocumentQueryEvaluator> so FilterAggReqData::clone() bumps a
refcount instead of duplicating the BitSet. Move SegmentFilterCollector's
matching_docs_buffer out of FilterAggReqData so its pre-allocated
capacity is preserved per collector instead of being lost on every clone.
Closes#2285
The TermFrequencyRecorder was completely untested. Add five focused tests:
- term_frequency_recorder_has_term_freq: verifies the recorder
correctly advertises term-frequency support via has_term_freq()
- term_frequency_recorder_zero_docs: term_doc_freq() returns Some(0)
before any documents are recorded
- term_frequency_recorder_term_doc_freq_single_doc: one document with
two occurrences yields term_doc_freq() == Some(1)
- term_frequency_recorder_term_doc_freq_multiple_docs: three documents
with varying term frequencies yield term_doc_freq() == Some(3),
confirming the count tracks documents, not occurrences
- term_frequency_recorder_single_occurrence_per_doc: each of three
documents has exactly one occurrence
- term_frequency_recorder_high_frequency_doc: a single document with
1000 occurrences still yields term_doc_freq() == Some(1)
* Add filter_vec benchmarks (dense, sparse, full coverage)
Uses get_ids_for_value_range to exercise both the bitpacking decode and
the filter_vec SIMD path together under realistic cache conditions.
* Add NEON and SVE implementations for filter_vec
Adds aarch64-specific SIMD paths (NEON always available on aarch64;
SVE gated on nightly + non-Apple target) with routing logic in mod.rs
that selects the best available instruction set at runtime.
* Using asm! to workaround the lack of stabilized SVE intrinsics
* showing instruction set
* improved proptesting
* removing build.rs
---------
Co-authored-by: Paul Masurel <paul.masurel@datadoghq.com>
Applies @PSeitz's review suggestion to make the function name more
descriptive of what it checks. Also adds a doc note clarifying why
validation is opt-in rather than enforced by default.
The early return for `scorers.len() == 1` in `scorer_union` short-circuits a single TermScorer into `SpecializedScorer::Other`, bypassing the `TermUnion` path that enables block-max WAND (BMW) in `for_each_pruning`.
This was originally addressed in PR #2898 (backed out), which added a special case in `BooleanWeight::for_each_pruning`. PR #2912 (merged as d27ca164a) added a single-scorer fast path inside `block_wand` itself, but did not remove this early return — so a single SHOULD TermScorer still never reaches the BMW path.
Removing the early return lets a single TermScorer with freq reading flow through to `SpecializedScorer::TermUnion`, where `block_wand` → `block_wand_single_scorer` handles it efficiently.
* Optimizing top K using Adrien Grand's ideas
https://jpountz.github.io/2025/08/28/compiled-vs-vectorized-search-engine-edition.html
* Suffix-sum pruning for multi-term intersection candidates
After scoring each secondary in Phase 2, check whether remaining
secondaries' block_max scores can still beat the threshold. Skip
to the next candidate early if impossible, avoiding expensive seeks
into later secondaries.
Improves three-term intersection by ~8% on the balanced benchmark
while keeping two-term performance neutral.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* Claude CR comment
* Removed 16 term scorer limit.
---------
Co-authored-by: Paul Masurel <paul.masurel@datadoghq.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
When a document has the exact registered facet path (not a child),
compute_collapse_mapping_one maps it to a sentinel (u64::MAX, 0).
Without filtering, harvest() passes u64::MAX to ord_to_term which
resolves to the last dictionary entry, producing a spurious facet
from an unrelated branch.
Skip entries where facet_ord == u64::MAX in harvest().
Closes#2494
Signed-off-by: majiayu000 <1835304752@qq.com>
