Intermediate writes are an implementation detail. From Tantivy side we only decide when a file is finished. This change is done to remove flush overhead for VecWriter. On finalization we just move the Vec to the directory.
Rename TerminatingWrite to FinishableWrite to reflect these semantics.
BooleanWeight::new just default min_should_match to 1.
This is misleading because I think someone who passes a single must clause would expect the result
to match that clause.
Due to min_should_match, it actually returns nothing.
Co-authored-by: Paul Masurel <paul.masurel@datadoghq.com>
`Streamer::term_ord()` derived the ordinal by counting `delta_reader.advance()`
calls from a seed taken only when the stream had a key lower bound. An automaton
search has no key bounds, so the seed was 0 — but the reader it is handed *is*
block-pruned by that automaton (`get_block_iterator_for_range_and_automaton`).
Every block skipped ahead of the first match went uncounted, so `term_ord()`
returned the term's position among the blocks actually scanned rather than its
ordinal in the dictionary.
The error is silent and grows with how deep the first match sits: on a 262k-term
dictionary, a regex matching only the last key reported ordinal 999 instead of
262142. Callers that resolve those ordinals back to terms therefore act on a
different term entirely — `build_allowed_term_ids_for_str` builds the terms
aggregation's allowed-ordinal bitset this way, so an `include` regex could make
the aggregation count unrelated terms while returning the expected bucket count.
Broad patterns matching from the start of the dictionary hid it, since nothing is
pruned ahead of the first match.
Each slice handed to the reader now carries the ordinal of its first term, and
the streamer resets to it on entering a slice instead of incrementing across the
gap. Blocks merged into one slice stay contiguous, so counting within a slice is
still correct.
`Dictionary::sorted_ords_to_term_cb` already tracked `BlockAddr::first_ordinal`
explicitly, which is why ordinal->term resolution was unaffected.
When a string cardinality aggregation is nested it end up being applied to different buckets.
Dictionary encoding relies on a different dictionaries for each segment.
As a result, during segment collection, we only collect term ordinals in a HashSet, and decode them in the
term dictionary at the end of collection.
Before this PR, this decoding phase was done once for each bucket, causing the same work to be done over and over. This PR introduce a coupon cache. The HLL sketch relies on a hash of the string values.
We populate the cache before bucket collection, and get our values from it.
This PR also rename "caching" "buffering" in aggregation (it was never caching), and does several cleanups.
trinity-1686a
Pascal Seitz
dependabot[bot]
Paul MasurelandPaul Masurel
ildis
trinity-1686a
PSeitz
PSeitz-dd
Ang
Stu Hood
Eric Ridge
Parth
trinity-1686a
Remi Dettai
Bruce Mitchener