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base: rust:congxie/supportAgg
Branches Tags
rust:main rust:congxie/supportAgg rust:postings-writer-enum-codec5 rust:postings-writer-enum-codec4 rust:segmentreader_trait rust:stuhood.intersection-termination-upstream rust:postings-writer-enum-codec3 rust:postings-writer-enum-codec2 rust:paradedb/fix-agg-validation rust:postings-writer-enum rust:paul.masurel/skip-first-doc-on-intersection rust:stuhood.lazy-scorers-blocks-upstream rust:paul.masurel/seek_into_the_danger_zone_result rust:paul.masurel/search_into_danger_zone_fastfield rust:stuhood.lazy-scorers-blocks rust:flatheadmill-geo rust:paradedb-paradedb/fix-overflow-issue rust:low_card_optimization rust:paul.masurel/clippy rust:qw-airmail-20250916 rust:unit-test-aggregation-sum-other rust:clippy-and-cleanups rust:trinity.pointard/opti-sstable-sorted-ords-to-term rust:release_0.24 rust:dependabot/cargo/rand-0.9.1 rust:dependabot/cargo/lru-0.14.0 rust:dependabot/cargo/fs4-0.13.1 rust:tagged-user-input-ast rust:1686a/parse-agg-res rust:dependabot/cargo/rand_distr-0.5.1 rust:issue/2411-adding-panic-handler-to-rayon-merge-thread-pool rust:dependabot/cargo/nom-8 rust:upgrade_deps rust:test_parser rust:dependabot/github_actions/codecov/codecov-action-5 rust:binggan-0.12.0 rust:agg_format rust:path_collector rust:test_order_bug rust:test_columnar_multi rust:columnar_optionalmask_in_multivalues rust:prefix-phrase-query-optim rust:tantivy-with-oneshot rust:update_example rust:store-reader-enumerate rust:document-deserialize-seed rust:check_doc_mem rust:experimental-do-not-merge rust:expdonotmerge rust:cherry-pick-vec-instead-of-btreemap rust:validate_length rust:raphael_bench_avx_filter rust:raphael_optim_memset2 rust:query-field-name-avoid-alloc rust:check_bug rust:missing_test rust:list_fields rust:block-cache-control rust:trinity--multilayer-sstable rust:tracing-tantivy2 rust:tracing-tantivy rust:index_writer_err rust:default_fast_field_tokenizer rust:fmassot/add-preserve-original-ascii-folding rust:numeric_with_str_col rust:straightforward-simplify rust:fmassot/fake-test-branch rust:fmassot/dynamic-tokenizer-poc-follow-up rust:fmassot/add-box-token-filter-and-refactor rust:dynamic-tokenizer-proof-of-concept rust:fmassot/add-box-tokenizer-and-token-filter rust:tokenizer-api-0.1.1 rust:addconversion rust:removed-extra-enum-alternative-for-datetime-precision rust:issue/1981-reproduce-bm25-bug rust:tokenizer_docs rust:merge-proptests rust:columnar-todo rust:quickwit-0.5 rust:remove-byteorder rust:remove_dyn rust:pr/alexcole/1855-inject-bm25-statistics rust:evance-expose-build-query-from-user-input-ast rust:missing-specialized-method-arcdyncolumn rust:fast-u64-range-query rust:0.19.2 rust:columnar-cli2 rust:trinity--pub-term-as-slice rust:typed-column3 rust:columnar-merge3 rust:columnar-merge-exploring-fn rust:use_columnar rust:typed-column2 rust:term_agg_bucket_limit rust:range rust:typed-column rust:columnar-main rust:forced-types rust:u128-columnar rust:use_stats rust:truncation_comment rust:0.19.1 rust:trinity/yoke-documents rust:column-handle rust:columnar-cli rust:columnar rust:revert-1711-sparse_dense_index rust:commit-changes rust:sparse_dense_index_headroom rust:optional_column rust:no-column-for-multivalued rust:fmassot--bench-hdfs-with-array rust:bugfix-position-broken rust:float rust:simplify rust:debug_time rust:sparse_codecs rust:fix_estimate rust:column-reader rust:column-reader-b rust:columnreader-simple rust:col-trait-refact rust:ip_fastfield rust:column-trait-2 rust:refact-dyn-column rust:column-trait rust:refact-codec-trait rust:pr/PSeitz/1485-1 rust:fastfieldcodec rust:termmap_per_field rust:fastfield-codecs-tests rust:rayon-indexing-writers rust:issue/1251 rust:index-bench rust:fix_open_bytes_index rust:warming rust:revert-1222-issue/1195 rust:add-random-bench-for-fast-field rust:wasm-friendly-exploratory rust:revert-1159-patch-1 rust:debug-position-panic-0.15.3 rust:fix-issue-1111 rust:remove_rand rust:unused-deps rust:hfb/phrase_match_slop rust:0.15.3 rust:expose-min-max-on-multi-fast-field-reader rust:revert-1094-expose-min-max-on-multi-fast-field-reader rust:hotfix-1088 rust:owned-bytes-instead-of-rawdoc rust:rihardsk-date-ranges rust:issue/997 rust:0.13.3 rust:fail-fast-store-checkpoint rust:debugging-store rust:issue/reproduce-897 rust:issue/969-reproduce rust:troublescooter-static rust:intermediate-mergeable-troublescooter rust:barrotsteindev-filter-collector-tpredicatevalue rust:issue/938b rust:issue/938 rust:barrotsteindev-filter-collector rust:issue/922 rust:issue/896 rust:quickfix-explain rust:slog rust:limit-random-seeks rust:0.13.1 rust:issue/866b rust:bugfix-unittest-macos rust:githubactions rust:fieldnorm_readers rust:blockwand rust:nodeffeatfails rust:removedaliveiterator rust:robyoung-introduce-offset-to-top-docs rust:specialization-of-foreach-for-union-scorer rust:elshize-bmw rust:cutt rust:nrt rust:storewriter-out rust:segment_writer_in_ram2 rust:polling rust:audunhalland-query-boost rust:poll-meta rust:segment_writer_in_ram rust:bundle rust:petr-tik-n662_footer_is_incompatible_impl rust:race-condition-in-tests rust:hotfix-0.10.3-issue681 rust:remove-tru rust:kkoziara-pre-tokenized-text rust:issue/681 rust:issue/680 rust:refactoring/field rust:updating/uuid rust:fix-bench rust:hotfix-656 rust:readd-macos-ci rust:incremental-search rust:crate-division rust:streamer-with-state rust:criterion rust:python-binding-changes rust:bump-version rust:gh-pages rust:issue/554 rust:perf/experimental-union-for_each rust:issue/526b rust:softcommits rust:0.9.1-hotfix rust:revert-521-fix-non-english-stemmers rust:issue/500-hotfix rust:hotfix/0.8.2 rust:issue/483 rust:bug/merge-deted rust:issue/407 rust:issue/457 rust:segment_fruits rust:doc rust:dds/lenient rust:issue/webasm rust:issue/396 rust:broken_collector_with_result rust:dss/automaton-weight-suggestion rust:wasm rust:common-crawl rust:tantivy-imhotep
rust:0.25.0 rust:0.22.1 rust:0.24.2 rust:0.24.1 rust:tantivy-query-grammar-v0.24.0 rust:tantivy-columnar-v0.5.0 rust:tantivy-bitpacker-v0.8.0 rust:ownedbytes-v0.9.0 rust:tantivy-stacker-v0.5.0 rust:tantivy-sstable-v0.5.0 rust:tantivy-common-v0.9.0 rust:tantivy-tokenizer-api-v0.5.0 rust:0.24 rust:qw-airmail-20250224-hotfix-merge-panic rust:qw-airmail-20250219-hotfix-merge-panic rust:qw-airmail-202406 rust:qw-airmail-20240611 rust:qw-airmail-20240606 rust:quickwit-rev rust:0.22.0 rust:tantivy-stacker-v0.3.0 rust:ownedbytes-v0.7.0 rust:tantivy-tokenizer-api-v0.3.0 rust:tantivy-columnar-v0.3.0 rust:tantivy-common-v0.7.0 rust:tantivy-query-grammar-v0.22.0 rust:tantivy-sstable-v0.3.0 rust:tantivy-bitpacker-v0.6.0 rust:0.21.1 rust:0.21 rust:0.20.2 rust:0.20.1 rust:0.20 rust:quickwit-0.5-rev rust:0.19.2 rust:0.19.1 rust:0.19 rust:0.18.1 rust:0.18 rust:0.17 rust:0.16.1 rust:0.15.3 rust:0.15.2 rust:0.15.1 rust:0.15 rust:0.14 rust:0.13.3 rust:0.13.2 rust:0.13.1 rust:0.13 rust:0.12 rust:0.11.3 rust:0.11.1 rust:0.11 rust:0.10.3 rust:0.1 rust:0.10.2 rust:0.10.1 rust:0.10.0 rust:0.9.1 rust:0.9 rust:0.8.2 rust:0.8.2b rust:0.8.1 rust:0.8.0 rust:0.7.2 rust:0.7.1 rust:0.7.0 rust:0.6.1 rust:0.6.0 rust:0.5.2 rust:0.5.1 rust:0.5.0 rust:0.4.3 rust:0.4.2 rust:0.4.0 rust:0.3.1 rust:0.3.0 rust:0.2.0
..
compare: rust:flatheadmill-geo
Branches Tags
rust:congxie/supportAgg rust:postings-writer-enum-codec5 rust:main rust:postings-writer-enum-codec4 rust:segmentreader_trait rust:stuhood.intersection-termination-upstream rust:postings-writer-enum-codec3 rust:postings-writer-enum-codec2 rust:paradedb/fix-agg-validation rust:postings-writer-enum rust:paul.masurel/skip-first-doc-on-intersection rust:stuhood.lazy-scorers-blocks-upstream rust:paul.masurel/seek_into_the_danger_zone_result rust:paul.masurel/search_into_danger_zone_fastfield rust:stuhood.lazy-scorers-blocks rust:flatheadmill-geo rust:paradedb-paradedb/fix-overflow-issue rust:low_card_optimization rust:paul.masurel/clippy rust:qw-airmail-20250916 rust:unit-test-aggregation-sum-other rust:clippy-and-cleanups rust:trinity.pointard/opti-sstable-sorted-ords-to-term rust:release_0.24 rust:dependabot/cargo/rand-0.9.1 rust:dependabot/cargo/lru-0.14.0 rust:dependabot/cargo/fs4-0.13.1 rust:tagged-user-input-ast rust:1686a/parse-agg-res rust:dependabot/cargo/rand_distr-0.5.1 rust:issue/2411-adding-panic-handler-to-rayon-merge-thread-pool rust:dependabot/cargo/nom-8 rust:upgrade_deps rust:test_parser rust:dependabot/github_actions/codecov/codecov-action-5 rust:binggan-0.12.0 rust:agg_format rust:path_collector rust:test_order_bug rust:test_columnar_multi rust:columnar_optionalmask_in_multivalues rust:prefix-phrase-query-optim rust:tantivy-with-oneshot rust:update_example rust:store-reader-enumerate rust:document-deserialize-seed rust:check_doc_mem rust:experimental-do-not-merge rust:expdonotmerge rust:cherry-pick-vec-instead-of-btreemap rust:validate_length rust:raphael_bench_avx_filter rust:raphael_optim_memset2 rust:query-field-name-avoid-alloc rust:check_bug rust:missing_test rust:list_fields rust:block-cache-control rust:trinity--multilayer-sstable rust:tracing-tantivy2 rust:tracing-tantivy rust:index_writer_err rust:default_fast_field_tokenizer rust:fmassot/add-preserve-original-ascii-folding rust:numeric_with_str_col rust:straightforward-simplify rust:fmassot/fake-test-branch rust:fmassot/dynamic-tokenizer-poc-follow-up rust:fmassot/add-box-token-filter-and-refactor rust:dynamic-tokenizer-proof-of-concept rust:fmassot/add-box-tokenizer-and-token-filter rust:tokenizer-api-0.1.1 rust:addconversion rust:removed-extra-enum-alternative-for-datetime-precision rust:issue/1981-reproduce-bm25-bug rust:tokenizer_docs rust:merge-proptests rust:columnar-todo rust:quickwit-0.5 rust:remove-byteorder rust:remove_dyn rust:pr/alexcole/1855-inject-bm25-statistics rust:evance-expose-build-query-from-user-input-ast rust:missing-specialized-method-arcdyncolumn rust:fast-u64-range-query rust:0.19.2 rust:columnar-cli2 rust:trinity--pub-term-as-slice rust:typed-column3 rust:columnar-merge3 rust:columnar-merge-exploring-fn rust:use_columnar rust:typed-column2 rust:term_agg_bucket_limit rust:range rust:typed-column rust:columnar-main rust:forced-types rust:u128-columnar rust:use_stats rust:truncation_comment rust:0.19.1 rust:trinity/yoke-documents rust:column-handle rust:columnar-cli rust:columnar rust:revert-1711-sparse_dense_index rust:commit-changes rust:sparse_dense_index_headroom rust:optional_column rust:no-column-for-multivalued rust:fmassot--bench-hdfs-with-array rust:bugfix-position-broken rust:float rust:simplify rust:debug_time rust:sparse_codecs rust:fix_estimate rust:column-reader rust:column-reader-b rust:columnreader-simple rust:col-trait-refact rust:ip_fastfield rust:column-trait-2 rust:refact-dyn-column rust:column-trait rust:refact-codec-trait rust:pr/PSeitz/1485-1 rust:fastfieldcodec rust:termmap_per_field rust:fastfield-codecs-tests rust:rayon-indexing-writers rust:issue/1251 rust:index-bench rust:fix_open_bytes_index rust:warming rust:revert-1222-issue/1195 rust:add-random-bench-for-fast-field rust:wasm-friendly-exploratory rust:revert-1159-patch-1 rust:debug-position-panic-0.15.3 rust:fix-issue-1111 rust:remove_rand rust:unused-deps rust:hfb/phrase_match_slop rust:0.15.3 rust:expose-min-max-on-multi-fast-field-reader rust:revert-1094-expose-min-max-on-multi-fast-field-reader rust:hotfix-1088 rust:owned-bytes-instead-of-rawdoc rust:rihardsk-date-ranges rust:issue/997 rust:0.13.3 rust:fail-fast-store-checkpoint rust:debugging-store rust:issue/reproduce-897 rust:issue/969-reproduce rust:troublescooter-static rust:intermediate-mergeable-troublescooter rust:barrotsteindev-filter-collector-tpredicatevalue rust:issue/938b rust:issue/938 rust:barrotsteindev-filter-collector rust:issue/922 rust:issue/896 rust:quickfix-explain rust:slog rust:limit-random-seeks rust:0.13.1 rust:issue/866b rust:bugfix-unittest-macos rust:githubactions rust:fieldnorm_readers rust:blockwand rust:nodeffeatfails rust:removedaliveiterator rust:robyoung-introduce-offset-to-top-docs rust:specialization-of-foreach-for-union-scorer rust:elshize-bmw rust:cutt rust:nrt rust:storewriter-out rust:segment_writer_in_ram2 rust:polling rust:audunhalland-query-boost rust:poll-meta rust:segment_writer_in_ram rust:bundle rust:petr-tik-n662_footer_is_incompatible_impl rust:race-condition-in-tests rust:hotfix-0.10.3-issue681 rust:remove-tru rust:kkoziara-pre-tokenized-text rust:issue/681 rust:issue/680 rust:refactoring/field rust:updating/uuid rust:fix-bench rust:hotfix-656 rust:readd-macos-ci rust:incremental-search rust:crate-division rust:streamer-with-state rust:criterion rust:python-binding-changes rust:bump-version rust:gh-pages rust:issue/554 rust:perf/experimental-union-for_each rust:issue/526b rust:softcommits rust:0.9.1-hotfix rust:revert-521-fix-non-english-stemmers rust:issue/500-hotfix rust:hotfix/0.8.2 rust:issue/483 rust:bug/merge-deted rust:issue/407 rust:issue/457 rust:segment_fruits rust:doc rust:dds/lenient rust:issue/webasm rust:issue/396 rust:broken_collector_with_result rust:dss/automaton-weight-suggestion rust:wasm rust:common-crawl rust:tantivy-imhotep
rust:0.25.0 rust:0.22.1 rust:0.24.2 rust:0.24.1 rust:tantivy-query-grammar-v0.24.0 rust:tantivy-columnar-v0.5.0 rust:tantivy-bitpacker-v0.8.0 rust:ownedbytes-v0.9.0 rust:tantivy-stacker-v0.5.0 rust:tantivy-sstable-v0.5.0 rust:tantivy-common-v0.9.0 rust:tantivy-tokenizer-api-v0.5.0 rust:0.24 rust:qw-airmail-20250224-hotfix-merge-panic rust:qw-airmail-20250219-hotfix-merge-panic rust:qw-airmail-202406 rust:qw-airmail-20240611 rust:qw-airmail-20240606 rust:quickwit-rev rust:0.22.0 rust:tantivy-stacker-v0.3.0 rust:ownedbytes-v0.7.0 rust:tantivy-tokenizer-api-v0.3.0 rust:tantivy-columnar-v0.3.0 rust:tantivy-common-v0.7.0 rust:tantivy-query-grammar-v0.22.0 rust:tantivy-sstable-v0.3.0 rust:tantivy-bitpacker-v0.6.0 rust:0.21.1 rust:0.21 rust:0.20.2 rust:0.20.1 rust:0.20 rust:quickwit-0.5-rev rust:0.19.2 rust:0.19.1 rust:0.19 rust:0.18.1 rust:0.18 rust:0.17 rust:0.16.1 rust:0.15.3 rust:0.15.2 rust:0.15.1 rust:0.15 rust:0.14 rust:0.13.3 rust:0.13.2 rust:0.13.1 rust:0.13 rust:0.12 rust:0.11.3 rust:0.11.1 rust:0.11 rust:0.10.3 rust:0.1 rust:0.10.2 rust:0.10.1 rust:0.10.0 rust:0.9.1 rust:0.9 rust:0.8.2 rust:0.8.2b rust:0.8.1 rust:0.8.0 rust:0.7.2 rust:0.7.1 rust:0.7.0 rust:0.6.1 rust:0.6.0 rust:0.5.2 rust:0.5.1 rust:0.5.0 rust:0.4.3 rust:0.4.2 rust:0.4.0 rust:0.3.1 rust:0.3.0 rust:0.2.0

22 Commits
congxie/su ... flatheadmi

Author SHA1 Message Date
Paul Masurel
643639f14b Introduced geopoint. 2025-12-03 17:05:27 +01:00
Paul Masurel
f85a27068d Introduced geopoint. 2025-12-03 17:05:16 +01:00
Paul Masurel
1619e05bc5 plastic surgery 2025-12-03 16:20:18 +01:00
Paul Masurel
5d03c600ba Added bugfix and unit tests 
Removed use of robust.
 2025-12-03 15:21:37 +01:00
Paul Masurel
32beb06382 plastic surgery 2025-12-03 13:02:10 +01:00
Paul Masurel
d8bc0e7c99 added doc 2025-12-03 12:41:17 +01:00
Paul Masurel
79622f1f0b bugfix 2025-12-01 17:13:57 +01:00
Alan Gutierrez
d26d6c34fc Fix select_nth_unstable_by_key midpoint duplicates. 
Existing code behaved as if the result of `select_nth_unstable_by_key`
was either a sorted array or the product of an algorithm that gathered
partition values as in the Dutch national flag problem. The existing
code was written knowing that the former isn't true and the latter isn't
advertised. Knowing, but not remembering. Quite the oversight.
 2025-12-01 16:49:22 +01:00
Alan Gutierrez
6da54fa5da Revert "Remove radix_select.rs." 
This reverts commit 19eab167b6.

Restore radix select in order to implement a merge solution that will
not require a temporary file.
 2025-12-01 16:49:21 +01:00
Alan Gutierrez
9f10279681 Complete Spatial/Geometry type integration. 
Addressed all `todo!()` markers created when adding `Spatial` field type
and `Geometry` value type to existing code paths:

- Dynamic field handling: `Geometry` not supported in dynamic JSON
  fields, return `unimplemented!()` consistently with other complex
  types.
- Fast field writer: Panic if geometry routed incorrectly (internal
  error.)
- `OwnedValue` serialization: Implement `Geometry` to GeoJSON
  serialization and reference-to-owned conversion.
- Field type: Return `None` for `get_index_record_option()` since
  spatial fields use BKD trees, not inverted index.
- Space usage tracking: Add spatial field to `SegmentSpaceUsage` with
  proper integration through `SegmentReader`.
- Spatial query explain: Implement `explain()` method following pattern of
  other binary/constant-score queries.

Fixed `MultiPolygon` deserialization bug: count total points across all
rings, not number of rings.

Added clippy expects for legitimate too_many_arguments cases in geometric
predicates.
 2025-12-01 16:49:21 +01:00
Alan Gutierrez
68009bb25b Read block kd-tree nodes using from_le_bytes. 
Read node structures using `from_le_bytes` instead of casting memory.
After an inspection of columnar storage, it appears that this is the
standard practice in Rust and in the Tantivy code base. Left the
structure alignment for now in case it tends to align with cache
boundaries.
 2025-12-01 16:49:20 +01:00
Alan Gutierrez
459456ca28 Remove radix_select.rs. 
Ended up using `select_nth_unstable_by_key` from the Rust standard
library instead.
 2025-12-01 16:49:20 +01:00
Alan Gutierrez
dbbc8c3f65 Slot block kd-tree into Tantivy. 
Implemented a geometry document field with a minimal `Geometry` enum.
Now able to add that Geometry from GeoJSON parsed from a JSON document.
Geometry is triangulated if it is a polygon, otherwise it is correctly
encoded as a degenerate triangle if it is a point or a line string.
Write accumulated triangles to a block kd-tree on commit.

Serialize the original `f64` polygon for retrieval from search.

Created a query method for intersection. Query against the memory mapped
block kd-tree. Return hits and original `f64` polygon.

Implemented a merge of one or more block kd-trees from one or more
segments during merge.

Updated the block kd-tree to write to a Tantivy `WritePtr` instead of
more generic Rust I/O.
 2025-12-01 16:49:16 +01:00
Alan Gutierrez
d3049cb323 Triangulation is not just a conversion. 
The triangulation function in `triangle.rs` is now called
`delaunay_to_triangles` and it accepts the output of a Delaunay
triangulation from `i_triangle` and not a GeoRust multi-polygon. The
translation of user polygons to `i_triangle` polygons and subsequent
triangulation will take place outside of `triangle.rs`.
 2025-12-01 16:48:34 +01:00
Alan Gutierrez
ccdf399cd7 XOR delta compression for f64 polygon coordinates. 
Lossless compression for floating-point lat/lon coordinates using XOR
delta encoding on IEEE 754 bit patterns with variable-length integer
encoding. Designed for per-polygon random access in the document store,
where each polygon compresses independently without requiring sequential
decompression.
 2025-12-01 16:48:33 +01:00
Alan Gutierrez
2dc46b235e Implement block kd-tree. 
Implement an immutable bulk-loaded spatial index using recursive median
partitioning on bounding box dimensions. Each leaf stores up to 512
triangles with delta-compressed coordinates and doc IDs. The tree
provides three query types (intersects, within, contains) that use exact
integer arithmetic for geometric predicates and accumulate results in
bit sets for efficient deduplication across leaves.

The serialized format stores compressed leaf pages followed by the tree
structure (leaf and branch nodes), enabling zero-copy access through
memory-mapped segments without upfront decompression.
 2025-12-01 16:48:32 +01:00
Alan Gutierrez
f38140f72f Add delta compression for block kd-tree leaf nodes. 
Implements dimension-major bit-packing with zigzag encoding for signed i32
deltas, enabling compression of spatially-clustered triangles from 32-bit
coordinates down to 4-19 bits per delta depending on spatial extent.
 2025-12-01 16:48:32 +01:00
Alan Gutierrez
0996bea7ac Add a surveyor to determine spread and prefix. 
Implemented a `Surveyor` that will evaluate the bounding boxes of a set
of triangles and determine the dimension with the maximum spread and the
shared prefix for the values of dimension with the maximum spread.
 2025-12-01 16:48:31 +01:00
Alan Gutierrez
1c66567efc Radix selection for block kd-tree partitioning. 
Implemented byte-wise histogram selection to find median values without
comparisons, enabling efficient partitioning of spatial data during
block kd-tree construction. Processes values through multiple passes,
building histograms for each byte position after a common prefix,
avoiding the need to sort or compare elements directly.
 2025-12-01 16:48:31 +01:00
Alan Gutierrez
b2a9bb279d Implement polygon tessellation. 
The `triangulate` function takes a polygon with floating-point lat/lon
coordinates, converts to integer coordinates with millimeter precision
(using 2^32 scaling), performs constrained Delaunay triangulation, and
encodes the resulting triangles with boundary edge information for block
kd-tree spatial indexing.

It handles polygons with holes correctly, preserving which triangle
edges lie on the original polygon boundaries versus internal
tessellation edges.
 2025-12-01 16:48:26 +01:00
Alan Gutierrez
558c99fa2d Triangle encoding for spatial indexing. 
Encodes triangles with the bounding box in the first four words,
enabling efficient spatial pruning during tree traversal without
reconstructing the full triangle. The remaining words contain an
additional vertex and packed reconstruction metadata, allowing exact
triangle recovery when needed.
 2025-12-01 16:47:56 +01:00
Alan Gutierrez
43b5f34721 Implement SPATIAL flag. 
Implement a SPATIAL flag for use in creating a spatial field.
 2025-12-01 16:47:55 +01:00
177 changed files with 5906 additions and 7441 deletions
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---
name: rationalize-deps
description: Analyze Cargo.toml dependencies and attempt to remove unused features to reduce compile times and binary size
---
# Rationalize Dependencies
This skill analyzes Cargo.toml dependencies to identify and remove unused features.
## Overview
Many crates enable features by default that may not be needed. This skill:
1. Identifies dependencies with default features enabled
2. Tests if `default-features = false` works
3. Identifies which specific features are actually needed
4. Verifies compilation after changes
## Step 1: Identify the target
Ask the user which crate(s) to analyze:
- A specific crate name (e.g., "tokio", "serde")
- A specific workspace member (e.g., "quickwit-search")
- "all" to scan the entire workspace
## Step 2: Analyze current dependencies
For the workspace Cargo.toml (`quickwit/Cargo.toml`), list dependencies that:
- Do NOT have `default-features = false`
- Have default features that might be unnecessary
Run: `cargo tree -p <crate> -f "{p} {f}" --edges features` to see what features are actually used.
## Step 3: For each candidate dependency
### 3a: Check the crate's default features
Look up the crate on crates.io or check its Cargo.toml to understand:
- What features are enabled by default
- What each feature provides
Use: `cargo metadata --format-version=1 | jq '.packages[] | select(.name == "<crate>") | .features'`
### 3b: Try disabling default features
Modify the dependency in `quickwit/Cargo.toml`:
From:
```toml
some-crate = { version = "1.0" }
```
To:
```toml
some-crate = { version = "1.0", default-features = false }
```
### 3c: Run cargo check
Run: `cargo check --workspace` (or target specific packages for faster feedback)
If compilation fails:
1. Read the error messages to identify which features are needed
2. Add only the required features explicitly:
```toml
some-crate = { version = "1.0", default-features = false, features = ["needed-feature"] }
```
3. Re-run cargo check
### 3d: Binary search for minimal features
If there are many default features, use binary search:
1. Start with no features
2. If it fails, add half the default features
3. Continue until you find the minimal set
## Step 4: Document findings
For each dependency analyzed, report:
- Original configuration
- New configuration (if changed)
- Features that were removed
- Any features that are required
## Step 5: Verify full build
After all changes, run:
```bash
cargo check --workspace --all-targets
cargo test --workspace --no-run
```
## Common Patterns
### Serde
Often only needs `derive`:
```toml
serde = { version = "1.0", default-features = false, features = ["derive", "std"] }
```
### Tokio
Identify which runtime features are actually used:
```toml
tokio = { version = "1.0", default-features = false, features = ["rt-multi-thread", "macros", "sync"] }
```
### Reqwest
Often doesn't need all TLS backends:
```toml
reqwest = { version = "0.11", default-features = false, features = ["rustls-tls", "json"] }
```
## Rollback
If changes cause issues:
```bash
git checkout quickwit/Cargo.toml
cargo check --workspace
```
## Tips
- Start with large crates that have many default features (tokio, reqwest, hyper)
- Use `cargo bloat --crates` to identify large dependencies
- Check `cargo tree -d` for duplicate dependencies that might indicate feature conflicts
- Some features are needed only for tests - consider using `[dev-dependencies]` features

60
.claude/skills/simple-pr/SKILL.md
View File

@@ -1,60 +0,0 @@
---
name: simple-pr
description: Create a simple PR from staged changes with an auto-generated commit message
disable-model-invocation: true
---
# Simple PR
Follow these steps to create a simple PR from staged changes:
## Step 1: Check workspace state
Run: `git status`
Verify that all changes have been staged (no unstaged changes). If there are unstaged changes, abort and ask the user to stage their changes first with `git add`.
Also verify that we are on the `main` branch. If not, abort and ask the user to switch to main first.
## Step 2: Ensure main is up to date
Run: `git pull origin main`
This ensures we're working from the latest code.
## Step 3: Review staged changes
Run: `git diff --cached`
Review the staged changes to understand what the PR will contain.
## Step 4: Generate commit message
Based on the staged changes, generate a concise commit message (1-2 sentences) that describes the "why" rather than the "what".
Display the proposed commit message to the user and ask for confirmation before proceeding.
## Step 5: Create a new branch
Get the git username: `git config user.name | tr ' ' '-' | tr '[:upper:]' '[:lower:]'`
Create a short, descriptive branch name based on the changes (e.g., `fix-typo-in-readme`, `add-retry-logic`, `update-deps`).
Create and checkout the branch: `git checkout -b {username}/{short-descriptive-name}`
## Step 6: Commit changes
Commit with the message from step 3:
```
git commit -m "{commit-message}"
```
## Step 7: Push and open a PR
Push the branch and open a PR:
```
git push -u origin {branch-name}
gh pr create --title "{commit-message-title}" --body "{longer-description-if-needed}"
```
Report the PR URL to the user when complete.

4
.github/workflows/coverage.yml vendored
View File

@@ -15,11 +15,11 @@ jobs:
steps:
- uses: actions/checkout@v4
- name: Install Rust
run: rustup toolchain install nightly-2025-12-01 --profile minimal --component llvm-tools-preview
run: rustup toolchain install nightly-2024-07-01 --profile minimal --component llvm-tools-preview
- uses: Swatinem/rust-cache@v2
- uses: taiki-e/install-action@cargo-llvm-cov
- name: Generate code coverage
run: cargo +nightly-2025-12-01 llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
run: cargo +nightly-2024-07-01 llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v3
continue-on-error: true

30
.github/workflows/test.yml vendored
View File

@@ -39,11 +39,11 @@ jobs:
- name: Check Formatting
run: cargo +nightly fmt --all -- --check
- name: Check Stable Compilation
run: cargo build --all-features
- name: Check Bench Compilation
run: cargo +nightly bench --no-run --profile=dev --all-features
@@ -59,10 +59,10 @@ jobs:
strategy:
matrix:
features:
- { label: "all", flags: "mmap,stopwords,lz4-compression,zstd-compression,failpoints,stemmer" }
- { label: "quickwit", flags: "mmap,quickwit,failpoints" }
- { label: "none", flags: "" }
features: [
{ label: "all", flags: "mmap,stopwords,lz4-compression,zstd-compression,failpoints" },
{ label: "quickwit", flags: "mmap,quickwit,failpoints" }
]
name: test-${{ matrix.features.label}}
@@ -80,21 +80,7 @@ jobs:
- uses: Swatinem/rust-cache@v2
- name: Run tests
run: |
# if matrix.feature.flags is empty then run on --lib to avoid compiling examples
# (as most of them rely on mmap) otherwise run all
if [ -z "${{ matrix.features.flags }}" ]; then
cargo +stable nextest run --lib --no-default-features --verbose --workspace
else
cargo +stable nextest run --features ${{ matrix.features.flags }} --no-default-features --verbose --workspace
fi
run: cargo +stable nextest run --features ${{ matrix.features.flags }} --verbose --workspace
- name: Run doctests
run: |
# if matrix.feature.flags is empty then run on --lib to avoid compiling examples
# (as most of them rely on mmap) otherwise run all
if [ -z "${{ matrix.features.flags }}" ]; then
echo "no doctest for no feature flag"
else
cargo +stable test --doc --features ${{ matrix.features.flags }} --verbose --workspace
fi
run: cargo +stable test --doc --features ${{ matrix.features.flags }} --verbose --workspace

48
Cargo.toml
View File

@@ -15,7 +15,7 @@ rust-version = "1.85"
exclude = ["benches/*.json", "benches/*.txt"]
[dependencies]
oneshot = "0.1.13"
oneshot = "0.1.7"
base64 = "0.22.0"
byteorder = "1.4.3"
crc32fast = "1.3.2"
@@ -27,7 +27,7 @@ regex = { version = "1.5.5", default-features = false, features = [
aho-corasick = "1.0"
tantivy-fst = "0.5"
memmap2 = { version = "0.9.0", optional = true }
lz4_flex = { version = "0.12", default-features = false, optional = true }
lz4_flex = { version = "0.11", default-features = false, optional = true }
zstd = { version = "0.13", optional = true, default-features = false }
tempfile = { version = "3.12.0", optional = true }
log = "0.4.16"
@@ -37,9 +37,9 @@ fs4 = { version = "0.13.1", optional = true }
levenshtein_automata = "0.2.1"
uuid = { version = "1.0.0", features = ["v4", "serde"] }
crossbeam-channel = "0.5.4"
rust-stemmers = { version = "1.2.0", optional = true }
rust-stemmers = "1.2.0"
downcast-rs = "2.0.1"
bitpacking = { version = "0.9.3", default-features = false, features = [
bitpacking = { version = "0.9.2", default-features = false, features = [
"bitpacker4x",
] }
census = "0.4.2"
@@ -50,12 +50,13 @@ fail = { version = "0.5.0", optional = true }
time = { version = "0.3.35", features = ["serde-well-known"] }
smallvec = "1.8.0"
rayon = "1.5.2"
lru = "0.16.3"
lru = "0.12.0"
fastdivide = "0.4.0"
itertools = "0.14.0"
measure_time = "0.9.0"
arc-swap = "1.5.0"
bon = "3.3.1"
i_triangle = "0.38.0"
columnar = { version = "0.6", path = "./columnar", package = "tantivy-columnar" }
sstable = { version = "0.6", path = "./sstable", package = "tantivy-sstable", optional = true }
@@ -70,22 +71,23 @@ futures-util = { version = "0.3.28", optional = true }
futures-channel = { version = "0.3.28", optional = true }
fnv = "1.0.7"
typetag = "0.2.21"
geo-types = "0.7.17"
[target.'cfg(windows)'.dependencies]
winapi = "0.3.9"
[dev-dependencies]
binggan = "0.14.2"
rand = "0.9"
binggan = "0.14.0"
rand = "0.8.5"
maplit = "1.0.2"
matches = "0.1.9"
pretty_assertions = "1.2.1"
proptest = "1.7.0"
proptest = "1.0.0"
test-log = "0.2.10"
futures = "0.3.21"
paste = "1.0.11"
more-asserts = "0.3.1"
rand_distr = "0.5"
rand_distr = "0.4.3"
time = { version = "0.3.10", features = ["serde-well-known", "macros"] }
postcard = { version = "1.0.4", features = [
"use-std",
@@ -113,8 +115,7 @@ debug-assertions = true
overflow-checks = true
[features]
default = ["mmap", "stopwords", "lz4-compression", "columnar-zstd-compression", "stemmer"]
stemmer = ["rust-stemmers"]
default = ["mmap", "stopwords", "lz4-compression", "columnar-zstd-compression"]
mmap = ["fs4", "tempfile", "memmap2"]
stopwords = []
@@ -174,31 +175,6 @@ harness = false
name = "exists_json"
harness = false
[[bench]]
name = "range_query"
harness = false
[[bench]]
name = "and_or_queries"
harness = false
[[bench]]
name = "range_queries"
harness = false
[[bench]]
name = "bool_queries_with_range"
harness = false
[[bench]]
name = "str_search_and_get"
harness = false
[[bench]]
name = "merge_segments"
harness = false
[[bench]]
name = "regex_all_terms"
harness = false

1
README.md
View File

@@ -123,7 +123,6 @@ You can also find other bindings on [GitHub](https://github.com/search?q=tantivy
- [seshat](https://github.com/matrix-org/seshat/): A matrix message database/indexer
- [tantiny](https://github.com/baygeldin/tantiny): Tiny full-text search for Ruby
- [lnx](https://github.com/lnx-search/lnx): adaptable, typo tolerant search engine with a REST API
- [Bichon](https://github.com/rustmailer/bichon): A lightweight, high-performance Rust email archiver with WebUI
- and [more](https://github.com/search?q=tantivy)!
### On average, how much faster is Tantivy compared to Lucene?

181
benches/agg_bench.rs
View File

@@ -1,8 +1,7 @@
use binggan::plugins::PeakMemAllocPlugin;
use binggan::{black_box, InputGroup, PeakMemAlloc, INSTRUMENTED_SYSTEM};
use rand::distr::weighted::WeightedIndex;
use rand::prelude::SliceRandom;
use rand::rngs::StdRng;
use rand::seq::IndexedRandom;
use rand::{Rng, SeedableRng};
use rand_distr::Distribution;
use serde_json::json;
@@ -54,33 +53,27 @@ fn bench_agg(mut group: InputGroup<Index>) {
register!(group, stats_f64);
register!(group, extendedstats_f64);
register!(group, percentiles_f64);
register!(group, terms_7);
register!(group, terms_all_unique);
register!(group, terms_150_000);
register!(group, terms_few);
register!(group, terms_many);
register!(group, terms_many_top_1000);
register!(group, terms_many_order_by_term);
register!(group, terms_many_with_top_hits);
register!(group, terms_all_unique_with_avg_sub_agg);
register!(group, terms_many_with_avg_sub_agg);
register!(group, terms_status_with_avg_sub_agg);
register!(group, terms_status_with_histogram);
register!(group, terms_zipf_1000);
register!(group, terms_zipf_1000_with_histogram);
register!(group, terms_zipf_1000_with_avg_sub_agg);
register!(group, terms_few_with_avg_sub_agg);
register!(group, terms_many_json_mixed_type_with_avg_sub_agg);
register!(group, cardinality_agg);
register!(group, terms_status_with_cardinality_agg);
register!(group, terms_few_with_cardinality_agg);
register!(group, range_agg);
register!(group, range_agg_with_avg_sub_agg);
register!(group, range_agg_with_term_agg_status);
register!(group, range_agg_with_term_agg_few);
register!(group, range_agg_with_term_agg_many);
register!(group, histogram);
register!(group, histogram_hard_bounds);
register!(group, histogram_with_avg_sub_agg);
register!(group, histogram_with_term_agg_status);
register!(group, histogram_with_term_agg_few);
register!(group, avg_and_range_with_avg_sub_agg);
// Filter aggregation benchmarks
@@ -139,12 +132,12 @@ fn extendedstats_f64(index: &Index) {
}
fn percentiles_f64(index: &Index) {
let agg_req = json!({
"mypercentiles": {
"percentiles": {
"field": "score_f64",
"percents": [ 95, 99, 99.9 ]
}
"mypercentiles": {
"percentiles": {
"field": "score_f64",
"percents": [ 95, 99, 99.9 ]
}
}
});
execute_agg(index, agg_req);
}
@@ -159,10 +152,10 @@ fn cardinality_agg(index: &Index) {
});
execute_agg(index, agg_req);
}
fn terms_status_with_cardinality_agg(index: &Index) {
fn terms_few_with_cardinality_agg(index: &Index) {
let agg_req = json!({
"my_texts": {
"terms": { "field": "text_few_terms_status" },
"terms": { "field": "text_few_terms" },
"aggs": {
"cardinality": {
"cardinality": {
@@ -175,20 +168,13 @@ fn terms_status_with_cardinality_agg(index: &Index) {
execute_agg(index, agg_req);
}
fn terms_7(index: &Index) {
fn terms_few(index: &Index) {
let agg_req = json!({
"my_texts": { "terms": { "field": "text_few_terms_status" } },
"my_texts": { "terms": { "field": "text_few_terms" } },
});
execute_agg(index, agg_req);
}
fn terms_all_unique(index: &Index) {
let agg_req = json!({
"my_texts": { "terms": { "field": "text_all_unique_terms" } },
});
execute_agg(index, agg_req);
}
fn terms_150_000(index: &Index) {
fn terms_many(index: &Index) {
let agg_req = json!({
"my_texts": { "terms": { "field": "text_many_terms" } },
});
@@ -236,10 +222,11 @@ fn terms_many_with_avg_sub_agg(index: &Index) {
});
execute_agg(index, agg_req);
}
fn terms_all_unique_with_avg_sub_agg(index: &Index) {
fn terms_few_with_avg_sub_agg(index: &Index) {
let agg_req = json!({
"my_texts": {
"terms": { "field": "text_all_unique_terms" },
"terms": { "field": "text_few_terms" },
"aggs": {
"average_f64": { "avg": { "field": "score_f64" } }
}
@@ -247,60 +234,6 @@ fn terms_all_unique_with_avg_sub_agg(index: &Index) {
});
execute_agg(index, agg_req);
}
fn terms_status_with_histogram(index: &Index) {
let agg_req = json!({
"my_texts": {
"terms": { "field": "text_few_terms_status" },
"aggs": {
"histo": {"histogram": { "field": "score_f64", "interval": 10 }}
}
}
});
execute_agg(index, agg_req);
}
fn terms_zipf_1000_with_histogram(index: &Index) {
let agg_req = json!({
"my_texts": {
"terms": { "field": "text_1000_terms_zipf" },
"aggs": {
"histo": {"histogram": { "field": "score_f64", "interval": 10 }}
}
}
});
execute_agg(index, agg_req);
}
fn terms_status_with_avg_sub_agg(index: &Index) {
let agg_req = json!({
"my_texts": {
"terms": { "field": "text_few_terms_status" },
"aggs": {
"average_f64": { "avg": { "field": "score_f64" } }
}
},
});
execute_agg(index, agg_req);
}
fn terms_zipf_1000_with_avg_sub_agg(index: &Index) {
let agg_req = json!({
"my_texts": {
"terms": { "field": "text_1000_terms_zipf" },
"aggs": {
"average_f64": { "avg": { "field": "score_f64" } }
}
},
});
execute_agg(index, agg_req);
}
fn terms_zipf_1000(index: &Index) {
let agg_req = json!({
"my_texts": { "terms": { "field": "text_1000_terms_zipf" } },
});
execute_agg(index, agg_req);
}
fn terms_many_json_mixed_type_with_avg_sub_agg(index: &Index) {
let agg_req = json!({
@@ -357,7 +290,7 @@ fn range_agg_with_avg_sub_agg(index: &Index) {
execute_agg(index, agg_req);
}
fn range_agg_with_term_agg_status(index: &Index) {
fn range_agg_with_term_agg_few(index: &Index) {
let agg_req = json!({
"rangef64": {
"range": {
@@ -372,7 +305,7 @@ fn range_agg_with_term_agg_status(index: &Index) {
]
},
"aggs": {
"my_texts": { "terms": { "field": "text_few_terms_status" } },
"my_texts": { "terms": { "field": "text_few_terms" } },
}
},
});
@@ -428,12 +361,12 @@ fn histogram_with_avg_sub_agg(index: &Index) {
});
execute_agg(index, agg_req);
}
fn histogram_with_term_agg_status(index: &Index) {
fn histogram_with_term_agg_few(index: &Index) {
let agg_req = json!({
"rangef64": {
"histogram": { "field": "score_f64", "interval": 10 },
"aggs": {
"my_texts": { "terms": { "field": "text_few_terms_status" } }
"my_texts": { "terms": { "field": "text_few_terms" } }
}
}
});
@@ -478,13 +411,6 @@ fn get_collector(agg_req: Aggregations) -> AggregationCollector {
}
fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
// Flag to use existing index
let reuse_index = std::env::var("REUSE_AGG_BENCH_INDEX").is_ok();
if reuse_index && std::path::Path::new("agg_bench").exists() {
return Index::open_in_dir("agg_bench");
}
// crreate dir
std::fs::create_dir_all("agg_bench")?;
let mut schema_builder = Schema::builder();
let text_fieldtype = tantivy::schema::TextOptions::default()
.set_indexing_options(
@@ -493,47 +419,20 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
.set_stored();
let text_field = schema_builder.add_text_field("text", text_fieldtype);
let json_field = schema_builder.add_json_field("json", FAST);
let text_field_all_unique_terms =
schema_builder.add_text_field("text_all_unique_terms", STRING | FAST);
let text_field_many_terms = schema_builder.add_text_field("text_many_terms", STRING | FAST);
let text_field_few_terms_status =
schema_builder.add_text_field("text_few_terms_status", STRING | FAST);
let text_field_1000_terms_zipf =
schema_builder.add_text_field("text_1000_terms_zipf", STRING | FAST);
let text_field_few_terms = schema_builder.add_text_field("text_few_terms", STRING | FAST);
let score_fieldtype = tantivy::schema::NumericOptions::default().set_fast();
let score_field = schema_builder.add_u64_field("score", score_fieldtype.clone());
let score_field_f64 = schema_builder.add_f64_field("score_f64", score_fieldtype.clone());
let score_field_i64 = schema_builder.add_i64_field("score_i64", score_fieldtype);
// use tmp dir
let index = if reuse_index {
Index::create_in_dir("agg_bench", schema_builder.build())?
} else {
Index::create_from_tempdir(schema_builder.build())?
};
// Approximate log proportions
let status_field_data = [
("INFO", 8000),
("ERROR", 300),
("WARN", 1200),
("DEBUG", 500),
("OK", 500),
("CRITICAL", 20),
("EMERGENCY", 1),
];
let log_level_distribution =
WeightedIndex::new(status_field_data.iter().map(|item| item.1)).unwrap();
let index = Index::create_from_tempdir(schema_builder.build())?;
let few_terms_data = ["INFO", "ERROR", "WARN", "DEBUG"];
let lg_norm = rand_distr::LogNormal::new(2.996f64, 0.979f64).unwrap();
let many_terms_data = (0..150_000)
.map(|num| format!("author{num}"))
.collect::<Vec<_>>();
// Prepare 1000 unique terms sampled using a Zipf distribution.
// Exponent ~1.1 approximates top-20 terms covering around ~20%.
let terms_1000: Vec<String> = (1..=1000).map(|i| format!("term_{i}")).collect();
let zipf_1000 = rand_distr::Zipf::new(1000.0, 1.1f64).unwrap();
{
let mut rng = StdRng::from_seed([1u8; 32]);
let mut index_writer = index.writer_with_num_threads(1, 200_000_000)?;
@@ -543,25 +442,15 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
index_writer.add_document(doc!())?;
}
if cardinality == Cardinality::Multivalued {
let log_level_sample_a = status_field_data[log_level_distribution.sample(&mut rng)].0;
let log_level_sample_b = status_field_data[log_level_distribution.sample(&mut rng)].0;
let idx_a = zipf_1000.sample(&mut rng) as usize - 1;
let idx_b = zipf_1000.sample(&mut rng) as usize - 1;
let term_1000_a = &terms_1000[idx_a];
let term_1000_b = &terms_1000[idx_b];
index_writer.add_document(doc!(
json_field => json!({"mixed_type": 10.0}),
json_field => json!({"mixed_type": 10.0}),
text_field => "cool",
text_field => "cool",
text_field_all_unique_terms => "cool",
text_field_all_unique_terms => "coolo",
text_field_many_terms => "cool",
text_field_many_terms => "cool",
text_field_few_terms_status => log_level_sample_a,
text_field_few_terms_status => log_level_sample_b,
text_field_1000_terms_zipf => term_1000_a.as_str(),
text_field_1000_terms_zipf => term_1000_b.as_str(),
text_field_few_terms => "cool",
text_field_few_terms => "cool",
score_field => 1u64,
score_field => 1u64,
score_field_f64 => lg_norm.sample(&mut rng),
@@ -576,8 +465,8 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
}
let _val_max = 1_000_000.0;
for _ in 0..doc_with_value {
let val: f64 = rng.random_range(0.0..1_000_000.0);
let json = if rng.random_bool(0.1) {
let val: f64 = rng.gen_range(0.0..1_000_000.0);
let json = if rng.gen_bool(0.1) {
// 10% are numeric values
json!({ "mixed_type": val })
} else {
@@ -586,10 +475,8 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
index_writer.add_document(doc!(
text_field => "cool",
json_field => json,
text_field_all_unique_terms => format!("unique_term_{}", rng.random::<u64>()),
text_field_many_terms => many_terms_data.choose(&mut rng).unwrap().to_string(),
text_field_few_terms_status => status_field_data[log_level_distribution.sample(&mut rng)].0,
text_field_1000_terms_zipf => terms_1000[zipf_1000.sample(&mut rng) as usize - 1].as_str(),
text_field_few_terms => few_terms_data.choose(&mut rng).unwrap().to_string(),
score_field => val as u64,
score_field_f64 => lg_norm.sample(&mut rng),
score_field_i64 => val as i64,
@@ -641,7 +528,7 @@ fn filter_agg_all_query_with_sub_aggs(index: &Index) {
"avg_score": { "avg": { "field": "score" } },
"stats_score": { "stats": { "field": "score_f64" } },
"terms_text": {
"terms": { "field": "text_few_terms_status" }
"terms": { "field": "text_few_terms" }
}
}
}
@@ -657,7 +544,7 @@ fn filter_agg_term_query_with_sub_aggs(index: &Index) {
"avg_score": { "avg": { "field": "score" } },
"stats_score": { "stats": { "field": "score_f64" } },
"terms_text": {
"terms": { "field": "text_few_terms_status" }
"terms": { "field": "text_few_terms" }
}
}
}

16
benches/and_or_queries.rs
View File

@@ -55,29 +55,29 @@ fn build_shared_indices(num_docs: usize, p_a: f32, p_b: f32, p_c: f32) -> (Bench
{
let mut writer = index.writer_with_num_threads(1, 500_000_000).unwrap();
for _ in 0..num_docs {
let has_a = rng.random_bool(p_a as f64);
let has_b = rng.random_bool(p_b as f64);
let has_c = rng.random_bool(p_c as f64);
let score = rng.random_range(0u64..100u64);
let score2 = rng.random_range(0u64..100_000u64);
let has_a = rng.gen_bool(p_a as f64);
let has_b = rng.gen_bool(p_b as f64);
let has_c = rng.gen_bool(p_c as f64);
let score = rng.gen_range(0u64..100u64);
let score2 = rng.gen_range(0u64..100_000u64);
let mut title_tokens: Vec<&str> = Vec::new();
let mut body_tokens: Vec<&str> = Vec::new();
if has_a {
if rng.random_bool(0.1) {
if rng.gen_bool(0.1) {
title_tokens.push("a");
} else {
body_tokens.push("a");
}
}
if has_b {
if rng.random_bool(0.1) {
if rng.gen_bool(0.1) {
title_tokens.push("b");
} else {
body_tokens.push("b");
}
}
if has_c {
if rng.random_bool(0.1) {
if rng.gen_bool(0.1) {
title_tokens.push("c");
} else {
body_tokens.push("c");

288
benches/bool_queries_with_range.rs
View File

@@ -1,288 +0,0 @@
use binggan::{black_box, BenchGroup, BenchRunner};
use rand::prelude::*;
use rand::rngs::StdRng;
use rand::SeedableRng;
use tantivy::collector::{Collector, Count, DocSetCollector, TopDocs};
use tantivy::query::{Query, QueryParser};
use tantivy::schema::{Schema, FAST, INDEXED, TEXT};
use tantivy::{doc, Index, Order, ReloadPolicy, Searcher};
#[derive(Clone)]
struct BenchIndex {
#[allow(dead_code)]
index: Index,
searcher: Searcher,
query_parser: QueryParser,
}
fn build_shared_indices(num_docs: usize, p_title_a: f32, distribution: &str) -> BenchIndex {
// Unified schema
let mut schema_builder = Schema::builder();
let f_title = schema_builder.add_text_field("title", TEXT);
let f_num_rand = schema_builder.add_u64_field("num_rand", INDEXED);
let f_num_asc = schema_builder.add_u64_field("num_asc", INDEXED);
let f_num_rand_fast = schema_builder.add_u64_field("num_rand_fast", INDEXED | FAST);
let f_num_asc_fast = schema_builder.add_u64_field("num_asc_fast", INDEXED | FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
// Populate index with stable RNG for reproducibility.
let mut rng = StdRng::from_seed([7u8; 32]);
{
let mut writer = index.writer_with_num_threads(1, 4_000_000_000).unwrap();
match distribution {
"dense" => {
for doc_id in 0..num_docs {
// Always add title to avoid empty documents
let title_token = if rng.random_bool(p_title_a as f64) {
"a"
} else {
"b"
};
let num_rand = rng.random_range(0u64..1000u64);
let num_asc = (doc_id / 10000) as u64;
writer
.add_document(doc!(
f_title=>title_token,
f_num_rand=>num_rand,
f_num_asc=>num_asc,
f_num_rand_fast=>num_rand,
f_num_asc_fast=>num_asc,
))
.unwrap();
}
}
"sparse" => {
for doc_id in 0..num_docs {
// Always add title to avoid empty documents
let title_token = if rng.random_bool(p_title_a as f64) {
"a"
} else {
"b"
};
let num_rand = rng.random_range(0u64..10000000u64);
let num_asc = doc_id as u64;
writer
.add_document(doc!(
f_title=>title_token,
f_num_rand=>num_rand,
f_num_asc=>num_asc,
f_num_rand_fast=>num_rand,
f_num_asc_fast=>num_asc,
))
.unwrap();
}
}
_ => {
panic!("Unsupported distribution type");
}
}
writer.commit().unwrap();
}
// Prepare reader/searcher once.
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::Manual)
.try_into()
.unwrap();
let searcher = reader.searcher();
// Build query parser for title field
let qp_title = QueryParser::for_index(&index, vec![f_title]);
BenchIndex {
index,
searcher,
query_parser: qp_title,
}
}
fn main() {
// Prepare corpora with varying scenarios
let scenarios = vec![
(
"dense and 99% a".to_string(),
10_000_000,
0.99,
"dense",
0,
9,
),
(
"dense and 99% a".to_string(),
10_000_000,
0.99,
"dense",
990,
999,
),
(
"sparse and 99% a".to_string(),
10_000_000,
0.99,
"sparse",
0,
9,
),
(
"sparse and 99% a".to_string(),
10_000_000,
0.99,
"sparse",
9_999_990,
9_999_999,
),
];
let mut runner = BenchRunner::new();
for (scenario_id, n, p_title_a, num_rand_distribution, range_low, range_high) in scenarios {
// Build index for this scenario
let bench_index = build_shared_indices(n, p_title_a, num_rand_distribution);
// Create benchmark group
let mut group = runner.new_group();
// Now set the name (this moves scenario_id)
group.set_name(scenario_id);
// Define all four field types
let field_names = ["num_rand", "num_asc", "num_rand_fast", "num_asc_fast"];
// Define the three terms we want to test with
let terms = ["a", "b", "z"];
// Generate all combinations of terms and field names
let mut queries = Vec::new();
for &term in &terms {
for &field_name in &field_names {
let query_str = format!(
"{} AND {}:[{} TO {}]",
term, field_name, range_low, range_high
);
queries.push((query_str, field_name.to_string()));
}
}
let query_str = format!(
"{}:[{} TO {}] AND {}:[{} TO {}]",
"num_rand_fast", range_low, range_high, "num_asc_fast", range_low, range_high
);
queries.push((query_str, "num_asc_fast".to_string()));
// Run all benchmark tasks for each query and its corresponding field name
for (query_str, field_name) in queries {
run_benchmark_tasks(&mut group, &bench_index, &query_str, &field_name);
}
group.run();
}
}
/// Run all benchmark tasks for a given query string and field name
fn run_benchmark_tasks(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query_str: &str,
field_name: &str,
) {
// Test count
add_bench_task(bench_group, bench_index, query_str, Count, "count");
// Test all results
add_bench_task(
bench_group,
bench_index,
query_str,
DocSetCollector,
"all results",
);
// Test top 100 by the field (if it's a FAST field)
if field_name.ends_with("_fast") {
// Ascending order
{
let collector_name = format!("top100_by_{}_asc", field_name);
let field_name_owned = field_name.to_string();
add_bench_task(
bench_group,
bench_index,
query_str,
TopDocs::with_limit(100).order_by_fast_field::<u64>(field_name_owned, Order::Asc),
&collector_name,
);
}
// Descending order
{
let collector_name = format!("top100_by_{}_desc", field_name);
let field_name_owned = field_name.to_string();
add_bench_task(
bench_group,
bench_index,
query_str,
TopDocs::with_limit(100).order_by_fast_field::<u64>(field_name_owned, Order::Desc),
&collector_name,
);
}
}
}
fn add_bench_task<C: Collector + 'static>(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query_str: &str,
collector: C,
collector_name: &str,
) {
let task_name = format!("{}_{}", query_str.replace(" ", "_"), collector_name);
let query = bench_index.query_parser.parse_query(query_str).unwrap();
let search_task = SearchTask {
searcher: bench_index.searcher.clone(),
collector,
query,
};
bench_group.register(task_name, move |_| black_box(search_task.run()));
}
struct SearchTask<C: Collector> {
searcher: Searcher,
collector: C,
query: Box<dyn Query>,
}
impl<C: Collector> SearchTask<C> {
#[inline(never)]
pub fn run(&self) -> usize {
let result = self.searcher.search(&self.query, &self.collector).unwrap();
if let Some(count) = (&result as &dyn std::any::Any).downcast_ref::<usize>() {
*count
} else if let Some(top_docs) = (&result as &dyn std::any::Any)
.downcast_ref::<Vec<(Option<u64>, tantivy::DocAddress)>>()
{
top_docs.len()
} else if let Some(top_docs) =
(&result as &dyn std::any::Any).downcast_ref::<Vec<(u64, tantivy::DocAddress)>>()
{
top_docs.len()
} else if let Some(doc_set) = (&result as &dyn std::any::Any)
.downcast_ref::<std::collections::HashSet<tantivy::DocAddress>>()
{
doc_set.len()
} else {
eprintln!(
"Unknown collector result type: {:?}",
std::any::type_name::<C::Fruit>()
);
0
}
}
}

224
benches/merge_segments.rs
View File

@@ -1,224 +0,0 @@
// Benchmarks segment merging
//
// Notes:
// - Input segments are kept intact (no deletes / no IndexWriter merge).
// - Output is written to a `NullDirectory` that discards all files except
// fieldnorms (needed for merging).
use std::collections::HashMap;
use std::io::{self, Write};
use std::path::{Path, PathBuf};
use std::sync::{Arc, RwLock};
use binggan::{black_box, BenchRunner};
use rand::prelude::*;
use rand::rngs::StdRng;
use rand::SeedableRng;
use tantivy::directory::error::{DeleteError, OpenReadError, OpenWriteError};
use tantivy::directory::{
AntiCallToken, Directory, FileHandle, OwnedBytes, TerminatingWrite, WatchCallback, WatchHandle,
WritePtr,
};
use tantivy::indexer::{merge_filtered_segments, NoMergePolicy};
use tantivy::schema::{Schema, TEXT};
use tantivy::{doc, HasLen, Index, IndexSettings, Segment};
#[derive(Clone, Default, Debug)]
struct NullDirectory {
blobs: Arc<RwLock<HashMap<PathBuf, OwnedBytes>>>,
}
struct NullWriter;
impl Write for NullWriter {
fn write(&mut self, buf: &[u8]) -> io::Result<usize> {
Ok(buf.len())
}
fn flush(&mut self) -> io::Result<()> {
Ok(())
}
}
impl TerminatingWrite for NullWriter {
fn terminate_ref(&mut self, _token: AntiCallToken) -> io::Result<()> {
Ok(())
}
}
struct InMemoryWriter {
path: PathBuf,
buffer: Vec<u8>,
blobs: Arc<RwLock<HashMap<PathBuf, OwnedBytes>>>,
}
impl Write for InMemoryWriter {
fn write(&mut self, buf: &[u8]) -> io::Result<usize> {
self.buffer.extend_from_slice(buf);
Ok(buf.len())
}
fn flush(&mut self) -> io::Result<()> {
Ok(())
}
}
impl TerminatingWrite for InMemoryWriter {
fn terminate_ref(&mut self, _token: AntiCallToken) -> io::Result<()> {
let bytes = OwnedBytes::new(std::mem::take(&mut self.buffer));
self.blobs.write().unwrap().insert(self.path.clone(), bytes);
Ok(())
}
}
#[derive(Debug, Default)]
struct NullFileHandle;
impl HasLen for NullFileHandle {
fn len(&self) -> usize {
0
}
}
impl FileHandle for NullFileHandle {
fn read_bytes(&self, _range: std::ops::Range<usize>) -> io::Result<OwnedBytes> {
unimplemented!()
}
}
impl Directory for NullDirectory {
fn get_file_handle(&self, path: &Path) -> Result<Arc<dyn FileHandle>, OpenReadError> {
if let Some(bytes) = self.blobs.read().unwrap().get(path) {
return Ok(Arc::new(bytes.clone()));
}
Ok(Arc::new(NullFileHandle))
}
fn delete(&self, _path: &Path) -> Result<(), DeleteError> {
Ok(())
}
fn exists(&self, _path: &Path) -> Result<bool, OpenReadError> {
Ok(true)
}
fn open_write(&self, path: &Path) -> Result<WritePtr, OpenWriteError> {
let path_buf = path.to_path_buf();
if path.to_string_lossy().ends_with(".fieldnorm") {
let writer = InMemoryWriter {
path: path_buf,
buffer: Vec::new(),
blobs: Arc::clone(&self.blobs),
};
Ok(io::BufWriter::new(Box::new(writer)))
} else {
Ok(io::BufWriter::new(Box::new(NullWriter)))
}
}
fn atomic_read(&self, path: &Path) -> Result<Vec<u8>, OpenReadError> {
if let Some(bytes) = self.blobs.read().unwrap().get(path) {
return Ok(bytes.as_slice().to_vec());
}
Err(OpenReadError::FileDoesNotExist(path.to_path_buf()))
}
fn atomic_write(&self, _path: &Path, _data: &[u8]) -> io::Result<()> {
Ok(())
}
fn sync_directory(&self) -> io::Result<()> {
Ok(())
}
fn watch(&self, _watch_callback: WatchCallback) -> tantivy::Result<WatchHandle> {
Ok(WatchHandle::empty())
}
}
struct MergeScenario {
#[allow(dead_code)]
index: Index,
segments: Vec<Segment>,
settings: IndexSettings,
label: String,
}
fn build_index(
num_segments: usize,
docs_per_segment: usize,
tokens_per_doc: usize,
vocab_size: usize,
) -> MergeScenario {
let mut schema_builder = Schema::builder();
let body = schema_builder.add_text_field("body", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
assert!(vocab_size > 0);
let total_tokens = num_segments * docs_per_segment * tokens_per_doc;
let use_unique_terms = vocab_size >= total_tokens;
let mut rng = StdRng::from_seed([7u8; 32]);
let mut next_token_id: u64 = 0;
{
let mut writer = index.writer_with_num_threads(1, 256_000_000).unwrap();
writer.set_merge_policy(Box::new(NoMergePolicy));
for _ in 0..num_segments {
for _ in 0..docs_per_segment {
let mut tokens = Vec::with_capacity(tokens_per_doc);
for _ in 0..tokens_per_doc {
let token_id = if use_unique_terms {
let id = next_token_id;
next_token_id += 1;
id
} else {
rng.random_range(0..vocab_size as u64)
};
tokens.push(format!("term_{token_id}"));
}
writer.add_document(doc!(body => tokens.join(" "))).unwrap();
}
writer.commit().unwrap();
}
}
let segments = index.searchable_segments().unwrap();
let settings = index.settings().clone();
let label = format!(
"segments={}, docs/seg={}, tokens/doc={}, vocab={}",
num_segments, docs_per_segment, tokens_per_doc, vocab_size
);
MergeScenario {
index,
segments,
settings,
label,
}
}
fn main() {
let scenarios = vec![
build_index(8, 50_000, 12, 8),
build_index(16, 50_000, 12, 8),
build_index(16, 100_000, 12, 8),
build_index(8, 50_000, 8, 8 * 50_000 * 8),
];
let mut runner = BenchRunner::new();
for scenario in scenarios {
let mut group = runner.new_group();
group.set_name(format!("merge_segments inv_index — {}", scenario.label));
let segments = scenario.segments.clone();
let settings = scenario.settings.clone();
group.register("merge", move |_| {
let output_dir = NullDirectory::default();
let filter_doc_ids = vec![None; segments.len()];
let merged_index =
merge_filtered_segments(&segments, settings.clone(), filter_doc_ids, output_dir)
.unwrap();
black_box(merged_index);
});
group.run();
}
}

365
benches/range_queries.rs
View File

@@ -1,365 +0,0 @@
use std::ops::Bound;
use binggan::{black_box, BenchGroup, BenchRunner};
use rand::prelude::*;
use rand::rngs::StdRng;
use rand::SeedableRng;
use tantivy::collector::{Count, DocSetCollector, TopDocs};
use tantivy::query::RangeQuery;
use tantivy::schema::{Schema, FAST, INDEXED};
use tantivy::{doc, Index, Order, ReloadPolicy, Searcher, Term};
#[derive(Clone)]
struct BenchIndex {
#[allow(dead_code)]
index: Index,
searcher: Searcher,
}
fn build_shared_indices(num_docs: usize, distribution: &str) -> BenchIndex {
// Schema with fast fields only
let mut schema_builder = Schema::builder();
let f_num_rand_fast = schema_builder.add_u64_field("num_rand_fast", INDEXED | FAST);
let f_num_asc_fast = schema_builder.add_u64_field("num_asc_fast", INDEXED | FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
// Populate index with stable RNG for reproducibility.
let mut rng = StdRng::from_seed([7u8; 32]);
{
let mut writer = index.writer_with_num_threads(1, 4_000_000_000).unwrap();
match distribution {
"dense" => {
for doc_id in 0..num_docs {
let num_rand = rng.random_range(0u64..1000u64);
let num_asc = (doc_id / 10000) as u64;
writer
.add_document(doc!(
f_num_rand_fast=>num_rand,
f_num_asc_fast=>num_asc,
))
.unwrap();
}
}
"sparse" => {
for doc_id in 0..num_docs {
let num_rand = rng.random_range(0u64..10000000u64);
let num_asc = doc_id as u64;
writer
.add_document(doc!(
f_num_rand_fast=>num_rand,
f_num_asc_fast=>num_asc,
))
.unwrap();
}
}
_ => {
panic!("Unsupported distribution type");
}
}
writer.commit().unwrap();
}
// Prepare reader/searcher once.
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::Manual)
.try_into()
.unwrap();
let searcher = reader.searcher();
BenchIndex { index, searcher }
}
fn main() {
// Prepare corpora with varying scenarios
let scenarios = vec![
// Dense distribution - random values in small range (0-999)
(
"dense_values_search_low_value_range".to_string(),
10_000_000,
"dense",
0,
9,
),
(
"dense_values_search_high_value_range".to_string(),
10_000_000,
"dense",
990,
999,
),
(
"dense_values_search_out_of_range".to_string(),
10_000_000,
"dense",
1000,
1002,
),
(
"sparse_values_search_low_value_range".to_string(),
10_000_000,
"sparse",
0,
9,
),
(
"sparse_values_search_high_value_range".to_string(),
10_000_000,
"sparse",
9_999_990,
9_999_999,
),
(
"sparse_values_search_out_of_range".to_string(),
10_000_000,
"sparse",
10_000_000,
10_000_002,
),
];
let mut runner = BenchRunner::new();
for (scenario_id, n, num_rand_distribution, range_low, range_high) in scenarios {
// Build index for this scenario
let bench_index = build_shared_indices(n, num_rand_distribution);
// Create benchmark group
let mut group = runner.new_group();
// Now set the name (this moves scenario_id)
group.set_name(scenario_id);
// Define fast field types
let field_names = ["num_rand_fast", "num_asc_fast"];
// Generate range queries for fast fields
for &field_name in &field_names {
// Create the range query
let field = bench_index.searcher.schema().get_field(field_name).unwrap();
let lower_term = Term::from_field_u64(field, range_low);
let upper_term = Term::from_field_u64(field, range_high);
let query = RangeQuery::new(Bound::Included(lower_term), Bound::Included(upper_term));
run_benchmark_tasks(
&mut group,
&bench_index,
query,
field_name,
range_low,
range_high,
);
}
group.run();
}
}
/// Run all benchmark tasks for a given range query and field name
fn run_benchmark_tasks(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
field_name: &str,
range_low: u64,
range_high: u64,
) {
// Test count
add_bench_task_count(
bench_group,
bench_index,
query.clone(),
"count",
field_name,
range_low,
range_high,
);
// Test top 100 by the field (ascending order)
{
let collector_name = format!("top100_by_{}_asc", field_name);
let field_name_owned = field_name.to_string();
add_bench_task_top100_asc(
bench_group,
bench_index,
query.clone(),
&collector_name,
field_name,
range_low,
range_high,
field_name_owned,
);
}
// Test top 100 by the field (descending order)
{
let collector_name = format!("top100_by_{}_desc", field_name);
let field_name_owned = field_name.to_string();
add_bench_task_top100_desc(
bench_group,
bench_index,
query,
&collector_name,
field_name,
range_low,
range_high,
field_name_owned,
);
}
}
fn add_bench_task_count(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
collector_name: &str,
field_name: &str,
range_low: u64,
range_high: u64,
) {
let task_name = format!(
"range_{}_[{} TO {}]_{}",
field_name, range_low, range_high, collector_name
);
let search_task = CountSearchTask {
searcher: bench_index.searcher.clone(),
query,
};
bench_group.register(task_name, move |_| black_box(search_task.run()));
}
fn add_bench_task_docset(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
collector_name: &str,
field_name: &str,
range_low: u64,
range_high: u64,
) {
let task_name = format!(
"range_{}_[{} TO {}]_{}",
field_name, range_low, range_high, collector_name
);
let search_task = DocSetSearchTask {
searcher: bench_index.searcher.clone(),
query,
};
bench_group.register(task_name, move |_| black_box(search_task.run()));
}
fn add_bench_task_top100_asc(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
collector_name: &str,
field_name: &str,
range_low: u64,
range_high: u64,
field_name_owned: String,
) {
let task_name = format!(
"range_{}_[{} TO {}]_{}",
field_name, range_low, range_high, collector_name
);
let search_task = Top100AscSearchTask {
searcher: bench_index.searcher.clone(),
query,
field_name: field_name_owned,
};
bench_group.register(task_name, move |_| black_box(search_task.run()));
}
fn add_bench_task_top100_desc(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
collector_name: &str,
field_name: &str,
range_low: u64,
range_high: u64,
field_name_owned: String,
) {
let task_name = format!(
"range_{}_[{} TO {}]_{}",
field_name, range_low, range_high, collector_name
);
let search_task = Top100DescSearchTask {
searcher: bench_index.searcher.clone(),
query,
field_name: field_name_owned,
};
bench_group.register(task_name, move |_| black_box(search_task.run()));
}
struct CountSearchTask {
searcher: Searcher,
query: RangeQuery,
}
impl CountSearchTask {
#[inline(never)]
pub fn run(&self) -> usize {
self.searcher.search(&self.query, &Count).unwrap()
}
}
struct DocSetSearchTask {
searcher: Searcher,
query: RangeQuery,
}
impl DocSetSearchTask {
#[inline(never)]
pub fn run(&self) -> usize {
let result = self.searcher.search(&self.query, &DocSetCollector).unwrap();
result.len()
}
}
struct Top100AscSearchTask {
searcher: Searcher,
query: RangeQuery,
field_name: String,
}
impl Top100AscSearchTask {
#[inline(never)]
pub fn run(&self) -> usize {
let collector =
TopDocs::with_limit(100).order_by_fast_field::<u64>(&self.field_name, Order::Asc);
let result = self.searcher.search(&self.query, &collector).unwrap();
for (_score, doc_address) in &result {
let _doc: tantivy::TantivyDocument = self.searcher.doc(*doc_address).unwrap();
}
result.len()
}
}
struct Top100DescSearchTask {
searcher: Searcher,
query: RangeQuery,
field_name: String,
}
impl Top100DescSearchTask {
#[inline(never)]
pub fn run(&self) -> usize {
let collector =
TopDocs::with_limit(100).order_by_fast_field::<u64>(&self.field_name, Order::Desc);
let result = self.searcher.search(&self.query, &collector).unwrap();
for (_score, doc_address) in &result {
let _doc: tantivy::TantivyDocument = self.searcher.doc(*doc_address).unwrap();
}
result.len()
}
}

260
benches/range_query.rs
View File

@@ -1,260 +0,0 @@
use std::fmt::Display;
use std::net::Ipv6Addr;
use std::ops::RangeInclusive;
use binggan::plugins::PeakMemAllocPlugin;
use binggan::{black_box, BenchRunner, OutputValue, PeakMemAlloc, INSTRUMENTED_SYSTEM};
use columnar::MonotonicallyMappableToU128;
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use tantivy::collector::{Count, TopDocs};
use tantivy::query::QueryParser;
use tantivy::schema::*;
use tantivy::{doc, Index};
#[global_allocator]
pub static GLOBAL: &PeakMemAlloc<std::alloc::System> = &INSTRUMENTED_SYSTEM;
fn main() {
bench_range_query();
}
fn bench_range_query() {
let index = get_index_0_to_100();
let mut runner = BenchRunner::new();
runner.add_plugin(PeakMemAllocPlugin::new(GLOBAL));
runner.set_name("range_query on u64");
let field_name_and_descr: Vec<_> = vec![
("id", "Single Valued Range Field"),
("ids", "Multi Valued Range Field"),
];
let range_num_hits = vec![
("90_percent", get_90_percent()),
("10_percent", get_10_percent()),
("1_percent", get_1_percent()),
];
test_range(&mut runner, &index, &field_name_and_descr, range_num_hits);
runner.set_name("range_query on ip");
let field_name_and_descr: Vec<_> = vec![
("ip", "Single Valued Range Field"),
("ips", "Multi Valued Range Field"),
];
let range_num_hits = vec![
("90_percent", get_90_percent_ip()),
("10_percent", get_10_percent_ip()),
("1_percent", get_1_percent_ip()),
];
test_range(&mut runner, &index, &field_name_and_descr, range_num_hits);
}
fn test_range<T: Display>(
runner: &mut BenchRunner,
index: &Index,
field_name_and_descr: &[(&str, &str)],
range_num_hits: Vec<(&str, RangeInclusive<T>)>,
) {
for (field, suffix) in field_name_and_descr {
let term_num_hits = vec![
("", ""),
("1_percent", "veryfew"),
("10_percent", "few"),
("90_percent", "most"),
];
let mut group = runner.new_group();
group.set_name(suffix);
// all intersect combinations
for (range_name, range) in &range_num_hits {
for (term_name, term) in &term_num_hits {
let index = &index;
let test_name = if term_name.is_empty() {
format!("id_range_hit_{}", range_name)
} else {
format!(
"id_range_hit_{}_intersect_with_term_{}",
range_name, term_name
)
};
group.register(test_name, move |_| {
let query = if term_name.is_empty() {
"".to_string()
} else {
format!("AND id_name:{}", term)
};
black_box(execute_query(field, range, &query, index));
});
}
}
group.run();
}
}
fn get_index_0_to_100() -> Index {
let mut rng = StdRng::from_seed([1u8; 32]);
let num_vals = 100_000;
let docs: Vec<_> = (0..num_vals)
.map(|_i| {
let id_name = if rng.random_bool(0.01) {
"veryfew".to_string() // 1%
} else if rng.random_bool(0.1) {
"few".to_string() // 9%
} else {
"most".to_string() // 90%
};
Doc {
id_name,
id: rng.random_range(0..100),
// Multiply by 1000, so that we create most buckets in the compact space
// The benches depend on this range to select n-percent of elements with the
// methods below.
ip: Ipv6Addr::from_u128(rng.random_range(0..100) * 1000),
}
})
.collect();
create_index_from_docs(&docs)
}
#[derive(Clone, Debug)]
pub struct Doc {
pub id_name: String,
pub id: u64,
pub ip: Ipv6Addr,
}
pub fn create_index_from_docs(docs: &[Doc]) -> Index {
let mut schema_builder = Schema::builder();
let id_u64_field = schema_builder.add_u64_field("id", INDEXED | STORED | FAST);
let ids_u64_field =
schema_builder.add_u64_field("ids", NumericOptions::default().set_fast().set_indexed());
let id_f64_field = schema_builder.add_f64_field("id_f64", INDEXED | STORED | FAST);
let ids_f64_field = schema_builder.add_f64_field(
"ids_f64",
NumericOptions::default().set_fast().set_indexed(),
);
let id_i64_field = schema_builder.add_i64_field("id_i64", INDEXED | STORED | FAST);
let ids_i64_field = schema_builder.add_i64_field(
"ids_i64",
NumericOptions::default().set_fast().set_indexed(),
);
let text_field = schema_builder.add_text_field("id_name", STRING | STORED);
let text_field2 = schema_builder.add_text_field("id_name_fast", STRING | STORED | FAST);
let ip_field = schema_builder.add_ip_addr_field("ip", FAST);
let ips_field = schema_builder.add_ip_addr_field("ips", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut index_writer = index.writer_with_num_threads(1, 50_000_000).unwrap();
for doc in docs.iter() {
index_writer
.add_document(doc!(
ids_i64_field => doc.id as i64,
ids_i64_field => doc.id as i64,
ids_f64_field => doc.id as f64,
ids_f64_field => doc.id as f64,
ids_u64_field => doc.id,
ids_u64_field => doc.id,
id_u64_field => doc.id,
id_f64_field => doc.id as f64,
id_i64_field => doc.id as i64,
text_field => doc.id_name.to_string(),
text_field2 => doc.id_name.to_string(),
ips_field => doc.ip,
ips_field => doc.ip,
ip_field => doc.ip,
))
.unwrap();
}
index_writer.commit().unwrap();
}
index
}
fn get_90_percent() -> RangeInclusive<u64> {
0..=90
}
fn get_10_percent() -> RangeInclusive<u64> {
0..=10
}
fn get_1_percent() -> RangeInclusive<u64> {
10..=10
}
fn get_90_percent_ip() -> RangeInclusive<Ipv6Addr> {
let start = Ipv6Addr::from_u128(0);
let end = Ipv6Addr::from_u128(90 * 1000);
start..=end
}
fn get_10_percent_ip() -> RangeInclusive<Ipv6Addr> {
let start = Ipv6Addr::from_u128(0);
let end = Ipv6Addr::from_u128(10 * 1000);
start..=end
}
fn get_1_percent_ip() -> RangeInclusive<Ipv6Addr> {
let start = Ipv6Addr::from_u128(10 * 1000);
let end = Ipv6Addr::from_u128(10 * 1000);
start..=end
}
struct NumHits {
count: usize,
}
impl OutputValue for NumHits {
fn column_title() -> &'static str {
"NumHits"
}
fn format(&self) -> Option<String> {
Some(self.count.to_string())
}
}
fn execute_query<T: Display>(
field: &str,
id_range: &RangeInclusive<T>,
suffix: &str,
index: &Index,
) -> NumHits {
let gen_query_inclusive = |from: &T, to: &T| {
format!(
"{}:[{} TO {}] {}",
field,
&from.to_string(),
&to.to_string(),
suffix
)
};
let query = gen_query_inclusive(id_range.start(), id_range.end());
execute_query_(&query, index)
}
fn execute_query_(query: &str, index: &Index) -> NumHits {
let query_from_text = |text: &str| {
QueryParser::for_index(index, vec![])
.parse_query(text)
.unwrap()
};
let query = query_from_text(query);
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let num_hits = searcher
.search(&query, &(TopDocs::with_limit(10).order_by_score(), Count))
.unwrap()
.1;
NumHits { count: num_hits }
}

113
benches/regex_all_terms.rs
View File

@@ -1,113 +0,0 @@
// Benchmarks regex query that matches all terms in a synthetic index.
//
// Corpus model:
// - N unique terms: t000000, t000001, ...
// - M docs
// - K tokens per doc: doc i gets terms derived from (i, token_index)
//
// Query:
// - Regex "t.*" to match all terms
//
// Run with:
// - cargo bench --bench regex_all_terms
//
use std::fmt::Write;
use binggan::{black_box, BenchRunner};
use tantivy::collector::Count;
use tantivy::query::RegexQuery;
use tantivy::schema::{Schema, TEXT};
use tantivy::{doc, Index, ReloadPolicy};
const HEAP_SIZE_BYTES: usize = 200_000_000;
#[derive(Clone, Copy)]
struct BenchConfig {
num_terms: usize,
num_docs: usize,
tokens_per_doc: usize,
}
fn main() {
let configs = default_configs();
let mut runner = BenchRunner::new();
for config in configs {
let (index, text_field) = build_index(config, HEAP_SIZE_BYTES);
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::Manual)
.try_into()
.expect("reader");
let searcher = reader.searcher();
let query = RegexQuery::from_pattern("t.*", text_field).expect("regex query");
let mut group = runner.new_group();
group.set_name(format!(
"regex_all_terms_t{}_d{}_k{}",
config.num_terms, config.num_docs, config.tokens_per_doc
));
group.register("regex_count", move |_| {
let count = searcher.search(&query, &Count).expect("search");
black_box(count);
});
group.run();
}
}
fn default_configs() -> Vec<BenchConfig> {
vec![
BenchConfig {
num_terms: 10_000,
num_docs: 100_000,
tokens_per_doc: 1,
},
BenchConfig {
num_terms: 10_000,
num_docs: 100_000,
tokens_per_doc: 8,
},
BenchConfig {
num_terms: 100_000,
num_docs: 100_000,
tokens_per_doc: 1,
},
BenchConfig {
num_terms: 100_000,
num_docs: 100_000,
tokens_per_doc: 8,
},
]
}
fn build_index(config: BenchConfig, heap_size_bytes: usize) -> (Index, tantivy::schema::Field) {
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("text", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let term_width = config.num_terms.to_string().len();
{
let mut writer = index
.writer_with_num_threads(1, heap_size_bytes)
.expect("writer");
let mut buffer = String::new();
for doc_id in 0..config.num_docs {
buffer.clear();
for token_idx in 0..config.tokens_per_doc {
if token_idx > 0 {
buffer.push(' ');
}
let term_id = (doc_id * config.tokens_per_doc + token_idx) % config.num_terms;
write!(&mut buffer, "t{term_id:0term_width$}").expect("write token");
}
writer
.add_document(doc!(text_field => buffer.as_str()))
.expect("add_document");
}
writer.commit().expect("commit");
}
(index, text_field)
}

421
benches/str_search_and_get.rs
View File

@@ -1,421 +0,0 @@
// This benchmark compares different approaches for retrieving string values:
//
// 1. Fast Field Approach: retrieves string values via term_ords() and ord_to_str()
//
// 2. Doc Store Approach: retrieves string values via searcher.doc() and field extraction
//
// The benchmark includes various data distributions:
// - Dense Sequential: Sequential document IDs with dense data
// - Dense Random: Random document IDs with dense data
// - Sparse Sequential: Sequential document IDs with sparse data
// - Sparse Random: Random document IDs with sparse data
use std::ops::Bound;
use binggan::{black_box, BenchGroup, BenchRunner};
use rand::prelude::*;
use rand::rngs::StdRng;
use rand::SeedableRng;
use tantivy::collector::{Count, DocSetCollector};
use tantivy::query::RangeQuery;
use tantivy::schema::document::TantivyDocument;
use tantivy::schema::{Schema, Value, FAST, STORED, STRING};
use tantivy::{doc, Index, ReloadPolicy, Searcher, Term};
#[derive(Clone)]
struct BenchIndex {
#[allow(dead_code)]
index: Index,
searcher: Searcher,
}
fn build_shared_indices(num_docs: usize, distribution: &str) -> BenchIndex {
// Schema with string fast field and stored field for doc access
let mut schema_builder = Schema::builder();
let f_str_fast = schema_builder.add_text_field("str_fast", STRING | STORED | FAST);
let f_str_stored = schema_builder.add_text_field("str_stored", STRING | STORED);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
// Populate index with stable RNG for reproducibility.
let mut rng = StdRng::from_seed([7u8; 32]);
{
let mut writer = index.writer_with_num_threads(1, 4_000_000_000).unwrap();
match distribution {
"dense_random" => {
for _doc_id in 0..num_docs {
let suffix = rng.gen_range(0u64..1000u64);
let str_val = format!("str_{:03}", suffix);
writer
.add_document(doc!(
f_str_fast=>str_val.clone(),
f_str_stored=>str_val,
))
.unwrap();
}
}
"dense_sequential" => {
for doc_id in 0..num_docs {
let suffix = doc_id as u64 % 1000;
let str_val = format!("str_{:03}", suffix);
writer
.add_document(doc!(
f_str_fast=>str_val.clone(),
f_str_stored=>str_val,
))
.unwrap();
}
}
"sparse_random" => {
for _doc_id in 0..num_docs {
let suffix = rng.gen_range(0u64..1000000u64);
let str_val = format!("str_{:07}", suffix);
writer
.add_document(doc!(
f_str_fast=>str_val.clone(),
f_str_stored=>str_val,
))
.unwrap();
}
}
"sparse_sequential" => {
for doc_id in 0..num_docs {
let suffix = doc_id as u64;
let str_val = format!("str_{:07}", suffix);
writer
.add_document(doc!(
f_str_fast=>str_val.clone(),
f_str_stored=>str_val,
))
.unwrap();
}
}
_ => {
panic!("Unsupported distribution type");
}
}
writer.commit().unwrap();
}
// Prepare reader/searcher once.
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::Manual)
.try_into()
.unwrap();
let searcher = reader.searcher();
BenchIndex { index, searcher }
}
fn main() {
// Prepare corpora with varying scenarios
let scenarios = vec![
(
"dense_random_search_low_range".to_string(),
1_000_000,
"dense_random",
0,
9,
),
(
"dense_random_search_high_range".to_string(),
1_000_000,
"dense_random",
990,
999,
),
(
"dense_sequential_search_low_range".to_string(),
1_000_000,
"dense_sequential",
0,
9,
),
(
"dense_sequential_search_high_range".to_string(),
1_000_000,
"dense_sequential",
990,
999,
),
(
"sparse_random_search_low_range".to_string(),
1_000_000,
"sparse_random",
0,
9999,
),
(
"sparse_random_search_high_range".to_string(),
1_000_000,
"sparse_random",
990_000,
999_999,
),
(
"sparse_sequential_search_low_range".to_string(),
1_000_000,
"sparse_sequential",
0,
9999,
),
(
"sparse_sequential_search_high_range".to_string(),
1_000_000,
"sparse_sequential",
990_000,
999_999,
),
];
let mut runner = BenchRunner::new();
for (scenario_id, n, distribution, range_low, range_high) in scenarios {
let bench_index = build_shared_indices(n, distribution);
let mut group = runner.new_group();
group.set_name(scenario_id);
let field = bench_index.searcher.schema().get_field("str_fast").unwrap();
let (lower_str, upper_str) =
if distribution == "dense_sequential" || distribution == "dense_random" {
(
format!("str_{:03}", range_low),
format!("str_{:03}", range_high),
)
} else {
(
format!("str_{:07}", range_low),
format!("str_{:07}", range_high),
)
};
let lower_term = Term::from_field_text(field, &lower_str);
let upper_term = Term::from_field_text(field, &upper_str);
let query = RangeQuery::new(Bound::Included(lower_term), Bound::Included(upper_term));
run_benchmark_tasks(&mut group, &bench_index, query, range_low, range_high);
group.run();
}
}
/// Run all benchmark tasks for a given range query
fn run_benchmark_tasks(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
range_low: u64,
range_high: u64,
) {
// Test count of matching documents
add_bench_task_count(
bench_group,
bench_index,
query.clone(),
range_low,
range_high,
);
// Test fetching all DocIds of matching documents
add_bench_task_docset(
bench_group,
bench_index,
query.clone(),
range_low,
range_high,
);
// Test fetching all string fast field values of matching documents
add_bench_task_fetch_all_strings(
bench_group,
bench_index,
query.clone(),
range_low,
range_high,
);
// Test fetching all string values of matching documents through doc() method
add_bench_task_fetch_all_strings_from_doc(
bench_group,
bench_index,
query,
range_low,
range_high,
);
}
fn add_bench_task_count(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
range_low: u64,
range_high: u64,
) {
let task_name = format!("string_search_count_[{}-{}]", range_low, range_high);
let search_task = CountSearchTask {
searcher: bench_index.searcher.clone(),
query,
};
bench_group.register(task_name, move |_| black_box(search_task.run()));
}
fn add_bench_task_docset(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
range_low: u64,
range_high: u64,
) {
let task_name = format!("string_fetch_all_docset_[{}-{}]", range_low, range_high);
let search_task = DocSetSearchTask {
searcher: bench_index.searcher.clone(),
query,
};
bench_group.register(task_name, move |_| black_box(search_task.run()));
}
fn add_bench_task_fetch_all_strings(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
range_low: u64,
range_high: u64,
) {
let task_name = format!(
"string_fastfield_fetch_all_strings_[{}-{}]",
range_low, range_high
);
let search_task = FetchAllStringsSearchTask {
searcher: bench_index.searcher.clone(),
query,
};
bench_group.register(task_name, move |_| {
let result = black_box(search_task.run());
result.len()
});
}
fn add_bench_task_fetch_all_strings_from_doc(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
range_low: u64,
range_high: u64,
) {
let task_name = format!(
"string_doc_fetch_all_strings_[{}-{}]",
range_low, range_high
);
let search_task = FetchAllStringsFromDocTask {
searcher: bench_index.searcher.clone(),
query,
};
bench_group.register(task_name, move |_| {
let result = black_box(search_task.run());
result.len()
});
}
struct CountSearchTask {
searcher: Searcher,
query: RangeQuery,
}
impl CountSearchTask {
#[inline(never)]
pub fn run(&self) -> usize {
self.searcher.search(&self.query, &Count).unwrap()
}
}
struct DocSetSearchTask {
searcher: Searcher,
query: RangeQuery,
}
impl DocSetSearchTask {
#[inline(never)]
pub fn run(&self) -> usize {
let result = self.searcher.search(&self.query, &DocSetCollector).unwrap();
result.len()
}
}
struct FetchAllStringsSearchTask {
searcher: Searcher,
query: RangeQuery,
}
impl FetchAllStringsSearchTask {
#[inline(never)]
pub fn run(&self) -> Vec<String> {
let doc_addresses = self.searcher.search(&self.query, &DocSetCollector).unwrap();
let mut docs = doc_addresses.into_iter().collect::<Vec<_>>();
docs.sort();
let mut strings = Vec::with_capacity(docs.len());
for doc_address in docs {
let segment_reader = &self.searcher.segment_readers()[doc_address.segment_ord as usize];
let str_column_opt = segment_reader.fast_fields().str("str_fast");
if let Ok(Some(str_column)) = str_column_opt {
let doc_id = doc_address.doc_id;
let term_ord = str_column.term_ords(doc_id).next().unwrap();
let mut str_buffer = String::new();
if str_column.ord_to_str(term_ord, &mut str_buffer).is_ok() {
strings.push(str_buffer);
}
}
}
strings
}
}
struct FetchAllStringsFromDocTask {
searcher: Searcher,
query: RangeQuery,
}
impl FetchAllStringsFromDocTask {
#[inline(never)]
pub fn run(&self) -> Vec<String> {
let doc_addresses = self.searcher.search(&self.query, &DocSetCollector).unwrap();
let mut docs = doc_addresses.into_iter().collect::<Vec<_>>();
docs.sort();
let mut strings = Vec::with_capacity(docs.len());
let str_stored_field = self
.searcher
.schema()
.get_field("str_stored")
.expect("str_stored field should exist");
for doc_address in docs {
// Get the document from the doc store (row store access)
if let Ok(doc) = self.searcher.doc::<TantivyDocument>(doc_address) {
// Extract string values from the stored field
if let Some(field_value) = doc.get_first(str_stored_field) {
if let Some(text) = field_value.as_value().as_str() {
strings.push(text.to_string());
}
}
}
}
strings
}
}

2
bitpacker/Cargo.toml
View File

@@ -18,5 +18,5 @@ homepage = "https://github.com/quickwit-oss/tantivy"
bitpacking = { version = "0.9.2", default-features = false, features = ["bitpacker1x"] }
[dev-dependencies]
rand = "0.9"
rand = "0.8"
proptest = "1"

4
bitpacker/benches/bench.rs
View File

@@ -4,8 +4,8 @@ extern crate test;
#[cfg(test)]
mod tests {
use rand::rng;
use rand::seq::IteratorRandom;
use rand::thread_rng;
use tantivy_bitpacker::{BitPacker, BitUnpacker, BlockedBitpacker};
use test::Bencher;
@@ -27,7 +27,7 @@ mod tests {
let num_els = 1_000_000u32;
let bit_unpacker = BitUnpacker::new(bit_width);
let data = create_bitpacked_data(bit_width, num_els);
let idxs: Vec<u32> = (0..num_els).choose_multiple(&mut rng(), 100_000);
let idxs: Vec<u32> = (0..num_els).choose_multiple(&mut thread_rng(), 100_000);
b.iter(|| {
let mut out = 0u64;
for &idx in &idxs {

27
bitpacker/src/filter_vec/avx2.rs
View File

@@ -19,7 +19,7 @@ fn u32_to_i32(val: u32) -> i32 {
#[inline]
unsafe fn u32_to_i32_avx2(vals_u32x8s: DataType) -> DataType {
const HIGHEST_BIT_MASK: DataType = from_u32x8([HIGHEST_BIT; NUM_LANES]);
unsafe { op_xor(vals_u32x8s, HIGHEST_BIT_MASK) }
op_xor(vals_u32x8s, HIGHEST_BIT_MASK)
}
pub fn filter_vec_in_place(range: RangeInclusive<u32>, offset: u32, output: &mut Vec<u32>) {
@@ -66,19 +66,17 @@ unsafe fn filter_vec_avx2_aux(
]);
const SHIFT: __m256i = from_u32x8([NUM_LANES as u32; NUM_LANES]);
for _ in 0..num_words {
unsafe {
let word = load_unaligned(input);
let word = u32_to_i32_avx2(word);
let keeper_bitset = compute_filter_bitset(word, range_simd.clone());
let added_len = keeper_bitset.count_ones();
let filtered_doc_ids = compact(ids, keeper_bitset);
store_unaligned(output_tail as *mut __m256i, filtered_doc_ids);
output_tail = output_tail.offset(added_len as isize);
ids = op_add(ids, SHIFT);
input = input.offset(1);
}
let word = load_unaligned(input);
let word = u32_to_i32_avx2(word);
let keeper_bitset = compute_filter_bitset(word, range_simd.clone());
let added_len = keeper_bitset.count_ones();
let filtered_doc_ids = compact(ids, keeper_bitset);
store_unaligned(output_tail as *mut __m256i, filtered_doc_ids);
output_tail = output_tail.offset(added_len as isize);
ids = op_add(ids, SHIFT);
input = input.offset(1);
}
unsafe { output_tail.offset_from(output) as usize }
output_tail.offset_from(output) as usize
}
#[inline]
@@ -94,7 +92,8 @@ unsafe fn compute_filter_bitset(val: __m256i, range: std::ops::RangeInclusive<__
let too_low = op_greater(*range.start(), val);
let too_high = op_greater(val, *range.end());
let inside = op_or(too_low, too_high);
255 - std::arch::x86_64::_mm256_movemask_ps(_mm256_castsi256_ps(inside)) as u8
255 - std::arch::x86_64::_mm256_movemask_ps(std::mem::transmute::<DataType, __m256>(inside))
as u8
}
union U8x32 {

2
columnar/Cargo.toml
View File

@@ -22,7 +22,7 @@ downcast-rs = "2.0.1"
[dev-dependencies]
proptest = "1"
more-asserts = "0.3.1"
rand = "0.9"
rand = "0.8"
binggan = "0.14.0"
[[bench]]

2
columnar/benches/bench_column_values_get.rs
View File

@@ -9,7 +9,7 @@ use tantivy_columnar::column_values::{CodecType, serialize_and_load_u64_based_co
fn get_data() -> Vec<u64> {
let mut rng = StdRng::seed_from_u64(2u64);
let mut data: Vec<_> = (100..55_000_u64)
.map(|num| num + rng.random::<u8>() as u64)
.map(|num| num + rng.r#gen::<u8>() as u64)
.collect();
data.push(99_000);
data.insert(1000, 2000);

2
columnar/benches/bench_create_column_values.rs
View File

@@ -6,7 +6,7 @@ use tantivy_columnar::column_values::{CodecType, serialize_u64_based_column_valu
fn get_data() -> Vec<u64> {
let mut rng = StdRng::seed_from_u64(2u64);
let mut data: Vec<_> = (100..55_000_u64)
.map(|num| num + rng.random::<u8>() as u64)
.map(|num| num + rng.r#gen::<u8>() as u64)
.collect();
data.push(99_000);
data.insert(1000, 2000);

4
columnar/benches/bench_optional_index.rs
View File

@@ -8,7 +8,7 @@ const TOTAL_NUM_VALUES: u32 = 1_000_000;
fn gen_optional_index(fill_ratio: f64) -> OptionalIndex {
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let vals: Vec<u32> = (0..TOTAL_NUM_VALUES)
.map(|_| rng.random_bool(fill_ratio))
.map(|_| rng.gen_bool(fill_ratio))
.enumerate()
.filter(|(_pos, val)| *val)
.map(|(pos, _)| pos as u32)
@@ -25,7 +25,7 @@ fn random_range_iterator(
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let mut current = start;
std::iter::from_fn(move || {
current += rng.random_range(avg_step_size - avg_deviation..=avg_step_size + avg_deviation);
current += rng.gen_range(avg_step_size - avg_deviation..=avg_step_size + avg_deviation);
if current >= end { None } else { Some(current) }
})
}

2
columnar/benches/bench_values_u128.rs
View File

@@ -39,7 +39,7 @@ fn get_data_50percent_item() -> Vec<u128> {
let mut data = vec![];
for _ in 0..300_000 {
let val = rng.random_range(1..=100);
let val = rng.gen_range(1..=100);
data.push(val);
}
data.push(SINGLE_ITEM);

2
columnar/benches/bench_values_u64.rs
View File

@@ -34,7 +34,7 @@ fn get_data_50percent_item() -> Vec<u128> {
let mut data = vec![];
for _ in 0..300_000 {
let val = rng.random_range(1..=100);
let val = rng.gen_range(1..=100);
data.push(val);
}
data.push(SINGLE_ITEM);

10
columnar/src/block_accessor.rs
View File

@@ -29,20 +29,12 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
}
}
#[inline]
pub fn fetch_block_with_missing(
&mut self,
docs: &[u32],
accessor: &Column<T>,
missing: Option<T>,
) {
pub fn fetch_block_with_missing(&mut self, docs: &[u32], accessor: &Column<T>, missing: T) {
self.fetch_block(docs, accessor);
// no missing values
if accessor.index.get_cardinality().is_full() {
return;
}
let Some(missing) = missing else {
return;
};
// We can compare docid_cache length with docs to find missing docs
// For multi value columns we can't rely on the length and always need to scan

4
columnar/src/column/mod.rs
View File

@@ -85,8 +85,8 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
}
#[inline]
pub fn first(&self, doc_id: DocId) -> Option<T> {
self.values_for_doc(doc_id).next()
pub fn first(&self, row_id: RowId) -> Option<T> {
self.values_for_doc(row_id).next()
}
/// Load the first value for each docid in the provided slice.

6
columnar/src/column_values/u64_based/bitpacked.rs
View File

@@ -41,6 +41,12 @@ fn transform_range_before_linear_transformation(
if range.is_empty() {
return None;
}
if stats.min_value > *range.end() {
return None;
}
if stats.max_value < *range.start() {
return None;
}
let shifted_range =
range.start().saturating_sub(stats.min_value)..=range.end().saturating_sub(stats.min_value);
let start_before_gcd_multiplication: u64 = div_ceil(*shifted_range.start(), stats.gcd);

2
columnar/src/column_values/u64_based/linear.rs
View File

@@ -268,7 +268,7 @@ mod tests {
#[test]
fn linear_interpol_fast_field_rand() {
let mut rng = rand::rng();
let mut rng = rand::thread_rng();
for _ in 0..50 {
let mut data = (0..10_000).map(|_| rng.next_u64()).collect::<Vec<_>>();
create_and_validate::<LinearCodec>(&data, "random");

2
columnar/src/column_values/u64_based/tests.rs
View File

@@ -122,7 +122,7 @@ pub(crate) fn create_and_validate<TColumnCodec: ColumnCodec>(
assert_eq!(vals, buffer);
if !vals.is_empty() {
let test_rand_idx = rand::rng().random_range(0..=vals.len() - 1);
let test_rand_idx = rand::thread_rng().gen_range(0..=vals.len() - 1);
let expected_positions: Vec<u32> = vals
.iter()
.enumerate()

84
columnar/src/dynamic_column.rs
View File

@@ -3,8 +3,7 @@ use std::sync::Arc;
use std::{fmt, io};
use common::file_slice::FileSlice;
use common::{ByteCount, DateTime, OwnedBytes};
use serde::{Deserialize, Serialize};
use common::{ByteCount, DateTime, HasLen, OwnedBytes};
use crate::column::{BytesColumn, Column, StrColumn};
use crate::column_values::{StrictlyMonotonicFn, monotonic_map_column};
@@ -318,89 +317,10 @@ impl DynamicColumnHandle {
}
pub fn num_bytes(&self) -> ByteCount {
self.file_slice.num_bytes()
}
/// Legacy helper returning the column space usage.
pub fn column_and_dictionary_num_bytes(&self) -> io::Result<ColumnSpaceUsage> {
self.space_usage()
}
/// Return the space usage of the column, optionally broken down by dictionary and column
/// values.
///
/// For dictionary encoded columns (strings and bytes), this splits the total footprint into
/// the dictionary and the remaining column data (including index and values).
/// For all other column types, the dictionary size is `None` and the column size
/// equals the total bytes.
pub fn space_usage(&self) -> io::Result<ColumnSpaceUsage> {
let total_num_bytes = self.num_bytes();
let dynamic_column = self.open()?;
let dictionary_num_bytes = match &dynamic_column {
DynamicColumn::Bytes(bytes_column) => bytes_column.dictionary().num_bytes(),
DynamicColumn::Str(str_column) => str_column.dictionary().num_bytes(),
_ => {
return Ok(ColumnSpaceUsage::new(self.num_bytes(), None));
}
};
assert!(dictionary_num_bytes <= total_num_bytes);
let column_num_bytes =
ByteCount::from(total_num_bytes.get_bytes() - dictionary_num_bytes.get_bytes());
Ok(ColumnSpaceUsage::new(
column_num_bytes,
Some(dictionary_num_bytes),
))
self.file_slice.len().into()
}
pub fn column_type(&self) -> ColumnType {
self.column_type
}
}
/// Represents space usage of a column.
///
/// `column_num_bytes` tracks the column payload (index, values and footer).
/// For dictionary encoded columns, `dictionary_num_bytes` captures the dictionary footprint.
/// [`ColumnSpaceUsage::total_num_bytes`] returns the sum of both parts.
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct ColumnSpaceUsage {
column_num_bytes: ByteCount,
dictionary_num_bytes: Option<ByteCount>,
}
impl ColumnSpaceUsage {
pub(crate) fn new(
column_num_bytes: ByteCount,
dictionary_num_bytes: Option<ByteCount>,
) -> Self {
ColumnSpaceUsage {
column_num_bytes,
dictionary_num_bytes,
}
}
pub fn column_num_bytes(&self) -> ByteCount {
self.column_num_bytes
}
pub fn dictionary_num_bytes(&self) -> Option<ByteCount> {
self.dictionary_num_bytes
}
pub fn total_num_bytes(&self) -> ByteCount {
self.column_num_bytes + self.dictionary_num_bytes.unwrap_or_default()
}
/// Merge two space usage values by summing their components.
pub fn merge(&self, other: &ColumnSpaceUsage) -> ColumnSpaceUsage {
let dictionary_num_bytes = match (self.dictionary_num_bytes, other.dictionary_num_bytes) {
(Some(lhs), Some(rhs)) => Some(lhs + rhs),
(Some(val), None) | (None, Some(val)) => Some(val),
(None, None) => None,
};
ColumnSpaceUsage {
column_num_bytes: self.column_num_bytes + other.column_num_bytes,
dictionary_num_bytes,
}
}
}

2
columnar/src/lib.rs
View File

@@ -48,7 +48,7 @@ pub use columnar::{
use sstable::VoidSSTable;
pub use value::{NumericalType, NumericalValue};
pub use self::dynamic_column::{ColumnSpaceUsage, DynamicColumn, DynamicColumnHandle};
pub use self::dynamic_column::{DynamicColumn, DynamicColumnHandle};
pub type RowId = u32;
pub type DocId = u32;

8
columnar/src/tests.rs
View File

@@ -60,7 +60,7 @@ fn test_dataframe_writer_bool() {
let DynamicColumn::Bool(bool_col) = dyn_bool_col else {
panic!();
};
let vals: Vec<Option<bool>> = (0..5).map(|doc_id| bool_col.first(doc_id)).collect();
let vals: Vec<Option<bool>> = (0..5).map(|row_id| bool_col.first(row_id)).collect();
assert_eq!(&vals, &[None, Some(false), None, Some(true), None,]);
}
@@ -108,7 +108,7 @@ fn test_dataframe_writer_ip_addr() {
let DynamicColumn::IpAddr(ip_col) = dyn_bool_col else {
panic!();
};
let vals: Vec<Option<Ipv6Addr>> = (0..5).map(|doc_id| ip_col.first(doc_id)).collect();
let vals: Vec<Option<Ipv6Addr>> = (0..5).map(|row_id| ip_col.first(row_id)).collect();
assert_eq!(
&vals,
&[
@@ -169,7 +169,7 @@ fn test_dictionary_encoded_str() {
let DynamicColumn::Str(str_col) = col_handles[0].open().unwrap() else {
panic!();
};
let index: Vec<Option<u64>> = (0..5).map(|doc_id| str_col.ords().first(doc_id)).collect();
let index: Vec<Option<u64>> = (0..5).map(|row_id| str_col.ords().first(row_id)).collect();
assert_eq!(index, &[None, Some(0), None, Some(2), Some(1)]);
assert_eq!(str_col.num_rows(), 5);
let mut term_buffer = String::new();
@@ -204,7 +204,7 @@ fn test_dictionary_encoded_bytes() {
panic!();
};
let index: Vec<Option<u64>> = (0..5)
.map(|doc_id| bytes_col.ords().first(doc_id))
.map(|row_id| bytes_col.ords().first(row_id))
.collect();
assert_eq!(index, &[None, Some(0), None, Some(2), Some(1)]);
assert_eq!(bytes_col.num_rows(), 5);

2
common/Cargo.toml
View File

@@ -21,5 +21,5 @@ serde = { version = "1.0.136", features = ["derive"] }
[dev-dependencies]
binggan = "0.14.0"
proptest = "1.0.0"
rand = "0.9"
rand = "0.8.4"

4
common/benches/bench.rs
View File

@@ -1,6 +1,6 @@
use binggan::{BenchRunner, black_box};
use rand::rng;
use rand::seq::IteratorRandom;
use rand::thread_rng;
use tantivy_common::{BitSet, TinySet, serialize_vint_u32};
fn bench_vint() {
@@ -17,7 +17,7 @@ fn bench_vint() {
black_box(out);
});
let vals: Vec<u32> = (0..20_000).choose_multiple(&mut rng(), 100_000);
let vals: Vec<u32> = (0..20_000).choose_multiple(&mut thread_rng(), 100_000);
runner.bench_function("bench_vint_rand", move |_| {
let mut out = 0u64;
for val in vals.iter().cloned() {

10
common/src/bitset.rs
View File

@@ -181,14 +181,6 @@ pub struct BitSet {
len: u64,
max_value: u32,
}
impl std::fmt::Debug for BitSet {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
f.debug_struct("BitSet")
.field("len", &self.len)
.field("max_value", &self.max_value)
.finish()
}
}
fn num_buckets(max_val: u32) -> u32 {
max_val.div_ceil(64u32)
@@ -416,7 +408,7 @@ mod tests {
use std::collections::HashSet;
use ownedbytes::OwnedBytes;
use rand::distr::Bernoulli;
use rand::distributions::Bernoulli;
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};

4
doc/src/json.md
View File

@@ -60,7 +60,7 @@ At indexing, tantivy will try to interpret number and strings as different type
priority order.
Numbers will be interpreted as u64, i64 and f64 in that order.
Strings will be interpreted as rfc3339 dates or simple strings.
Strings will be interpreted as rfc3999 dates or simple strings.
The first working type is picked and is the only term that is emitted for indexing.
Note this interpretation happens on a per-document basis, and there is no effort to try to sniff
@@ -81,7 +81,7 @@ Will be interpreted as
(my_path.my_segment, String, 233) or (my_path.my_segment, u64, 233)
```
Likewise, we need to emit two tokens if the query contains an rfc3339 date.
Likewise, we need to emit two tokens if the query contains an rfc3999 date.
Indeed the date could have been actually a single token inside the text of a document at ingestion time. Generally speaking, we will always at least emit a string token in query parsing, and sometimes more.
If one more json field is defined, things get even more complicated.

66
examples/geo_json.rs Normal file
View File

@@ -0,0 +1,66 @@
use geo_types::Point;
use tantivy::collector::TopDocs;
use tantivy::query::SpatialQuery;
use tantivy::schema::{Schema, Value, SPATIAL, STORED, TEXT};
use tantivy::spatial::point::GeoPoint;
use tantivy::{Index, IndexWriter, TantivyDocument};
fn main() -> tantivy::Result<()> {
let mut schema_builder = Schema::builder();
schema_builder.add_json_field("properties", STORED | TEXT);
schema_builder.add_spatial_field("geometry", STORED | SPATIAL);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let doc = TantivyDocument::parse_json(
&schema,
r#"{
"type":"Feature",
"geometry":{
"type":"Polygon",
"coordinates":[[[-99.483911,45.577697],[-99.483869,45.571457],[-99.481739,45.571461],[-99.474881,45.571584],[-99.473167,45.571615],[-99.463394,45.57168],[-99.463391,45.57883],[-99.463368,45.586076],[-99.48177,45.585926],[-99.48384,45.585953],[-99.483885,45.57873],[-99.483911,45.577697]]]
},
"properties":{
"admin_level":"8",
"border_type":"city",
"boundary":"administrative",
"gnis:feature_id":"1267426",
"name":"Hosmer",
"place":"city",
"source":"TIGER/Line® 2008 Place Shapefiles (http://www.census.gov/geo/www/tiger/)",
"wikidata":"Q2442118",
"wikipedia":"en:Hosmer, South Dakota"
}
}"#,
)?;
index_writer.add_document(doc)?;
index_writer.commit()?;
let reader = index.reader()?;
let searcher = reader.searcher();
let field = schema.get_field("geometry").unwrap();
let query = SpatialQuery::new(
field,
[
GeoPoint {
lon: -99.49,
lat: 45.56,
},
GeoPoint {
lon: -99.45,
lat: 45.59,
},
],
tantivy::query::SpatialQueryType::Intersects,
);
let hits = searcher.search(&query, &TopDocs::with_limit(10).order_by_score())?;
for (_score, doc_address) in &hits {
let retrieved_doc: TantivyDocument = searcher.doc(*doc_address)?;
if let Some(field_value) = retrieved_doc.get_first(field) {
if let Some(geometry_box) = field_value.as_value().into_geometry() {
println!("Retrieved geometry: {:?}", geometry_box);
}
}
}
assert_eq!(hits.len(), 1);
Ok(())
}

16
query-grammar/src/query_grammar.rs
View File

@@ -560,7 +560,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
(
(
value((), tag(">=")),
map(word_infallible(")", false), |(bound, err)| {
map(word_infallible("", false), |(bound, err)| {
(
(
bound
@@ -574,7 +574,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
),
(
value((), tag("<=")),
map(word_infallible(")", false), |(bound, err)| {
map(word_infallible("", false), |(bound, err)| {
(
(
UserInputBound::Unbounded,
@@ -588,7 +588,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
),
(
value((), tag(">")),
map(word_infallible(")", false), |(bound, err)| {
map(word_infallible("", false), |(bound, err)| {
(
(
bound
@@ -602,7 +602,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
),
(
value((), tag("<")),
map(word_infallible(")", false), |(bound, err)| {
map(word_infallible("", false), |(bound, err)| {
(
(
UserInputBound::Unbounded,
@@ -1323,14 +1323,6 @@ mod test {
test_parse_query_to_ast_helper("<a", "{\"*\" TO \"a\"}");
test_parse_query_to_ast_helper("<=a", "{\"*\" TO \"a\"]");
test_parse_query_to_ast_helper("<=bsd", "{\"*\" TO \"bsd\"]");
test_parse_query_to_ast_helper("(<=42)", "{\"*\" TO \"42\"]");
test_parse_query_to_ast_helper("(<=42 )", "{\"*\" TO \"42\"]");
test_parse_query_to_ast_helper("(age:>5)", "\"age\":{\"5\" TO \"*\"}");
test_parse_query_to_ast_helper(
"(title:bar AND age:>12)",
"(+\"title\":bar +\"age\":{\"12\" TO \"*\"})",
);
}
#[test]

113
src/aggregation/agg_data.rs
View File

@@ -1,4 +1,4 @@
use columnar::{Column, ColumnBlockAccessor, ColumnType, StrColumn};
use columnar::{Column, ColumnType, StrColumn};
use common::BitSet;
use rustc_hash::FxHashSet;
use serde::Serialize;
@@ -10,16 +10,16 @@ use crate::aggregation::accessor_helpers::{
};
use crate::aggregation::agg_req::{Aggregation, AggregationVariants, Aggregations};
use crate::aggregation::bucket::{
build_segment_filter_collector, build_segment_range_collector, FilterAggReqData,
HistogramAggReqData, HistogramBounds, IncludeExcludeParam, MissingTermAggReqData,
RangeAggReqData, SegmentHistogramCollector, TermMissingAgg, TermsAggReqData, TermsAggregation,
FilterAggReqData, HistogramAggReqData, HistogramBounds, IncludeExcludeParam,
MissingTermAggReqData, RangeAggReqData, SegmentFilterCollector, SegmentHistogramCollector,
SegmentRangeCollector, TermMissingAgg, TermsAggReqData, TermsAggregation,
TermsAggregationInternal,
};
use crate::aggregation::metric::{
build_segment_stats_collector, AverageAggregation, CardinalityAggReqData,
CardinalityAggregationReq, CountAggregation, ExtendedStatsAggregation, MaxAggregation,
MetricAggReqData, MinAggregation, SegmentCardinalityCollector, SegmentExtendedStatsCollector,
SegmentPercentilesCollector, StatsAggregation, StatsType, SumAggregation, TopHitsAggReqData,
AverageAggregation, CardinalityAggReqData, CardinalityAggregationReq, CountAggregation,
ExtendedStatsAggregation, MaxAggregation, MetricAggReqData, MinAggregation,
SegmentCardinalityCollector, SegmentExtendedStatsCollector, SegmentPercentilesCollector,
SegmentStatsCollector, StatsAggregation, StatsType, SumAggregation, TopHitsAggReqData,
TopHitsSegmentCollector,
};
use crate::aggregation::segment_agg_result::{
@@ -35,7 +35,6 @@ pub struct AggregationsSegmentCtx {
/// Request data for each aggregation type.
pub per_request: PerRequestAggSegCtx,
pub context: AggContextParams,
pub column_block_accessor: ColumnBlockAccessor<u64>,
}
impl AggregationsSegmentCtx {
@@ -108,14 +107,21 @@ impl AggregationsSegmentCtx {
.as_deref()
.expect("range_req_data slot is empty (taken)")
}
#[inline]
pub(crate) fn get_filter_req_data(&self, idx: usize) -> &FilterAggReqData {
self.per_request.filter_req_data[idx]
.as_deref()
.expect("filter_req_data slot is empty (taken)")
}
// ---------- mutable getters ----------
#[inline]
pub(crate) fn get_metric_req_data_mut(&mut self, idx: usize) -> &mut MetricAggReqData {
&mut self.per_request.stats_metric_req_data[idx]
pub(crate) fn get_term_req_data_mut(&mut self, idx: usize) -> &mut TermsAggReqData {
self.per_request.term_req_data[idx]
.as_deref_mut()
.expect("term_req_data slot is empty (taken)")
}
#[inline]
pub(crate) fn get_cardinality_req_data_mut(
&mut self,
@@ -123,7 +129,10 @@ impl AggregationsSegmentCtx {
) -> &mut CardinalityAggReqData {
&mut self.per_request.cardinality_req_data[idx]
}
#[inline]
pub(crate) fn get_metric_req_data_mut(&mut self, idx: usize) -> &mut MetricAggReqData {
&mut self.per_request.stats_metric_req_data[idx]
}
#[inline]
pub(crate) fn get_histogram_req_data_mut(&mut self, idx: usize) -> &mut HistogramAggReqData {
self.per_request.histogram_req_data[idx]
@@ -133,6 +142,21 @@ impl AggregationsSegmentCtx {
// ---------- take / put (terms, histogram, range) ----------
/// Move out the boxed Terms request at `idx`, leaving `None`.
#[inline]
pub(crate) fn take_term_req_data(&mut self, idx: usize) -> Box<TermsAggReqData> {
self.per_request.term_req_data[idx]
.take()
.expect("term_req_data slot is empty (taken)")
}
/// Put back a Terms request into an empty slot at `idx`.
#[inline]
pub(crate) fn put_back_term_req_data(&mut self, idx: usize, value: Box<TermsAggReqData>) {
debug_assert!(self.per_request.term_req_data[idx].is_none());
self.per_request.term_req_data[idx] = Some(value);
}
/// Move out the boxed Histogram request at `idx`, leaving `None`.
#[inline]
pub(crate) fn take_histogram_req_data(&mut self, idx: usize) -> Box<HistogramAggReqData> {
@@ -296,7 +320,6 @@ impl PerRequestAggSegCtx {
/// Convert the aggregation tree into a serializable struct representation.
/// Each node contains: { name, kind, children }.
#[allow(dead_code)]
pub fn get_view_tree(&self) -> Vec<AggTreeViewNode> {
fn node_to_view(node: &AggRefNode, pr: &PerRequestAggSegCtx) -> AggTreeViewNode {
let mut children: Vec<AggTreeViewNode> =
@@ -322,19 +345,12 @@ impl PerRequestAggSegCtx {
pub(crate) fn build_segment_agg_collectors_root(
req: &mut AggregationsSegmentCtx,
) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
build_segment_agg_collectors_generic(req, &req.per_request.agg_tree.clone())
build_segment_agg_collectors(req, &req.per_request.agg_tree.clone())
}
pub(crate) fn build_segment_agg_collectors(
req: &mut AggregationsSegmentCtx,
nodes: &[AggRefNode],
) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
build_segment_agg_collectors_generic(req, nodes)
}
fn build_segment_agg_collectors_generic(
req: &mut AggregationsSegmentCtx,
nodes: &[AggRefNode],
) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
let mut collectors = Vec::new();
for node in nodes.iter() {
@@ -372,8 +388,6 @@ pub(crate) fn build_segment_agg_collector(
Ok(Box::new(SegmentCardinalityCollector::from_req(
req_data.column_type,
node.idx_in_req_data,
req_data.accessor.clone(),
req_data.missing_value_for_accessor,
)))
}
AggKind::StatsKind(stats_type) => {
@@ -384,21 +398,20 @@ pub(crate) fn build_segment_agg_collector(
| StatsType::Count
| StatsType::Max
| StatsType::Min
| StatsType::Stats => build_segment_stats_collector(req_data),
StatsType::ExtendedStats(sigma) => Ok(Box::new(
SegmentExtendedStatsCollector::from_req(req_data, sigma),
)),
StatsType::Percentiles => {
let req_data = req.get_metric_req_data_mut(node.idx_in_req_data);
Ok(Box::new(
SegmentPercentilesCollector::from_req_and_validate(
req_data.field_type,
req_data.missing_u64,
req_data.accessor.clone(),
node.idx_in_req_data,
),
))
| StatsType::Stats => Ok(Box::new(SegmentStatsCollector::from_req(
node.idx_in_req_data,
))),
StatsType::ExtendedStats(sigma) => {
Ok(Box::new(SegmentExtendedStatsCollector::from_req(
req_data.field_type,
sigma,
node.idx_in_req_data,
req_data.missing,
)))
}
StatsType::Percentiles => Ok(Box::new(
SegmentPercentilesCollector::from_req_and_validate(node.idx_in_req_data)?,
)),
}
}
AggKind::TopHits => {
@@ -415,8 +428,12 @@ pub(crate) fn build_segment_agg_collector(
AggKind::DateHistogram => Ok(Box::new(SegmentHistogramCollector::from_req_and_validate(
req, node,
)?)),
AggKind::Range => Ok(build_segment_range_collector(req, node)?),
AggKind::Filter => build_segment_filter_collector(req, node),
AggKind::Range => Ok(Box::new(SegmentRangeCollector::from_req_and_validate(
req, node,
)?)),
AggKind::Filter => Ok(Box::new(SegmentFilterCollector::from_req_and_validate(
req, node,
)?)),
}
}
@@ -476,7 +493,6 @@ pub(crate) fn build_aggregations_data_from_req(
let mut data = AggregationsSegmentCtx {
per_request: Default::default(),
context,
column_block_accessor: ColumnBlockAccessor::default(),
};
for (name, agg) in aggs.iter() {
@@ -505,9 +521,9 @@ fn build_nodes(
let idx_in_req_data = data.push_range_req_data(RangeAggReqData {
accessor,
field_type,
column_block_accessor: Default::default(),
name: agg_name.to_string(),
req: range_req.clone(),
is_top_level,
});
let children = build_children(&req.sub_aggregation, reader, segment_ordinal, data)?;
Ok(vec![AggRefNode {
@@ -525,7 +541,9 @@ fn build_nodes(
let idx_in_req_data = data.push_histogram_req_data(HistogramAggReqData {
accessor,
field_type,
column_block_accessor: Default::default(),
name: agg_name.to_string(),
sub_aggregation_blueprint: None,
req: histo_req.clone(),
is_date_histogram: false,
bounds: HistogramBounds {
@@ -550,7 +568,9 @@ fn build_nodes(
let idx_in_req_data = data.push_histogram_req_data(HistogramAggReqData {
accessor,
field_type,
column_block_accessor: Default::default(),
name: agg_name.to_string(),
sub_aggregation_blueprint: None,
req: histo_req,
is_date_histogram: true,
bounds: HistogramBounds {
@@ -630,6 +650,7 @@ fn build_nodes(
let idx_in_req_data = data.push_metric_req_data(MetricAggReqData {
accessor,
field_type,
column_block_accessor: Default::default(),
name: agg_name.to_string(),
collecting_for,
missing: *missing,
@@ -657,6 +678,7 @@ fn build_nodes(
let idx_in_req_data = data.push_metric_req_data(MetricAggReqData {
accessor,
field_type,
column_block_accessor: Default::default(),
name: agg_name.to_string(),
collecting_for: StatsType::Percentiles,
missing: percentiles_req.missing,
@@ -731,7 +753,6 @@ fn build_nodes(
segment_reader: reader.clone(),
evaluator,
matching_docs_buffer,
is_top_level,
});
let children = build_children(&req.sub_aggregation, reader, segment_ordinal, data)?;
Ok(vec![AggRefNode {
@@ -874,7 +895,7 @@ fn build_terms_or_cardinality_nodes(
});
}
// Add one node per accessor
// Add one node per accessor to mirror previous behavior and allow per-type missing handling.
for (accessor, column_type) in column_and_types {
let missing_value_for_accessor = if use_special_missing_agg {
None
@@ -905,8 +926,11 @@ fn build_terms_or_cardinality_nodes(
column_type,
str_dict_column: str_dict_column.clone(),
missing_value_for_accessor,
column_block_accessor: Default::default(),
name: agg_name.to_string(),
req: TermsAggregationInternal::from_req(req),
// Will be filled later when building collectors
sub_aggregation_blueprint: None,
sug_aggregations: sub_aggs.clone(),
allowed_term_ids,
is_top_level,
@@ -919,6 +943,7 @@ fn build_terms_or_cardinality_nodes(
column_type,
str_dict_column: str_dict_column.clone(),
missing_value_for_accessor,
column_block_accessor: Default::default(),
name: agg_name.to_string(),
req: req.clone(),
});

13
src/aggregation/agg_result.rs
View File

@@ -10,8 +10,7 @@ use serde::{Deserialize, Serialize};
use super::bucket::GetDocCount;
use super::metric::{
AverageMetricResult, CardinalityMetricResult, ExtendedStats, PercentilesMetricResult,
SingleMetricResult, Stats, TopHitsMetricResult,
ExtendedStats, PercentilesMetricResult, SingleMetricResult, Stats, TopHitsMetricResult,
};
use super::{AggregationError, Key};
use crate::TantivyError;
@@ -82,8 +81,8 @@ impl AggregationResult {
#[serde(untagged)]
/// MetricResult
pub enum MetricResult {
/// Average metric result with sum and count for multi-step merging.
Average(AverageMetricResult),
/// Average metric result.
Average(SingleMetricResult),
/// Count metric result.
Count(SingleMetricResult),
/// Max metric result.
@@ -100,8 +99,8 @@ pub enum MetricResult {
Percentiles(PercentilesMetricResult),
/// Top hits metric result
TopHits(TopHitsMetricResult),
/// Cardinality metric result with HLL sketch for multi-step merging.
Cardinality(CardinalityMetricResult),
/// Cardinality metric result
Cardinality(SingleMetricResult),
}
impl MetricResult {
@@ -120,7 +119,7 @@ impl MetricResult {
MetricResult::TopHits(_) => Err(TantivyError::AggregationError(
AggregationError::InvalidRequest("top_hits can't be used to order".to_string()),
)),
MetricResult::Cardinality(card) => Ok(card.value), // CardinalityMetricResult.value
MetricResult::Cardinality(card) => Ok(card.value),
}
}
}

445
src/aggregation/agg_tests.rs
View File

@@ -2,441 +2,15 @@ use serde_json::Value;
use crate::aggregation::agg_req::{Aggregation, Aggregations};
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::buf_collector::DOC_BLOCK_SIZE;
use crate::aggregation::collector::AggregationCollector;
use crate::aggregation::intermediate_agg_result::IntermediateAggregationResults;
use crate::aggregation::tests::{get_test_index_2_segments, get_test_index_from_values_and_terms};
use crate::aggregation::DistributedAggregationCollector;
use crate::docset::COLLECT_BLOCK_BUFFER_LEN;
use crate::query::{AllQuery, TermQuery};
use crate::schema::{IndexRecordOption, Schema, FAST};
use crate::{Index, IndexWriter, Term};
// The following tests ensure that each bucket aggregation type correctly functions as a
// sub-aggregation of another bucket aggregation in two scenarios:
// 1) The parent has more buckets than the child sub-aggregation
// 2) The child sub-aggregation has more buckets than the parent
//
// These scenarios exercise the bucket id mapping and sub-aggregation routing logic.
#[test]
fn test_terms_as_subagg_parent_more_vs_child_more() -> crate::Result<()> {
let index = get_test_index_2_segments(false)?;
// Case A: parent has more buckets than child
// Parent: range with 4 buckets
// Child: terms on text -> 2 buckets
let agg_parent_more: Aggregations = serde_json::from_value(json!({
"parent_range": {
"range": {
"field": "score",
"ranges": [
{"to": 3.0},
{"from": 3.0, "to": 7.0},
{"from": 7.0, "to": 20.0},
{"from": 20.0}
]
},
"aggs": {
"child_terms": {"terms": {"field": "text", "order": {"_key": "asc"}}}
}
}
}))
.unwrap();
let res = crate::aggregation::tests::exec_request(agg_parent_more, &index)?;
// Exact expected structure and counts
assert_eq!(
res["parent_range"]["buckets"],
json!([
{
"key": "*-3",
"doc_count": 1,
"to": 3.0,
"child_terms": {
"buckets": [
{"doc_count": 1, "key": "cool"}
],
"sum_other_doc_count": 0
}
},
{
"key": "3-7",
"doc_count": 3,
"from": 3.0,
"to": 7.0,
"child_terms": {
"buckets": [
{"doc_count": 2, "key": "cool"},
{"doc_count": 1, "key": "nohit"}
],
"sum_other_doc_count": 0
}
},
{
"key": "7-20",
"doc_count": 3,
"from": 7.0,
"to": 20.0,
"child_terms": {
"buckets": [
{"doc_count": 3, "key": "cool"}
],
"sum_other_doc_count": 0
}
},
{
"key": "20-*",
"doc_count": 2,
"from": 20.0,
"child_terms": {
"buckets": [
{"doc_count": 1, "key": "cool"},
{"doc_count": 1, "key": "nohit"}
],
"sum_other_doc_count": 0
}
}
])
);
// Case B: child has more buckets than parent
// Parent: histogram on score with large interval -> 1 bucket
// Child: terms on text -> 2 buckets (cool/nohit)
let agg_child_more: Aggregations = serde_json::from_value(json!({
"parent_hist": {
"histogram": {"field": "score", "interval": 100.0},
"aggs": {
"child_terms": {"terms": {"field": "text", "order": {"_key": "asc"}}}
}
}
}))
.unwrap();
let res = crate::aggregation::tests::exec_request(agg_child_more, &index)?;
assert_eq!(
res["parent_hist"],
json!({
"buckets": [
{
"key": 0.0,
"doc_count": 9,
"child_terms": {
"buckets": [
{"doc_count": 7, "key": "cool"},
{"doc_count": 2, "key": "nohit"}
],
"sum_other_doc_count": 0
}
}
]
})
);
Ok(())
}
#[test]
fn test_range_as_subagg_parent_more_vs_child_more() -> crate::Result<()> {
let index = get_test_index_2_segments(false)?;
// Case A: parent has more buckets than child
// Parent: range with 5 buckets
// Child: coarse range with 3 buckets
let agg_parent_more: Aggregations = serde_json::from_value(json!({
"parent_range": {
"range": {
"field": "score",
"ranges": [
{"to": 3.0},
{"from": 3.0, "to": 7.0},
{"from": 7.0, "to": 11.0},
{"from": 11.0, "to": 20.0},
{"from": 20.0}
]
},
"aggs": {
"child_range": {
"range": {
"field": "score",
"ranges": [
{"to": 3.0},
{"from": 3.0, "to": 20.0}
]
}
}
}
}
}))
.unwrap();
let res = crate::aggregation::tests::exec_request(agg_parent_more, &index)?;
assert_eq!(
res["parent_range"]["buckets"],
json!([
{"key": "*-3", "doc_count": 1, "to": 3.0,
"child_range": {"buckets": [
{"key": "*-3", "doc_count": 1, "to": 3.0},
{"key": "3-20", "doc_count": 0, "from": 3.0, "to": 20.0},
{"key": "20-*", "doc_count": 0, "from": 20.0}
]}
},
{"key": "3-7", "doc_count": 3, "from": 3.0, "to": 7.0,
"child_range": {"buckets": [
{"key": "*-3", "doc_count": 0, "to": 3.0},
{"key": "3-20", "doc_count": 3, "from": 3.0, "to": 20.0},
{"key": "20-*", "doc_count": 0, "from": 20.0}
]}
},
{"key": "7-11", "doc_count": 1, "from": 7.0, "to": 11.0,
"child_range": {"buckets": [
{"key": "*-3", "doc_count": 0, "to": 3.0},
{"key": "3-20", "doc_count": 1, "from": 3.0, "to": 20.0},
{"key": "20-*", "doc_count": 0, "from": 20.0}
]}
},
{"key": "11-20", "doc_count": 2, "from": 11.0, "to": 20.0,
"child_range": {"buckets": [
{"key": "*-3", "doc_count": 0, "to": 3.0},
{"key": "3-20", "doc_count": 2, "from": 3.0, "to": 20.0},
{"key": "20-*", "doc_count": 0, "from": 20.0}
]}
},
{"key": "20-*", "doc_count": 2, "from": 20.0,
"child_range": {"buckets": [
{"key": "*-3", "doc_count": 0, "to": 3.0},
{"key": "3-20", "doc_count": 0, "from": 3.0, "to": 20.0},
{"key": "20-*", "doc_count": 2, "from": 20.0}
]}
}
])
);
// Case B: child has more buckets than parent
// Parent: terms on text (2 buckets)
// Child: range with 4 buckets
let agg_child_more: Aggregations = serde_json::from_value(json!({
"parent_terms": {
"terms": {"field": "text"},
"aggs": {
"child_range": {
"range": {
"field": "score",
"ranges": [
{"to": 3.0},
{"from": 3.0, "to": 7.0},
{"from": 7.0, "to": 20.0}
]
}
}
}
}
}))
.unwrap();
let res = crate::aggregation::tests::exec_request(agg_child_more, &index)?;
assert_eq!(
res["parent_terms"],
json!({
"buckets": [
{
"key": "cool",
"doc_count": 7,
"child_range": {
"buckets": [
{"key": "*-3", "doc_count": 1, "to": 3.0},
{"key": "3-7", "doc_count": 2, "from": 3.0, "to": 7.0},
{"key": "7-20", "doc_count": 3, "from": 7.0, "to": 20.0},
{"key": "20-*", "doc_count": 1, "from": 20.0}
]
}
},
{
"key": "nohit",
"doc_count": 2,
"child_range": {
"buckets": [
{"key": "*-3", "doc_count": 0, "to": 3.0},
{"key": "3-7", "doc_count": 1, "from": 3.0, "to": 7.0},
{"key": "7-20", "doc_count": 0, "from": 7.0, "to": 20.0},
{"key": "20-*", "doc_count": 1, "from": 20.0}
]
}
}
],
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0
})
);
Ok(())
}
#[test]
fn test_histogram_as_subagg_parent_more_vs_child_more() -> crate::Result<()> {
let index = get_test_index_2_segments(false)?;
// Case A: parent has more buckets than child
// Parent: range with several ranges
// Child: histogram with large interval (single bucket per parent)
let agg_parent_more: Aggregations = serde_json::from_value(json!({
"parent_range": {
"range": {
"field": "score",
"ranges": [
{"to": 3.0},
{"from": 3.0, "to": 7.0},
{"from": 7.0, "to": 11.0},
{"from": 11.0, "to": 20.0},
{"from": 20.0}
]
},
"aggs": {
"child_hist": {"histogram": {"field": "score", "interval": 100.0}}
}
}
}))
.unwrap();
let res = crate::aggregation::tests::exec_request(agg_parent_more, &index)?;
assert_eq!(
res["parent_range"]["buckets"],
json!([
{"key": "*-3", "doc_count": 1, "to": 3.0,
"child_hist": {"buckets": [ {"key": 0.0, "doc_count": 1} ]}
},
{"key": "3-7", "doc_count": 3, "from": 3.0, "to": 7.0,
"child_hist": {"buckets": [ {"key": 0.0, "doc_count": 3} ]}
},
{"key": "7-11", "doc_count": 1, "from": 7.0, "to": 11.0,
"child_hist": {"buckets": [ {"key": 0.0, "doc_count": 1} ]}
},
{"key": "11-20", "doc_count": 2, "from": 11.0, "to": 20.0,
"child_hist": {"buckets": [ {"key": 0.0, "doc_count": 2} ]}
},
{"key": "20-*", "doc_count": 2, "from": 20.0,
"child_hist": {"buckets": [ {"key": 0.0, "doc_count": 2} ]}
}
])
);
// Case B: child has more buckets than parent
// Parent: terms on text -> 2 buckets
// Child: histogram with small interval -> multiple buckets including empties
let agg_child_more: Aggregations = serde_json::from_value(json!({
"parent_terms": {
"terms": {"field": "text"},
"aggs": {
"child_hist": {"histogram": {"field": "score", "interval": 10.0}}
}
}
}))
.unwrap();
let res = crate::aggregation::tests::exec_request(agg_child_more, &index)?;
assert_eq!(
res["parent_terms"],
json!({
"buckets": [
{
"key": "cool",
"doc_count": 7,
"child_hist": {
"buckets": [
{"key": 0.0, "doc_count": 4},
{"key": 10.0, "doc_count": 2},
{"key": 20.0, "doc_count": 0},
{"key": 30.0, "doc_count": 0},
{"key": 40.0, "doc_count": 1}
]
}
},
{
"key": "nohit",
"doc_count": 2,
"child_hist": {
"buckets": [
{"key": 0.0, "doc_count": 1},
{"key": 10.0, "doc_count": 0},
{"key": 20.0, "doc_count": 0},
{"key": 30.0, "doc_count": 0},
{"key": 40.0, "doc_count": 1}
]
}
}
],
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0
})
);
Ok(())
}
#[test]
fn test_date_histogram_as_subagg_parent_more_vs_child_more() -> crate::Result<()> {
let index = get_test_index_2_segments(false)?;
// Case A: parent has more buckets than child
// Parent: range with several buckets
// Child: date_histogram with 30d -> single bucket per parent
let agg_parent_more: Aggregations = serde_json::from_value(json!({
"parent_range": {
"range": {
"field": "score",
"ranges": [
{"to": 3.0},
{"from": 3.0, "to": 7.0},
{"from": 7.0, "to": 11.0},
{"from": 11.0, "to": 20.0},
{"from": 20.0}
]
},
"aggs": {
"child_date_hist": {"date_histogram": {"field": "date", "fixed_interval": "30d"}}
}
}
}))
.unwrap();
let res = crate::aggregation::tests::exec_request(agg_parent_more, &index)?;
let buckets = res["parent_range"]["buckets"].as_array().unwrap();
// Verify each parent bucket has exactly one child date bucket with matching doc_count
for bucket in buckets {
let parent_count = bucket["doc_count"].as_u64().unwrap();
let child_buckets = bucket["child_date_hist"]["buckets"].as_array().unwrap();
assert_eq!(child_buckets.len(), 1);
assert_eq!(child_buckets[0]["doc_count"], parent_count);
}
// Case B: child has more buckets than parent
// Parent: terms on text (2 buckets)
// Child: date_histogram with 1d -> multiple buckets
let agg_child_more: Aggregations = serde_json::from_value(json!({
"parent_terms": {
"terms": {"field": "text"},
"aggs": {
"child_date_hist": {"date_histogram": {"field": "date", "fixed_interval": "1d"}}
}
}
}))
.unwrap();
let res = crate::aggregation::tests::exec_request(agg_child_more, &index)?;
let buckets = res["parent_terms"]["buckets"].as_array().unwrap();
// cool bucket
assert_eq!(buckets[0]["key"], "cool");
let cool_buckets = buckets[0]["child_date_hist"]["buckets"].as_array().unwrap();
assert_eq!(cool_buckets.len(), 3);
assert_eq!(cool_buckets[0]["doc_count"], 1); // day 0
assert_eq!(cool_buckets[1]["doc_count"], 4); // day 1
assert_eq!(cool_buckets[2]["doc_count"], 2); // day 2
// nohit bucket
assert_eq!(buckets[1]["key"], "nohit");
let nohit_buckets = buckets[1]["child_date_hist"]["buckets"].as_array().unwrap();
assert_eq!(nohit_buckets.len(), 2);
assert_eq!(nohit_buckets[0]["doc_count"], 1); // day 1
assert_eq!(nohit_buckets[1]["doc_count"], 1); // day 2
Ok(())
}
fn get_avg_req(field_name: &str) -> Aggregation {
serde_json::from_value(json!({
"avg": {
@@ -451,10 +25,6 @@ fn get_collector(agg_req: Aggregations) -> AggregationCollector {
}
// *** EVERY BUCKET-TYPE SHOULD BE TESTED HERE ***
// Note: The flushng part of these tests are outdated, since the buffering change after converting
// the collection into one collector per request instead of per bucket.
//
// However they are useful as they test a complex aggregation requests.
fn test_aggregation_flushing(
merge_segments: bool,
use_distributed_collector: bool,
@@ -467,9 +37,8 @@ fn test_aggregation_flushing(
let reader = index.reader()?;
assert_eq!(COLLECT_BLOCK_BUFFER_LEN, 64);
// In the tree we cache documents of COLLECT_BLOCK_BUFFER_LEN before passing them down as one
// block.
assert_eq!(DOC_BLOCK_SIZE, 64);
// In the tree we cache Documents of DOC_BLOCK_SIZE, before passing them down as one block.
//
// Build a request so that on the first level we have one full cache, which is then flushed.
// The same cache should have some residue docs at the end, which are flushed (Range 0-70)
@@ -1359,10 +928,10 @@ fn test_aggregation_on_json_object_mixed_types() {
&serde_json::json!({
"rangeagg": {
"buckets": [
{ "average_in_range": { "value": -20.5, "sum": -20.5, "count": 1 }, "doc_count": 1, "key": "*-3", "to": 3.0 },
{ "average_in_range": { "value": 10.0, "sum": 10.0, "count": 1 }, "doc_count": 1, "from": 3.0, "key": "3-19", "to": 19.0 },
{ "average_in_range": { "value": null, "sum": 0.0, "count": 0 }, "doc_count": 0, "from": 19.0, "key": "19-20", "to": 20.0 },
{ "average_in_range": { "value": null, "sum": 0.0, "count": 0 }, "doc_count": 0, "from": 20.0, "key": "20-*" }
{ "average_in_range": { "value": -20.5 }, "doc_count": 1, "key": "*-3", "to": 3.0 },
{ "average_in_range": { "value": 10.0 }, "doc_count": 1, "from": 3.0, "key": "3-19", "to": 19.0 },
{ "average_in_range": { "value": null }, "doc_count": 0, "from": 19.0, "key": "19-20", "to": 20.0 },
{ "average_in_range": { "value": null }, "doc_count": 0, "from": 20.0, "key": "20-*" }
]
},
"termagg": {

174
src/aggregation/bucket/filter.rs
View File

@@ -6,14 +6,10 @@ use serde::{Deserialize, Deserializer, Serialize, Serializer};
use crate::aggregation::agg_data::{
build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
};
use crate::aggregation::cached_sub_aggs::{
CachedSubAggs, HighCardSubAggCache, LowCardSubAggCache, SubAggCache,
};
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
};
use crate::aggregation::segment_agg_result::{BucketIdProvider, SegmentAggregationCollector};
use crate::aggregation::BucketId;
use crate::aggregation::segment_agg_result::{CollectorClone, SegmentAggregationCollector};
use crate::docset::DocSet;
use crate::query::{AllQuery, EnableScoring, Query, QueryParser};
use crate::schema::Schema;
@@ -408,18 +404,15 @@ pub struct FilterAggReqData {
pub evaluator: DocumentQueryEvaluator,
/// Reusable buffer for matching documents to minimize allocations during collection
pub matching_docs_buffer: Vec<DocId>,
/// True if this filter aggregation is at the top level of the aggregation tree (not nested).
pub is_top_level: bool,
}
impl FilterAggReqData {
pub(crate) fn get_memory_consumption(&self) -> usize {
// Estimate: name + segment reader reference + bitset + buffer capacity
self.name.len()
+ std::mem::size_of::<SegmentReader>()
+ self.evaluator.bitset.len() / 8 // BitSet memory (bits to bytes)
+ self.matching_docs_buffer.capacity() * std::mem::size_of::<DocId>()
+ std::mem::size_of::<bool>()
+ std::mem::size_of::<SegmentReader>()
+ self.evaluator.bitset.len() / 8 // BitSet memory (bits to bytes)
+ self.matching_docs_buffer.capacity() * std::mem::size_of::<DocId>()
}
}
@@ -496,24 +489,17 @@ impl Debug for DocumentQueryEvaluator {
}
}
#[derive(Debug, Clone, PartialEq, Copy)]
struct DocCount {
doc_count: u64,
bucket_id: BucketId,
}
/// Segment collector for filter aggregation
pub struct SegmentFilterCollector<C: SubAggCache> {
/// Document counts per parent bucket
parent_buckets: Vec<DocCount>,
pub struct SegmentFilterCollector {
/// Document count in this bucket
doc_count: u64,
/// Sub-aggregation collectors
sub_aggregations: Option<CachedSubAggs<C>>,
bucket_id_provider: BucketIdProvider,
sub_aggregations: Option<Box<dyn SegmentAggregationCollector>>,
/// Accessor index for this filter aggregation (to access FilterAggReqData)
accessor_idx: usize,
}
impl<C: SubAggCache> SegmentFilterCollector<C> {
impl SegmentFilterCollector {
/// Create a new filter segment collector following the new agg_data pattern
pub(crate) fn from_req_and_validate(
req: &mut AggregationsSegmentCtx,
@@ -525,75 +511,47 @@ impl<C: SubAggCache> SegmentFilterCollector<C> {
} else {
None
};
let sub_agg_collector = sub_agg_collector.map(CachedSubAggs::new);
Ok(SegmentFilterCollector {
parent_buckets: Vec::new(),
doc_count: 0,
sub_aggregations: sub_agg_collector,
accessor_idx: node.idx_in_req_data,
bucket_id_provider: BucketIdProvider::default(),
})
}
}
pub(crate) fn build_segment_filter_collector(
req: &mut AggregationsSegmentCtx,
node: &AggRefNode,
) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
let is_top_level = req.per_request.filter_req_data[node.idx_in_req_data]
.as_ref()
.expect("filter_req_data slot is empty")
.is_top_level;
if is_top_level {
Ok(Box::new(
SegmentFilterCollector::<LowCardSubAggCache>::from_req_and_validate(req, node)?,
))
} else {
Ok(Box::new(
SegmentFilterCollector::<HighCardSubAggCache>::from_req_and_validate(req, node)?,
))
}
}
impl<C: SubAggCache> Debug for SegmentFilterCollector<C> {
impl Debug for SegmentFilterCollector {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_struct("SegmentFilterCollector")
.field("buckets", &self.parent_buckets)
.field("doc_count", &self.doc_count)
.field("has_sub_aggs", &self.sub_aggregations.is_some())
.field("accessor_idx", &self.accessor_idx)
.finish()
}
}
impl<C: SubAggCache> SegmentAggregationCollector for SegmentFilterCollector<C> {
impl CollectorClone for SegmentFilterCollector {
fn clone_box(&self) -> Box<dyn SegmentAggregationCollector> {
// For now, panic - this needs proper implementation with weight recreation
panic!("SegmentFilterCollector cloning not yet implemented - requires weight recreation")
}
}
impl SegmentAggregationCollector for SegmentFilterCollector {
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
let mut sub_results = IntermediateAggregationResults::default();
let bucket_opt = self.parent_buckets.get(parent_bucket_id as usize);
if let Some(sub_aggs) = &mut self.sub_aggregations {
sub_aggs
.get_sub_agg_collector()
.add_intermediate_aggregation_result(
agg_data,
&mut sub_results,
// Here we create a new bucket ID for sub-aggregations if the bucket doesn't
// exist, so that sub-aggregations can still produce results (e.g., zero doc
// count)
bucket_opt
.map(|bucket| bucket.bucket_id)
.unwrap_or(self.bucket_id_provider.next_bucket_id()),
)?;
if let Some(sub_aggs) = self.sub_aggregations {
sub_aggs.add_intermediate_aggregation_result(agg_data, &mut sub_results)?;
}
// Create the filter bucket result
let filter_bucket_result = IntermediateBucketResult::Filter {
doc_count: bucket_opt.map(|b| b.doc_count).unwrap_or(0),
doc_count: self.doc_count,
sub_aggregations: sub_results,
};
@@ -612,17 +570,32 @@ impl<C: SubAggCache> SegmentAggregationCollector for SegmentFilterCollector<C> {
Ok(())
}
fn collect(
fn collect(&mut self, doc: DocId, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
// Access the evaluator from FilterAggReqData
let req_data = agg_data.get_filter_req_data(self.accessor_idx);
// O(1) BitSet lookup to check if document matches filter
if req_data.evaluator.matches_document(doc) {
self.doc_count += 1;
// If we have sub-aggregations, collect on them for this filtered document
if let Some(sub_aggs) = &mut self.sub_aggregations {
sub_aggs.collect(doc, agg_data)?;
}
}
Ok(())
}
#[inline]
fn collect_block(
&mut self,
parent_bucket_id: BucketId,
docs: &[crate::DocId],
docs: &[DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
if docs.is_empty() {
return Ok(());
}
let mut bucket = self.parent_buckets[parent_bucket_id as usize];
// Take the request data to avoid borrow checker issues with sub-aggregations
let mut req = agg_data.take_filter_req_data(self.accessor_idx);
@@ -631,24 +604,18 @@ impl<C: SubAggCache> SegmentAggregationCollector for SegmentFilterCollector<C> {
req.evaluator
.filter_batch(docs, &mut req.matching_docs_buffer);
bucket.doc_count += req.matching_docs_buffer.len() as u64;
self.doc_count += req.matching_docs_buffer.len() as u64;
// Batch process sub-aggregations if we have matches
if !req.matching_docs_buffer.is_empty() {
if let Some(sub_aggs) = &mut self.sub_aggregations {
for &doc_id in &req.matching_docs_buffer {
sub_aggs.push(bucket.bucket_id, doc_id);
}
// Use collect_block for better sub-aggregation performance
sub_aggs.collect_block(&req.matching_docs_buffer, agg_data)?;
}
}
// Put the request data back
agg_data.put_back_filter_req_data(self.accessor_idx, req);
if let Some(sub_aggs) = &mut self.sub_aggregations {
sub_aggs.check_flush_local(agg_data)?;
}
// put back bucket
self.parent_buckets[parent_bucket_id as usize] = bucket;
Ok(())
}
@@ -659,21 +626,6 @@ impl<C: SubAggCache> SegmentAggregationCollector for SegmentFilterCollector<C> {
}
Ok(())
}
fn prepare_max_bucket(
&mut self,
max_bucket: BucketId,
_agg_data: &AggregationsSegmentCtx,
) -> crate::Result<()> {
while self.parent_buckets.len() <= max_bucket as usize {
let bucket_id = self.bucket_id_provider.next_bucket_id();
self.parent_buckets.push(DocCount {
doc_count: 0,
bucket_id,
});
}
Ok(())
}
}
/// Intermediate result for filter aggregation
@@ -838,7 +790,7 @@ mod tests {
let expected = json!({
"electronics": {
"doc_count": 2,
"avg_price": { "value": 899.0, "sum": 1798.0, "count": 2 } // (999 + 799) / 2
"avg_price": { "value": 899.0 } // (999 + 799) / 2
}
});
@@ -868,7 +820,7 @@ mod tests {
let expected = json!({
"furniture": {
"doc_count": 0,
"avg_price": { "value": null, "sum": 0.0, "count": 0 }
"avg_price": { "value": null }
}
});
@@ -904,7 +856,7 @@ mod tests {
let expected = json!({
"electronics": {
"doc_count": 2,
"avg_price": { "value": 899.0, "sum": 1798.0, "count": 2 }
"avg_price": { "value": 899.0 }
},
"in_stock": {
"doc_count": 3, // apple, samsung, penguin
@@ -1000,7 +952,7 @@ mod tests {
let expected = json!({
"premium_electronics": {
"doc_count": 1, // Only apple (999) is >= 800 in tantivy's range semantics
"avg_rating": { "value": 4.5, "sum": 4.5, "count": 1 }
"avg_rating": { "value": 4.5 }
}
});
@@ -1032,7 +984,7 @@ mod tests {
let expected = json!({
"in_stock": {
"doc_count": 3, // apple, samsung, penguin
"avg_price": { "value": 607.67, "sum": 1823.0, "count": 3 } // (999 + 799 + 25) / 3 ≈ 607.67
"avg_price": { "value": 607.67 } // (999 + 799 + 25) / 3 ≈ 607.67
},
"out_of_stock": {
"doc_count": 1, // nike
@@ -1183,7 +1135,7 @@ mod tests {
"doc_count": 4,
"electronics_branch": {
"doc_count": 2,
"avg_price": { "value": 899.0, "sum": 1798.0, "count": 2 }
"avg_price": { "value": 899.0 }
},
"in_stock_branch": {
"doc_count": 3,
@@ -1259,7 +1211,7 @@ mod tests {
"doc_count": 2, // apple (999), samsung (799)
"electronics": {
"doc_count": 2, // both are electronics
"avg_rating": { "value": 4.35, "sum": 8.7, "count": 2 } // (4.5 + 4.2) / 2
"avg_rating": { "value": 4.35 } // (4.5 + 4.2) / 2
},
"in_stock": {
"doc_count": 2, // both are in stock
@@ -1321,12 +1273,12 @@ mod tests {
{
"key": "samsung",
"doc_count": 1,
"avg_price": { "value": 799.0, "sum": 799.0, "count": 1 }
"avg_price": { "value": 799.0 }
},
{
"key": "apple",
"doc_count": 1,
"avg_price": { "value": 999.0, "sum": 999.0, "count": 1 }
"avg_price": { "value": 999.0 }
}
],
"sum_other_doc_count": 0,
@@ -1370,7 +1322,7 @@ mod tests {
"sum": 1798.0,
"avg": 899.0
},
"rating_avg": { "value": 4.35, "sum": 8.7, "count": 2 },
"rating_avg": { "value": 4.35 },
"count": { "value": 2.0 }
}
});
@@ -1411,7 +1363,7 @@ mod tests {
let expected = json!({
"electronics": {
"doc_count": 0,
"avg_price": { "value": null, "sum": 0.0, "count": 0 }
"avg_price": { "value": null }
}
});
@@ -1567,9 +1519,9 @@ mod tests {
let searcher = reader.searcher();
let agg = json!({
"test": {
"filter": deserialized,
"aggs": { "count": { "value_count": { "field": "brand" } } }
"test": {
"filter": deserialized,
"aggs": { "count": { "value_count": { "field": "brand" } } }
}
});
@@ -1698,15 +1650,13 @@ mod tests {
let filter_expected = json!({
"electronics": {
"doc_count": 2,
"avg_price": { "value": 899.0, "sum": 1798.0, "count": 2 }
"avg_price": { "value": 899.0 }
}
});
let separate_expected = json!({
"result": {
"value": 899.0,
"sum": 1798.0,
"count": 2
"value": 899.0
}
});

129
src/aggregation/bucket/histogram/histogram.rs
View File

@@ -1,6 +1,6 @@
use std::cmp::Ordering;
use columnar::{Column, ColumnType};
use columnar::{Column, ColumnBlockAccessor, ColumnType};
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use tantivy_bitpacker::minmax;
@@ -8,14 +8,14 @@ use tantivy_bitpacker::minmax;
use crate::aggregation::agg_data::{
build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
};
use crate::aggregation::agg_limits::MemoryConsumption;
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::agg_result::BucketEntry;
use crate::aggregation::cached_sub_aggs::{CachedSubAggs, HighCardCachedSubAggs};
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
IntermediateHistogramBucketEntry,
};
use crate::aggregation::segment_agg_result::{BucketIdProvider, SegmentAggregationCollector};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::TantivyError;
@@ -26,8 +26,13 @@ pub struct HistogramAggReqData {
pub accessor: Column<u64>,
/// The field type of the fast field.
pub field_type: ColumnType,
/// The column block accessor to access the fast field values.
pub column_block_accessor: ColumnBlockAccessor<u64>,
/// The name of the aggregation.
pub name: String,
/// The sub aggregation blueprint, used to create sub aggregations for each bucket.
/// Will be filled during initialization of the collector.
pub sub_aggregation_blueprint: Option<Box<dyn SegmentAggregationCollector>>,
/// The histogram aggregation request.
pub req: HistogramAggregation,
/// True if this is a date_histogram aggregation.
@@ -252,24 +257,18 @@ impl HistogramBounds {
pub(crate) struct SegmentHistogramBucketEntry {
pub key: f64,
pub doc_count: u64,
pub bucket_id: BucketId,
}
impl SegmentHistogramBucketEntry {
pub(crate) fn into_intermediate_bucket_entry(
self,
sub_aggregation: &mut Option<HighCardCachedSubAggs>,
sub_aggregation: Option<Box<dyn SegmentAggregationCollector>>,
agg_data: &AggregationsSegmentCtx,
) -> crate::Result<IntermediateHistogramBucketEntry> {
let mut sub_aggregation_res = IntermediateAggregationResults::default();
if let Some(sub_aggregation) = sub_aggregation {
sub_aggregation
.get_sub_agg_collector()
.add_intermediate_aggregation_result(
agg_data,
&mut sub_aggregation_res,
self.bucket_id,
)?;
.add_intermediate_aggregation_result(agg_data, &mut sub_aggregation_res)?;
}
Ok(IntermediateHistogramBucketEntry {
key: self.key,
@@ -279,38 +278,27 @@ impl SegmentHistogramBucketEntry {
}
}
#[derive(Clone, Debug, Default)]
struct HistogramBuckets {
pub buckets: FxHashMap<i64, SegmentHistogramBucketEntry>,
}
/// The collector puts values from the fast field into the correct buckets and does a conversion to
/// the correct datatype.
#[derive(Debug)]
#[derive(Clone, Debug)]
pub struct SegmentHistogramCollector {
/// The buckets containing the aggregation data.
/// One Histogram bucket per parent bucket id.
parent_buckets: Vec<HistogramBuckets>,
sub_agg: Option<HighCardCachedSubAggs>,
buckets: FxHashMap<i64, SegmentHistogramBucketEntry>,
sub_aggregations: FxHashMap<i64, Box<dyn SegmentAggregationCollector>>,
accessor_idx: usize,
bucket_id_provider: BucketIdProvider,
}
impl SegmentAggregationCollector for SegmentHistogramCollector {
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
let name = agg_data
.get_histogram_req_data(self.accessor_idx)
.name
.clone();
// TODO: avoid prepare_max_bucket here and handle empty buckets.
self.prepare_max_bucket(parent_bucket_id, agg_data)?;
let histogram = std::mem::take(&mut self.parent_buckets[parent_bucket_id as usize]);
let bucket = self.add_intermediate_bucket_result(agg_data, histogram)?;
let bucket = self.into_intermediate_bucket_result(agg_data)?;
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
Ok(())
@@ -319,40 +307,44 @@ impl SegmentAggregationCollector for SegmentHistogramCollector {
#[inline]
fn collect(
&mut self,
parent_bucket_id: BucketId,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)
}
#[inline]
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
let req = agg_data.take_histogram_req_data(self.accessor_idx);
let mut req = agg_data.take_histogram_req_data(self.accessor_idx);
let mem_pre = self.get_memory_consumption();
let buckets = &mut self.parent_buckets[parent_bucket_id as usize].buckets;
let bounds = req.bounds;
let interval = req.req.interval;
let offset = req.offset;
let get_bucket_pos = |val| get_bucket_pos_f64(val, interval, offset) as i64;
agg_data
.column_block_accessor
.fetch_block(docs, &req.accessor);
for (doc, val) in agg_data
req.column_block_accessor.fetch_block(docs, &req.accessor);
for (doc, val) in req
.column_block_accessor
.iter_docid_vals(docs, &req.accessor)
{
let val = f64_from_fastfield_u64(val, req.field_type);
let val = f64_from_fastfield_u64(val, &req.field_type);
let bucket_pos = get_bucket_pos(val);
if bounds.contains(val) {
let bucket = buckets.entry(bucket_pos).or_insert_with(|| {
let bucket = self.buckets.entry(bucket_pos).or_insert_with(|| {
let key = get_bucket_key_from_pos(bucket_pos as f64, interval, offset);
SegmentHistogramBucketEntry {
key,
doc_count: 0,
bucket_id: self.bucket_id_provider.next_bucket_id(),
}
SegmentHistogramBucketEntry { key, doc_count: 0 }
});
bucket.doc_count += 1;
if let Some(sub_agg) = &mut self.sub_agg {
sub_agg.push(bucket.bucket_id, doc);
if let Some(sub_aggregation_blueprint) = req.sub_aggregation_blueprint.as_ref() {
self.sub_aggregations
.entry(bucket_pos)
.or_insert_with(|| sub_aggregation_blueprint.clone())
.collect(doc, agg_data)?;
}
}
}
@@ -366,30 +358,14 @@ impl SegmentAggregationCollector for SegmentHistogramCollector {
.add_memory_consumed(mem_delta as u64)?;
}
if let Some(sub_agg) = &mut self.sub_agg {
sub_agg.check_flush_local(agg_data)?;
}
Ok(())
}
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
if let Some(sub_aggregation) = &mut self.sub_agg {
for sub_aggregation in self.sub_aggregations.values_mut() {
sub_aggregation.flush(agg_data)?;
}
Ok(())
}
fn prepare_max_bucket(
&mut self,
max_bucket: BucketId,
_agg_data: &AggregationsSegmentCtx,
) -> crate::Result<()> {
while self.parent_buckets.len() <= max_bucket as usize {
self.parent_buckets.push(HistogramBuckets {
buckets: FxHashMap::default(),
});
}
Ok(())
}
}
@@ -397,19 +373,22 @@ impl SegmentAggregationCollector for SegmentHistogramCollector {
impl SegmentHistogramCollector {
fn get_memory_consumption(&self) -> usize {
let self_mem = std::mem::size_of::<Self>();
let buckets_mem = self.parent_buckets.len() * std::mem::size_of::<HistogramBuckets>();
self_mem + buckets_mem
let sub_aggs_mem = self.sub_aggregations.memory_consumption();
let buckets_mem = self.buckets.memory_consumption();
self_mem + sub_aggs_mem + buckets_mem
}
/// Converts the collector result into a intermediate bucket result.
fn add_intermediate_bucket_result(
&mut self,
pub fn into_intermediate_bucket_result(
self,
agg_data: &AggregationsSegmentCtx,
histogram: HistogramBuckets,
) -> crate::Result<IntermediateBucketResult> {
let mut buckets = Vec::with_capacity(histogram.buckets.len());
let mut buckets = Vec::with_capacity(self.buckets.len());
for bucket in histogram.buckets.into_values() {
let bucket_res = bucket.into_intermediate_bucket_entry(&mut self.sub_agg, agg_data);
for (bucket_pos, bucket) in self.buckets {
let bucket_res = bucket.into_intermediate_bucket_entry(
self.sub_aggregations.get(&bucket_pos).cloned(),
agg_data,
);
buckets.push(bucket_res?);
}
@@ -429,7 +408,7 @@ impl SegmentHistogramCollector {
agg_data: &mut AggregationsSegmentCtx,
node: &AggRefNode,
) -> crate::Result<Self> {
let sub_agg = if !node.children.is_empty() {
let blueprint = if !node.children.is_empty() {
Some(build_segment_agg_collectors(agg_data, &node.children)?)
} else {
None
@@ -444,13 +423,13 @@ impl SegmentHistogramCollector {
max: f64::MAX,
});
req_data.offset = req_data.req.offset.unwrap_or(0.0);
let sub_agg = sub_agg.map(CachedSubAggs::new);
req_data.sub_aggregation_blueprint = blueprint;
Ok(Self {
parent_buckets: Default::default(),
sub_agg,
buckets: Default::default(),
sub_aggregations: Default::default(),
accessor_idx: node.idx_in_req_data,
bucket_id_provider: BucketIdProvider::default(),
})
}
}
@@ -1222,9 +1201,7 @@ mod tests {
res["histogram"]["buckets"][0],
json!({
"avg": {
"value": Value::Null,
"sum": 0.0,
"count": 0
"value": Value::Null
},
"doc_count": 0,
"key": 2.0,

331
src/aggregation/bucket/range.rs
View File

@@ -1,22 +1,18 @@
use std::fmt::Debug;
use std::ops::Range;
use columnar::{Column, ColumnType};
use columnar::{Column, ColumnBlockAccessor, ColumnType};
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use crate::aggregation::agg_data::{
build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
};
use crate::aggregation::agg_limits::AggregationLimitsGuard;
use crate::aggregation::cached_sub_aggs::{
CachedSubAggs, HighCardSubAggCache, LowCardCachedSubAggs, LowCardSubAggCache, SubAggCache,
};
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
IntermediateRangeBucketEntry, IntermediateRangeBucketResult,
};
use crate::aggregation::segment_agg_result::{BucketIdProvider, SegmentAggregationCollector};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::TantivyError;
@@ -27,12 +23,12 @@ pub struct RangeAggReqData {
pub accessor: Column<u64>,
/// The type of the fast field.
pub field_type: ColumnType,
/// The column block accessor to access the fast field values.
pub column_block_accessor: ColumnBlockAccessor<u64>,
/// The range aggregation request.
pub req: RangeAggregation,
/// The name of the aggregation.
pub name: String,
/// Whether this is a top-level aggregation.
pub is_top_level: bool,
}
impl RangeAggReqData {
@@ -155,47 +151,19 @@ pub(crate) struct SegmentRangeAndBucketEntry {
/// The collector puts values from the fast field into the correct buckets and does a conversion to
/// the correct datatype.
pub struct SegmentRangeCollector<C: SubAggCache> {
#[derive(Clone, Debug)]
pub struct SegmentRangeCollector {
/// The buckets containing the aggregation data.
/// One for each ParentBucketId
parent_buckets: Vec<Vec<SegmentRangeAndBucketEntry>>,
buckets: Vec<SegmentRangeAndBucketEntry>,
column_type: ColumnType,
pub(crate) accessor_idx: usize,
sub_agg: Option<CachedSubAggs<C>>,
/// Here things get a bit weird. We need to assign unique bucket ids across all
/// parent buckets. So we keep track of the next available bucket id here.
/// This allows a kind of flattening of the bucket ids across all parent buckets.
/// E.g. in nested aggregations:
/// Term Agg -> Range aggregation -> Stats aggregation
/// E.g. the Term Agg creates 3 buckets ["INFO", "ERROR", "WARN"], each of these has a Range
/// aggregation with 4 buckets. The Range aggregation will create buckets with ids:
/// - INFO: 0,1,2,3
/// - ERROR: 4,5,6,7
/// - WARN: 8,9,10,11
///
/// This allows the Stats aggregation to have unique bucket ids to refer to.
bucket_id_provider: BucketIdProvider,
limits: AggregationLimitsGuard,
}
impl<C: SubAggCache> Debug for SegmentRangeCollector<C> {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_struct("SegmentRangeCollector")
.field("parent_buckets_len", &self.parent_buckets.len())
.field("column_type", &self.column_type)
.field("accessor_idx", &self.accessor_idx)
.field("has_sub_agg", &self.sub_agg.is_some())
.finish()
}
}
/// TODO: Bad naming, there's also SegmentRangeAndBucketEntry
#[derive(Clone)]
pub(crate) struct SegmentRangeBucketEntry {
pub key: Key,
pub doc_count: u64,
// pub sub_aggregation: Option<Box<dyn SegmentAggregationCollector>>,
pub bucket_id: BucketId,
pub sub_aggregation: Option<Box<dyn SegmentAggregationCollector>>,
/// The from range of the bucket. Equals `f64::MIN` when `None`.
pub from: Option<f64>,
/// The to range of the bucket. Equals `f64::MAX` when `None`. Open interval, `to` is not
@@ -216,50 +184,48 @@ impl Debug for SegmentRangeBucketEntry {
impl SegmentRangeBucketEntry {
pub(crate) fn into_intermediate_bucket_entry(
self,
agg_data: &AggregationsSegmentCtx,
) -> crate::Result<IntermediateRangeBucketEntry> {
let sub_aggregation = IntermediateAggregationResults::default();
let mut sub_aggregation_res = IntermediateAggregationResults::default();
if let Some(sub_aggregation) = self.sub_aggregation {
sub_aggregation
.add_intermediate_aggregation_result(agg_data, &mut sub_aggregation_res)?
} else {
Default::default()
};
Ok(IntermediateRangeBucketEntry {
key: self.key.into(),
doc_count: self.doc_count,
sub_aggregation_res: sub_aggregation,
sub_aggregation: sub_aggregation_res,
from: self.from,
to: self.to,
})
}
}
impl<C: SubAggCache> SegmentAggregationCollector for SegmentRangeCollector<C> {
impl SegmentAggregationCollector for SegmentRangeCollector {
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
self.prepare_max_bucket(parent_bucket_id, agg_data)?;
let field_type = self.column_type;
let name = agg_data
.get_range_req_data(self.accessor_idx)
.name
.to_string();
let buckets = std::mem::take(&mut self.parent_buckets[parent_bucket_id as usize]);
let buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry> = buckets
let buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry> = self
.buckets
.into_iter()
.map(|range_bucket| {
let bucket_id = range_bucket.bucket.bucket_id;
let mut agg = range_bucket.bucket.into_intermediate_bucket_entry()?;
if let Some(sub_aggregation) = &mut self.sub_agg {
sub_aggregation
.get_sub_agg_collector()
.add_intermediate_aggregation_result(
agg_data,
&mut agg.sub_aggregation_res,
bucket_id,
)?;
}
Ok((range_to_string(&range_bucket.range, &field_type)?, agg))
.map(move |range_bucket| {
Ok((
range_to_string(&range_bucket.range, &field_type)?,
range_bucket
.bucket
.into_intermediate_bucket_entry(agg_data)?,
))
})
.collect::<crate::Result<_>>()?;
@@ -276,114 +242,73 @@ impl<C: SubAggCache> SegmentAggregationCollector for SegmentRangeCollector<C> {
#[inline]
fn collect(
&mut self,
parent_bucket_id: BucketId,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)
}
#[inline]
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
let req = agg_data.take_range_req_data(self.accessor_idx);
// Take request data to avoid borrow conflicts during sub-aggregation
let mut req = agg_data.take_range_req_data(self.accessor_idx);
agg_data
.column_block_accessor
.fetch_block(docs, &req.accessor);
req.column_block_accessor.fetch_block(docs, &req.accessor);
let buckets = &mut self.parent_buckets[parent_bucket_id as usize];
for (doc, val) in agg_data
for (doc, val) in req
.column_block_accessor
.iter_docid_vals(docs, &req.accessor)
{
let bucket_pos = get_bucket_pos(val, buckets);
let bucket = &mut buckets[bucket_pos];
let bucket_pos = self.get_bucket_pos(val);
let bucket = &mut self.buckets[bucket_pos];
bucket.bucket.doc_count += 1;
if let Some(sub_agg) = self.sub_agg.as_mut() {
sub_agg.push(bucket.bucket.bucket_id, doc);
if let Some(sub_agg) = bucket.bucket.sub_aggregation.as_mut() {
sub_agg.collect(doc, agg_data)?;
}
}
agg_data.put_back_range_req_data(self.accessor_idx, req);
if let Some(sub_agg) = self.sub_agg.as_mut() {
sub_agg.check_flush_local(agg_data)?;
}
Ok(())
}
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
if let Some(sub_agg) = self.sub_agg.as_mut() {
sub_agg.flush(agg_data)?;
for bucket in self.buckets.iter_mut() {
if let Some(sub_agg) = bucket.bucket.sub_aggregation.as_mut() {
sub_agg.flush(agg_data)?;
}
}
Ok(())
}
fn prepare_max_bucket(
&mut self,
max_bucket: BucketId,
agg_data: &AggregationsSegmentCtx,
) -> crate::Result<()> {
while self.parent_buckets.len() <= max_bucket as usize {
let new_buckets = self.create_new_buckets(agg_data)?;
self.parent_buckets.push(new_buckets);
}
Ok(())
}
}
/// Build a concrete `SegmentRangeCollector` with either a Vec- or HashMap-backed
/// bucket storage, depending on the column type and aggregation level.
pub(crate) fn build_segment_range_collector(
agg_data: &mut AggregationsSegmentCtx,
node: &AggRefNode,
) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
let accessor_idx = node.idx_in_req_data;
let req_data = agg_data.get_range_req_data(node.idx_in_req_data);
let field_type = req_data.field_type;
// TODO: A better metric instead of is_top_level would be the number of buckets expected.
// E.g. If range agg is not top level, but the parent is a bucket agg with less than 10 buckets,
// we can are still in low cardinality territory.
let is_low_card = req_data.is_top_level && req_data.req.ranges.len() <= 64;
let sub_agg = if !node.children.is_empty() {
Some(build_segment_agg_collectors(agg_data, &node.children)?)
} else {
None
};
if is_low_card {
Ok(Box::new(SegmentRangeCollector::<LowCardSubAggCache> {
sub_agg: sub_agg.map(LowCardCachedSubAggs::new),
column_type: field_type,
accessor_idx,
parent_buckets: Vec::new(),
bucket_id_provider: BucketIdProvider::default(),
limits: agg_data.context.limits.clone(),
}))
} else {
Ok(Box::new(SegmentRangeCollector::<HighCardSubAggCache> {
sub_agg: sub_agg.map(CachedSubAggs::new),
column_type: field_type,
accessor_idx,
parent_buckets: Vec::new(),
bucket_id_provider: BucketIdProvider::default(),
limits: agg_data.context.limits.clone(),
}))
}
}
impl<C: SubAggCache> SegmentRangeCollector<C> {
pub(crate) fn create_new_buckets(
&mut self,
agg_data: &AggregationsSegmentCtx,
) -> crate::Result<Vec<SegmentRangeAndBucketEntry>> {
let field_type = self.column_type;
let req_data = agg_data.get_range_req_data(self.accessor_idx);
impl SegmentRangeCollector {
pub(crate) fn from_req_and_validate(
req_data: &mut AggregationsSegmentCtx,
node: &AggRefNode,
) -> crate::Result<Self> {
let accessor_idx = node.idx_in_req_data;
let (field_type, ranges) = {
let req_view = req_data.get_range_req_data(node.idx_in_req_data);
(req_view.field_type, req_view.req.ranges.clone())
};
// The range input on the request is f64.
// We need to convert to u64 ranges, because we read the values as u64.
// The mapping from the conversion is monotonic so ordering is preserved.
let buckets: Vec<_> = extend_validate_ranges(&req_data.req.ranges, &field_type)?
let sub_agg_prototype = if !node.children.is_empty() {
Some(build_segment_agg_collectors(req_data, &node.children)?)
} else {
None
};
let buckets: Vec<_> = extend_validate_ranges(&ranges, &field_type)?
.iter()
.map(|range| {
let bucket_id = self.bucket_id_provider.next_bucket_id();
let key = range
.key
.clone()
@@ -392,20 +317,20 @@ impl<C: SubAggCache> SegmentRangeCollector<C> {
let to = if range.range.end == u64::MAX {
None
} else {
Some(f64_from_fastfield_u64(range.range.end, field_type))
Some(f64_from_fastfield_u64(range.range.end, &field_type))
};
let from = if range.range.start == u64::MIN {
None
} else {
Some(f64_from_fastfield_u64(range.range.start, field_type))
Some(f64_from_fastfield_u64(range.range.start, &field_type))
};
// let sub_aggregation = sub_agg_prototype.clone();
let sub_aggregation = sub_agg_prototype.clone();
Ok(SegmentRangeAndBucketEntry {
range: range.range.clone(),
bucket: SegmentRangeBucketEntry {
doc_count: 0,
bucket_id,
sub_aggregation,
key,
from,
to,
@@ -414,19 +339,26 @@ impl<C: SubAggCache> SegmentRangeCollector<C> {
})
.collect::<crate::Result<_>>()?;
self.limits.add_memory_consumed(
req_data.context.limits.add_memory_consumed(
buckets.len() as u64 * std::mem::size_of::<SegmentRangeAndBucketEntry>() as u64,
)?;
Ok(buckets)
Ok(SegmentRangeCollector {
buckets,
column_type: field_type,
accessor_idx,
})
}
#[inline]
fn get_bucket_pos(&self, val: u64) -> usize {
let pos = self
.buckets
.binary_search_by_key(&val, |probe| probe.range.start)
.unwrap_or_else(|pos| pos - 1);
debug_assert!(self.buckets[pos].range.contains(&val));
pos
}
}
#[inline]
fn get_bucket_pos(val: u64, buckets: &[SegmentRangeAndBucketEntry]) -> usize {
let pos = buckets
.binary_search_by_key(&val, |probe| probe.range.start)
.unwrap_or_else(|pos| pos - 1);
debug_assert!(buckets[pos].range.contains(&val));
pos
}
/// Converts the user provided f64 range value to fast field value space.
@@ -524,7 +456,7 @@ pub(crate) fn range_to_string(
let val = i64::from_u64(val);
format_date(val)
} else {
Ok(f64_from_fastfield_u64(val, *field_type).to_string())
Ok(f64_from_fastfield_u64(val, field_type).to_string())
}
};
@@ -554,7 +486,7 @@ mod tests {
pub fn get_collector_from_ranges(
ranges: Vec<RangeAggregationRange>,
field_type: ColumnType,
) -> SegmentRangeCollector<HighCardSubAggCache> {
) -> SegmentRangeCollector {
let req = RangeAggregation {
field: "dummy".to_string(),
ranges,
@@ -574,33 +506,30 @@ mod tests {
let to = if range.range.end == u64::MAX {
None
} else {
Some(f64_from_fastfield_u64(range.range.end, field_type))
Some(f64_from_fastfield_u64(range.range.end, &field_type))
};
let from = if range.range.start == u64::MIN {
None
} else {
Some(f64_from_fastfield_u64(range.range.start, field_type))
Some(f64_from_fastfield_u64(range.range.start, &field_type))
};
SegmentRangeAndBucketEntry {
range: range.range.clone(),
bucket: SegmentRangeBucketEntry {
doc_count: 0,
sub_aggregation: None,
key,
from,
to,
bucket_id: 0,
},
}
})
.collect();
SegmentRangeCollector {
parent_buckets: vec![buckets],
buckets,
column_type: field_type,
accessor_idx: 0,
sub_agg: None,
bucket_id_provider: Default::default(),
limits: AggregationLimitsGuard::default(),
}
}
@@ -847,7 +776,7 @@ mod tests {
let buckets = vec![(10f64..20f64).into(), (30f64..40f64).into()];
let collector = get_collector_from_ranges(buckets, ColumnType::F64);
let buckets = collector.parent_buckets[0].clone();
let buckets = collector.buckets;
assert_eq!(buckets[0].range.start, u64::MIN);
assert_eq!(buckets[0].range.end, 10f64.to_u64());
assert_eq!(buckets[1].range.start, 10f64.to_u64());
@@ -870,7 +799,7 @@ mod tests {
];
let collector = get_collector_from_ranges(buckets, ColumnType::F64);
let buckets = collector.parent_buckets[0].clone();
let buckets = collector.buckets;
assert_eq!(buckets[0].range.start, u64::MIN);
assert_eq!(buckets[0].range.end, 10f64.to_u64());
assert_eq!(buckets[1].range.start, 10f64.to_u64());
@@ -885,7 +814,7 @@ mod tests {
let buckets = vec![(-10f64..-1f64).into()];
let collector = get_collector_from_ranges(buckets, ColumnType::F64);
let buckets = collector.parent_buckets[0].clone();
let buckets = collector.buckets;
assert_eq!(&buckets[0].bucket.key.to_string(), "*--10");
assert_eq!(&buckets[buckets.len() - 1].bucket.key.to_string(), "-1-*");
}
@@ -894,7 +823,7 @@ mod tests {
let buckets = vec![(0f64..10f64).into()];
let collector = get_collector_from_ranges(buckets, ColumnType::F64);
let buckets = collector.parent_buckets[0].clone();
let buckets = collector.buckets;
assert_eq!(&buckets[0].bucket.key.to_string(), "*-0");
assert_eq!(&buckets[buckets.len() - 1].bucket.key.to_string(), "10-*");
}
@@ -903,7 +832,7 @@ mod tests {
fn range_binary_search_test_u64() {
let check_ranges = |ranges: Vec<RangeAggregationRange>| {
let collector = get_collector_from_ranges(ranges, ColumnType::U64);
let search = |val: u64| get_bucket_pos(val, &collector.parent_buckets[0]);
let search = |val: u64| collector.get_bucket_pos(val);
assert_eq!(search(u64::MIN), 0);
assert_eq!(search(9), 0);
@@ -949,7 +878,7 @@ mod tests {
let ranges = vec![(10.0..100.0).into()];
let collector = get_collector_from_ranges(ranges, ColumnType::F64);
let search = |val: u64| get_bucket_pos(val, &collector.parent_buckets[0]);
let search = |val: u64| collector.get_bucket_pos(val);
assert_eq!(search(u64::MIN), 0);
assert_eq!(search(9f64.to_u64()), 0);
@@ -961,3 +890,63 @@ mod tests {
// the max value
}
}
#[cfg(all(test, feature = "unstable"))]
mod bench {
use itertools::Itertools;
use rand::seq::SliceRandom;
use rand::thread_rng;
use super::*;
use crate::aggregation::bucket::range::tests::get_collector_from_ranges;
const TOTAL_DOCS: u64 = 1_000_000u64;
const NUM_DOCS: u64 = 50_000u64;
fn get_collector_with_buckets(num_buckets: u64, num_docs: u64) -> SegmentRangeCollector {
let bucket_size = num_docs / num_buckets;
let mut buckets: Vec<RangeAggregationRange> = vec![];
for i in 0..num_buckets {
let bucket_start = (i * bucket_size) as f64;
buckets.push((bucket_start..bucket_start + bucket_size as f64).into())
}
get_collector_from_ranges(buckets, ColumnType::U64)
}
fn get_rand_docs(total_docs: u64, num_docs_returned: u64) -> Vec<u64> {
let mut rng = thread_rng();
let all_docs = (0..total_docs - 1).collect_vec();
let mut vals = all_docs
.as_slice()
.choose_multiple(&mut rng, num_docs_returned as usize)
.cloned()
.collect_vec();
vals.sort();
vals
}
fn bench_range_binary_search(b: &mut test::Bencher, num_buckets: u64) {
let collector = get_collector_with_buckets(num_buckets, TOTAL_DOCS);
let vals = get_rand_docs(TOTAL_DOCS, NUM_DOCS);
b.iter(|| {
let mut bucket_pos = 0;
for val in &vals {
bucket_pos = collector.get_bucket_pos(*val);
}
bucket_pos
})
}
#[bench]
fn bench_range_100_buckets(b: &mut test::Bencher) {
bench_range_binary_search(b, 100)
}
#[bench]
fn bench_range_10_buckets(b: &mut test::Bencher) {
bench_range_binary_search(b, 10)
}
}

819
src/aggregation/bucket/term_agg.rs
View File

File diff suppressed because it is too large Load Diff

103
src/aggregation/bucket/term_missing_agg.rs
View File

@@ -5,13 +5,11 @@ use crate::aggregation::agg_data::{
build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
};
use crate::aggregation::bucket::term_agg::TermsAggregation;
use crate::aggregation::cached_sub_aggs::{CachedSubAggs, HighCardCachedSubAggs};
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
IntermediateKey, IntermediateTermBucketEntry, IntermediateTermBucketResult,
};
use crate::aggregation::segment_agg_result::{BucketIdProvider, SegmentAggregationCollector};
use crate::aggregation::BucketId;
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
/// Special aggregation to handle missing values for term aggregations.
/// This missing aggregation will check multiple columns for existence.
@@ -37,55 +35,41 @@ impl MissingTermAggReqData {
}
}
#[derive(Default, Debug, Clone)]
struct MissingCount {
missing_count: u32,
bucket_id: BucketId,
}
/// The specialized missing term aggregation.
#[derive(Default, Debug)]
#[derive(Default, Debug, Clone)]
pub struct TermMissingAgg {
missing_count: u32,
accessor_idx: usize,
sub_agg: Option<HighCardCachedSubAggs>,
/// Idx = parent bucket id, Value = missing count for that bucket
missing_count_per_bucket: Vec<MissingCount>,
bucket_id_provider: BucketIdProvider,
sub_agg: Option<Box<dyn SegmentAggregationCollector>>,
}
impl TermMissingAgg {
pub(crate) fn new(
agg_data: &mut AggregationsSegmentCtx,
req_data: &mut AggregationsSegmentCtx,
node: &AggRefNode,
) -> crate::Result<Self> {
let has_sub_aggregations = !node.children.is_empty();
let accessor_idx = node.idx_in_req_data;
let sub_agg = if has_sub_aggregations {
let sub_aggregation = build_segment_agg_collectors(agg_data, &node.children)?;
let sub_aggregation = build_segment_agg_collectors(req_data, &node.children)?;
Some(sub_aggregation)
} else {
None
};
let sub_agg = sub_agg.map(CachedSubAggs::new);
let bucket_id_provider = BucketIdProvider::default();
Ok(Self {
accessor_idx,
sub_agg,
missing_count_per_bucket: Vec::new(),
bucket_id_provider,
..Default::default()
})
}
}
impl SegmentAggregationCollector for TermMissingAgg {
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
self.prepare_max_bucket(parent_bucket_id, agg_data)?;
let req_data = agg_data.get_missing_term_req_data(self.accessor_idx);
let term_agg = &req_data.req;
let missing = term_agg
@@ -96,16 +80,13 @@ impl SegmentAggregationCollector for TermMissingAgg {
let mut entries: FxHashMap<IntermediateKey, IntermediateTermBucketEntry> =
Default::default();
let missing_count = &self.missing_count_per_bucket[parent_bucket_id as usize];
let mut missing_entry = IntermediateTermBucketEntry {
doc_count: missing_count.missing_count,
doc_count: self.missing_count,
sub_aggregation: Default::default(),
};
if let Some(sub_agg) = &mut self.sub_agg {
if let Some(sub_agg) = self.sub_agg {
let mut res = IntermediateAggregationResults::default();
sub_agg
.get_sub_agg_collector()
.add_intermediate_aggregation_result(agg_data, &mut res, missing_count.bucket_id)?;
sub_agg.add_intermediate_aggregation_result(agg_data, &mut res)?;
missing_entry.sub_aggregation = res;
}
entries.insert(missing.into(), missing_entry);
@@ -128,52 +109,30 @@ impl SegmentAggregationCollector for TermMissingAgg {
fn collect(
&mut self,
parent_bucket_id: BucketId,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
let req_data = agg_data.get_missing_term_req_data(self.accessor_idx);
let has_value = req_data
.accessors
.iter()
.any(|(acc, _)| acc.index.has_value(doc));
if !has_value {
self.missing_count += 1;
if let Some(sub_agg) = self.sub_agg.as_mut() {
sub_agg.collect(doc, agg_data)?;
}
}
Ok(())
}
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
let bucket = &mut self.missing_count_per_bucket[parent_bucket_id as usize];
let req_data = agg_data.get_missing_term_req_data(self.accessor_idx);
for doc in docs {
let doc = *doc;
let has_value = req_data
.accessors
.iter()
.any(|(acc, _)| acc.index.has_value(doc));
if !has_value {
bucket.missing_count += 1;
if let Some(sub_agg) = self.sub_agg.as_mut() {
sub_agg.push(bucket.bucket_id, doc);
}
}
}
if let Some(sub_agg) = self.sub_agg.as_mut() {
sub_agg.check_flush_local(agg_data)?;
}
Ok(())
}
fn prepare_max_bucket(
&mut self,
max_bucket: BucketId,
_agg_data: &AggregationsSegmentCtx,
) -> crate::Result<()> {
while self.missing_count_per_bucket.len() <= max_bucket as usize {
let bucket_id = self.bucket_id_provider.next_bucket_id();
self.missing_count_per_bucket.push(MissingCount {
missing_count: 0,
bucket_id,
});
}
Ok(())
}
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
if let Some(sub_agg) = self.sub_agg.as_mut() {
sub_agg.flush(agg_data)?;
self.collect(*doc, agg_data)?;
}
Ok(())
}

87
src/aggregation/buf_collector.rs Normal file
View File

@@ -0,0 +1,87 @@
use super::intermediate_agg_result::IntermediateAggregationResults;
use super::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::DocId;
#[cfg(test)]
pub(crate) const DOC_BLOCK_SIZE: usize = 64;
#[cfg(not(test))]
pub(crate) const DOC_BLOCK_SIZE: usize = 256;
pub(crate) type DocBlock = [DocId; DOC_BLOCK_SIZE];
/// BufAggregationCollector buffers documents before calling collect_block().
#[derive(Clone)]
pub(crate) struct BufAggregationCollector {
pub(crate) collector: Box<dyn SegmentAggregationCollector>,
staged_docs: DocBlock,
num_staged_docs: usize,
}
impl std::fmt::Debug for BufAggregationCollector {
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
f.debug_struct("SegmentAggregationResultsCollector")
.field("staged_docs", &&self.staged_docs[..self.num_staged_docs])
.field("num_staged_docs", &self.num_staged_docs)
.finish()
}
}
impl BufAggregationCollector {
pub fn new(collector: Box<dyn SegmentAggregationCollector>) -> Self {
Self {
collector,
num_staged_docs: 0,
staged_docs: [0; DOC_BLOCK_SIZE],
}
}
}
impl SegmentAggregationCollector for BufAggregationCollector {
#[inline]
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
Box::new(self.collector).add_intermediate_aggregation_result(agg_data, results)
}
#[inline]
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.staged_docs[self.num_staged_docs] = doc;
self.num_staged_docs += 1;
if self.num_staged_docs == self.staged_docs.len() {
self.collector
.collect_block(&self.staged_docs[..self.num_staged_docs], agg_data)?;
self.num_staged_docs = 0;
}
Ok(())
}
#[inline]
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.collector.collect_block(docs, agg_data)?;
Ok(())
}
#[inline]
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
self.collector
.collect_block(&self.staged_docs[..self.num_staged_docs], agg_data)?;
self.num_staged_docs = 0;
self.collector.flush(agg_data)?;
Ok(())
}
}

245
src/aggregation/cached_sub_aggs.rs
View File

@@ -1,245 +0,0 @@
use std::fmt::Debug;
use super::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::bucket::MAX_NUM_TERMS_FOR_VEC;
use crate::aggregation::BucketId;
use crate::DocId;
/// A cache for sub-aggregations, storing doc ids per bucket id.
/// Depending on the cardinality of the parent aggregation, we use different
/// storage strategies.
///
/// ## Low Cardinality
/// Cardinality here refers to the number of unique flattened buckets that can be created
/// by the parent aggregation.
/// Flattened buckets are the result of combining all buckets per collector
/// into a single list of buckets, where each bucket is identified by its BucketId.
///
/// ## Usage
/// Since this is caching for sub-aggregations, it is only used by bucket
/// aggregations.
///
/// TODO: consider using a more advanced data structure for high cardinality
/// aggregations.
/// What this datastructure does in general is to group docs by bucket id.
#[derive(Debug)]
pub(crate) struct CachedSubAggs<C: SubAggCache> {
cache: C,
sub_agg_collector: Box<dyn SegmentAggregationCollector>,
num_docs: usize,
}
pub type LowCardCachedSubAggs = CachedSubAggs<LowCardSubAggCache>;
pub type HighCardCachedSubAggs = CachedSubAggs<HighCardSubAggCache>;
const FLUSH_THRESHOLD: usize = 2048;
/// A trait for caching sub-aggregation doc ids per bucket id.
/// Different implementations can be used depending on the cardinality
/// of the parent aggregation.
pub trait SubAggCache: Debug {
fn new() -> Self;
fn push(&mut self, bucket_id: BucketId, doc_id: DocId);
fn flush_local(
&mut self,
sub_agg: &mut Box<dyn SegmentAggregationCollector>,
agg_data: &mut AggregationsSegmentCtx,
force: bool,
) -> crate::Result<()>;
}
impl<Backend: SubAggCache + Debug> CachedSubAggs<Backend> {
pub fn new(sub_agg: Box<dyn SegmentAggregationCollector>) -> Self {
Self {
cache: Backend::new(),
sub_agg_collector: sub_agg,
num_docs: 0,
}
}
pub fn get_sub_agg_collector(&mut self) -> &mut Box<dyn SegmentAggregationCollector> {
&mut self.sub_agg_collector
}
#[inline]
pub fn push(&mut self, bucket_id: BucketId, doc_id: DocId) {
self.cache.push(bucket_id, doc_id);
self.num_docs += 1;
}
/// Check if we need to flush based on the number of documents cached.
/// If so, flushes the cache to the provided aggregation collector.
pub fn check_flush_local(
&mut self,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
if self.num_docs >= FLUSH_THRESHOLD {
self.cache
.flush_local(&mut self.sub_agg_collector, agg_data, false)?;
self.num_docs = 0;
}
Ok(())
}
/// Note: this _does_ flush the sub aggregations.
pub fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
if self.num_docs != 0 {
self.cache
.flush_local(&mut self.sub_agg_collector, agg_data, true)?;
self.num_docs = 0;
}
self.sub_agg_collector.flush(agg_data)?;
Ok(())
}
}
/// Number of partitions for high cardinality sub-aggregation cache.
const NUM_PARTITIONS: usize = 16;
#[derive(Debug)]
pub(crate) struct HighCardSubAggCache {
/// This weird partitioning is used to do some cheap grouping on the bucket ids.
/// bucket ids are dense, e.g. when we don't detect the cardinality as low cardinality,
/// but there are just 16 bucket ids, each bucket id will go to its own partition.
///
/// We want to keep this cheap, because high cardinality aggregations can have a lot of
/// buckets, and there may be nothing to group.
partitions: Box<[PartitionEntry; NUM_PARTITIONS]>,
}
impl HighCardSubAggCache {
#[inline]
fn clear(&mut self) {
for partition in self.partitions.iter_mut() {
partition.clear();
}
}
}
#[derive(Debug, Clone, Default)]
struct PartitionEntry {
bucket_ids: Vec<BucketId>,
docs: Vec<DocId>,
}
impl PartitionEntry {
#[inline]
fn clear(&mut self) {
self.bucket_ids.clear();
self.docs.clear();
}
}
impl SubAggCache for HighCardSubAggCache {
fn new() -> Self {
Self {
partitions: Box::new(core::array::from_fn(|_| PartitionEntry::default())),
}
}
fn push(&mut self, bucket_id: BucketId, doc_id: DocId) {
let idx = bucket_id % NUM_PARTITIONS as u32;
let slot = &mut self.partitions[idx as usize];
slot.bucket_ids.push(bucket_id);
slot.docs.push(doc_id);
}
fn flush_local(
&mut self,
sub_agg: &mut Box<dyn SegmentAggregationCollector>,
agg_data: &mut AggregationsSegmentCtx,
_force: bool,
) -> crate::Result<()> {
let mut max_bucket = 0u32;
for partition in self.partitions.iter() {
if let Some(&local_max) = partition.bucket_ids.iter().max() {
max_bucket = max_bucket.max(local_max);
}
}
sub_agg.prepare_max_bucket(max_bucket, agg_data)?;
for slot in self.partitions.iter() {
if !slot.bucket_ids.is_empty() {
// Reduce dynamic dispatch overhead by collecting a full partition in one call.
sub_agg.collect_multiple(&slot.bucket_ids, &slot.docs, agg_data)?;
}
}
self.clear();
Ok(())
}
}
#[derive(Debug)]
pub(crate) struct LowCardSubAggCache {
/// Cache doc ids per bucket for sub-aggregations.
///
/// The outer Vec is indexed by BucketId.
per_bucket_docs: Vec<Vec<DocId>>,
}
impl LowCardSubAggCache {
#[inline]
fn clear(&mut self) {
for v in &mut self.per_bucket_docs {
v.clear();
}
}
}
impl SubAggCache for LowCardSubAggCache {
fn new() -> Self {
Self {
per_bucket_docs: Vec::new(),
}
}
fn push(&mut self, bucket_id: BucketId, doc_id: DocId) {
let idx = bucket_id as usize;
if self.per_bucket_docs.len() <= idx {
self.per_bucket_docs.resize_with(idx + 1, Vec::new);
}
self.per_bucket_docs[idx].push(doc_id);
}
fn flush_local(
&mut self,
sub_agg: &mut Box<dyn SegmentAggregationCollector>,
agg_data: &mut AggregationsSegmentCtx,
force: bool,
) -> crate::Result<()> {
// Pre-aggregated: call collect per bucket.
let max_bucket = (self.per_bucket_docs.len() as BucketId).saturating_sub(1);
sub_agg.prepare_max_bucket(max_bucket, agg_data)?;
// The threshold above which we flush buckets individually.
// Note: We need to make sure that we don't lock ourselves into a situation where we hit
// the FLUSH_THRESHOLD, but never flush any buckets. (except the final flush)
let mut bucket_treshold = FLUSH_THRESHOLD / (self.per_bucket_docs.len().max(1) * 2);
const _: () = {
// MAX_NUM_TERMS_FOR_VEC threshold is used for term aggregations
// Note: There may be other flexible values, for other aggregations, but we can use the
// const value here as a upper bound. (better than nothing)
let bucket_treshold_limit = FLUSH_THRESHOLD / (MAX_NUM_TERMS_FOR_VEC as usize * 2);
assert!(
bucket_treshold_limit > 0,
"Bucket threshold must be greater than 0"
);
};
if force {
bucket_treshold = 0;
}
for (bucket_id, docs) in self
.per_bucket_docs
.iter()
.enumerate()
.filter(|(_, docs)| docs.len() > bucket_treshold)
{
sub_agg.collect(bucket_id as BucketId, docs, agg_data)?;
}
self.clear();
Ok(())
}
}

53
src/aggregation/collector.rs
View File

@@ -1,9 +1,9 @@
use super::agg_req::Aggregations;
use super::agg_result::AggregationResults;
use super::cached_sub_aggs::LowCardCachedSubAggs;
use super::buf_collector::BufAggregationCollector;
use super::intermediate_agg_result::IntermediateAggregationResults;
use super::segment_agg_result::SegmentAggregationCollector;
use super::AggContextParams;
// group buffering strategy is chosen explicitly by callers; no need to hash-group on the fly.
use crate::aggregation::agg_data::{
build_aggregations_data_from_req, build_segment_agg_collectors_root, AggregationsSegmentCtx,
};
@@ -136,7 +136,7 @@ fn merge_fruits(
/// `AggregationSegmentCollector` does the aggregation collection on a segment.
pub struct AggregationSegmentCollector {
aggs_with_accessor: AggregationsSegmentCtx,
agg_collector: LowCardCachedSubAggs,
agg_collector: BufAggregationCollector,
error: Option<TantivyError>,
}
@@ -151,11 +151,8 @@ impl AggregationSegmentCollector {
) -> crate::Result<Self> {
let mut agg_data =
build_aggregations_data_from_req(agg, reader, segment_ordinal, context.clone())?;
let mut result =
LowCardCachedSubAggs::new(build_segment_agg_collectors_root(&mut agg_data)?);
result
.get_sub_agg_collector()
.prepare_max_bucket(0, &agg_data)?; // prepare for bucket zero
let result =
BufAggregationCollector::new(build_segment_agg_collectors_root(&mut agg_data)?);
Ok(AggregationSegmentCollector {
aggs_with_accessor: agg_data,
@@ -173,31 +170,26 @@ impl SegmentCollector for AggregationSegmentCollector {
if self.error.is_some() {
return;
}
self.agg_collector.push(0, doc);
match self
if let Err(err) = self
.agg_collector
.check_flush_local(&mut self.aggs_with_accessor)
.collect(doc, &mut self.aggs_with_accessor)
{
Ok(_) => {}
Err(e) => {
self.error = Some(e);
}
self.error = Some(err);
}
}
/// The query pushes the documents to the collector via this method.
///
/// Only valid for Collectors that ignore docs
fn collect_block(&mut self, docs: &[DocId]) {
if self.error.is_some() {
return;
}
match self.agg_collector.get_sub_agg_collector().collect(
0,
docs,
&mut self.aggs_with_accessor,
) {
Ok(_) => {}
Err(e) => {
self.error = Some(e);
}
if let Err(err) = self
.agg_collector
.collect_block(docs, &mut self.aggs_with_accessor)
{
self.error = Some(err);
}
}
@@ -208,13 +200,10 @@ impl SegmentCollector for AggregationSegmentCollector {
self.agg_collector.flush(&mut self.aggs_with_accessor)?;
let mut sub_aggregation_res = IntermediateAggregationResults::default();
self.agg_collector
.get_sub_agg_collector()
.add_intermediate_aggregation_result(
&self.aggs_with_accessor,
&mut sub_aggregation_res,
0,
)?;
Box::new(self.agg_collector).add_intermediate_aggregation_result(
&self.aggs_with_accessor,
&mut sub_aggregation_res,
)?;
Ok(sub_aggregation_res)
}

30
src/aggregation/intermediate_agg_result.rs
View File

@@ -19,9 +19,8 @@ use super::bucket::{
GetDocCount, Order, OrderTarget, RangeAggregation, TermsAggregation,
};
use super::metric::{
AverageMetricResult, CardinalityMetricResult, IntermediateAverage, IntermediateCount,
IntermediateExtendedStats, IntermediateMax, IntermediateMin, IntermediateStats,
IntermediateSum, PercentilesCollector, TopHitsTopNComputer,
IntermediateAverage, IntermediateCount, IntermediateExtendedStats, IntermediateMax,
IntermediateMin, IntermediateStats, IntermediateSum, PercentilesCollector, TopHitsTopNComputer,
};
use super::segment_agg_result::AggregationLimitsGuard;
use super::{format_date, AggregationError, Key, SerializedKey};
@@ -326,11 +325,7 @@ impl IntermediateMetricResult {
fn into_final_metric_result(self, req: &Aggregation) -> MetricResult {
match self {
IntermediateMetricResult::Average(intermediate_avg) => {
MetricResult::Average(AverageMetricResult {
value: intermediate_avg.finalize(),
sum: intermediate_avg.sum(),
count: intermediate_avg.count(),
})
MetricResult::Average(intermediate_avg.finalize().into())
}
IntermediateMetricResult::Count(intermediate_count) => {
MetricResult::Count(intermediate_count.finalize().into())
@@ -358,11 +353,7 @@ impl IntermediateMetricResult {
MetricResult::TopHits(top_hits.into_final_result())
}
IntermediateMetricResult::Cardinality(cardinality) => {
let value = cardinality.finalize();
MetricResult::Cardinality(CardinalityMetricResult {
value,
sketch: Some(cardinality),
})
MetricResult::Cardinality(cardinality.finalize().into())
}
}
}
@@ -801,7 +792,7 @@ pub struct IntermediateRangeBucketEntry {
/// The number of documents in the bucket.
pub doc_count: u64,
/// The sub_aggregation in this bucket.
pub sub_aggregation_res: IntermediateAggregationResults,
pub sub_aggregation: IntermediateAggregationResults,
/// The from range of the bucket. Equals `f64::MIN` when `None`.
pub from: Option<f64>,
/// The to range of the bucket. Equals `f64::MAX` when `None`.
@@ -820,7 +811,7 @@ impl IntermediateRangeBucketEntry {
key: self.key.into(),
doc_count: self.doc_count,
sub_aggregation: self
.sub_aggregation_res
.sub_aggregation
.into_final_result_internal(req, limits)?,
to: self.to,
from: self.from,
@@ -829,7 +820,7 @@ impl IntermediateRangeBucketEntry {
};
// If we have a date type on the histogram buckets, we add the `key_as_string` field as
// rfc3339
// rfc339
if column_type == Some(ColumnType::DateTime) {
if let Some(val) = range_bucket_entry.to {
let key_as_string = format_date(val as i64)?;
@@ -866,8 +857,7 @@ impl MergeFruits for IntermediateTermBucketEntry {
impl MergeFruits for IntermediateRangeBucketEntry {
fn merge_fruits(&mut self, other: IntermediateRangeBucketEntry) -> crate::Result<()> {
self.doc_count += other.doc_count;
self.sub_aggregation_res
.merge_fruits(other.sub_aggregation_res)?;
self.sub_aggregation.merge_fruits(other.sub_aggregation)?;
Ok(())
}
}
@@ -897,7 +887,7 @@ mod tests {
IntermediateRangeBucketEntry {
key: IntermediateKey::Str(key.to_string()),
doc_count: *doc_count,
sub_aggregation_res: Default::default(),
sub_aggregation: Default::default(),
from: None,
to: None,
},
@@ -930,7 +920,7 @@ mod tests {
doc_count: *doc_count,
from: None,
to: None,
sub_aggregation_res: get_sub_test_tree(&[(
sub_aggregation: get_sub_test_tree(&[(
sub_aggregation_key.to_string(),
*sub_aggregation_count,
)]),

16
src/aggregation/metric/average.rs
View File

@@ -52,8 +52,10 @@ pub struct IntermediateAverage {
impl IntermediateAverage {
/// Creates a new [`IntermediateAverage`] instance from a [`SegmentStatsCollector`].
pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
Self { stats }
pub(crate) fn from_collector(collector: SegmentStatsCollector) -> Self {
Self {
stats: collector.stats,
}
}
/// Merges the other intermediate result into self.
pub fn merge_fruits(&mut self, other: IntermediateAverage) {
@@ -63,16 +65,6 @@ impl IntermediateAverage {
pub fn finalize(&self) -> Option<f64> {
self.stats.finalize().avg
}
/// Returns the sum of all collected values.
pub fn sum(&self) -> f64 {
self.stats.sum
}
/// Returns the count of all collected values.
pub fn count(&self) -> u64 {
self.stats.count
}
}
#[cfg(test)]

129
src/aggregation/metric/cardinality.rs
View File

@@ -2,7 +2,7 @@ use std::collections::hash_map::DefaultHasher;
use std::hash::{BuildHasher, Hasher};
use columnar::column_values::CompactSpaceU64Accessor;
use columnar::{Column, ColumnType, Dictionary, StrColumn};
use columnar::{Column, ColumnBlockAccessor, ColumnType, Dictionary, StrColumn};
use common::f64_to_u64;
use hyperloglogplus::{HyperLogLog, HyperLogLogPlus};
use rustc_hash::FxHashSet;
@@ -106,6 +106,8 @@ pub struct CardinalityAggReqData {
pub str_dict_column: Option<StrColumn>,
/// The missing value normalized to the internal u64 representation of the field type.
pub missing_value_for_accessor: Option<u64>,
/// The column block accessor to access the fast field values.
pub(crate) column_block_accessor: ColumnBlockAccessor<u64>,
/// The name of the aggregation.
pub name: String,
/// The aggregation request.
@@ -133,34 +135,45 @@ impl CardinalityAggregationReq {
}
}
#[derive(Clone, Debug)]
#[derive(Clone, Debug, PartialEq)]
pub(crate) struct SegmentCardinalityCollector {
buckets: Vec<SegmentCardinalityCollectorBucket>,
accessor_idx: usize,
/// The column accessor to access the fast field values.
accessor: Column<u64>,
/// The column_type of the field.
column_type: ColumnType,
/// The missing value normalized to the internal u64 representation of the field type.
missing_value_for_accessor: Option<u64>,
}
#[derive(Clone, Debug, PartialEq, Default)]
pub(crate) struct SegmentCardinalityCollectorBucket {
cardinality: CardinalityCollector,
entries: FxHashSet<u64>,
accessor_idx: usize,
}
impl SegmentCardinalityCollectorBucket {
pub fn new(column_type: ColumnType) -> Self {
impl SegmentCardinalityCollector {
pub fn from_req(column_type: ColumnType, accessor_idx: usize) -> Self {
Self {
cardinality: CardinalityCollector::new(column_type as u8),
entries: FxHashSet::default(),
entries: Default::default(),
accessor_idx,
}
}
fn fetch_block_with_field(
&mut self,
docs: &[crate::DocId],
agg_data: &mut CardinalityAggReqData,
) {
if let Some(missing) = agg_data.missing_value_for_accessor {
agg_data.column_block_accessor.fetch_block_with_missing(
docs,
&agg_data.accessor,
missing,
);
} else {
agg_data
.column_block_accessor
.fetch_block(docs, &agg_data.accessor);
}
}
fn into_intermediate_metric_result(
mut self,
req_data: &CardinalityAggReqData,
agg_data: &AggregationsSegmentCtx,
) -> crate::Result<IntermediateMetricResult> {
let req_data = &agg_data.get_cardinality_req_data(self.accessor_idx);
if req_data.column_type == ColumnType::Str {
let fallback_dict = Dictionary::empty();
let dict = req_data
@@ -181,7 +194,6 @@ impl SegmentCardinalityCollectorBucket {
term_ids.push(term_ord as u32);
}
}
term_ids.sort_unstable();
dict.sorted_ords_to_term_cb(term_ids.iter().map(|term| *term as u64), |term| {
self.cardinality.sketch.insert_any(&term);
@@ -215,49 +227,16 @@ impl SegmentCardinalityCollectorBucket {
}
}
impl SegmentCardinalityCollector {
pub fn from_req(
column_type: ColumnType,
accessor_idx: usize,
accessor: Column<u64>,
missing_value_for_accessor: Option<u64>,
) -> Self {
Self {
buckets: vec![SegmentCardinalityCollectorBucket::new(column_type); 1],
column_type,
accessor_idx,
accessor,
missing_value_for_accessor,
}
}
fn fetch_block_with_field(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) {
agg_data.column_block_accessor.fetch_block_with_missing(
docs,
&self.accessor,
self.missing_value_for_accessor,
);
}
}
impl SegmentAggregationCollector for SegmentCardinalityCollector {
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
self.prepare_max_bucket(parent_bucket_id, agg_data)?;
let req_data = &agg_data.get_cardinality_req_data(self.accessor_idx);
let name = req_data.name.to_string();
// take the bucket in buckets and replace it with a new empty one
let bucket = std::mem::take(&mut self.buckets[parent_bucket_id as usize]);
let intermediate_result = bucket.into_intermediate_metric_result(req_data)?;
let intermediate_result = self.into_intermediate_metric_result(agg_data)?;
results.push(
name,
IntermediateAggregationResult::Metric(intermediate_result),
@@ -268,20 +247,27 @@ impl SegmentAggregationCollector for SegmentCardinalityCollector {
fn collect(
&mut self,
parent_bucket_id: BucketId,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)
}
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.fetch_block_with_field(docs, agg_data);
let bucket = &mut self.buckets[parent_bucket_id as usize];
let req_data = agg_data.get_cardinality_req_data_mut(self.accessor_idx);
self.fetch_block_with_field(docs, req_data);
let col_block_accessor = &agg_data.column_block_accessor;
if self.column_type == ColumnType::Str {
let col_block_accessor = &req_data.column_block_accessor;
if req_data.column_type == ColumnType::Str {
for term_ord in col_block_accessor.iter_vals() {
bucket.entries.insert(term_ord);
self.entries.insert(term_ord);
}
} else if self.column_type == ColumnType::IpAddr {
let compact_space_accessor = self
} else if req_data.column_type == ColumnType::IpAddr {
let compact_space_accessor = req_data
.accessor
.values
.clone()
@@ -296,29 +282,16 @@ impl SegmentAggregationCollector for SegmentCardinalityCollector {
})?;
for val in col_block_accessor.iter_vals() {
let val: u128 = compact_space_accessor.compact_to_u128(val as u32);
bucket.cardinality.sketch.insert_any(&val);
self.cardinality.sketch.insert_any(&val);
}
} else {
for val in col_block_accessor.iter_vals() {
bucket.cardinality.sketch.insert_any(&val);
self.cardinality.sketch.insert_any(&val);
}
}
Ok(())
}
fn prepare_max_bucket(
&mut self,
max_bucket: BucketId,
_agg_data: &AggregationsSegmentCtx,
) -> crate::Result<()> {
if max_bucket as usize >= self.buckets.len() {
self.buckets.resize_with(max_bucket as usize + 1, || {
SegmentCardinalityCollectorBucket::new(self.column_type)
});
}
Ok(())
}
}
#[derive(Clone, Debug, Serialize, Deserialize)]
@@ -340,7 +313,7 @@ impl PartialEq for CardinalityCollector {
impl CardinalityCollector {
/// Compute the final cardinality estimate.
pub fn finalize(&self) -> Option<f64> {
pub fn finalize(self) -> Option<f64> {
Some(self.sketch.clone().count().trunc())
}

6
src/aggregation/metric/count.rs
View File

@@ -52,8 +52,10 @@ pub struct IntermediateCount {
impl IntermediateCount {
/// Creates a new [`IntermediateCount`] instance from a [`SegmentStatsCollector`].
pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
Self { stats }
pub(crate) fn from_collector(collector: SegmentStatsCollector) -> Self {
Self {
stats: collector.stats,
}
}
/// Merges the other intermediate result into self.
pub fn merge_fruits(&mut self, other: IntermediateCount) {

108
src/aggregation/metric/extended_stats.rs
View File

@@ -8,9 +8,10 @@ use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
use crate::aggregation::metric::MetricAggReqData;
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::TantivyError;
use crate::{DocId, TantivyError};
/// A multi-value metric aggregation that computes a collection of extended statistics
/// on numeric values that are extracted
@@ -317,28 +318,51 @@ impl IntermediateExtendedStats {
}
}
#[derive(Clone, Debug)]
#[derive(Clone, Debug, PartialEq)]
pub(crate) struct SegmentExtendedStatsCollector {
name: String,
missing: Option<u64>,
field_type: ColumnType,
accessor: columnar::Column<u64>,
buckets: Vec<IntermediateExtendedStats>,
sigma: Option<f64>,
pub(crate) extended_stats: IntermediateExtendedStats,
pub(crate) accessor_idx: usize,
val_cache: Vec<u64>,
}
impl SegmentExtendedStatsCollector {
pub fn from_req(req: &MetricAggReqData, sigma: Option<f64>) -> Self {
let missing = req
.missing
.and_then(|val| f64_to_fastfield_u64(val, &req.field_type));
pub fn from_req(
field_type: ColumnType,
sigma: Option<f64>,
accessor_idx: usize,
missing: Option<f64>,
) -> Self {
let missing = missing.and_then(|val| f64_to_fastfield_u64(val, &field_type));
Self {
name: req.name.clone(),
field_type: req.field_type,
accessor: req.accessor.clone(),
field_type,
extended_stats: IntermediateExtendedStats::with_sigma(sigma),
accessor_idx,
missing,
buckets: vec![IntermediateExtendedStats::with_sigma(sigma); 16],
sigma,
val_cache: Default::default(),
}
}
#[inline]
pub(crate) fn collect_block_with_field(
&mut self,
docs: &[DocId],
req_data: &mut MetricAggReqData,
) {
if let Some(missing) = self.missing.as_ref() {
req_data.column_block_accessor.fetch_block_with_missing(
docs,
&req_data.accessor,
*missing,
);
} else {
req_data
.column_block_accessor
.fetch_block(docs, &req_data.accessor);
}
for val in req_data.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.extended_stats.collect(val1);
}
}
}
@@ -346,18 +370,15 @@ impl SegmentExtendedStatsCollector {
impl SegmentAggregationCollector for SegmentExtendedStatsCollector {
#[inline]
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
let name = self.name.clone();
self.prepare_max_bucket(parent_bucket_id, agg_data)?;
let extended_stats = std::mem::take(&mut self.buckets[parent_bucket_id as usize]);
let name = agg_data.get_metric_req_data(self.accessor_idx).name.clone();
results.push(
name,
IntermediateAggregationResult::Metric(IntermediateMetricResult::ExtendedStats(
extended_stats,
self.extended_stats,
)),
)?;
@@ -367,36 +388,39 @@ impl SegmentAggregationCollector for SegmentExtendedStatsCollector {
#[inline]
fn collect(
&mut self,
parent_bucket_id: BucketId,
docs: &[crate::DocId],
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
let mut extended_stats = self.buckets[parent_bucket_id as usize].clone();
agg_data
.column_block_accessor
.fetch_block_with_missing(docs, &self.accessor, self.missing);
for val in agg_data.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, self.field_type);
extended_stats.collect(val1);
let req_data = agg_data.get_metric_req_data(self.accessor_idx);
if let Some(missing) = self.missing {
let mut has_val = false;
for val in req_data.accessor.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.extended_stats.collect(val1);
has_val = true;
}
if !has_val {
self.extended_stats
.collect(f64_from_fastfield_u64(missing, &self.field_type));
}
} else {
for val in req_data.accessor.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.extended_stats.collect(val1);
}
}
// store back
self.buckets[parent_bucket_id as usize] = extended_stats;
Ok(())
}
fn prepare_max_bucket(
#[inline]
fn collect_block(
&mut self,
max_bucket: BucketId,
_agg_data: &AggregationsSegmentCtx,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
if self.buckets.len() <= max_bucket as usize {
self.buckets.resize_with(max_bucket as usize + 1, || {
IntermediateExtendedStats::with_sigma(self.sigma)
});
}
let req_data = agg_data.get_metric_req_data_mut(self.accessor_idx);
self.collect_block_with_field(docs, req_data);
Ok(())
}
}

6
src/aggregation/metric/max.rs
View File

@@ -52,8 +52,10 @@ pub struct IntermediateMax {
impl IntermediateMax {
/// Creates a new [`IntermediateMax`] instance from a [`SegmentStatsCollector`].
pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
Self { stats }
pub(crate) fn from_collector(collector: SegmentStatsCollector) -> Self {
Self {
stats: collector.stats,
}
}
/// Merges the other intermediate result into self.
pub fn merge_fruits(&mut self, other: IntermediateMax) {

6
src/aggregation/metric/min.rs
View File

@@ -52,8 +52,10 @@ pub struct IntermediateMin {
impl IntermediateMin {
/// Creates a new [`IntermediateMin`] instance from a [`SegmentStatsCollector`].
pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
Self { stats }
pub(crate) fn from_collector(collector: SegmentStatsCollector) -> Self {
Self {
stats: collector.stats,
}
}
/// Merges the other intermediate result into self.
pub fn merge_fruits(&mut self, other: IntermediateMin) {

161
src/aggregation/metric/mod.rs
View File

@@ -31,7 +31,7 @@ use std::collections::HashMap;
pub use average::*;
pub use cardinality::*;
use columnar::{Column, ColumnType};
use columnar::{Column, ColumnBlockAccessor, ColumnType};
pub use count::*;
pub use extended_stats::*;
pub use max::*;
@@ -55,6 +55,8 @@ pub struct MetricAggReqData {
pub field_type: ColumnType,
/// The missing value normalized to the internal u64 representation of the field type.
pub missing_u64: Option<u64>,
/// The column block accessor to access the fast field values.
pub column_block_accessor: ColumnBlockAccessor<u64>,
/// The column accessor to access the fast field values.
pub accessor: Column<u64>,
/// Used when converting to intermediate result
@@ -93,41 +95,6 @@ impl From<Option<f64>> for SingleMetricResult {
}
}
/// Average metric result with intermediate data for merging.
///
/// Unlike [`SingleMetricResult`], this struct includes the raw `sum` and `count`
/// values that can be used for multi-step query merging.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct AverageMetricResult {
/// The computed average value. None if no documents matched.
pub value: Option<f64>,
/// The sum of all values (for multi-step merging).
pub sum: f64,
/// The count of all values (for multi-step merging).
pub count: u64,
}
/// Cardinality metric result with computed value and raw HLL sketch for multi-step merging.
///
/// The `value` field contains the computed cardinality estimate.
/// The `sketch` field contains the serialized HyperLogLog++ sketch that can be used
/// for merging results across multiple query steps.
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct CardinalityMetricResult {
/// The computed cardinality estimate.
pub value: Option<f64>,
/// The serialized HyperLogLog++ sketch for multi-step merging.
#[serde(skip_serializing_if = "Option::is_none")]
pub sketch: Option<CardinalityCollector>,
}
impl PartialEq for CardinalityMetricResult {
fn eq(&self, other: &Self) -> bool {
// Only compare values, not sketch (sketch comparison is complex)
self.value == other.value
}
}
/// This is the wrapper of percentile entries, which can be vector or hashmap
/// depending on if it's keyed or not.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
@@ -146,26 +113,13 @@ pub struct PercentileValuesVecEntry {
value: f64,
}
/// Percentiles metric result with computed values and raw sketch for multi-step merging.
/// Single-metric aggregations use this common result structure.
///
/// The `values` field contains the computed percentile values.
/// The `sketch` field contains the serialized DDSketch that can be used for merging
/// results across multiple query steps.
#[derive(Clone, Debug, Serialize, Deserialize)]
/// Main reason to wrap it in value is to match elasticsearch output structure.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct PercentilesMetricResult {
/// The computed percentile values.
/// The result of the percentile metric.
pub values: PercentileValues,
/// The serialized DDSketch for multi-step merging.
/// This is the raw sketch data that can be deserialized and merged with other sketches.
#[serde(skip_serializing_if = "Option::is_none")]
pub sketch: Option<PercentilesCollector>,
}
impl PartialEq for PercentilesMetricResult {
fn eq(&self, other: &Self) -> bool {
// Only compare values, not sketch (sketch comparison is complex)
self.values == other.values
}
}
/// The top_hits metric results entry
@@ -246,105 +200,4 @@ mod tests {
assert_eq!(aggregations_res_json["price_min"]["value"], 0.0);
assert_eq!(aggregations_res_json["price_sum"]["value"], 15.0);
}
#[test]
fn test_average_returns_sum_and_count() {
let mut schema_builder = Schema::builder();
let field_options = NumericOptions::default().set_fast();
let field = schema_builder.add_f64_field("price", field_options);
let index = Index::create_in_ram(schema_builder.build());
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// Add documents with values 0, 1, 2, 3, 4, 5
// sum = 15, count = 6, avg = 2.5
for i in 0..6 {
index_writer
.add_document(doc!(
field => i as f64,
))
.unwrap();
}
index_writer.commit().unwrap();
let aggregations_json = r#"{ "price_avg": { "avg": { "field": "price" } } }"#;
let aggregations: Aggregations = serde_json::from_str(aggregations_json).unwrap();
let collector = AggregationCollector::from_aggs(aggregations, Default::default());
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let aggregations_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
let aggregations_res_json = serde_json::to_value(aggregations_res).unwrap();
// Verify all three fields are present and correct
assert_eq!(aggregations_res_json["price_avg"]["value"], 2.5);
assert_eq!(aggregations_res_json["price_avg"]["sum"], 15.0);
assert_eq!(aggregations_res_json["price_avg"]["count"], 6);
}
#[test]
fn test_percentiles_returns_sketch() {
let mut schema_builder = Schema::builder();
let field_options = NumericOptions::default().set_fast();
let field = schema_builder.add_f64_field("latency", field_options);
let index = Index::create_in_ram(schema_builder.build());
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// Add documents with latency values
for i in 0..100 {
index_writer
.add_document(doc!(
field => i as f64,
))
.unwrap();
}
index_writer.commit().unwrap();
let aggregations_json =
r#"{ "latency_percentiles": { "percentiles": { "field": "latency" } } }"#;
let aggregations: Aggregations = serde_json::from_str(aggregations_json).unwrap();
let collector = AggregationCollector::from_aggs(aggregations, Default::default());
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let aggregations_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
let aggregations_res_json = serde_json::to_value(aggregations_res).unwrap();
// Verify percentile values are present
assert!(aggregations_res_json["latency_percentiles"]["values"].is_object());
// Verify sketch is present (serialized DDSketch)
assert!(aggregations_res_json["latency_percentiles"]["sketch"].is_object());
}
#[test]
fn test_cardinality_returns_sketch() {
let mut schema_builder = Schema::builder();
let field_options = NumericOptions::default().set_fast();
let field = schema_builder.add_u64_field("user_id", field_options);
let index = Index::create_in_ram(schema_builder.build());
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// Add documents with some duplicate user_ids
for i in 0..50 {
index_writer
.add_document(doc!(
field => (i % 10) as u64, // 10 unique values
))
.unwrap();
}
index_writer.commit().unwrap();
let aggregations_json = r#"{ "unique_users": { "cardinality": { "field": "user_id" } } }"#;
let aggregations: Aggregations = serde_json::from_str(aggregations_json).unwrap();
let collector = AggregationCollector::from_aggs(aggregations, Default::default());
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let aggregations_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
let aggregations_res_json = serde_json::to_value(aggregations_res).unwrap();
// Verify cardinality value is present and approximately correct
let cardinality = aggregations_res_json["unique_users"]["value"]
.as_f64()
.unwrap();
assert!(cardinality >= 9.0 && cardinality <= 11.0); // HLL is approximate
// Verify sketch is present (serialized HyperLogLog++)
assert!(aggregations_res_json["unique_users"]["sketch"].is_object());
}
}

114
src/aggregation/metric/percentiles.rs
View File

@@ -7,9 +7,10 @@ use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
use crate::aggregation::metric::MetricAggReqData;
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::TantivyError;
use crate::{DocId, TantivyError};
/// # Percentiles
///
@@ -130,16 +131,10 @@ impl PercentilesAggregationReq {
}
}
#[derive(Clone, Debug)]
#[derive(Clone, Debug, PartialEq)]
pub(crate) struct SegmentPercentilesCollector {
pub(crate) buckets: Vec<PercentilesCollector>,
pub(crate) percentiles: PercentilesCollector,
pub(crate) accessor_idx: usize,
/// The type of the field.
pub field_type: ColumnType,
/// The missing value normalized to the internal u64 representation of the field type.
pub missing_u64: Option<u64>,
/// The column accessor to access the fast field values.
pub accessor: Column<u64>,
}
#[derive(Clone, Serialize, Deserialize)]
@@ -178,9 +173,6 @@ fn format_percentile(percentile: f64) -> String {
impl PercentilesCollector {
/// Convert result into final result. This will query the quantils from the underlying quantil
/// collector.
///
/// The result includes both the computed percentile values and the raw DDSketch
/// for multi-step query merging.
pub fn into_final_result(self, req: &PercentilesAggregationReq) -> PercentilesMetricResult {
let percentiles: &[f64] = req
.percents
@@ -213,15 +205,7 @@ impl PercentilesCollector {
.collect(),
)
};
PercentilesMetricResult {
values,
sketch: Some(self),
}
}
/// Returns a reference to the underlying DDSketch.
pub fn sketch(&self) -> &sketches_ddsketch::DDSketch {
&self.sketch
PercentilesMetricResult { values }
}
fn new() -> Self {
@@ -245,18 +229,33 @@ impl PercentilesCollector {
}
impl SegmentPercentilesCollector {
pub fn from_req_and_validate(
field_type: ColumnType,
missing_u64: Option<u64>,
accessor: Column<u64>,
accessor_idx: usize,
) -> Self {
Self {
buckets: Vec::with_capacity(64),
field_type,
missing_u64,
accessor,
pub fn from_req_and_validate(accessor_idx: usize) -> crate::Result<Self> {
Ok(Self {
percentiles: PercentilesCollector::new(),
accessor_idx,
})
}
#[inline]
pub(crate) fn collect_block_with_field(
&mut self,
docs: &[DocId],
req_data: &mut MetricAggReqData,
) {
if let Some(missing) = req_data.missing_u64.as_ref() {
req_data.column_block_accessor.fetch_block_with_missing(
docs,
&req_data.accessor,
*missing,
);
} else {
req_data
.column_block_accessor
.fetch_block(docs, &req_data.accessor);
}
for val in req_data.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
self.percentiles.collect(val1);
}
}
}
@@ -264,18 +263,12 @@ impl SegmentPercentilesCollector {
impl SegmentAggregationCollector for SegmentPercentilesCollector {
#[inline]
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
let name = agg_data.get_metric_req_data(self.accessor_idx).name.clone();
self.prepare_max_bucket(parent_bucket_id, agg_data)?;
// Swap collector with an empty one to avoid cloning
let percentiles_collector = std::mem::take(&mut self.buckets[parent_bucket_id as usize]);
let intermediate_metric_result =
IntermediateMetricResult::Percentiles(percentiles_collector);
let intermediate_metric_result = IntermediateMetricResult::Percentiles(self.percentiles);
results.push(
name,
@@ -288,33 +281,40 @@ impl SegmentAggregationCollector for SegmentPercentilesCollector {
#[inline]
fn collect(
&mut self,
parent_bucket_id: BucketId,
docs: &[crate::DocId],
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
let percentiles = &mut self.buckets[parent_bucket_id as usize];
agg_data.column_block_accessor.fetch_block_with_missing(
docs,
&self.accessor,
self.missing_u64,
);
let req_data = agg_data.get_metric_req_data(self.accessor_idx);
for val in agg_data.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, self.field_type);
percentiles.collect(val1);
if let Some(missing) = req_data.missing_u64 {
let mut has_val = false;
for val in req_data.accessor.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
self.percentiles.collect(val1);
has_val = true;
}
if !has_val {
self.percentiles
.collect(f64_from_fastfield_u64(missing, &req_data.field_type));
}
} else {
for val in req_data.accessor.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
self.percentiles.collect(val1);
}
}
Ok(())
}
fn prepare_max_bucket(
#[inline]
fn collect_block(
&mut self,
max_bucket: BucketId,
_agg_data: &AggregationsSegmentCtx,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
while self.buckets.len() <= max_bucket as usize {
self.buckets.push(PercentilesCollector::new());
}
let req_data = agg_data.get_metric_req_data_mut(self.accessor_idx);
self.collect_block_with_field(docs, req_data);
Ok(())
}
}

194
src/aggregation/metric/stats.rs
View File

@@ -1,6 +1,5 @@
use std::fmt::Debug;
use columnar::{Column, ColumnType};
use serde::{Deserialize, Serialize};
use super::*;
@@ -8,9 +7,10 @@ use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
use crate::aggregation::metric::MetricAggReqData;
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::TantivyError;
use crate::{DocId, TantivyError};
/// A multi-value metric aggregation that computes a collection of statistics on numeric values that
/// are extracted from the aggregated documents.
@@ -83,7 +83,7 @@ impl Stats {
/// Intermediate result of the stats aggregation that can be combined with other intermediate
/// results.
#[derive(Clone, Copy, Debug, PartialEq, Serialize, Deserialize)]
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct IntermediateStats {
/// The number of extracted values.
pub(crate) count: u64,
@@ -187,75 +187,75 @@ pub enum StatsType {
Percentiles,
}
fn create_collector<const TYPE_ID: u8>(
req: &MetricAggReqData,
) -> Box<dyn SegmentAggregationCollector> {
Box::new(SegmentStatsCollector::<TYPE_ID> {
name: req.name.clone(),
collecting_for: req.collecting_for,
is_number_or_date_type: req.is_number_or_date_type,
missing_u64: req.missing_u64,
accessor: req.accessor.clone(),
buckets: vec![IntermediateStats::default()],
})
#[derive(Clone, Debug)]
pub(crate) struct SegmentStatsCollector {
pub(crate) stats: IntermediateStats,
pub(crate) accessor_idx: usize,
}
/// Build a concrete `SegmentStatsCollector` depending on the column type.
pub(crate) fn build_segment_stats_collector(
req: &MetricAggReqData,
) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
match req.field_type {
ColumnType::I64 => Ok(create_collector::<{ ColumnType::I64 as u8 }>(req)),
ColumnType::U64 => Ok(create_collector::<{ ColumnType::U64 as u8 }>(req)),
ColumnType::F64 => Ok(create_collector::<{ ColumnType::F64 as u8 }>(req)),
ColumnType::Bool => Ok(create_collector::<{ ColumnType::Bool as u8 }>(req)),
ColumnType::DateTime => Ok(create_collector::<{ ColumnType::DateTime as u8 }>(req)),
ColumnType::Bytes => Ok(create_collector::<{ ColumnType::Bytes as u8 }>(req)),
ColumnType::Str => Ok(create_collector::<{ ColumnType::Str as u8 }>(req)),
ColumnType::IpAddr => Ok(create_collector::<{ ColumnType::IpAddr as u8 }>(req)),
impl SegmentStatsCollector {
pub fn from_req(accessor_idx: usize) -> Self {
Self {
stats: IntermediateStats::default(),
accessor_idx,
}
}
#[inline]
pub(crate) fn collect_block_with_field(
&mut self,
docs: &[DocId],
req_data: &mut MetricAggReqData,
) {
if let Some(missing) = req_data.missing_u64.as_ref() {
req_data.column_block_accessor.fetch_block_with_missing(
docs,
&req_data.accessor,
*missing,
);
} else {
req_data
.column_block_accessor
.fetch_block(docs, &req_data.accessor);
}
if req_data.is_number_or_date_type {
for val in req_data.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
self.stats.collect(val1);
}
} else {
for _val in req_data.column_block_accessor.iter_vals() {
// we ignore the value and simply record that we got something
self.stats.collect(0.0);
}
}
}
}
#[repr(C)]
#[derive(Clone, Debug)]
pub(crate) struct SegmentStatsCollector<const COLUMN_TYPE_ID: u8> {
pub(crate) missing_u64: Option<u64>,
pub(crate) accessor: Column<u64>,
pub(crate) is_number_or_date_type: bool,
pub(crate) buckets: Vec<IntermediateStats>,
pub(crate) name: String,
pub(crate) collecting_for: StatsType,
}
impl<const COLUMN_TYPE_ID: u8> SegmentAggregationCollector
for SegmentStatsCollector<COLUMN_TYPE_ID>
{
impl SegmentAggregationCollector for SegmentStatsCollector {
#[inline]
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
let name = self.name.clone();
let req = agg_data.get_metric_req_data(self.accessor_idx);
let name = req.name.clone();
self.prepare_max_bucket(parent_bucket_id, agg_data)?;
let stats = self.buckets[parent_bucket_id as usize];
let intermediate_metric_result = match self.collecting_for {
let intermediate_metric_result = match req.collecting_for {
StatsType::Average => {
IntermediateMetricResult::Average(IntermediateAverage::from_stats(stats))
IntermediateMetricResult::Average(IntermediateAverage::from_collector(*self))
}
StatsType::Count => {
IntermediateMetricResult::Count(IntermediateCount::from_stats(stats))
IntermediateMetricResult::Count(IntermediateCount::from_collector(*self))
}
StatsType::Max => IntermediateMetricResult::Max(IntermediateMax::from_stats(stats)),
StatsType::Min => IntermediateMetricResult::Min(IntermediateMin::from_stats(stats)),
StatsType::Stats => IntermediateMetricResult::Stats(stats),
StatsType::Sum => IntermediateMetricResult::Sum(IntermediateSum::from_stats(stats)),
StatsType::Max => IntermediateMetricResult::Max(IntermediateMax::from_collector(*self)),
StatsType::Min => IntermediateMetricResult::Min(IntermediateMin::from_collector(*self)),
StatsType::Stats => IntermediateMetricResult::Stats(self.stats),
StatsType::Sum => IntermediateMetricResult::Sum(IntermediateSum::from_collector(*self)),
_ => {
return Err(TantivyError::InvalidArgument(format!(
"Unsupported stats type for stats aggregation: {:?}",
self.collecting_for
req.collecting_for
)))
}
};
@@ -271,67 +271,41 @@ impl<const COLUMN_TYPE_ID: u8> SegmentAggregationCollector
#[inline]
fn collect(
&mut self,
parent_bucket_id: BucketId,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
let req_data = agg_data.get_metric_req_data(self.accessor_idx);
if let Some(missing) = req_data.missing_u64 {
let mut has_val = false;
for val in req_data.accessor.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
self.stats.collect(val1);
has_val = true;
}
if !has_val {
self.stats
.collect(f64_from_fastfield_u64(missing, &req_data.field_type));
}
} else {
for val in req_data.accessor.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
self.stats.collect(val1);
}
}
Ok(())
}
#[inline]
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
// TODO: remove once we fetch all values for all bucket ids in one go
if docs.len() == 1 && self.missing_u64.is_none() {
collect_stats::<COLUMN_TYPE_ID>(
&mut self.buckets[parent_bucket_id as usize],
self.accessor.values_for_doc(docs[0]),
self.is_number_or_date_type,
)?;
return Ok(());
}
agg_data.column_block_accessor.fetch_block_with_missing(
docs,
&self.accessor,
self.missing_u64,
);
collect_stats::<COLUMN_TYPE_ID>(
&mut self.buckets[parent_bucket_id as usize],
agg_data.column_block_accessor.iter_vals(),
self.is_number_or_date_type,
)?;
let req_data = agg_data.get_metric_req_data_mut(self.accessor_idx);
self.collect_block_with_field(docs, req_data);
Ok(())
}
fn prepare_max_bucket(
&mut self,
max_bucket: BucketId,
_agg_data: &AggregationsSegmentCtx,
) -> crate::Result<()> {
let required_buckets = (max_bucket as usize) + 1;
if self.buckets.len() < required_buckets {
self.buckets
.resize_with(required_buckets, IntermediateStats::default);
}
Ok(())
}
}
#[inline]
fn collect_stats<const COLUMN_TYPE_ID: u8>(
stats: &mut IntermediateStats,
vals: impl Iterator<Item = u64>,
is_number_or_date_type: bool,
) -> crate::Result<()> {
if is_number_or_date_type {
for val in vals {
let val1 = convert_to_f64::<COLUMN_TYPE_ID>(val);
stats.collect(val1);
}
} else {
for _val in vals {
// we ignore the value and simply record that we got something
stats.collect(0.0);
}
}
Ok(())
}
#[cfg(test)]

6
src/aggregation/metric/sum.rs
View File

@@ -52,8 +52,10 @@ pub struct IntermediateSum {
impl IntermediateSum {
/// Creates a new [`IntermediateSum`] instance from a [`SegmentStatsCollector`].
pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
Self { stats }
pub(crate) fn from_collector(collector: SegmentStatsCollector) -> Self {
Self {
stats: collector.stats,
}
}
/// Merges the other intermediate result into self.
pub fn merge_fruits(&mut self, other: IntermediateSum) {

127
src/aggregation/metric/top_hits.rs
View File

@@ -15,11 +15,12 @@ use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateMetricResult,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::{AggregationError, BucketId};
use crate::aggregation::AggregationError;
use crate::collector::sort_key::ReverseComparator;
use crate::collector::TopNComputer;
use crate::schema::OwnedValue;
use crate::{DocAddress, DocId, SegmentOrdinal};
// duplicate import removed; already imported above
/// Contains all information required by the TopHitsSegmentCollector to perform the
/// top_hits aggregation on a segment.
@@ -471,10 +472,7 @@ impl TopHitsTopNComputer {
/// Create a new TopHitsCollector
pub fn new(req: &TopHitsAggregationReq) -> Self {
Self {
top_n: TopNComputer::new_with_comparator(
req.size + req.from.unwrap_or(0),
ReverseComparator,
),
top_n: TopNComputer::new(req.size + req.from.unwrap_or(0)),
req: req.clone(),
}
}
@@ -520,8 +518,7 @@ impl TopHitsTopNComputer {
pub(crate) struct TopHitsSegmentCollector {
segment_ordinal: SegmentOrdinal,
accessor_idx: usize,
buckets: Vec<TopNComputer<Vec<DocValueAndOrder>, DocAddress, ReverseComparator>>,
num_hits: usize,
top_n: TopNComputer<Vec<DocValueAndOrder>, DocAddress, ReverseComparator>,
}
impl TopHitsSegmentCollector {
@@ -530,29 +527,19 @@ impl TopHitsSegmentCollector {
accessor_idx: usize,
segment_ordinal: SegmentOrdinal,
) -> Self {
let num_hits = req.size + req.from.unwrap_or(0);
Self {
num_hits,
top_n: TopNComputer::new(req.size + req.from.unwrap_or(0)),
segment_ordinal,
accessor_idx,
buckets: vec![TopNComputer::new_with_comparator(num_hits, ReverseComparator); 1],
}
}
fn get_top_hits_computer(
&mut self,
parent_bucket_id: BucketId,
fn into_top_hits_collector(
self,
value_accessors: &HashMap<String, Vec<DynamicColumn>>,
req: &TopHitsAggregationReq,
) -> TopHitsTopNComputer {
if parent_bucket_id as usize >= self.buckets.len() {
return TopHitsTopNComputer::new(req);
}
let top_n = std::mem::replace(
&mut self.buckets[parent_bucket_id as usize],
TopNComputer::new(0),
);
let mut top_hits_computer = TopHitsTopNComputer::new(req);
let top_results = top_n.into_vec();
let top_results = self.top_n.into_vec();
for res in top_results {
let doc_value_fields = req.get_document_field_data(value_accessors, res.doc.doc_id);
@@ -567,24 +554,54 @@ impl TopHitsSegmentCollector {
top_hits_computer
}
/// TODO add a specialized variant for a single sort field
fn collect_with(
&mut self,
doc_id: crate::DocId,
req: &TopHitsAggregationReq,
accessors: &[(Column<u64>, ColumnType)],
) -> crate::Result<()> {
let sorts: Vec<DocValueAndOrder> = req
.sort
.iter()
.enumerate()
.map(|(idx, KeyOrder { order, .. })| {
let order = *order;
let value = accessors
.get(idx)
.expect("could not find field in accessors")
.0
.values_for_doc(doc_id)
.next();
DocValueAndOrder { value, order }
})
.collect();
self.top_n.push(
sorts,
DocAddress {
segment_ord: self.segment_ordinal,
doc_id,
},
);
Ok(())
}
}
impl SegmentAggregationCollector for TopHitsSegmentCollector {
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut crate::aggregation::intermediate_agg_result::IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
let req_data = agg_data.get_top_hits_req_data(self.accessor_idx);
let value_accessors = &req_data.value_accessors;
let intermediate_result = IntermediateMetricResult::TopHits(self.get_top_hits_computer(
parent_bucket_id,
value_accessors,
&req_data.req,
));
let intermediate_result = IntermediateMetricResult::TopHits(
self.into_top_hits_collector(value_accessors, &req_data.req),
);
results.push(
req_data.name.to_string(),
IntermediateAggregationResult::Metric(intermediate_result),
@@ -594,54 +611,24 @@ impl SegmentAggregationCollector for TopHitsSegmentCollector {
/// TODO: Consider a caching layer to reduce the call overhead
fn collect(
&mut self,
parent_bucket_id: BucketId,
docs: &[crate::DocId],
doc_id: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
let top_n = &mut self.buckets[parent_bucket_id as usize];
let req_data = agg_data.get_top_hits_req_data(self.accessor_idx);
let req = &req_data.req;
let accessors = &req_data.accessors;
for &doc_id in docs {
// TODO: this is terrible, a new vec is allocated for every doc
// We can fetch blocks instead
// We don't need to store the order for every value
let sorts: Vec<DocValueAndOrder> = req
.sort
.iter()
.enumerate()
.map(|(idx, KeyOrder { order, .. })| {
let order = *order;
let value = accessors
.get(idx)
.expect("could not find field in accessors")
.0
.values_for_doc(doc_id)
.next();
DocValueAndOrder { value, order }
})
.collect();
top_n.push(
sorts,
DocAddress {
segment_ord: self.segment_ordinal,
doc_id,
},
);
}
self.collect_with(doc_id, &req_data.req, &req_data.accessors)?;
Ok(())
}
fn prepare_max_bucket(
fn collect_block(
&mut self,
max_bucket: BucketId,
_agg_data: &AggregationsSegmentCtx,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.buckets.resize(
(max_bucket as usize) + 1,
TopNComputer::new_with_comparator(self.num_hits, ReverseComparator),
);
let req_data = agg_data.get_top_hits_req_data(self.accessor_idx);
// TODO: Consider getting fields with the column block accessor.
for doc in docs {
self.collect_with(*doc, &req_data.req, &req_data.accessors)?;
}
Ok(())
}
}
@@ -759,7 +746,7 @@ mod tests {
],
"from": 0,
}
}
}
}))
.unwrap();
@@ -888,7 +875,7 @@ mod tests {
"mixed.*",
],
}
}
}
}))?;
let collector = AggregationCollector::from_aggs(d, Default::default());

49
src/aggregation/mod.rs
View File

@@ -133,7 +133,7 @@ mod agg_limits;
pub mod agg_req;
pub mod agg_result;
pub mod bucket;
pub(crate) mod cached_sub_aggs;
mod buf_collector;
mod collector;
mod date;
mod error;
@@ -162,19 +162,6 @@ use serde::{Deserialize, Deserializer, Serialize};
use crate::tokenizer::TokenizerManager;
/// A bucket id is a dense identifier for a bucket within an aggregation.
/// It is used to index into a Vec that hold per-bucket data.
///
/// For example, in a terms aggregation, each unique term will be assigned a incremental BucketId.
/// This BucketId will be forwarded to sub-aggregations to identify the parent bucket.
///
/// This allows to have a single AggregationCollector instance per aggregation,
/// that can handle multiple buckets efficiently.
///
/// The API to call sub-aggregations is therefore a &[(BucketId, &[DocId])].
/// For that we'll need a buffer. One Vec per bucket aggregation is needed.
pub type BucketId = u32;
/// Context parameters for aggregation execution
///
/// This struct holds shared resources needed during aggregation execution:
@@ -348,37 +335,19 @@ impl Display for Key {
}
}
pub(crate) fn convert_to_f64<const COLUMN_TYPE_ID: u8>(val: u64) -> f64 {
if COLUMN_TYPE_ID == ColumnType::U64 as u8 {
val as f64
} else if COLUMN_TYPE_ID == ColumnType::I64 as u8
|| COLUMN_TYPE_ID == ColumnType::DateTime as u8
{
i64::from_u64(val) as f64
} else if COLUMN_TYPE_ID == ColumnType::F64 as u8 {
f64::from_u64(val)
} else if COLUMN_TYPE_ID == ColumnType::Bool as u8 {
val as f64
} else {
panic!(
"ColumnType ID {} cannot be converted to f64 metric",
COLUMN_TYPE_ID
)
}
}
/// Inverse of `to_fastfield_u64`. Used to convert to `f64` for metrics.
///
/// # Panics
/// Only `u64`, `f64`, `date`, and `i64` are supported.
pub(crate) fn f64_from_fastfield_u64(val: u64, field_type: ColumnType) -> f64 {
pub(crate) fn f64_from_fastfield_u64(val: u64, field_type: &ColumnType) -> f64 {
match field_type {
ColumnType::U64 => convert_to_f64::<{ ColumnType::U64 as u8 }>(val),
ColumnType::I64 => convert_to_f64::<{ ColumnType::I64 as u8 }>(val),
ColumnType::F64 => convert_to_f64::<{ ColumnType::F64 as u8 }>(val),
ColumnType::Bool => convert_to_f64::<{ ColumnType::Bool as u8 }>(val),
ColumnType::DateTime => convert_to_f64::<{ ColumnType::DateTime as u8 }>(val),
_ => panic!("unexpected type {field_type:?}. This should not happen"),
ColumnType::U64 => val as f64,
ColumnType::I64 | ColumnType::DateTime => i64::from_u64(val) as f64,
ColumnType::F64 => f64::from_u64(val),
ColumnType::Bool => val as f64,
_ => {
panic!("unexpected type {field_type:?}. This should not happen")
}
}
}

103
src/aggregation/segment_agg_result.rs
View File

@@ -8,67 +8,25 @@ use std::fmt::Debug;
pub(crate) use super::agg_limits::AggregationLimitsGuard;
use super::intermediate_agg_result::IntermediateAggregationResults;
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::BucketId;
/// Monotonically increasing provider of BucketIds.
#[derive(Debug, Clone, Default)]
pub struct BucketIdProvider(u32);
impl BucketIdProvider {
/// Get the next BucketId.
pub fn next_bucket_id(&mut self) -> BucketId {
let bucket_id = self.0;
self.0 += 1;
bucket_id
}
}
/// A SegmentAggregationCollector is used to collect aggregation results.
pub trait SegmentAggregationCollector: Debug {
pub trait SegmentAggregationCollector: CollectorClone + Debug {
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()>;
/// Note: The caller needs to call `prepare_max_bucket` before calling `collect`.
fn collect(
&mut self,
parent_bucket_id: BucketId,
docs: &[crate::DocId],
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()>;
/// Collect docs for multiple buckets in one call.
/// Minimizes dynamic dispatch overhead when collecting many buckets.
///
/// Note: The caller needs to call `prepare_max_bucket` before calling `collect`.
fn collect_multiple(
fn collect_block(
&mut self,
bucket_ids: &[BucketId],
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
debug_assert_eq!(bucket_ids.len(), docs.len());
let mut start = 0;
while start < bucket_ids.len() {
let bucket_id = bucket_ids[start];
let mut end = start + 1;
while end < bucket_ids.len() && bucket_ids[end] == bucket_id {
end += 1;
}
self.collect(bucket_id, &docs[start..end], agg_data)?;
start = end;
}
Ok(())
}
/// Prepare the collector for collecting up to BucketId `max_bucket`.
/// This is useful so we can split allocation ahead of time of collecting.
fn prepare_max_bucket(
&mut self,
max_bucket: BucketId,
agg_data: &AggregationsSegmentCtx,
) -> crate::Result<()>;
/// Finalize method. Some Aggregator collect blocks of docs before calling `collect_block`.
@@ -78,7 +36,26 @@ pub trait SegmentAggregationCollector: Debug {
}
}
#[derive(Default)]
/// A helper trait to enable cloning of Box<dyn SegmentAggregationCollector>
pub trait CollectorClone {
fn clone_box(&self) -> Box<dyn SegmentAggregationCollector>;
}
impl<T> CollectorClone for T
where T: 'static + SegmentAggregationCollector + Clone
{
fn clone_box(&self) -> Box<dyn SegmentAggregationCollector> {
Box::new(self.clone())
}
}
impl Clone for Box<dyn SegmentAggregationCollector> {
fn clone(&self) -> Box<dyn SegmentAggregationCollector> {
self.clone_box()
}
}
#[derive(Clone, Default)]
/// The GenericSegmentAggregationResultsCollector is the generic version of the collector, which
/// can handle arbitrary complexity of sub-aggregations. Ideally we never have to pick this one
/// and can provide specialized versions instead, that remove some of its overhead.
@@ -96,13 +73,12 @@ impl Debug for GenericSegmentAggregationResultsCollector {
impl SegmentAggregationCollector for GenericSegmentAggregationResultsCollector {
fn add_intermediate_aggregation_result(
&mut self,
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
for agg in &mut self.aggs {
agg.add_intermediate_aggregation_result(agg_data, results, parent_bucket_id)?;
for agg in self.aggs {
agg.add_intermediate_aggregation_result(agg_data, results)?;
}
Ok(())
@@ -110,13 +86,23 @@ impl SegmentAggregationCollector for GenericSegmentAggregationResultsCollector {
fn collect(
&mut self,
parent_bucket_id: BucketId,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)?;
Ok(())
}
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
for collector in &mut self.aggs {
collector.collect(parent_bucket_id, docs, agg_data)?;
collector.collect_block(docs, agg_data)?;
}
Ok(())
}
@@ -126,15 +112,4 @@ impl SegmentAggregationCollector for GenericSegmentAggregationResultsCollector {
}
Ok(())
}
fn prepare_max_bucket(
&mut self,
max_bucket: BucketId,
agg_data: &AggregationsSegmentCtx,
) -> crate::Result<()> {
for collector in &mut self.aggs {
collector.prepare_max_bucket(max_bucket, agg_data)?;
}
Ok(())
}
}

17
src/collector/facet_collector.rs
View File

@@ -486,9 +486,9 @@ mod tests {
use std::collections::BTreeSet;
use columnar::Dictionary;
use rand::distr::Uniform;
use rand::distributions::Uniform;
use rand::prelude::SliceRandom;
use rand::{rng, Rng};
use rand::{thread_rng, Rng};
use super::{FacetCollector, FacetCounts};
use crate::collector::facet_collector::compress_mapping;
@@ -731,7 +731,7 @@ mod tests {
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let uniform = Uniform::new_inclusive(1, 100_000).unwrap();
let uniform = Uniform::new_inclusive(1, 100_000);
let mut docs: Vec<TantivyDocument> =
vec![("a", 10), ("b", 100), ("c", 7), ("d", 12), ("e", 21)]
.into_iter()
@@ -741,11 +741,14 @@ mod tests {
std::iter::repeat_n(doc, count)
})
.map(|mut doc| {
doc.add_facet(facet_field, &format!("/facet/{}", rng().sample(uniform)));
doc.add_facet(
facet_field,
&format!("/facet/{}", thread_rng().sample(uniform)),
);
doc
})
.collect();
docs[..].shuffle(&mut rng());
docs[..].shuffle(&mut thread_rng());
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
for doc in docs {
@@ -819,8 +822,8 @@ mod tests {
#[cfg(all(test, feature = "unstable"))]
mod bench {
use rand::rng;
use rand::seq::SliceRandom;
use rand::thread_rng;
use test::Bencher;
use crate::collector::FacetCollector;
@@ -843,7 +846,7 @@ mod bench {
}
}
// 40425 docs
docs[..].shuffle(&mut rng());
docs[..].shuffle(&mut thread_rng());
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
for doc in docs {

93
src/collector/sort_key/mod.rs
View File

@@ -1,48 +1,25 @@
mod order;
mod sort_by_erased_type;
mod sort_by_score;
mod sort_by_static_fast_value;
mod sort_by_string;
mod sort_key_computer;
pub use order::*;
pub use sort_by_erased_type::SortByErasedType;
pub use sort_by_score::SortBySimilarityScore;
pub use sort_by_static_fast_value::SortByStaticFastValue;
pub use sort_by_string::SortByString;
pub use sort_key_computer::{SegmentSortKeyComputer, SortKeyComputer};
#[cfg(test)]
pub(crate) mod tests {
// By spec, regardless of whether ascending or descending order was requested, in presence of a
// tie, we sort by ascending doc id/doc address.
pub(crate) fn sort_hits<TSortKey: Ord, D: Ord>(
hits: &mut [ComparableDoc<TSortKey, D>],
order: Order,
) {
if order.is_asc() {
hits.sort_by(|l, r| l.sort_key.cmp(&r.sort_key).then(l.doc.cmp(&r.doc)));
} else {
hits.sort_by(|l, r| {
l.sort_key
.cmp(&r.sort_key)
.reverse() // This is descending
.then(l.doc.cmp(&r.doc))
});
}
}
mod tests {
use std::collections::HashMap;
use std::ops::Range;
use crate::collector::sort_key::{
SortByErasedType, SortBySimilarityScore, SortByStaticFastValue, SortByString,
};
use crate::collector::sort_key::{SortBySimilarityScore, SortByStaticFastValue, SortByString};
use crate::collector::{ComparableDoc, DocSetCollector, TopDocs};
use crate::indexer::NoMergePolicy;
use crate::query::{AllQuery, QueryParser};
use crate::schema::{OwnedValue, Schema, FAST, TEXT};
use crate::schema::{Schema, FAST, TEXT};
use crate::{DocAddress, Document, Index, Order, Score, Searcher};
fn make_index() -> crate::Result<Index> {
@@ -317,9 +294,11 @@ pub(crate) mod tests {
(SortBySimilarityScore, score_order),
(SortByString::for_field("city"), city_order),
));
let results: Vec<((Score, Option<String>), DocAddress)> =
searcher.search(&AllQuery, &top_collector)?;
Ok(results.into_iter().map(|(f, doc)| (f, ids[&doc])).collect())
Ok(searcher
.search(&AllQuery, &top_collector)?
.into_iter()
.map(|(f, doc)| (f, ids[&doc]))
.collect())
}
assert_eq!(
@@ -344,51 +323,6 @@ pub(crate) mod tests {
Ok(())
}
#[test]
fn test_order_by_score_then_owned_value() -> crate::Result<()> {
let index = make_index()?;
type SortKey = (Score, OwnedValue);
fn query(
index: &Index,
score_order: Order,
city_order: Order,
) -> crate::Result<Vec<(SortKey, u64)>> {
let searcher = index.reader()?.searcher();
let ids = id_mapping(&searcher);
let top_collector = TopDocs::with_limit(4).order_by::<(Score, OwnedValue)>((
(SortBySimilarityScore, score_order),
(SortByErasedType::for_field("city"), city_order),
));
let results: Vec<((Score, OwnedValue), DocAddress)> =
searcher.search(&AllQuery, &top_collector)?;
Ok(results.into_iter().map(|(f, doc)| (f, ids[&doc])).collect())
}
assert_eq!(
&query(&index, Order::Asc, Order::Asc)?,
&[
((1.0, OwnedValue::Str("austin".to_owned())), 0),
((1.0, OwnedValue::Str("greenville".to_owned())), 1),
((1.0, OwnedValue::Str("tokyo".to_owned())), 2),
((1.0, OwnedValue::Null), 3),
]
);
assert_eq!(
&query(&index, Order::Asc, Order::Desc)?,
&[
((1.0, OwnedValue::Str("tokyo".to_owned())), 2),
((1.0, OwnedValue::Str("greenville".to_owned())), 1),
((1.0, OwnedValue::Str("austin".to_owned())), 0),
((1.0, OwnedValue::Null), 3),
]
);
Ok(())
}
use proptest::prelude::*;
proptest! {
@@ -438,10 +372,15 @@ pub(crate) mod tests {
// Using the TopDocs collector should always be equivalent to sorting, skipping the
// offset, and then taking the limit.
let sorted_docs: Vec<_> = {
let mut comparable_docs: Vec<ComparableDoc<_, _>> =
let sorted_docs: Vec<_> = if order.is_desc() {
let mut comparable_docs: Vec<ComparableDoc<_, _, true>> =
all_results.into_iter().map(|(sort_key, doc)| ComparableDoc { sort_key, doc}).collect();
sort_hits(&mut comparable_docs, order);
comparable_docs.sort();
comparable_docs.into_iter().map(|cd| (cd.sort_key, cd.doc)).collect()
} else {
let mut comparable_docs: Vec<ComparableDoc<_, _, false>> =
all_results.into_iter().map(|(sort_key, doc)| ComparableDoc { sort_key, doc}).collect();
comparable_docs.sort();
comparable_docs.into_iter().map(|cd| (cd.sort_key, cd.doc)).collect()
};
let expected_docs = sorted_docs.into_iter().skip(offset).take(limit).collect::<Vec<_>>();

245
src/collector/sort_key/order.rs
View File

@@ -1,116 +1,36 @@
use std::cmp::Ordering;
use columnar::MonotonicallyMappableToU64;
use serde::{Deserialize, Serialize};
use crate::collector::{SegmentSortKeyComputer, SortKeyComputer};
use crate::schema::{OwnedValue, Schema};
use crate::schema::Schema;
use crate::{DocId, Order, Score};
fn compare_owned_value<const NULLS_FIRST: bool>(lhs: &OwnedValue, rhs: &OwnedValue) -> Ordering {
match (lhs, rhs) {
(OwnedValue::Null, OwnedValue::Null) => Ordering::Equal,
(OwnedValue::Null, _) => {
if NULLS_FIRST {
Ordering::Less
} else {
Ordering::Greater
}
}
(_, OwnedValue::Null) => {
if NULLS_FIRST {
Ordering::Greater
} else {
Ordering::Less
}
}
(OwnedValue::Str(a), OwnedValue::Str(b)) => a.cmp(b),
(OwnedValue::PreTokStr(a), OwnedValue::PreTokStr(b)) => a.cmp(b),
(OwnedValue::U64(a), OwnedValue::U64(b)) => a.cmp(b),
(OwnedValue::I64(a), OwnedValue::I64(b)) => a.cmp(b),
(OwnedValue::F64(a), OwnedValue::F64(b)) => a.to_u64().cmp(&b.to_u64()),
(OwnedValue::Bool(a), OwnedValue::Bool(b)) => a.cmp(b),
(OwnedValue::Date(a), OwnedValue::Date(b)) => a.cmp(b),
(OwnedValue::Facet(a), OwnedValue::Facet(b)) => a.cmp(b),
(OwnedValue::Bytes(a), OwnedValue::Bytes(b)) => a.cmp(b),
(OwnedValue::IpAddr(a), OwnedValue::IpAddr(b)) => a.cmp(b),
(OwnedValue::U64(a), OwnedValue::I64(b)) => {
if *b < 0 {
Ordering::Greater
} else {
a.cmp(&(*b as u64))
}
}
(OwnedValue::I64(a), OwnedValue::U64(b)) => {
if *a < 0 {
Ordering::Less
} else {
(*a as u64).cmp(b)
}
}
(OwnedValue::U64(a), OwnedValue::F64(b)) => (*a as f64).to_u64().cmp(&b.to_u64()),
(OwnedValue::F64(a), OwnedValue::U64(b)) => a.to_u64().cmp(&(*b as f64).to_u64()),
(OwnedValue::I64(a), OwnedValue::F64(b)) => (*a as f64).to_u64().cmp(&b.to_u64()),
(OwnedValue::F64(a), OwnedValue::I64(b)) => a.to_u64().cmp(&(*b as f64).to_u64()),
(a, b) => {
let ord = a.discriminant_value().cmp(&b.discriminant_value());
// If the discriminant is equal, it's because a new type was added, but hasn't been
// included in this `match` statement.
assert!(
ord != Ordering::Equal,
"Unimplemented comparison for type of {a:?}, {b:?}"
);
ord
}
}
}
/// Comparator trait defining the order in which documents should be ordered.
pub trait Comparator<T>: Send + Sync + std::fmt::Debug + Default {
/// Return the order between two values.
fn compare(&self, lhs: &T, rhs: &T) -> Ordering;
}
/// Compare values naturally (e.g. 1 < 2).
///
/// When used with `TopDocs`, which reverses the order, this results in a
/// "Descending" sort (Greatest values first).
///
/// `None` (or Null for `OwnedValue`) values are considered to be smaller than any other value,
/// and will therefore appear last in a descending sort (e.g. `[Some(20), Some(10), None]`).
/// With the natural comparator, the top k collector will return
/// the top documents in decreasing order.
#[derive(Debug, Copy, Clone, Default, Serialize, Deserialize)]
pub struct NaturalComparator;
impl<T: PartialOrd> Comparator<T> for NaturalComparator {
#[inline(always)]
fn compare(&self, lhs: &T, rhs: &T) -> Ordering {
lhs.partial_cmp(rhs).unwrap_or(Ordering::Equal)
lhs.partial_cmp(rhs).unwrap()
}
}
/// A (partial) implementation of comparison for OwnedValue.
/// Sorts document in reverse order.
///
/// Intended for use within columns of homogenous types, and so will panic for OwnedValues with
/// mismatched types. The one exception is Null, for which we do define all comparisons.
impl Comparator<OwnedValue> for NaturalComparator {
#[inline(always)]
fn compare(&self, lhs: &OwnedValue, rhs: &OwnedValue) -> Ordering {
compare_owned_value::</* NULLS_FIRST= */ true>(lhs, rhs)
}
}
/// Compare values in reverse (e.g. 2 < 1).
///
/// When used with `TopDocs`, which reverses the order, this results in an
/// "Ascending" sort (Smallest values first).
///
/// `None` is considered smaller than `Some` in the underlying comparator, but because the
/// comparison is reversed, `None` is effectively treated as the lowest value in the resulting
/// Ascending sort (e.g. `[None, Some(10), Some(20)]`).
/// If the sort key is None, it will considered as the lowest value, and will therefore appear
/// first.
///
/// The ReverseComparator does not necessarily imply that the sort order is reversed compared
/// to the NaturalComparator. In presence of a tie on the sort key, documents will always be
/// sorted by ascending `DocId`/`DocAddress` in TopN results, regardless of the sort key's order.
/// to the NaturalComparator. In presence of a tie, both version will retain the higher doc ids.
#[derive(Debug, Copy, Clone, Default, Serialize, Deserialize)]
pub struct ReverseComparator;
@@ -123,15 +43,11 @@ where NaturalComparator: Comparator<T>
}
}
/// Compare values in reverse, but treating `None` as lower than `Some`.
///
/// When used with `TopDocs`, which reverses the order, this results in an
/// "Ascending" sort (Smallest values first), but with `None` values appearing last
/// (e.g. `[Some(10), Some(20), None]`).
/// Sorts document in reverse order, but considers None as having the lowest value.
///
/// This is usually what is wanted when sorting by a field in an ascending order.
/// For instance, in an e-commerce website, if sorting by price ascending,
/// the cheapest items would appear first, and items without a price would appear last.
/// For instance, in a e-commerce website, if I sort by price ascending, I most likely want the
/// cheapest items first, and the items without a price at last.
#[derive(Debug, Copy, Clone, Default)]
pub struct ReverseNoneIsLowerComparator;
@@ -191,84 +107,6 @@ impl Comparator<String> for ReverseNoneIsLowerComparator {
}
}
impl Comparator<OwnedValue> for ReverseNoneIsLowerComparator {
#[inline(always)]
fn compare(&self, lhs: &OwnedValue, rhs: &OwnedValue) -> Ordering {
compare_owned_value::</* NULLS_FIRST= */ false>(rhs, lhs)
}
}
/// Compare values naturally, but treating `None` as higher than `Some`.
///
/// When used with `TopDocs`, which reverses the order, this results in a
/// "Descending" sort (Greatest values first), but with `None` values appearing first
/// (e.g. `[None, Some(20), Some(10)]`).
#[derive(Debug, Copy, Clone, Default, Serialize, Deserialize)]
pub struct NaturalNoneIsHigherComparator;
impl<T> Comparator<Option<T>> for NaturalNoneIsHigherComparator
where NaturalComparator: Comparator<T>
{
#[inline(always)]
fn compare(&self, lhs_opt: &Option<T>, rhs_opt: &Option<T>) -> Ordering {
match (lhs_opt, rhs_opt) {
(None, None) => Ordering::Equal,
(None, Some(_)) => Ordering::Greater,
(Some(_), None) => Ordering::Less,
(Some(lhs), Some(rhs)) => NaturalComparator.compare(lhs, rhs),
}
}
}
impl Comparator<u32> for NaturalNoneIsHigherComparator {
#[inline(always)]
fn compare(&self, lhs: &u32, rhs: &u32) -> Ordering {
NaturalComparator.compare(lhs, rhs)
}
}
impl Comparator<u64> for NaturalNoneIsHigherComparator {
#[inline(always)]
fn compare(&self, lhs: &u64, rhs: &u64) -> Ordering {
NaturalComparator.compare(lhs, rhs)
}
}
impl Comparator<f64> for NaturalNoneIsHigherComparator {
#[inline(always)]
fn compare(&self, lhs: &f64, rhs: &f64) -> Ordering {
NaturalComparator.compare(lhs, rhs)
}
}
impl Comparator<f32> for NaturalNoneIsHigherComparator {
#[inline(always)]
fn compare(&self, lhs: &f32, rhs: &f32) -> Ordering {
NaturalComparator.compare(lhs, rhs)
}
}
impl Comparator<i64> for NaturalNoneIsHigherComparator {
#[inline(always)]
fn compare(&self, lhs: &i64, rhs: &i64) -> Ordering {
NaturalComparator.compare(lhs, rhs)
}
}
impl Comparator<String> for NaturalNoneIsHigherComparator {
#[inline(always)]
fn compare(&self, lhs: &String, rhs: &String) -> Ordering {
NaturalComparator.compare(lhs, rhs)
}
}
impl Comparator<OwnedValue> for NaturalNoneIsHigherComparator {
#[inline(always)]
fn compare(&self, lhs: &OwnedValue, rhs: &OwnedValue) -> Ordering {
compare_owned_value::</* NULLS_FIRST= */ false>(lhs, rhs)
}
}
/// An enum representing the different sort orders.
#[derive(Debug, Clone, Copy, Eq, PartialEq, Default)]
pub enum ComparatorEnum {
@@ -277,10 +115,8 @@ pub enum ComparatorEnum {
Natural,
/// Reverse order (See [ReverseComparator])
Reverse,
/// Reverse order by treating None as the lowest value. (See [ReverseNoneLowerComparator])
/// Reverse order by treating None as the lowest value.(See [ReverseNoneLowerComparator])
ReverseNoneLower,
/// Natural order but treating None as the highest value. (See [NaturalNoneIsHigherComparator])
NaturalNoneHigher,
}
impl From<Order> for ComparatorEnum {
@@ -297,7 +133,6 @@ where
ReverseNoneIsLowerComparator: Comparator<T>,
NaturalComparator: Comparator<T>,
ReverseComparator: Comparator<T>,
NaturalNoneIsHigherComparator: Comparator<T>,
{
#[inline(always)]
fn compare(&self, lhs: &T, rhs: &T) -> Ordering {
@@ -305,7 +140,6 @@ where
ComparatorEnum::Natural => NaturalComparator.compare(lhs, rhs),
ComparatorEnum::Reverse => ReverseComparator.compare(lhs, rhs),
ComparatorEnum::ReverseNoneLower => ReverseNoneIsLowerComparator.compare(lhs, rhs),
ComparatorEnum::NaturalNoneHigher => NaturalNoneIsHigherComparator.compare(lhs, rhs),
}
}
}
@@ -488,12 +322,11 @@ impl<TSegmentSortKeyComputer, TSegmentSortKey, TComparator> SegmentSortKeyComput
for SegmentSortKeyComputerWithComparator<TSegmentSortKeyComputer, TComparator>
where
TSegmentSortKeyComputer: SegmentSortKeyComputer<SegmentSortKey = TSegmentSortKey>,
TSegmentSortKey: Clone + 'static + Sync + Send,
TSegmentSortKey: PartialOrd + Clone + 'static + Sync + Send,
TComparator: Comparator<TSegmentSortKey> + 'static + Sync + Send,
{
type SortKey = TSegmentSortKeyComputer::SortKey;
type SegmentSortKey = TSegmentSortKey;
type SegmentComparator = TComparator;
fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Self::SegmentSortKey {
self.segment_sort_key_computer.segment_sort_key(doc, score)
@@ -513,55 +346,3 @@ where
.convert_segment_sort_key(sort_key)
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::schema::OwnedValue;
#[test]
fn test_natural_none_is_higher() {
let comp = NaturalNoneIsHigherComparator;
let null = None;
let v1 = Some(1_u64);
let v2 = Some(2_u64);
// NaturalNoneIsGreaterComparator logic:
// 1. Delegates to NaturalComparator for non-nulls.
// NaturalComparator compare(2, 1) -> 2.cmp(1) -> Greater.
assert_eq!(comp.compare(&v2, &v1), Ordering::Greater);
// 2. Treats None (Null) as Greater than any value.
// compare(None, Some(2)) should be Greater.
assert_eq!(comp.compare(&null, &v2), Ordering::Greater);
// compare(Some(1), None) should be Less.
assert_eq!(comp.compare(&v1, &null), Ordering::Less);
// compare(None, None) should be Equal.
assert_eq!(comp.compare(&null, &null), Ordering::Equal);
}
#[test]
fn test_mixed_ownedvalue_compare() {
let u = OwnedValue::U64(10);
let i = OwnedValue::I64(10);
let f = OwnedValue::F64(10.0);
let nc = NaturalComparator;
assert_eq!(nc.compare(&u, &i), Ordering::Equal);
assert_eq!(nc.compare(&u, &f), Ordering::Equal);
assert_eq!(nc.compare(&i, &f), Ordering::Equal);
let u2 = OwnedValue::U64(11);
assert_eq!(nc.compare(&u2, &f), Ordering::Greater);
let s = OwnedValue::Str("a".to_string());
// Str < U64
assert_eq!(nc.compare(&s, &u), Ordering::Less);
// Str < I64
assert_eq!(nc.compare(&s, &i), Ordering::Less);
// Str < F64
assert_eq!(nc.compare(&s, &f), Ordering::Less);
}
}

361
src/collector/sort_key/sort_by_erased_type.rs
View File

@@ -1,361 +0,0 @@
use columnar::{ColumnType, MonotonicallyMappableToU64};
use crate::collector::sort_key::{
NaturalComparator, SortBySimilarityScore, SortByStaticFastValue, SortByString,
};
use crate::collector::{SegmentSortKeyComputer, SortKeyComputer};
use crate::fastfield::FastFieldNotAvailableError;
use crate::schema::OwnedValue;
use crate::{DateTime, DocId, Score};
/// Sort by the boxed / OwnedValue representation of either a fast field, or of the score.
///
/// Using the OwnedValue representation allows for type erasure, and can be useful when sort orders
/// are not known until runtime. But it comes with a performance cost: wherever possible, prefer to
/// use a SortKeyComputer implementation with a known-type at compile time.
#[derive(Debug, Clone)]
pub enum SortByErasedType {
/// Sort by a fast field
Field(String),
/// Sort by score
Score,
}
impl SortByErasedType {
/// Creates a new sort key computer which will sort by the given fast field column, with type
/// erasure.
pub fn for_field(column_name: impl ToString) -> Self {
Self::Field(column_name.to_string())
}
/// Creates a new sort key computer which will sort by score, with type erasure.
pub fn for_score() -> Self {
Self::Score
}
}
trait ErasedSegmentSortKeyComputer: Send + Sync {
fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Option<u64>;
fn convert_segment_sort_key(&self, sort_key: Option<u64>) -> OwnedValue;
}
struct ErasedSegmentSortKeyComputerWrapper<C, F> {
inner: C,
converter: F,
}
impl<C, F> ErasedSegmentSortKeyComputer for ErasedSegmentSortKeyComputerWrapper<C, F>
where
C: SegmentSortKeyComputer<SegmentSortKey = Option<u64>> + Send + Sync,
F: Fn(C::SortKey) -> OwnedValue + Send + Sync + 'static,
{
fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Option<u64> {
self.inner.segment_sort_key(doc, score)
}
fn convert_segment_sort_key(&self, sort_key: Option<u64>) -> OwnedValue {
let val = self.inner.convert_segment_sort_key(sort_key);
(self.converter)(val)
}
}
struct ScoreSegmentSortKeyComputer {
segment_computer: SortBySimilarityScore,
}
impl ErasedSegmentSortKeyComputer for ScoreSegmentSortKeyComputer {
fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Option<u64> {
let score_value: f64 = self.segment_computer.segment_sort_key(doc, score).into();
Some(score_value.to_u64())
}
fn convert_segment_sort_key(&self, sort_key: Option<u64>) -> OwnedValue {
let score_value: u64 = sort_key.expect("This implementation always produces a score.");
OwnedValue::F64(f64::from_u64(score_value))
}
}
impl SortKeyComputer for SortByErasedType {
type SortKey = OwnedValue;
type Child = ErasedColumnSegmentSortKeyComputer;
type Comparator = NaturalComparator;
fn requires_scoring(&self) -> bool {
matches!(self, Self::Score)
}
fn segment_sort_key_computer(
&self,
segment_reader: &crate::SegmentReader,
) -> crate::Result<Self::Child> {
let inner: Box<dyn ErasedSegmentSortKeyComputer> = match self {
Self::Field(column_name) => {
let fast_fields = segment_reader.fast_fields();
// TODO: We currently double-open the column to avoid relying on the implementation
// details of `SortByString` or `SortByStaticFastValue`. Once
// https://github.com/quickwit-oss/tantivy/issues/2776 is resolved, we should
// consider directly constructing the appropriate `SegmentSortKeyComputer` type for
// the column that we open here.
let (_column, column_type) =
fast_fields.u64_lenient(column_name)?.ok_or_else(|| {
FastFieldNotAvailableError {
field_name: column_name.to_owned(),
}
})?;
match column_type {
ColumnType::Str => {
let computer = SortByString::for_field(column_name);
let inner = computer.segment_sort_key_computer(segment_reader)?;
Box::new(ErasedSegmentSortKeyComputerWrapper {
inner,
converter: |val: Option<String>| {
val.map(OwnedValue::Str).unwrap_or(OwnedValue::Null)
},
})
}
ColumnType::U64 => {
let computer = SortByStaticFastValue::<u64>::for_field(column_name);
let inner = computer.segment_sort_key_computer(segment_reader)?;
Box::new(ErasedSegmentSortKeyComputerWrapper {
inner,
converter: |val: Option<u64>| {
val.map(OwnedValue::U64).unwrap_or(OwnedValue::Null)
},
})
}
ColumnType::I64 => {
let computer = SortByStaticFastValue::<i64>::for_field(column_name);
let inner = computer.segment_sort_key_computer(segment_reader)?;
Box::new(ErasedSegmentSortKeyComputerWrapper {
inner,
converter: |val: Option<i64>| {
val.map(OwnedValue::I64).unwrap_or(OwnedValue::Null)
},
})
}
ColumnType::F64 => {
let computer = SortByStaticFastValue::<f64>::for_field(column_name);
let inner = computer.segment_sort_key_computer(segment_reader)?;
Box::new(ErasedSegmentSortKeyComputerWrapper {
inner,
converter: |val: Option<f64>| {
val.map(OwnedValue::F64).unwrap_or(OwnedValue::Null)
},
})
}
ColumnType::Bool => {
let computer = SortByStaticFastValue::<bool>::for_field(column_name);
let inner = computer.segment_sort_key_computer(segment_reader)?;
Box::new(ErasedSegmentSortKeyComputerWrapper {
inner,
converter: |val: Option<bool>| {
val.map(OwnedValue::Bool).unwrap_or(OwnedValue::Null)
},
})
}
ColumnType::DateTime => {
let computer = SortByStaticFastValue::<DateTime>::for_field(column_name);
let inner = computer.segment_sort_key_computer(segment_reader)?;
Box::new(ErasedSegmentSortKeyComputerWrapper {
inner,
converter: |val: Option<DateTime>| {
val.map(OwnedValue::Date).unwrap_or(OwnedValue::Null)
},
})
}
column_type => {
return Err(crate::TantivyError::SchemaError(format!(
"Field `{}` is of type {column_type:?}, which is not supported for \
sorting by owned value yet.",
column_name
)))
}
}
}
Self::Score => Box::new(ScoreSegmentSortKeyComputer {
segment_computer: SortBySimilarityScore,
}),
};
Ok(ErasedColumnSegmentSortKeyComputer { inner })
}
}
pub struct ErasedColumnSegmentSortKeyComputer {
inner: Box<dyn ErasedSegmentSortKeyComputer>,
}
impl SegmentSortKeyComputer for ErasedColumnSegmentSortKeyComputer {
type SortKey = OwnedValue;
type SegmentSortKey = Option<u64>;
type SegmentComparator = NaturalComparator;
#[inline(always)]
fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Option<u64> {
self.inner.segment_sort_key(doc, score)
}
fn convert_segment_sort_key(&self, segment_sort_key: Self::SegmentSortKey) -> OwnedValue {
self.inner.convert_segment_sort_key(segment_sort_key)
}
}
#[cfg(test)]
mod tests {
use crate::collector::sort_key::{ComparatorEnum, SortByErasedType};
use crate::collector::TopDocs;
use crate::query::AllQuery;
use crate::schema::{OwnedValue, Schema, FAST, TEXT};
use crate::Index;
#[test]
fn test_sort_by_owned_u64() {
let mut schema_builder = Schema::builder();
let id_field = schema_builder.add_u64_field("id", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests().unwrap();
writer.add_document(doc!(id_field => 10u64)).unwrap();
writer.add_document(doc!(id_field => 2u64)).unwrap();
writer.add_document(doc!()).unwrap();
writer.commit().unwrap();
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let collector = TopDocs::with_limit(10)
.order_by((SortByErasedType::for_field("id"), ComparatorEnum::Natural));
let top_docs = searcher.search(&AllQuery, &collector).unwrap();
let values: Vec<OwnedValue> = top_docs.into_iter().map(|(key, _)| key).collect();
assert_eq!(
values,
vec![OwnedValue::U64(10), OwnedValue::U64(2), OwnedValue::Null]
);
let collector = TopDocs::with_limit(10).order_by((
SortByErasedType::for_field("id"),
ComparatorEnum::ReverseNoneLower,
));
let top_docs = searcher.search(&AllQuery, &collector).unwrap();
let values: Vec<OwnedValue> = top_docs.into_iter().map(|(key, _)| key).collect();
assert_eq!(
values,
vec![OwnedValue::U64(2), OwnedValue::U64(10), OwnedValue::Null]
);
}
#[test]
fn test_sort_by_owned_string() {
let mut schema_builder = Schema::builder();
let city_field = schema_builder.add_text_field("city", FAST | TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests().unwrap();
writer.add_document(doc!(city_field => "tokyo")).unwrap();
writer.add_document(doc!(city_field => "austin")).unwrap();
writer.add_document(doc!()).unwrap();
writer.commit().unwrap();
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let collector = TopDocs::with_limit(10).order_by((
SortByErasedType::for_field("city"),
ComparatorEnum::ReverseNoneLower,
));
let top_docs = searcher.search(&AllQuery, &collector).unwrap();
let values: Vec<OwnedValue> = top_docs.into_iter().map(|(key, _)| key).collect();
assert_eq!(
values,
vec![
OwnedValue::Str("austin".to_string()),
OwnedValue::Str("tokyo".to_string()),
OwnedValue::Null
]
);
}
#[test]
fn test_sort_by_owned_reverse() {
let mut schema_builder = Schema::builder();
let id_field = schema_builder.add_u64_field("id", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests().unwrap();
writer.add_document(doc!(id_field => 10u64)).unwrap();
writer.add_document(doc!(id_field => 2u64)).unwrap();
writer.add_document(doc!()).unwrap();
writer.commit().unwrap();
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let collector = TopDocs::with_limit(10)
.order_by((SortByErasedType::for_field("id"), ComparatorEnum::Reverse));
let top_docs = searcher.search(&AllQuery, &collector).unwrap();
let values: Vec<OwnedValue> = top_docs.into_iter().map(|(key, _)| key).collect();
assert_eq!(
values,
vec![OwnedValue::Null, OwnedValue::U64(2), OwnedValue::U64(10)]
);
}
#[test]
fn test_sort_by_owned_score() {
let mut schema_builder = Schema::builder();
let body_field = schema_builder.add_text_field("body", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests().unwrap();
writer.add_document(doc!(body_field => "a a")).unwrap();
writer.add_document(doc!(body_field => "a")).unwrap();
writer.commit().unwrap();
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let query_parser = crate::query::QueryParser::for_index(&index, vec![body_field]);
let query = query_parser.parse_query("a").unwrap();
// Sort by score descending (Natural)
let collector = TopDocs::with_limit(10)
.order_by((SortByErasedType::for_score(), ComparatorEnum::Natural));
let top_docs = searcher.search(&query, &collector).unwrap();
let values: Vec<f64> = top_docs
.into_iter()
.map(|(key, _)| match key {
OwnedValue::F64(val) => val,
_ => panic!("Wrong type {key:?}"),
})
.collect();
assert_eq!(values.len(), 2);
assert!(values[0] > values[1]);
// Sort by score ascending (ReverseNoneLower)
let collector = TopDocs::with_limit(10).order_by((
SortByErasedType::for_score(),
ComparatorEnum::ReverseNoneLower,
));
let top_docs = searcher.search(&query, &collector).unwrap();
let values: Vec<f64> = top_docs
.into_iter()
.map(|(key, _)| match key {
OwnedValue::F64(val) => val,
_ => panic!("Wrong type {key:?}"),
})
.collect();
assert_eq!(values.len(), 2);
assert!(values[0] < values[1]);
}
}

2
src/collector/sort_key/sort_by_score.rs
View File

@@ -63,8 +63,8 @@ impl SortKeyComputer for SortBySimilarityScore {
impl SegmentSortKeyComputer for SortBySimilarityScore {
type SortKey = Score;
type SegmentSortKey = Score;
type SegmentComparator = NaturalComparator;
#[inline(always)]
fn segment_sort_key(&mut self, _doc: DocId, score: Score) -> Score {

4
src/collector/sort_key/sort_by_static_fast_value.rs
View File

@@ -34,7 +34,9 @@ impl<T: FastValue> SortByStaticFastValue<T> {
impl<T: FastValue> SortKeyComputer for SortByStaticFastValue<T> {
type Child = SortByFastValueSegmentSortKeyComputer<T>;
type SortKey = Option<T>;
type Comparator = NaturalComparator;
fn check_schema(&self, schema: &crate::schema::Schema) -> crate::Result<()> {
@@ -82,8 +84,8 @@ pub struct SortByFastValueSegmentSortKeyComputer<T> {
impl<T: FastValue> SegmentSortKeyComputer for SortByFastValueSegmentSortKeyComputer<T> {
type SortKey = Option<T>;
type SegmentSortKey = Option<u64>;
type SegmentComparator = NaturalComparator;
#[inline(always)]
fn segment_sort_key(&mut self, doc: DocId, _score: Score) -> Self::SegmentSortKey {

6
src/collector/sort_key/sort_by_string.rs
View File

@@ -30,7 +30,9 @@ impl SortByString {
impl SortKeyComputer for SortByString {
type SortKey = Option<String>;
type Child = ByStringColumnSegmentSortKeyComputer;
type Comparator = NaturalComparator;
fn segment_sort_key_computer(
@@ -48,8 +50,8 @@ pub struct ByStringColumnSegmentSortKeyComputer {
impl SegmentSortKeyComputer for ByStringColumnSegmentSortKeyComputer {
type SortKey = Option<String>;
type SegmentSortKey = Option<TermOrdinal>;
type SegmentComparator = NaturalComparator;
#[inline(always)]
fn segment_sort_key(&mut self, doc: DocId, _score: Score) -> Option<TermOrdinal> {
@@ -58,8 +60,6 @@ impl SegmentSortKeyComputer for ByStringColumnSegmentSortKeyComputer {
}
fn convert_segment_sort_key(&self, term_ord_opt: Option<TermOrdinal>) -> Option<String> {
// TODO: Individual lookups to the dictionary like this are very likely to repeatedly
// decompress the same blocks. See https://github.com/quickwit-oss/tantivy/issues/2776
let term_ord = term_ord_opt?;
let str_column = self.str_column_opt.as_ref()?;
let mut bytes = Vec::new();

32
src/collector/sort_key/sort_key_computer.rs
View File

@@ -12,21 +12,13 @@ use crate::{DocAddress, DocId, Result, Score, SegmentReader};
/// It is the segment local version of the [`SortKeyComputer`].
pub trait SegmentSortKeyComputer: 'static {
/// The final score being emitted.
type SortKey: 'static + Send + Sync + Clone;
type SortKey: 'static + PartialOrd + Send + Sync + Clone;
/// Sort key used by at the segment level by the `SegmentSortKeyComputer`.
///
/// It is typically small like a `u64`, and is meant to be converted
/// to the final score at the end of the collection of the segment.
type SegmentSortKey: 'static + Clone + Send + Sync + Clone;
/// Comparator type.
type SegmentComparator: Comparator<Self::SegmentSortKey> + 'static;
/// Returns the segment sort key comparator.
fn segment_comparator(&self) -> Self::SegmentComparator {
Self::SegmentComparator::default()
}
type SegmentSortKey: 'static + PartialOrd + Clone + Send + Sync + Clone;
/// Computes the sort key for the given document and score.
fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Self::SegmentSortKey;
@@ -55,7 +47,7 @@ pub trait SegmentSortKeyComputer: 'static {
left: &Self::SegmentSortKey,
right: &Self::SegmentSortKey,
) -> Ordering {
self.segment_comparator().compare(left, right)
NaturalComparator.compare(left, right)
}
/// Implementing this method makes it possible to avoid computing
@@ -89,7 +81,7 @@ pub trait SegmentSortKeyComputer: 'static {
/// the sort key at a segment scale.
pub trait SortKeyComputer: Sync {
/// The sort key type.
type SortKey: 'static + Send + Sync + Clone + std::fmt::Debug;
type SortKey: 'static + Send + Sync + PartialOrd + Clone + std::fmt::Debug;
/// Type of the associated [`SegmentSortKeyComputer`].
type Child: SegmentSortKeyComputer<SortKey = Self::SortKey>;
/// Comparator type.
@@ -144,7 +136,10 @@ where
HeadSortKeyComputer: SortKeyComputer,
TailSortKeyComputer: SortKeyComputer,
{
type SortKey = (HeadSortKeyComputer::SortKey, TailSortKeyComputer::SortKey);
type SortKey = (
<HeadSortKeyComputer::Child as SegmentSortKeyComputer>::SortKey,
<TailSortKeyComputer::Child as SegmentSortKeyComputer>::SortKey,
);
type Child = (HeadSortKeyComputer::Child, TailSortKeyComputer::Child);
type Comparator = (
@@ -193,11 +188,6 @@ where
TailSegmentSortKeyComputer::SegmentSortKey,
);
type SegmentComparator = (
HeadSegmentSortKeyComputer::SegmentComparator,
TailSegmentSortKeyComputer::SegmentComparator,
);
/// A SegmentSortKeyComputer maps to a SegmentSortKey, but it can also decide on
/// its ordering.
///
@@ -279,12 +269,11 @@ impl<T, PreviousScore, NewScore> SegmentSortKeyComputer
for MappedSegmentSortKeyComputer<T, PreviousScore, NewScore>
where
T: SegmentSortKeyComputer<SortKey = PreviousScore>,
PreviousScore: 'static + Clone + Send + Sync,
NewScore: 'static + Clone + Send + Sync,
PreviousScore: 'static + Clone + Send + Sync + PartialOrd,
NewScore: 'static + Clone + Send + Sync + PartialOrd,
{
type SortKey = NewScore;
type SegmentSortKey = T::SegmentSortKey;
type SegmentComparator = T::SegmentComparator;
fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Self::SegmentSortKey {
self.sort_key_computer.segment_sort_key(doc, score)
@@ -474,7 +463,6 @@ where
{
type SortKey = TSortKey;
type SegmentSortKey = TSortKey;
type SegmentComparator = NaturalComparator;
fn segment_sort_key(&mut self, doc: DocId, _score: Score) -> TSortKey {
(self)(doc)

2
src/collector/sort_key_top_collector.rs
View File

@@ -160,7 +160,7 @@ mod tests {
expected: &[(crate::Score, usize)],
) {
let mut vals: Vec<(crate::Score, usize)> = (0..10).map(|val| (val as f32, val)).collect();
vals.shuffle(&mut rand::rng());
vals.shuffle(&mut rand::thread_rng());
let vals_merged = merge_top_k(vals.into_iter(), doc_range, ComparatorEnum::from(order));
assert_eq!(&vals_merged, expected);
}

58
src/collector/top_collector.rs
View File

@@ -1,22 +1,64 @@
use std::cmp::Ordering;
use serde::{Deserialize, Serialize};
/// Contains a feature (field, score, etc.) of a document along with the document address.
///
/// Used only by TopNComputer, which implements the actual comparison via a `Comparator`.
#[derive(Clone, Default, Eq, PartialEq, Serialize, Deserialize)]
pub struct ComparableDoc<T, D> {
/// It guarantees stable sorting: in case of a tie on the feature, the document
/// address is used.
///
/// The REVERSE_ORDER generic parameter controls whether the by-feature order
/// should be reversed, which is useful for achieving for example largest-first
/// semantics without having to wrap the feature in a `Reverse`.
#[derive(Clone, Default, Serialize, Deserialize)]
pub struct ComparableDoc<T, D, const REVERSE_ORDER: bool = false> {
/// The feature of the document. In practice, this is
/// is a type which can be compared with a `Comparator<T>`.
/// is any type that implements `PartialOrd`.
pub sort_key: T,
/// The document address. In practice, this is either a `DocId` or `DocAddress`.
/// The document address. In practice, this is any
/// type that implements `PartialOrd`, and is guaranteed
/// to be unique for each document.
pub doc: D,
}
impl<T: std::fmt::Debug, D: std::fmt::Debug> std::fmt::Debug for ComparableDoc<T, D> {
impl<T: std::fmt::Debug, D: std::fmt::Debug, const R: bool> std::fmt::Debug
for ComparableDoc<T, D, R>
{
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
f.debug_struct("ComparableDoc")
f.debug_struct(format!("ComparableDoc<_, _ {R}").as_str())
.field("feature", &self.sort_key)
.field("doc", &self.doc)
.finish()
}
}
impl<T: PartialOrd, D: PartialOrd, const R: bool> PartialOrd for ComparableDoc<T, D, R> {
fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
Some(self.cmp(other))
}
}
impl<T: PartialOrd, D: PartialOrd, const R: bool> Ord for ComparableDoc<T, D, R> {
#[inline]
fn cmp(&self, other: &Self) -> Ordering {
let by_feature = self
.sort_key
.partial_cmp(&other.sort_key)
.map(|ord| if R { ord.reverse() } else { ord })
.unwrap_or(Ordering::Equal);
let lazy_by_doc_address = || self.doc.partial_cmp(&other.doc).unwrap_or(Ordering::Equal);
// In case of a tie on the feature, we sort by ascending
// `DocAddress` in order to ensure a stable sorting of the
// documents.
by_feature.then_with(lazy_by_doc_address)
}
}
impl<T: PartialOrd, D: PartialOrd, const R: bool> PartialEq for ComparableDoc<T, D, R> {
fn eq(&self, other: &Self) -> bool {
self.cmp(other) == Ordering::Equal
}
}
impl<T: PartialOrd, D: PartialOrd, const R: bool> Eq for ComparableDoc<T, D, R> {}

96
src/collector/top_score_collector.rs
View File

@@ -23,9 +23,10 @@ use crate::{DocAddress, DocId, Order, Score, SegmentReader};
/// The theoretical complexity for collecting the top `K` out of `N` documents
/// is `O(N + K)`.
///
/// This collector guarantees a stable sorting in case of a tie on the
/// document score/sort key: The document address (`DocAddress`) is used as a tie breaker.
/// In case of a tie on the sort key, documents are always sorted by ascending `DocAddress`.
/// This collector does not guarantee a stable sorting in case of a tie on the
/// document score, for stable sorting `PartialOrd` needs to resolve on other fields
/// like docid in case of score equality.
/// Only then, it is suitable for pagination.
///
/// ```rust
/// use tantivy::collector::TopDocs;
@@ -324,7 +325,7 @@ impl TopDocs {
sort_key_computer: impl SortKeyComputer<SortKey = TSortKey> + Send + 'static,
) -> impl Collector<Fruit = Vec<(TSortKey, DocAddress)>>
where
TSortKey: 'static + Clone + Send + Sync + std::fmt::Debug,
TSortKey: 'static + Clone + Send + Sync + PartialOrd + std::fmt::Debug,
{
TopBySortKeyCollector::new(sort_key_computer, self.doc_range())
}
@@ -445,7 +446,7 @@ where
F: 'static + Send + Sync + Fn(&SegmentReader) -> TTweakScoreSortKeyFn,
TTweakScoreSortKeyFn: 'static + Fn(DocId, Score) -> TSortKey,
TweakScoreSegmentSortKeyComputer<TTweakScoreSortKeyFn>:
SegmentSortKeyComputer<SortKey = TSortKey, SegmentSortKey = TSortKey>,
SegmentSortKeyComputer<SortKey = TSortKey>,
TSortKey: 'static + PartialOrd + Clone + Send + Sync + std::fmt::Debug,
{
type SortKey = TSortKey;
@@ -480,7 +481,6 @@ where
{
type SortKey = TSortKey;
type SegmentSortKey = TSortKey;
type SegmentComparator = NaturalComparator;
fn segment_sort_key(&mut self, doc: DocId, score: Score) -> TSortKey {
(self.sort_key_fn)(doc, score)
@@ -500,13 +500,8 @@ where
///
/// For TopN == 0, it will be relative expensive.
///
/// The TopNComputer will tiebreak by using ascending `D` (DocId or DocAddress):
/// i.e., in case of a tie on the sort key, the `DocId|DocAddress` are always sorted in
/// ascending order, regardless of the `Comparator` used for the `Score` type.
///
/// NOTE: Items must be `push`ed to the TopNComputer in ascending `DocId|DocAddress` order, as the
/// threshold used to eliminate docs does not include the `DocId` or `DocAddress`: this provides
/// the ascending `DocId|DocAddress` tie-breaking behavior without additional comparisons.
/// When using the natural comparator, the top N computer returns the top N elements in
/// descending order, as expected for a top N.
#[derive(Serialize, Deserialize)]
#[serde(from = "TopNComputerDeser<Score, D, C>")]
pub struct TopNComputer<Score, D, C> {
@@ -585,18 +580,6 @@ where
}
}
#[inline(always)]
fn compare_for_top_k<TSortKey, D: Ord, C: Comparator<TSortKey>>(
c: &C,
lhs: &ComparableDoc<TSortKey, D>,
rhs: &ComparableDoc<TSortKey, D>,
) -> std::cmp::Ordering {
c.compare(&lhs.sort_key, &rhs.sort_key)
.reverse() // Reverse here because we want top K.
.then_with(|| lhs.doc.cmp(&rhs.doc)) // Regardless of asc/desc, in presence of a tie, we
// sort by doc id
}
impl<TSortKey, D, C> TopNComputer<TSortKey, D, C>
where
D: Ord,
@@ -617,13 +600,10 @@ where
/// Push a new document to the top n.
/// If the document is below the current threshold, it will be ignored.
///
/// NOTE: `push` must be called in ascending `DocId`/`DocAddress` order.
#[inline]
pub fn push(&mut self, sort_key: TSortKey, doc: D) {
if let Some(last_median) = &self.threshold {
// See the struct docs for an explanation of why this comparison is strict.
if self.comparator.compare(&sort_key, last_median) != Ordering::Greater {
if self.comparator.compare(&sort_key, last_median) == Ordering::Less {
return;
}
}
@@ -649,7 +629,9 @@ where
fn truncate_top_n(&mut self) -> TSortKey {
// Use select_nth_unstable to find the top nth score
let (_, median_el, _) = self.buffer.select_nth_unstable_by(self.top_n, |lhs, rhs| {
compare_for_top_k(&self.comparator, lhs, rhs)
self.comparator
.compare(&rhs.sort_key, &lhs.sort_key)
.then_with(|| lhs.doc.cmp(&rhs.doc))
});
let median_score = median_el.sort_key.clone();
@@ -664,8 +646,11 @@ where
if self.buffer.len() > self.top_n {
self.truncate_top_n();
}
self.buffer
.sort_unstable_by(|lhs, rhs| compare_for_top_k(&self.comparator, lhs, rhs));
self.buffer.sort_unstable_by(|left, right| {
self.comparator
.compare(&right.sort_key, &left.sort_key)
.then_with(|| left.doc.cmp(&right.doc))
});
self.buffer
}
@@ -770,33 +755,6 @@ mod tests {
);
}
#[test]
fn test_topn_computer_duplicates() {
let mut computer: TopNComputer<u32, u32, NaturalComparator> =
TopNComputer::new_with_comparator(2, NaturalComparator);
computer.push(1u32, 1u32);
computer.push(1u32, 2u32);
computer.push(1u32, 3u32);
computer.push(1u32, 4u32);
computer.push(1u32, 5u32);
// In the presence of duplicates, DocIds are always ascending order.
assert_eq!(
computer.into_sorted_vec(),
&[
ComparableDoc {
sort_key: 1u32,
doc: 1u32,
},
ComparableDoc {
sort_key: 1u32,
doc: 2u32,
}
]
);
}
#[test]
fn test_topn_computer_no_panic() {
for top_n in 0..10 {
@@ -814,17 +772,14 @@ mod tests {
#[test]
fn test_topn_computer_asc_prop(
limit in 0..10_usize,
mut docs in proptest::collection::vec((0..100_u64, 0..100_u64), 0..100_usize),
docs in proptest::collection::vec((0..100_u64, 0..100_u64), 0..100_usize),
) {
// NB: TopNComputer must receive inputs in ascending DocId order.
docs.sort_by_key(|(_, doc_id)| *doc_id);
let mut computer: TopNComputer<_, _, ReverseComparator> = TopNComputer::new_with_comparator(limit, ReverseComparator);
for (feature, doc) in &docs {
computer.push(*feature, *doc);
}
let mut comparable_docs: Vec<ComparableDoc<u64, u64>> =
docs.into_iter().map(|(sort_key, doc)| ComparableDoc { sort_key, doc }).collect();
crate::collector::sort_key::tests::sort_hits(&mut comparable_docs, Order::Asc);
let mut comparable_docs: Vec<ComparableDoc<u64, u64>> = docs.into_iter().map(|(sort_key, doc)| ComparableDoc { sort_key, doc }).collect::<Vec<_>>();
comparable_docs.sort();
comparable_docs.truncate(limit);
prop_assert_eq!(
computer.into_sorted_vec(),
@@ -1451,10 +1406,15 @@ mod tests {
// Using the TopDocs collector should always be equivalent to sorting, skipping the
// offset, and then taking the limit.
let sorted_docs: Vec<_> = {
let mut comparable_docs: Vec<ComparableDoc<_, _>> =
let sorted_docs: Vec<_> = if order.is_desc() {
let mut comparable_docs: Vec<ComparableDoc<_, _, true>> =
all_results.into_iter().map(|(sort_key, doc)| ComparableDoc { sort_key, doc}).collect();
crate::collector::sort_key::tests::sort_hits(&mut comparable_docs, order);
comparable_docs.sort();
comparable_docs.into_iter().map(|cd| (cd.sort_key, cd.doc)).collect()
} else {
let mut comparable_docs: Vec<ComparableDoc<_, _, false>> =
all_results.into_iter().map(|(sort_key, doc)| ComparableDoc { sort_key, doc}).collect();
comparable_docs.sort();
comparable_docs.into_iter().map(|cd| (cd.sort_key, cd.doc)).collect()
};
let expected_docs = sorted_docs.into_iter().skip(offset).take(limit).collect::<Vec<_>>();

10
src/core/executor.rs
View File

@@ -48,15 +48,7 @@ impl Executor {
F: Sized + Sync + Fn(A) -> crate::Result<R>,
{
match self {
Executor::SingleThread => {
// Avoid `collect`, since the stacktrace is blown up by it, which makes profiling
// harder.
let mut result = Vec::with_capacity(args.size_hint().0);
for arg in args {
result.push(f(arg)?);
}
Ok(result)
}
Executor::SingleThread => args.map(f).collect::<crate::Result<_>>(),
Executor::ThreadPool(pool) => {
let args: Vec<A> = args.collect();
let num_fruits = args.len();

21
src/core/json_utils.rs
View File

@@ -227,6 +227,9 @@ pub(crate) fn index_json_value<'a, V: Value<'a>>(
ReferenceValueLeaf::IpAddr(_) => {
unimplemented!("IP address support in dynamic fields is not yet implemented")
}
ReferenceValueLeaf::Geometry(_) => {
unimplemented!("Geometry support in dynamic fields is not implemented")
}
},
ReferenceValue::Array(elements) => {
for val in elements {
@@ -406,7 +409,7 @@ mod tests {
let mut term = Term::from_field_json_path(field, "color", false);
term.append_type_and_str("red");
assert_eq!(term.serialized_value_bytes(), b"color\x00sred".to_vec())
assert_eq!(term.serialized_term(), b"\x00\x00\x00\x01jcolor\x00sred")
}
#[test]
@@ -416,8 +419,8 @@ mod tests {
term.append_type_and_fast_value(-4i64);
assert_eq!(
term.serialized_value_bytes(),
b"color\x00i\x7f\xff\xff\xff\xff\xff\xff\xfc".to_vec()
term.serialized_term(),
b"\x00\x00\x00\x01jcolor\x00i\x7f\xff\xff\xff\xff\xff\xff\xfc"
)
}
@@ -428,8 +431,8 @@ mod tests {
term.append_type_and_fast_value(4u64);
assert_eq!(
term.serialized_value_bytes(),
b"color\x00u\x00\x00\x00\x00\x00\x00\x00\x04".to_vec()
term.serialized_term(),
b"\x00\x00\x00\x01jcolor\x00u\x00\x00\x00\x00\x00\x00\x00\x04"
)
}
@@ -439,8 +442,8 @@ mod tests {
let mut term = Term::from_field_json_path(field, "color", false);
term.append_type_and_fast_value(4.0f64);
assert_eq!(
term.serialized_value_bytes(),
b"color\x00f\xc0\x10\x00\x00\x00\x00\x00\x00".to_vec()
term.serialized_term(),
b"\x00\x00\x00\x01jcolor\x00f\xc0\x10\x00\x00\x00\x00\x00\x00"
)
}
@@ -450,8 +453,8 @@ mod tests {
let mut term = Term::from_field_json_path(field, "color", false);
term.append_type_and_fast_value(true);
assert_eq!(
term.serialized_value_bytes(),
b"color\x00o\x00\x00\x00\x00\x00\x00\x00\x01".to_vec()
term.serialized_term(),
b"\x00\x00\x00\x01jcolor\x00o\x00\x00\x00\x00\x00\x00\x00\x01"
)
}

7
src/directory/composite_file.rs
View File

@@ -5,7 +5,7 @@ use std::ops::Range;
use common::{BinarySerializable, CountingWriter, HasLen, VInt};
use crate::directory::{FileSlice, TerminatingWrite, WritePtr};
use crate::schema::{Field, Schema};
use crate::schema::Field;
use crate::space_usage::{FieldUsage, PerFieldSpaceUsage};
#[derive(Eq, PartialEq, Hash, Copy, Ord, PartialOrd, Clone, Debug)]
@@ -167,11 +167,10 @@ impl CompositeFile {
.map(|byte_range| self.data.slice(byte_range.clone()))
}
pub fn space_usage(&self, schema: &Schema) -> PerFieldSpaceUsage {
pub fn space_usage(&self) -> PerFieldSpaceUsage {
let mut fields = Vec::new();
for (&field_addr, byte_range) in &self.offsets_index {
let field_name = schema.get_field_name(field_addr.field).to_string();
let mut field_usage = FieldUsage::empty(field_name);
let mut field_usage = FieldUsage::empty(field_addr.field);
field_usage.add_field_idx(field_addr.idx, byte_range.len().into());
fields.push(field_usage);
}

0
src/directory/mmap_directory/file_watcher.rs → src/directory/file_watcher.rs
View File

6
src/directory/mmap_directory/mod.rs → src/directory/mmap_directory.rs
View File

@@ -1,5 +1,3 @@
mod file_watcher;
use std::collections::HashMap;
use std::fmt;
use std::fs::{self, File, OpenOptions};
@@ -9,7 +7,6 @@ use std::path::{Path, PathBuf};
use std::sync::{Arc, RwLock, Weak};
use common::StableDeref;
use file_watcher::FileWatcher;
use fs4::fs_std::FileExt;
#[cfg(all(feature = "mmap", unix))]
pub use memmap2::Advice;
@@ -21,6 +18,7 @@ use crate::core::META_FILEPATH;
use crate::directory::error::{
DeleteError, LockError, OpenDirectoryError, OpenReadError, OpenWriteError,
};
use crate::directory::file_watcher::FileWatcher;
use crate::directory::{
AntiCallToken, Directory, DirectoryLock, FileHandle, Lock, OwnedBytes, TerminatingWrite,
WatchCallback, WatchHandle, WritePtr,
@@ -676,7 +674,7 @@ mod tests {
let num_segments = reader.searcher().segment_readers().len();
assert!(num_segments <= 4);
let num_components_except_deletes_and_tempstore =
crate::index::SegmentComponent::iterator().len() - 1;
crate::index::SegmentComponent::iterator().len() - 2;
let max_num_mmapped = num_components_except_deletes_and_tempstore * num_segments;
assert_eventually(|| {
let num_mmapped = mmap_directory.get_cache_info().mmapped.len();

1
src/directory/mod.rs
View File

@@ -5,6 +5,7 @@ mod mmap_directory;
mod directory;
mod directory_lock;
mod file_watcher;
pub mod footer;
mod managed_directory;
mod ram_directory;

82
src/docset.rs
View File

@@ -40,8 +40,6 @@ pub trait DocSet: Send {
/// of `DocSet` should support it.
///
/// Calling `seek(TERMINATED)` is also legal and is the normal way to consume a `DocSet`.
///
/// `target` has to be larger or equal to `.doc()` when calling `seek`.
fn seek(&mut self, target: DocId) -> DocId {
let mut doc = self.doc();
debug_assert!(doc <= target);
@@ -51,57 +49,6 @@ pub trait DocSet: Send {
doc
}
/// !!!Dragons ahead!!!
/// In spirit, this is an approximate and dangerous version of `seek`.
///
/// It can leave the DocSet in an `invalid` state and might return a
/// lower bound of what the result of Seek would have been.
///
///
/// More accurately it returns either:
/// - Found if the target is in the docset. In that case, the DocSet is left in a valid state.
/// - SeekLowerBound(seek_lower_bound) if the target is not in the docset. In that case, The
/// DocSet can be the left in a invalid state. The DocSet should then only receives call to
/// `seek_danger(..)` until it returns `Found`, and get back to a valid state.
///
/// `seek_lower_bound` can be any `DocId` (in the docset or not) as long as it is in
/// `(target .. seek_result] U {TERMINATED}` where `seek_result` is the first document in the
/// docset greater than to `target`.
///
/// `seek_danger` may return `SeekLowerBound(TERMINATED)`.
///
/// Calling `seek_danger` with TERMINATED as a target is allowed,
/// and should always return NewTarget(TERMINATED) or anything larger as TERMINATED is NOT in
/// the DocSet.
///
/// DocSets that already have an efficient `seek` method don't need to implement
/// `seek_danger`.
///
/// Consecutive calls to seek_danger are guaranteed to have strictly increasing `target`
/// values.
fn seek_danger(&mut self, target: DocId) -> SeekDangerResult {
if target >= TERMINATED {
debug_assert!(target == TERMINATED);
// No need to advance.
return SeekDangerResult::SeekLowerBound(target);
}
// The default implementation does not include any
// `danger zone` behavior.
//
// It does not leave the scorer in an invalid state.
// For this reason, we can safely call `self.doc()`.
let mut doc = self.doc();
if doc < target {
doc = self.seek(target);
}
if doc == target {
SeekDangerResult::Found
} else {
SeekDangerResult::SeekLowerBound(doc)
}
}
/// Fills a given mutable buffer with the next doc ids from the
/// `DocSet`
///
@@ -147,15 +94,6 @@ pub trait DocSet: Send {
/// which would be the number of documents in the DocSet.
///
/// By default this returns `size_hint()`.
///
/// DocSets may have vastly different cost depending on their type,
/// e.g. an intersection with 10 hits is much cheaper than
/// a phrase search with 10 hits, since it needs to load positions.
///
/// ### Future Work
/// We may want to differentiate `DocSet` costs more more granular, e.g.
/// creation_cost, advance_cost, seek_cost on to get a good estimation
/// what query types to choose.
fn cost(&self) -> u64 {
self.size_hint() as u64
}
@@ -190,17 +128,6 @@ pub trait DocSet: Send {
}
}
#[derive(Clone, Copy, Debug, PartialEq, Eq)]
pub enum SeekDangerResult {
/// The target was found in the DocSet.
Found,
/// The target was not found in the DocSet.
/// We return a range in which the value could be.
/// The given target can be any DocId, that is <= than the first document
/// in the docset after the target.
SeekLowerBound(DocId),
}
impl DocSet for &mut dyn DocSet {
fn advance(&mut self) -> u32 {
(**self).advance()
@@ -210,10 +137,6 @@ impl DocSet for &mut dyn DocSet {
(**self).seek(target)
}
fn seek_danger(&mut self, target: DocId) -> SeekDangerResult {
(**self).seek_danger(target)
}
fn doc(&self) -> u32 {
(**self).doc()
}
@@ -246,11 +169,6 @@ impl<TDocSet: DocSet + ?Sized> DocSet for Box<TDocSet> {
unboxed.seek(target)
}
fn seek_danger(&mut self, target: DocId) -> SeekDangerResult {
let unboxed: &mut TDocSet = self.borrow_mut();
unboxed.seek_danger(target)
}
fn fill_buffer(&mut self, buffer: &mut [DocId; COLLECT_BLOCK_BUFFER_LEN]) -> usize {
let unboxed: &mut TDocSet = self.borrow_mut();
unboxed.fill_buffer(buffer)

4
src/fastfield/alive_bitset.rs
View File

@@ -162,7 +162,7 @@ mod tests {
mod bench {
use rand::prelude::IteratorRandom;
use rand::rng;
use rand::thread_rng;
use test::Bencher;
use super::AliveBitSet;
@@ -176,7 +176,7 @@ mod bench {
}
fn remove_rand(raw: &mut Vec<u32>) {
let i = (0..raw.len()).choose(&mut rng()).unwrap();
let i = (0..raw.len()).choose(&mut thread_rng()).unwrap();
raw.remove(i);
}

41
src/fastfield/mod.rs
View File

@@ -683,7 +683,7 @@ mod tests {
}
#[test]
fn test_datefastfield() -> crate::Result<()> {
fn test_datefastfield() {
let mut schema_builder = Schema::builder();
let date_field = schema_builder.add_date_field(
"date",
@@ -697,22 +697,28 @@ mod tests {
);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer = index.writer_for_tests()?;
let mut index_writer = index.writer_for_tests().unwrap();
index_writer.set_merge_policy(Box::new(NoMergePolicy));
index_writer.add_document(doc!(
date_field => DateTime::from_u64(1i64.to_u64()),
multi_date_field => DateTime::from_u64(2i64.to_u64()),
multi_date_field => DateTime::from_u64(3i64.to_u64())
))?;
index_writer.add_document(doc!(
date_field => DateTime::from_u64(4i64.to_u64())
))?;
index_writer.add_document(doc!(
multi_date_field => DateTime::from_u64(5i64.to_u64()),
multi_date_field => DateTime::from_u64(6i64.to_u64())
))?;
index_writer.commit()?;
let reader = index.reader()?;
index_writer
.add_document(doc!(
date_field => DateTime::from_u64(1i64.to_u64()),
multi_date_field => DateTime::from_u64(2i64.to_u64()),
multi_date_field => DateTime::from_u64(3i64.to_u64())
))
.unwrap();
index_writer
.add_document(doc!(
date_field => DateTime::from_u64(4i64.to_u64())
))
.unwrap();
index_writer
.add_document(doc!(
multi_date_field => DateTime::from_u64(5i64.to_u64()),
multi_date_field => DateTime::from_u64(6i64.to_u64())
))
.unwrap();
index_writer.commit().unwrap();
let reader = index.reader().unwrap();
let searcher = reader.searcher();
assert_eq!(searcher.segment_readers().len(), 1);
let segment_reader = searcher.segment_reader(0);
@@ -746,7 +752,6 @@ mod tests {
assert_eq!(dates[0].into_timestamp_nanos(), 5i64);
assert_eq!(dates[1].into_timestamp_nanos(), 6i64);
}
Ok(())
}
#[test]
@@ -879,7 +884,7 @@ mod tests {
const ONE_HOUR_IN_MICROSECS: i64 = 3_600 * 1_000_000;
let times: Vec<DateTime> = std::iter::repeat_with(|| {
// +- One hour.
let t = T0 + rng.random_range(-ONE_HOUR_IN_MICROSECS..ONE_HOUR_IN_MICROSECS);
let t = T0 + rng.gen_range(-ONE_HOUR_IN_MICROSECS..ONE_HOUR_IN_MICROSECS);
DateTime::from_timestamp_micros(t)
})
.take(1_000)

18
src/fastfield/readers.rs
View File

@@ -8,7 +8,7 @@ use columnar::{
};
use common::ByteCount;
use crate::core::json_utils::{encode_column_name, json_path_sep_to_dot};
use crate::core::json_utils::encode_column_name;
use crate::directory::FileSlice;
use crate::schema::{Field, FieldEntry, FieldType, Schema};
use crate::space_usage::{FieldUsage, PerFieldSpaceUsage};
@@ -39,15 +39,19 @@ impl FastFieldReaders {
self.resolve_column_name_given_default_field(column_name, default_field_opt)
}
pub(crate) fn space_usage(&self) -> io::Result<PerFieldSpaceUsage> {
pub(crate) fn space_usage(&self, schema: &Schema) -> io::Result<PerFieldSpaceUsage> {
let mut per_field_usages: Vec<FieldUsage> = Default::default();
for (mut field_name, column_handle) in self.columnar.iter_columns()? {
json_path_sep_to_dot(&mut field_name);
let space_usage = column_handle.space_usage()?;
let mut field_usage = FieldUsage::empty(field_name);
field_usage.set_column_usage(space_usage);
for (field, field_entry) in schema.fields() {
let column_handles = self.columnar.read_columns(field_entry.name())?;
let num_bytes: ByteCount = column_handles
.iter()
.map(|column_handle| column_handle.num_bytes())
.sum();
let mut field_usage = FieldUsage::empty(field);
field_usage.add_field_idx(0, num_bytes);
per_field_usages.push(field_usage);
}
// TODO fix space usage for JSON fields.
Ok(PerFieldSpaceUsage::new(per_field_usages))
}

6
src/fastfield/writer.rs
View File

@@ -189,6 +189,9 @@ impl FastFieldsWriter {
.record_str(doc_id, field_name, &token.text);
}
}
ReferenceValueLeaf::Geometry(_) => {
panic!("Geometry fields should not be routed to fast field writer")
}
},
ReferenceValue::Array(val) => {
// TODO: Check this is the correct behaviour we want.
@@ -320,6 +323,9 @@ fn record_json_value_to_columnar_writer<'a, V: Value<'a>>(
"Pre-tokenized string support in dynamic fields is not yet implemented"
)
}
ReferenceValueLeaf::Geometry(_) => {
unimplemented!("Geometry support in dynamic fields is not yet implemented")
}
},
ReferenceValue::Array(elements) => {
for el in elements {

6
src/fieldnorm/reader.rs
View File

@@ -2,7 +2,7 @@ use std::sync::Arc;
use super::{fieldnorm_to_id, id_to_fieldnorm};
use crate::directory::{CompositeFile, FileSlice, OwnedBytes};
use crate::schema::{Field, Schema};
use crate::schema::Field;
use crate::space_usage::PerFieldSpaceUsage;
use crate::DocId;
@@ -37,8 +37,8 @@ impl FieldNormReaders {
}
/// Return a break down of the space usage per field.
pub fn space_usage(&self, schema: &Schema) -> PerFieldSpaceUsage {
self.data.space_usage(schema)
pub fn space_usage(&self) -> PerFieldSpaceUsage {
self.data.space_usage()
}
/// Returns a handle to inner file

18
src/functional_test.rs
View File

@@ -1,6 +1,6 @@
use std::collections::HashSet;
use rand::{rng, Rng};
use rand::{thread_rng, Rng};
use crate::indexer::index_writer::MEMORY_BUDGET_NUM_BYTES_MIN;
use crate::schema::*;
@@ -29,7 +29,7 @@ fn test_functional_store() -> crate::Result<()> {
let index = Index::create_in_ram(schema);
let reader = index.reader()?;
let mut rng = rng();
let mut rng = thread_rng();
let mut index_writer: IndexWriter =
index.writer_with_num_threads(3, 3 * MEMORY_BUDGET_NUM_BYTES_MIN)?;
@@ -38,9 +38,9 @@ fn test_functional_store() -> crate::Result<()> {
let mut doc_id = 0u64;
for _iteration in 0..get_num_iterations() {
let num_docs: usize = rng.random_range(0..4);
let num_docs: usize = rng.gen_range(0..4);
if !doc_set.is_empty() {
let doc_to_remove_id = rng.random_range(0..doc_set.len());
let doc_to_remove_id = rng.gen_range(0..doc_set.len());
let removed_doc_id = doc_set.swap_remove(doc_to_remove_id);
index_writer.delete_term(Term::from_field_u64(id_field, removed_doc_id));
}
@@ -70,10 +70,10 @@ const LOREM: &str = "Doc Lorem ipsum dolor sit amet, consectetur adipiscing elit
cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat \
non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.";
fn get_text() -> String {
use rand::seq::IndexedRandom;
let mut rng = rng();
use rand::seq::SliceRandom;
let mut rng = thread_rng();
let tokens: Vec<_> = LOREM.split(' ').collect();
let random_val = rng.random_range(0..20);
let random_val = rng.gen_range(0..20);
(0..random_val)
.map(|_| tokens.choose(&mut rng).unwrap())
@@ -101,7 +101,7 @@ fn test_functional_indexing_unsorted() -> crate::Result<()> {
let index = Index::create_from_tempdir(schema)?;
let reader = index.reader()?;
let mut rng = rng();
let mut rng = thread_rng();
let mut index_writer: IndexWriter =
index.writer_with_num_threads(3, 3 * MEMORY_BUDGET_NUM_BYTES_MIN)?;
@@ -110,7 +110,7 @@ fn test_functional_indexing_unsorted() -> crate::Result<()> {
let mut uncommitted_docs: HashSet<u64> = HashSet::new();
for _ in 0..get_num_iterations() {
let random_val = rng.random_range(0..20);
let random_val = rng.gen_range(0..20);
if random_val == 0 {
index_writer.commit()?;
committed_docs.extend(&uncommitted_docs);

56
src/index/index_meta.rs
View File

@@ -1,6 +1,8 @@
use std::collections::HashSet;
use std::fmt;
use std::path::PathBuf;
use std::sync::atomic::AtomicBool;
use std::sync::Arc;
use serde::{Deserialize, Serialize};
@@ -11,9 +13,9 @@ use crate::store::Compressor;
use crate::{Inventory, Opstamp, TrackedObject};
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct DeleteMeta {
struct DeleteMeta {
num_deleted_docs: u32,
pub opstamp: Opstamp,
opstamp: Opstamp,
}
#[derive(Clone, Default)]
@@ -35,6 +37,7 @@ impl SegmentMetaInventory {
let inner = InnerSegmentMeta {
segment_id,
max_doc,
include_temp_doc_store: Arc::new(AtomicBool::new(true)),
deletes: None,
};
SegmentMeta::from(self.inventory.track(inner))
@@ -82,6 +85,15 @@ impl SegmentMeta {
self.tracked.segment_id
}
/// Removes the Component::TempStore from the alive list and
/// therefore marks the temp docstore file to be deleted by
/// the garbage collection.
pub fn untrack_temp_docstore(&self) {
self.tracked
.include_temp_doc_store
.store(false, std::sync::atomic::Ordering::Relaxed);
}
/// Returns the number of deleted documents.
pub fn num_deleted_docs(&self) -> u32 {
self.tracked
@@ -99,9 +111,20 @@ impl SegmentMeta {
/// is by removing all files that have been created by tantivy
/// and are not used by any segment anymore.
pub fn list_files(&self) -> HashSet<PathBuf> {
SegmentComponent::iterator()
.map(|component| self.relative_path(*component))
.collect::<HashSet<PathBuf>>()
if self
.tracked
.include_temp_doc_store
.load(std::sync::atomic::Ordering::Relaxed)
{
SegmentComponent::iterator()
.map(|component| self.relative_path(*component))
.collect::<HashSet<PathBuf>>()
} else {
SegmentComponent::iterator()
.filter(|comp| *comp != &SegmentComponent::TempStore)
.map(|component| self.relative_path(*component))
.collect::<HashSet<PathBuf>>()
}
}
/// Returns the relative path of a component of our segment.
@@ -115,9 +138,11 @@ impl SegmentMeta {
SegmentComponent::Positions => ".pos".to_string(),
SegmentComponent::Terms => ".term".to_string(),
SegmentComponent::Store => ".store".to_string(),
SegmentComponent::TempStore => ".store.temp".to_string(),
SegmentComponent::FastFields => ".fast".to_string(),
SegmentComponent::FieldNorms => ".fieldnorm".to_string(),
SegmentComponent::Delete => format!(".{}.del", self.delete_opstamp().unwrap_or(0)),
SegmentComponent::Spatial => ".spatial".to_string(),
});
PathBuf::from(path)
}
@@ -159,6 +184,7 @@ impl SegmentMeta {
segment_id: inner_meta.segment_id,
max_doc,
deletes: None,
include_temp_doc_store: Arc::new(AtomicBool::new(true)),
});
SegmentMeta { tracked }
}
@@ -177,6 +203,7 @@ impl SegmentMeta {
let tracked = self.tracked.map(move |inner_meta| InnerSegmentMeta {
segment_id: inner_meta.segment_id,
max_doc: inner_meta.max_doc,
include_temp_doc_store: Arc::new(AtomicBool::new(true)),
deletes: Some(delete_meta),
});
SegmentMeta { tracked }
@@ -187,7 +214,15 @@ impl SegmentMeta {
struct InnerSegmentMeta {
segment_id: SegmentId,
max_doc: u32,
pub deletes: Option<DeleteMeta>,
deletes: Option<DeleteMeta>,
/// If you want to avoid the SegmentComponent::TempStore file to be covered by
/// garbage collection and deleted, set this to true. This is used during merge.
#[serde(skip)]
#[serde(default = "default_temp_store")]
pub(crate) include_temp_doc_store: Arc<AtomicBool>,
}
fn default_temp_store() -> Arc<AtomicBool> {
Arc::new(AtomicBool::new(false))
}
impl InnerSegmentMeta {
@@ -370,10 +405,7 @@ mod tests {
schema_builder.build()
};
let index_metas = IndexMeta {
index_settings: IndexSettings {
docstore_compression: Compressor::None,
..Default::default()
},
index_settings: IndexSettings::default(),
segments: Vec::new(),
schema,
opstamp: 0u64,
@@ -382,7 +414,7 @@ mod tests {
let json = serde_json::ser::to_string(&index_metas).expect("serialization failed");
assert_eq!(
json,
r#"{"index_settings":{"docstore_compression":"none","docstore_blocksize":16384},"segments":[],"schema":[{"name":"text","type":"text","options":{"indexing":{"record":"position","fieldnorms":true,"tokenizer":"default"},"stored":false,"fast":false}}],"opstamp":0}"#
r#"{"index_settings":{"docstore_compression":"lz4","docstore_blocksize":16384},"segments":[],"schema":[{"name":"text","type":"text","options":{"indexing":{"record":"position","fieldnorms":true,"tokenizer":"default"},"stored":false,"fast":false}}],"opstamp":0}"#
);
let deser_meta: UntrackedIndexMeta = serde_json::from_str(&json).unwrap();
@@ -463,8 +495,6 @@ mod tests {
#[test]
#[cfg(feature = "lz4-compression")]
fn test_index_settings_default() {
use crate::store::Compressor;
let mut index_settings = IndexSettings::default();
assert_eq!(
index_settings,

2
src/index/segment.rs
View File

@@ -46,7 +46,7 @@ impl Segment {
///
/// This method is only used when updating `max_doc` from 0
/// as we finalize a fresh new segment.
pub fn with_max_doc(self, max_doc: u32) -> Segment {
pub(crate) fn with_max_doc(self, max_doc: u32) -> Segment {
Segment {
index: self.index,
meta: self.meta.with_max_doc(max_doc),

8
src/index/segment_component.rs
View File

@@ -23,22 +23,28 @@ pub enum SegmentComponent {
/// Accessing a document from the store is relatively slow, as it
/// requires to decompress the entire block it belongs to.
Store,
/// Temporary storage of the documents, before streamed to `Store`.
TempStore,
/// Bitset describing which document of the segment is alive.
/// (It was representing deleted docs but changed to represent alive docs from v0.17)
Delete,
/// HUSH
Spatial,
}
impl SegmentComponent {
/// Iterates through the components.
pub fn iterator() -> slice::Iter<'static, SegmentComponent> {
static SEGMENT_COMPONENTS: [SegmentComponent; 7] = [
static SEGMENT_COMPONENTS: [SegmentComponent; 9] = [
SegmentComponent::Postings,
SegmentComponent::Positions,
SegmentComponent::FastFields,
SegmentComponent::FieldNorms,
SegmentComponent::Terms,
SegmentComponent::Store,
SegmentComponent::TempStore,
SegmentComponent::Delete,
SegmentComponent::Spatial,
];
SEGMENT_COMPONENTS.iter()
}

25
src/index/segment_reader.rs
View File

@@ -14,6 +14,7 @@ use crate::index::{InvertedIndexReader, Segment, SegmentComponent, SegmentId};
use crate::json_utils::json_path_sep_to_dot;
use crate::schema::{Field, IndexRecordOption, Schema, Type};
use crate::space_usage::SegmentSpaceUsage;
use crate::spatial::reader::SpatialReaders;
use crate::store::StoreReader;
use crate::termdict::TermDictionary;
use crate::{DocId, Opstamp};
@@ -43,6 +44,7 @@ pub struct SegmentReader {
positions_composite: CompositeFile,
fast_fields_readers: FastFieldReaders,
fieldnorm_readers: FieldNormReaders,
spatial_readers: SpatialReaders,
store_file: FileSlice,
alive_bitset_opt: Option<AliveBitSet>,
@@ -92,6 +94,11 @@ impl SegmentReader {
&self.fast_fields_readers
}
/// HUSH
pub fn spatial_fields(&self) -> &SpatialReaders {
&self.spatial_readers
}
/// Accessor to the `FacetReader` associated with a given `Field`.
pub fn facet_reader(&self, field_name: &str) -> crate::Result<FacetReader> {
let schema = self.schema();
@@ -173,6 +180,12 @@ impl SegmentReader {
let fast_fields_readers = FastFieldReaders::open(fast_fields_data, schema.clone())?;
let fieldnorm_data = segment.open_read(SegmentComponent::FieldNorms)?;
let fieldnorm_readers = FieldNormReaders::open(fieldnorm_data)?;
let spatial_readers = if schema.contains_spatial_field() {
let spatial_data = segment.open_read(SegmentComponent::Spatial)?;
SpatialReaders::open(spatial_data)?
} else {
SpatialReaders::empty()
};
let original_bitset = if segment.meta().has_deletes() {
let alive_doc_file_slice = segment.open_read(SegmentComponent::Delete)?;
@@ -198,6 +211,7 @@ impl SegmentReader {
postings_composite,
fast_fields_readers,
fieldnorm_readers,
spatial_readers,
segment_id: segment.id(),
delete_opstamp: segment.meta().delete_opstamp(),
store_file,
@@ -455,11 +469,12 @@ impl SegmentReader {
pub fn space_usage(&self) -> io::Result<SegmentSpaceUsage> {
Ok(SegmentSpaceUsage::new(
self.num_docs(),
self.termdict_composite.space_usage(self.schema()),
self.postings_composite.space_usage(self.schema()),
self.positions_composite.space_usage(self.schema()),
self.fast_fields_readers.space_usage()?,
self.fieldnorm_readers.space_usage(self.schema()),
self.termdict_composite.space_usage(),
self.postings_composite.space_usage(),
self.positions_composite.space_usage(),
self.fast_fields_readers.space_usage(self.schema())?,
self.fieldnorm_readers.space_usage(),
self.spatial_readers.space_usage(),
self.get_store_reader(0)?.space_usage(),
self.alive_bitset_opt
.as_ref()

54
src/indexer/delete_queue.rs
View File

@@ -4,37 +4,38 @@ use std::sync::{Arc, RwLock, Weak};
use super::operation::DeleteOperation;
use crate::Opstamp;
/// The DeleteQueue is similar in conceptually to a multiple
/// consumer single producer broadcast channel.
///
/// All consumer will receive all messages.
///
/// Consumer of the delete queue are holding a `DeleteCursor`,
/// which points to a specific place of the `DeleteQueue`.
///
/// New consumer can be created in two ways
/// - calling `delete_queue.cursor()` returns a cursor, that will include all future delete
/// operation (and some or none of the past operations... The client is in charge of checking the
/// opstamps.).
/// - cloning an existing cursor returns a new cursor, that is at the exact same position, and can
/// now advance independently from the original cursor.
// The DeleteQueue is similar in conceptually to a multiple
// consumer single producer broadcast channel.
//
// All consumer will receive all messages.
//
// Consumer of the delete queue are holding a `DeleteCursor`,
// which points to a specific place of the `DeleteQueue`.
//
// New consumer can be created in two ways
// - calling `delete_queue.cursor()` returns a cursor, that will include all future delete operation
// (and some or none of the past operations... The client is in charge of checking the opstamps.).
// - cloning an existing cursor returns a new cursor, that is at the exact same position, and can
// now advance independently from the original cursor.
#[derive(Default)]
struct InnerDeleteQueue {
writer: Vec<DeleteOperation>,
last_block: Weak<Block>,
}
/// The delete queue is a linked list storing delete operations.
///
/// Several consumers can hold a reference to it. Delete operations
/// get dropped/gc'ed when no more consumers are holding a reference
/// to them.
#[derive(Clone, Default)]
#[derive(Clone)]
pub struct DeleteQueue {
inner: Arc<RwLock<InnerDeleteQueue>>,
}
impl DeleteQueue {
// Creates a new delete queue.
pub fn new() -> DeleteQueue {
DeleteQueue {
inner: Arc::default(),
}
}
fn get_last_block(&self) -> Arc<Block> {
{
// try get the last block with simply acquiring the read lock.
@@ -57,10 +58,10 @@ impl DeleteQueue {
block
}
/// Creates a new cursor that makes it possible to
/// consume future delete operations.
///
/// Past delete operations are not accessible.
// Creates a new cursor that makes it possible to
// consume future delete operations.
//
// Past delete operations are not accessible.
pub fn cursor(&self) -> DeleteCursor {
let last_block = self.get_last_block();
let operations_len = last_block.operations.len();
@@ -70,7 +71,7 @@ impl DeleteQueue {
}
}
/// Appends a new delete operations.
// Appends a new delete operations.
pub fn push(&self, delete_operation: DeleteOperation) {
self.inner
.write()
@@ -168,7 +169,6 @@ struct Block {
next: NextBlock,
}
/// As we process delete operations, keeps track of our position.
#[derive(Clone)]
pub struct DeleteCursor {
block: Arc<Block>,
@@ -261,7 +261,7 @@ mod tests {
#[test]
fn test_deletequeue() {
let delete_queue = DeleteQueue::default();
let delete_queue = DeleteQueue::new();
let make_op = |i: usize| DeleteOperation {
opstamp: i as u64,

6
src/indexer/index_writer.rs
View File

@@ -128,7 +128,7 @@ fn compute_deleted_bitset(
/// is `==` target_opstamp.
/// For instance, there was no delete operation between the state of the `segment_entry` and
/// the `target_opstamp`, `segment_entry` is not updated.
pub fn advance_deletes(
pub(crate) fn advance_deletes(
mut segment: Segment,
segment_entry: &mut SegmentEntry,
target_opstamp: Opstamp,
@@ -218,7 +218,7 @@ fn index_documents<D: Document>(
let alive_bitset_opt = apply_deletes(&segment_with_max_doc, &mut delete_cursor, &doc_opstamps)?;
let meta = segment_with_max_doc.meta().clone();
meta.untrack_temp_docstore();
// update segment_updater inventory to remove tempstore
let segment_entry = SegmentEntry::new(meta, delete_cursor, alive_bitset_opt);
segment_updater.schedule_add_segment(segment_entry).wait()?;
@@ -303,7 +303,7 @@ impl<D: Document> IndexWriter<D> {
let (document_sender, document_receiver) =
crossbeam_channel::bounded(PIPELINE_MAX_SIZE_IN_DOCS);
let delete_queue = DeleteQueue::default();
let delete_queue = DeleteQueue::new();
let current_opstamp = index.load_metas()?.opstamp;

80
src/indexer/indexing_term.rs
View File

@@ -3,21 +3,21 @@ use std::net::Ipv6Addr;
use columnar::MonotonicallyMappableToU128;
use crate::fastfield::FastValue;
use crate::schema::Field;
use crate::schema::{Field, Type};
/// IndexingTerm is used to represent a term during indexing.
/// It's a serialized representation over field and value.
/// Term represents the value that the token can take.
/// It's a serialized representation over different types.
///
/// It actually wraps a `Vec<u8>`. The first 4 bytes are the field.
/// It actually wraps a `Vec<u8>`. The first 5 bytes are metadata.
/// 4 bytes are the field id, and the last byte is the type.
///
/// We serialize the field, because we index everything in a single
/// global term dictionary during indexing.
/// The serialized value `ValueBytes` is considered everything after the 4 first bytes (term id).
#[derive(Clone)]
pub(crate) struct IndexingTerm<B = Vec<u8>>(B)
where B: AsRef<[u8]>;
/// The number of bytes used as metadata by `Term`.
const TERM_METADATA_LENGTH: usize = 4;
const TERM_METADATA_LENGTH: usize = 5;
impl IndexingTerm {
/// Create a new Term with a buffer with a given capacity.
@@ -31,9 +31,10 @@ impl IndexingTerm {
/// Use `clear_with_field_and_type` in that case.
///
/// Sets field and the type.
pub(crate) fn set_field(&mut self, field: Field) {
pub(crate) fn set_field_and_type(&mut self, field: Field, typ: Type) {
assert!(self.is_empty());
self.0[0..4].clone_from_slice(field.field_id().to_be_bytes().as_ref());
self.0[4] = typ.to_code();
}
/// Is empty if there are no value bytes.
@@ -41,10 +42,10 @@ impl IndexingTerm {
self.0.len() == TERM_METADATA_LENGTH
}
/// Removes the value_bytes and set the field
pub(crate) fn clear_with_field(&mut self, field: Field) {
/// Removes the value_bytes and set the field and type code.
pub(crate) fn clear_with_field_and_type(&mut self, typ: Type, field: Field) {
self.truncate_value_bytes(0);
self.set_field(field);
self.set_field_and_type(field, typ);
}
/// Sets a u64 value in the term.
@@ -121,23 +122,6 @@ impl IndexingTerm {
impl<B> IndexingTerm<B>
where B: AsRef<[u8]>
{
/// Wraps serialized term bytes.
///
/// The input buffer is expected to be the concatenation of the big endian encoded field id
/// followed by the serialized value bytes (type tag + payload).
#[inline]
pub fn wrap(serialized_term: B) -> IndexingTerm<B> {
debug_assert!(serialized_term.as_ref().len() >= TERM_METADATA_LENGTH);
IndexingTerm(serialized_term)
}
/// Returns the field this term belongs to.
#[inline]
pub fn field(&self) -> Field {
let field_id_bytes: [u8; 4] = self.0.as_ref()[..4].try_into().unwrap();
Field::from_field_id(u32::from_be_bytes(field_id_bytes))
}
/// Returns the serialized representation of Term.
/// This includes field_id, value type and value.
///
@@ -152,7 +136,6 @@ where B: AsRef<[u8]>
#[cfg(test)]
mod tests {
use super::IndexingTerm;
use crate::schema::*;
#[test]
@@ -160,55 +143,42 @@ mod tests {
let mut schema_builder = Schema::builder();
schema_builder.add_text_field("text", STRING);
let title_field = schema_builder.add_text_field("title", STRING);
let mut term = IndexingTerm::with_capacity(0);
term.set_field(title_field);
term.set_bytes(b"test");
let term = Term::from_field_text(title_field, "test");
assert_eq!(term.field(), title_field);
assert_eq!(term.serialized_term(), b"\x00\x00\x00\x01test".to_vec())
assert_eq!(term.typ(), Type::Str);
assert_eq!(term.value().as_str(), Some("test"))
}
/// Size (in bytes) of the buffer of a fast value (u64, i64, f64, or date) term.
/// <field> + <type byte> + <value len>
///
/// - <field> is a big endian encoded u32 field id
/// - <type_byte>'s most significant bit expresses whether the term is a json term or not The
/// remaining 7 bits are used to encode the type of the value. If this is a JSON term, the
/// type is the type of the leaf of the json.
/// - <value> is, if this is not the json term, a binary representation specific to the type.
/// If it is a JSON Term, then it is prepended with the path that leads to this leaf value.
const FAST_VALUE_TERM_LEN: usize = 4 + 8;
const FAST_VALUE_TERM_LEN: usize = 4 + 1 + 8;
#[test]
pub fn test_term_u64() {
let mut schema_builder = Schema::builder();
let count_field = schema_builder.add_u64_field("count", INDEXED);
let mut term = IndexingTerm::with_capacity(0);
term.set_field(count_field);
term.set_u64(983u64);
let term = Term::from_field_u64(count_field, 983u64);
assert_eq!(term.field(), count_field);
assert_eq!(term.typ(), Type::U64);
assert_eq!(term.serialized_term().len(), FAST_VALUE_TERM_LEN);
assert_eq!(term.value().as_u64(), Some(983u64))
}
#[test]
pub fn test_term_bool() {
let mut schema_builder = Schema::builder();
let bool_field = schema_builder.add_bool_field("bool", INDEXED);
let term = {
let mut term = IndexingTerm::with_capacity(0);
term.set_field(bool_field);
term.set_bool(true);
term
};
let term = Term::from_field_bool(bool_field, true);
assert_eq!(term.field(), bool_field);
assert_eq!(term.typ(), Type::Bool);
assert_eq!(term.serialized_term().len(), FAST_VALUE_TERM_LEN);
}
#[test]
pub fn indexing_term_wrap_extracts_field() {
let field = Field::from_field_id(7u32);
let mut term = IndexingTerm::with_capacity(0);
term.set_field(field);
term.append_bytes(b"abc");
let wrapped = IndexingTerm::wrap(term.serialized_term());
assert_eq!(wrapped.field(), field);
assert_eq!(wrapped.serialized_term(), term.serialized_term());
assert_eq!(term.value().as_bool(), Some(true))
}
}

92
src/indexer/merger.rs
View File

@@ -1,3 +1,5 @@
use std::collections::HashMap;
use std::io::{BufWriter, Write};
use std::sync::Arc;
use columnar::{
@@ -6,6 +8,7 @@ use columnar::{
use common::ReadOnlyBitSet;
use itertools::Itertools;
use measure_time::debug_time;
use tempfile::NamedTempFile;
use crate::directory::WritePtr;
use crate::docset::{DocSet, TERMINATED};
@@ -17,6 +20,8 @@ use crate::indexer::doc_id_mapping::{MappingType, SegmentDocIdMapping};
use crate::indexer::SegmentSerializer;
use crate::postings::{InvertedIndexSerializer, Postings, SegmentPostings};
use crate::schema::{value_type_to_column_type, Field, FieldType, Schema};
use crate::spatial::bkd::LeafPageIterator;
use crate::spatial::triangle::Triangle;
use crate::store::StoreWriter;
use crate::termdict::{TermMerger, TermOrdinal};
use crate::{DocAddress, DocId, InvertedIndexReader};
@@ -170,6 +175,7 @@ impl IndexMerger {
let mut readers = vec![];
for (segment, new_alive_bitset_opt) in segments.iter().zip(alive_bitset_opt) {
if segment.meta().num_docs() > 0 {
dbg!("segment");
let reader =
SegmentReader::open_with_custom_alive_set(segment, new_alive_bitset_opt)?;
readers.push(reader);
@@ -520,6 +526,89 @@ impl IndexMerger {
Ok(())
}
fn write_spatial_fields(
&self,
serializer: &mut SegmentSerializer,
doc_id_mapping: &SegmentDocIdMapping,
) -> crate::Result<()> {
/// We need to rebuild a BKD-tree based off the list of triangles.
///
/// Because the data can be large, we do this by writing the sequence of triangles to
/// disk, and mmapping it as mutable slice, and calling the same code as what
/// is done for the segment serialization.
///
/// The OS is in charge of deciding how to handle its page cache.
/// This is the same as what would have happened with swapping,
/// except by explicitly mapping the file, the OS is more likely to
/// swap, the memory will not be accounted as anonymous memory,
/// swap space is reserved etc.
use crate::spatial::bkd::Segment;
let Some(mut spatial_serializer) = serializer.extract_spatial_serializer() else {
// The schema does not contain any spatial field.
return Ok(());
};
let mut segment_mappings: Vec<Vec<Option<DocId>>> = Vec::new();
for reader in &self.readers {
let max_doc = reader.max_doc();
segment_mappings.push(vec![None; max_doc as usize]);
}
for (new_doc_id, old_doc_addr) in doc_id_mapping.iter_old_doc_addrs().enumerate() {
segment_mappings[old_doc_addr.segment_ord as usize][old_doc_addr.doc_id as usize] =
Some(new_doc_id as DocId);
}
let mut temp_files: HashMap<Field, NamedTempFile> = HashMap::new();
for (field, field_entry) in self.schema.fields() {
if matches!(field_entry.field_type(), FieldType::Spatial(_)) {
temp_files.insert(field, NamedTempFile::new()?);
}
}
for (segment_ord, reader) in self.readers.iter().enumerate() {
for (field, temp_file) in &mut temp_files {
let mut buf_temp_file = BufWriter::new(temp_file);
let spatial_readers = reader.spatial_fields();
let Some(spatial_reader) = spatial_readers.get_field(*field)? else {
continue;
};
let segment = Segment::new(spatial_reader.get_bytes());
for triangle_result in LeafPageIterator::new(&segment) {
let triangles = triangle_result?;
for triangle in triangles {
if let Some(new_doc_id) =
segment_mappings[segment_ord][triangle.doc_id as usize]
{
// This is really just a temporary file, not meant to be portable, so we
// use native endianness here.
for &word in &triangle.words {
buf_temp_file.write_all(&word.to_ne_bytes())?;
}
buf_temp_file.write_all(&new_doc_id.to_ne_bytes())?;
}
}
}
buf_temp_file.flush()?;
// No need to fsync here. This file is not here for persistency.
}
}
for (field, temp_file) in temp_files {
// Memory map the triangle file.
use memmap2::MmapOptions;
let mmap = unsafe { MmapOptions::new().map_mut(temp_file.as_file())? };
// Cast to &[Triangle] slice
let triangle_count = mmap.len() / std::mem::size_of::<Triangle>();
let triangles = unsafe {
std::slice::from_raw_parts_mut(mmap.as_ptr() as *mut Triangle, triangle_count)
};
// Get spatial writer and rebuild block kd-tree.
spatial_serializer.serialize_field(field, triangles)?;
}
spatial_serializer.close()?;
Ok(())
}
/// Writes the merged segment by pushing information
/// to the `SegmentSerializer`.
///
@@ -544,9 +633,10 @@ impl IndexMerger {
debug!("write-storagefields");
self.write_storable_fields(serializer.get_store_writer())?;
debug!("write-spatialfields");
self.write_spatial_fields(&mut serializer, &doc_id_mapping)?;
debug!("write-fastfields");
self.write_fast_fields(serializer.get_fast_field_write(), doc_id_mapping)?;
debug!("close-serializer");
serializer.close()?;
Ok(self.max_doc)

6
src/indexer/mod.rs
View File

@@ -4,7 +4,6 @@
//! `IndexWriter` is the main entry point for that, which created from
//! [`Index::writer`](crate::Index::writer).
/// Delete queue implementation for broadcasting delete operations to consumers.
pub(crate) mod delete_queue;
pub(crate) mod path_to_unordered_id;
@@ -33,11 +32,12 @@ mod stamper;
use crossbeam_channel as channel;
use smallvec::SmallVec;
pub use self::index_writer::{advance_deletes, IndexWriter, IndexWriterOptions};
pub use self::index_writer::{IndexWriter, IndexWriterOptions};
pub use self::log_merge_policy::LogMergePolicy;
pub use self::merge_operation::MergeOperation;
pub use self::merge_policy::{MergeCandidate, MergePolicy, NoMergePolicy};
pub use self::operation::{AddOperation, DeleteOperation, UserOperation};
use self::operation::AddOperation;
pub use self::operation::UserOperation;
pub use self::prepared_commit::PreparedCommit;
pub use self::segment_entry::SegmentEntry;
pub(crate) use self::segment_serializer::SegmentSerializer;

6
src/indexer/operation.rs
View File

@@ -5,20 +5,14 @@ use crate::Opstamp;
/// Timestamped Delete operation.
pub struct DeleteOperation {
/// Operation stamp.
/// It is used to check whether the delete operation
/// applies to an added document operation.
pub opstamp: Opstamp,
/// Weight is used to define the set of documents to be deleted.
pub target: Box<dyn Weight>,
}
/// Timestamped Add operation.
#[derive(Eq, PartialEq, Debug)]
pub struct AddOperation<D: Document = TantivyDocument> {
/// Operation stamp.
pub opstamp: Opstamp,
/// Document to be added.
pub document: D,
}

2
src/indexer/segment_register.rs
View File

@@ -117,7 +117,7 @@ mod tests {
#[test]
fn test_segment_register() {
let inventory = SegmentMetaInventory::default();
let delete_queue = DeleteQueue::default();
let delete_queue = DeleteQueue::new();
let mut segment_register = SegmentRegister::default();
let segment_id_a = SegmentId::generate_random();

19
src/indexer/segment_serializer.rs
View File

@@ -4,6 +4,7 @@ use crate::directory::WritePtr;
use crate::fieldnorm::FieldNormsSerializer;
use crate::index::{Segment, SegmentComponent};
use crate::postings::InvertedIndexSerializer;
use crate::spatial::serializer::SpatialSerializer;
use crate::store::StoreWriter;
/// Segment serializer is in charge of laying out on disk
@@ -12,6 +13,7 @@ pub struct SegmentSerializer {
segment: Segment,
pub(crate) store_writer: StoreWriter,
fast_field_write: WritePtr,
spatial_serializer: Option<SpatialSerializer>,
fieldnorms_serializer: Option<FieldNormsSerializer>,
postings_serializer: InvertedIndexSerializer,
}
@@ -35,11 +37,20 @@ impl SegmentSerializer {
let fieldnorms_write = segment.open_write(SegmentComponent::FieldNorms)?;
let fieldnorms_serializer = FieldNormsSerializer::from_write(fieldnorms_write)?;
let spatial_serializer: Option<SpatialSerializer> =
if segment.schema().contains_spatial_field() {
let spatial_write = segment.open_write(SegmentComponent::Spatial)?;
Some(SpatialSerializer::from_write(spatial_write)?)
} else {
None
};
let postings_serializer = InvertedIndexSerializer::open(&mut segment)?;
Ok(SegmentSerializer {
segment,
store_writer,
fast_field_write,
spatial_serializer,
fieldnorms_serializer: Some(fieldnorms_serializer),
postings_serializer,
})
@@ -64,6 +75,11 @@ impl SegmentSerializer {
&mut self.fast_field_write
}
/// Accessor to the `SpatialSerializer`
pub fn extract_spatial_serializer(&mut self) -> Option<SpatialSerializer> {
self.spatial_serializer.take()
}
/// Extract the field norm serializer.
///
/// Note the fieldnorms serializer can only be extracted once.
@@ -81,6 +97,9 @@ impl SegmentSerializer {
if let Some(fieldnorms_serializer) = self.extract_fieldnorms_serializer() {
fieldnorms_serializer.close()?;
}
if let Some(spatial_serializer) = self.extract_spatial_serializer() {
spatial_serializer.close()?;
}
self.fast_field_write.terminate()?;
self.postings_serializer.close()?;
self.store_writer.close()?;

26
src/indexer/segment_writer.rs
View File

@@ -16,6 +16,7 @@ use crate::postings::{
};
use crate::schema::document::{Document, Value};
use crate::schema::{FieldEntry, FieldType, Schema, DATE_TIME_PRECISION_INDEXED};
use crate::spatial::writer::SpatialWriter;
use crate::tokenizer::{FacetTokenizer, PreTokenizedStream, TextAnalyzer, Tokenizer};
use crate::{DocId, Opstamp, TantivyError};
@@ -52,6 +53,7 @@ pub struct SegmentWriter {
pub(crate) segment_serializer: SegmentSerializer,
pub(crate) fast_field_writers: FastFieldsWriter,
pub(crate) fieldnorms_writer: FieldNormsWriter,
pub(crate) spatial_writer: SpatialWriter,
pub(crate) json_path_writer: JsonPathWriter,
pub(crate) json_positions_per_path: IndexingPositionsPerPath,
pub(crate) doc_opstamps: Vec<Opstamp>,
@@ -104,6 +106,7 @@ impl SegmentWriter {
ctx: IndexingContext::new(table_size),
per_field_postings_writers,
fieldnorms_writer: FieldNormsWriter::for_schema(&schema),
spatial_writer: SpatialWriter::default(),
json_path_writer: JsonPathWriter::default(),
json_positions_per_path: IndexingPositionsPerPath::default(),
segment_serializer,
@@ -130,6 +133,7 @@ impl SegmentWriter {
self.ctx,
self.fast_field_writers,
&self.fieldnorms_writer,
&mut self.spatial_writer,
self.segment_serializer,
)?;
Ok(self.doc_opstamps)
@@ -142,6 +146,7 @@ impl SegmentWriter {
+ self.fieldnorms_writer.mem_usage()
+ self.fast_field_writers.mem_usage()
+ self.segment_serializer.mem_usage()
+ self.spatial_writer.mem_usage()
}
fn index_document<D: Document>(&mut self, doc: &D) -> crate::Result<()> {
@@ -171,7 +176,7 @@ impl SegmentWriter {
let (term_buffer, ctx) = (&mut self.term_buffer, &mut self.ctx);
let postings_writer: &mut dyn PostingsWriter =
self.per_field_postings_writers.get_for_field_mut(field);
term_buffer.clear_with_field(field);
term_buffer.clear_with_field_and_type(field_entry.field_type().value_type(), field);
match field_entry.field_type() {
FieldType::Facet(_) => {
@@ -338,6 +343,13 @@ impl SegmentWriter {
self.fieldnorms_writer.record(doc_id, field, num_vals);
}
}
FieldType::Spatial(_) => {
for value in values {
if let Some(geometry) = value.as_geometry() {
self.spatial_writer.add_geometry(doc_id, field, *geometry);
}
}
}
}
}
Ok(())
@@ -392,12 +404,16 @@ fn remap_and_write(
ctx: IndexingContext,
fast_field_writers: FastFieldsWriter,
fieldnorms_writer: &FieldNormsWriter,
spatial_writer: &mut SpatialWriter,
mut serializer: SegmentSerializer,
) -> crate::Result<()> {
debug!("remap-and-write");
if let Some(fieldnorms_serializer) = serializer.extract_fieldnorms_serializer() {
fieldnorms_writer.serialize(fieldnorms_serializer)?;
}
if let Some(spatial_serializer) = serializer.extract_spatial_serializer() {
spatial_writer.serialize(spatial_serializer)?;
}
let fieldnorm_data = serializer
.segment()
.open_read(SegmentComponent::FieldNorms)?;
@@ -421,9 +437,10 @@ fn remap_and_write(
#[cfg(test)]
mod tests {
use std::collections::BTreeMap;
use std::path::Path;
use std::path::{Path, PathBuf};
use columnar::ColumnType;
use tempfile::TempDir;
use crate::collector::{Count, TopDocs};
use crate::directory::RamDirectory;
@@ -1066,7 +1083,10 @@ mod tests {
let mut schema_builder = Schema::builder();
schema_builder.add_text_field("title", text_options);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let tempdir = TempDir::new().unwrap();
let tempdir_path = PathBuf::from(tempdir.path());
Index::create_in_dir(&tempdir_path, schema).unwrap();
let index = Index::open_in_dir(tempdir_path).unwrap();
let schema = index.schema();
let mut index_writer = index.writer(50_000_000).unwrap();
let title = schema.get_field("title").unwrap();

23
src/lib.rs
View File

@@ -17,7 +17,6 @@
//!
//! ```rust
//! # use std::path::Path;
//! # use std::fs;
//! # use tempfile::TempDir;
//! # use tantivy::collector::TopDocs;
//! # use tantivy::query::QueryParser;
@@ -28,11 +27,8 @@
//! # // Let's create a temporary directory for the
//! # // sake of this example
//! # if let Ok(dir) = TempDir::new() {
//! # let index_path = dir.path().join("index");
//! # // In case the directory already exists, we remove it
//! # let _ = fs::remove_dir_all(&index_path);
//! # fs::create_dir_all(&index_path).unwrap();
//! # run_example(&index_path).unwrap();
//! # run_example(dir.path()).unwrap();
//! # dir.close().unwrap();
//! # }
//! # }
//! #
@@ -195,6 +191,7 @@ pub mod fieldnorm;
pub mod index;
pub mod positions;
pub mod postings;
pub mod spatial;
/// Module containing the different query implementations.
pub mod query;
@@ -207,7 +204,6 @@ mod docset;
mod reader;
#[cfg(test)]
#[cfg(feature = "mmap")]
mod compat_tests;
pub use self::reader::{IndexReader, IndexReaderBuilder, ReloadPolicy, Warmer};
@@ -221,7 +217,9 @@ use once_cell::sync::Lazy;
use serde::{Deserialize, Serialize};
pub use self::docset::{DocSet, COLLECT_BLOCK_BUFFER_LEN, TERMINATED};
pub use crate::core::{json_utils, Executor, Searcher, SearcherGeneration};
#[doc(hidden)]
pub use crate::core::json_utils;
pub use crate::core::{Executor, Searcher, SearcherGeneration};
pub use crate::directory::Directory;
pub use crate::index::{
Index, IndexBuilder, IndexMeta, IndexSettings, InvertedIndexReader, Order, Segment,
@@ -377,7 +375,7 @@ pub mod tests {
use common::{BinarySerializable, FixedSize};
use query_grammar::{UserInputAst, UserInputLeaf, UserInputLiteral};
use rand::distr::{Bernoulli, Uniform};
use rand::distributions::{Bernoulli, Uniform};
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use time::OffsetDateTime;
@@ -428,7 +426,7 @@ pub mod tests {
pub fn generate_nonunique_unsorted(max_value: u32, n_elems: usize) -> Vec<u32> {
let seed: [u8; 32] = [1; 32];
StdRng::from_seed(seed)
.sample_iter(&Uniform::new(0u32, max_value).unwrap())
.sample_iter(&Uniform::new(0u32, max_value))
.take(n_elems)
.collect::<Vec<u32>>()
}
@@ -1175,11 +1173,12 @@ pub mod tests {
#[test]
fn test_validate_checksum() -> crate::Result<()> {
let index_path = tempfile::tempdir().expect("dir");
let mut builder = Schema::builder();
let body = builder.add_text_field("body", TEXT | STORED);
let schema = builder.build();
let index = Index::create_in_ram(schema);
let mut writer: IndexWriter = index.writer_for_tests()?;
let index = Index::create_in_dir(&index_path, schema)?;
let mut writer: IndexWriter = index.writer(50_000_000)?;
writer.set_merge_policy(Box::new(NoMergePolicy));
for _ in 0..5000 {
writer.add_document(doc!(body => "foo"))?;

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