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base: rust:refact-codec-trait
Branches Tags
rust:main rust:stuhood.upstream-erased-sort-computer rust:trinity.pointard/ff-query rust:bucket_id_agg rust:paradedb/fix-agg-validation rust:flatheadmill-geo rust:paradedb-paradedb/fix-overflow-issue rust:low_card_optimization rust:paul.masurel/clippy rust:fix_size_hint 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:optional_column
Branches Tags
rust:stuhood.upstream-erased-sort-computer rust:main rust:trinity.pointard/ff-query rust:bucket_id_agg rust:paradedb/fix-agg-validation rust:flatheadmill-geo rust:paradedb-paradedb/fix-overflow-issue rust:low_card_optimization rust:paul.masurel/clippy rust:fix_size_hint 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

282 Commits
refact-cod ... optional_c

Author SHA1 Message Date
Pascal Seitz
208e5fd61a remove superfluous impls 2022-11-21 10:50:53 +08:00
PSeitz
caca4cdda4 Apply suggestions from code review 
Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-11-21 03:42:52 +01:00
Pascal Seitz
191fe5101b migrate to OptionalColumn 2022-11-18 15:09:15 +08:00
Pascal Seitz
c4474fef3a add OptionalColumn 2022-11-18 12:30:03 +08:00
trinity-1686a
e758080465 add support for TermSetQuery in query parser (#1683) 2022-11-17 16:49:49 +01:00
Paul Masurel
2a39289a1b Handle escaped dot in json path in the QueryParser. (#1682) 2022-11-16 07:18:34 +09:00
Adam Reichold
ca6231170e Make the built-in stop word lists selectable via the Language enum already used by the Stemmer filter. (#1671) 2022-11-15 17:40:25 +09:00
PSeitz
eda6e5a10a Merge pull request #1681 from quickwit-oss/ip_range_query_multi 
remove Column from MultiValuedU128FastFieldReader
 2022-11-15 09:27:46 +08:00
Pascal Seitz
8641155cbb remove column from MultiValuedU128FastFieldReader 2022-11-14 18:49:15 +08:00
PSeitz
9a090ed994 Merge pull request #1659 from quickwit-oss/ip_range_query_multi 
add support for ip range query on multivalue fastfields
 2022-11-14 15:17:41 +08:00
Pascal Seitz
b7d0dd154a fmt 2022-11-14 14:49:15 +08:00
PSeitz
ce10fab20f Apply suggestions from code review 
Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-11-14 14:21:53 +08:00
Pascal Seitz
e034328a8b Improve position_to_docid, refactor, add tests 2022-11-14 14:21:53 +08:00
Pascal Seitz
f811d1616b add support for ip range query on multivalue fastfields 2022-11-14 14:21:52 +08:00
PSeitz
c665b16ff0 Merge pull request #1672 from quickwit-oss/allow_range_without_indexed 
Allow range query on fastfield without INDEXED
 2022-11-14 12:45:12 +08:00
PSeitz
3b5f810051 Merge pull request #1677 from quickwit-oss/switch_to_u32 
switch total_num_val to u32
 2022-11-14 12:01:40 +08:00
trinity-1686a
5765c261aa allow warming up of the full posting list (#1673) 
* allow warming up of the full posting list

* cargo fmt
 2022-11-14 10:27:56 +09:00
Pascal Seitz
fb9f03118d switch total_num_val to u32 2022-11-11 17:35:52 +08:00
PSeitz
55a9d808d4 Merge pull request #1674 from quickwit-oss/u128_codec_header 
add header with codec type for u128
 2022-11-11 13:47:51 +08:00
Pascal Seitz
32166682b3 add header deser test 2022-11-11 13:28:12 +08:00
Pascal Seitz
e6acf8f76d add header with codec type for u128 2022-11-11 11:52:17 +08:00
Pascal Seitz
9e8a0c2cca Allow range query on fastfield without INDEXED 2022-11-10 15:56:08 +08:00
Paul Masurel
3edf0a2724 Using the manual reload policy in IndexWriter. (#1667) 2022-11-09 11:20:41 +01:00
Paul Masurel
8ca12a5683 Added stop word filter to CHANGELOG.md 2022-11-09 17:00:45 +09:00
Adam Reichold
a4b759d2fe Include stop word lists from Lucene and the Snowball project (#1666) 2022-11-09 16:57:35 +09:00
PSeitz
3e9c806890 Merge pull request #1665 from quickwit-oss/fix_num_vals 
fix num_vals on u128 value index after merge
 2022-11-07 21:46:02 +08:00
Pascal Seitz
c69a873dd3 fix num_vals on value index after merge 2022-11-07 21:05:21 +08:00
PSeitz
666afcf641 Merge pull request #1663 from PSeitz/fix_clippy 
fix clippy
 2022-11-07 18:11:20 +08:00
Pascal Seitz
38ad46e580 fix clippy 2022-11-07 16:09:55 +08:00
PSeitz
e948889f4c Merge pull request #1662 from quickwit-oss/fix_num_vals 
fix num_vals in multivalue index after merge
 2022-11-07 15:57:32 +08:00
Pascal Seitz
6e636c9cea fix num_vals in multivalue index after merge 2022-11-07 15:00:52 +08:00
PSeitz
5a610efbc1 Merge pull request #1661 from quickwit-oss/upgrade_criterion 
update criterion to 0.4
 2022-11-04 14:45:34 +08:00
Pascal Seitz
500a0d5e48 update criterion to 0.4 2022-11-04 13:26:29 +08:00
PSeitz
509a265659 add docstore version (#1652) 
* add docstore version

closes #1589

* assert for docstore version
 2022-11-04 10:19:16 +09:00
PSeitz
5b2cea1b97 Merge pull request #1656 from quickwit-oss/multival_offset_index 
move multivalue index to own file
 2022-11-02 14:03:06 +08:00
PSeitz
a5a80ffaea Update fastfield_codecs/src/column.rs 
Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-11-02 06:37:27 +01:00
PSeitz
0f98d91a39 Merge pull request #1646 from quickwit-oss/no_score_calls 
No score calls if score is not requested
 2022-11-01 20:09:32 +08:00
PSeitz
2af6b01c17 Update src/query/boolean_query/boolean_weight.rs 
Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-11-01 16:13:00 +08:00
Adam Reichold
c32ab66bbd Small improvements to StopWorldFilter (#1657) 
* Do not copy the whole set of stop words for each stream

* Make construction of StopWordFilter more flexible.
 2022-11-01 16:47:34 +09:00
PSeitz
3f3a6f9990 Merge pull request #1653 from quickwit-oss/faster_hash 
switch to fx hashmap
 2022-11-01 14:53:18 +08:00
Pascal Seitz
83325d8f3f move multivalue index to own file 
start_doc parameter in positions to docids
 2022-11-01 10:36:13 +08:00
PSeitz
4e46f4f8c4 Merge pull request #1649 from adamreichold/split-compound-words 
RFC: Add dictionary-based SplitCompoundWords token filter.
 2022-10-27 17:12:48 +08:00
Pascal Seitz
43df356010 rename to docset 2022-10-27 16:53:38 +08:00
PSeitz
6647362464 Merge pull request #1648 from adamreichold/stemmer-todo-alloc 
Avoid unconditional allocation in StemmerTokenStream.
 2022-10-27 16:50:41 +08:00
Pascal Seitz
279b1b28d3 switch to fx hashmap 2022-10-27 16:19:59 +08:00
PSeitz
7a80851e36 Merge pull request #1645 from quickwit-oss/ip_field_range_query 
add ip range query benchmark, add seek behaviour
 2022-10-27 16:13:52 +08:00
Adam Reichold
cd952429d2 Add dictionary-based SplitCompoundWords token filter. 2022-10-27 08:30:33 +02:00
PSeitz
d777c964da Merge pull request #1650 from adamreichold/fnv-rustc-hash 
Replace FNV by rustc-hash
 2022-10-27 12:11:26 +08:00
Adam Reichold
bbb058d976 Replace FNV by rustc-hash 
Both construction have similar goals but rustc-hash ist better suited for
contemporary CPU as it works one word at a time instead of byte per byte.
 2022-10-27 00:35:09 +02:00
Adam Reichold
5f7d027a52 Avoid unconditional allocation in StemmerTokenStream. 
This fixes the TODO in two ways: If the stemmer already yields an owned string,
it is used directly as the new text of the token. Otherwise, a temporary buffer
is used to copy the stemmed text (just as before) and then swapping it into the
token to reuse its existing buffer.
 2022-10-26 18:11:15 +02:00
Pascal Seitz
dfab201191 for_each_docset to iterate without score 2022-10-26 17:25:05 +08:00
PSeitz
0c2bd36fe3 Panic on duplicate field names (#1647) 
fixes #1601
 2022-10-26 16:17:33 +09:00
Pascal Seitz
af839753e0 No score calls if score is not requested 2022-10-26 12:18:35 +08:00
Pascal Seitz
fec2b63571 improve bench by adding more blanks in compact space 2022-10-25 22:09:01 +08:00
Pascal Seitz
6213ea476a pass positions parameter 2022-10-25 17:44:51 +08:00
Pascal Seitz
5e159c26bf add ip range query benchmark, add seek behaviour 2022-10-25 15:57:19 +08:00
PSeitz
a5e59ab598 Merge pull request #1644 from quickwit-oss/get_val_u32 
switch get_val() to u32
 2022-10-24 19:30:03 +08:00
Pascal Seitz
e772d3170d switch get_val() to u32 
Fixes #1638
 2022-10-24 19:05:57 +08:00
PSeitz
8c2ba7bd55 Merge pull request #1637 from quickwit-oss/ip_field_range_query 
add range query via ip fast field
 2022-10-24 18:10:47 +08:00
Pascal Seitz
02328b0151 fix proptest 2022-10-24 17:46:06 +08:00
Pascal Seitz
7cc775256c add comments, rename 2022-10-24 17:08:37 +08:00
Pascal Seitz
07b40f8b8b add proptest 2022-10-24 16:52:55 +08:00
PSeitz
9b6b6be5b9 Apply suggestions from code review 
Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-10-24 16:00:38 +08:00
Pascal Seitz
6bb73a527f add range query via ip fast field 2022-10-24 16:00:38 +08:00
PSeitz
03885d0f3c Merge pull request #1643 from quickwit-oss/range_query_parser 
allow more characters in range query
 2022-10-24 15:09:47 +08:00
Pascal Seitz
f2e5135870 allow more characters in range query 
closes #1642
 2022-10-21 18:05:15 +08:00
Paul Masurel
c24157f28b Bumping version format. (#1640) 
The docstore format has changed in a non-compatible manner.
 2022-10-21 15:35:35 +09:00
PSeitz
873382cdcb Merge pull request #1639 from quickwit-oss/num_vals_u32 
switch num_vals() to u32
 2022-10-21 12:36:50 +08:00
Pascal Seitz
791350091c switch num_vals() to u32 
fixes #1630
 2022-10-20 19:44:28 +08:00
Paul Masurel
483b1d13d4 Added unit test for long tokens (#1635) 
* Bugfix on long tokens and multivalue text fields.

Fixes a minor bug for the strong edge case
in which a tokenizer would emit tokens where
the last token does not cover the last position.

More importantly, this adds unit tests.

Closes #1634

* Update src/indexer/segment_writer.rs

Co-authored-by: PSeitz <PSeitz@users.noreply.github.com>

Co-authored-by: PSeitz <PSeitz@users.noreply.github.com>
 2022-10-20 15:05:37 +09:00
PSeitz
8de7fa9d95 Merge pull request #1631 from quickwit-oss/high_positions 
add test for phrase search on multi text field
 2022-10-20 10:26:00 +08:00
Paul Masurel
94313b62f8 Hotfix issue/1629 - position broken (#1633) 
* Bugfix position broken.

For Field with several FieldValues, with a
value that contained no token at all, the token position
was reinitialized to 0.

As a result, PhraseQueries can show some false positives.
In addition, after the computation of the position delta, we can
underflow u32, and end up with gigantic delta.

We haven't been able to actually explain the bug in 1629, but it
is assumed that in some corner case these delta can cause a panic.

Closes #1629
 2022-10-20 11:03:55 +09:00
Pascal Seitz
f2b2628feb add test for phrase search on multi text field 2022-10-19 16:29:56 +08:00
PSeitz
449f595832 Merge pull request #1628 from quickwit-oss/skip_index_deser 
faster skipindex deserialization, larger blocksize on sort
 2022-10-19 11:05:20 +08:00
PSeitz
c9235df059 Merge pull request #1627 from quickwit-oss/ip_field_range_query 
add range query handling for ip via term dictionary
 2022-10-19 10:53:00 +08:00
Pascal Seitz
a4485f7611 faster skipindex deserialization, larger blocksize on sort 2022-10-18 19:32:23 +08:00
Pascal Seitz
1082ff60f9 add range query handling for ip via term dictionary 
since IPs are mapped monotonically we can use the term dictionary for range queries
 2022-10-18 13:08:27 +08:00
PSeitz
491854155c Merge pull request #1625 from quickwit-oss/index_ip_field 
index ip field
 2022-10-18 11:18:17 +08:00
Christoph Herzog
96c3d54ac7 fix: Fix power of two computation on 32bit architectures (#1624) 
The current `compute_previous_power_of_two()` implementation used for
TermHashmap takes and returns `usize` , but actually only works
correclty on 64 bit architectures (aka usize == u64)

On other architectures the leading_zeros computation is run on the wrong
type (must be u64), and leads to overflows.

Fixed simply computing the leading_zeros based on a u64 value.
 2022-10-18 11:55:02 +09:00
Pascal Seitz
6800fdec9d add indexing for ip field 
Closes #1595
 2022-10-18 10:07:48 +08:00
PSeitz
c9cf9c952a Merge pull request #1614 from quickwit-oss/remove_superfluous_steps 
refactor Term
 2022-10-17 18:25:31 +08:00
Pascal Seitz
024e53a99c remove truncate 2022-10-17 12:14:35 +08:00
Pascal Seitz
8d75e451bd fix truncate, remove mutable access from term 2022-10-17 12:14:35 +08:00
Pascal Seitz
fcfd76ec55 refactor Term 
fixes some issues with Term
Remove duplicate calls to truncate or resize
Replace Magic Number 5 with constant
Enforce minimum size of 5 for metadata
Fix broken truncate docs
use constructor instead new + set calls
normalize constructor stack
replace assert on internal behavior fixes #1585
 2022-10-17 12:14:34 +08:00
PSeitz
6b7b1cc4fa Merge pull request #1623 from quickwit-oss/remove_unused_buffer 
remove unused buffer
 2022-10-14 20:36:00 +08:00
Pascal Seitz
129f7422f5 remove unused buffer 2022-10-14 20:01:10 +08:00
PSeitz
f39cce2c8b Merge pull request #1622 from quickwit-oss/term_aggregation 
add term aggregation clarification
 2022-10-14 18:09:18 +08:00
PSeitz
d2478fac8a Merge pull request #1621 from quickwit-oss/changelog 
update CHANGELOG
 2022-10-14 18:08:57 +08:00
Pascal Seitz
952b048341 add term aggregation clarification 2022-10-14 16:12:19 +08:00
PSeitz
80f9596ec8 Merge pull request #1611 from quickwit-oss/remove_token_stream_alloc 
remove tokenstream vec alloc
 2022-10-14 15:12:30 +08:00
Pascal Seitz
84f9e77e1d update CHANGELOG 2022-10-14 15:10:33 +08:00
PSeitz
a602c248fb Merge pull request #1590 from waywardmonkeys/fix-doc-warnings-quickwit 
Fix missing doc warnings when enabling feature "quickwit".
 2022-10-14 14:09:25 +08:00
PSeitz
4b9d1fe828 Merge pull request #1620 from quickwit-oss/fix_fieldnorms_indexing 
Fix missing fieldnorm indexing
 2022-10-14 13:41:38 +08:00
Pascal Seitz
63bc390b02 Fix missing fieldnorm indexing 
Fixes broken search (no results) with BM25 for u64, i64, f64, bool, bytes and date after deletion and merge.
There were no fieldnorms recorded for those field. After merge InvertedIndexReader::total_num_tokens returns 0 (Sum over the fieldnorms is 0). BM25 does not work when total_num_tokens is 0.
Fixes #1617
 2022-10-14 12:44:40 +08:00
Paul Masurel
07393c2fa0 Attempt to fix race condition in test. (#1619) 
Close #1550
 2022-10-14 10:56:37 +09:00
PSeitz
77a415cbe4 rename NothingRecorder to DocIdRecorder (#1615) 2022-10-13 15:43:40 +09:00
PSeitz
4b4c231bba Merge pull request #1612 from quickwit-oss/no_panic_please 
return Error instead panic in fastfields
 2022-10-11 18:33:00 +08:00
PSeitz
11d3409286 add missing docs for fastfield_codecs crate (#1613) 
closes #1603
 2022-10-11 18:54:24 +09:00
Pascal Seitz
9cb8cfbea8 return Error instead panic in fastfields 
fixes #1572
 2022-10-11 14:15:22 +08:00
PSeitz
8b69aab0fc avoid prepare_doc allocation (#1610) 
avoid prepare_doc allocation, ~10% more thoughput best case
 2022-10-11 14:15:55 +09:00
PSeitz
3650d1f36a Merge pull request #1553 from quickwit-oss/ip_field 
ip field
 2022-10-11 13:09:47 +08:00
Pascal Seitz
2efebdb1bb remove tokenstream vec alloc 2022-10-11 10:30:56 +08:00
François Massot
e443ca63aa Merge pull request #1608 from quickwit-oss/nigel/serialise-bytes-as-b64-#2042 
Serialise bytes as base64 strings instead of arrays.
 2022-10-10 11:51:23 +02:00
Pascal Seitz
5c9cbee29d handle IpV4 serialization case 2022-10-07 19:52:00 +08:00
Pascal Seitz
b2ca83a93c switch to ipv6, add monotonic_mapping tests 2022-10-07 18:47:55 +08:00
Nigel Andrews
3b189080d4 Use raw string literals in tests 2022-10-07 12:28:25 +02:00
Nigel Andrews
00a6586efe Replaced String::serialize for serializer.serialize_str 2022-10-07 11:55:05 +02:00
Pascal Seitz
b9b913510e fmt 2022-10-07 16:56:19 +08:00
PSeitz
534b1d33c3 use ipv6 
Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-10-07 16:56:00 +08:00
PSeitz
f465173872 Apply suggestions from code review 
Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-10-07 16:55:53 +08:00
Pascal Seitz
96315df20d use idx part only for positions_to_docid 2022-10-07 16:54:04 +08:00
Pascal Seitz
9a1609d364 add test 2022-10-07 16:25:01 +08:00
Pascal Seitz
39f4e58450 improve comment 2022-10-07 16:25:01 +08:00
Pascal Seitz
a8a36b62cd enable test 2022-10-07 16:25:01 +08:00
Pascal Seitz
226a49338f add StrictlyMonotonicFn 2022-10-07 16:25:01 +08:00
Pascal Seitz
2864bf7123 use serializer for u128 2022-10-07 16:25:01 +08:00
Pascal Seitz
5171ff611b serialize ip as u128, add test for positions_to_docid 2022-10-07 16:25:01 +08:00
Pascal Seitz
e50e74acf8 remove u128 type 2022-10-07 16:25:01 +08:00
Pascal Seitz
0b86658389 rename ip addr, use buffer 2022-10-07 16:25:01 +08:00
Pascal Seitz
5d6602a8d9 mark null handling TODO 2022-10-07 16:25:01 +08:00
Pascal Seitz
4d29ff4d01 finalize ip addr rename 2022-10-07 16:25:01 +08:00
Pascal Seitz
cdc8e3a8be group montonic mapping and inverse 
fix mapping inverse
remove ip indexing
add get_between_vals test
 2022-10-07 16:25:01 +08:00
Pascal Seitz
67f453b534 rename to iter_gen 2022-10-07 16:25:01 +08:00
Pascal Seitz
787a37bacf expect instead of unwrap 2022-10-07 16:25:01 +08:00
Pascal Seitz
f5039f1846 remove roaring 2022-10-07 16:25:01 +08:00
Pascal Seitz
eeb1f19093 rename to iter_gen 2022-10-07 16:25:01 +08:00
Pascal Seitz
087beaf328 remove null handling 2022-10-07 16:25:01 +08:00
Pascal Seitz
309449dba3 rename to IpAddr 2022-10-07 16:25:01 +08:00
Pascal Seitz
5a76e6c5d3 fix get_between_vals forwarding 
fix get_between_vals forwarding in monotonicmapping column by adding an additional conversion function Output->Input
 2022-10-07 16:25:01 +08:00
Pascal Seitz
c8713a01ed use iter api 2022-10-07 16:25:01 +08:00
Pascal Seitz
6113e0408c remove comment 2022-10-07 16:25:01 +08:00
Pascal Seitz
400a20b7af add ip field 
add u128 multivalue reader and writer
add ip to schema
add ip writers, handle merge
 2022-10-07 16:25:01 +08:00
PSeitz
5f565e77de Merge pull request #1604 from quickwit-oss/replace_cbor 
replace cbor with cborium
 2022-10-07 14:42:55 +08:00
Pascal Seitz
516e60900d remove unwrap 2022-10-07 14:22:37 +08:00
Pascal Seitz
36e1c79f37 replace cbor with cborium 
closes #1526
 2022-10-07 13:23:39 +08:00
Bruce Mitchener
c2f1c250f9 doc: Remove reference to Searcher pool. (#1598) 
The pool of searchers was removed in 23fe73a6 as part of #1411.
 2022-10-06 00:04:11 +09:00
Bruce Mitchener
c694bc039a Fix missing doc warnings when enabling feature "quickwit". 2022-10-05 20:17:10 +07:00
PSeitz
2063f1717f Merge pull request #1591 from quickwit-oss/ff_refact 
disable linear codec for multivalue values
 2022-10-05 19:39:36 +08:00
Pascal Seitz
d742275048 renames 2022-10-05 19:16:49 +08:00
PSeitz
b9f06bc287 Update src/fastfield/multivalued/mod.rs 
Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-10-05 19:09:19 +08:00
Pascal Seitz
8b42c4c126 disable linear codec for multivalue value index 
don't materialize index column on merge
use simpler chain() variant
 2022-10-05 19:09:17 +08:00
PSeitz
7905965800 Merge pull request #1594 from quickwit-oss/flat_map_with_buffer 
Removing alloc on all .next() in MultiValueColumn
 2022-10-05 18:34:15 +08:00
Pascal Seitz
f60a551890 add flat_map_with_buffer to Iterator trait 2022-10-05 17:44:26 +08:00
Paul Masurel
7baa6e3ec5 Removing alloc on all .next() in MultiValueColumn 2022-10-05 17:12:06 +09:00
PSeitz
2100ec5d26 Merge pull request #1593 from waywardmonkeys/doc-improvements 
Documentation improvements.
 2022-10-05 15:50:08 +08:00
Bruce Mitchener
b3bf9a5716 Documentation improvements. 2022-10-05 14:18:10 +07:00
Paul Masurel
0dc8c458e0 Flaky unit test. (#1592) 2022-10-05 16:15:48 +09:00
Nigel Andrews
e5043d78d2 added a couple of tests + make fmt 2022-10-04 12:52:44 +02:00
Nigel Andrews
6d0bb82bd2 Fix issue 1576: serialize bytes as base64 strings 2022-10-04 12:18:13 +02:00
trinity-1686a
5945dbf0bd change format for store to make it faster with small documents (#1569) 
* use new format for docstore blocks

* move index to end of block

it makes writing the block faster due to one less memcopy
 2022-10-04 09:58:55 +02:00
PSeitz
4cf911d56a Merge pull request #1587 from quickwit-oss/no_get_val_in_serialize 
remove get_val in serialization
 2022-10-04 12:56:48 +08:00
Pascal Seitz
0f5cff762f move enumerate and remove computation 2022-10-04 12:30:19 +08:00
Pascal Seitz
6d9a123cf2 remove get_val in serialization 
remove get_val in serialization and mark as unimplemented!()
replace get_val with iter in linear codec
remove MultivalueStartIndexRandomSeeker
replace MultivalueStartIndexIter with closure
Sample 100 values in linear codec
 2022-10-04 12:01:25 +08:00
PSeitz
0f4a47816a Merge pull request #1582 from quickwit-oss/faster_sorted_field_values 
use groupby instead of vec allocation
 2022-10-04 09:36:24 +08:00
Pascal Seitz
b062ab2196 use groupby instead of vec allocation 2022-10-04 09:26:26 +08:00
Bruce Mitchener
a9d2f3db23 Tantivy requires Rust 1.62 or later. (#1583) 
Tantivy needs the `total_cmp` feature to compile, which was stabilized
in Rust 1.62.
 2022-10-03 18:31:07 +09:00
Bruce Mitchener
44e03791f9 Fix warnings when doc'ing private items. (#1579) 
This also fixes a couple of typos, but plenty remain!
 2022-10-03 14:24:00 +09:00
Bruce Mitchener
2d23763e9f Use u64::from boolean more. (#1580) 
This case is inverted from the previous cases fixed.

This is from nightly clippy.
 2022-10-03 14:17:50 +09:00
Bruce Mitchener
a24ae8d924 clippy: Fix needless-borrow warnings. (#1581) 
These show on nightly clippy.
 2022-10-03 14:15:09 +09:00
PSeitz
927dff5262 Merge pull request #1578 from quickwit-oss/dead_code 
remove dead indexing code
 2022-10-03 11:25:10 +08:00
Pascal Seitz
a695edcc95 remove dead indexing code 2022-10-03 09:44:02 +08:00
Paul Masurel
b4b4f3fa73 Removing default features for zstd (#1574) 2022-09-30 13:02:46 +09:00
PSeitz
b50e4b7c20 Merge pull request #1566 from quickwit-oss/fix_docstore_sorting 
fix docstore settings for temp docstore
 2022-09-30 10:10:36 +08:00
PSeitz
f8686ab1ec improve comments 
Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-09-30 10:06:34 +08:00
PSeitz
2fe42719d8 Merge pull request #1570 from quickwit-oss/no_sort_on_multi 
validate index settings on create
 2022-09-30 09:17:03 +08:00
PSeitz
fadd784a25 log improvements (#1564) 2022-09-30 09:39:26 +09:00
Pascal Seitz
0e94213af0 validate index settings on create 2022-09-29 18:58:09 +08:00
PSeitz
0da2a2e70d Merge pull request #1567 from quickwit-oss/dependabot/cargo/tantivy-fst-0.4.0 
Update tantivy-fst requirement from 0.3.0 to 0.4.0
 2022-09-29 10:00:16 +08:00
dependabot[bot]
0bcdf3cbbf Update tantivy-fst requirement from 0.3.0 to 0.4.0 
Updates the requirements on [tantivy-fst](https://github.com/tantivy-search/fst) to permit the latest version.
- [Release notes](https://github.com/tantivy-search/fst/releases)
- [Commits](https://github.com/tantivy-search/fst/commits)

---
updated-dependencies:
- dependency-name: tantivy-fst
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
 2022-09-28 20:50:43 +00:00
Pascal Seitz
8f647b817f fix docstore settings for temp docstore 
fixes #1565
 2022-09-28 17:53:59 +08:00
trinity-1686a
a86b0df6f4 Add query matching terms in a set (#1539) 2022-09-28 09:43:18 +02:00
Bruce Mitchener
f842da758c Move ArcBytes,WeakArcBytes to mmap_directory. (#1555) 
When building without default features (so without mmap, etc),
there are some warnings about unused things. This fixes the
ones related to `ArcBytes` and `WeakArcBytes`, which are only
used with the `mmap_directory` code.
 2022-09-27 09:57:28 +09:00
Bruce Mitchener
97ccd6d712 Avoid slicing a string in DocParsingError. (#1559) 
Fixes #1339.
 2022-09-26 20:27:15 +09:00
Bruce Mitchener
cb252a42af docs: "associated to" -> "associated with" (#1557) 
This reads better this way.
 2022-09-26 20:23:37 +09:00
Bruce Mitchener
d9609dd6b6 POLLING_INTERVAL needn't be pub. (#1556) 
This is only used within the file watcher and is const, so it
can't be configured.
 2022-09-26 20:22:55 +09:00
Bruce Mitchener
f03667d967 Remove references to /cpp directory. (#1560) 
This was removed in 2018, so these should be fine to remove now.
 2022-09-26 20:22:28 +09:00
PSeitz
10f10a322f Merge pull request #1554 from quickwit-oss/prepare_ip_field 
prepare for ip field
 2022-09-26 16:34:24 +08:00
Pascal Seitz
f757471077 prepare for ip field 2022-09-26 16:27:35 +08:00
PSeitz
21e0adefda use binary search instead of linear for get_val in merge (#1548) 
* use binary search instead of linear for get_val in merge

* use partition_point
 2022-09-26 09:42:33 +09:00
Bruce Mitchener
ea8e6d7b1d Tidy up clippy config. (#1547) 
* Checking cfg_attr is no longer necessary.
* Don't need multiple `clippy::` prefixes on a name.
 2022-09-26 09:37:55 +09:00
PSeitz
dac7da780e Merge pull request #1545 from waywardmonkeys/remove-some-refs 
clippy: Remove borrows that the compiler will do.
 2022-09-23 15:33:23 +08:00
PSeitz
20c87903b2 fix multivalue ff index creation regression (#1543) 
fixes multivalue ff regression by avoiding using `get_val`. Line::train calls repeatedly get_val, but get_val implementation on Column for multivalues is very slow. The fix is to use the iterator instead. Longterm fix should be to remove get_val access in serialization.

Old Code

test fastfield::bench::bench_multi_value_ff_merge_few_segments                                                           ... bench:  46,103,960 ns/iter (+/- 2,066,083)
test fastfield::bench::bench_multi_value_ff_merge_many_segments                                                          ... bench:  83,073,036 ns/iter (+/- 4,373,615)
est fastfield::bench::bench_multi_value_ff_merge_many_segments_log_merge                                                ... bench:  64,178,576 ns/iter (+/- 1,466,700)

Current

running 3 tests
test fastfield::multivalued::bench::bench_multi_value_ff_merge_few_segments                                              ... bench:  57,379,523 ns/iter (+/- 3,220,787)
test fastfield::multivalued::bench::bench_multi_value_ff_merge_many_segments                                             ... bench:  90,831,688 ns/iter (+/- 1,445,486)
test fastfield::multivalued::bench::bench_multi_value_ff_merge_many_segments_log_merge                                   ... bench: 158,313,264 ns/iter (+/- 28,823,250)

With Fix

running 3 tests
test fastfield::multivalued::bench::bench_multi_value_ff_merge_few_segments                                              ... bench:  57,635,671 ns/iter (+/- 2,707,361)
test fastfield::multivalued::bench::bench_multi_value_ff_merge_many_segments                                             ... bench:  91,468,712 ns/iter (+/- 11,393,581)
test fastfield::multivalued::bench::bench_multi_value_ff_merge_many_segments_log_merge                                   ... bench:  73,909,138 ns/iter (+/- 15,846,097)
 2022-09-23 15:36:29 +09:00
PSeitz
f9c3947803 Merge pull request #1546 from waywardmonkeys/use-ux-from-bool 
Use u8::from(bool), u64::from(bool).
 2022-09-23 09:06:24 +08:00
Bruce Mitchener
e9a384bb15 Use u8::from(bool), u64::from(bool). 2022-09-22 22:44:53 +07:00
Bruce Mitchener
d231671fe2 clippy: Remove borrows that the compiler will do. 
This started showing up with clippy in rust 1.64.
 2022-09-22 22:38:23 +07:00
trinity-1686a
fa3d786a2f Add support for deleting all documents matching query (#1535) 
* add support for deleting all documents matching query

#1494
 2022-09-22 21:26:09 +09:00
Paul Masurel
75aafeeb9b Added a function to deep clone RamDirectory. (#1544) 2022-09-22 12:04:02 +02:00
PSeitz
6f066c7f65 Merge pull request #1541 from quickwit-oss/add_bench 
add benchmarks for multivalued fastfield merge
 2022-09-22 15:28:00 +08:00
Pascal Seitz
22e56aaee3 add benchmarks for multivalued fastfield merge 2022-09-22 11:25:41 +08:00
Paul Masurel
d641979127 Minor refactor of fast fields (#1538) 2022-09-21 12:55:03 +09:00
Paul Masurel
1998111521 Minor refactoring fast fields (#1537) 2022-09-21 12:46:11 +09:00
PSeitz
acb2e2e282 Merge pull request #1532 from quickwit-oss/refactor_ff 
remove fast_field_cardinality from FastValue
 2022-09-21 04:00:35 +02:00
Pascal Seitz
1ff5da5eb4 remove fast_field_cardinality from FastValue 
unused and at the wrong placed
 2022-09-21 09:38:46 +08:00
Bruce Mitchener
c3b25710ad doc: Improve directory::Lock docs. (#1534) 
Update the docs to reflect the lack of LockParams, correct an error,
and improve cross-linking.
 2022-09-20 18:03:35 +09:00
PSeitz
8492010d43 Merge pull request #1531 from waywardmonkeys/improve-docs-more 
Improvements to doc linking, grammar, etc.
 2022-09-20 15:37:07 +08:00
Bruce Mitchener
cf02e32578 Improvements to doc linking, grammar, etc. 2022-09-19 18:10:22 +07:00
PSeitz
8cca1014c9 Merge pull request #1527 from waywardmonkeys/remove-stream_field-reference 
docs: Remove mentions of stream_field method.
 2022-09-19 17:16:46 +08:00
PSeitz
938f884e32 Merge pull request #1525 from waywardmonkeys/fix-etsy-logo-alt-text-readme 
README: Fix Etsy logo and alt text.
 2022-09-19 16:55:08 +08:00
PSeitz
ed68afb698 Merge pull request #1528 from quickwit-oss/ff_refact 
fix benches
 2022-09-19 11:37:08 +08:00
PSeitz
8a7962dc22 Merge pull request #1524 from waywardmonkeys/improve-docs-1 
Documentation improvements.
 2022-09-19 11:15:42 +08:00
Pascal Seitz
a06039dea8 fix benches 
move some benches to lib.rs to test unexported items
 2022-09-19 11:07:20 +08:00
Bruce Mitchener
68b6254b09 docs: Remove mentions of stream_field method. 
This method doesn't exist, so no need to mention it.
 2022-09-18 23:13:41 +07:00
Bruce Mitchener
6a88ac3fe3 Documentation improvements. 
Fix some linking, some grammar, some typos, etc.
 2022-09-18 18:05:37 +07:00
Bruce Mitchener
191b934650 README: Fix Etsy logo and alt text. 2022-09-18 15:02:35 +07:00
PSeitz
1a2ba7025a Merge pull request #1513 from quickwit-oss/ip_codec 
add ip codec
 2022-09-16 18:53:08 +08:00
Pascal Seitz
02599ebeb7 remove ip_to_u128 2022-09-16 18:16:16 +08:00
Pascal Seitz
a16b466460 merge ColumnExt with Column trait 2022-09-16 18:15:18 +08:00
Pascal Seitz
b8d8fdeb6e move benches, improve bench data 2022-09-16 16:42:23 +08:00
Pascal Seitz
12856d80fa change bench, update numbers 2022-09-16 16:41:01 +08:00
Pascal Seitz
e75472ec9a add serialize_u128, open_u128, refactor 2022-09-16 16:40:59 +08:00
Pascal Seitz
e2e6c94ba8 remove ColumnV2 2022-09-16 16:40:06 +08:00
Pascal Seitz
9f610b25af fix benches, add benches 2022-09-16 16:38:48 +08:00
Pascal Seitz
237b64025e take ColumnV2 as parameter 
improve algorithm
stricter assertions
improve names
 2022-09-16 16:38:48 +08:00
Pascal Seitz
592caeefa0 renames 2022-09-16 16:38:48 +08:00
Pascal Seitz
570009b5b1 move to mod.rs 2022-09-16 16:38:48 +08:00
Pascal Seitz
61b5110db7 use 0 as null in compact space 2022-09-16 16:38:48 +08:00
PSeitz
58af1235e4 Apply suggestions from code review 
Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-09-16 16:38:48 +08:00
Pascal Seitz
d3e7c41a1f refactor to range_mapping 2022-09-16 16:38:48 +08:00
Pascal Seitz
11275854ca unroll get range iteration 2022-09-16 16:38:48 +08:00
Pascal Seitz
3ca48cd826 fix test 2022-09-16 16:38:48 +08:00
Pascal Seitz
47dc511733 add inline 2022-09-16 16:38:48 +08:00
Pascal Seitz
cae6b28a8f remove num_vals param 2022-09-16 16:38:48 +08:00
Pascal Seitz
9aa9efe2a4 fix bench 2022-09-16 16:38:48 +08:00
Pascal Seitz
57570b38a2 use vint, forward errors, removed unused var 2022-09-16 16:38:48 +08:00
Pascal Seitz
584394db1e fix Cargo.toml 2022-09-16 16:38:48 +08:00
Pascal Seitz
3aeb026970 fix blank_size, add comments 2022-09-16 16:38:48 +08:00
Pascal Seitz
df32ee2df2 refactor, use BTreeSet for sorted deduped values 2022-09-16 16:38:48 +08:00
Pascal Seitz
762e662bfd extend proptest for get_range 2022-09-16 16:38:48 +08:00
Pascal Seitz
63b2420058 fix get_range 
change blank handling
optimize blank collection
fix off by one errors
extend tests
fix get_range
dedupe values to save space
add bench
 2022-09-16 16:38:47 +08:00
Pascal Seitz
ced21b8791 move tests 2022-09-16 16:38:02 +08:00
Pascal Seitz
bc85947105 add ip codec 2022-09-16 16:38:01 +08:00
Paul Masurel
64f08a1a5c Hiding useless symbols and removing code. (#1522) 2022-09-16 14:42:27 +09:00
Paul Masurel
e029fdfca7 Perf fix on the MonotonicMapping column (#1519) 
The Monotonic mapping was using the default implementation
for `get_range` and `.iter`.

As a result, some of the column used in merge (e.g. multivalued
fast fields) were exhibiting a very strong performance regression.
 2022-09-15 14:20:43 +09:00
Paul Masurel
817225edfb Allow for a same-thread doc compressor. (#1510) 
In addition, it isolates the doc compressor logic,
better reports io::Result.

In the case of the same-thread doc compressor,
the blocks are also not copied.
 2022-09-13 15:32:48 +09:00
Shikhar Bhushan
1eab12396d Make Column: Send + Sync (#1518) 2022-09-13 13:31:28 +09:00
dependabot[bot]
8006f63426 Update criterion requirement from 0.3.5 to 0.4.0 (#1517) 
Updates the requirements on [criterion](https://github.com/bheisler/criterion.rs) to permit the latest version.
- [Release notes](https://github.com/bheisler/criterion.rs/releases)
- [Changelog](https://github.com/bheisler/criterion.rs/blob/master/CHANGELOG.md)
- [Commits](https://github.com/bheisler/criterion.rs/compare/0.3.5...0.4.0)

---
updated-dependencies:
- dependency-name: criterion
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
 2022-09-13 10:02:12 +09:00
Adam Reichold
0a907d0319 Move pretty_assertions from dependencies to dev-dependencies to reduce dependency closure of downstream projects. (#1515) 2022-09-10 18:01:26 +09:00
PSeitz
45924711fd improve docs (#1514) 
fix link alias after https://github.com/rust-lang/rustfmt/pull/5262 has been merged and released.
fix dead links
 2022-09-08 22:33:59 +09:00
PSeitz
14cb817a52 Merge pull request #1509 from quickwit-oss/refact-fast-field 
refactor, fix api
 2022-09-07 22:04:32 -07:00
Pascal Seitz
edd9155b88 return Write, add documentation 2022-09-08 12:41:55 +08:00
PSeitz
9497794d40 fix positions docs (#1511) 2022-09-08 10:24:00 +09:00
Pascal Seitz
29d56111de refactor, fix api 
refactor
fix clippy
fix docs
remove unused code
fix bytesfield index api flaw
 2022-09-07 18:43:04 +08:00
Paul Masurel
4d634d61ff Expose memory usage in SingleSegmentIndexWriter (#1508) 2022-09-07 18:33:52 +09:00
PSeitz
1f3d8ca7e2 Merge pull request #1507 from quickwit-oss/improve_test 
add check to proptest
 2022-09-07 02:30:29 -07:00
PSeitz
54696da771 Merge pull request #1505 from quickwit-oss/refact-fast-field 
Refact fast field
 2022-09-07 02:07:42 -07:00
Pascal Seitz
21c2205de9 add check to proptest 2022-09-07 16:58:07 +08:00
PSeitz
9436049d85 Merge pull request #1506 from quickwit-oss/multifastfieldbench 
add benchmark for multivalue fast field
 2022-09-07 01:36:16 -07:00
Pascal Seitz
21c9a26182 add ff creation benchmark 2022-09-07 15:43:50 +08:00
Pascal Seitz
56c68f5869 add ff creation benchmark 2022-09-07 14:03:24 +08:00
Pascal Seitz
f5e66042d8 no alloc in loop 2022-09-07 12:42:16 +08:00
Pascal Seitz
bf3327acd3 add benchmark for multivalue fast field 2022-09-06 16:55:30 +08:00
PSeitz
2a6479b66d Merge pull request #1427 from quickwit-oss/empty_segments_crash 
handle empty segments for merge
 2022-09-05 22:59:06 -07:00
Pascal Seitz
9c2ef81198 fix clippy 2022-09-06 13:34:36 +08:00
Paul Masurel
c5d30a54bc CR 2022-09-06 00:16:41 +09:00
Paul Masurel
c632fc014e Refactoring fast fields codecs. 
This removes the GCD part as a codec, and
makes it so that fastfield codecs all share
the same normalization part (shift + gcd).
 2022-09-05 23:07:12 +09:00
Pascal Seitz
085e63ae43 return new segment meta 2022-09-05 15:19:01 +08:00
Pascal Seitz
f6f23ba684 optionally create segment on merge 
create a new segment only if it contains data

fixes #1189
 2022-09-05 15:07:03 +08:00
Paul Masurel
ea72cf34d6 Int based linear interpol (#1482) 
* Rename BlockwiseLinear to BlockwiseLinearLegacy

Reimplements the blockwise multilinear codec using integer arithmetics.
Added comments

* add estimate for blockwise

* Added one unit test

* use int based for linear interpol

* fix merge conflicts

* reuse code

* cargo fmt

* fix clippy

* fix test

* fix off by one

fix off by one to accurately interpolate autoincrement fields

* extend test, fix estimate

* remove legacy codec

Co-authored-by: Pascal Seitz <pascal.seitz@gmail.com>
 2022-09-05 15:53:00 +09:00
PSeitz
00657d9e99 Merge pull request #1504 from quickwit-oss/move-to-fastfield-codec 
Move to fastfield codec
 2022-09-03 05:18:35 -07:00
Paul Masurel
26876d41d7 Moving the serialization logic to the fastfield_codecs crate. 2022-09-03 00:29:52 +09:00
Paul Masurel
8e775b6c3d Refactoring dyn Column (#1502) 2022-09-02 17:26:30 +09:00
Maxim Kraynyuchenko
e1f9af4384 Added Etsy logo to readme (#1503) 2022-09-02 15:27:59 +09:00
Paul Masurel
4e350c5f1b Clippy 2022-09-02 13:05:00 +09:00
Paul Masurel
84e0c75598 Bench fixing 2022-09-02 11:15:44 +09:00
Paul Masurel
08c4412d73 Adding dragon API to build index without any thread. (#1496) 
Closes #1487
 2022-09-01 10:32:36 +09:00
Shikhar Bhushan
70e58adff9 OwnedBytes doc clarification (#1498) 
It only exposes it with the same lifetime as `&self`, which is what keeps things safe
 2022-09-01 10:32:17 +09:00
PSeitz
0d1cd119e9 Merge pull request #1497 from quickwit-oss/improve_proptest 
custom num strategy, faster test
 2022-08-31 06:25:25 -07:00
Pascal Seitz
d3dd620048 fix clippy 2022-08-31 13:13:56 +02:00
Pascal Seitz
e89c220b56 custom num strategy, faster test 
closes #1486
faster test with rand values
 2022-08-31 12:08:44 +02:00
Paul Masurel
a451f6d60d Minor refactoring. (#1495) 2022-08-31 12:00:58 +09:00
PSeitz
f740ddeee3 Merge pull request #1493 from quickwit-oss/remove_vec_impl 
remove Column impl on Vec
 2022-08-29 07:54:33 -07:00
Pascal Seitz
7a26cc9022 add VecColumn 2022-08-29 15:49:43 +02:00
Pascal Seitz
54972caa7c remove Column impl on Vec 
remove Column impl on Vec to avoid function shadowing
 2022-08-29 11:57:41 +02:00
PSeitz
5d436759b0 Merge pull request #1480 from quickwit-oss/overflow_issue 
fix overflow issue in interpolation
 2022-08-28 16:44:00 -07:00
PSeitz
6f563b1606 Merge pull request #1491 from quickwit-oss/col-trait-refact 
Introducing a column trait
 2022-08-28 10:05:25 -07:00
Pascal Seitz
095fb68fda fix doc test 2022-08-28 18:30:39 +02:00
Pascal Seitz
6316eaefc6 fix benches 2022-08-28 14:38:30 +02:00
Paul Masurel
5331be800b Introducing a column trait 2022-08-28 14:14:27 +02:00
Paul Masurel
c73b425bc1 Fixing unit tests 2022-08-27 23:20:57 +02:00
Paul Masurel
54cfd0d154 Removing Deserializer trait (#1489) 
Removing Deserializer trait and renaming the `Serializer` trait `FastFieldCodec`.
Small refactoring estimate.
 2022-08-28 04:54:55 +09:00
PSeitz
0dd62169c8 merge FastFieldCodecReader wit FastFieldDataAccess (#1485) 
* num_vals to FastFieldCodecReader

* split open_from_bytes to own trait

* rename get_u64 to ge_val

* merge traits
 2022-08-28 03:58:28 +09:00
Pascal Seitz
3984cafccc fix overflow issue in interpolation 
use saturating_sub and saturating_add to cover edge cases with values close to u64::MAX or 0 in combination with imprecise computation
 2022-08-24 20:08:13 +02:00
211 changed files with 13395 additions and 4527 deletions
Expand all files Collapse all files

1
.gitattributes vendored
View File

@@ -1 +0,0 @@
cpp/* linguist-vendored

2
.github/workflows/test.yml vendored
View File

@@ -48,7 +48,7 @@ jobs:
strategy:
matrix:
features: [
{ label: "all", flags: "mmap,brotli-compression,lz4-compression,snappy-compression,zstd-compression,failpoints" },
{ label: "all", flags: "mmap,stopwords,brotli-compression,lz4-compression,snappy-compression,zstd-compression,failpoints" },
{ label: "quickwit", flags: "mmap,quickwit,failpoints" }
]

1
.gitignore vendored
View File

@@ -9,7 +9,6 @@ target/release
Cargo.lock
benchmark
.DS_Store
cpp/simdcomp/bitpackingbenchmark
*.bk
.idea
trace.dat

2
ARCHITECTURE.md
View File

@@ -95,7 +95,7 @@ called [`Directory`](src/directory/directory.rs).
Contrary to Lucene however, "files" are quite different from some kind of `io::Read` object.
Check out [`src/directory/directory.rs`](src/directory/directory.rs) trait for more details.
Tantivy ships two main directory implementation: the `MMapDirectory` and the `RAMDirectory`,
Tantivy ships two main directory implementation: the `MmapDirectory` and the `RamDirectory`,
but users can extend tantivy with their own implementation.
## [schema/](src/schema): What are documents?

32
CHANGELOG.md
View File

@@ -1,10 +1,34 @@
Tantivy 0.19
================================
- Skip score calculation, when no scoring is required [#1646](https://github.com/quickwit-oss/tantivy/pull/1646) (@PSeitz)
- Limit fast fields to u32 (`get_val(u32)`) [#1644](https://github.com/quickwit-oss/tantivy/pull/1644) (@PSeitz)
- Major bugfix: Fix missing fieldnorms for u64, i64, f64, bool, bytes and date [#1620](https://github.com/quickwit-oss/tantivy/pull/1620) (@PSeitz)
- Updated [Date Field Type](https://github.com/quickwit-oss/tantivy/pull/1396)
The `DateTime` type has been updated to hold timestamps with microseconds precision.
`DateOptions` and `DatePrecision` have been added to configure Date fields. The precision is used to hint on fast values compression. Otherwise, seconds precision is used everywhere else (i.e terms, indexing).
- Remove Searcher pool and make `Searcher` cloneable.
`DateOptions` and `DatePrecision` have been added to configure Date fields. The precision is used to hint on fast values compression. Otherwise, seconds precision is used everywhere else (i.e terms, indexing). (@evanxg852000)
- Add IP address field type [#1553](https://github.com/quickwit-oss/tantivy/pull/1553) (@PSeitz)
- Add boolean field type [#1382](https://github.com/quickwit-oss/tantivy/pull/1382) (@boraarslan)
- Remove Searcher pool and make `Searcher` cloneable. (@PSeitz)
- Validate settings on create [#1570](https://github.com/quickwit-oss/tantivy/pull/1570 (@PSeitz)
- Fix interpolation overflow in linear interpolation fastfield codec [#1480](https://github.com/quickwit-oss/tantivy/pull/1480 (@PSeitz @fulmicoton)
- Detect and apply gcd on fastfield codecs [#1418](https://github.com/quickwit-oss/tantivy/pull/1418) (@PSeitz)
- Doc store
- use separate thread to compress block store [#1389](https://github.com/quickwit-oss/tantivy/pull/1389) [#1510](https://github.com/quickwit-oss/tantivy/pull/1510 (@PSeitz @fulmicoton)
- Expose doc store cache size [#1403](https://github.com/quickwit-oss/tantivy/pull/1403) (@PSeitz)
- Enable compression levels for doc store [#1378](https://github.com/quickwit-oss/tantivy/pull/1378) (@PSeitz)
- Make block size configurable [#1374](https://github.com/quickwit-oss/tantivy/pull/1374) (@kryesh)
- Make `tantivy::TantivyError` cloneable [#1402](https://github.com/quickwit-oss/tantivy/pull/1402) (@PSeitz)
- Add support for phrase slop in query language [#1393](https://github.com/quickwit-oss/tantivy/pull/1393) (@saroh)
- Aggregation
- Add support for keyed parameter in range and histgram aggregations [#1424](https://github.com/quickwit-oss/tantivy/pull/1424) (@k-yomo)
- Add aggregation bucket limit [#1363](https://github.com/quickwit-oss/tantivy/pull/1363) (@PSeitz)
- Faster indexing
- [#1610](https://github.com/quickwit-oss/tantivy/pull/1610) (@PSeitz)
- [#1594](https://github.com/quickwit-oss/tantivy/pull/1594) (@PSeitz)
- [#1582](https://github.com/quickwit-oss/tantivy/pull/1582) (@PSeitz)
- [#1611](https://github.com/quickwit-oss/tantivy/pull/1611) (@PSeitz)
- Added a pre-configured stop word filter for various language [#1666](https://github.com/quickwit-oss/tantivy/pull/1666) (@adamreichold)
Tantivy 0.18
================================
@@ -22,6 +46,10 @@ Tantivy 0.18
- Add terms aggregation (@PSeitz)
- Add support for zstd compression (@kryesh)
Tantivy 0.18.1
================================
- Hotfix: positions computation. #1629 (@fmassot, @fulmicoton, @PSeitz)
Tantivy 0.17
================================

27
Cargo.toml
View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy"
version = "0.18.0"
version = "0.19.0-dev"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
categories = ["database-implementations", "data-structures"]
@@ -11,26 +11,28 @@ repository = "https://github.com/quickwit-oss/tantivy"
readme = "README.md"
keywords = ["search", "information", "retrieval"]
edition = "2021"
rust-version = "1.62"
[dependencies]
oneshot = "0.1.3"
oneshot = "0.1.5"
base64 = "0.13.0"
byteorder = "1.4.3"
crc32fast = "1.3.2"
once_cell = "1.10.0"
regex = { version = "1.5.5", default-features = false, features = ["std", "unicode"] }
tantivy-fst = "0.3.0"
aho-corasick = "0.7"
tantivy-fst = "0.4.0"
memmap2 = { version = "0.5.3", optional = true }
lz4_flex = { version = "0.9.2", default-features = false, features = ["checked-decode"], optional = true }
brotli = { version = "3.3.4", optional = true }
zstd = { version = "0.11", optional = true }
zstd = { version = "0.11", optional = true, default-features = false }
snap = { version = "1.0.5", optional = true }
tempfile = { version = "3.3.0", optional = true }
log = "0.4.16"
serde = { version = "1.0.136", features = ["derive"] }
serde_json = "1.0.79"
num_cpus = "1.13.1"
fs2={ version = "0.4.3", optional = true }
fs2 = { version = "0.4.3", optional = true }
levenshtein_automata = "0.2.1"
uuid = { version = "1.0.0", features = ["v4", "serde"] }
crossbeam-channel = "0.5.4"
@@ -44,7 +46,7 @@ rust-stemmers = "1.2.0"
downcast-rs = "1.2.0"
bitpacking = { version = "0.8.4", default-features = false, features = ["bitpacker4x"] }
census = "0.4.0"
fnv = "1.0.7"
rustc-hash = "1.1.0"
thiserror = "1.0.30"
htmlescape = "0.3.1"
fail = "0.5.0"
@@ -56,8 +58,7 @@ lru = "0.7.5"
fastdivide = "0.4.0"
itertools = "0.10.3"
measure_time = "0.8.2"
pretty_assertions = "1.2.1"
serde_cbor = { version = "0.11.2", optional = true }
ciborium = { version = "0.2", optional = true}
async-trait = "0.1.53"
arc-swap = "1.5.0"
@@ -68,11 +69,12 @@ winapi = "0.3.9"
rand = "0.8.5"
maplit = "1.0.2"
matches = "0.1.9"
pretty_assertions = "1.2.1"
proptest = "1.0.0"
criterion = "0.3.5"
criterion = "0.4"
test-log = "0.2.10"
env_logger = "0.9.0"
pprof = { version = "0.10.0", features = ["flamegraph", "criterion"] }
pprof = { version = "0.11.0", features = ["flamegraph", "criterion"] }
futures = "0.3.21"
[dev-dependencies.fail]
@@ -89,8 +91,9 @@ debug-assertions = true
overflow-checks = true
[features]
default = ["mmap", "lz4-compression" ]
default = ["mmap", "stopwords", "lz4-compression"]
mmap = ["fs2", "tempfile", "memmap2"]
stopwords = []
brotli-compression = ["brotli"]
lz4-compression = ["lz4_flex"]
@@ -100,7 +103,7 @@ zstd-compression = ["zstd"]
failpoints = ["fail/failpoints"]
unstable = [] # useful for benches.
quickwit = ["serde_cbor"]
quickwit = ["ciborium"]
[workspace]
members = ["query-grammar", "bitpacker", "common", "fastfield_codecs", "ownedbytes"]

9
README.md
View File

@@ -58,7 +58,7 @@ Distributed search is out of the scope of Tantivy, but if you are looking for th
# Getting started
Tantivy works on stable Rust (>= 1.27) and supports Linux, macOS, and Windows.
Tantivy works on stable Rust and supports Linux, macOS, and Windows.
- [Tantivy's simple search example](https://tantivy-search.github.io/examples/basic_search.html)
- [tantivy-cli and its tutorial](https://github.com/quickwit-oss/tantivy-cli) - `tantivy-cli` is an actual command-line interface that makes it easy for you to create a search engine,
@@ -81,9 +81,13 @@ There are many ways to support this project.
We use the GitHub Pull Request workflow: reference a GitHub ticket and/or include a comprehensive commit message when opening a PR.
## Minimum supported Rust version
Tantivy currently requires at least Rust 1.62 or later to compile.
## Clone and build locally
Tantivy compiles on stable Rust but requires `Rust >= 1.27`.
Tantivy compiles on stable Rust.
To check out and run tests, you can simply run:
```bash
@@ -127,6 +131,7 @@ $ gdb run
# Companies Using Tantivy
<p align="left">
<img align="center" src="doc/assets/images/etsy.png" alt="Etsy" height="25" width="auto" />&nbsp;
<img align="center" src="doc/assets/images/Nuclia.png#gh-light-mode-only" alt="Nuclia" height="25" width="auto" /> &nbsp;
<img align="center" src="doc/assets/images/humanfirst.png#gh-light-mode-only" alt="Humanfirst.ai" height="30" width="auto" />
<img align="center" src="doc/assets/images/element.io.svg#gh-light-mode-only" alt="Element.io" height="25" width="auto" />

8
bitpacker/src/bitpacker.rs
View File

@@ -87,15 +87,15 @@ impl BitUnpacker {
}
#[inline]
pub fn get(&self, idx: u64, data: &[u8]) -> u64 {
pub fn get(&self, idx: u32, data: &[u8]) -> u64 {
if self.num_bits == 0 {
return 0u64;
}
let addr_in_bits = idx * self.num_bits;
let addr_in_bits = idx * self.num_bits as u32;
let addr = addr_in_bits >> 3;
let bit_shift = addr_in_bits & 7;
debug_assert!(
addr + 8 <= data.len() as u64,
addr + 8 <= data.len() as u32,
"The fast field field should have been padded with 7 bytes."
);
let bytes: [u8; 8] = (&data[(addr as usize)..(addr as usize) + 8])
@@ -130,7 +130,7 @@ mod test {
fn test_bitpacker_util(len: usize, num_bits: u8) {
let (bitunpacker, vals, data) = create_fastfield_bitpacker(len, num_bits);
for (i, val) in vals.iter().enumerate() {
assert_eq!(bitunpacker.get(i as u64, &data), *val);
assert_eq!(bitunpacker.get(i as u32, &data), *val);
}
}

2
bitpacker/src/blocked_bitpacker.rs
View File

@@ -130,7 +130,7 @@ impl BlockedBitpacker {
let pos_in_block = idx % BLOCK_SIZE as usize;
if let Some(metadata) = self.offset_and_bits.get(metadata_pos) {
let unpacked = BitUnpacker::new(metadata.num_bits()).get(
pos_in_block as u64,
pos_in_block as u32,
&self.compressed_blocks[metadata.offset() as usize..],
);
unpacked + metadata.base_value()

14
common/src/bitset.rs
View File

@@ -259,11 +259,7 @@ impl BitSet {
// we do not check saturated els.
let higher = el / 64u32;
let lower = el % 64u32;
self.len += if self.tinysets[higher as usize].insert_mut(lower) {
1
} else {
0
};
self.len += u64::from(self.tinysets[higher as usize].insert_mut(lower));
}
/// Inserts an element in the `BitSet`
@@ -272,11 +268,7 @@ impl BitSet {
// we do not check saturated els.
let higher = el / 64u32;
let lower = el % 64u32;
self.len -= if self.tinysets[higher as usize].remove_mut(lower) {
1
} else {
0
};
self.len -= u64::from(self.tinysets[higher as usize].remove_mut(lower));
}
/// Returns true iff the elements is in the `BitSet`.
@@ -285,7 +277,7 @@ impl BitSet {
self.tinyset(el / 64u32).contains(el % 64)
}
/// Returns the first non-empty `TinySet` associated to a bucket lower
/// Returns the first non-empty `TinySet` associated with a bucket lower
/// or greater than bucket.
///
/// Reminder: the tiny set with the bucket `bucket`, represents the

13
common/src/lib.rs
View File

@@ -11,7 +11,10 @@ mod writer;
pub use bitset::*;
pub use serialize::{BinarySerializable, DeserializeFrom, FixedSize};
pub use vint::{read_u32_vint, read_u32_vint_no_advance, serialize_vint_u32, write_u32_vint, VInt};
pub use vint::{
deserialize_vint_u128, read_u32_vint, read_u32_vint_no_advance, serialize_vint_u128,
serialize_vint_u32, write_u32_vint, VInt, VIntU128,
};
pub use writer::{AntiCallToken, CountingWriter, TerminatingWrite};
/// Has length trait
@@ -52,13 +55,13 @@ const HIGHEST_BIT: u64 = 1 << 63;
/// to values over 2^63, and all values end up requiring 64 bits.
///
/// # See also
/// The [reverse mapping is `u64_to_i64`](./fn.u64_to_i64.html).
/// The reverse mapping is [`u64_to_i64()`].
#[inline]
pub fn i64_to_u64(val: i64) -> u64 {
(val as u64) ^ HIGHEST_BIT
}
/// Reverse the mapping given by [`i64_to_u64`](./fn.i64_to_u64.html).
/// Reverse the mapping given by [`i64_to_u64()`].
#[inline]
pub fn u64_to_i64(val: u64) -> i64 {
(val ^ HIGHEST_BIT) as i64
@@ -80,7 +83,7 @@ pub fn u64_to_i64(val: u64) -> i64 {
/// explains the mapping in a clear manner.
///
/// # See also
/// The [reverse mapping is `u64_to_f64`](./fn.u64_to_f64.html).
/// The reverse mapping is [`u64_to_f64()`].
#[inline]
pub fn f64_to_u64(val: f64) -> u64 {
let bits = val.to_bits();
@@ -91,7 +94,7 @@ pub fn f64_to_u64(val: f64) -> u64 {
}
}
/// Reverse the mapping given by [`i64_to_u64`](./fn.i64_to_u64.html).
/// Reverse the mapping given by [`f64_to_u64()`].
#[inline]
pub fn u64_to_f64(val: u64) -> f64 {
f64::from_bits(if val & HIGHEST_BIT != 0 {

16
common/src/serialize.rs
View File

@@ -107,6 +107,19 @@ impl FixedSize for u64 {
const SIZE_IN_BYTES: usize = 8;
}
impl BinarySerializable for u128 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
writer.write_u128::<Endianness>(*self)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
reader.read_u128::<Endianness>()
}
}
impl FixedSize for u128 {
const SIZE_IN_BYTES: usize = 16;
}
impl BinarySerializable for f32 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
writer.write_f32::<Endianness>(*self)
@@ -161,8 +174,7 @@ impl FixedSize for u8 {
impl BinarySerializable for bool {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
let val = if *self { 1 } else { 0 };
writer.write_u8(val)
writer.write_u8(u8::from(*self))
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<bool> {
let val = reader.read_u8()?;

92
common/src/vint.rs
View File

@@ -5,6 +5,75 @@ use byteorder::{ByteOrder, LittleEndian};
use super::BinarySerializable;
/// Variable int serializes a u128 number
pub fn serialize_vint_u128(mut val: u128, output: &mut Vec<u8>) {
loop {
let next_byte: u8 = (val % 128u128) as u8;
val /= 128u128;
if val == 0 {
output.push(next_byte | STOP_BIT);
return;
} else {
output.push(next_byte);
}
}
}
/// Deserializes a u128 number
///
/// Returns the number and the slice after the vint
pub fn deserialize_vint_u128(data: &[u8]) -> io::Result<(u128, &[u8])> {
let mut result = 0u128;
let mut shift = 0u64;
for i in 0..19 {
let b = data[i];
result |= u128::from(b % 128u8) << shift;
if b >= STOP_BIT {
return Ok((result, &data[i + 1..]));
}
shift += 7;
}
Err(io::Error::new(
io::ErrorKind::InvalidData,
"Failed to deserialize u128 vint",
))
}
/// Wrapper over a `u128` that serializes as a variable int.
#[derive(Clone, Copy, Debug, Eq, PartialEq)]
pub struct VIntU128(pub u128);
impl BinarySerializable for VIntU128 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
let mut buffer = vec![];
serialize_vint_u128(self.0, &mut buffer);
writer.write_all(&buffer)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
let mut bytes = reader.bytes();
let mut result = 0u128;
let mut shift = 0u64;
loop {
match bytes.next() {
Some(Ok(b)) => {
result |= u128::from(b % 128u8) << shift;
if b >= STOP_BIT {
return Ok(VIntU128(result));
}
shift += 7;
}
_ => {
return Err(io::Error::new(
io::ErrorKind::InvalidData,
"Reach end of buffer while reading VInt",
));
}
}
}
}
}
/// Wrapper over a `u64` that serializes as a variable int.
#[derive(Clone, Copy, Debug, Eq, PartialEq)]
pub struct VInt(pub u64);
@@ -88,7 +157,7 @@ fn vint_len(data: &[u8]) -> usize {
/// If the buffer does not start by a valid
/// vint payload
pub fn read_u32_vint(data: &mut &[u8]) -> u32 {
let (result, vlen) = read_u32_vint_no_advance(*data);
let (result, vlen) = read_u32_vint_no_advance(data);
*data = &data[vlen..];
result
}
@@ -176,6 +245,7 @@ impl BinarySerializable for VInt {
mod tests {
use super::{serialize_vint_u32, BinarySerializable, VInt};
use crate::vint::{deserialize_vint_u128, serialize_vint_u128, VIntU128};
fn aux_test_vint(val: u64) {
let mut v = [14u8; 10];
@@ -217,6 +287,26 @@ mod tests {
assert_eq!(&buffer[..len_vint], res2, "array wrong for {}", val);
}
fn aux_test_vint_u128(val: u128) {
let mut data = vec![];
serialize_vint_u128(val, &mut data);
let (deser_val, _data) = deserialize_vint_u128(&data).unwrap();
assert_eq!(val, deser_val);
let mut out = vec![];
VIntU128(val).serialize(&mut out).unwrap();
let deser_val = VIntU128::deserialize(&mut &out[..]).unwrap();
assert_eq!(val, deser_val.0);
}
#[test]
fn test_vint_u128() {
aux_test_vint_u128(0);
aux_test_vint_u128(1);
aux_test_vint_u128(u128::MAX / 3);
aux_test_vint_u128(u128::MAX);
}
#[test]
fn test_vint_u32() {
aux_test_serialize_vint_u32(0);

4
common/src/writer.rs
View File

@@ -55,14 +55,14 @@ impl<W: TerminatingWrite> TerminatingWrite for CountingWriter<W> {
}
/// Struct used to prevent from calling
/// [`terminate_ref`](trait.TerminatingWrite.html#tymethod.terminate_ref) directly
/// [`terminate_ref`](TerminatingWrite::terminate_ref) directly
///
/// The point is that while the type is public, it cannot be built by anyone
/// outside of this module.
pub struct AntiCallToken(());
/// Trait used to indicate when no more write need to be done on a writer
pub trait TerminatingWrite: Write + Send {
pub trait TerminatingWrite: Write + Send + Sync {
/// Indicate that the writer will no longer be used. Internally call terminate_ref.
fn terminate(mut self) -> io::Result<()>
where Self: Sized {

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2
doc/src/basis.md
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@@ -50,7 +50,7 @@ to get tantivy to fit your use case:
*Example 1* You could for instance use hadoop to build a very large search index in a timely manner, copy all of the resulting segment files in the same directory and edit the `meta.json` to get a functional index.[^2]
*Example 2* You could also disable your merge policy and enforce daily segments. Removing data after one week can then be done very efficiently by just editing the `meta.json` and deleting the files associated to segment `D-7`.
*Example 2* You could also disable your merge policy and enforce daily segments. Removing data after one week can then be done very efficiently by just editing the `meta.json` and deleting the files associated with segment `D-7`.
## Merging

16
examples/custom_collector.rs
View File

@@ -7,10 +7,12 @@
// Of course, you can have a look at the tantivy's built-in collectors
// such as the `CountCollector` for more examples.
use std::sync::Arc;
use fastfield_codecs::OptionalColumn;
// ---
// Importing tantivy...
use tantivy::collector::{Collector, SegmentCollector};
use tantivy::fastfield::{DynamicFastFieldReader, FastFieldReader};
use tantivy::query::QueryParser;
use tantivy::schema::{Field, Schema, FAST, INDEXED, TEXT};
use tantivy::{doc, Index, Score, SegmentReader};
@@ -95,7 +97,7 @@ impl Collector for StatsCollector {
}
struct StatsSegmentCollector {
fast_field_reader: DynamicFastFieldReader<u64>,
fast_field_reader: Arc<dyn OptionalColumn<u64>>,
stats: Stats,
}
@@ -103,10 +105,12 @@ impl SegmentCollector for StatsSegmentCollector {
type Fruit = Option<Stats>;
fn collect(&mut self, doc: u32, _score: Score) {
let value = self.fast_field_reader.get(doc) as f64;
self.stats.count += 1;
self.stats.sum += value;
self.stats.squared_sum += value * value;
if let Some(value) = self.fast_field_reader.get_val(doc) {
let value = value as f64;
self.stats.count += 1;
self.stats.sum += value;
self.stats.squared_sum += value * value;
}
}
fn harvest(self) -> <Self as SegmentCollector>::Fruit {

3
examples/custom_tokenizer.rs
View File

@@ -36,8 +36,7 @@ fn main() -> tantivy::Result<()> {
// need to be able to be able to retrieve it
// for our application.
//
// We can make our index lighter and
// by omitting `STORED` flag.
// We can make our index lighter by omitting the `STORED` flag.
let body = schema_builder.add_text_field("body", TEXT);
let schema = schema_builder.build();

2
examples/deleting_updating_documents.rs
View File

@@ -113,7 +113,7 @@ fn main() -> tantivy::Result<()> {
// on its id.
//
// Note that `tantivy` does nothing to enforce the idea that
// there is only one document associated to this id.
// there is only one document associated with this id.
//
// Also you might have noticed that we apply the delete before
// having committed. This does not matter really...

4
examples/iterating_docs_and_positions.rs
View File

@@ -44,7 +44,7 @@ fn main() -> tantivy::Result<()> {
// A segment contains different data structure.
// Inverted index stands for the combination of
// - the term dictionary
// - the inverted lists associated to each terms and their positions
// - the inverted lists associated with each terms and their positions
let inverted_index = segment_reader.inverted_index(title)?;
// A `Term` is a text token associated with a field.
@@ -105,7 +105,7 @@ fn main() -> tantivy::Result<()> {
// A segment contains different data structure.
// Inverted index stands for the combination of
// - the term dictionary
// - the inverted lists associated to each terms and their positions
// - the inverted lists associated with each terms and their positions
let inverted_index = segment_reader.inverted_index(title)?;
// This segment posting object is like a cursor over the documents matching the term.

3
examples/warmer.rs
View File

@@ -3,7 +3,6 @@ use std::collections::{HashMap, HashSet};
use std::sync::{Arc, RwLock, Weak};
use tantivy::collector::TopDocs;
use tantivy::fastfield::FastFieldReader;
use tantivy::query::QueryParser;
use tantivy::schema::{Field, Schema, FAST, TEXT};
use tantivy::{
@@ -52,7 +51,7 @@ impl Warmer for DynamicPriceColumn {
let product_id_reader = segment.fast_fields().u64(self.field)?;
let product_ids: Vec<ProductId> = segment
.doc_ids_alive()
.map(|doc| product_id_reader.get(doc))
.flat_map(|doc| product_id_reader.get_val(doc))
.collect();
let mut prices_it = self.price_fetcher.fetch_prices(&product_ids).into_iter();
let mut price_vals: Vec<Price> = Vec::new();

7
fastfield_codecs/Cargo.toml
View File

@@ -14,6 +14,10 @@ tantivy-bitpacker = { version="0.2", path = "../bitpacker/" }
ownedbytes = { version = "0.3.0", path = "../ownedbytes" }
prettytable-rs = {version="0.9.0", optional= true}
rand = {version="0.8.3", optional= true}
fastdivide = "0.4"
log = "0.4"
itertools = { version = "0.10.3" }
measure_time = { version="0.8.2", optional=true}
[dev-dependencies]
more-asserts = "0.3.0"
@@ -21,6 +25,7 @@ proptest = "1.0.0"
rand = "0.8.3"
[features]
bin = ["prettytable-rs", "rand"]
bin = ["prettytable-rs", "rand", "measure_time"]
default = ["bin"]
unstable = []

277
fastfield_codecs/benches/bench.rs
View File

@@ -4,90 +4,243 @@ extern crate test;
#[cfg(test)]
mod tests {
use fastfield_codecs::bitpacked::{BitpackedReader, BitpackedSerializer};
use fastfield_codecs::blockwise_linear::{BlockwiseLinearReader, BlockwiseLinearSerializer};
use fastfield_codecs::linear::{LinearReader, LinearSerializer};
use fastfield_codecs::*;
use std::iter;
use std::sync::Arc;
fn get_data() -> Vec<u64> {
let mut data: Vec<_> = (100..55000_u64)
.map(|num| num + rand::random::<u8>() as u64)
use fastfield_codecs::*;
use ownedbytes::OwnedBytes;
use rand::prelude::*;
use test::Bencher;
use super::*;
// Warning: this generates the same permutation at each call
fn generate_permutation() -> Vec<u64> {
let mut permutation: Vec<u64> = (0u64..100_000u64).collect();
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
fn generate_random() -> Vec<u64> {
let mut permutation: Vec<u64> = (0u64..100_000u64)
.map(|el| el + random::<u16>() as u64)
.collect();
data.push(99_000);
data.insert(1000, 2000);
data.insert(2000, 100);
data.insert(3000, 4100);
data.insert(4000, 100);
data.insert(5000, 800);
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
// Warning: this generates the same permutation at each call
fn generate_permutation_gcd() -> Vec<u64> {
let mut permutation: Vec<u64> = (1u64..100_000u64).map(|el| el * 1000).collect();
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
pub fn serialize_and_load<T: MonotonicallyMappableToU64 + Ord + Default>(
column: &[T],
) -> Arc<dyn Column<T>> {
let mut buffer = Vec::new();
serialize(VecColumn::from(&column), &mut buffer, &ALL_CODEC_TYPES).unwrap();
open(OwnedBytes::new(buffer)).unwrap().to_full().unwrap()
}
#[bench]
fn bench_intfastfield_jumpy_veclookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
b.iter(|| {
let mut a = 0u64;
for _ in 0..n {
a = permutation[a as usize];
}
a
});
}
#[bench]
fn bench_intfastfield_jumpy_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn Column<u64>> = serialize_and_load(&permutation);
b.iter(|| {
let mut a = 0u64;
for _ in 0..n {
a = column.get_val(a as u32);
}
a
});
}
fn get_exp_data() -> Vec<u64> {
let mut data = vec![];
for i in 0..100 {
let num = i * i;
data.extend(iter::repeat(i as u64).take(num));
}
data.shuffle(&mut StdRng::from_seed([1u8; 32]));
// lengt = 328350
data
}
fn value_iter() -> impl Iterator<Item = u64> {
0..20_000
fn get_data_50percent_item() -> (u128, u128, Vec<u128>) {
let mut permutation = get_exp_data();
let major_item = 20;
let minor_item = 10;
permutation.extend(iter::repeat(major_item).take(permutation.len()));
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
let permutation = permutation.iter().map(|el| *el as u128).collect::<Vec<_>>();
(major_item as u128, minor_item as u128, permutation)
}
fn bench_get<S: FastFieldCodecSerializer, R: FastFieldCodecReader>(
b: &mut Bencher,
data: &[u64],
) {
let mut bytes = vec![];
S::serialize(&mut bytes, &data).unwrap();
let reader = R::open_from_bytes(OwnedBytes::new(bytes)).unwrap();
b.iter(|| {
let mut sum = 0u64;
for pos in value_iter() {
let val = reader.get_u64(pos as u64);
debug_assert_eq!(data[pos as usize], val);
sum = sum.wrapping_add(val);
}
sum
});
fn get_u128_column_random() -> Arc<dyn Column<u128>> {
let permutation = generate_random();
let permutation = permutation.iter().map(|el| *el as u128).collect::<Vec<_>>();
get_u128_column_from_data(&permutation)
}
fn bench_create<S: FastFieldCodecSerializer>(b: &mut Bencher, data: &[u64]) {
let mut bytes = vec![];
fn get_u128_column_from_data(data: &[u128]) -> Arc<dyn Column<u128>> {
let mut out = vec![];
let iter_gen = || data.iter().cloned();
serialize_u128(iter_gen, data.len() as u32, &mut out).unwrap();
let out = OwnedBytes::new(out);
open_u128::<u128>(out).unwrap().to_full().unwrap()
}
#[bench]
fn bench_intfastfield_getrange_u128_50percent_hit(b: &mut Bencher) {
let (major_item, _minor_item, data) = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| {
S::serialize(&mut bytes, &data).unwrap();
let mut positions = Vec::new();
column.get_docids_for_value_range(
major_item..=major_item,
0..data.len() as u32,
&mut positions,
);
positions
});
}
use ownedbytes::OwnedBytes;
use test::Bencher;
#[bench]
fn bench_fastfield_bitpack_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<BitpackedSerializer>(b, &data);
fn bench_intfastfield_getrange_u128_single_hit(b: &mut Bencher) {
let (_major_item, minor_item, data) = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(
minor_item..=minor_item,
0..data.len() as u32,
&mut positions,
);
positions
});
}
#[bench]
fn bench_fastfield_linearinterpol_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<LinearSerializer>(b, &data);
fn bench_intfastfield_getrange_u128_hit_all(b: &mut Bencher) {
let (_major_item, _minor_item, data) = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(0..=u128::MAX, 0..data.len() as u32, &mut positions);
positions
});
}
#[bench]
fn bench_fastfield_multilinearinterpol_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<BlockwiseLinearSerializer>(b, &data);
fn bench_intfastfield_scan_all_fflookup_u128(b: &mut Bencher) {
let column = get_u128_column_random();
b.iter(|| {
let mut a = 0u128;
for i in 0u64..column.num_vals() as u64 {
a += column.get_val(i as u32);
}
a
});
}
#[bench]
fn bench_fastfield_bitpack_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<BitpackedSerializer, BitpackedReader>(b, &data);
fn bench_intfastfield_jumpy_stride5_u128(b: &mut Bencher) {
let column = get_u128_column_random();
b.iter(|| {
let n = column.num_vals();
let mut a = 0u128;
for i in (0..n / 5).map(|val| val * 5) {
a += column.get_val(i);
}
a
});
}
#[bench]
fn bench_fastfield_linearinterpol_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<LinearSerializer, LinearReader>(b, &data);
fn bench_intfastfield_stride7_vec(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
b.iter(|| {
let mut a = 0u64;
for i in (0..n / 7).map(|val| val * 7) {
a += permutation[i as usize];
}
a
});
}
#[bench]
fn bench_fastfield_multilinearinterpol_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<BlockwiseLinearSerializer, BlockwiseLinearReader>(b, &data);
fn bench_intfastfield_stride7_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn Column<u64>> = serialize_and_load(&permutation);
b.iter(|| {
let mut a = 0;
for i in (0..n / 7).map(|val| val * 7) {
a += column.get_val(i as u32);
}
a
});
}
pub fn stats_from_vec(data: &[u64]) -> FastFieldStats {
let min_value = data.iter().cloned().min().unwrap_or(0);
let max_value = data.iter().cloned().max().unwrap_or(0);
FastFieldStats {
min_value,
max_value,
num_vals: data.len() as u64,
}
#[bench]
fn bench_intfastfield_scan_all_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn Column<u64>> = serialize_and_load(&permutation);
b.iter(|| {
let mut a = 0u64;
for i in 0u32..n as u32 {
a += column.get_val(i);
}
a
});
}
#[bench]
fn bench_intfastfield_scan_all_fflookup_gcd(b: &mut Bencher) {
let permutation = generate_permutation_gcd();
let n = permutation.len();
let column: Arc<dyn Column<u64>> = serialize_and_load(&permutation);
b.iter(|| {
let mut a = 0u64;
for i in 0..n {
a += column.get_val(i as u32);
}
a
});
}
#[bench]
fn bench_intfastfield_scan_all_vec(b: &mut Bencher) {
let permutation = generate_permutation();
b.iter(|| {
let mut a = 0u64;
for i in 0..permutation.len() {
a += permutation[i as usize] as u64;
}
a
});
}
}

152
fastfield_codecs/src/bitpacked.rs
View File

@@ -1,12 +1,10 @@
use std::io::{self, Write};
use common::BinarySerializable;
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::{
FastFieldCodecReader, FastFieldCodecSerializer, FastFieldCodecType, FastFieldDataAccess,
};
use crate::serialize::NormalizedHeader;
use crate::{Column, FastFieldCodec, FastFieldCodecType};
/// Depending on the field type, a different
/// fast field is required.
@@ -14,144 +12,88 @@ use crate::{
pub struct BitpackedReader {
data: OwnedBytes,
bit_unpacker: BitUnpacker,
pub min_value_u64: u64,
pub max_value_u64: u64,
normalized_header: NormalizedHeader,
}
impl FastFieldCodecReader for BitpackedReader {
/// Opens a fast field given a file.
fn open_from_bytes(bytes: OwnedBytes) -> io::Result<Self> {
let footer_offset = bytes.len() - 16;
let (data, mut footer) = bytes.split(footer_offset);
let min_value = u64::deserialize(&mut footer)?;
let amplitude = u64::deserialize(&mut footer)?;
let max_value = min_value + amplitude;
let num_bits = compute_num_bits(amplitude);
let bit_unpacker = BitUnpacker::new(num_bits);
Ok(BitpackedReader {
data,
min_value_u64: min_value,
max_value_u64: max_value,
bit_unpacker,
})
}
impl Column for BitpackedReader {
#[inline]
fn get_u64(&self, doc: u64) -> u64 {
self.min_value_u64 + self.bit_unpacker.get(doc, &self.data)
fn get_val(&self, doc: u32) -> u64 {
self.bit_unpacker.get(doc, &self.data)
}
#[inline]
fn min_value(&self) -> u64 {
self.min_value_u64
// The BitpackedReader assumes a normalized vector.
0
}
#[inline]
fn max_value(&self) -> u64 {
self.max_value_u64
self.normalized_header.max_value
}
}
pub struct BitpackedSerializerLegacy<'a, W: 'a + Write> {
bit_packer: BitPacker,
write: &'a mut W,
min_value: u64,
amplitude: u64,
num_bits: u8,
}
impl<'a, W: Write> BitpackedSerializerLegacy<'a, W> {
/// Creates a new fast field serializer.
///
/// The serializer in fact encode the values by bitpacking
/// `(val - min_value)`.
///
/// It requires a `min_value` and a `max_value` to compute
/// compute the minimum number of bits required to encode
/// values.
pub fn open(
write: &'a mut W,
min_value: u64,
max_value: u64,
) -> io::Result<BitpackedSerializerLegacy<'a, W>> {
assert!(min_value <= max_value);
let amplitude = max_value - min_value;
let num_bits = compute_num_bits(amplitude);
let bit_packer = BitPacker::new();
Ok(BitpackedSerializerLegacy {
bit_packer,
write,
min_value,
amplitude,
num_bits,
})
}
/// Pushes a new value to the currently open u64 fast field.
#[inline]
pub fn add_val(&mut self, val: u64) -> io::Result<()> {
let val_to_write: u64 = val - self.min_value;
self.bit_packer
.write(val_to_write, self.num_bits, &mut self.write)?;
Ok(())
}
pub fn close_field(mut self) -> io::Result<()> {
self.bit_packer.close(&mut self.write)?;
self.min_value.serialize(&mut self.write)?;
self.amplitude.serialize(&mut self.write)?;
Ok(())
fn num_vals(&self) -> u32 {
self.normalized_header.num_vals
}
}
pub struct BitpackedSerializer {}
pub struct BitpackedCodec;
impl FastFieldCodecSerializer for BitpackedSerializer {
impl FastFieldCodec for BitpackedCodec {
/// The CODEC_TYPE is an enum value used for serialization.
const CODEC_TYPE: FastFieldCodecType = FastFieldCodecType::Bitpacked;
type Reader = BitpackedReader;
/// Opens a fast field given a file.
fn open_from_bytes(
data: OwnedBytes,
normalized_header: NormalizedHeader,
) -> io::Result<Self::Reader> {
let num_bits = compute_num_bits(normalized_header.max_value);
let bit_unpacker = BitUnpacker::new(num_bits);
Ok(BitpackedReader {
data,
bit_unpacker,
normalized_header,
})
}
/// Serializes data with the BitpackedFastFieldSerializer.
///
/// The serializer in fact encode the values by bitpacking
/// `(val - min_value)`.
/// The bitpacker assumes that the column has been normalized.
/// i.e. It has already been shifted by its minimum value, so that its
/// current minimum value is 0.
///
/// It requires a `min_value` and a `max_value` to compute
/// compute the minimum number of bits required to encode
/// values.
fn serialize(
write: &mut impl Write,
fastfield_accessor: &dyn FastFieldDataAccess,
) -> io::Result<()> {
let mut serializer = BitpackedSerializerLegacy::open(
write,
fastfield_accessor.min_value(),
fastfield_accessor.max_value(),
)?;
for val in fastfield_accessor.iter() {
serializer.add_val(val)?;
/// Ideally, we made a shift upstream on the column so that `col.min_value() == 0`.
fn serialize(column: &dyn Column, write: &mut impl Write) -> io::Result<()> {
assert_eq!(column.min_value(), 0u64);
let num_bits = compute_num_bits(column.max_value());
let mut bit_packer = BitPacker::new();
for val in column.iter() {
bit_packer.write(val, num_bits, write)?;
}
serializer.close_field()?;
bit_packer.close(write)?;
Ok(())
}
fn is_applicable(_fastfield_accessor: &impl FastFieldDataAccess) -> bool {
true
}
fn estimate(fastfield_accessor: &impl FastFieldDataAccess) -> f32 {
let amplitude = fastfield_accessor.max_value() - fastfield_accessor.min_value();
let num_bits = compute_num_bits(amplitude);
fn estimate(column: &dyn Column) -> Option<f32> {
let num_bits = compute_num_bits(column.max_value());
let num_bits_uncompressed = 64;
num_bits as f32 / num_bits_uncompressed as f32
Some(num_bits as f32 / num_bits_uncompressed as f32)
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::tests::get_codec_test_data_sets;
use crate::tests::get_codec_test_datasets;
fn create_and_validate(data: &[u64], name: &str) {
crate::tests::create_and_validate::<BitpackedSerializer, BitpackedReader>(data, name);
crate::tests::create_and_validate::<BitpackedCodec>(data, name);
}
#[test]
fn test_with_codec_data_sets() {
let data_sets = get_codec_test_data_sets();
let data_sets = get_codec_test_datasets();
for (mut data, name) in data_sets {
create_and_validate(&data, name);
data.reverse();

534
fastfield_codecs/src/blockwise_linear.rs
View File

@@ -1,436 +1,186 @@
//! The BlockwiseLinear codec uses linear interpolation to guess a values and stores the
//! offset, but in blocks of 512.
//!
//! With a CHUNK_SIZE of 512 and 29 byte metadata per block, we get a overhead for metadata of 232 /
//! 512 = 0,45 bits per element. The additional space required per element in a block is the the
//! maximum deviation of the linear interpolation estimation function.
//!
//! E.g. if the maximum deviation of an element is 12, all elements cost 4bits.
//!
//! Size per block:
//! Num Elements * Maximum Deviation from Interpolation + 29 Byte Metadata
use std::io::{self, Read, Write};
use std::ops::Sub;
use std::sync::Arc;
use std::{io, iter};
use common::{BinarySerializable, CountingWriter, DeserializeFrom};
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::linear::{get_calculated_value, get_slope};
use crate::{
FastFieldCodecReader, FastFieldCodecSerializer, FastFieldCodecType, FastFieldDataAccess,
};
use crate::line::Line;
use crate::serialize::NormalizedHeader;
use crate::{Column, FastFieldCodec, FastFieldCodecType, VecColumn};
const CHUNK_SIZE: u64 = 512;
const CHUNK_SIZE: usize = 512;
/// Depending on the field type, a different
/// fast field is required.
#[derive(Clone)]
pub struct BlockwiseLinearReader {
data: OwnedBytes,
pub footer: BlockwiseLinearFooter,
}
#[derive(Clone, Debug, Default)]
struct Function {
// The offset in the data is required, because we have different bit_widths per block
data_start_offset: u64,
// start_pos in the block will be CHUNK_SIZE * BLOCK_NUM
start_pos: u64,
// only used during serialization, 0 after deserialization
end_pos: u64,
// only used during serialization, 0 after deserialization
value_start_pos: u64,
// only used during serialization, 0 after deserialization
value_end_pos: u64,
slope: f32,
// The offset so that all values are positive when writing them
positive_val_offset: u64,
num_bits: u8,
#[derive(Debug, Default)]
struct Block {
line: Line,
bit_unpacker: BitUnpacker,
data_start_offset: usize,
}
impl Function {
fn calc_slope(&mut self) {
let num_vals = self.end_pos - self.start_pos;
self.slope = get_slope(self.value_start_pos, self.value_end_pos, num_vals);
}
// split the interpolation into two function, change self and return the second split
fn split(&mut self, split_pos: u64, split_pos_value: u64) -> Function {
let mut new_function = Function {
start_pos: split_pos,
end_pos: self.end_pos,
value_start_pos: split_pos_value,
value_end_pos: self.value_end_pos,
..Default::default()
};
new_function.calc_slope();
self.end_pos = split_pos;
self.value_end_pos = split_pos_value;
self.calc_slope();
new_function
}
}
impl BinarySerializable for Function {
fn serialize<W: Write>(&self, write: &mut W) -> io::Result<()> {
self.data_start_offset.serialize(write)?;
self.value_start_pos.serialize(write)?;
self.positive_val_offset.serialize(write)?;
self.slope.serialize(write)?;
self.num_bits.serialize(write)?;
impl BinarySerializable for Block {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
self.line.serialize(writer)?;
self.bit_unpacker.bit_width().serialize(writer)?;
Ok(())
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Function> {
let data_start_offset = u64::deserialize(reader)?;
let value_start_pos = u64::deserialize(reader)?;
let offset = u64::deserialize(reader)?;
let slope = f32::deserialize(reader)?;
let num_bits = u8::deserialize(reader)?;
let interpolation = Function {
data_start_offset,
value_start_pos,
positive_val_offset: offset,
num_bits,
bit_unpacker: BitUnpacker::new(num_bits),
slope,
..Default::default()
};
Ok(interpolation)
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let line = Line::deserialize(reader)?;
let bit_width = u8::deserialize(reader)?;
Ok(Block {
line,
bit_unpacker: BitUnpacker::new(bit_width),
data_start_offset: 0,
})
}
}
#[derive(Clone, Debug)]
pub struct BlockwiseLinearFooter {
pub num_vals: u64,
pub min_value: u64,
pub max_value: u64,
interpolations: Vec<Function>,
fn compute_num_blocks(num_vals: u32) -> usize {
(num_vals as usize + CHUNK_SIZE - 1) / CHUNK_SIZE
}
impl BinarySerializable for BlockwiseLinearFooter {
fn serialize<W: Write>(&self, write: &mut W) -> io::Result<()> {
let mut out = vec![];
self.num_vals.serialize(&mut out)?;
self.min_value.serialize(&mut out)?;
self.max_value.serialize(&mut out)?;
self.interpolations.serialize(&mut out)?;
write.write_all(&out)?;
(out.len() as u32).serialize(write)?;
Ok(())
}
pub struct BlockwiseLinearCodec;
fn deserialize<R: Read>(reader: &mut R) -> io::Result<BlockwiseLinearFooter> {
let mut footer = BlockwiseLinearFooter {
num_vals: u64::deserialize(reader)?,
min_value: u64::deserialize(reader)?,
max_value: u64::deserialize(reader)?,
interpolations: Vec::<Function>::deserialize(reader)?,
};
for (num, interpol) in footer.interpolations.iter_mut().enumerate() {
interpol.start_pos = CHUNK_SIZE * num as u64;
}
Ok(footer)
}
}
impl FastFieldCodec for BlockwiseLinearCodec {
const CODEC_TYPE: crate::FastFieldCodecType = FastFieldCodecType::BlockwiseLinear;
type Reader = BlockwiseLinearReader;
#[inline]
fn get_interpolation_position(doc: u64) -> usize {
let index = doc / CHUNK_SIZE;
index as usize
}
#[inline]
fn get_interpolation_function(doc: u64, interpolations: &[Function]) -> &Function {
&interpolations[get_interpolation_position(doc)]
}
impl FastFieldCodecReader for BlockwiseLinearReader {
/// Opens a fast field given a file.
fn open_from_bytes(bytes: OwnedBytes) -> io::Result<Self> {
fn open_from_bytes(
bytes: ownedbytes::OwnedBytes,
normalized_header: NormalizedHeader,
) -> io::Result<Self::Reader> {
let footer_len: u32 = (&bytes[bytes.len() - 4..]).deserialize()?;
let footer_offset = bytes.len() - 4 - footer_len as usize;
let (data, mut footer) = bytes.split(footer_offset);
let footer = BlockwiseLinearFooter::deserialize(&mut footer)?;
Ok(BlockwiseLinearReader { data, footer })
}
let num_blocks = compute_num_blocks(normalized_header.num_vals);
let mut blocks: Vec<Block> = iter::repeat_with(|| Block::deserialize(&mut footer))
.take(num_blocks)
.collect::<io::Result<_>>()?;
#[inline]
fn get_u64(&self, idx: u64) -> u64 {
let interpolation = get_interpolation_function(idx, &self.footer.interpolations);
let in_block_idx = idx - interpolation.start_pos;
let calculated_value = get_calculated_value(
interpolation.value_start_pos,
in_block_idx,
interpolation.slope,
);
let diff = interpolation.bit_unpacker.get(
in_block_idx,
&self.data[interpolation.data_start_offset as usize..],
);
(calculated_value + diff) - interpolation.positive_val_offset
}
#[inline]
fn min_value(&self) -> u64 {
self.footer.min_value
}
#[inline]
fn max_value(&self) -> u64 {
self.footer.max_value
}
}
/// Same as LinearSerializer, but working on chunks of CHUNK_SIZE elements.
pub struct BlockwiseLinearSerializer {}
impl FastFieldCodecSerializer for BlockwiseLinearSerializer {
const CODEC_TYPE: FastFieldCodecType = FastFieldCodecType::BlockwiseLinear;
/// Creates a new fast field serializer.
fn serialize(
write: &mut impl Write,
fastfield_accessor: &dyn FastFieldDataAccess,
) -> io::Result<()> {
assert!(fastfield_accessor.min_value() <= fastfield_accessor.max_value());
let first_val = fastfield_accessor.get_val(0);
let last_val = fastfield_accessor.get_val(fastfield_accessor.num_vals() as u64 - 1);
let mut first_function = Function {
end_pos: fastfield_accessor.num_vals(),
value_start_pos: first_val,
value_end_pos: last_val,
..Default::default()
};
first_function.calc_slope();
let mut interpolations = vec![first_function];
// Since we potentially apply multiple passes over the data, the data is cached.
// Multiple iteration can be expensive (merge with index sorting can add lot of overhead per
// iteration)
let data = fastfield_accessor.iter().collect::<Vec<_>>();
//// let's split this into chunks of CHUNK_SIZE
for data_pos in (0..data.len() as u64).step_by(CHUNK_SIZE as usize).skip(1) {
let new_fun = {
let current_interpolation = interpolations.last_mut().unwrap();
current_interpolation.split(data_pos, data[data_pos as usize])
};
interpolations.push(new_fun);
let mut start_offset = 0;
for block in &mut blocks {
block.data_start_offset = start_offset;
start_offset += (block.bit_unpacker.bit_width() as usize) * CHUNK_SIZE / 8;
}
// calculate offset and max (-> numbits) for each function
for interpolation in &mut interpolations {
let mut offset = 0;
let mut rel_positive_max = 0;
for (pos, actual_value) in data
[interpolation.start_pos as usize..interpolation.end_pos as usize]
.iter()
.cloned()
.enumerate()
{
let calculated_value = get_calculated_value(
interpolation.value_start_pos,
pos as u64,
interpolation.slope,
);
if calculated_value > actual_value {
// negative value we need to apply an offset
// we ignore negative values in the max value calculation, because negative
// values will be offset to 0
offset = offset.max(calculated_value - actual_value);
} else {
// positive value no offset reuqired
rel_positive_max = rel_positive_max.max(actual_value - calculated_value);
}
}
interpolation.positive_val_offset = offset;
interpolation.num_bits = compute_num_bits(rel_positive_max + offset);
}
let mut bit_packer = BitPacker::new();
let write = &mut CountingWriter::wrap(write);
for interpolation in &mut interpolations {
interpolation.data_start_offset = write.written_bytes();
let num_bits = interpolation.num_bits;
for (pos, actual_value) in data
[interpolation.start_pos as usize..interpolation.end_pos as usize]
.iter()
.cloned()
.enumerate()
{
let calculated_value = get_calculated_value(
interpolation.value_start_pos,
pos as u64,
interpolation.slope,
);
let diff = (actual_value + interpolation.positive_val_offset) - calculated_value;
bit_packer.write(diff, num_bits, write)?;
}
bit_packer.flush(write)?;
}
bit_packer.close(write)?;
let footer = BlockwiseLinearFooter {
num_vals: fastfield_accessor.num_vals(),
min_value: fastfield_accessor.min_value(),
max_value: fastfield_accessor.max_value(),
interpolations,
};
footer.serialize(write)?;
Ok(())
Ok(BlockwiseLinearReader {
blocks: Arc::new(blocks),
data,
normalized_header,
})
}
fn is_applicable(fastfield_accessor: &impl FastFieldDataAccess) -> bool {
if fastfield_accessor.num_vals() < 5_000 {
return false;
// Estimate first_chunk and extrapolate
fn estimate(column: &dyn crate::Column) -> Option<f32> {
if column.num_vals() < 10 * CHUNK_SIZE as u32 {
return None;
}
// On serialization the offset is added to the actual value.
// We need to make sure this won't run into overflow calculation issues.
// For this we take the maximum theroretical offset and add this to the max value.
// If this doesn't overflow the algorithm should be fine
let theorethical_maximum_offset =
fastfield_accessor.max_value() - fastfield_accessor.min_value();
if fastfield_accessor
.max_value()
.checked_add(theorethical_maximum_offset)
.is_none()
{
return false;
let mut first_chunk: Vec<u64> = column.iter().take(CHUNK_SIZE as usize).collect();
let line = Line::train(&VecColumn::from(&first_chunk));
for (i, buffer_val) in first_chunk.iter_mut().enumerate() {
let interpolated_val = line.eval(i as u32);
*buffer_val = buffer_val.wrapping_sub(interpolated_val);
}
true
}
/// estimation for linear interpolation is hard because, you don't know
/// where the local maxima are for the deviation of the calculated value and
/// the offset is also unknown.
fn estimate(fastfield_accessor: &impl FastFieldDataAccess) -> f32 {
let first_val_in_first_block = fastfield_accessor.get_val(0);
let last_elem_in_first_chunk = CHUNK_SIZE.min(fastfield_accessor.num_vals());
let last_val_in_first_block =
fastfield_accessor.get_val(last_elem_in_first_chunk as u64 - 1);
let slope = get_slope(
first_val_in_first_block,
last_val_in_first_block,
fastfield_accessor.num_vals(),
);
// let's sample at 0%, 5%, 10% .. 95%, 100%, but for the first block only
let sample_positions = (0..20)
.map(|pos| (last_elem_in_first_chunk as f32 / 100.0 * pos as f32 * 5.0) as usize)
.collect::<Vec<_>>();
let max_distance = sample_positions
let estimated_bit_width = first_chunk
.iter()
.map(|pos| {
let calculated_value =
get_calculated_value(first_val_in_first_block, *pos as u64, slope);
let actual_value = fastfield_accessor.get_val(*pos as u64);
distance(calculated_value, actual_value)
})
.map(|el| ((el + 1) as f32 * 3.0) as u64)
.map(compute_num_bits)
.max()
.unwrap();
// Estimate one block and extrapolate the cost to all blocks.
// the theory would be that we don't have the actual max_distance, but we are close within
// 50% threshold.
// It is multiplied by 2 because in a log case scenario the line would be as much above as
// below. So the offset would = max_distance
//
let relative_max_value = (max_distance as f32 * 1.5) * 2.0;
let num_bits = compute_num_bits(relative_max_value as u64) as u64 * fastfield_accessor.num_vals() as u64
let metadata_per_block = {
let mut out = vec![];
Block::default().serialize(&mut out).unwrap();
out.len()
};
let num_bits = estimated_bit_width as u64 * column.num_vals() as u64
// function metadata per block
+ 29 * (fastfield_accessor.num_vals() / CHUNK_SIZE);
let num_bits_uncompressed = 64 * fastfield_accessor.num_vals();
num_bits as f32 / num_bits_uncompressed as f32
}
}
fn distance<T: Sub<Output = T> + Ord>(x: T, y: T) -> T {
if x < y {
y - x
} else {
x - y
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::tests::get_codec_test_data_sets;
fn create_and_validate(data: &[u64], name: &str) -> (f32, f32) {
crate::tests::create_and_validate::<BlockwiseLinearSerializer, BlockwiseLinearReader>(
data, name,
)
+ metadata_per_block as u64 * (column.num_vals() as u64 / CHUNK_SIZE as u64);
let num_bits_uncompressed = 64 * column.num_vals();
Some(num_bits as f32 / num_bits_uncompressed as f32)
}
const HIGHEST_BIT: u64 = 1 << 63;
pub fn i64_to_u64(val: i64) -> u64 {
(val as u64) ^ HIGHEST_BIT
}
fn serialize(column: &dyn Column, wrt: &mut impl io::Write) -> io::Result<()> {
// The BitpackedReader assumes a normalized vector.
assert_eq!(column.min_value(), 0);
let mut buffer = Vec::with_capacity(CHUNK_SIZE);
let num_vals = column.num_vals();
#[test]
fn test_compression_i64() {
let data = (i64::MAX - 600_000..=i64::MAX - 550_000)
.map(i64_to_u64)
.collect::<Vec<_>>();
let (estimate, actual_compression) =
create_and_validate(&data, "simple monotonically large i64");
assert!(actual_compression < 0.2);
assert!(estimate < 0.20);
assert!(estimate > 0.15);
assert!(actual_compression > 0.01);
}
let num_blocks = compute_num_blocks(num_vals);
let mut blocks = Vec::with_capacity(num_blocks);
#[test]
fn test_compression() {
let data = (10..=6_000_u64).collect::<Vec<_>>();
let (estimate, actual_compression) =
create_and_validate(&data, "simple monotonically large");
assert!(actual_compression < 0.2);
assert!(estimate < 0.20);
assert!(estimate > 0.15);
assert!(actual_compression > 0.01);
}
let mut vals = column.iter();
#[test]
fn test_with_codec_data_sets() {
let data_sets = get_codec_test_data_sets();
for (mut data, name) in data_sets {
create_and_validate(&data, name);
data.reverse();
create_and_validate(&data, name);
let mut bit_packer = BitPacker::new();
for _ in 0..num_blocks {
buffer.clear();
buffer.extend((&mut vals).take(CHUNK_SIZE));
let line = Line::train(&VecColumn::from(&buffer));
assert!(!buffer.is_empty());
for (i, buffer_val) in buffer.iter_mut().enumerate() {
let interpolated_val = line.eval(i as u32);
*buffer_val = buffer_val.wrapping_sub(interpolated_val);
}
let bit_width = buffer.iter().copied().map(compute_num_bits).max().unwrap();
for &buffer_val in &buffer {
bit_packer.write(buffer_val, bit_width, wrt)?;
}
blocks.push(Block {
line,
bit_unpacker: BitUnpacker::new(bit_width),
data_start_offset: 0,
});
}
}
#[test]
fn test_simple() {
let data = (10..=20_u64).collect::<Vec<_>>();
create_and_validate(&data, "simple monotonically");
}
#[test]
fn border_cases_1() {
let data = (0..1024).collect::<Vec<_>>();
create_and_validate(&data, "border case");
}
#[test]
fn border_case_2() {
let data = (0..1025).collect::<Vec<_>>();
create_and_validate(&data, "border case");
}
#[test]
fn rand() {
for _ in 0..10 {
let mut data = (5_000..20_000)
.map(|_| rand::random::<u32>() as u64)
.collect::<Vec<_>>();
let _ = create_and_validate(&data, "random");
data.reverse();
create_and_validate(&data, "random");
bit_packer.close(wrt)?;
assert_eq!(blocks.len(), compute_num_blocks(num_vals));
let mut counting_wrt = CountingWriter::wrap(wrt);
for block in &blocks {
block.serialize(&mut counting_wrt)?;
}
let footer_len = counting_wrt.written_bytes();
(footer_len as u32).serialize(&mut counting_wrt)?;
Ok(())
}
}
#[derive(Clone)]
pub struct BlockwiseLinearReader {
blocks: Arc<Vec<Block>>,
normalized_header: NormalizedHeader,
data: OwnedBytes,
}
impl Column for BlockwiseLinearReader {
#[inline(always)]
fn get_val(&self, idx: u32) -> u64 {
let block_id = (idx / CHUNK_SIZE as u32) as usize;
let idx_within_block = idx % (CHUNK_SIZE as u32);
let block = &self.blocks[block_id];
let interpoled_val: u64 = block.line.eval(idx_within_block);
let block_bytes = &self.data[block.data_start_offset..];
let bitpacked_diff = block.bit_unpacker.get(idx_within_block, block_bytes);
interpoled_val.wrapping_add(bitpacked_diff)
}
fn min_value(&self) -> u64 {
// The BlockwiseLinearReader assumes a normalized vector.
0u64
}
fn max_value(&self) -> u64 {
self.normalized_header.max_value
}
fn num_vals(&self) -> u32 {
self.normalized_header.num_vals
}
}

348
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use std::marker::PhantomData;
use std::ops::{Range, RangeInclusive};
use tantivy_bitpacker::minmax;
use crate::monotonic_mapping::StrictlyMonotonicFn;
/// `Column` provides columnar access on a field.
pub trait Column<T: PartialOrd = u64>: Send + Sync {
/// Return the value associated with the given idx.
///
/// This accessor should return as fast as possible.
///
/// # Panics
///
/// May panic if `idx` is greater than the column length.
fn get_val(&self, idx: u32) -> T;
/// Fills an output buffer with the fast field values
/// associated with the `DocId` going from
/// `start` to `start + output.len()`.
///
/// # Panics
///
/// Must panic if `start + output.len()` is greater than
/// the segment's `maxdoc`.
#[inline]
fn get_range(&self, start: u64, output: &mut [T]) {
for (out, idx) in output.iter_mut().zip(start..) {
*out = self.get_val(idx as u32);
}
}
/// Get the positions of values which are in the provided value range.
///
/// Note that position == docid for single value fast fields
#[inline]
fn get_docids_for_value_range(
&self,
value_range: RangeInclusive<T>,
doc_id_range: Range<u32>,
positions: &mut Vec<u32>,
) {
let doc_id_range = doc_id_range.start..doc_id_range.end.min(self.num_vals());
for idx in doc_id_range.start..doc_id_range.end {
let val = self.get_val(idx);
if value_range.contains(&val) {
positions.push(idx);
}
}
}
/// Returns the minimum value for this fast field.
///
/// This min_value may not be exact.
/// For instance, the min value does not take in account of possible
/// deleted document. All values are however guaranteed to be higher than
/// `.min_value()`.
fn min_value(&self) -> T;
/// Returns the maximum value for this fast field.
///
/// This max_value may not be exact.
/// For instance, the max value does not take in account of possible
/// deleted document. All values are however guaranteed to be higher than
/// `.max_value()`.
fn max_value(&self) -> T;
/// The number of values in the column.
fn num_vals(&self) -> u32;
/// Returns a iterator over the data
fn iter<'a>(&'a self) -> Box<dyn Iterator<Item = T> + 'a> {
Box::new((0..self.num_vals()).map(|idx| self.get_val(idx)))
}
}
/// VecColumn provides `Column` over a slice.
pub struct VecColumn<'a, T = u64> {
values: &'a [T],
min_value: T,
max_value: T,
}
impl<'a, C: Column<T>, T: Copy + PartialOrd> Column<T> for &'a C {
fn get_val(&self, idx: u32) -> T {
(*self).get_val(idx)
}
fn min_value(&self) -> T {
(*self).min_value()
}
fn max_value(&self) -> T {
(*self).max_value()
}
fn num_vals(&self) -> u32 {
(*self).num_vals()
}
fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = T> + 'b> {
(*self).iter()
}
fn get_range(&self, start: u64, output: &mut [T]) {
(*self).get_range(start, output)
}
}
impl<'a, T: Copy + PartialOrd + Send + Sync> Column<T> for VecColumn<'a, T> {
fn get_val(&self, position: u32) -> T {
self.values[position as usize]
}
fn iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
Box::new(self.values.iter().copied())
}
fn min_value(&self) -> T {
self.min_value
}
fn max_value(&self) -> T {
self.max_value
}
fn num_vals(&self) -> u32 {
self.values.len() as u32
}
fn get_range(&self, start: u64, output: &mut [T]) {
output.copy_from_slice(&self.values[start as usize..][..output.len()])
}
}
impl<'a, T: Copy + Ord + Default, V> From<&'a V> for VecColumn<'a, T>
where V: AsRef<[T]> + ?Sized
{
fn from(values: &'a V) -> Self {
let values = values.as_ref();
let (min_value, max_value) = minmax(values.iter().copied()).unwrap_or_default();
Self {
values,
min_value,
max_value,
}
}
}
struct MonotonicMappingColumn<C, T, Input> {
from_column: C,
monotonic_mapping: T,
_phantom: PhantomData<Input>,
}
/// Creates a view of a column transformed by a strictly monotonic mapping. See
/// [`StrictlyMonotonicFn`].
///
/// E.g. apply a gcd monotonic_mapping([100, 200, 300]) == [1, 2, 3]
/// monotonic_mapping.mapping() is expected to be injective, and we should always have
/// monotonic_mapping.inverse(monotonic_mapping.mapping(el)) == el
///
/// The inverse of the mapping is required for:
/// `fn get_positions_for_value_range(&self, range: RangeInclusive<T>) -> Vec<u64> `
/// The user provides the original value range and we need to monotonic map them in the same way the
/// serialization does before calling the underlying column.
///
/// Note that when opening a codec, the monotonic_mapping should be the inverse of the mapping
/// during serialization. And therefore the monotonic_mapping_inv when opening is the same as
/// monotonic_mapping during serialization.
pub fn monotonic_map_column<C, T, Input, Output>(
from_column: C,
monotonic_mapping: T,
) -> impl Column<Output>
where
C: Column<Input>,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
Input: PartialOrd + Send + Sync + Clone,
Output: PartialOrd + Send + Sync + Clone,
{
MonotonicMappingColumn {
from_column,
monotonic_mapping,
_phantom: PhantomData,
}
}
impl<C, T, Input, Output> Column<Output> for MonotonicMappingColumn<C, T, Input>
where
C: Column<Input>,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
Input: PartialOrd + Send + Sync + Clone,
Output: PartialOrd + Send + Sync + Clone,
{
#[inline]
fn get_val(&self, idx: u32) -> Output {
let from_val = self.from_column.get_val(idx);
self.monotonic_mapping.mapping(from_val)
}
fn min_value(&self) -> Output {
let from_min_value = self.from_column.min_value();
self.monotonic_mapping.mapping(from_min_value)
}
fn max_value(&self) -> Output {
let from_max_value = self.from_column.max_value();
self.monotonic_mapping.mapping(from_max_value)
}
fn num_vals(&self) -> u32 {
self.from_column.num_vals()
}
fn iter(&self) -> Box<dyn Iterator<Item = Output> + '_> {
Box::new(
self.from_column
.iter()
.map(|el| self.monotonic_mapping.mapping(el)),
)
}
fn get_docids_for_value_range(
&self,
range: RangeInclusive<Output>,
doc_id_range: Range<u32>,
positions: &mut Vec<u32>,
) {
self.from_column.get_docids_for_value_range(
self.monotonic_mapping.inverse(range.start().clone())
..=self.monotonic_mapping.inverse(range.end().clone()),
doc_id_range,
positions,
)
}
// We voluntarily do not implement get_range as it yields a regression,
// and we do not have any specialized implementation anyway.
}
/// Wraps an iterator into a `Column`.
pub struct IterColumn<T>(T);
impl<T> From<T> for IterColumn<T>
where T: Iterator + Clone + ExactSizeIterator
{
fn from(iter: T) -> Self {
IterColumn(iter)
}
}
impl<T> Column<T::Item> for IterColumn<T>
where
T: Iterator + Clone + ExactSizeIterator + Send + Sync,
T::Item: PartialOrd,
{
fn get_val(&self, idx: u32) -> T::Item {
self.0.clone().nth(idx as usize).unwrap()
}
fn min_value(&self) -> T::Item {
self.0.clone().next().unwrap()
}
fn max_value(&self) -> T::Item {
self.0.clone().last().unwrap()
}
fn num_vals(&self) -> u32 {
self.0.len() as u32
}
fn iter(&self) -> Box<dyn Iterator<Item = T::Item> + '_> {
Box::new(self.0.clone())
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::monotonic_mapping::{
StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternalBaseval,
StrictlyMonotonicMappingToInternalGCDBaseval,
};
#[test]
fn test_monotonic_mapping() {
let vals = &[3u64, 5u64][..];
let col = VecColumn::from(vals);
let mapped = monotonic_map_column(col, StrictlyMonotonicMappingToInternalBaseval::new(2));
assert_eq!(mapped.min_value(), 1u64);
assert_eq!(mapped.max_value(), 3u64);
assert_eq!(mapped.num_vals(), 2);
assert_eq!(mapped.num_vals(), 2);
assert_eq!(mapped.get_val(0), 1);
assert_eq!(mapped.get_val(1), 3);
}
#[test]
fn test_range_as_col() {
let col = IterColumn::from(10..100);
assert_eq!(col.num_vals(), 90);
assert_eq!(col.max_value(), 99);
}
#[test]
fn test_monotonic_mapping_iter() {
let vals: Vec<u64> = (10..110u64).map(|el| el * 10).collect();
let col = VecColumn::from(&vals);
let mapped = monotonic_map_column(
col,
StrictlyMonotonicMappingInverter::from(
StrictlyMonotonicMappingToInternalGCDBaseval::new(10, 100),
),
);
let val_i64s: Vec<u64> = mapped.iter().collect();
for i in 0..100 {
assert_eq!(val_i64s[i as usize], mapped.get_val(i));
}
}
#[test]
fn test_monotonic_mapping_get_range() {
let vals: Vec<u64> = (0..100u64).map(|el| el * 10).collect();
let col = VecColumn::from(&vals);
let mapped = monotonic_map_column(
col,
StrictlyMonotonicMappingInverter::from(
StrictlyMonotonicMappingToInternalGCDBaseval::new(10, 0),
),
);
assert_eq!(mapped.min_value(), 0u64);
assert_eq!(mapped.max_value(), 9900u64);
assert_eq!(mapped.num_vals(), 100);
let val_u64s: Vec<u64> = mapped.iter().collect();
assert_eq!(val_u64s.len(), 100);
for i in 0..100 {
assert_eq!(val_u64s[i as usize], mapped.get_val(i));
assert_eq!(val_u64s[i as usize], vals[i as usize] * 10);
}
let mut buf = [0u64; 20];
mapped.get_range(7, &mut buf[..]);
assert_eq!(&val_u64s[7..][..20], &buf);
}
}

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use std::ops::RangeInclusive;
/// The range of a blank in value space.
///
/// A blank is an unoccupied space in the data.
/// Use try_into() to construct.
/// A range has to have at least length of 3. Invalid ranges will be rejected.
///
/// Ordered by range length.
#[derive(Debug, Eq, PartialEq, Clone)]
pub(crate) struct BlankRange {
blank_range: RangeInclusive<u128>,
}
impl TryFrom<RangeInclusive<u128>> for BlankRange {
type Error = &'static str;
fn try_from(range: RangeInclusive<u128>) -> Result<Self, Self::Error> {
let blank_size = range.end().saturating_sub(*range.start());
if blank_size < 2 {
Err("invalid range")
} else {
Ok(BlankRange { blank_range: range })
}
}
}
impl BlankRange {
pub(crate) fn blank_size(&self) -> u128 {
self.blank_range.end() - self.blank_range.start() + 1
}
pub(crate) fn blank_range(&self) -> RangeInclusive<u128> {
self.blank_range.clone()
}
}
impl Ord for BlankRange {
fn cmp(&self, other: &Self) -> std::cmp::Ordering {
self.blank_size().cmp(&other.blank_size())
}
}
impl PartialOrd for BlankRange {
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
Some(self.blank_size().cmp(&other.blank_size()))
}
}

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use std::collections::{BTreeSet, BinaryHeap};
use std::iter;
use std::ops::RangeInclusive;
use itertools::Itertools;
use super::blank_range::BlankRange;
use super::{CompactSpace, RangeMapping};
/// Put the blanks for the sorted values into a binary heap
fn get_blanks(values_sorted: &BTreeSet<u128>) -> BinaryHeap<BlankRange> {
let mut blanks: BinaryHeap<BlankRange> = BinaryHeap::new();
for (first, second) in values_sorted.iter().tuple_windows() {
// Correctness Overflow: the values are deduped and sorted (BTreeSet property), that means
// there's always space between two values.
let blank_range = first + 1..=second - 1;
let blank_range: Result<BlankRange, _> = blank_range.try_into();
if let Ok(blank_range) = blank_range {
blanks.push(blank_range);
}
}
blanks
}
struct BlankCollector {
blanks: Vec<BlankRange>,
staged_blanks_sum: u128,
}
impl BlankCollector {
fn new() -> Self {
Self {
blanks: vec![],
staged_blanks_sum: 0,
}
}
fn stage_blank(&mut self, blank: BlankRange) {
self.staged_blanks_sum += blank.blank_size();
self.blanks.push(blank);
}
fn drain(&mut self) -> impl Iterator<Item = BlankRange> + '_ {
self.staged_blanks_sum = 0;
self.blanks.drain(..)
}
fn staged_blanks_sum(&self) -> u128 {
self.staged_blanks_sum
}
fn num_staged_blanks(&self) -> usize {
self.blanks.len()
}
}
fn num_bits(val: u128) -> u8 {
(128u32 - val.leading_zeros()) as u8
}
/// Will collect blanks and add them to compact space if more bits are saved than cost from
/// metadata.
pub fn get_compact_space(
values_deduped_sorted: &BTreeSet<u128>,
total_num_values: u32,
cost_per_blank: usize,
) -> CompactSpace {
let mut compact_space_builder = CompactSpaceBuilder::new();
if values_deduped_sorted.is_empty() {
return compact_space_builder.finish();
}
let mut blanks: BinaryHeap<BlankRange> = get_blanks(values_deduped_sorted);
// Replace after stabilization of https://github.com/rust-lang/rust/issues/62924
// We start by space that's limited to min_value..=max_value
let min_value = *values_deduped_sorted.iter().next().unwrap_or(&0);
let max_value = *values_deduped_sorted.iter().last().unwrap_or(&0);
// +1 for null, in case min and max covers the whole space, we are off by one.
let mut amplitude_compact_space = (max_value - min_value).saturating_add(1);
if min_value != 0 {
compact_space_builder.add_blanks(iter::once(0..=min_value - 1));
}
if max_value != u128::MAX {
compact_space_builder.add_blanks(iter::once(max_value + 1..=u128::MAX));
}
let mut amplitude_bits: u8 = num_bits(amplitude_compact_space);
let mut blank_collector = BlankCollector::new();
// We will stage blanks until they reduce the compact space by at least 1 bit and then flush
// them if the metadata cost is lower than the total number of saved bits.
// Binary heap to process the gaps by their size
while let Some(blank_range) = blanks.pop() {
blank_collector.stage_blank(blank_range);
let staged_spaces_sum: u128 = blank_collector.staged_blanks_sum();
let amplitude_new_compact_space = amplitude_compact_space - staged_spaces_sum;
let amplitude_new_bits = num_bits(amplitude_new_compact_space);
if amplitude_bits == amplitude_new_bits {
continue;
}
let saved_bits = (amplitude_bits - amplitude_new_bits) as usize * total_num_values as usize;
// TODO: Maybe calculate exact cost of blanks and run this more expensive computation only,
// when amplitude_new_bits changes
let cost = blank_collector.num_staged_blanks() * cost_per_blank;
if cost >= saved_bits {
// Continue here, since although we walk over the blanks by size,
// we can potentially save a lot at the last bits, which are smaller blanks
//
// E.g. if the first range reduces the compact space by 1000 from 2000 to 1000, which
// saves 11-10=1 bit and the next range reduces the compact space by 950 to
// 50, which saves 10-6=4 bit
continue;
}
amplitude_compact_space = amplitude_new_compact_space;
amplitude_bits = amplitude_new_bits;
compact_space_builder.add_blanks(blank_collector.drain().map(|blank| blank.blank_range()));
}
// special case, when we don't collected any blanks because:
// * the data is empty (early exit)
// * the algorithm did decide it's not worth the cost, which can be the case for single values
//
// We drain one collected blank unconditionally, so the empty case is reserved for empty
// data, and therefore empty compact_space means the data is empty and no data is covered
// (conversely to all data) and we can assign null to it.
if compact_space_builder.is_empty() {
compact_space_builder.add_blanks(
blank_collector
.drain()
.map(|blank| blank.blank_range())
.take(1),
);
}
let compact_space = compact_space_builder.finish();
if max_value - min_value != u128::MAX {
debug_assert_eq!(
compact_space.amplitude_compact_space(),
amplitude_compact_space
);
}
compact_space
}
#[derive(Debug, Clone, Eq, PartialEq)]
struct CompactSpaceBuilder {
blanks: Vec<RangeInclusive<u128>>,
}
impl CompactSpaceBuilder {
/// Creates a new compact space builder which will initially cover the whole space.
fn new() -> Self {
Self { blanks: Vec::new() }
}
/// Assumes that repeated add_blank calls don't overlap and are not adjacent,
/// e.g. [3..=5, 5..=10] is not allowed
///
/// Both of those assumptions are true when blanks are produced from sorted values.
fn add_blanks(&mut self, blank: impl Iterator<Item = RangeInclusive<u128>>) {
self.blanks.extend(blank);
}
fn is_empty(&self) -> bool {
self.blanks.is_empty()
}
/// Convert blanks to covered space and assign null value
fn finish(mut self) -> CompactSpace {
// sort by start. ranges are not allowed to overlap
self.blanks.sort_unstable_by_key(|blank| *blank.start());
let mut covered_space = Vec::with_capacity(self.blanks.len());
// begining of the blanks
if let Some(first_blank_start) = self.blanks.first().map(RangeInclusive::start) {
if *first_blank_start != 0 {
covered_space.push(0..=first_blank_start - 1);
}
}
// Between the blanks
let between_blanks = self.blanks.iter().tuple_windows().map(|(left, right)| {
assert!(
left.end() < right.start(),
"overlapping or adjacent ranges detected"
);
*left.end() + 1..=*right.start() - 1
});
covered_space.extend(between_blanks);
// end of the blanks
if let Some(last_blank_end) = self.blanks.last().map(RangeInclusive::end) {
if *last_blank_end != u128::MAX {
covered_space.push(last_blank_end + 1..=u128::MAX);
}
}
if covered_space.is_empty() {
covered_space.push(0..=0); // empty data case
};
let mut compact_start: u64 = 1; // 0 is reserved for `null`
let mut ranges_mapping: Vec<RangeMapping> = Vec::with_capacity(covered_space.len());
for cov in covered_space {
let range_mapping = super::RangeMapping {
value_range: cov,
compact_start,
};
let covered_range_len = range_mapping.range_length();
ranges_mapping.push(range_mapping);
compact_start += covered_range_len as u64;
}
// println!("num ranges {}", ranges_mapping.len());
CompactSpace { ranges_mapping }
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_binary_heap_pop_order() {
let mut blanks: BinaryHeap<BlankRange> = BinaryHeap::new();
blanks.push((0..=10).try_into().unwrap());
blanks.push((100..=200).try_into().unwrap());
blanks.push((100..=110).try_into().unwrap());
assert_eq!(blanks.pop().unwrap().blank_size(), 101);
assert_eq!(blanks.pop().unwrap().blank_size(), 11);
}
}

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/// This codec takes a large number space (u128) and reduces it to a compact number space.
///
/// It will find spaces in the number range. For example:
///
/// 100, 101, 102, 103, 104, 50000, 50001
/// could be mapped to
/// 100..104 -> 0..4
/// 50000..50001 -> 5..6
///
/// Compact space 0..=6 requires much less bits than 100..=50001
///
/// The codec is created to compress ip addresses, but may be employed in other use cases.
use std::{
cmp::Ordering,
collections::BTreeSet,
io::{self, Write},
ops::{Range, RangeInclusive},
};
use common::{BinarySerializable, CountingWriter, VInt, VIntU128};
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{self, BitPacker, BitUnpacker};
use crate::compact_space::build_compact_space::get_compact_space;
use crate::Column;
mod blank_range;
mod build_compact_space;
/// The cost per blank is quite hard actually, since blanks are delta encoded, the actual cost of
/// blanks depends on the number of blanks.
///
/// The number is taken by looking at a real dataset. It is optimized for larger datasets.
const COST_PER_BLANK_IN_BITS: usize = 36;
#[derive(Debug, Clone, Eq, PartialEq)]
pub struct CompactSpace {
ranges_mapping: Vec<RangeMapping>,
}
/// Maps the range from the original space to compact_start + range.len()
#[derive(Debug, Clone, Eq, PartialEq)]
struct RangeMapping {
value_range: RangeInclusive<u128>,
compact_start: u64,
}
impl RangeMapping {
fn range_length(&self) -> u64 {
(self.value_range.end() - self.value_range.start()) as u64 + 1
}
// The last value of the compact space in this range
fn compact_end(&self) -> u64 {
self.compact_start + self.range_length() - 1
}
}
impl BinarySerializable for CompactSpace {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.ranges_mapping.len() as u64).serialize(writer)?;
let mut prev_value = 0;
for value_range in self
.ranges_mapping
.iter()
.map(|range_mapping| &range_mapping.value_range)
{
let blank_delta_start = value_range.start() - prev_value;
VIntU128(blank_delta_start).serialize(writer)?;
prev_value = *value_range.start();
let blank_delta_end = value_range.end() - prev_value;
VIntU128(blank_delta_end).serialize(writer)?;
prev_value = *value_range.end();
}
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let num_ranges = VInt::deserialize(reader)?.0;
let mut ranges_mapping: Vec<RangeMapping> = vec![];
let mut value = 0u128;
let mut compact_start = 1u64; // 0 is reserved for `null`
for _ in 0..num_ranges {
let blank_delta_start = VIntU128::deserialize(reader)?.0;
value += blank_delta_start;
let blank_start = value;
let blank_delta_end = VIntU128::deserialize(reader)?.0;
value += blank_delta_end;
let blank_end = value;
let range_mapping = RangeMapping {
value_range: blank_start..=blank_end,
compact_start,
};
let range_length = range_mapping.range_length();
ranges_mapping.push(range_mapping);
compact_start += range_length as u64;
}
Ok(Self { ranges_mapping })
}
}
impl CompactSpace {
/// Amplitude is the value range of the compact space including the sentinel value used to
/// identify null values. The compact space is 0..=amplitude .
///
/// It's only used to verify we don't exceed u64 number space, which would indicate a bug.
fn amplitude_compact_space(&self) -> u128 {
self.ranges_mapping
.last()
.map(|last_range| last_range.compact_end() as u128)
.unwrap_or(1) // compact space starts at 1, 0 == null
}
fn get_range_mapping(&self, pos: usize) -> &RangeMapping {
&self.ranges_mapping[pos]
}
/// Returns either Ok(the value in the compact space) or if it is outside the compact space the
/// Err(position where it would be inserted)
fn u128_to_compact(&self, value: u128) -> Result<u64, usize> {
self.ranges_mapping
.binary_search_by(|probe| {
let value_range = &probe.value_range;
if value < *value_range.start() {
Ordering::Greater
} else if value > *value_range.end() {
Ordering::Less
} else {
Ordering::Equal
}
})
.map(|pos| {
let range_mapping = &self.ranges_mapping[pos];
let pos_in_range = (value - range_mapping.value_range.start()) as u64;
range_mapping.compact_start + pos_in_range
})
}
/// Unpacks a value from compact space u64 to u128 space
fn compact_to_u128(&self, compact: u64) -> u128 {
let pos = self
.ranges_mapping
.binary_search_by_key(&compact, |range_mapping| range_mapping.compact_start)
// Correctness: Overflow. The first range starts at compact space 0, the error from
// binary search can never be 0
.map_or_else(|e| e - 1, |v| v);
let range_mapping = &self.ranges_mapping[pos];
let diff = compact - range_mapping.compact_start;
range_mapping.value_range.start() + diff as u128
}
}
pub struct CompactSpaceCompressor {
params: IPCodecParams,
}
#[derive(Debug, Clone)]
pub struct IPCodecParams {
compact_space: CompactSpace,
bit_unpacker: BitUnpacker,
min_value: u128,
max_value: u128,
num_vals: u32,
num_bits: u8,
}
impl CompactSpaceCompressor {
/// Taking the vals as Vec may cost a lot of memory. It is used to sort the vals.
pub fn train_from(iter: impl Iterator<Item = u128>, num_vals: u32) -> Self {
let mut values_sorted = BTreeSet::new();
values_sorted.extend(iter);
let total_num_values = num_vals;
let compact_space =
get_compact_space(&values_sorted, total_num_values, COST_PER_BLANK_IN_BITS);
let amplitude_compact_space = compact_space.amplitude_compact_space();
assert!(
amplitude_compact_space <= u64::MAX as u128,
"case unsupported."
);
let num_bits = tantivy_bitpacker::compute_num_bits(amplitude_compact_space as u64);
let min_value = *values_sorted.iter().next().unwrap_or(&0);
let max_value = *values_sorted.iter().last().unwrap_or(&0);
assert_eq!(
compact_space
.u128_to_compact(max_value)
.expect("could not convert max value to compact space"),
amplitude_compact_space as u64
);
CompactSpaceCompressor {
params: IPCodecParams {
compact_space,
bit_unpacker: BitUnpacker::new(num_bits),
min_value,
max_value,
num_vals: total_num_values,
num_bits,
},
}
}
fn write_footer(self, writer: &mut impl Write) -> io::Result<()> {
let writer = &mut CountingWriter::wrap(writer);
self.params.serialize(writer)?;
let footer_len = writer.written_bytes() as u32;
footer_len.serialize(writer)?;
Ok(())
}
pub fn compress_into(
self,
vals: impl Iterator<Item = u128>,
write: &mut impl Write,
) -> io::Result<()> {
let mut bitpacker = BitPacker::default();
for val in vals {
let compact = self
.params
.compact_space
.u128_to_compact(val)
.map_err(|_| {
io::Error::new(
io::ErrorKind::InvalidData,
"Could not convert value to compact_space. This is a bug.",
)
})?;
bitpacker.write(compact, self.params.num_bits, write)?;
}
bitpacker.close(write)?;
self.write_footer(write)?;
Ok(())
}
}
#[derive(Debug, Clone)]
pub struct CompactSpaceDecompressor {
data: OwnedBytes,
params: IPCodecParams,
}
impl BinarySerializable for IPCodecParams {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
// header flags for future optional dictionary encoding
let footer_flags = 0u64;
footer_flags.serialize(writer)?;
VIntU128(self.min_value).serialize(writer)?;
VIntU128(self.max_value).serialize(writer)?;
VIntU128(self.num_vals as u128).serialize(writer)?;
self.num_bits.serialize(writer)?;
self.compact_space.serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let _header_flags = u64::deserialize(reader)?;
let min_value = VIntU128::deserialize(reader)?.0;
let max_value = VIntU128::deserialize(reader)?.0;
let num_vals = VIntU128::deserialize(reader)?.0 as u32;
let num_bits = u8::deserialize(reader)?;
let compact_space = CompactSpace::deserialize(reader)?;
Ok(Self {
compact_space,
bit_unpacker: BitUnpacker::new(num_bits),
min_value,
max_value,
num_vals,
num_bits,
})
}
}
impl Column<u128> for CompactSpaceDecompressor {
#[inline]
fn get_val(&self, doc: u32) -> u128 {
self.get(doc)
}
fn min_value(&self) -> u128 {
self.min_value()
}
fn max_value(&self) -> u128 {
self.max_value()
}
fn num_vals(&self) -> u32 {
self.params.num_vals
}
#[inline]
fn iter(&self) -> Box<dyn Iterator<Item = u128> + '_> {
Box::new(self.iter())
}
#[inline]
fn get_docids_for_value_range(
&self,
value_range: RangeInclusive<u128>,
positions_range: Range<u32>,
positions: &mut Vec<u32>,
) {
self.get_positions_for_value_range(value_range, positions_range, positions)
}
}
impl CompactSpaceDecompressor {
pub fn open(data: OwnedBytes) -> io::Result<CompactSpaceDecompressor> {
let (data_slice, footer_len_bytes) = data.split_at(data.len() - 4);
let footer_len = u32::deserialize(&mut &footer_len_bytes[..])?;
let data_footer = &data_slice[data_slice.len() - footer_len as usize..];
let params = IPCodecParams::deserialize(&mut &data_footer[..])?;
let decompressor = CompactSpaceDecompressor { data, params };
Ok(decompressor)
}
/// Converting to compact space for the decompressor is more complex, since we may get values
/// which are outside the compact space. e.g. if we map
/// 1000 => 5
/// 2000 => 6
///
/// and we want a mapping for 1005, there is no equivalent compact space. We instead return an
/// error with the index of the next range.
fn u128_to_compact(&self, value: u128) -> Result<u64, usize> {
self.params.compact_space.u128_to_compact(value)
}
fn compact_to_u128(&self, compact: u64) -> u128 {
self.params.compact_space.compact_to_u128(compact)
}
/// Comparing on compact space: Random dataset 0,24 (50% random hit) - 1.05 GElements/s
/// Comparing on compact space: Real dataset 1.08 GElements/s
///
/// Comparing on original space: Real dataset .06 GElements/s (not completely optimized)
#[inline]
pub fn get_positions_for_value_range(
&self,
value_range: RangeInclusive<u128>,
position_range: Range<u32>,
positions: &mut Vec<u32>,
) {
if value_range.start() > value_range.end() {
return;
}
let position_range = position_range.start..position_range.end.min(self.num_vals());
let from_value = *value_range.start();
let to_value = *value_range.end();
assert!(to_value >= from_value);
let compact_from = self.u128_to_compact(from_value);
let compact_to = self.u128_to_compact(to_value);
// Quick return, if both ranges fall into the same non-mapped space, the range can't cover
// any values, so we can early exit
match (compact_to, compact_from) {
(Err(pos1), Err(pos2)) if pos1 == pos2 => return,
_ => {}
}
let compact_from = compact_from.unwrap_or_else(|pos| {
// Correctness: Out of bounds, if this value is Err(last_index + 1), we early exit,
// since the to_value also mapps into the same non-mapped space
let range_mapping = self.params.compact_space.get_range_mapping(pos);
range_mapping.compact_start
});
// If there is no compact space, we go to the closest upperbound compact space
let compact_to = compact_to.unwrap_or_else(|pos| {
// Correctness: Overflow, if this value is Err(0), we early exit,
// since the from_value also mapps into the same non-mapped space
// Get end of previous range
let pos = pos - 1;
let range_mapping = self.params.compact_space.get_range_mapping(pos);
range_mapping.compact_end()
});
let range = compact_from..=compact_to;
let scan_num_docs = position_range.end - position_range.start;
let step_size = 4;
let cutoff = position_range.start + scan_num_docs - scan_num_docs % step_size;
let mut push_if_in_range = |idx, val| {
if range.contains(&val) {
positions.push(idx);
}
};
let get_val = |idx| self.params.bit_unpacker.get(idx, &self.data);
// unrolled loop
for idx in (position_range.start..cutoff).step_by(step_size as usize) {
let idx1 = idx;
let idx2 = idx + 1;
let idx3 = idx + 2;
let idx4 = idx + 3;
let val1 = get_val(idx1 as u32);
let val2 = get_val(idx2 as u32);
let val3 = get_val(idx3 as u32);
let val4 = get_val(idx4 as u32);
push_if_in_range(idx1, val1);
push_if_in_range(idx2, val2);
push_if_in_range(idx3, val3);
push_if_in_range(idx4, val4);
}
// handle rest
for idx in cutoff..position_range.end {
push_if_in_range(idx, get_val(idx as u32));
}
}
#[inline]
fn iter_compact(&self) -> impl Iterator<Item = u64> + '_ {
(0..self.params.num_vals)
.map(move |idx| self.params.bit_unpacker.get(idx, &self.data) as u64)
}
#[inline]
fn iter(&self) -> impl Iterator<Item = u128> + '_ {
// TODO: Performance. It would be better to iterate on the ranges and check existence via
// the bit_unpacker.
self.iter_compact()
.map(|compact| self.compact_to_u128(compact))
}
#[inline]
pub fn get(&self, idx: u32) -> u128 {
let compact = self.params.bit_unpacker.get(idx, &self.data);
self.compact_to_u128(compact)
}
pub fn min_value(&self) -> u128 {
self.params.min_value
}
pub fn max_value(&self) -> u128 {
self.params.max_value
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::serialize::U128Header;
use crate::{open_u128, serialize_u128};
#[test]
fn compact_space_test() {
let ips = &[
2u128, 4u128, 1000, 1001, 1002, 1003, 1004, 1005, 1008, 1010, 1012, 1260,
]
.into_iter()
.collect();
let compact_space = get_compact_space(ips, ips.len() as u32, 11);
let amplitude = compact_space.amplitude_compact_space();
assert_eq!(amplitude, 17);
assert_eq!(1, compact_space.u128_to_compact(2).unwrap());
assert_eq!(2, compact_space.u128_to_compact(3).unwrap());
assert_eq!(compact_space.u128_to_compact(100).unwrap_err(), 1);
for (num1, num2) in (0..3).tuple_windows() {
assert_eq!(
compact_space.get_range_mapping(num1).compact_end() + 1,
compact_space.get_range_mapping(num2).compact_start
);
}
let mut output: Vec<u8> = Vec::new();
compact_space.serialize(&mut output).unwrap();
assert_eq!(
compact_space,
CompactSpace::deserialize(&mut &output[..]).unwrap()
);
for ip in ips {
let compact = compact_space.u128_to_compact(*ip).unwrap();
assert_eq!(compact_space.compact_to_u128(compact), *ip);
}
}
#[test]
fn compact_space_amplitude_test() {
let ips = &[100000u128, 1000000].into_iter().collect();
let compact_space = get_compact_space(ips, ips.len() as u32, 1);
let amplitude = compact_space.amplitude_compact_space();
assert_eq!(amplitude, 2);
}
fn test_all(mut data: OwnedBytes, expected: &[u128]) {
let _header = U128Header::deserialize(&mut data);
let decompressor = CompactSpaceDecompressor::open(data).unwrap();
for (idx, expected_val) in expected.iter().cloned().enumerate() {
let val = decompressor.get(idx as u32);
assert_eq!(val, expected_val);
let test_range = |range: RangeInclusive<u128>| {
let expected_positions = expected
.iter()
.positions(|val| range.contains(val))
.map(|pos| pos as u32)
.collect::<Vec<_>>();
let mut positions = Vec::new();
decompressor.get_positions_for_value_range(
range,
0..decompressor.num_vals(),
&mut positions,
);
assert_eq!(positions, expected_positions);
};
test_range(expected_val.saturating_sub(1)..=expected_val);
test_range(expected_val..=expected_val);
test_range(expected_val..=expected_val.saturating_add(1));
test_range(expected_val.saturating_sub(1)..=expected_val.saturating_add(1));
}
}
fn test_aux_vals(u128_vals: &[u128]) -> OwnedBytes {
let mut out = Vec::new();
serialize_u128(
|| u128_vals.iter().cloned(),
u128_vals.len() as u32,
&mut out,
)
.unwrap();
let data = OwnedBytes::new(out);
test_all(data.clone(), u128_vals);
data
}
#[test]
fn test_range_1() {
let vals = &[
1u128,
100u128,
3u128,
99999u128,
100000u128,
100001u128,
4_000_211_221u128,
4_000_211_222u128,
333u128,
];
let mut data = test_aux_vals(vals);
let _header = U128Header::deserialize(&mut data);
let decomp = CompactSpaceDecompressor::open(data).unwrap();
let complete_range = 0..vals.len() as u32;
for (pos, val) in vals.iter().enumerate() {
let val = *val as u128;
let pos = pos as u32;
let mut positions = Vec::new();
decomp.get_positions_for_value_range(val..=val, pos..pos + 1, &mut positions);
assert_eq!(positions, vec![pos]);
}
// handle docid range out of bounds
let positions = get_positions_for_value_range_helper(&decomp, 0..=1, 1..u32::MAX);
assert_eq!(positions, vec![]);
let positions =
get_positions_for_value_range_helper(&decomp, 0..=1, complete_range.clone());
assert_eq!(positions, vec![0]);
let positions =
get_positions_for_value_range_helper(&decomp, 0..=2, complete_range.clone());
assert_eq!(positions, vec![0]);
let positions =
get_positions_for_value_range_helper(&decomp, 0..=3, complete_range.clone());
assert_eq!(positions, vec![0, 2]);
assert_eq!(
get_positions_for_value_range_helper(
&decomp,
99999u128..=99999u128,
complete_range.clone()
),
vec![3]
);
assert_eq!(
get_positions_for_value_range_helper(
&decomp,
99999u128..=100000u128,
complete_range.clone()
),
vec![3, 4]
);
assert_eq!(
get_positions_for_value_range_helper(
&decomp,
99998u128..=100000u128,
complete_range.clone()
),
vec![3, 4]
);
assert_eq!(
get_positions_for_value_range_helper(
&decomp,
99998u128..=99999u128,
complete_range.clone()
),
vec![3]
);
assert_eq!(
get_positions_for_value_range_helper(
&decomp,
99998u128..=99998u128,
complete_range.clone()
),
vec![]
);
assert_eq!(
get_positions_for_value_range_helper(
&decomp,
333u128..=333u128,
complete_range.clone()
),
vec![8]
);
assert_eq!(
get_positions_for_value_range_helper(
&decomp,
332u128..=333u128,
complete_range.clone()
),
vec![8]
);
assert_eq!(
get_positions_for_value_range_helper(
&decomp,
332u128..=334u128,
complete_range.clone()
),
vec![8]
);
assert_eq!(
get_positions_for_value_range_helper(
&decomp,
333u128..=334u128,
complete_range.clone()
),
vec![8]
);
assert_eq!(
get_positions_for_value_range_helper(
&decomp,
4_000_211_221u128..=5_000_000_000u128,
complete_range.clone()
),
vec![6, 7]
);
}
#[test]
fn test_empty() {
let vals = &[];
let data = test_aux_vals(vals);
let _decomp = CompactSpaceDecompressor::open(data).unwrap();
}
#[test]
fn test_range_2() {
let vals = &[
100u128,
99999u128,
100000u128,
100001u128,
4_000_211_221u128,
4_000_211_222u128,
333u128,
];
let mut data = test_aux_vals(vals);
let _header = U128Header::deserialize(&mut data);
let decomp = CompactSpaceDecompressor::open(data).unwrap();
let complete_range = 0..vals.len() as u32;
assert_eq!(
get_positions_for_value_range_helper(&decomp, 0..=5, complete_range.clone()),
vec![]
);
assert_eq!(
get_positions_for_value_range_helper(&decomp, 0..=100, complete_range.clone()),
vec![0]
);
assert_eq!(
get_positions_for_value_range_helper(&decomp, 0..=105, complete_range.clone()),
vec![0]
);
}
fn get_positions_for_value_range_helper<C: Column<T> + ?Sized, T: PartialOrd>(
column: &C,
value_range: RangeInclusive<T>,
doc_id_range: Range<u32>,
) -> Vec<u32> {
let mut positions = Vec::new();
column.get_docids_for_value_range(value_range, doc_id_range, &mut positions);
positions
}
#[test]
fn test_range_3() {
let vals = &[
200u128,
201,
202,
203,
204,
204,
206,
207,
208,
209,
210,
1_000_000,
5_000_000_000,
];
let mut out = Vec::new();
serialize_u128(|| vals.iter().cloned(), vals.len() as u32, &mut out).unwrap();
let decomp = open_u128::<u128>(OwnedBytes::new(out))
.unwrap()
.to_full()
.unwrap();
let complete_range = 0..vals.len() as u32;
assert_eq!(
get_positions_for_value_range_helper(&*decomp, 199..=200, complete_range.clone()),
vec![0]
);
assert_eq!(
get_positions_for_value_range_helper(&*decomp, 199..=201, complete_range.clone()),
vec![0, 1]
);
assert_eq!(
get_positions_for_value_range_helper(&*decomp, 200..=200, complete_range.clone()),
vec![0]
);
assert_eq!(
get_positions_for_value_range_helper(
&*decomp,
1_000_000..=1_000_000,
complete_range.clone()
),
vec![11]
);
}
#[test]
fn test_bug1() {
let vals = &[9223372036854775806];
let _data = test_aux_vals(vals);
}
#[test]
fn test_bug2() {
let vals = &[340282366920938463463374607431768211455u128];
let _data = test_aux_vals(vals);
}
#[test]
fn test_bug3() {
let vals = &[340282366920938463463374607431768211454];
let _data = test_aux_vals(vals);
}
#[test]
fn test_bug4() {
let vals = &[340282366920938463463374607431768211455, 0];
let _data = test_aux_vals(vals);
}
#[test]
fn test_first_large_gaps() {
let vals = &[1_000_000_000u128; 100];
let _data = test_aux_vals(vals);
}
use itertools::Itertools;
use proptest::prelude::*;
fn num_strategy() -> impl Strategy<Value = u128> {
prop_oneof![
1 => prop::num::u128::ANY.prop_map(|num| u128::MAX - (num % 10) ),
1 => prop::num::u128::ANY.prop_map(|num| i64::MAX as u128 + 5 - (num % 10) ),
1 => prop::num::u128::ANY.prop_map(|num| i128::MAX as u128 + 5 - (num % 10) ),
1 => prop::num::u128::ANY.prop_map(|num| num % 10 ),
20 => prop::num::u128::ANY,
]
}
proptest! {
#![proptest_config(ProptestConfig::with_cases(10))]
#[test]
fn compress_decompress_random(vals in proptest::collection::vec(num_strategy()
, 1..1000)) {
let _data = test_aux_vals(&vals);
}
}
}

170
fastfield_codecs/src/gcd.rs Normal file
View File

@@ -0,0 +1,170 @@
use std::num::NonZeroU64;
use fastdivide::DividerU64;
/// Compute the gcd of two non null numbers.
///
/// It is recommended, but not required, to feed values such that `large >= small`.
fn compute_gcd(mut large: NonZeroU64, mut small: NonZeroU64) -> NonZeroU64 {
loop {
let rem: u64 = large.get() % small;
if let Some(new_small) = NonZeroU64::new(rem) {
(large, small) = (small, new_small);
} else {
return small;
}
}
}
// Find GCD for iterator of numbers
pub fn find_gcd(numbers: impl Iterator<Item = u64>) -> Option<NonZeroU64> {
let mut numbers = numbers.flat_map(NonZeroU64::new);
let mut gcd: NonZeroU64 = numbers.next()?;
if gcd.get() == 1 {
return Some(gcd);
}
let mut gcd_divider = DividerU64::divide_by(gcd.get());
for val in numbers {
let remainder = val.get() - (gcd_divider.divide(val.get())) * gcd.get();
if remainder == 0 {
continue;
}
gcd = compute_gcd(val, gcd);
if gcd.get() == 1 {
return Some(gcd);
}
gcd_divider = DividerU64::divide_by(gcd.get());
}
Some(gcd)
}
#[cfg(test)]
mod tests {
use std::io;
use std::num::NonZeroU64;
use ownedbytes::OwnedBytes;
use crate::gcd::{compute_gcd, find_gcd};
use crate::{FastFieldCodecType, VecColumn};
fn test_fastfield_gcd_i64_with_codec(
codec_type: FastFieldCodecType,
num_vals: usize,
) -> io::Result<()> {
let mut vals: Vec<i64> = (-4..=(num_vals as i64) - 5).map(|val| val * 1000).collect();
let mut buffer: Vec<u8> = Vec::new();
crate::serialize(VecColumn::from(&vals), &mut buffer, &[codec_type])?;
let buffer = OwnedBytes::new(buffer);
let column = crate::open::<i64>(buffer.clone())?;
assert_eq!(column.get_val(0), Some(-4000i64));
assert_eq!(column.get_val(1), Some(-3000i64));
assert_eq!(column.get_val(2), Some(-2000i64));
assert_eq!(column.max_value(), Some((num_vals as i64 - 5) * 1000));
assert_eq!(column.min_value(), Some(-4000i64));
// Can't apply gcd
let mut buffer_without_gcd = Vec::new();
vals.pop();
vals.push(1001i64);
crate::serialize(
VecColumn::from(&vals),
&mut buffer_without_gcd,
&[codec_type],
)?;
let buffer_without_gcd = OwnedBytes::new(buffer_without_gcd);
assert!(buffer_without_gcd.len() > buffer.len());
Ok(())
}
#[test]
fn test_fastfield_gcd_i64() -> io::Result<()> {
for &codec_type in &[
FastFieldCodecType::Bitpacked,
FastFieldCodecType::BlockwiseLinear,
FastFieldCodecType::Linear,
] {
test_fastfield_gcd_i64_with_codec(codec_type, 5500)?;
}
Ok(())
}
fn test_fastfield_gcd_u64_with_codec(
codec_type: FastFieldCodecType,
num_vals: usize,
) -> io::Result<()> {
let mut vals: Vec<u64> = (1..=num_vals).map(|i| i as u64 * 1000u64).collect();
let mut buffer: Vec<u8> = Vec::new();
crate::serialize(VecColumn::from(&vals), &mut buffer, &[codec_type])?;
let buffer = OwnedBytes::new(buffer);
let column = crate::open::<u64>(buffer.clone())?;
assert_eq!(column.get_val(0), Some(1000u64));
assert_eq!(column.get_val(1), Some(2000u64));
assert_eq!(column.get_val(2), Some(3000u64));
assert_eq!(column.max_value(), Some(num_vals as u64 * 1000));
assert_eq!(column.min_value(), Some(1000u64));
// Can't apply gcd
let mut buffer_without_gcd = Vec::new();
vals.pop();
vals.push(1001u64);
crate::serialize(
VecColumn::from(&vals),
&mut buffer_without_gcd,
&[codec_type],
)?;
let buffer_without_gcd = OwnedBytes::new(buffer_without_gcd);
assert!(buffer_without_gcd.len() > buffer.len());
Ok(())
}
#[test]
fn test_fastfield_gcd_u64() -> io::Result<()> {
for &codec_type in &[
FastFieldCodecType::Bitpacked,
FastFieldCodecType::BlockwiseLinear,
FastFieldCodecType::Linear,
] {
test_fastfield_gcd_u64_with_codec(codec_type, 5500)?;
}
Ok(())
}
#[test]
pub fn test_fastfield2() {
let test_fastfield = crate::serialize_and_load(&[100u64, 200u64, 300u64]);
assert_eq!(test_fastfield.get_val(0), 100);
assert_eq!(test_fastfield.get_val(1), 200);
assert_eq!(test_fastfield.get_val(2), 300);
}
#[test]
fn test_compute_gcd() {
let test_compute_gcd_aux = |large, small, expected| {
let large = NonZeroU64::new(large).unwrap();
let small = NonZeroU64::new(small).unwrap();
let expected = NonZeroU64::new(expected).unwrap();
assert_eq!(compute_gcd(small, large), expected);
assert_eq!(compute_gcd(large, small), expected);
};
test_compute_gcd_aux(1, 4, 1);
test_compute_gcd_aux(2, 4, 2);
test_compute_gcd_aux(10, 25, 5);
test_compute_gcd_aux(25, 25, 25);
}
#[test]
fn find_gcd_test() {
assert_eq!(find_gcd([0].into_iter()), None);
assert_eq!(find_gcd([0, 10].into_iter()), NonZeroU64::new(10));
assert_eq!(find_gcd([10, 0].into_iter()), NonZeroU64::new(10));
assert_eq!(find_gcd([].into_iter()), None);
assert_eq!(find_gcd([15, 30, 5, 10].into_iter()), NonZeroU64::new(5));
assert_eq!(find_gcd([15, 16, 10].into_iter()), NonZeroU64::new(1));
assert_eq!(find_gcd([0, 5, 5, 5].into_iter()), NonZeroU64::new(5));
assert_eq!(find_gcd([0, 0].into_iter()), None);
}
}

572
fastfield_codecs/src/lib.rs
View File

@@ -1,32 +1,70 @@
#![warn(missing_docs)]
#![cfg_attr(all(feature = "unstable", test), feature(test))]
//! # `fastfield_codecs`
//!
//! - Columnar storage of data for tantivy [`Column`].
//! - Encode data in different codecs.
//! - Monotonically map values to u64/u128
#[cfg(test)]
#[macro_use]
extern crate more_asserts;
#[cfg(all(test, feature = "unstable"))]
extern crate test;
use std::io;
use std::io::Write;
use std::sync::Arc;
use common::BinarySerializable;
use compact_space::CompactSpaceDecompressor;
use monotonic_mapping::{
StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternal,
StrictlyMonotonicMappingToInternalBaseval, StrictlyMonotonicMappingToInternalGCDBaseval,
};
pub use optional_column::OptionalColumn;
use optional_column::ToOptionalColumn;
use ownedbytes::OwnedBytes;
use serialize::{Header, U128Header};
pub mod bitpacked;
pub mod blockwise_linear;
pub mod linear;
mod bitpacked;
mod blockwise_linear;
mod compact_space;
mod line;
mod linear;
mod monotonic_mapping;
mod monotonic_mapping_u128;
mod optional_column;
pub trait FastFieldCodecReader: Sized {
/// reads the metadata and returns the CodecReader
fn open_from_bytes(bytes: OwnedBytes) -> std::io::Result<Self>;
fn get_u64(&self, doc: u64) -> u64;
fn min_value(&self) -> u64;
fn max_value(&self) -> u64;
}
mod column;
mod gcd;
mod serialize;
use self::bitpacked::BitpackedCodec;
use self::blockwise_linear::BlockwiseLinearCodec;
pub use self::column::{monotonic_map_column, Column, IterColumn, VecColumn};
use self::linear::LinearCodec;
pub use self::monotonic_mapping::{MonotonicallyMappableToU64, StrictlyMonotonicFn};
pub use self::monotonic_mapping_u128::MonotonicallyMappableToU128;
pub use self::serialize::{
estimate, serialize, serialize_and_load, serialize_u128, NormalizedHeader,
};
#[derive(PartialEq, Eq, PartialOrd, Ord, Debug, Clone, Copy)]
#[repr(u8)]
/// Available codecs to use to encode the u64 (via [`MonotonicallyMappableToU64`]) converted data.
pub enum FastFieldCodecType {
/// Bitpack all values in the value range. The number of bits is defined by the amplitude
/// `column.max_value() - column.min_value()`
Bitpacked = 1,
/// Linear interpolation puts a line between the first and last value and then bitpacks the
/// values by the offset from the line. The number of bits is defined by the max deviation from
/// the line.
Linear = 2,
/// Same as [`FastFieldCodecType::Linear`], but encodes in blocks of 512 elements.
BlockwiseLinear = 3,
Gcd = 4,
}
impl BinarySerializable for FastFieldCodecType {
@@ -43,179 +81,251 @@ impl BinarySerializable for FastFieldCodecType {
}
impl FastFieldCodecType {
pub fn to_code(self) -> u8 {
pub(crate) fn to_code(self) -> u8 {
self as u8
}
pub fn from_code(code: u8) -> Option<Self> {
pub(crate) fn from_code(code: u8) -> Option<Self> {
match code {
1 => Some(Self::Bitpacked),
2 => Some(Self::Linear),
3 => Some(Self::BlockwiseLinear),
4 => Some(Self::Gcd),
_ => None,
}
}
}
#[derive(PartialEq, Eq, PartialOrd, Ord, Debug, Clone, Copy)]
#[repr(u8)]
/// Available codecs to use to encode the u128 (via [`MonotonicallyMappableToU128`]) converted data.
pub enum U128FastFieldCodecType {
/// This codec takes a large number space (u128) and reduces it to a compact number space, by
/// removing the holes.
CompactSpace = 1,
}
impl BinarySerializable for U128FastFieldCodecType {
fn serialize<W: Write>(&self, wrt: &mut W) -> io::Result<()> {
self.to_code().serialize(wrt)
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let code = u8::deserialize(reader)?;
let codec_type: Self = Self::from_code(code)
.ok_or_else(|| io::Error::new(io::ErrorKind::InvalidData, "Unknown code `{code}.`"))?;
Ok(codec_type)
}
}
impl U128FastFieldCodecType {
pub(crate) fn to_code(self) -> u8 {
self as u8
}
pub(crate) fn from_code(code: u8) -> Option<Self> {
match code {
1 => Some(Self::CompactSpace),
_ => None,
}
}
}
/// Returns the correct codec reader wrapped in the `Arc` for the data.
pub fn open_u128<Item: MonotonicallyMappableToU128>(
mut bytes: OwnedBytes,
) -> io::Result<Arc<dyn OptionalColumn<Item>>> {
let header = U128Header::deserialize(&mut bytes)?;
assert_eq!(header.codec_type, U128FastFieldCodecType::CompactSpace);
let reader = CompactSpaceDecompressor::open(bytes)?;
let inverted: StrictlyMonotonicMappingInverter<StrictlyMonotonicMappingToInternal<Item>> =
StrictlyMonotonicMappingToInternal::<Item>::new().into();
Ok(Arc::new(ToOptionalColumn::new(Arc::new(
monotonic_map_column(reader, inverted),
))))
}
/// Returns the correct codec reader wrapped in the `Arc` for the data.
pub fn open<T: MonotonicallyMappableToU64>(
mut bytes: OwnedBytes,
) -> io::Result<Arc<dyn OptionalColumn<T>>> {
let header = Header::deserialize(&mut bytes)?;
match header.codec_type {
FastFieldCodecType::Bitpacked => open_specific_codec::<BitpackedCodec, _>(bytes, &header),
FastFieldCodecType::Linear => open_specific_codec::<LinearCodec, _>(bytes, &header),
FastFieldCodecType::BlockwiseLinear => {
open_specific_codec::<BlockwiseLinearCodec, _>(bytes, &header)
}
}
}
fn open_specific_codec<C: FastFieldCodec, Item: MonotonicallyMappableToU64>(
bytes: OwnedBytes,
header: &Header,
) -> io::Result<Arc<dyn OptionalColumn<Item>>> {
let normalized_header = header.normalized();
let reader = C::open_from_bytes(bytes, normalized_header)?;
let min_value = header.min_value;
if let Some(gcd) = header.gcd {
let mapping = StrictlyMonotonicMappingInverter::from(
StrictlyMonotonicMappingToInternalGCDBaseval::new(gcd.get(), min_value),
);
Ok(Arc::new(ToOptionalColumn::new(Arc::new(
monotonic_map_column(reader, mapping),
))))
} else {
let mapping = StrictlyMonotonicMappingInverter::from(
StrictlyMonotonicMappingToInternalBaseval::new(min_value),
);
Ok(Arc::new(ToOptionalColumn::new(Arc::new(
monotonic_map_column(reader, mapping),
))))
}
}
/// The FastFieldSerializerEstimate trait is required on all variants
/// of fast field compressions, to decide which one to choose.
pub trait FastFieldCodecSerializer {
trait FastFieldCodec: 'static {
/// A codex needs to provide a unique name and id, which is
/// used for debugging and de/serialization.
const CODEC_TYPE: FastFieldCodecType;
/// Check if the Codec is able to compress the data
fn is_applicable(fastfield_accessor: &impl FastFieldDataAccess) -> bool;
type Reader: Column<u64> + 'static;
/// Reads the metadata and returns the CodecReader
fn open_from_bytes(bytes: OwnedBytes, header: NormalizedHeader) -> io::Result<Self::Reader>;
/// Serializes the data using the serializer into write.
///
/// The column iterator should be preferred over using column `get_val` method for
/// performance reasons.
fn serialize(column: &dyn Column, write: &mut impl Write) -> io::Result<()>;
/// Returns an estimate of the compression ratio.
/// If the codec is not applicable, returns `None`.
///
/// The baseline is uncompressed 64bit data.
///
/// It could make sense to also return a value representing
/// computational complexity.
fn estimate(fastfield_accessor: &impl FastFieldDataAccess) -> f32;
/// Serializes the data using the serializer into write.
///
/// The fastfield_accessor iterator should be preferred over using fastfield_accessor for
/// performance reasons.
fn serialize(
write: &mut impl Write,
fastfield_accessor: &dyn FastFieldDataAccess,
) -> io::Result<()>;
fn estimate(column: &dyn Column) -> Option<f32>;
}
/// FastFieldDataAccess is the trait to access fast field data during serialization and estimation.
pub trait FastFieldDataAccess {
/// Return the value associated to the given position.
///
/// Whenever possible use the Iterator passed to the fastfield creation instead, for performance
/// reasons.
///
/// # Panics
///
/// May panic if `position` is greater than the index.
fn get_val(&self, position: u64) -> u64;
/// Returns a iterator over the data
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_>;
/// min value of the data
fn min_value(&self) -> u64;
/// max value of the data
fn max_value(&self) -> u64;
/// num vals
fn num_vals(&self) -> u64;
}
#[derive(Debug, Clone)]
/// Statistics are used in codec detection and stored in the fast field footer.
pub struct FastFieldStats {
pub min_value: u64,
pub max_value: u64,
pub num_vals: u64,
}
impl<'a> FastFieldDataAccess for &'a [u64] {
fn get_val(&self, position: u64) -> u64 {
self[position as usize]
}
fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = u64> + 'b> {
Box::new((self as &[u64]).iter().cloned())
}
fn min_value(&self) -> u64 {
self.iter().min().unwrap_or(0)
}
fn max_value(&self) -> u64 {
self.iter().max().unwrap_or(0)
}
fn num_vals(&self) -> u64 {
self.len() as u64
}
}
impl FastFieldDataAccess for Vec<u64> {
fn get_val(&self, position: u64) -> u64 {
self[position as usize]
}
fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = u64> + 'b> {
Box::new((self as &[u64]).iter().cloned())
}
fn min_value(&self) -> u64 {
self.iter().min().unwrap_or(0)
}
fn max_value(&self) -> u64 {
self.iter().max().unwrap_or(0)
}
fn num_vals(&self) -> u64 {
self.len() as u64
}
}
/// The list of all available codecs for u64 convertible data.
pub const ALL_CODEC_TYPES: [FastFieldCodecType; 3] = [
FastFieldCodecType::Bitpacked,
FastFieldCodecType::BlockwiseLinear,
FastFieldCodecType::Linear,
];
#[cfg(test)]
mod tests {
use proptest::arbitrary::any;
use proptest::proptest;
use crate::bitpacked::{BitpackedReader, BitpackedSerializer};
use crate::blockwise_linear::{BlockwiseLinearReader, BlockwiseLinearSerializer};
use crate::linear::{LinearReader, LinearSerializer};
use proptest::prelude::*;
use proptest::strategy::Strategy;
use proptest::{prop_oneof, proptest};
pub fn create_and_validate<S: FastFieldCodecSerializer, R: FastFieldCodecReader>(
use crate::bitpacked::BitpackedCodec;
use crate::blockwise_linear::BlockwiseLinearCodec;
use crate::linear::LinearCodec;
use crate::serialize::Header;
pub(crate) fn create_and_validate<Codec: FastFieldCodec>(
data: &[u64],
name: &str,
) -> (f32, f32) {
if !S::is_applicable(&data) {
return (f32::MAX, 0.0);
}
let estimation = S::estimate(&data);
let mut out: Vec<u8> = Vec::new();
S::serialize(&mut out, &data).unwrap();
) -> Option<(f32, f32)> {
let col = &VecColumn::from(data);
let header = Header::compute_header(col, &[Codec::CODEC_TYPE])?;
let normalized_col = header.normalize_column(col);
let estimation = Codec::estimate(&normalized_col)?;
let mut out = Vec::new();
let col = VecColumn::from(data);
serialize(col, &mut out, &[Codec::CODEC_TYPE]).unwrap();
let actual_compression = out.len() as f32 / (data.len() as f32 * 8.0);
let reader = R::open_from_bytes(OwnedBytes::new(out)).unwrap();
for (doc, orig_val) in data.iter().enumerate() {
let val = reader.get_u64(doc as u64);
if val != *orig_val {
panic!(
"val {val:?} does not match orig_val {orig_val:?}, in data set {name}, data \
{data:?}",
);
}
let reader = crate::open::<u64>(OwnedBytes::new(out)).unwrap();
assert_eq!(reader.num_vals(), data.len() as u32);
for (doc, orig_val) in data.iter().copied().enumerate() {
let val = reader.get_val(doc as u32);
assert_eq!(
val,
Some(orig_val),
"val `{val:?}` does not match orig_val {orig_val:?}, in data set {name}, data \
`{data:?}`",
);
}
(estimation, actual_compression)
if !data.is_empty() {
let test_rand_idx = rand::thread_rng().gen_range(0..=data.len() - 1);
let expected_positions: Vec<u32> = data
.iter()
.enumerate()
.filter(|(_, el)| **el == data[test_rand_idx])
.map(|(pos, _)| pos as u32)
.collect();
let mut positions = Vec::new();
reader.get_docids_for_value_range(
data[test_rand_idx]..=data[test_rand_idx],
0..data.len() as u32,
&mut positions,
);
assert_eq!(expected_positions, positions);
}
Some((estimation, actual_compression))
}
proptest! {
#![proptest_config(ProptestConfig::with_cases(100))]
#[test]
fn test_proptest_small(data in proptest::collection::vec(any::<u64>(), 1..10)) {
create_and_validate::<LinearSerializer, LinearReader>(&data, "proptest linearinterpol");
create_and_validate::<BlockwiseLinearSerializer, BlockwiseLinearReader>(&data, "proptest multilinearinterpol");
create_and_validate::<BitpackedSerializer, BitpackedReader>(&data, "proptest bitpacked");
fn test_proptest_small_bitpacked(data in proptest::collection::vec(num_strategy(), 1..10)) {
create_and_validate::<BitpackedCodec>(&data, "proptest bitpacked");
}
#[test]
fn test_proptest_large(data in proptest::collection::vec(any::<u64>(), 1..6000)) {
create_and_validate::<LinearSerializer, LinearReader>(&data, "proptest linearinterpol");
create_and_validate::<BlockwiseLinearSerializer, BlockwiseLinearReader>(&data, "proptest multilinearinterpol");
create_and_validate::<BitpackedSerializer, BitpackedReader>(&data, "proptest bitpacked");
fn test_proptest_small_linear(data in proptest::collection::vec(num_strategy(), 1..10)) {
create_and_validate::<LinearCodec>(&data, "proptest linearinterpol");
}
#[test]
fn test_proptest_small_blockwise_linear(data in proptest::collection::vec(num_strategy(), 1..10)) {
create_and_validate::<BlockwiseLinearCodec>(&data, "proptest multilinearinterpol");
}
}
pub fn get_codec_test_data_sets() -> Vec<(Vec<u64>, &'static str)> {
proptest! {
#![proptest_config(ProptestConfig::with_cases(10))]
#[test]
fn test_proptest_large_bitpacked(data in proptest::collection::vec(num_strategy(), 1..6000)) {
create_and_validate::<BitpackedCodec>(&data, "proptest bitpacked");
}
#[test]
fn test_proptest_large_linear(data in proptest::collection::vec(num_strategy(), 1..6000)) {
create_and_validate::<LinearCodec>(&data, "proptest linearinterpol");
}
#[test]
fn test_proptest_large_blockwise_linear(data in proptest::collection::vec(num_strategy(), 1..6000)) {
create_and_validate::<BlockwiseLinearCodec>(&data, "proptest multilinearinterpol");
}
}
fn num_strategy() -> impl Strategy<Value = u64> {
prop_oneof![
1 => prop::num::u64::ANY.prop_map(|num| u64::MAX - (num % 10) ),
1 => prop::num::u64::ANY.prop_map(|num| num % 10 ),
20 => prop::num::u64::ANY,
]
}
pub fn get_codec_test_datasets() -> Vec<(Vec<u64>, &'static str)> {
let mut data_and_names = vec![];
let data = (10..=20_u64).collect::<Vec<_>>();
let data = (10..=10_000_u64).collect::<Vec<_>>();
data_and_names.push((data, "simple monotonically increasing"));
data_and_names.push((
@@ -225,32 +335,38 @@ mod tests {
data_and_names.push((vec![5, 50, 3, 13, 1, 1000, 35], "rand small"));
data_and_names.push((vec![10], "single value"));
data_and_names.push((
vec![1572656989877777, 1170935903116329, 720575940379279, 0],
"overflow error",
));
data_and_names
}
fn test_codec<S: FastFieldCodecSerializer, R: FastFieldCodecReader>() {
let codec_name = format!("{:?}", S::CODEC_TYPE);
for (data, dataset_name) in get_codec_test_data_sets() {
let (estimate, actual) = crate::tests::create_and_validate::<S, R>(&data, dataset_name);
let result = if estimate == f32::MAX {
"Disabled".to_string()
} else {
fn test_codec<C: FastFieldCodec>() {
let codec_name = format!("{:?}", C::CODEC_TYPE);
for (data, dataset_name) in get_codec_test_datasets() {
let estimate_actual_opt: Option<(f32, f32)> =
crate::tests::create_and_validate::<C>(&data, dataset_name);
let result = if let Some((estimate, actual)) = estimate_actual_opt {
format!("Estimate `{estimate}` Actual `{actual}`")
} else {
"Disabled".to_string()
};
println!("Codec {codec_name}, DataSet {dataset_name}, {result}");
}
}
#[test]
fn test_codec_bitpacking() {
test_codec::<BitpackedSerializer, BitpackedReader>();
test_codec::<BitpackedCodec>();
}
#[test]
fn test_codec_interpolation() {
test_codec::<LinearSerializer, LinearReader>();
test_codec::<LinearCodec>();
}
#[test]
fn test_codec_multi_interpolation() {
test_codec::<BlockwiseLinearSerializer, BlockwiseLinearReader>();
test_codec::<BlockwiseLinearCodec>();
}
use super::*;
@@ -258,38 +374,50 @@ mod tests {
#[test]
fn estimation_good_interpolation_case() {
let data = (10..=20000_u64).collect::<Vec<_>>();
let data: VecColumn = data.as_slice().into();
let linear_interpol_estimation = LinearSerializer::estimate(&data);
let linear_interpol_estimation = LinearCodec::estimate(&data).unwrap();
assert_le!(linear_interpol_estimation, 0.01);
let multi_linear_interpol_estimation = BlockwiseLinearSerializer::estimate(&data);
let multi_linear_interpol_estimation = BlockwiseLinearCodec::estimate(&data).unwrap();
assert_le!(multi_linear_interpol_estimation, 0.2);
assert_le!(linear_interpol_estimation, multi_linear_interpol_estimation);
assert_lt!(linear_interpol_estimation, multi_linear_interpol_estimation);
let bitpacked_estimation = BitpackedSerializer::estimate(&data);
assert_le!(linear_interpol_estimation, bitpacked_estimation);
let bitpacked_estimation = BitpackedCodec::estimate(&data).unwrap();
assert_lt!(linear_interpol_estimation, bitpacked_estimation);
}
#[test]
fn estimation_test_bad_interpolation_case() {
let data = vec![200, 10, 10, 10, 10, 1000, 20];
let data: &[u64] = &[200, 10, 10, 10, 10, 1000, 20];
let linear_interpol_estimation = LinearSerializer::estimate(&data);
assert_le!(linear_interpol_estimation, 0.32);
let data: VecColumn = data.into();
let linear_interpol_estimation = LinearCodec::estimate(&data).unwrap();
assert_le!(linear_interpol_estimation, 0.34);
let bitpacked_estimation = BitpackedSerializer::estimate(&data);
assert_le!(bitpacked_estimation, linear_interpol_estimation);
let bitpacked_estimation = BitpackedCodec::estimate(&data).unwrap();
assert_lt!(bitpacked_estimation, linear_interpol_estimation);
}
#[test]
fn estimation_prefer_bitpacked() {
let data = VecColumn::from(&[10, 10, 10, 10]);
let linear_interpol_estimation = LinearCodec::estimate(&data).unwrap();
let bitpacked_estimation = BitpackedCodec::estimate(&data).unwrap();
assert_lt!(bitpacked_estimation, linear_interpol_estimation);
}
#[test]
fn estimation_test_bad_interpolation_case_monotonically_increasing() {
let mut data = (200..=20000_u64).collect::<Vec<_>>();
let mut data: Vec<u64> = (201..=20000_u64).collect();
data.push(1_000_000);
let data: VecColumn = data.as_slice().into();
// in this case the linear interpolation can't in fact not be worse than bitpacking,
// but the estimator adds some threshold, which leads to estimated worse behavior
let linear_interpol_estimation = LinearSerializer::estimate(&data);
let linear_interpol_estimation = LinearCodec::estimate(&data).unwrap();
assert_le!(linear_interpol_estimation, 0.35);
let bitpacked_estimation = BitpackedSerializer::estimate(&data);
let bitpacked_estimation = BitpackedCodec::estimate(&data).unwrap();
assert_le!(bitpacked_estimation, 0.32);
assert_le!(bitpacked_estimation, linear_interpol_estimation);
}
@@ -303,6 +431,134 @@ mod tests {
count_codec += 1;
}
}
assert_eq!(count_codec, 4);
assert_eq!(count_codec, 3);
}
}
#[cfg(all(test, feature = "unstable"))]
mod bench {
use std::sync::Arc;
use ownedbytes::OwnedBytes;
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use test::{self, Bencher};
use super::*;
use crate::Column;
fn get_data() -> Vec<u64> {
let mut rng = StdRng::seed_from_u64(2u64);
let mut data: Vec<_> = (100..55000_u64)
.map(|num| num + rng.gen::<u8>() as u64)
.collect();
data.push(99_000);
data.insert(1000, 2000);
data.insert(2000, 100);
data.insert(3000, 4100);
data.insert(4000, 100);
data.insert(5000, 800);
data
}
#[inline(never)]
fn value_iter() -> impl Iterator<Item = u64> {
0..20_000
}
fn get_reader_for_bench<Codec: FastFieldCodec>(data: &[u64]) -> Codec::Reader {
let mut bytes = Vec::new();
let min_value = *data.iter().min().unwrap();
let data = data.iter().map(|el| *el - min_value).collect::<Vec<_>>();
let col = VecColumn::from(&data);
let normalized_header = crate::NormalizedHeader {
num_vals: col.num_vals(),
max_value: col.max_value(),
};
Codec::serialize(&VecColumn::from(&data), &mut bytes).unwrap();
Codec::open_from_bytes(OwnedBytes::new(bytes), normalized_header).unwrap()
}
fn bench_get<Codec: FastFieldCodec>(b: &mut Bencher, data: &[u64]) {
let col = get_reader_for_bench::<Codec>(data);
b.iter(|| {
let mut sum = 0u64;
for pos in value_iter() {
let val = col.get_val(pos as u32);
sum = sum.wrapping_add(val);
}
sum
});
}
#[inline(never)]
fn bench_get_dynamic_helper(b: &mut Bencher, col: Arc<dyn Column>) {
b.iter(|| {
let mut sum = 0u64;
for pos in value_iter() {
let val = col.get_val(pos as u32);
sum = sum.wrapping_add(val);
}
sum
});
}
fn bench_get_dynamic<Codec: FastFieldCodec>(b: &mut Bencher, data: &[u64]) {
let col = Arc::new(get_reader_for_bench::<Codec>(data));
bench_get_dynamic_helper(b, col);
}
fn bench_create<Codec: FastFieldCodec>(b: &mut Bencher, data: &[u64]) {
let min_value = *data.iter().min().unwrap();
let data = data.iter().map(|el| *el - min_value).collect::<Vec<_>>();
let mut bytes = Vec::new();
b.iter(|| {
bytes.clear();
Codec::serialize(&VecColumn::from(&data), &mut bytes).unwrap();
});
}
#[bench]
fn bench_fastfield_bitpack_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<BitpackedCodec>(b, &data);
}
#[bench]
fn bench_fastfield_linearinterpol_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<LinearCodec>(b, &data);
}
#[bench]
fn bench_fastfield_multilinearinterpol_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<BlockwiseLinearCodec>(b, &data);
}
#[bench]
fn bench_fastfield_bitpack_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<BitpackedCodec>(b, &data);
}
#[bench]
fn bench_fastfield_bitpack_get_dynamic(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get_dynamic::<BitpackedCodec>(b, &data);
}
#[bench]
fn bench_fastfield_linearinterpol_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<LinearCodec>(b, &data);
}
#[bench]
fn bench_fastfield_linearinterpol_get_dynamic(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get_dynamic::<LinearCodec>(b, &data);
}
#[bench]
fn bench_fastfield_multilinearinterpol_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<BlockwiseLinearCodec>(b, &data);
}
#[bench]
fn bench_fastfield_multilinearinterpol_get_dynamic(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get_dynamic::<BlockwiseLinearCodec>(b, &data);
}
}

222
fastfield_codecs/src/line.rs Normal file
View File

@@ -0,0 +1,222 @@
use std::io;
use std::num::NonZeroU32;
use common::{BinarySerializable, VInt};
use crate::Column;
const MID_POINT: u64 = (1u64 << 32) - 1u64;
/// `Line` describes a line function `y: ax + b` using integer
/// arithmetics.
///
/// The slope is in fact a decimal split into a 32 bit integer value,
/// and a 32-bit decimal value.
///
/// The multiplication then becomes.
/// `y = m * x >> 32 + b`
#[derive(Debug, Clone, Copy, Default)]
pub struct Line {
slope: u64,
intercept: u64,
}
/// Compute the line slope.
///
/// This function has the nice property of being
/// invariant by translation.
/// `
/// compute_slope(y0, y1)
/// = compute_slope(y0 + X % 2^64, y1 + X % 2^64)
/// `
fn compute_slope(y0: u64, y1: u64, num_vals: NonZeroU32) -> u64 {
let dy = y1.wrapping_sub(y0);
let sign = dy <= (1 << 63);
let abs_dy = if sign {
y1.wrapping_sub(y0)
} else {
y0.wrapping_sub(y1)
};
if abs_dy >= 1 << 32 {
// This is outside of realm we handle.
// Let's just bail.
return 0u64;
}
let abs_slope = (abs_dy << 32) / num_vals.get() as u64;
if sign {
abs_slope
} else {
// The complement does indeed create the
// opposite decreasing slope...
//
// Intuitively (without the bitshifts and % u64::MAX)
// ```
// (x + shift)*(u64::MAX - abs_slope)
// - (x * (u64::MAX - abs_slope))
// = - shift * abs_slope
// ```
u64::MAX - abs_slope
}
}
impl Line {
#[inline(always)]
pub fn eval(&self, x: u32) -> u64 {
let linear_part = ((x as u64).wrapping_mul(self.slope) >> 32) as i32 as u64;
self.intercept.wrapping_add(linear_part)
}
// Same as train, but the intercept is only estimated from provided sample positions
pub fn estimate(sample_positions_and_values: &[(u64, u64)]) -> Self {
let first_val = sample_positions_and_values[0].1;
let last_val = sample_positions_and_values[sample_positions_and_values.len() - 1].1;
let num_vals = sample_positions_and_values[sample_positions_and_values.len() - 1].0 + 1;
Self::train_from(
first_val,
last_val,
num_vals as u32,
sample_positions_and_values.iter().cloned(),
)
}
// Intercept is only computed from provided positions
fn train_from(
first_val: u64,
last_val: u64,
num_vals: u32,
positions_and_values: impl Iterator<Item = (u64, u64)>,
) -> Self {
// TODO replace with let else
let idx_last_val = if let Some(idx_last_val) = NonZeroU32::new(num_vals - 1) {
idx_last_val
} else {
return Line::default();
};
let y0 = first_val;
let y1 = last_val;
// We first independently pick our slope.
let slope = compute_slope(y0, y1, idx_last_val);
// We picked our slope. Note that it does not have to be perfect.
// Now we need to compute the best intercept.
//
// Intuitively, the best intercept is such that line passes through one of the
// `(i, ys[])`.
//
// The best intercept therefore has the form
// `y[i] - line.eval(i)` (using wrapping arithmetics).
// In other words, the best intercept is one of the `y - Line::eval(ys[i])`
// and our task is just to pick the one that minimizes our error.
//
// Without sorting our values, this is a difficult problem.
// We however rely on the following trick...
//
// We only focus on the case where the interpolation is half decent.
// If the line interpolation is doing its job on a dataset suited for it,
// we can hope that the maximum error won't be larger than `u64::MAX / 2`.
//
// In other words, even without the intercept the values `y - Line::eval(ys[i])` will all be
// within an interval that takes less than half of the modulo space of `u64`.
//
// Our task is therefore to identify this interval.
// Here we simply translate all of our values by `y0 - 2^63` and pick the min.
let mut line = Line {
slope,
intercept: 0,
};
let heuristic_shift = y0.wrapping_sub(MID_POINT);
line.intercept = positions_and_values
.map(|(pos, y)| y.wrapping_sub(line.eval(pos as u32)))
.min_by_key(|&val| val.wrapping_sub(heuristic_shift))
.unwrap_or(0u64); //< Never happens.
line
}
/// Returns a line that attemps to approximate a function
/// f: i in 0..[ys.num_vals()) -> ys[i].
///
/// - The approximation is always lower than the actual value.
/// Or more rigorously, formally `f(i).wrapping_sub(ys[i])` is small
/// for any i in [0..ys.len()).
/// - It computes without panicking for any value of it.
///
/// This function is only invariable by translation if all of the
/// `ys` are packaged into half of the space. (See heuristic below)
pub fn train(ys: &dyn Column) -> Self {
let first_val = ys.iter().next().unwrap();
let last_val = ys.iter().nth(ys.num_vals() as usize - 1).unwrap();
Self::train_from(
first_val,
last_val,
ys.num_vals(),
ys.iter().enumerate().map(|(pos, val)| (pos as u64, val)),
)
}
}
impl BinarySerializable for Line {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.slope).serialize(writer)?;
VInt(self.intercept).serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let slope = VInt::deserialize(reader)?.0;
let intercept = VInt::deserialize(reader)?.0;
Ok(Line { slope, intercept })
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::VecColumn;
/// Test training a line and ensuring that the maximum difference between
/// the data points and the line is `expected`.
///
/// This function operates translation over the data for better coverage.
#[track_caller]
fn test_line_interpol_with_translation(ys: &[u64], expected: Option<u64>) {
let mut translations = vec![0, 100, u64::MAX / 2, u64::MAX, u64::MAX - 1];
translations.extend_from_slice(ys);
for translation in translations {
let translated_ys: Vec<u64> = ys
.iter()
.copied()
.map(|y| y.wrapping_add(translation))
.collect();
let largest_err = test_eval_max_err(&translated_ys);
assert_eq!(largest_err, expected);
}
}
fn test_eval_max_err(ys: &[u64]) -> Option<u64> {
let line = Line::train(&VecColumn::from(&ys));
ys.iter()
.enumerate()
.map(|(x, y)| y.wrapping_sub(line.eval(x as u32)))
.max()
}
#[test]
fn test_train() {
test_line_interpol_with_translation(&[11, 11, 11, 12, 12, 13], Some(1));
test_line_interpol_with_translation(&[13, 12, 12, 11, 11, 11], Some(1));
test_line_interpol_with_translation(&[13, 13, 12, 11, 11, 11], Some(1));
test_line_interpol_with_translation(&[13, 13, 12, 11, 11, 11], Some(1));
test_line_interpol_with_translation(&[u64::MAX - 1, 0, 0, 1], Some(1));
test_line_interpol_with_translation(&[u64::MAX - 1, u64::MAX, 0, 1], Some(0));
test_line_interpol_with_translation(&[0, 1, 2, 3, 5], Some(0));
test_line_interpol_with_translation(&[1, 2, 3, 4], Some(0));
let data: Vec<u64> = (0..255).collect();
test_line_interpol_with_translation(&data, Some(0));
let data: Vec<u64> = (0..255).map(|el| el * 2).collect();
test_line_interpol_with_translation(&data, Some(0));
}
}

355
fastfield_codecs/src/linear.rs
View File

@@ -1,301 +1,184 @@
use std::io::{self, Read, Write};
use std::ops::Sub;
use std::io::{self, Write};
use common::{BinarySerializable, FixedSize};
use common::BinarySerializable;
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::{
FastFieldCodecReader, FastFieldCodecSerializer, FastFieldCodecType, FastFieldDataAccess,
};
use crate::line::Line;
use crate::serialize::NormalizedHeader;
use crate::{Column, FastFieldCodec, FastFieldCodecType};
/// Depending on the field type, a different
/// fast field is required.
#[derive(Clone)]
pub struct LinearReader {
data: OwnedBytes,
bit_unpacker: BitUnpacker,
pub footer: LinearFooter,
pub slope: f32,
linear_params: LinearParams,
header: NormalizedHeader,
}
#[derive(Clone, Debug)]
pub struct LinearFooter {
pub relative_max_value: u64,
pub offset: u64,
pub first_val: u64,
pub last_val: u64,
pub num_vals: u64,
pub min_value: u64,
pub max_value: u64,
}
impl BinarySerializable for LinearFooter {
fn serialize<W: Write>(&self, write: &mut W) -> io::Result<()> {
self.relative_max_value.serialize(write)?;
self.offset.serialize(write)?;
self.first_val.serialize(write)?;
self.last_val.serialize(write)?;
self.num_vals.serialize(write)?;
self.min_value.serialize(write)?;
self.max_value.serialize(write)?;
Ok(())
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<LinearFooter> {
Ok(LinearFooter {
relative_max_value: u64::deserialize(reader)?,
offset: u64::deserialize(reader)?,
first_val: u64::deserialize(reader)?,
last_val: u64::deserialize(reader)?,
num_vals: u64::deserialize(reader)?,
min_value: u64::deserialize(reader)?,
max_value: u64::deserialize(reader)?,
})
}
}
impl FixedSize for LinearFooter {
const SIZE_IN_BYTES: usize = 56;
}
impl FastFieldCodecReader for LinearReader {
/// Opens a fast field given a file.
fn open_from_bytes(bytes: OwnedBytes) -> io::Result<Self> {
let footer_offset = bytes.len() - LinearFooter::SIZE_IN_BYTES;
let (data, mut footer) = bytes.split(footer_offset);
let footer = LinearFooter::deserialize(&mut footer)?;
let slope = get_slope(footer.first_val, footer.last_val, footer.num_vals);
let num_bits = compute_num_bits(footer.relative_max_value);
let bit_unpacker = BitUnpacker::new(num_bits);
Ok(LinearReader {
data,
bit_unpacker,
footer,
slope,
})
}
impl Column for LinearReader {
#[inline]
fn get_u64(&self, doc: u64) -> u64 {
let calculated_value = get_calculated_value(self.footer.first_val, doc, self.slope);
(calculated_value + self.bit_unpacker.get(doc, &self.data)) - self.footer.offset
fn get_val(&self, doc: u32) -> u64 {
let interpoled_val: u64 = self.linear_params.line.eval(doc);
let bitpacked_diff = self.linear_params.bit_unpacker.get(doc, &self.data);
interpoled_val.wrapping_add(bitpacked_diff)
}
#[inline]
fn min_value(&self) -> u64 {
self.footer.min_value
// The LinearReader assumes a normalized vector.
0u64
}
#[inline]
fn max_value(&self) -> u64 {
self.footer.max_value
self.header.max_value
}
#[inline]
fn num_vals(&self) -> u32 {
self.header.num_vals
}
}
/// Fastfield serializer, which tries to guess values by linear interpolation
/// and stores the difference bitpacked.
pub struct LinearSerializer {}
pub struct LinearCodec;
#[inline]
pub(crate) fn get_slope(first_val: u64, last_val: u64, num_vals: u64) -> f32 {
if num_vals <= 1 {
return 0.0;
}
// We calculate the slope with f64 high precision and use the result in lower precision f32
// This is done in order to handle estimations for very large values like i64::MAX
let diff = diff(last_val, first_val);
(diff / (num_vals - 1) as f64) as f32
#[derive(Debug, Clone)]
struct LinearParams {
line: Line,
bit_unpacker: BitUnpacker,
}
/// Delay the cast, to improve precision for very large u64 values.
///
/// Since i64 is mapped monotonically to u64 space, 0i64 is after the mapping i64::MAX.
/// So very large values are not uncommon.
///
/// ```rust
/// let val1 = i64::MAX;
/// let val2 = i64::MAX - 100;
/// assert_eq!(val1 - val2, 100);
/// assert_eq!(val1 as f64 - val2 as f64, 0.0);
/// ```
fn diff(val1: u64, val2: u64) -> f64 {
if val1 >= val2 {
(val1 - val2) as f64
} else {
(val2 - val1) as f64 * -1.0
impl BinarySerializable for LinearParams {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
self.line.serialize(writer)?;
self.bit_unpacker.bit_width().serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let line = Line::deserialize(reader)?;
let bit_width = u8::deserialize(reader)?;
Ok(Self {
line,
bit_unpacker: BitUnpacker::new(bit_width),
})
}
}
#[inline]
pub fn get_calculated_value(first_val: u64, pos: u64, slope: f32) -> u64 {
if slope < 0.0 {
first_val - (pos as f32 * -slope) as u64
} else {
first_val + (pos as f32 * slope) as u64
}
}
impl FastFieldCodecSerializer for LinearSerializer {
impl FastFieldCodec for LinearCodec {
const CODEC_TYPE: FastFieldCodecType = FastFieldCodecType::Linear;
type Reader = LinearReader;
/// Opens a fast field given a file.
fn open_from_bytes(mut data: OwnedBytes, header: NormalizedHeader) -> io::Result<Self::Reader> {
let linear_params = LinearParams::deserialize(&mut data)?;
Ok(LinearReader {
data,
linear_params,
header,
})
}
/// Creates a new fast field serializer.
fn serialize(
write: &mut impl Write,
fastfield_accessor: &dyn FastFieldDataAccess,
) -> io::Result<()> {
assert!(fastfield_accessor.min_value() <= fastfield_accessor.max_value());
fn serialize(column: &dyn Column, write: &mut impl Write) -> io::Result<()> {
assert_eq!(column.min_value(), 0);
let line = Line::train(column);
let first_val = fastfield_accessor.get_val(0);
let last_val = fastfield_accessor.get_val(fastfield_accessor.num_vals() as u64 - 1);
let slope = get_slope(first_val, last_val, fastfield_accessor.num_vals());
// calculate offset to ensure all values are positive
let mut offset = 0;
let mut rel_positive_max = 0;
for (pos, actual_value) in fastfield_accessor.iter().enumerate() {
let calculated_value = get_calculated_value(first_val, pos as u64, slope);
if calculated_value > actual_value {
// negative value we need to apply an offset
// we ignore negative values in the max value calculation, because negative values
// will be offset to 0
offset = offset.max(calculated_value - actual_value);
} else {
// positive value no offset reuqired
rel_positive_max = rel_positive_max.max(actual_value - calculated_value);
}
}
let max_offset_from_line = column
.iter()
.enumerate()
.map(|(pos, actual_value)| {
let calculated_value = line.eval(pos as u32);
actual_value.wrapping_sub(calculated_value)
})
.max()
.unwrap();
// rel_positive_max will be adjusted by offset
let relative_max_value = rel_positive_max + offset;
let num_bits = compute_num_bits(max_offset_from_line);
let linear_params = LinearParams {
line,
bit_unpacker: BitUnpacker::new(num_bits),
};
linear_params.serialize(write)?;
let num_bits = compute_num_bits(relative_max_value);
let mut bit_packer = BitPacker::new();
for (pos, val) in fastfield_accessor.iter().enumerate() {
let calculated_value = get_calculated_value(first_val, pos as u64, slope);
let diff = (val + offset) - calculated_value;
bit_packer.write(diff, num_bits, write)?;
for (pos, actual_value) in column.iter().enumerate() {
let calculated_value = line.eval(pos as u32);
let offset = actual_value.wrapping_sub(calculated_value);
bit_packer.write(offset, num_bits, write)?;
}
bit_packer.close(write)?;
let footer = LinearFooter {
relative_max_value,
offset,
first_val,
last_val,
num_vals: fastfield_accessor.num_vals(),
min_value: fastfield_accessor.min_value(),
max_value: fastfield_accessor.max_value(),
};
footer.serialize(write)?;
Ok(())
}
fn is_applicable(fastfield_accessor: &impl FastFieldDataAccess) -> bool {
if fastfield_accessor.num_vals() < 3 {
return false; // disable compressor for this case
}
// On serialisation the offset is added to the actual value.
// We need to make sure this won't run into overflow calculation issues.
// For this we take the maximum theroretical offset and add this to the max value.
// If this doesn't overflow the algorithm should be fine
let theorethical_maximum_offset =
fastfield_accessor.max_value() - fastfield_accessor.min_value();
if fastfield_accessor
.max_value()
.checked_add(theorethical_maximum_offset)
.is_none()
{
return false;
}
true
}
/// estimation for linear interpolation is hard because, you don't know
/// where the local maxima for the deviation of the calculated value are and
/// the offset to shift all values to >=0 is also unknown.
fn estimate(fastfield_accessor: &impl FastFieldDataAccess) -> f32 {
let first_val = fastfield_accessor.get_val(0);
let last_val = fastfield_accessor.get_val(fastfield_accessor.num_vals() as u64 - 1);
let slope = get_slope(first_val, last_val, fastfield_accessor.num_vals());
#[allow(clippy::question_mark)]
fn estimate(column: &dyn Column) -> Option<f32> {
if column.num_vals() < 3 {
return None; // disable compressor for this case
}
// let's sample at 0%, 5%, 10% .. 95%, 100%
let num_vals = fastfield_accessor.num_vals() as f32 / 100.0;
let sample_positions = (0..20)
.map(|pos| (num_vals * pos as f32 * 5.0) as usize)
.collect::<Vec<_>>();
let limit_num_vals = column.num_vals().min(100_000);
let max_distance = sample_positions
.iter()
.map(|pos| {
let calculated_value = get_calculated_value(first_val, *pos as u64, slope);
let actual_value = fastfield_accessor.get_val(*pos as u64);
distance(calculated_value, actual_value)
let num_samples = 100;
let step_size = (limit_num_vals / num_samples).max(1); // 20 samples
let mut sample_positions_and_values: Vec<_> = Vec::new();
for (pos, val) in column.iter().enumerate().step_by(step_size as usize) {
sample_positions_and_values.push((pos as u64, val));
}
let line = Line::estimate(&sample_positions_and_values);
let estimated_bit_width = sample_positions_and_values
.into_iter()
.map(|(pos, actual_value)| {
let interpolated_val = line.eval(pos as u32);
actual_value.wrapping_sub(interpolated_val)
})
.map(|diff| ((diff as f32 * 1.5) * 2.0) as u64)
.map(compute_num_bits)
.max()
.unwrap_or(0);
// the theory would be that we don't have the actual max_distance, but we are close within
// 50% threshold.
// It is multiplied by 2 because in a log case scenario the line would be as much above as
// below. So the offset would = max_distance
//
let relative_max_value = (max_distance as f32 * 1.5) * 2.0;
let num_bits = compute_num_bits(relative_max_value as u64) as u64
* fastfield_accessor.num_vals()
+ LinearFooter::SIZE_IN_BYTES as u64;
let num_bits_uncompressed = 64 * fastfield_accessor.num_vals();
num_bits as f32 / num_bits_uncompressed as f32
}
}
#[inline]
fn distance<T: Sub<Output = T> + Ord>(x: T, y: T) -> T {
if x < y {
y - x
} else {
x - y
// Extrapolate to whole column
let num_bits = (estimated_bit_width as u64 * column.num_vals() as u64) + 64;
let num_bits_uncompressed = 64 * column.num_vals();
Some(num_bits as f32 / num_bits_uncompressed as f32)
}
}
#[cfg(test)]
mod tests {
use rand::RngCore;
use super::*;
use crate::tests::get_codec_test_data_sets;
use crate::tests::get_codec_test_datasets;
fn create_and_validate(data: &[u64], name: &str) -> (f32, f32) {
crate::tests::create_and_validate::<LinearSerializer, LinearReader>(data, name)
}
#[test]
fn get_calculated_value_test() {
// pos slope
assert_eq!(get_calculated_value(100, 10, 5.0), 150);
// neg slope
assert_eq!(get_calculated_value(100, 10, -5.0), 50);
// pos slope, very high values
assert_eq!(
get_calculated_value(i64::MAX as u64, 10, 5.0),
i64::MAX as u64 + 50
);
// neg slope, very high values
assert_eq!(
get_calculated_value(i64::MAX as u64, 10, -5.0),
i64::MAX as u64 - 50
);
fn create_and_validate(data: &[u64], name: &str) -> Option<(f32, f32)> {
crate::tests::create_and_validate::<LinearCodec>(data, name)
}
#[test]
fn test_compression() {
let data = (10..=6_000_u64).collect::<Vec<_>>();
let (estimate, actual_compression) =
create_and_validate(&data, "simple monotonically large");
create_and_validate(&data, "simple monotonically large").unwrap();
assert!(actual_compression < 0.01);
assert!(estimate < 0.01);
assert_le!(actual_compression, 0.001);
assert_le!(estimate, 0.02);
}
#[test]
fn test_with_codec_data_sets() {
let data_sets = get_codec_test_data_sets();
fn test_with_codec_datasets() {
let data_sets = get_codec_test_datasets();
for (mut data, name) in data_sets {
create_and_validate(&data, name);
data.reverse();
@@ -312,6 +195,13 @@ mod tests {
create_and_validate(&data, "large amplitude");
}
#[test]
fn overflow_error_test() {
let data = vec![1572656989877777, 1170935903116329, 720575940379279, 0];
create_and_validate(&data, "overflow test");
}
#[test]
fn linear_interpol_fast_concave_data() {
let data = vec![0, 1, 2, 5, 8, 10, 20, 50];
@@ -325,16 +215,15 @@ mod tests {
#[test]
fn linear_interpol_fast_field_test_simple() {
let data = (10..=20_u64).collect::<Vec<_>>();
create_and_validate(&data, "simple monotonically");
}
#[test]
fn linear_interpol_fast_field_rand() {
for _ in 0..5000 {
let mut data = (0..50).map(|_| rand::random::<u64>()).collect::<Vec<_>>();
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(&data, "random");
data.reverse();
create_and_validate(&data, "random");
}

200
fastfield_codecs/src/main.rs
View File

@@ -1,48 +1,171 @@
#[macro_use]
extern crate prettytable;
use fastfield_codecs::blockwise_linear::BlockwiseLinearSerializer;
use fastfield_codecs::linear::LinearSerializer;
use fastfield_codecs::{FastFieldCodecSerializer, FastFieldCodecType, FastFieldStats};
use std::collections::HashSet;
use std::env;
use std::io::BufRead;
use std::net::{IpAddr, Ipv6Addr};
use std::str::FromStr;
use fastfield_codecs::{open_u128, serialize_u128, Column, FastFieldCodecType, VecColumn};
use itertools::Itertools;
use measure_time::print_time;
use ownedbytes::OwnedBytes;
use prettytable::{Cell, Row, Table};
fn print_set_stats(ip_addrs: &[u128]) {
println!("NumIps\t{}", ip_addrs.len());
let ip_addr_set: HashSet<u128> = ip_addrs.iter().cloned().collect();
println!("NumUniqueIps\t{}", ip_addr_set.len());
let ratio_unique = ip_addr_set.len() as f64 / ip_addrs.len() as f64;
println!("RatioUniqueOverTotal\t{ratio_unique:.4}");
// histogram
let mut ip_addrs = ip_addrs.to_vec();
ip_addrs.sort();
let mut cnts: Vec<usize> = ip_addrs
.into_iter()
.dedup_with_count()
.map(|(cnt, _)| cnt)
.collect();
cnts.sort();
let top_256_cnt: usize = cnts.iter().rev().take(256).sum();
let top_128_cnt: usize = cnts.iter().rev().take(128).sum();
let top_64_cnt: usize = cnts.iter().rev().take(64).sum();
let top_8_cnt: usize = cnts.iter().rev().take(8).sum();
let total: usize = cnts.iter().sum();
println!("{}", total);
println!("{}", top_256_cnt);
println!("{}", top_128_cnt);
println!("Percentage Top8 {:02}", top_8_cnt as f32 / total as f32);
println!("Percentage Top64 {:02}", top_64_cnt as f32 / total as f32);
println!("Percentage Top128 {:02}", top_128_cnt as f32 / total as f32);
println!("Percentage Top256 {:02}", top_256_cnt as f32 / total as f32);
let mut cnts: Vec<(usize, usize)> = cnts.into_iter().dedup_with_count().collect();
cnts.sort_by(|a, b| {
if a.1 == b.1 {
a.0.cmp(&b.0)
} else {
b.1.cmp(&a.1)
}
});
}
fn ip_dataset() -> Vec<u128> {
let mut ip_addr_v4 = 0;
let stdin = std::io::stdin();
let ip_addrs: Vec<u128> = stdin
.lock()
.lines()
.flat_map(|line| {
let line = line.unwrap();
let line = line.trim();
let ip_addr = IpAddr::from_str(line.trim()).ok()?;
if ip_addr.is_ipv4() {
ip_addr_v4 += 1;
}
let ip_addr_v6: Ipv6Addr = match ip_addr {
IpAddr::V4(v4) => v4.to_ipv6_mapped(),
IpAddr::V6(v6) => v6,
};
Some(ip_addr_v6)
})
.map(|ip_v6| u128::from_be_bytes(ip_v6.octets()))
.collect();
println!("IpAddrsAny\t{}", ip_addrs.len());
println!("IpAddrsV4\t{}", ip_addr_v4);
ip_addrs
}
fn bench_ip() {
let dataset = ip_dataset();
print_set_stats(&dataset);
// Chunks
{
let mut data = vec![];
for dataset in dataset.chunks(500_000) {
serialize_u128(|| dataset.iter().cloned(), dataset.len() as u32, &mut data).unwrap();
}
let compression = data.len() as f64 / (dataset.len() * 16) as f64;
println!("Compression 50_000 chunks {:.4}", compression);
println!(
"Num Bits per elem {:.2}",
(data.len() * 8) as f32 / dataset.len() as f32
);
}
let mut data = vec![];
{
print_time!("creation");
serialize_u128(|| dataset.iter().cloned(), dataset.len() as u32, &mut data).unwrap();
}
let compression = data.len() as f64 / (dataset.len() * 16) as f64;
println!("Compression {:.2}", compression);
println!(
"Num Bits per elem {:.2}",
(data.len() * 8) as f32 / dataset.len() as f32
);
let decompressor = open_u128::<u128>(OwnedBytes::new(data))
.unwrap()
.to_full()
.unwrap();
// Sample some ranges
let mut doc_values = Vec::new();
for value in dataset.iter().take(1110).skip(1100).cloned() {
doc_values.clear();
print_time!("get range");
decompressor.get_docids_for_value_range(
value..=value,
0..decompressor.num_vals(),
&mut doc_values,
);
println!("{:?}", doc_values.len());
}
}
fn main() {
if env::args().nth(1).unwrap() == "bench_ip" {
bench_ip();
return;
}
let mut table = Table::new();
// Add a row per time
table.add_row(row!["", "Compression Ratio", "Compression Estimation"]);
for (data, data_set_name) in get_codec_test_data_sets() {
let mut results = vec![];
let res = serialize_with_codec::<LinearSerializer>(&data);
results.push(res);
let res = serialize_with_codec::<BlockwiseLinearSerializer>(&data);
results.push(res);
let res = serialize_with_codec::<fastfield_codecs::bitpacked::BitpackedSerializer>(&data);
results.push(res);
// let best_estimation_codec = results
//.iter()
//.min_by(|res1, res2| res1.partial_cmp(&res2).unwrap())
//.unwrap();
let results: Vec<(f32, f32, FastFieldCodecType)> = [
serialize_with_codec(&data, FastFieldCodecType::Bitpacked),
serialize_with_codec(&data, FastFieldCodecType::Linear),
serialize_with_codec(&data, FastFieldCodecType::BlockwiseLinear),
]
.into_iter()
.flatten()
.collect();
let best_compression_ratio_codec = results
.iter()
.min_by(|res1, res2| res1.partial_cmp(res2).unwrap())
.min_by(|&res1, &res2| res1.partial_cmp(res2).unwrap())
.cloned()
.unwrap();
table.add_row(Row::new(vec![Cell::new(data_set_name).style_spec("Bbb")]));
for (is_applicable, est, comp, codec_type) in results {
let (est_cell, ratio_cell) = if !is_applicable {
("Codec Disabled".to_string(), "".to_string())
} else {
(est.to_string(), comp.to_string())
};
for (est, comp, codec_type) in results {
let est_cell = est.to_string();
let ratio_cell = comp.to_string();
let style = if comp == best_compression_ratio_codec.1 {
"Fb"
} else {
""
};
table.add_row(Row::new(vec![
Cell::new(&format!("{codec_type:?}")).style_spec("bFg"),
Cell::new(&ratio_cell).style_spec(style),
@@ -89,27 +212,14 @@ pub fn get_codec_test_data_sets() -> Vec<(Vec<u64>, &'static str)> {
data_and_names
}
pub fn serialize_with_codec<S: FastFieldCodecSerializer>(
pub fn serialize_with_codec(
data: &[u64],
) -> (bool, f32, f32, FastFieldCodecType) {
let is_applicable = S::is_applicable(&data);
if !is_applicable {
return (false, 0.0, 0.0, S::CODEC_TYPE);
}
let estimation = S::estimate(&data);
let mut out = vec![];
S::serialize(&mut out, &data).unwrap();
let actual_compression = out.len() as f32 / (data.len() * 8) as f32;
(true, estimation, actual_compression, S::CODEC_TYPE)
}
pub fn stats_from_vec(data: &[u64]) -> FastFieldStats {
let min_value = data.iter().cloned().min().unwrap_or(0);
let max_value = data.iter().cloned().max().unwrap_or(0);
FastFieldStats {
min_value,
max_value,
num_vals: data.len() as u64,
}
codec_type: FastFieldCodecType,
) -> Option<(f32, f32, FastFieldCodecType)> {
let col = VecColumn::from(data);
let estimation = fastfield_codecs::estimate(&col, codec_type)?;
let mut out = Vec::new();
fastfield_codecs::serialize(&col, &mut out, &[codec_type]).ok()?;
let actual_compression = out.len() as f32 / (col.num_vals() * 8) as f32;
Some((estimation, actual_compression, codec_type))
}

233
fastfield_codecs/src/monotonic_mapping.rs Normal file
View File

@@ -0,0 +1,233 @@
use std::marker::PhantomData;
use fastdivide::DividerU64;
use crate::MonotonicallyMappableToU128;
/// Monotonic maps a value to u64 value space.
/// Monotonic mapping enables `PartialOrd` on u64 space without conversion to original space.
pub trait MonotonicallyMappableToU64: 'static + PartialOrd + Copy + Send + Sync {
/// Converts a value to u64.
///
/// Internally all fast field values are encoded as u64.
fn to_u64(self) -> u64;
/// Converts a value from u64
///
/// Internally all fast field values are encoded as u64.
/// **Note: To be used for converting encoded Term, Posting values.**
fn from_u64(val: u64) -> Self;
}
/// Values need to be strictly monotonic mapped to a `Internal` value (u64 or u128) that can be
/// used in fast field codecs.
///
/// The monotonic mapping is required so that `PartialOrd` can be used on `Internal` without
/// converting to `External`.
///
/// All strictly monotonic functions are invertible because they are guaranteed to have a one-to-one
/// mapping from their range to their domain. The `inverse` method is required when opening a codec,
/// so a value can be converted back to its original domain (e.g. ip address or f64) from its
/// internal representation.
pub trait StrictlyMonotonicFn<External, Internal> {
/// Strictly monotonically maps the value from External to Internal.
fn mapping(&self, inp: External) -> Internal;
/// Inverse of `mapping`. Maps the value from Internal to External.
fn inverse(&self, out: Internal) -> External;
}
/// Inverts a strictly monotonic mapping from `StrictlyMonotonicFn<A, B>` to
/// `StrictlyMonotonicFn<B, A>`.
///
/// # Warning
///
/// This type comes with a footgun. A type being strictly monotonic does not impose that the inverse
/// mapping is strictly monotonic over the entire space External. e.g. a -> a * 2. Use at your own
/// risks.
pub(crate) struct StrictlyMonotonicMappingInverter<T> {
orig_mapping: T,
}
impl<T> From<T> for StrictlyMonotonicMappingInverter<T> {
fn from(orig_mapping: T) -> Self {
Self { orig_mapping }
}
}
impl<From, To, T> StrictlyMonotonicFn<To, From> for StrictlyMonotonicMappingInverter<T>
where T: StrictlyMonotonicFn<From, To>
{
fn mapping(&self, val: To) -> From {
self.orig_mapping.inverse(val)
}
fn inverse(&self, val: From) -> To {
self.orig_mapping.mapping(val)
}
}
/// Applies the strictly monotonic mapping from `T` without any additional changes.
pub(crate) struct StrictlyMonotonicMappingToInternal<T> {
_phantom: PhantomData<T>,
}
impl<T> StrictlyMonotonicMappingToInternal<T> {
pub(crate) fn new() -> StrictlyMonotonicMappingToInternal<T> {
Self {
_phantom: PhantomData,
}
}
}
impl<External: MonotonicallyMappableToU128, T: MonotonicallyMappableToU128>
StrictlyMonotonicFn<External, u128> for StrictlyMonotonicMappingToInternal<T>
where T: MonotonicallyMappableToU128
{
fn mapping(&self, inp: External) -> u128 {
External::to_u128(inp)
}
fn inverse(&self, out: u128) -> External {
External::from_u128(out)
}
}
impl<External: MonotonicallyMappableToU64, T: MonotonicallyMappableToU64>
StrictlyMonotonicFn<External, u64> for StrictlyMonotonicMappingToInternal<T>
where T: MonotonicallyMappableToU64
{
fn mapping(&self, inp: External) -> u64 {
External::to_u64(inp)
}
fn inverse(&self, out: u64) -> External {
External::from_u64(out)
}
}
/// Mapping dividing by gcd and a base value.
///
/// The function is assumed to be only called on values divided by passed
/// gcd value. (It is necessary for the function to be monotonic.)
pub(crate) struct StrictlyMonotonicMappingToInternalGCDBaseval {
gcd_divider: DividerU64,
gcd: u64,
min_value: u64,
}
impl StrictlyMonotonicMappingToInternalGCDBaseval {
pub(crate) fn new(gcd: u64, min_value: u64) -> Self {
let gcd_divider = DividerU64::divide_by(gcd);
Self {
gcd_divider,
gcd,
min_value,
}
}
}
impl<External: MonotonicallyMappableToU64> StrictlyMonotonicFn<External, u64>
for StrictlyMonotonicMappingToInternalGCDBaseval
{
fn mapping(&self, inp: External) -> u64 {
self.gcd_divider
.divide(External::to_u64(inp) - self.min_value)
}
fn inverse(&self, out: u64) -> External {
External::from_u64(self.min_value + out * self.gcd)
}
}
/// Strictly monotonic mapping with a base value.
pub(crate) struct StrictlyMonotonicMappingToInternalBaseval {
min_value: u64,
}
impl StrictlyMonotonicMappingToInternalBaseval {
pub(crate) fn new(min_value: u64) -> Self {
Self { min_value }
}
}
impl<External: MonotonicallyMappableToU64> StrictlyMonotonicFn<External, u64>
for StrictlyMonotonicMappingToInternalBaseval
{
fn mapping(&self, val: External) -> u64 {
External::to_u64(val) - self.min_value
}
fn inverse(&self, val: u64) -> External {
External::from_u64(self.min_value + val)
}
}
impl MonotonicallyMappableToU64 for u64 {
fn to_u64(self) -> u64 {
self
}
fn from_u64(val: u64) -> Self {
val
}
}
impl MonotonicallyMappableToU64 for i64 {
#[inline(always)]
fn to_u64(self) -> u64 {
common::i64_to_u64(self)
}
#[inline(always)]
fn from_u64(val: u64) -> Self {
common::u64_to_i64(val)
}
}
impl MonotonicallyMappableToU64 for bool {
#[inline(always)]
fn to_u64(self) -> u64 {
u64::from(self)
}
#[inline(always)]
fn from_u64(val: u64) -> Self {
val > 0
}
}
impl MonotonicallyMappableToU64 for f64 {
fn to_u64(self) -> u64 {
common::f64_to_u64(self)
}
fn from_u64(val: u64) -> Self {
common::u64_to_f64(val)
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn strictly_monotonic_test() {
// identity mapping
test_round_trip(&StrictlyMonotonicMappingToInternal::<u64>::new(), 100u64);
// round trip to i64
test_round_trip(&StrictlyMonotonicMappingToInternal::<i64>::new(), 100u64);
// identity mapping
test_round_trip(&StrictlyMonotonicMappingToInternal::<u128>::new(), 100u128);
// base value to i64 round trip
let mapping = StrictlyMonotonicMappingToInternalBaseval::new(100);
test_round_trip::<_, _, u64>(&mapping, 100i64);
// base value and gcd to u64 round trip
let mapping = StrictlyMonotonicMappingToInternalGCDBaseval::new(10, 100);
test_round_trip::<_, _, u64>(&mapping, 100u64);
}
fn test_round_trip<T: StrictlyMonotonicFn<K, L>, K: std::fmt::Debug + Eq + Copy, L>(
mapping: &T,
test_val: K,
) {
assert_eq!(mapping.inverse(mapping.mapping(test_val)), test_val);
}
}

40
fastfield_codecs/src/monotonic_mapping_u128.rs Normal file
View File

@@ -0,0 +1,40 @@
use std::net::Ipv6Addr;
/// Montonic maps a value to u128 value space
/// Monotonic mapping enables `PartialOrd` on u128 space without conversion to original space.
pub trait MonotonicallyMappableToU128: 'static + PartialOrd + Copy + Send + Sync {
/// Converts a value to u128.
///
/// Internally all fast field values are encoded as u64.
fn to_u128(self) -> u128;
/// Converts a value from u128
///
/// Internally all fast field values are encoded as u64.
/// **Note: To be used for converting encoded Term, Posting values.**
fn from_u128(val: u128) -> Self;
}
impl MonotonicallyMappableToU128 for u128 {
fn to_u128(self) -> u128 {
self
}
fn from_u128(val: u128) -> Self {
val
}
}
impl MonotonicallyMappableToU128 for Ipv6Addr {
fn to_u128(self) -> u128 {
ip_to_u128(self)
}
fn from_u128(val: u128) -> Self {
Ipv6Addr::from(val.to_be_bytes())
}
}
fn ip_to_u128(ip_addr: Ipv6Addr) -> u128 {
u128::from_be_bytes(ip_addr.octets())
}

119
fastfield_codecs/src/optional_column.rs Normal file
View File

@@ -0,0 +1,119 @@
use std::ops::{Range, RangeInclusive};
use std::sync::Arc;
use crate::Column;
/// `OptionalColumn` provides columnar access on a field.
pub trait OptionalColumn<T: PartialOrd = u64>: Send + Sync {
/// Return the value associated with the given idx.
///
/// This accessor should return as fast as possible.
///
/// # Panics
///
/// May panic if `idx` is greater than the column length.
fn get_val(&self, idx: u32) -> Option<T>;
/// Fills an output buffer with the fast field values
/// associated with the `DocId` going from
/// `start` to `start + output.len()`.
///
/// # Panics
///
/// Must panic if `start + output.len()` is greater than
/// the segment's `maxdoc`.
fn get_range(&self, start: u64, output: &mut [Option<T>]) {
for (out, idx) in output.iter_mut().zip(start..) {
*out = self.get_val(idx as u32);
}
}
/// Return the positions of values which are in the provided range.
fn get_docids_for_value_range(
&self,
value_range: RangeInclusive<T>,
doc_id_range: Range<u32>,
positions: &mut Vec<u32>,
) {
let doc_id_range = doc_id_range.start..doc_id_range.end.min(self.num_vals());
for idx in doc_id_range {
let val = self.get_val(idx);
if let Some(val) = val {
if value_range.contains(&val) {
positions.push(idx);
}
}
}
}
/// Returns the minimum value for this fast field.
///
/// This min_value may not be exact.
/// For instance, the min value does not take in account of possible
/// deleted document. All values are however guaranteed to be higher than
/// `.min_value()`.
fn min_value(&self) -> Option<T>;
/// Returns the maximum value for this fast field.
///
/// This max_value may not be exact.
/// For instance, the max value does not take in account of possible
/// deleted document. All values are however guaranteed to be higher than
/// `.max_value()`.
fn max_value(&self) -> Option<T>;
/// The number of values including `None` in the column.
fn num_vals(&self) -> u32;
/// Returns a iterator over the data
fn iter<'a>(&'a self) -> Box<dyn Iterator<Item = Option<T>> + 'a> {
Box::new((0..self.num_vals()).map(|idx| self.get_val(idx)))
}
/// return full column if all values are set and is not empty
fn to_full(&self) -> Option<Arc<dyn Column<T>>> {
None
}
}
/// Temporary wrapper to migrate to optional column
pub(crate) struct ToOptionalColumn<T> {
column: Arc<dyn Column<T>>,
}
impl<T: PartialOrd> ToOptionalColumn<T> {
pub(crate) fn new(column: Arc<dyn Column<T>>) -> Self {
Self { column }
}
}
impl<T: PartialOrd> OptionalColumn<T> for ToOptionalColumn<T> {
#[inline]
fn get_val(&self, idx: u32) -> Option<T> {
let val = self.column.get_val(idx);
Some(val)
}
fn min_value(&self) -> Option<T> {
let min_value = self.column.min_value();
Some(min_value)
}
fn max_value(&self) -> Option<T> {
let max_value = self.column.max_value();
Some(max_value)
}
fn num_vals(&self) -> u32 {
self.column.num_vals()
}
fn iter(&self) -> Box<dyn Iterator<Item = Option<T>> + '_> {
Box::new(self.column.iter().map(|el| Some(el)))
}
/// return full column if all values are set and is not empty
fn to_full(&self) -> Option<Arc<dyn Column<T>>> {
Some(self.column.clone())
}
}

337
fastfield_codecs/src/serialize.rs Normal file
View File

@@ -0,0 +1,337 @@
// Copyright (C) 2022 Quickwit, Inc.
//
// Quickwit is offered under the AGPL v3.0 and as commercial software.
// For commercial licensing, contact us at hello@quickwit.io.
//
// AGPL:
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as
// published by the Free Software Foundation, either version 3 of the
// License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.
use std::io;
use std::num::NonZeroU64;
use std::sync::Arc;
use common::{BinarySerializable, VInt};
use log::warn;
use ownedbytes::OwnedBytes;
use crate::bitpacked::BitpackedCodec;
use crate::blockwise_linear::BlockwiseLinearCodec;
use crate::compact_space::CompactSpaceCompressor;
use crate::linear::LinearCodec;
use crate::monotonic_mapping::{
StrictlyMonotonicFn, StrictlyMonotonicMappingToInternal,
StrictlyMonotonicMappingToInternalGCDBaseval,
};
use crate::{
monotonic_map_column, Column, FastFieldCodec, FastFieldCodecType, MonotonicallyMappableToU64,
U128FastFieldCodecType, VecColumn, ALL_CODEC_TYPES,
};
/// The normalized header gives some parameters after applying the following
/// normalization of the vector:
/// `val -> (val - min_value) / gcd`
///
/// By design, after normalization, `min_value = 0` and `gcd = 1`.
#[derive(Debug, Copy, Clone)]
pub struct NormalizedHeader {
/// The number of values in the underlying column.
pub num_vals: u32,
/// The max value of the underlying column.
pub max_value: u64,
}
#[derive(Debug, Copy, Clone)]
pub(crate) struct Header {
pub num_vals: u32,
pub min_value: u64,
pub max_value: u64,
pub gcd: Option<NonZeroU64>,
pub codec_type: FastFieldCodecType,
}
impl Header {
pub fn normalized(self) -> NormalizedHeader {
let gcd = self.gcd.map(|gcd| gcd.get()).unwrap_or(1);
let gcd_min_val_mapping =
StrictlyMonotonicMappingToInternalGCDBaseval::new(gcd, self.min_value);
let max_value = gcd_min_val_mapping.mapping(self.max_value);
NormalizedHeader {
num_vals: self.num_vals,
max_value,
}
}
pub fn normalize_column<C: Column>(&self, from_column: C) -> impl Column {
normalize_column(from_column, self.min_value, self.gcd)
}
pub fn compute_header(
column: impl Column<u64>,
codecs: &[FastFieldCodecType],
) -> Option<Header> {
let num_vals = column.num_vals();
let min_value = column.min_value();
let max_value = column.max_value();
let gcd = crate::gcd::find_gcd(column.iter().map(|val| val - min_value))
.filter(|gcd| gcd.get() > 1u64);
let normalized_column = normalize_column(column, min_value, gcd);
let codec_type = detect_codec(normalized_column, codecs)?;
Some(Header {
num_vals,
min_value,
max_value,
gcd,
codec_type,
})
}
}
#[derive(Debug, Copy, Clone, PartialEq, Eq)]
pub(crate) struct U128Header {
pub num_vals: u32,
pub codec_type: U128FastFieldCodecType,
}
impl BinarySerializable for U128Header {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.num_vals as u64).serialize(writer)?;
self.codec_type.serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let num_vals = VInt::deserialize(reader)?.0 as u32;
let codec_type = U128FastFieldCodecType::deserialize(reader)?;
Ok(U128Header {
num_vals,
codec_type,
})
}
}
pub fn normalize_column<C: Column>(
from_column: C,
min_value: u64,
gcd: Option<NonZeroU64>,
) -> impl Column {
let gcd = gcd.map(|gcd| gcd.get()).unwrap_or(1);
let mapping = StrictlyMonotonicMappingToInternalGCDBaseval::new(gcd, min_value);
monotonic_map_column(from_column, mapping)
}
impl BinarySerializable for Header {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.num_vals as u64).serialize(writer)?;
VInt(self.min_value).serialize(writer)?;
VInt(self.max_value - self.min_value).serialize(writer)?;
if let Some(gcd) = self.gcd {
VInt(gcd.get()).serialize(writer)?;
} else {
VInt(0u64).serialize(writer)?;
}
self.codec_type.serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let num_vals = VInt::deserialize(reader)?.0 as u32;
let min_value = VInt::deserialize(reader)?.0;
let amplitude = VInt::deserialize(reader)?.0;
let max_value = min_value + amplitude;
let gcd_u64 = VInt::deserialize(reader)?.0;
let codec_type = FastFieldCodecType::deserialize(reader)?;
Ok(Header {
num_vals,
min_value,
max_value,
gcd: NonZeroU64::new(gcd_u64),
codec_type,
})
}
}
/// Return estimated compression for given codec in the value range [0.0..1.0], where 1.0 means no
/// compression.
pub fn estimate<T: MonotonicallyMappableToU64>(
typed_column: impl Column<T>,
codec_type: FastFieldCodecType,
) -> Option<f32> {
let column = monotonic_map_column(typed_column, StrictlyMonotonicMappingToInternal::<T>::new());
let min_value = column.min_value();
let gcd = crate::gcd::find_gcd(column.iter().map(|val| val - min_value))
.filter(|gcd| gcd.get() > 1u64);
let mapping = StrictlyMonotonicMappingToInternalGCDBaseval::new(
gcd.map(|gcd| gcd.get()).unwrap_or(1u64),
min_value,
);
let normalized_column = monotonic_map_column(&column, mapping);
match codec_type {
FastFieldCodecType::Bitpacked => BitpackedCodec::estimate(&normalized_column),
FastFieldCodecType::Linear => LinearCodec::estimate(&normalized_column),
FastFieldCodecType::BlockwiseLinear => BlockwiseLinearCodec::estimate(&normalized_column),
}
}
/// Serializes u128 values with the compact space codec.
pub fn serialize_u128<F: Fn() -> I, I: Iterator<Item = u128>>(
iter_gen: F,
num_vals: u32,
output: &mut impl io::Write,
) -> io::Result<()> {
let header = U128Header {
num_vals,
codec_type: U128FastFieldCodecType::CompactSpace,
};
header.serialize(output)?;
let compressor = CompactSpaceCompressor::train_from(iter_gen(), num_vals);
compressor.compress_into(iter_gen(), output).unwrap();
Ok(())
}
/// Serializes the column with the codec with the best estimate on the data.
pub fn serialize<T: MonotonicallyMappableToU64>(
typed_column: impl Column<T>,
output: &mut impl io::Write,
codecs: &[FastFieldCodecType],
) -> io::Result<()> {
let column = monotonic_map_column(typed_column, StrictlyMonotonicMappingToInternal::<T>::new());
let header = Header::compute_header(&column, codecs).ok_or_else(|| {
io::Error::new(
io::ErrorKind::InvalidInput,
format!(
"Data cannot be serialized with this list of codec. {:?}",
codecs
),
)
})?;
header.serialize(output)?;
let normalized_column = header.normalize_column(column);
assert_eq!(normalized_column.min_value(), 0u64);
serialize_given_codec(normalized_column, header.codec_type, output)?;
Ok(())
}
fn detect_codec(
column: impl Column<u64>,
codecs: &[FastFieldCodecType],
) -> Option<FastFieldCodecType> {
let mut estimations = Vec::new();
for &codec in codecs {
let estimation_opt = match codec {
FastFieldCodecType::Bitpacked => BitpackedCodec::estimate(&column),
FastFieldCodecType::Linear => LinearCodec::estimate(&column),
FastFieldCodecType::BlockwiseLinear => BlockwiseLinearCodec::estimate(&column),
};
if let Some(estimation) = estimation_opt {
estimations.push((estimation, codec));
}
}
if let Some(broken_estimation) = estimations.iter().find(|estimation| estimation.0.is_nan()) {
warn!(
"broken estimation for fast field codec {:?}",
broken_estimation.1
);
}
// removing nan values for codecs with broken calculations, and max values which disables
// codecs
estimations.retain(|estimation| !estimation.0.is_nan() && estimation.0 != f32::MAX);
estimations.sort_by(|(score_left, _), (score_right, _)| score_left.total_cmp(score_right));
Some(estimations.first()?.1)
}
fn serialize_given_codec(
column: impl Column<u64>,
codec_type: FastFieldCodecType,
output: &mut impl io::Write,
) -> io::Result<()> {
match codec_type {
FastFieldCodecType::Bitpacked => {
BitpackedCodec::serialize(&column, output)?;
}
FastFieldCodecType::Linear => {
LinearCodec::serialize(&column, output)?;
}
FastFieldCodecType::BlockwiseLinear => {
BlockwiseLinearCodec::serialize(&column, output)?;
}
}
output.flush()?;
Ok(())
}
/// Helper function to serialize a column (autodetect from all codecs) and then open it
pub fn serialize_and_load<T: MonotonicallyMappableToU64 + Ord + Default>(
column: &[T],
) -> Arc<dyn Column<T>> {
let mut buffer = Vec::new();
super::serialize(VecColumn::from(&column), &mut buffer, &ALL_CODEC_TYPES).unwrap();
super::open(OwnedBytes::new(buffer))
.unwrap()
.to_full()
.unwrap()
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_serialize_deserialize_u128_header() {
let original = U128Header {
num_vals: 11,
codec_type: U128FastFieldCodecType::CompactSpace,
};
let mut out = Vec::new();
original.serialize(&mut out).unwrap();
let restored = U128Header::deserialize(&mut &out[..]).unwrap();
assert_eq!(restored, original);
}
#[test]
fn test_serialize_deserialize() {
let original = [1u64, 5u64, 10u64];
let restored: Vec<u64> = serialize_and_load(&original[..]).iter().collect();
assert_eq!(&restored, &original[..]);
}
#[test]
fn test_fastfield_bool_size_bitwidth_1() {
let mut buffer = Vec::new();
let col = VecColumn::from(&[false, true][..]);
serialize(col, &mut buffer, &ALL_CODEC_TYPES).unwrap();
// 5 bytes of header, 1 byte of value, 7 bytes of padding.
assert_eq!(buffer.len(), 5 + 8);
}
#[test]
fn test_fastfield_bool_bit_size_bitwidth_0() {
let mut buffer = Vec::new();
let col = VecColumn::from(&[true][..]);
serialize(col, &mut buffer, &ALL_CODEC_TYPES).unwrap();
// 5 bytes of header, 0 bytes of value, 7 bytes of padding.
assert_eq!(buffer.len(), 5 + 7);
}
#[test]
fn test_fastfield_gcd() {
let mut buffer = Vec::new();
let vals: Vec<u64> = (0..80).map(|val| (val % 7) * 1_000u64).collect();
let col = VecColumn::from(&vals[..]);
serialize(col, &mut buffer, &[FastFieldCodecType::Bitpacked]).unwrap();
// Values are stored over 3 bits.
assert_eq!(buffer.len(), 7 + (3 * 80 / 8) + 7);
}
}

2
ownedbytes/src/lib.rs
View File

@@ -6,7 +6,7 @@ use std::{fmt, io, mem};
use stable_deref_trait::StableDeref;
/// An OwnedBytes simply wraps an object that owns a slice of data and exposes
/// this data as a static slice.
/// this data as a slice.
///
/// The backing object is required to be `StableDeref`.
#[derive(Clone)]

71
query-grammar/src/query_grammar.rs
View File

@@ -5,7 +5,8 @@ use combine::parser::range::{take_while, take_while1};
use combine::parser::repeat::escaped;
use combine::parser::Parser;
use combine::{
attempt, choice, eof, many, many1, one_of, optional, parser, satisfy, skip_many1, value,
attempt, between, choice, eof, many, many1, one_of, optional, parser, satisfy, sep_by,
skip_many1, value,
};
use once_cell::sync::Lazy;
use regex::Regex;
@@ -23,7 +24,7 @@ const ESCAPED_SPECIAL_CHARS_PATTERN: &str = r#"\\(\+|\^|`|:|\{|\}|"|\[|\]|\(|\)|
/// Parses a field_name
/// A field name must have at least one character and be followed by a colon.
/// All characters are allowed including special characters `SPECIAL_CHARS`, but these
/// need to be escaped with a backslack character '\'.
/// need to be escaped with a backslash character '\'.
fn field_name<'a>() -> impl Parser<&'a str, Output = String> {
static ESCAPED_SPECIAL_CHARS_RE: Lazy<Regex> =
Lazy::new(|| Regex::new(ESCAPED_SPECIAL_CHARS_PATTERN).unwrap());
@@ -62,13 +63,27 @@ fn word<'a>() -> impl Parser<&'a str, Output = String> {
})
}
// word variant that allows more characters, e.g. for range queries that don't allow field
// specifier
fn relaxed_word<'a>() -> impl Parser<&'a str, Output = String> {
(
satisfy(|c: char| {
!c.is_whitespace() && !['`', '{', '}', '"', '[', ']', '(', ')'].contains(&c)
}),
many(satisfy(|c: char| {
!c.is_whitespace() && !['{', '}', '"', '[', ']', '(', ')'].contains(&c)
})),
)
.map(|(s1, s2): (char, String)| format!("{}{}", s1, s2))
}
/// Parses a date time according to rfc3339
/// 2015-08-02T18:54:42+02
/// 2021-04-13T19:46:26.266051969+00:00
///
/// NOTE: also accepts 999999-99-99T99:99:99.266051969+99:99
/// We delegate rejecting such invalid dates to the logical AST computation code
/// which invokes time::OffsetDateTime::parse(..., &Rfc3339) on the value to actually parse
/// which invokes `time::OffsetDateTime::parse(..., &Rfc3339)` on the value to actually parse
/// it (instead of merely extracting the datetime value as string as done here).
fn date_time<'a>() -> impl Parser<&'a str, Output = String> {
let two_digits = || recognize::<String, _, _>((digit(), digit()));
@@ -181,8 +196,8 @@ fn spaces1<'a>() -> impl Parser<&'a str, Output = ()> {
fn range<'a>() -> impl Parser<&'a str, Output = UserInputLeaf> {
let range_term_val = || {
attempt(date_time())
.or(word())
.or(negative_number())
.or(relaxed_word())
.or(char('*').with(value("*".to_string())))
};
@@ -250,6 +265,17 @@ fn range<'a>() -> impl Parser<&'a str, Output = UserInputLeaf> {
})
}
/// Function that parses a set out of a Stream
/// Supports ranges like: `IN [val1 val2 val3]`
fn set<'a>() -> impl Parser<&'a str, Output = UserInputLeaf> {
let term_list = between(char('['), char(']'), sep_by(term_val(), spaces()));
let set_content = ((string("IN"), spaces()), term_list).map(|(_, elements)| elements);
(optional(attempt(field_name().skip(spaces()))), set_content)
.map(|(field, elements)| UserInputLeaf::Set { field, elements })
}
fn negate(expr: UserInputAst) -> UserInputAst {
expr.unary(Occur::MustNot)
}
@@ -264,6 +290,7 @@ fn leaf<'a>() -> impl Parser<&'a str, Output = UserInputAst> {
string("NOT").skip(spaces1()).with(leaf()).map(negate),
))
.or(attempt(range().map(UserInputAst::from)))
.or(attempt(set().map(UserInputAst::from)))
.or(literal().map(UserInputAst::from))
.parse_stream(input)
.into_result()
@@ -649,6 +676,34 @@ mod test {
.expect("Cannot parse date range")
.0;
assert_eq!(res6, expected_flexible_dates);
// IP Range Unbounded
let expected_weight = UserInputLeaf::Range {
field: Some("ip".to_string()),
lower: UserInputBound::Inclusive("::1".to_string()),
upper: UserInputBound::Unbounded,
};
let res1 = range()
.parse("ip: >=::1")
.expect("Cannot parse ip v6 format")
.0;
let res2 = range()
.parse("ip:[::1 TO *}")
.expect("Cannot parse ip v6 format")
.0;
assert_eq!(res1, expected_weight);
assert_eq!(res2, expected_weight);
// IP Range Bounded
let expected_weight = UserInputLeaf::Range {
field: Some("ip".to_string()),
lower: UserInputBound::Inclusive("::0.0.0.50".to_string()),
upper: UserInputBound::Exclusive("::0.0.0.52".to_string()),
};
let res1 = range()
.parse("ip:[::0.0.0.50 TO ::0.0.0.52}")
.expect("Cannot parse ip v6 format")
.0;
assert_eq!(res1, expected_weight);
}
#[test]
@@ -705,6 +760,14 @@ mod test {
test_parse_query_to_ast_helper("+(a b) +d", "(+(*\"a\" *\"b\") +\"d\")");
}
#[test]
fn test_parse_test_query_set() {
test_parse_query_to_ast_helper("abc: IN [a b c]", r#""abc": IN ["a" "b" "c"]"#);
test_parse_query_to_ast_helper("abc: IN [1]", r#""abc": IN ["1"]"#);
test_parse_query_to_ast_helper("abc: IN []", r#""abc": IN []"#);
test_parse_query_to_ast_helper("IN [1 2]", r#"IN ["1" "2"]"#);
}
#[test]
fn test_parse_test_query_other() {
test_parse_query_to_ast_helper("(+a +b) d", "(*(+\"a\" +\"b\") *\"d\")");

17
query-grammar/src/user_input_ast.rs
View File

@@ -12,6 +12,10 @@ pub enum UserInputLeaf {
lower: UserInputBound,
upper: UserInputBound,
},
Set {
field: Option<String>,
elements: Vec<String>,
},
}
impl Debug for UserInputLeaf {
@@ -31,6 +35,19 @@ impl Debug for UserInputLeaf {
upper.display_upper(formatter)?;
Ok(())
}
UserInputLeaf::Set { field, elements } => {
if let Some(ref field) = field {
write!(formatter, "\"{}\": ", field)?;
}
write!(formatter, "IN [")?;
for (i, element) in elements.iter().enumerate() {
if i != 0 {
write!(formatter, " ")?;
}
write!(formatter, "\"{}\"", element)?;
}
write!(formatter, "]")
}
UserInputLeaf::All => write!(formatter, "*"),
}
}

14
src/aggregation/agg_req.rs
View File

@@ -1,7 +1,7 @@
//! Contains the aggregation request tree. Used to build an
//! [AggregationCollector](super::AggregationCollector).
//! [`AggregationCollector`](super::AggregationCollector).
//!
//! [Aggregations] is the top level entry point to create a request, which is a `HashMap<String,
//! [`Aggregations`] is the top level entry point to create a request, which is a `HashMap<String,
//! Aggregation>`.
//!
//! Requests are compatible with the json format of elasticsearch.
@@ -54,8 +54,8 @@ use super::bucket::{HistogramAggregation, TermsAggregation};
use super::metric::{AverageAggregation, StatsAggregation};
use super::VecWithNames;
/// The top-level aggregation request structure, which contains [Aggregation] and their user defined
/// names. It is also used in [buckets](BucketAggregation) to define sub-aggregations.
/// The top-level aggregation request structure, which contains [`Aggregation`] and their user
/// defined names. It is also used in [buckets](BucketAggregation) to define sub-aggregations.
///
/// The key is the user defined name of the aggregation.
pub type Aggregations = HashMap<String, Aggregation>;
@@ -139,15 +139,15 @@ pub fn get_fast_field_names(aggs: &Aggregations) -> HashSet<String> {
fast_field_names
}
/// Aggregation request of [BucketAggregation] or [MetricAggregation].
/// Aggregation request of [`BucketAggregation`] or [`MetricAggregation`].
///
/// An aggregation is either a bucket or a metric.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
#[serde(untagged)]
pub enum Aggregation {
/// Bucket aggregation, see [BucketAggregation] for details.
/// Bucket aggregation, see [`BucketAggregation`] for details.
Bucket(BucketAggregation),
/// Metric aggregation, see [MetricAggregation] for details.
/// Metric aggregation, see [`MetricAggregation`] for details.
Metric(MetricAggregation),
}

23
src/aggregation/agg_req_with_accessor.rs
View File

@@ -4,14 +4,14 @@ use std::rc::Rc;
use std::sync::atomic::AtomicU32;
use std::sync::Arc;
use fastfield_codecs::OptionalColumn;
use super::agg_req::{Aggregation, Aggregations, BucketAggregationType, MetricAggregation};
use super::bucket::{HistogramAggregation, RangeAggregation, TermsAggregation};
use super::metric::{AverageAggregation, StatsAggregation};
use super::segment_agg_result::BucketCount;
use super::VecWithNames;
use crate::fastfield::{
type_and_cardinality, DynamicFastFieldReader, FastType, MultiValuedFastFieldReader,
};
use crate::fastfield::{type_and_cardinality, FastType, MultiValuedFastFieldReader};
use crate::schema::{Cardinality, Type};
use crate::{InvertedIndexReader, SegmentReader, TantivyError};
@@ -37,10 +37,16 @@ impl AggregationsWithAccessor {
#[derive(Clone)]
pub(crate) enum FastFieldAccessor {
Multi(MultiValuedFastFieldReader<u64>),
Single(DynamicFastFieldReader<u64>),
Single(Arc<dyn OptionalColumn<u64>>),
}
impl FastFieldAccessor {
pub fn as_single(&self) -> Option<&DynamicFastFieldReader<u64>> {
pub fn as_single(&self) -> Option<&dyn OptionalColumn<u64>> {
match self {
FastFieldAccessor::Multi(_) => None,
FastFieldAccessor::Single(reader) => Some(&**reader),
}
}
pub fn into_single(self) -> Option<Arc<dyn OptionalColumn<u64>>> {
match self {
FastFieldAccessor::Multi(_) => None,
FastFieldAccessor::Single(reader) => Some(reader),
@@ -118,7 +124,7 @@ impl BucketAggregationWithAccessor {
pub struct MetricAggregationWithAccessor {
pub metric: MetricAggregation,
pub field_type: Type,
pub accessor: DynamicFastFieldReader<u64>,
pub accessor: Arc<dyn OptionalColumn>,
}
impl MetricAggregationWithAccessor {
@@ -134,9 +140,8 @@ impl MetricAggregationWithAccessor {
Ok(MetricAggregationWithAccessor {
accessor: accessor
.as_single()
.expect("unexpected fast field cardinality")
.clone(),
.into_single()
.expect("unexpected fast field cardinality"),
field_type,
metric: metric.clone(),
})

16
src/aggregation/agg_result.rs
View File

@@ -4,9 +4,7 @@
//! intermediate average results, which is the sum and the number of values. The actual average is
//! calculated on the step from intermediate to final aggregation result tree.
use std::collections::HashMap;
use fnv::FnvHashMap;
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use super::agg_req::BucketAggregationInternal;
@@ -18,7 +16,7 @@ use crate::TantivyError;
#[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
/// The final aggegation result.
pub struct AggregationResults(pub HashMap<String, AggregationResult>);
pub struct AggregationResults(pub FxHashMap<String, AggregationResult>);
impl AggregationResults {
pub(crate) fn get_value_from_aggregation(
@@ -113,14 +111,14 @@ pub enum BucketResult {
///
/// If there are holes depends on the request, if min_doc_count is 0, then there are no
/// holes between the first and last bucket.
/// See [HistogramAggregation](super::bucket::HistogramAggregation)
/// See [`HistogramAggregation`](super::bucket::HistogramAggregation)
buckets: BucketEntries<BucketEntry>,
},
/// This is the term result
Terms {
/// The buckets.
///
/// See [TermsAggregation](super::bucket::TermsAggregation)
/// See [`TermsAggregation`](super::bucket::TermsAggregation)
buckets: Vec<BucketEntry>,
/// The number of documents that didn’t make it into to TOP N due to shard_size or size
sum_other_doc_count: u64,
@@ -145,7 +143,7 @@ pub enum BucketEntries<T> {
/// Vector format bucket entries
Vec(Vec<T>),
/// HashMap format bucket entries
HashMap(FnvHashMap<String, T>),
HashMap(FxHashMap<String, T>),
}
/// This is the default entry for a bucket, which contains a key, count, and optionally
@@ -234,10 +232,10 @@ pub struct RangeBucketEntry {
#[serde(flatten)]
/// sub-aggregations in this bucket.
pub sub_aggregation: AggregationResults,
/// The from range of the bucket. Equals f64::MIN when None.
/// The from range of the bucket. Equals `f64::MIN` when `None`.
#[serde(skip_serializing_if = "Option::is_none")]
pub from: Option<f64>,
/// The to range of the bucket. Equals f64::MAX when None.
/// The to range of the bucket. Equals `f64::MAX` when `None`.
#[serde(skip_serializing_if = "Option::is_none")]
pub to: Option<f64>,
}

123
src/aggregation/bucket/histogram/histogram.rs
View File

@@ -1,6 +1,7 @@
use std::cmp::Ordering;
use std::fmt::Display;
use fastfield_codecs::OptionalColumn;
use itertools::Itertools;
use serde::{Deserialize, Serialize};
@@ -14,7 +15,6 @@ use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResults, IntermediateBucketResult, IntermediateHistogramBucketEntry,
};
use crate::aggregation::segment_agg_result::SegmentAggregationResultsCollector;
use crate::fastfield::{DynamicFastFieldReader, FastFieldReader};
use crate::schema::Type;
use crate::{DocId, TantivyError};
@@ -37,14 +37,14 @@ use crate::{DocId, TantivyError};
/// [hard_bounds](HistogramAggregation::hard_bounds).
///
/// # Result
/// Result type is [BucketResult](crate::aggregation::agg_result::BucketResult) with
/// [BucketEntry](crate::aggregation::agg_result::BucketEntry) on the
/// AggregationCollector.
/// Result type is [`BucketResult`](crate::aggregation::agg_result::BucketResult) with
/// [`BucketEntry`](crate::aggregation::agg_result::BucketEntry) on the
/// `AggregationCollector`.
///
/// Result type is
/// [crate::aggregation::intermediate_agg_result::IntermediateBucketResult] with
/// [crate::aggregation::intermediate_agg_result::IntermediateHistogramBucketEntry] on the
/// DistributedAggregationCollector.
/// [`IntermediateBucketResult`](crate::aggregation::intermediate_agg_result::IntermediateBucketResult) with
/// [`IntermediateHistogramBucketEntry`](crate::aggregation::intermediate_agg_result::IntermediateHistogramBucketEntry) on the
/// `DistributedAggregationCollector`.
///
/// # Limitations/Compatibility
///
@@ -61,7 +61,7 @@ use crate::{DocId, TantivyError};
/// ```
///
/// Response
/// See [BucketEntry](crate::aggregation::agg_result::BucketEntry)
/// See [`BucketEntry`](crate::aggregation::agg_result::BucketEntry)
#[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize)]
pub struct HistogramAggregation {
@@ -263,13 +263,17 @@ impl SegmentHistogramCollector {
req: &HistogramAggregation,
sub_aggregation: &AggregationsWithAccessor,
field_type: Type,
accessor: &DynamicFastFieldReader<u64>,
accessor: &dyn OptionalColumn<u64>,
) -> crate::Result<Self> {
req.validate()?;
let min = f64_from_fastfield_u64(accessor.min_value(), &field_type);
let max = f64_from_fastfield_u64(accessor.max_value(), &field_type);
let min_max_u64 = accessor.min_value().zip(accessor.max_value());
let min_max_f64 = min_max_u64.map(|(min, max)| {
let min = f64_from_fastfield_u64(min, &field_type);
let max = f64_from_fastfield_u64(max, &field_type);
(min, max)
});
let (min, max) = get_req_min_max(req, Some((min, max)));
let (min, max) = get_req_min_max(req, min_max_f64);
// We compute and generate the buckets range (min, max) based on the request and the min
// max in the fast field, but this is likely not ideal when this is a subbucket, where many
@@ -331,47 +335,58 @@ impl SegmentHistogramCollector {
.expect("unexpected fast field cardinatility");
let mut iter = doc.chunks_exact(4);
for docs in iter.by_ref() {
let val0 = self.f64_from_fastfield_u64(accessor.get(docs[0]));
let val1 = self.f64_from_fastfield_u64(accessor.get(docs[1]));
let val2 = self.f64_from_fastfield_u64(accessor.get(docs[2]));
let val3 = self.f64_from_fastfield_u64(accessor.get(docs[3]));
if let Some(val) = accessor.get_val(docs[0]) {
let val = self.f64_from_fastfield_u64(val);
let bucket_pos = get_bucket_num(val);
self.increment_bucket_if_in_bounds(
val,
&bounds,
bucket_pos,
docs[0],
&bucket_with_accessor.sub_aggregation,
)?;
}
let bucket_pos0 = get_bucket_num(val0);
let bucket_pos1 = get_bucket_num(val1);
let bucket_pos2 = get_bucket_num(val2);
let bucket_pos3 = get_bucket_num(val3);
if let Some(val) = accessor.get_val(docs[1]) {
let val = self.f64_from_fastfield_u64(val);
let bucket_pos = get_bucket_num(val);
self.increment_bucket_if_in_bounds(
val,
&bounds,
bucket_pos,
docs[1],
&bucket_with_accessor.sub_aggregation,
)?;
}
self.increment_bucket_if_in_bounds(
val0,
&bounds,
bucket_pos0,
docs[0],
&bucket_with_accessor.sub_aggregation,
)?;
self.increment_bucket_if_in_bounds(
val1,
&bounds,
bucket_pos1,
docs[1],
&bucket_with_accessor.sub_aggregation,
)?;
self.increment_bucket_if_in_bounds(
val2,
&bounds,
bucket_pos2,
docs[2],
&bucket_with_accessor.sub_aggregation,
)?;
self.increment_bucket_if_in_bounds(
val3,
&bounds,
bucket_pos3,
docs[3],
&bucket_with_accessor.sub_aggregation,
)?;
if let Some(val) = accessor.get_val(docs[2]) {
let val = self.f64_from_fastfield_u64(val);
let bucket_pos = get_bucket_num(val);
self.increment_bucket_if_in_bounds(
val,
&bounds,
bucket_pos,
docs[2],
&bucket_with_accessor.sub_aggregation,
)?;
}
if let Some(val) = accessor.get_val(docs[3]) {
let val = self.f64_from_fastfield_u64(val);
let bucket_pos = get_bucket_num(val);
self.increment_bucket_if_in_bounds(
val,
&bounds,
bucket_pos,
docs[3],
&bucket_with_accessor.sub_aggregation,
)?;
}
}
for doc in iter.remainder() {
let val = f64_from_fastfield_u64(accessor.get(*doc), &self.field_type);
for &doc in iter.remainder() {
let Some(val) = accessor.get_val(doc).map(|val|f64_from_fastfield_u64(val, &self.field_type)) else{
continue;
};
if !bounds.contains(val) {
continue;
}
@@ -382,7 +397,7 @@ impl SegmentHistogramCollector {
self.buckets[bucket_pos].key,
get_bucket_val(val, self.interval, self.offset) as f64
);
self.increment_bucket(bucket_pos, *doc, &bucket_with_accessor.sub_aggregation)?;
self.increment_bucket(bucket_pos, doc, &bucket_with_accessor.sub_aggregation)?;
}
if force_flush {
if let Some(sub_aggregations) = self.sub_aggregations.as_mut() {
@@ -425,7 +440,7 @@ impl SegmentHistogramCollector {
let bucket = &mut self.buckets[bucket_pos];
bucket.doc_count += 1;
if let Some(sub_aggregation) = self.sub_aggregations.as_mut() {
(&mut sub_aggregation[bucket_pos]).collect(doc, bucket_with_accessor)?;
sub_aggregation[bucket_pos].collect(doc, bucket_with_accessor)?;
}
Ok(())
}
@@ -452,7 +467,7 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
histogram_req: &HistogramAggregation,
sub_aggregation: &AggregationsInternal,
) -> crate::Result<Vec<BucketEntry>> {
// Generate the the full list of buckets without gaps.
// Generate the full list of buckets without gaps.
//
// The bounds are the min max from the current buckets, optionally extended by
// extended_bounds from the request
@@ -518,7 +533,7 @@ pub(crate) fn intermediate_histogram_buckets_to_final_buckets(
/// Applies req extended_bounds/hard_bounds on the min_max value
///
/// May return (f64::MAX, f64::MIN), if there is no range.
/// May return `(f64::MAX, f64::MIN)`, if there is no range.
fn get_req_min_max(req: &HistogramAggregation, min_max: Option<(f64, f64)>) -> (f64, f64) {
let (mut min, mut max) = min_max.unwrap_or((f64::MAX, f64::MIN));

6
src/aggregation/bucket/mod.rs
View File

@@ -1,11 +1,11 @@
//! Module for all bucket aggregations.
//!
//! BucketAggregations create buckets of documents
//! [BucketAggregation](super::agg_req::BucketAggregation).
//! [`BucketAggregation`](super::agg_req::BucketAggregation).
//!
//! Results of final buckets are [BucketResult](super::agg_result::BucketResult).
//! Results of final buckets are [`BucketResult`](super::agg_result::BucketResult).
//! Results of intermediate buckets are
//! [IntermediateBucketResult](super::intermediate_agg_result::IntermediateBucketResult)
//! [`IntermediateBucketResult`](super::intermediate_agg_result::IntermediateBucketResult)
mod histogram;
mod range;

79
src/aggregation/bucket/range.rs
View File

@@ -1,7 +1,7 @@
use std::fmt::Debug;
use std::ops::Range;
use fnv::FnvHashMap;
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use crate::aggregation::agg_req_with_accessor::{
@@ -12,7 +12,6 @@ use crate::aggregation::intermediate_agg_result::{
};
use crate::aggregation::segment_agg_result::{BucketCount, SegmentAggregationResultsCollector};
use crate::aggregation::{f64_from_fastfield_u64, f64_to_fastfield_u64, Key, SerializedKey};
use crate::fastfield::FastFieldReader;
use crate::schema::Type;
use crate::{DocId, TantivyError};
@@ -23,14 +22,14 @@ use crate::{DocId, TantivyError};
/// against each bucket range. Note that this aggregation includes the from value and excludes the
/// to value for each range.
///
/// Result type is [BucketResult](crate::aggregation::agg_result::BucketResult) with
/// [RangeBucketEntry](crate::aggregation::agg_result::RangeBucketEntry) on the
/// AggregationCollector.
/// Result type is [`BucketResult`](crate::aggregation::agg_result::BucketResult) with
/// [`RangeBucketEntry`](crate::aggregation::agg_result::RangeBucketEntry) on the
/// `AggregationCollector`.
///
/// Result type is
/// [crate::aggregation::intermediate_agg_result::IntermediateBucketResult] with
/// [crate::aggregation::intermediate_agg_result::IntermediateRangeBucketEntry] on the
/// DistributedAggregationCollector.
/// [`IntermediateBucketResult`](crate::aggregation::intermediate_agg_result::IntermediateBucketResult) with
/// [`IntermediateRangeBucketEntry`](crate::aggregation::intermediate_agg_result::IntermediateRangeBucketEntry) on the
/// `DistributedAggregationCollector`.
///
/// # Limitations/Compatibility
/// Overlapping ranges are not yet supported.
@@ -68,11 +67,11 @@ pub struct RangeAggregationRange {
#[serde(skip_serializing_if = "Option::is_none", default)]
pub key: Option<String>,
/// The from range value, which is inclusive in the range.
/// None equals to an open ended interval.
/// `None` equals to an open ended interval.
#[serde(skip_serializing_if = "Option::is_none", default)]
pub from: Option<f64>,
/// The to range value, which is not inclusive in the range.
/// None equals to an open ended interval.
/// `None` equals to an open ended interval.
#[serde(skip_serializing_if = "Option::is_none", default)]
pub to: Option<f64>,
}
@@ -102,7 +101,7 @@ impl From<Range<f64>> for RangeAggregationRange {
pub(crate) struct InternalRangeAggregationRange {
/// Custom key for the range bucket
key: Option<String>,
/// u64 range value
/// `u64` range value
range: Range<u64>,
}
@@ -132,9 +131,9 @@ pub(crate) struct SegmentRangeBucketEntry {
pub key: Key,
pub doc_count: u64,
pub sub_aggregation: Option<SegmentAggregationResultsCollector>,
/// The from range of the bucket. Equals f64::MIN when None.
/// 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
/// The to range of the bucket. Equals `f64::MAX` when `None`. Open interval, `to` is not
/// inclusive.
pub to: Option<f64>,
}
@@ -177,7 +176,7 @@ impl SegmentRangeCollector {
) -> crate::Result<IntermediateBucketResult> {
let field_type = self.field_type;
let buckets: FnvHashMap<SerializedKey, IntermediateRangeBucketEntry> = self
let buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry> = self
.buckets
.into_iter()
.map(move |range_bucket| {
@@ -262,26 +261,35 @@ impl SegmentRangeCollector {
let accessor = bucket_with_accessor
.accessor
.as_single()
.expect("unexpected fast field cardinatility");
.expect("unexpected fast field cardinality");
for docs in iter.by_ref() {
let val1 = accessor.get(docs[0]);
let val2 = accessor.get(docs[1]);
let val3 = accessor.get(docs[2]);
let val4 = accessor.get(docs[3]);
let bucket_pos1 = self.get_bucket_pos(val1);
let bucket_pos2 = self.get_bucket_pos(val2);
let bucket_pos3 = self.get_bucket_pos(val3);
let bucket_pos4 = self.get_bucket_pos(val4);
self.increment_bucket(bucket_pos1, docs[0], &bucket_with_accessor.sub_aggregation)?;
self.increment_bucket(bucket_pos2, docs[1], &bucket_with_accessor.sub_aggregation)?;
self.increment_bucket(bucket_pos3, docs[2], &bucket_with_accessor.sub_aggregation)?;
self.increment_bucket(bucket_pos4, docs[3], &bucket_with_accessor.sub_aggregation)?;
let val1 = accessor.get_val(docs[0]);
let val2 = accessor.get_val(docs[1]);
let val3 = accessor.get_val(docs[2]);
let val4 = accessor.get_val(docs[3]);
if let Some(val) = val1 {
let bucket_pos = self.get_bucket_pos(val);
self.increment_bucket(bucket_pos, docs[0], &bucket_with_accessor.sub_aggregation)?;
}
if let Some(val) = val2 {
let bucket_pos = self.get_bucket_pos(val);
self.increment_bucket(bucket_pos, docs[1], &bucket_with_accessor.sub_aggregation)?;
}
if let Some(val) = val3 {
let bucket_pos = self.get_bucket_pos(val);
self.increment_bucket(bucket_pos, docs[2], &bucket_with_accessor.sub_aggregation)?;
}
if let Some(val) = val4 {
let bucket_pos = self.get_bucket_pos(val);
self.increment_bucket(bucket_pos, docs[3], &bucket_with_accessor.sub_aggregation)?;
}
}
for doc in iter.remainder() {
let val = accessor.get(*doc);
let bucket_pos = self.get_bucket_pos(val);
self.increment_bucket(bucket_pos, *doc, &bucket_with_accessor.sub_aggregation)?;
for &doc in iter.remainder() {
let val = accessor.get_val(doc);
if let Some(val) = val {
let bucket_pos = self.get_bucket_pos(val);
self.increment_bucket(bucket_pos, doc, &bucket_with_accessor.sub_aggregation)?;
}
}
if force_flush {
for bucket in &mut self.buckets {
@@ -324,8 +332,8 @@ impl SegmentRangeCollector {
/// Converts the user provided f64 range value to fast field value space.
///
/// Internally fast field values are always stored as u64.
/// If the fast field has u64 [1,2,5], these values are stored as is in the fast field.
/// A fast field with f64 [1.0, 2.0, 5.0] is converted to u64 space, using a
/// If the fast field has u64 `[1, 2, 5]`, these values are stored as is in the fast field.
/// A fast field with f64 `[1.0, 2.0, 5.0]` is converted to u64 space, using a
/// monotonic mapping function, so the order is preserved.
///
/// Consequently, a f64 user range 1.0..3.0 needs to be converted to fast field value space using
@@ -424,12 +432,13 @@ pub(crate) fn range_to_key(range: &Range<u64>, field_type: &Type) -> Key {
#[cfg(test)]
mod tests {
use fastfield_codecs::MonotonicallyMappableToU64;
use super::*;
use crate::aggregation::agg_req::{
Aggregation, Aggregations, BucketAggregation, BucketAggregationType,
};
use crate::aggregation::tests::{exec_request_with_query, get_test_index_with_num_docs};
use crate::fastfield::FastValue;
pub fn get_collector_from_ranges(
ranges: Vec<RangeAggregationRange>,

81
src/aggregation/bucket/term_agg.rs
View File

@@ -1,7 +1,7 @@
use std::fmt::Debug;
use fnv::FnvHashMap;
use itertools::Itertools;
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use super::{CustomOrder, Order, OrderTarget};
@@ -17,7 +17,11 @@ use crate::fastfield::MultiValuedFastFieldReader;
use crate::schema::Type;
use crate::{DocId, TantivyError};
/// Creates a bucket for every unique term
/// Creates a bucket for every unique term and counts the number of occurences.
/// Note that doc_count in the response buckets equals term count here.
///
/// If the text is untokenized and single value, that means one term per document and therefore it
/// is in fact doc count.
///
/// ### Terminology
/// Shard parameters are supposed to be equivalent to elasticsearch shard parameter.
@@ -31,7 +35,7 @@ use crate::{DocId, TantivyError};
///
/// Even with a larger `segment_size` value, doc_count values for a terms aggregation may be
/// approximate. As a result, any sub-aggregations on the terms aggregation may also be approximate.
/// `sum_other_doc_count` is the number of documents that didn’t make it into the the top size
/// `sum_other_doc_count` is the number of documents that didn’t make it into the top size
/// terms. If this is greater than 0, you can be sure that the terms agg had to throw away some
/// buckets, either because they didn’t fit into size on the root node or they didn’t fit into
/// `segment_size` on the segment node.
@@ -42,14 +46,14 @@ use crate::{DocId, TantivyError};
/// each segment. It’s the sum of the size of the largest bucket on each segment that didn’t fit
/// into segment_size.
///
/// Result type is [BucketResult](crate::aggregation::agg_result::BucketResult) with
/// [TermBucketEntry](crate::aggregation::agg_result::BucketEntry) on the
/// AggregationCollector.
/// Result type is [`BucketResult`](crate::aggregation::agg_result::BucketResult) with
/// [`TermBucketEntry`](crate::aggregation::agg_result::BucketEntry) on the
/// `AggregationCollector`.
///
/// Result type is
/// [crate::aggregation::intermediate_agg_result::IntermediateBucketResult] with
/// [crate::aggregation::intermediate_agg_result::IntermediateTermBucketEntry] on the
/// DistributedAggregationCollector.
/// [`IntermediateBucketResult`](crate::aggregation::intermediate_agg_result::IntermediateBucketResult) with
/// [`IntermediateTermBucketEntry`](crate::aggregation::intermediate_agg_result::IntermediateTermBucketEntry) on the
/// `DistributedAggregationCollector`.
///
/// # Limitations/Compatibility
///
@@ -64,6 +68,25 @@ use crate::{DocId, TantivyError};
/// }
/// }
/// ```
///
/// /// # Response JSON Format
/// ```json
/// {
/// ...
/// "aggregations": {
/// "genres": {
/// "doc_count_error_upper_bound": 0,
/// "sum_other_doc_count": 0,
/// "buckets": [
/// { "key": "drumnbass", "doc_count": 6 },
/// { "key": "raggae", "doc_count": 4 },
/// { "key": "jazz", "doc_count": 2 }
/// ]
/// }
/// }
/// }
/// ```
#[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize)]
pub struct TermsAggregation {
/// The field to aggregate on.
@@ -176,7 +199,7 @@ impl TermsAggregationInternal {
#[derive(Clone, Debug, PartialEq)]
/// Container to store term_ids and their buckets.
struct TermBuckets {
pub(crate) entries: FnvHashMap<u32, TermBucketEntry>,
pub(crate) entries: FxHashMap<u32, TermBucketEntry>,
blueprint: Option<SegmentAggregationResultsCollector>,
}
@@ -374,7 +397,7 @@ impl SegmentTermCollector {
.expect("internal error: inverted index not loaded for term aggregation");
let term_dict = inverted_index.terms();
let mut dict: FnvHashMap<String, IntermediateTermBucketEntry> = Default::default();
let mut dict: FxHashMap<String, IntermediateTermBucketEntry> = Default::default();
let mut buffer = vec![];
for (term_id, entry) in entries {
term_dict
@@ -1106,9 +1129,9 @@ mod tests {
assert_eq!(res["my_texts"]["buckets"][0]["key"], "terma");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 4);
assert_eq!(res["my_texts"]["buckets"][1]["key"], "termb");
assert_eq!(res["my_texts"]["buckets"][1]["key"], "termc");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 0);
assert_eq!(res["my_texts"]["buckets"][2]["key"], "termc");
assert_eq!(res["my_texts"]["buckets"][2]["key"], "termb");
assert_eq!(res["my_texts"]["buckets"][2]["doc_count"], 0);
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
@@ -1206,11 +1229,43 @@ mod tests {
.collect();
let res = exec_request_with_query(agg_req, &index, None);
assert!(res.is_err());
Ok(())
}
#[test]
fn terms_aggregation_multi_token_per_doc() -> crate::Result<()> {
let terms = vec!["Hello Hello", "Hallo Hallo"];
let index = get_test_index_from_terms(true, &[terms])?;
let agg_req: Aggregations = vec![(
"my_texts".to_string(),
Aggregation::Bucket(BucketAggregation {
bucket_agg: BucketAggregationType::Terms(TermsAggregation {
field: "text_id".to_string(),
min_doc_count: Some(0),
..Default::default()
}),
sub_aggregation: Default::default(),
}),
)]
.into_iter()
.collect();
let res = exec_request_with_query(agg_req, &index, None).unwrap();
assert_eq!(res["my_texts"]["buckets"][0]["key"], "hello");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 2);
assert_eq!(res["my_texts"]["buckets"][1]["key"], "hallo");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 2);
Ok(())
}
#[test]
fn test_json_format() -> crate::Result<()> {
let agg_req: Aggregations = vec![(

6
src/aggregation/collector.rs
View File

@@ -131,7 +131,7 @@ fn merge_fruits(
}
}
/// AggregationSegmentCollector does the aggregation collection on a segment.
/// `AggregationSegmentCollector` does the aggregation collection on a segment.
pub struct AggregationSegmentCollector {
aggs_with_accessor: AggregationsWithAccessor,
result: SegmentAggregationResultsCollector,
@@ -139,8 +139,8 @@ pub struct AggregationSegmentCollector {
}
impl AggregationSegmentCollector {
/// Creates an AggregationSegmentCollector from an [Aggregations] request and a segment reader.
/// Also includes validation, e.g. checking field types and existence.
/// Creates an `AggregationSegmentCollector from` an [`Aggregations`] request and a segment
/// reader. Also includes validation, e.g. checking field types and existence.
pub fn from_agg_req_and_reader(
agg: &Aggregations,
reader: &SegmentReader,

37
src/aggregation/intermediate_agg_result.rs
View File

@@ -3,10 +3,9 @@
//! indices.
use std::cmp::Ordering;
use std::collections::HashMap;
use fnv::FnvHashMap;
use itertools::Itertools;
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use super::agg_req::{
@@ -51,7 +50,7 @@ impl IntermediateAggregationResults {
// Important assumption:
// When the tree contains buckets/metric, we expect it to have all buckets/metrics from the
// request
let mut results: HashMap<String, AggregationResult> = HashMap::new();
let mut results: FxHashMap<String, AggregationResult> = FxHashMap::default();
if let Some(buckets) = self.buckets {
convert_and_add_final_buckets_to_result(&mut results, buckets, &req.buckets)?
@@ -108,10 +107,10 @@ impl IntermediateAggregationResults {
Self { metrics, buckets }
}
/// Merge an other intermediate aggregation result into this result.
/// Merge another intermediate aggregation result into this result.
///
/// The order of the values need to be the same on both results. This is ensured when the same
/// (key values) are present on the underlying VecWithNames struct.
/// (key values) are present on the underlying `VecWithNames` struct.
pub fn merge_fruits(&mut self, other: IntermediateAggregationResults) {
if let (Some(buckets_left), Some(buckets_right)) = (&mut self.buckets, other.buckets) {
for (bucket_left, bucket_right) in
@@ -132,7 +131,7 @@ impl IntermediateAggregationResults {
}
fn convert_and_add_final_metrics_to_result(
results: &mut HashMap<String, AggregationResult>,
results: &mut FxHashMap<String, AggregationResult>,
metrics: VecWithNames<IntermediateMetricResult>,
) {
results.extend(
@@ -143,7 +142,7 @@ fn convert_and_add_final_metrics_to_result(
}
fn add_empty_final_metrics_to_result(
results: &mut HashMap<String, AggregationResult>,
results: &mut FxHashMap<String, AggregationResult>,
req_metrics: &VecWithNames<MetricAggregation>,
) -> crate::Result<()> {
results.extend(req_metrics.iter().map(|(key, req)| {
@@ -157,7 +156,7 @@ fn add_empty_final_metrics_to_result(
}
fn add_empty_final_buckets_to_result(
results: &mut HashMap<String, AggregationResult>,
results: &mut FxHashMap<String, AggregationResult>,
req_buckets: &VecWithNames<BucketAggregationInternal>,
) -> crate::Result<()> {
let requested_buckets = req_buckets.iter();
@@ -169,7 +168,7 @@ fn add_empty_final_buckets_to_result(
}
fn convert_and_add_final_buckets_to_result(
results: &mut HashMap<String, AggregationResult>,
results: &mut FxHashMap<String, AggregationResult>,
buckets: VecWithNames<IntermediateBucketResult>,
req_buckets: &VecWithNames<BucketAggregationInternal>,
) -> crate::Result<()> {
@@ -288,7 +287,7 @@ impl IntermediateBucketResult {
.keyed;
let buckets = if is_keyed {
let mut bucket_map =
FnvHashMap::with_capacity_and_hasher(buckets.len(), Default::default());
FxHashMap::with_capacity_and_hasher(buckets.len(), Default::default());
for bucket in buckets {
bucket_map.insert(bucket.key.to_string(), bucket);
}
@@ -308,7 +307,7 @@ impl IntermediateBucketResult {
let buckets = if req.as_histogram().unwrap().keyed {
let mut bucket_map =
FnvHashMap::with_capacity_and_hasher(buckets.len(), Default::default());
FxHashMap::with_capacity_and_hasher(buckets.len(), Default::default());
for bucket in buckets {
bucket_map.insert(bucket.key.to_string(), bucket);
}
@@ -396,13 +395,13 @@ impl IntermediateBucketResult {
#[derive(Default, Clone, Debug, PartialEq, Serialize, Deserialize)]
/// Range aggregation including error counts
pub struct IntermediateRangeBucketResult {
pub(crate) buckets: FnvHashMap<SerializedKey, IntermediateRangeBucketEntry>,
pub(crate) buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry>,
}
#[derive(Default, Clone, Debug, PartialEq, Serialize, Deserialize)]
/// Term aggregation including error counts
pub struct IntermediateTermBucketResult {
pub(crate) entries: FnvHashMap<String, IntermediateTermBucketEntry>,
pub(crate) entries: FxHashMap<String, IntermediateTermBucketEntry>,
pub(crate) sum_other_doc_count: u64,
pub(crate) doc_count_error_upper_bound: u64,
}
@@ -499,8 +498,8 @@ trait MergeFruits {
}
fn merge_maps<V: MergeFruits + Clone>(
entries_left: &mut FnvHashMap<SerializedKey, V>,
mut entries_right: FnvHashMap<SerializedKey, V>,
entries_left: &mut FxHashMap<SerializedKey, V>,
mut entries_right: FxHashMap<SerializedKey, V>,
) {
for (name, entry_left) in entries_left.iter_mut() {
if let Some(entry_right) = entries_right.remove(name) {
@@ -560,10 +559,10 @@ pub struct IntermediateRangeBucketEntry {
pub doc_count: u64,
/// The sub_aggregation in this bucket.
pub sub_aggregation: IntermediateAggregationResults,
/// The from range of the bucket. Equals f64::MIN when None.
/// The from range of the bucket. Equals `f64::MIN` when `None`.
#[serde(skip_serializing_if = "Option::is_none")]
pub from: Option<f64>,
/// The to range of the bucket. Equals f64::MAX when None.
/// The to range of the bucket. Equals `f64::MAX` when `None`.
#[serde(skip_serializing_if = "Option::is_none")]
pub to: Option<f64>,
}
@@ -626,7 +625,7 @@ mod tests {
fn get_sub_test_tree(data: &[(String, u64)]) -> IntermediateAggregationResults {
let mut map = HashMap::new();
let mut buckets = FnvHashMap::default();
let mut buckets = FxHashMap::default();
for (key, doc_count) in data {
buckets.insert(
key.to_string(),
@@ -653,7 +652,7 @@ mod tests {
data: &[(String, u64, String, u64)],
) -> IntermediateAggregationResults {
let mut map = HashMap::new();
let mut buckets: FnvHashMap<_, _> = Default::default();
let mut buckets: FxHashMap<_, _> = Default::default();
for (key, doc_count, sub_aggregation_key, sub_aggregation_count) in data {
buckets.insert(
key.to_string(),

43
src/aggregation/metric/average.rs
View File

@@ -1,9 +1,9 @@
use std::fmt::Debug;
use fastfield_codecs::OptionalColumn;
use serde::{Deserialize, Serialize};
use crate::aggregation::f64_from_fastfield_u64;
use crate::fastfield::{DynamicFastFieldReader, FastFieldReader};
use crate::schema::Type;
use crate::DocId;
@@ -57,26 +57,33 @@ impl SegmentAverageCollector {
data: Default::default(),
}
}
pub(crate) fn collect_block(&mut self, doc: &[DocId], field: &DynamicFastFieldReader<u64>) {
pub(crate) fn collect_block(&mut self, doc: &[DocId], field: &dyn OptionalColumn<u64>) {
let mut iter = doc.chunks_exact(4);
for docs in iter.by_ref() {
let val1 = field.get(docs[0]);
let val2 = field.get(docs[1]);
let val3 = field.get(docs[2]);
let val4 = field.get(docs[3]);
let val1 = f64_from_fastfield_u64(val1, &self.field_type);
let val2 = f64_from_fastfield_u64(val2, &self.field_type);
let val3 = f64_from_fastfield_u64(val3, &self.field_type);
let val4 = f64_from_fastfield_u64(val4, &self.field_type);
self.data.collect(val1);
self.data.collect(val2);
self.data.collect(val3);
self.data.collect(val4);
if let Some(val) = field.get_val(docs[0]) {
let val = f64_from_fastfield_u64(val, &self.field_type);
self.data.collect(val);
}
if let Some(val) = field.get_val(docs[1]) {
let val = f64_from_fastfield_u64(val, &self.field_type);
self.data.collect(val);
}
if let Some(val) = field.get_val(docs[2]) {
let val = f64_from_fastfield_u64(val, &self.field_type);
self.data.collect(val);
}
if let Some(val) = field.get_val(docs[3]) {
let val = f64_from_fastfield_u64(val, &self.field_type);
self.data.collect(val);
}
}
for doc in iter.remainder() {
let val = field.get(*doc);
let val = f64_from_fastfield_u64(val, &self.field_type);
self.data.collect(val);
for &doc in iter.remainder() {
if let Some(val) = field.get_val(doc) {
let val = f64_from_fastfield_u64(val, &self.field_type);
self.data.collect(val);
}
}
}
}

51
src/aggregation/metric/stats.rs
View File

@@ -1,14 +1,14 @@
use fastfield_codecs::OptionalColumn;
use serde::{Deserialize, Serialize};
use crate::aggregation::f64_from_fastfield_u64;
use crate::fastfield::{DynamicFastFieldReader, FastFieldReader};
use crate::schema::Type;
use crate::{DocId, TantivyError};
/// A multi-value metric aggregation that computes stats of numeric values that are
/// extracted from the aggregated documents.
/// Supported field types are u64, i64, and f64.
/// See [Stats] for returned statistics.
/// Supported field types are `u64`, `i64`, and `f64`.
/// See [`Stats`] for returned statistics.
///
/// # JSON Format
/// ```json
@@ -43,13 +43,13 @@ pub struct Stats {
pub count: usize,
/// The sum of the fast field values.
pub sum: f64,
/// The standard deviation of the fast field values. None for count == 0.
/// The standard deviation of the fast field values. `None` for count == 0.
pub standard_deviation: Option<f64>,
/// The min value of the fast field values.
pub min: Option<f64>,
/// The max value of the fast field values.
pub max: Option<f64>,
/// The average of the values. None for count == 0.
/// The average of the values. `None` for count == 0.
pub avg: Option<f64>,
}
@@ -70,7 +70,7 @@ impl Stats {
}
}
/// IntermediateStats contains the mergeable version for stats.
/// `IntermediateStats` contains the mergeable version for stats.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct IntermediateStats {
count: usize,
@@ -163,26 +163,31 @@ impl SegmentStatsCollector {
stats: IntermediateStats::default(),
}
}
pub(crate) fn collect_block(&mut self, doc: &[DocId], field: &DynamicFastFieldReader<u64>) {
pub(crate) fn collect_block(&mut self, doc: &[DocId], field: &dyn OptionalColumn<u64>) {
let mut iter = doc.chunks_exact(4);
for docs in iter.by_ref() {
let val1 = field.get(docs[0]);
let val2 = field.get(docs[1]);
let val3 = field.get(docs[2]);
let val4 = field.get(docs[3]);
let val1 = f64_from_fastfield_u64(val1, &self.field_type);
let val2 = f64_from_fastfield_u64(val2, &self.field_type);
let val3 = f64_from_fastfield_u64(val3, &self.field_type);
let val4 = f64_from_fastfield_u64(val4, &self.field_type);
self.stats.collect(val1);
self.stats.collect(val2);
self.stats.collect(val3);
self.stats.collect(val4);
if let Some(val) = field.get_val(docs[0]) {
let val = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val);
}
if let Some(val) = field.get_val(docs[1]) {
let val = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val);
}
if let Some(val) = field.get_val(docs[2]) {
let val = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val);
}
if let Some(val) = field.get_val(docs[3]) {
let val = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val);
}
}
for doc in iter.remainder() {
let val = field.get(*doc);
let val = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val);
for &doc in iter.remainder() {
if let Some(val) = field.get_val(doc) {
let val = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val);
}
}
}
}

64
src/aggregation/mod.rs
View File

@@ -10,20 +10,19 @@
//!
//! There are two categories: [Metrics](metric) and [Buckets](bucket).
//!
//! # Usage
//!
//! ## Prerequisite
//! Currently aggregations work only on [fast fields](`crate::fastfield`). Single value fast fields
//! of type `u64`, `f64`, `i64` and fast fields on text fields.
//!
//! ## Usage
//! To use aggregations, build an aggregation request by constructing
//! [Aggregations](agg_req::Aggregations).
//! Create an [AggregationCollector] from this request. AggregationCollector implements the
//! `Collector` trait and can be passed as collector into `searcher.search()`.
//! [`Aggregations`](agg_req::Aggregations).
//! Create an [`AggregationCollector`] from this request. `AggregationCollector` implements the
//! [`Collector`](crate::collector::Collector) trait and can be passed as collector into
//! [`Searcher::search()`](crate::Searcher::search).
//!
//! #### Limitations
//!
//! Currently aggregations work only on single value fast fields of type u64, f64, i64 and
//! fast fields on text fields.
//!
//! # JSON Format
//! ## JSON Format
//! Aggregations request and result structures de/serialize into elasticsearch compatible JSON.
//!
//! ```verbatim
@@ -34,7 +33,7 @@
//! let json_response_string: String = &serde_json::to_string(&agg_res)?;
//! ```
//!
//! # Supported Aggregations
//! ## Supported Aggregations
//! - [Bucket](bucket)
//! - [Histogram](bucket::HistogramAggregation)
//! - [Range](bucket::RangeAggregation)
@@ -44,8 +43,8 @@
//! - [Stats](metric::StatsAggregation)
//!
//! # Example
//! Compute the average metric, by building [agg_req::Aggregations], which is built from an (String,
//! [agg_req::Aggregation]) iterator.
//! Compute the average metric, by building [`agg_req::Aggregations`], which is built from an
//! `(String, agg_req::Aggregation)` iterator.
//!
//! ```
//! use tantivy::aggregation::agg_req::{Aggregations, Aggregation, MetricAggregation};
@@ -143,15 +142,15 @@
//! ```
//!
//! # Distributed Aggregation
//! When the data is distributed on different [crate::Index] instances, the
//! [DistributedAggregationCollector] provides functionality to merge data between independent
//! When the data is distributed on different [`Index`](crate::Index) instances, the
//! [`DistributedAggregationCollector`] provides functionality to merge data between independent
//! search calls by returning
//! [IntermediateAggregationResults](intermediate_agg_result::IntermediateAggregationResults).
//! IntermediateAggregationResults provides the
//! [merge_fruits](intermediate_agg_result::IntermediateAggregationResults::merge_fruits) method to
//! merge multiple results. The merged result can then be converted into
//! [agg_result::AggregationResults] via the
//! [agg_result::AggregationResults::from_intermediate_and_req] method.
//! [`IntermediateAggregationResults`](intermediate_agg_result::IntermediateAggregationResults).
//! `IntermediateAggregationResults` provides the
//! [`merge_fruits`](intermediate_agg_result::IntermediateAggregationResults::merge_fruits) method
//! to merge multiple results. The merged result can then be converted into
//! [`AggregationResults`](agg_result::AggregationResults) via the
//! [`into_final_bucket_result`](intermediate_agg_result::IntermediateAggregationResults::into_final_bucket_result) method.
pub mod agg_req;
mod agg_req_with_accessor;
@@ -161,7 +160,6 @@ mod collector;
pub mod intermediate_agg_result;
pub mod metric;
mod segment_agg_result;
use std::collections::HashMap;
use std::fmt::Display;
@@ -169,10 +167,10 @@ pub use collector::{
AggregationCollector, AggregationSegmentCollector, DistributedAggregationCollector,
MAX_BUCKET_COUNT,
};
use fastfield_codecs::MonotonicallyMappableToU64;
use itertools::Itertools;
use serde::{Deserialize, Serialize};
use crate::fastfield::FastValue;
use crate::schema::Type;
/// Represents an associative array `(key => values)` in a very efficient manner.
@@ -260,7 +258,7 @@ impl<T: Clone> VecWithNames<T> {
}
}
/// The serialized key is used in a HashMap.
/// The serialized key is used in a `HashMap`.
pub type SerializedKey = String;
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, PartialOrd)]
@@ -269,7 +267,7 @@ pub type SerializedKey = String;
pub enum Key {
/// String key
Str(String),
/// f64 key
/// `f64` key
F64(f64),
}
@@ -282,10 +280,10 @@ impl Display for Key {
}
}
/// Invert of to_fastfield_u64. Used to convert to f64 for metrics.
/// Inverse of `to_fastfield_u64`. Used to convert to `f64` for metrics.
///
/// # Panics
/// Only u64, f64, i64 is supported
/// Only `u64`, `f64`, and `i64` are supported.
pub(crate) fn f64_from_fastfield_u64(val: u64, field_type: &Type) -> f64 {
match field_type {
Type::U64 => val as f64,
@@ -297,15 +295,15 @@ pub(crate) fn f64_from_fastfield_u64(val: u64, field_type: &Type) -> f64 {
}
}
/// Converts the f64 value to fast field value space.
/// Converts the `f64` value to fast field value space.
///
/// If the fast field has u64, values are stored as u64 in the fast field.
/// A f64 value of e.g. 2.0 therefore needs to be converted to 1u64
/// If the fast field has `u64`, values are stored as `u64` in the fast field.
/// A `f64` value of e.g. `2.0` therefore needs to be converted to `1u64`.
///
/// If the fast field has f64 values are converted and stored to u64 using a
/// If the fast field has `f64` values are converted and stored to `u64` using a
/// monotonic mapping.
/// A f64 value of e.g. 2.0 needs to be converted using the same monotonic
/// conversion function, so that the value matches the u64 value stored in the fast
/// A `f64` value of e.g. `2.0` needs to be converted using the same monotonic
/// conversion function, so that the value matches the `u64` value stored in the fast
/// field.
pub(crate) fn f64_to_fastfield_u64(val: f64, field_type: &Type) -> Option<u64> {
match field_type {

4
src/aggregation/segment_agg_result.rs
View File

@@ -185,10 +185,10 @@ impl SegmentMetricResultCollector {
pub(crate) fn collect_block(&mut self, doc: &[DocId], metric: &MetricAggregationWithAccessor) {
match self {
SegmentMetricResultCollector::Average(avg_collector) => {
avg_collector.collect_block(doc, &metric.accessor);
avg_collector.collect_block(doc, &*metric.accessor);
}
SegmentMetricResultCollector::Stats(stats_collector) => {
stats_collector.collect_block(doc, &metric.accessor);
stats_collector.collect_block(doc, &*metric.accessor);
}
}
}

6
src/collector/custom_score_top_collector.rs
View File

@@ -24,7 +24,7 @@ where TScore: Clone + PartialOrd
/// A custom segment scorer makes it possible to define any kind of score
/// for a given document belonging to a specific segment.
///
/// It is the segment local version of the [`CustomScorer`](./trait.CustomScorer.html).
/// It is the segment local version of the [`CustomScorer`].
pub trait CustomSegmentScorer<TScore>: 'static {
/// Computes the score of a specific `doc`.
fn score(&mut self, doc: DocId) -> TScore;
@@ -36,9 +36,9 @@ pub trait CustomSegmentScorer<TScore>: 'static {
/// Instead, it helps constructing `Self::Child` instances that will compute
/// the score at a segment scale.
pub trait CustomScorer<TScore>: Sync {
/// Type of the associated [`CustomSegmentScorer`](./trait.CustomSegmentScorer.html).
/// Type of the associated [`CustomSegmentScorer`].
type Child: CustomSegmentScorer<TScore>;
/// Builds a child scorer for a specific segment. The child scorer is associated to
/// Builds a child scorer for a specific segment. The child scorer is associated with
/// a specific segment.
fn segment_scorer(&self, segment_reader: &SegmentReader) -> crate::Result<Self::Child>;
}

20
src/collector/facet_collector.rs
View File

@@ -67,10 +67,10 @@ fn facet_depth(facet_bytes: &[u8]) -> usize {
/// (e.g. `/category/fiction`, `/category/biography`, `/category/personal_development`).
///
/// Once collection is finished, you can harvest its results in the form
/// of a `FacetCounts` object, and extract your face t counts from it.
/// of a [`FacetCounts`] object, and extract your facet counts from it.
///
/// This implementation assumes you are working with a number of facets that
/// is much hundreds of time lower than your number of documents.
/// is many hundreds of times smaller than your number of documents.
///
///
/// ```rust
@@ -91,7 +91,7 @@ fn facet_depth(facet_bytes: &[u8]) -> usize {
/// let index = Index::create_in_ram(schema);
/// {
/// let mut index_writer = index.writer(3_000_000)?;
/// // a document can be associated to any number of facets
/// // a document can be associated with any number of facets
/// index_writer.add_document(doc!(
/// title => "The Name of the Wind",
/// facet => Facet::from("/lang/en"),
@@ -231,7 +231,7 @@ impl FacetCollector {
///
/// Adding two facets within which one is the prefix of the other is forbidden.
/// If you need the correct number of unique documents for two such facets,
/// just add them in separate `FacetCollector`.
/// just add them in a separate `FacetCollector`.
pub fn add_facet<T>(&mut self, facet_from: T)
where Facet: From<T> {
let facet = Facet::from(facet_from);
@@ -338,11 +338,7 @@ impl SegmentCollector for FacetSegmentCollector {
let mut previous_collapsed_ord: usize = usize::MAX;
for &facet_ord in &self.facet_ords_buf {
let collapsed_ord = self.collapse_mapping[facet_ord as usize];
self.counts[collapsed_ord] += if collapsed_ord == previous_collapsed_ord {
0
} else {
1
};
self.counts[collapsed_ord] += u64::from(collapsed_ord != previous_collapsed_ord);
previous_collapsed_ord = collapsed_ord;
}
}
@@ -391,7 +387,7 @@ impl<'a> Iterator for FacetChildIterator<'a> {
impl FacetCounts {
/// Returns an iterator over all of the facet count pairs inside this result.
/// See the documentation for [FacetCollector] for a usage example.
/// See the documentation for [`FacetCollector`] for a usage example.
pub fn get<T>(&self, facet_from: T) -> FacetChildIterator<'_>
where Facet: From<T> {
let facet = Facet::from(facet_from);
@@ -410,7 +406,7 @@ impl FacetCounts {
}
/// Returns a vector of top `k` facets with their counts, sorted highest-to-lowest by counts.
/// See the documentation for [FacetCollector] for a usage example.
/// See the documentation for [`FacetCollector`] for a usage example.
pub fn top_k<T>(&self, facet: T, k: usize) -> Vec<(&Facet, u64)>
where Facet: From<T> {
let mut heap = BinaryHeap::with_capacity(k);
@@ -620,7 +616,7 @@ mod tests {
.map(|mut doc| {
doc.add_facet(
facet_field,
&format!("/facet/{}", thread_rng().sample(&uniform)),
&format!("/facet/{}", thread_rng().sample(uniform)),
);
doc
})

13
src/collector/filter_collector_wrapper.rs
View File

@@ -10,9 +10,12 @@
// ---
// Importing tantivy...
use std::marker::PhantomData;
use std::sync::Arc;
use fastfield_codecs::Column;
use crate::collector::{Collector, SegmentCollector};
use crate::fastfield::{DynamicFastFieldReader, FastFieldReader, FastValue};
use crate::fastfield::FastValue;
use crate::schema::Field;
use crate::{Score, SegmentReader, TantivyError};
@@ -127,7 +130,9 @@ where
let fast_field_reader = segment_reader
.fast_fields()
.typed_fast_field_reader(self.field)?;
.typed_fast_field_reader(self.field)?
.to_full()
.expect("temp migration solution");
let segment_collector = self
.collector
@@ -158,7 +163,7 @@ where
TPredicate: 'static,
TPredicateValue: FastValue,
{
fast_field_reader: DynamicFastFieldReader<TPredicateValue>,
fast_field_reader: Arc<dyn Column<TPredicateValue>>,
segment_collector: TSegmentCollector,
predicate: TPredicate,
t_predicate_value: PhantomData<TPredicateValue>,
@@ -174,7 +179,7 @@ where
type Fruit = TSegmentCollector::Fruit;
fn collect(&mut self, doc: u32, score: Score) {
let value = self.fast_field_reader.get(doc);
let value = self.fast_field_reader.get_val(doc);
if (self.predicate)(value) {
self.segment_collector.collect(doc, score)
}

17
src/collector/histogram_collector.rs
View File

@@ -1,7 +1,10 @@
use std::sync::Arc;
use fastdivide::DividerU64;
use fastfield_codecs::Column;
use crate::collector::{Collector, SegmentCollector};
use crate::fastfield::{DynamicFastFieldReader, FastFieldReader, FastValue};
use crate::fastfield::FastValue;
use crate::schema::{Field, Type};
use crate::{DocId, Score};
@@ -34,7 +37,7 @@ impl HistogramCollector {
/// The scale/range of the histogram is not dynamic. It is required to
/// define it by supplying following parameter:
/// - `min_value`: the minimum value that can be recorded in the histogram.
/// - `bucket_width`: the length of the interval that is associated to each buckets.
/// - `bucket_width`: the length of the interval that is associated with each buckets.
/// - `num_buckets`: The overall number of buckets.
///
/// Together, this parameters define a partition of `[min_value, min_value + num_buckets *
@@ -84,14 +87,14 @@ impl HistogramComputer {
}
pub struct SegmentHistogramCollector {
histogram_computer: HistogramComputer,
ff_reader: DynamicFastFieldReader<u64>,
ff_reader: Arc<dyn Column<u64>>,
}
impl SegmentCollector for SegmentHistogramCollector {
type Fruit = Vec<u64>;
fn collect(&mut self, doc: DocId, _score: Score) {
let value = self.ff_reader.get(doc);
let value = self.ff_reader.get_val(doc);
self.histogram_computer.add_value(value);
}
@@ -109,7 +112,11 @@ impl Collector for HistogramCollector {
_segment_local_id: crate::SegmentOrdinal,
segment: &crate::SegmentReader,
) -> crate::Result<Self::Child> {
let ff_reader = segment.fast_fields().u64_lenient(self.field)?;
let ff_reader = segment
.fast_fields()
.u64_lenient(self.field)?
.to_full()
.expect("temp migration solution");
Ok(SegmentHistogramCollector {
histogram_computer: HistogramComputer {
counts: vec![0; self.num_buckets],

54
src/collector/mod.rs
View File

@@ -4,13 +4,13 @@
//! In tantivy jargon, we call this information your search "fruit".
//!
//! Your fruit could for instance be :
//! - [the count of matching documents](./struct.Count.html)
//! - [the top 10 documents, by relevancy or by a fast field](./struct.TopDocs.html)
//! - [facet counts](./struct.FacetCollector.html)
//! - [the count of matching documents](crate::collector::Count)
//! - [the top 10 documents, by relevancy or by a fast field](crate::collector::TopDocs)
//! - [facet counts](FacetCollector)
//!
//! At one point in your code, you will trigger the actual search operation by calling
//! [the `search(...)` method of your `Searcher` object](../struct.Searcher.html#method.search).
//! This call will look like this.
//! At some point in your code, you will trigger the actual search operation by calling
//! [`Searcher::search()`](crate::Searcher::search).
//! This call will look like this:
//!
//! ```verbatim
//! let fruit = searcher.search(&query, &collector)?;
@@ -64,7 +64,7 @@
//!
//! The `Collector` trait is implemented for up to 4 collectors.
//! If you have more than 4 collectors, you can either group them into
//! tuples of tuples `(a,(b,(c,d)))`, or rely on [`MultiCollector`](./struct.MultiCollector.html).
//! tuples of tuples `(a,(b,(c,d)))`, or rely on [`MultiCollector`].
//!
//! # Combining several collectors dynamically
//!
@@ -74,7 +74,7 @@
//!
//! Unfortunately it requires you to know at compile time your collector types.
//! If on the other hand, the collectors depend on some query parameter,
//! you can rely on `MultiCollector`'s.
//! you can rely on [`MultiCollector`]'s.
//!
//!
//! # Implementing your own collectors.
@@ -142,7 +142,7 @@ pub trait Collector: Sync + Send {
/// e.g. `usize` for the `Count` collector.
type Fruit: Fruit;
/// Type of the `SegmentCollector` associated to this collector.
/// Type of the `SegmentCollector` associated with this collector.
type Child: SegmentCollector;
/// `set_segment` is called before beginning to enumerate
@@ -156,7 +156,7 @@ pub trait Collector: Sync + Send {
/// Returns true iff the collector requires to compute scores for documents.
fn requires_scoring(&self) -> bool;
/// Combines the fruit associated to the collection of each segments
/// Combines the fruit associated with the collection of each segments
/// into one fruit.
fn merge_fruits(
&self,
@@ -172,17 +172,33 @@ pub trait Collector: Sync + Send {
) -> crate::Result<<Self::Child as SegmentCollector>::Fruit> {
let mut segment_collector = self.for_segment(segment_ord as u32, reader)?;
if let Some(alive_bitset) = reader.alive_bitset() {
weight.for_each(reader, &mut |doc, score| {
if alive_bitset.is_alive(doc) {
match (reader.alive_bitset(), self.requires_scoring()) {
(Some(alive_bitset), true) => {
weight.for_each(reader, &mut |doc, score| {
if alive_bitset.is_alive(doc) {
segment_collector.collect(doc, score);
}
})?;
}
(Some(alive_bitset), false) => {
weight.for_each_no_score(reader, &mut |doc| {
if alive_bitset.is_alive(doc) {
segment_collector.collect(doc, 0.0);
}
})?;
}
(None, true) => {
weight.for_each(reader, &mut |doc, score| {
segment_collector.collect(doc, score);
}
})?;
} else {
weight.for_each(reader, &mut |doc, score| {
segment_collector.collect(doc, score);
})?;
})?;
}
(None, false) => {
weight.for_each_no_score(reader, &mut |doc| {
segment_collector.collect(doc, 0.0);
})?;
}
}
Ok(segment_collector.harvest())
}
}

14
src/collector/tests.rs
View File

@@ -1,7 +1,11 @@
use std::sync::Arc;
use fastfield_codecs::OptionalColumn;
use super::*;
use crate::collector::{Count, FilterCollector, TopDocs};
use crate::core::SegmentReader;
use crate::fastfield::{BytesFastFieldReader, DynamicFastFieldReader, FastFieldReader};
use crate::fastfield::BytesFastFieldReader;
use crate::query::{AllQuery, QueryParser};
use crate::schema::{Field, Schema, FAST, TEXT};
use crate::time::format_description::well_known::Rfc3339;
@@ -156,7 +160,7 @@ pub struct FastFieldTestCollector {
pub struct FastFieldSegmentCollector {
vals: Vec<u64>,
reader: DynamicFastFieldReader<u64>,
reader: Arc<dyn OptionalColumn<u64>>,
}
impl FastFieldTestCollector {
@@ -197,8 +201,10 @@ impl SegmentCollector for FastFieldSegmentCollector {
type Fruit = Vec<u64>;
fn collect(&mut self, doc: DocId, _score: Score) {
let val = self.reader.get(doc);
self.vals.push(val);
let val = self.reader.get_val(doc);
if let Some(val) = val {
self.vals.push(val);
}
}
fn harvest(self) -> Vec<u64> {

36
src/collector/top_score_collector.rs
View File

@@ -1,6 +1,9 @@
use std::collections::BinaryHeap;
use std::fmt;
use std::marker::PhantomData;
use std::sync::Arc;
use fastfield_codecs::Column;
use super::Collector;
use crate::collector::custom_score_top_collector::CustomScoreTopCollector;
@@ -9,7 +12,7 @@ use crate::collector::tweak_score_top_collector::TweakedScoreTopCollector;
use crate::collector::{
CustomScorer, CustomSegmentScorer, ScoreSegmentTweaker, ScoreTweaker, SegmentCollector,
};
use crate::fastfield::{DynamicFastFieldReader, FastFieldReader, FastValue};
use crate::fastfield::FastValue;
use crate::query::Weight;
use crate::schema::Field;
use crate::{DocAddress, DocId, Score, SegmentOrdinal, SegmentReader, TantivyError};
@@ -129,12 +132,12 @@ impl fmt::Debug for TopDocs {
}
struct ScorerByFastFieldReader {
ff_reader: DynamicFastFieldReader<u64>,
ff_reader: Arc<dyn Column<u64>>,
}
impl CustomSegmentScorer<u64> for ScorerByFastFieldReader {
fn score(&mut self, doc: DocId) -> u64 {
self.ff_reader.get(doc)
self.ff_reader.get_val(doc)
}
}
@@ -153,7 +156,9 @@ impl CustomScorer<u64> for ScorerByField {
// The conversion will then happen only on the top-K docs.
let ff_reader = segment_reader
.fast_fields()
.typed_fast_field_reader(self.field)?;
.typed_fast_field_reader(self.field)?
.to_full()
.expect("temp migration solution");
Ok(ScorerByFastFieldReader { ff_reader })
}
}
@@ -284,7 +289,7 @@ impl TopDocs {
/// # See also
///
/// To comfortably work with `u64`s, `i64`s, `f64`s, or `date`s, please refer to
/// [.order_by_fast_field(...)](#method.order_by_fast_field) method.
/// the [.order_by_fast_field(...)](TopDocs::order_by_fast_field) method.
pub fn order_by_u64_field(
self,
field: Field,
@@ -381,7 +386,7 @@ impl TopDocs {
///
/// This method offers a convenient way to tweak or replace
/// the documents score. As suggested by the prototype you can
/// manually define your own [`ScoreTweaker`](./trait.ScoreTweaker.html)
/// manually define your own [`ScoreTweaker`]
/// and pass it as an argument, but there is a much simpler way to
/// tweak your score: you can use a closure as in the following
/// example.
@@ -398,7 +403,7 @@ impl TopDocs {
/// In the following example will will tweak our ranking a bit by
/// boosting popular products a notch.
///
/// In more serious application, this tweaking could involved running a
/// In more serious application, this tweaking could involve running a
/// learning-to-rank model over various features
///
/// ```rust
@@ -407,7 +412,6 @@ impl TopDocs {
/// # use tantivy::query::QueryParser;
/// use tantivy::SegmentReader;
/// use tantivy::collector::TopDocs;
/// use tantivy::fastfield::FastFieldReader;
/// use tantivy::schema::Field;
///
/// fn create_schema() -> Schema {
@@ -456,7 +460,7 @@ impl TopDocs {
///
/// // We can now define our actual scoring function
/// move |doc: DocId, original_score: Score| {
/// let popularity: u64 = popularity_reader.get(doc);
/// let popularity: u64 = popularity_reader.get_val(doc).unwrap();
/// // Well.. For the sake of the example we use a simple logarithm
/// // function.
/// let popularity_boost_score = ((2u64 + popularity) as Score).log2();
@@ -472,7 +476,7 @@ impl TopDocs {
/// ```
///
/// # See also
/// [custom_score(...)](#method.custom_score).
/// - [custom_score(...)](TopDocs::custom_score)
pub fn tweak_score<TScore, TScoreSegmentTweaker, TScoreTweaker>(
self,
score_tweaker: TScoreTweaker,
@@ -489,8 +493,7 @@ impl TopDocs {
///
/// This method offers a convenient way to use a different score.
///
/// As suggested by the prototype you can manually define your
/// own [`CustomScorer`](./trait.CustomScorer.html)
/// As suggested by the prototype you can manually define your own [`CustomScorer`]
/// and pass it as an argument, but there is a much simpler way to
/// tweak your score: you can use a closure as in the following
/// example.
@@ -515,7 +518,6 @@ impl TopDocs {
/// use tantivy::SegmentReader;
/// use tantivy::collector::TopDocs;
/// use tantivy::schema::Field;
/// use tantivy::fastfield::FastFieldReader;
///
/// # fn create_schema() -> Schema {
/// # let mut schema_builder = Schema::builder();
@@ -567,8 +569,8 @@ impl TopDocs {
///
/// // We can now define our actual scoring function
/// move |doc: DocId| {
/// let popularity: u64 = popularity_reader.get(doc);
/// let boosted: u64 = boosted_reader.get(doc);
/// let popularity: u64 = popularity_reader.get_val(doc).unwrap();
/// let boosted: u64 = boosted_reader.get_val(doc).unwrap();
/// // Score do not have to be `f64` in tantivy.
/// // Here we return a couple to get lexicographical order
/// // for free.
@@ -587,7 +589,7 @@ impl TopDocs {
/// ```
///
/// # See also
/// [tweak_score(...)](#method.tweak_score).
/// - [tweak_score(...)](TopDocs::tweak_score)
pub fn custom_score<TScore, TCustomSegmentScorer, TCustomScorer>(
self,
custom_score: TCustomScorer,
@@ -693,7 +695,7 @@ impl Collector for TopDocs {
}
}
/// Segment Collector associated to `TopDocs`.
/// Segment Collector associated with `TopDocs`.
pub struct TopScoreSegmentCollector(TopSegmentCollector<Score>);
impl SegmentCollector for TopScoreSegmentCollector {

6
src/collector/tweak_score_top_collector.rs
View File

@@ -24,7 +24,7 @@ where TScore: Clone + PartialOrd
/// A `ScoreSegmentTweaker` makes it possible to modify the default score
/// for a given document belonging to a specific segment.
///
/// It is the segment local version of the [`ScoreTweaker`](./trait.ScoreTweaker.html).
/// It is the segment local version of the [`ScoreTweaker`].
pub trait ScoreSegmentTweaker<TScore>: 'static {
/// Tweak the given `score` for the document `doc`.
fn score(&mut self, doc: DocId, score: Score) -> TScore;
@@ -37,10 +37,10 @@ pub trait ScoreSegmentTweaker<TScore>: 'static {
/// Instead, it helps constructing `Self::Child` instances that will compute
/// the score at a segment scale.
pub trait ScoreTweaker<TScore>: Sync {
/// Type of the associated [`ScoreSegmentTweaker`](./trait.ScoreSegmentTweaker.html).
/// Type of the associated [`ScoreSegmentTweaker`].
type Child: ScoreSegmentTweaker<TScore>;
/// Builds a child tweaker for a specific segment. The child scorer is associated to
/// Builds a child tweaker for a specific segment. The child scorer is associated with
/// a specific segment.
fn segment_tweaker(&self, segment_reader: &SegmentReader) -> Result<Self::Child>;
}

174
src/core/index.rs
View File

@@ -7,6 +7,7 @@ use std::sync::Arc;
use super::segment::Segment;
use super::IndexSettings;
use crate::core::single_segment_index_writer::SingleSegmentIndexWriter;
use crate::core::{
Executor, IndexMeta, SegmentId, SegmentMeta, SegmentMetaInventory, META_FILEPATH,
};
@@ -16,9 +17,9 @@ use crate::directory::MmapDirectory;
use crate::directory::{Directory, ManagedDirectory, RamDirectory, INDEX_WRITER_LOCK};
use crate::error::{DataCorruption, TantivyError};
use crate::indexer::index_writer::{MAX_NUM_THREAD, MEMORY_ARENA_NUM_BYTES_MIN};
use crate::indexer::segment_updater::save_new_metas;
use crate::indexer::segment_updater::save_metas;
use crate::reader::{IndexReader, IndexReaderBuilder};
use crate::schema::{Field, FieldType, Schema};
use crate::schema::{Cardinality, Field, FieldType, Schema};
use crate::tokenizer::{TextAnalyzer, TokenizerManager};
use crate::IndexWriter;
@@ -47,10 +48,38 @@ fn load_metas(
.map_err(From::from)
}
/// Save the index meta file.
/// This operation is atomic :
/// Either
/// - it fails, in which case an error is returned,
/// and the `meta.json` remains untouched,
/// - it succeeds, and `meta.json` is written
/// and flushed.
///
/// This method is not part of tantivy's public API
fn save_new_metas(
schema: Schema,
index_settings: IndexSettings,
directory: &dyn Directory,
) -> crate::Result<()> {
save_metas(
&IndexMeta {
index_settings,
segments: Vec::new(),
schema,
opstamp: 0u64,
payload: None,
},
directory,
)?;
directory.sync_directory()?;
Ok(())
}
/// IndexBuilder can be used to create an index.
///
/// Use in conjunction with `SchemaBuilder`. Global index settings
/// can be configured with `IndexSettings`
/// Use in conjunction with [`SchemaBuilder`][crate::schema::SchemaBuilder].
/// Global index settings can be configured with [`IndexSettings`].
///
/// # Examples
///
@@ -68,7 +97,13 @@ fn load_metas(
/// );
///
/// let schema = schema_builder.build();
/// let settings = IndexSettings{sort_by_field: Some(IndexSortByField{field:"number".to_string(), order:Order::Asc}), ..Default::default()};
/// let settings = IndexSettings{
/// sort_by_field: Some(IndexSortByField{
/// field: "number".to_string(),
/// order: Order::Asc
/// }),
/// ..Default::default()
/// };
/// let index = Index::builder().schema(schema).settings(settings).create_in_ram();
/// ```
pub struct IndexBuilder {
@@ -111,21 +146,20 @@ impl IndexBuilder {
self
}
/// Creates a new index using the `RAMDirectory`.
/// Creates a new index using the [`RamDirectory`].
///
/// The index will be allocated in anonymous memory.
/// This should only be used for unit tests.
pub fn create_in_ram(self) -> Result<Index, TantivyError> {
let ram_directory = RamDirectory::create();
Ok(self
.create(ram_directory)
.expect("Creating a RAMDirectory should never fail"))
self.create(ram_directory)
}
/// Creates a new index in a given filepath.
/// The index will use the `MMapDirectory`.
/// The index will use the [`MmapDirectory`].
///
/// If a previous index was in this directory, it returns an `IndexAlreadyExists` error.
/// If a previous index was in this directory, it returns an
/// [`TantivyError::IndexAlreadyExists`] error.
#[cfg(feature = "mmap")]
pub fn create_in_dir<P: AsRef<Path>>(self, directory_path: P) -> crate::Result<Index> {
let mmap_directory: Box<dyn Directory> = Box::new(MmapDirectory::open(directory_path)?);
@@ -135,14 +169,34 @@ impl IndexBuilder {
self.create(mmap_directory)
}
/// Dragons ahead!!!
///
/// The point of this API is to let users create a simple index with a single segment
/// and without starting any thread.
///
/// Do not use this method if you are not sure what you are doing.
///
/// It expects an originally empty directory, and will not run any GC operation.
#[doc(hidden)]
pub fn single_segment_index_writer(
self,
dir: impl Into<Box<dyn Directory>>,
mem_budget: usize,
) -> crate::Result<SingleSegmentIndexWriter> {
let index = self.create(dir)?;
let index_simple_writer = SingleSegmentIndexWriter::new(index, mem_budget)?;
Ok(index_simple_writer)
}
/// Creates a new index in a temp directory.
///
/// The index will use the `MMapDirectory` in a newly created directory.
/// The temp directory will be destroyed automatically when the `Index` object
/// The index will use the [`MmapDirectory`] in a newly created directory.
/// The temp directory will be destroyed automatically when the [`Index`] object
/// is destroyed.
///
/// The temp directory is only used for testing the `MmapDirectory`.
/// For other unit tests, prefer the `RAMDirectory`, see: `create_in_ram`.
/// The temp directory is only used for testing the [`MmapDirectory`].
/// For other unit tests, prefer the [`RamDirectory`], see:
/// [`IndexBuilder::create_in_ram()`].
#[cfg(feature = "mmap")]
pub fn create_from_tempdir(self) -> crate::Result<Index> {
let mmap_directory: Box<dyn Directory> = Box::new(MmapDirectory::create_from_tempdir()?);
@@ -172,10 +226,44 @@ impl IndexBuilder {
))
}
}
fn validate(&self) -> crate::Result<()> {
if let Some(schema) = self.schema.as_ref() {
if let Some(sort_by_field) = self.index_settings.sort_by_field.as_ref() {
let schema_field = schema.get_field(&sort_by_field.field).ok_or_else(|| {
TantivyError::InvalidArgument(format!(
"Field to sort index {} not found in schema",
sort_by_field.field
))
})?;
let entry = schema.get_field_entry(schema_field);
if !entry.is_fast() {
return Err(TantivyError::InvalidArgument(format!(
"Field {} is no fast field. Field needs to be a single value fast field \
to be used to sort an index",
sort_by_field.field
)));
}
if entry.field_type().fastfield_cardinality() != Some(Cardinality::SingleValue) {
return Err(TantivyError::InvalidArgument(format!(
"Only single value fast field Cardinality supported for sorting index {}",
sort_by_field.field
)));
}
}
Ok(())
} else {
Err(TantivyError::InvalidArgument(
"no schema passed".to_string(),
))
}
}
/// Creates a new index given an implementation of the trait `Directory`.
///
/// If a directory previously existed, it will be erased.
fn create<T: Into<Box<dyn Directory>>>(self, dir: T) -> crate::Result<Index> {
self.validate()?;
let dir = dir.into();
let directory = ManagedDirectory::wrap(dir)?;
save_new_metas(
@@ -238,7 +326,7 @@ impl Index {
self.set_multithread_executor(default_num_threads)
}
/// Creates a new index using the `RamDirectory`.
/// Creates a new index using the [`RamDirectory`].
///
/// The index will be allocated in anonymous memory.
/// This is useful for indexing small set of documents
@@ -248,9 +336,10 @@ impl Index {
}
/// Creates a new index in a given filepath.
/// The index will use the `MMapDirectory`.
/// The index will use the [`MmapDirectory`].
///
/// If a previous index was in this directory, then it returns an `IndexAlreadyExists` error.
/// If a previous index was in this directory, then it returns
/// a [`TantivyError::IndexAlreadyExists`] error.
#[cfg(feature = "mmap")]
pub fn create_in_dir<P: AsRef<Path>>(
directory_path: P,
@@ -272,12 +361,13 @@ impl Index {
/// Creates a new index in a temp directory.
///
/// The index will use the `MMapDirectory` in a newly created directory.
/// The temp directory will be destroyed automatically when the `Index` object
/// The index will use the [`MmapDirectory`] in a newly created directory.
/// The temp directory will be destroyed automatically when the [`Index`] object
/// is destroyed.
///
/// The temp directory is only used for testing the `MmapDirectory`.
/// For other unit tests, prefer the `RamDirectory`, see: `create_in_ram`.
/// The temp directory is only used for testing the [`MmapDirectory`].
/// For other unit tests, prefer the [`RamDirectory`],
/// see: [`IndexBuilder::create_in_ram()`].
#[cfg(feature = "mmap")]
pub fn create_from_tempdir(schema: Schema) -> crate::Result<Index> {
IndexBuilder::new().schema(schema).create_from_tempdir()
@@ -297,7 +387,7 @@ impl Index {
builder.create(dir)
}
/// Creates a new index given a directory and an `IndexMeta`.
/// Creates a new index given a directory and an [`IndexMeta`].
fn open_from_metas(
directory: ManagedDirectory,
metas: &IndexMeta,
@@ -324,7 +414,7 @@ impl Index {
&self.tokenizers
}
/// Helper to access the tokenizer associated to a specific field.
/// Get the tokenizer associated with a specific field.
pub fn tokenizer_for_field(&self, field: Field) -> crate::Result<TextAnalyzer> {
let field_entry = self.schema.get_field_entry(field);
let field_type = field_entry.field_type();
@@ -356,14 +446,14 @@ impl Index {
})
}
/// Create a default `IndexReader` for the given index.
/// Create a default [`IndexReader`] for the given index.
///
/// See [`Index.reader_builder()`](#method.reader_builder).
/// See [`Index.reader_builder()`].
pub fn reader(&self) -> crate::Result<IndexReader> {
self.reader_builder().try_into()
}
/// Create a `IndexReader` for the given index.
/// Create a [`IndexReader`] for the given index.
///
/// Most project should create at most one reader for a given index.
/// This method is typically called only once per `Index` instance.
@@ -580,10 +670,12 @@ impl fmt::Debug for Index {
#[cfg(test)]
mod tests {
use crate::collector::Count;
use crate::directory::{RamDirectory, WatchCallback};
use crate::schema::{Field, Schema, INDEXED, TEXT};
use crate::query::TermQuery;
use crate::schema::{Field, IndexRecordOption, Schema, INDEXED, TEXT};
use crate::tokenizer::TokenizerManager;
use crate::{Directory, Index, IndexBuilder, IndexReader, IndexSettings, ReloadPolicy};
use crate::{Directory, Index, IndexBuilder, IndexReader, IndexSettings, ReloadPolicy, Term};
#[test]
fn test_indexer_for_field() {
@@ -849,4 +941,28 @@ mod tests {
);
Ok(())
}
#[test]
fn test_single_segment_index_writer() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("text", TEXT);
let schema = schema_builder.build();
let directory = RamDirectory::default();
let mut single_segment_index_writer = Index::builder()
.schema(schema)
.single_segment_index_writer(directory, 10_000_000)?;
for _ in 0..10 {
let doc = doc!(text_field=>"hello");
single_segment_index_writer.add_document(doc)?;
}
let index = single_segment_index_writer.finalize()?;
let searcher = index.reader()?.searcher();
let term_query = TermQuery::new(
Term::from_field_text(text_field, "hello"),
IndexRecordOption::Basic,
);
let count = searcher.search(&term_query, &Count)?;
assert_eq!(count, 10);
Ok(())
}
}

71
src/core/index_meta.rs
View File

@@ -130,10 +130,10 @@ impl SegmentMeta {
/// Returns the relative path of a component of our segment.
///
/// It just joins the segment id with the extension
/// associated to a segment component.
/// associated with a segment component.
pub fn relative_path(&self, component: SegmentComponent) -> PathBuf {
let mut path = self.id().uuid_string();
path.push_str(&*match component {
path.push_str(&match component {
SegmentComponent::Postings => ".idx".to_string(),
SegmentComponent::Positions => ".pos".to_string(),
SegmentComponent::Terms => ".term".to_string(),
@@ -235,6 +235,14 @@ impl InnerSegmentMeta {
}
}
fn return_true() -> bool {
true
}
fn is_true(val: &bool) -> bool {
*val
}
/// Search Index Settings.
///
/// Contains settings which are applied on the whole
@@ -248,6 +256,12 @@ pub struct IndexSettings {
/// The `Compressor` used to compress the doc store.
#[serde(default)]
pub docstore_compression: Compressor,
/// If set to true, docstore compression will happen on a dedicated thread.
/// (defaults: true)
#[doc(hidden)]
#[serde(default = "return_true")]
#[serde(skip_serializing_if = "is_true")]
pub docstore_compress_dedicated_thread: bool,
#[serde(default = "default_docstore_blocksize")]
/// The size of each block that will be compressed and written to disk
pub docstore_blocksize: usize,
@@ -264,6 +278,7 @@ impl Default for IndexSettings {
sort_by_field: None,
docstore_compression: Compressor::default(),
docstore_blocksize: default_docstore_blocksize(),
docstore_compress_dedicated_thread: true,
}
}
}
@@ -311,13 +326,13 @@ pub struct IndexMeta {
/// `IndexSettings` to configure index options.
#[serde(default)]
pub index_settings: IndexSettings,
/// List of `SegmentMeta` information associated to each finalized segment of the index.
/// List of `SegmentMeta` information associated with each finalized segment of the index.
pub segments: Vec<SegmentMeta>,
/// Index `Schema`
pub schema: Schema,
/// Opstamp associated to the last `commit` operation.
/// Opstamp associated with the last `commit` operation.
pub opstamp: Opstamp,
/// Payload associated to the last commit.
/// Payload associated with the last commit.
///
/// Upon commit, clients can optionally add a small `String` payload to their commit
/// to help identify this commit.
@@ -395,7 +410,7 @@ mod tests {
use super::IndexMeta;
use crate::core::index_meta::UntrackedIndexMeta;
use crate::schema::{Schema, TEXT};
use crate::store::ZstdCompressor;
use crate::store::{Compressor, ZstdCompressor};
use crate::{IndexSettings, IndexSortByField, Order};
#[test]
@@ -447,6 +462,7 @@ mod tests {
compression_level: Some(4),
}),
docstore_blocksize: 1_000_000,
docstore_compress_dedicated_thread: true,
},
segments: Vec::new(),
schema,
@@ -485,4 +501,47 @@ mod tests {
"unknown zstd option \"bla\" at line 1 column 103".to_string()
);
}
#[test]
#[cfg(feature = "lz4-compression")]
fn test_index_settings_default() {
let mut index_settings = IndexSettings::default();
assert_eq!(
index_settings,
IndexSettings {
sort_by_field: None,
docstore_compression: Compressor::default(),
docstore_compress_dedicated_thread: true,
docstore_blocksize: 16_384
}
);
{
let index_settings_json = serde_json::to_value(&index_settings).unwrap();
assert_eq!(
index_settings_json,
serde_json::json!({
"docstore_compression": "lz4",
"docstore_blocksize": 16384
})
);
let index_settings_deser: IndexSettings =
serde_json::from_value(index_settings_json).unwrap();
assert_eq!(index_settings_deser, index_settings);
}
{
index_settings.docstore_compress_dedicated_thread = false;
let index_settings_json = serde_json::to_value(&index_settings).unwrap();
assert_eq!(
index_settings_json,
serde_json::json!({
"docstore_compression": "lz4",
"docstore_blocksize": 16384,
"docstore_compress_dedicated_thread": false,
})
);
let index_settings_deser: IndexSettings =
serde_json::from_value(index_settings_json).unwrap();
assert_eq!(index_settings_deser, index_settings);
}
}
}

41
src/core/inverted_index_reader.rs
View File

@@ -9,18 +9,17 @@ use crate::schema::{IndexRecordOption, Term};
use crate::termdict::TermDictionary;
/// The inverted index reader is in charge of accessing
/// the inverted index associated to a specific field.
/// the inverted index associated with a specific field.
///
/// # Note
///
/// It is safe to delete the segment associated to
/// It is safe to delete the segment associated with
/// an `InvertedIndexReader`. As long as it is open,
/// the `FileSlice` it is relying on should
/// the [`FileSlice`] it is relying on should
/// stay available.
///
///
/// `InvertedIndexReader` are created by calling
/// the `SegmentReader`'s [`.inverted_index(...)`] method
/// [`SegmentReader::inverted_index()`](crate::SegmentReader::inverted_index).
pub struct InvertedIndexReader {
termdict: TermDictionary,
postings_file_slice: FileSlice,
@@ -30,7 +29,7 @@ pub struct InvertedIndexReader {
}
impl InvertedIndexReader {
#[cfg_attr(feature = "cargo-clippy", allow(clippy::needless_pass_by_value))] // for symmetry
#[allow(clippy::needless_pass_by_value)] // for symmetry
pub(crate) fn new(
termdict: TermDictionary,
postings_file_slice: FileSlice,
@@ -75,7 +74,7 @@ impl InvertedIndexReader {
///
/// This is useful for enumerating through a list of terms,
/// and consuming the associated posting lists while avoiding
/// reallocating a `BlockSegmentPostings`.
/// reallocating a [`BlockSegmentPostings`].
///
/// # Warning
///
@@ -96,7 +95,7 @@ impl InvertedIndexReader {
/// Returns a block postings given a `Term`.
/// This method is for an advanced usage only.
///
/// Most user should prefer using `read_postings` instead.
/// Most users should prefer using [`Self::read_postings()`] instead.
pub fn read_block_postings(
&self,
term: &Term,
@@ -110,7 +109,7 @@ impl InvertedIndexReader {
/// Returns a block postings given a `term_info`.
/// This method is for an advanced usage only.
///
/// Most user should prefer using `read_postings` instead.
/// Most users should prefer using [`Self::read_postings()`] instead.
pub fn read_block_postings_from_terminfo(
&self,
term_info: &TermInfo,
@@ -130,7 +129,7 @@ impl InvertedIndexReader {
/// Returns a posting object given a `term_info`.
/// This method is for an advanced usage only.
///
/// Most user should prefer using `read_postings` instead.
/// Most users should prefer using [`Self::read_postings()`] instead.
pub fn read_postings_from_terminfo(
&self,
term_info: &TermInfo,
@@ -164,12 +163,12 @@ impl InvertedIndexReader {
/// or `None` if the term has never been encountered and indexed.
///
/// If the field was not indexed with the indexing options that cover
/// the requested options, the returned `SegmentPostings` the method does not fail
/// the requested options, the returned [`SegmentPostings`] the method does not fail
/// and returns a `SegmentPostings` with as much information as possible.
///
/// For instance, requesting `IndexRecordOption::Freq` for a
/// `TextIndexingOptions` that does not index position will return a `SegmentPostings`
/// with `DocId`s and frequencies.
/// For instance, requesting [`IndexRecordOption::WithFreqs`] for a
/// [`TextOptions`](crate::schema::TextOptions) that does not index position
/// will return a [`SegmentPostings`] with `DocId`s and frequencies.
pub fn read_postings(
&self,
term: &Term,
@@ -211,7 +210,7 @@ impl InvertedIndexReader {
/// Returns a block postings given a `Term`.
/// This method is for an advanced usage only.
///
/// Most user should prefer using `read_postings` instead.
/// Most users should prefer using [`Self::read_postings()`] instead.
pub async fn warm_postings(
&self,
term: &Term,
@@ -231,6 +230,18 @@ impl InvertedIndexReader {
Ok(())
}
/// Read the block postings for all terms.
/// This method is for an advanced usage only.
///
/// If you know which terms to pre-load, prefer using [`Self::warm_postings`] instead.
pub async fn warm_postings_full(&self, with_positions: bool) -> crate::AsyncIoResult<()> {
self.postings_file_slice.read_bytes_async().await?;
if with_positions {
self.positions_file_slice.read_bytes_async().await?;
}
Ok(())
}
/// Returns the number of documents containing the term asynchronously.
pub async fn doc_freq_async(&self, term: &Term) -> crate::AsyncIoResult<u32> {
Ok(self

2
src/core/mod.rs
View File

@@ -7,6 +7,7 @@ mod segment;
mod segment_component;
mod segment_id;
mod segment_reader;
mod single_segment_index_writer;
use std::path::Path;
@@ -23,6 +24,7 @@ pub use self::segment::Segment;
pub use self::segment_component::SegmentComponent;
pub use self::segment_id::SegmentId;
pub use self::segment_reader::SegmentReader;
pub use self::single_segment_index_writer::SingleSegmentIndexWriter;
/// The meta file contains all the information about the list of segments and the schema
/// of the index.

31
src/core/searcher.rs
View File

@@ -4,18 +4,18 @@ use std::{fmt, io};
use crate::collector::Collector;
use crate::core::{Executor, SegmentReader};
use crate::query::Query;
use crate::query::{EnableScoring, Query};
use crate::schema::{Document, Schema, Term};
use crate::space_usage::SearcherSpaceUsage;
use crate::store::{CacheStats, StoreReader};
use crate::{DocAddress, Index, Opstamp, SegmentId, TrackedObject};
/// Identifies the searcher generation accessed by a [Searcher].
/// Identifies the searcher generation accessed by a [`Searcher`].
///
/// While this might seem redundant, a [SearcherGeneration] contains
/// While this might seem redundant, a [`SearcherGeneration`] contains
/// both a `generation_id` AND a list of `(SegmentId, DeleteOpstamp)`.
///
/// This is on purpose. This object is used by the `Warmer` API.
/// This is on purpose. This object is used by the [`Warmer`](crate::reader::Warmer) API.
/// Having both information makes it possible to identify which
/// artifact should be refreshed or garbage collected.
///
@@ -69,20 +69,20 @@ pub struct Searcher {
}
impl Searcher {
/// Returns the `Index` associated to the `Searcher`
/// Returns the `Index` associated with the `Searcher`
pub fn index(&self) -> &Index {
&self.inner.index
}
/// [SearcherGeneration] which identifies the version of the snapshot held by this `Searcher`.
/// [`SearcherGeneration`] which identifies the version of the snapshot held by this `Searcher`.
pub fn generation(&self) -> &SearcherGeneration {
self.inner.generation.as_ref()
}
/// Fetches a document from tantivy's store given a `DocAddress`.
/// Fetches a document from tantivy's store given a [`DocAddress`].
///
/// The searcher uses the segment ordinal to route the
/// the request to the right `Segment`.
/// request to the right `Segment`.
pub fn doc(&self, doc_address: DocAddress) -> crate::Result<Document> {
let store_reader = &self.inner.store_readers[doc_address.segment_ord as usize];
store_reader.get(doc_address.doc_id)
@@ -108,7 +108,7 @@ impl Searcher {
store_reader.get_async(doc_address.doc_id).await
}
/// Access the schema associated to the index of this searcher.
/// Access the schema associated with the index of this searcher.
pub fn schema(&self) -> &Schema {
&self.inner.schema
}
@@ -161,11 +161,11 @@ impl Searcher {
///
/// Search works as follows :
///
/// First the weight object associated to the query is created.
/// First the weight object associated with the query is created.
///
/// Then, the query loops over the segments and for each segment :
/// - setup the collector and informs it that the segment being processed has changed.
/// - creates a SegmentCollector for collecting documents associated to the segment
/// - creates a SegmentCollector for collecting documents associated with the segment
/// - creates a `Scorer` object associated for this segment
/// - iterate through the matched documents and push them to the segment collector.
///
@@ -180,7 +180,7 @@ impl Searcher {
self.search_with_executor(query, collector, executor)
}
/// Same as [`search(...)`](#method.search) but multithreaded.
/// Same as [`search(...)`](Searcher::search) but multithreaded.
///
/// The current implementation is rather naive :
/// multithreading is by splitting search into as many task
@@ -199,7 +199,12 @@ impl Searcher {
executor: &Executor,
) -> crate::Result<C::Fruit> {
let scoring_enabled = collector.requires_scoring();
let weight = query.weight(self, scoring_enabled)?;
let enabled_scoring = if scoring_enabled {
EnableScoring::Enabled(self)
} else {
EnableScoring::Disabled(self.schema())
};
let weight = query.weight(enabled_scoring)?;
let segment_readers = self.segment_readers();
let fruits = executor.map(
|(segment_ord, segment_reader)| {

2
src/core/segment.rs
View File

@@ -70,7 +70,7 @@ impl Segment {
/// Returns the relative path of a component of our segment.
///
/// It just joins the segment id with the extension
/// associated to a segment component.
/// associated with a segment component.
pub fn relative_path(&self, component: SegmentComponent) -> PathBuf {
self.meta.relative_path(component)
}

2
src/core/segment_component.rs
View File

@@ -6,7 +6,7 @@ use std::slice;
/// except the delete component that takes an `segment_uuid`.`delete_opstamp`.`component_extension`
#[derive(Copy, Clone, Eq, PartialEq)]
pub enum SegmentComponent {
/// Postings (or inverted list). Sorted lists of document ids, associated to terms
/// Postings (or inverted list). Sorted lists of document ids, associated with terms
Postings,
/// Positions of terms in each document.
Positions,

2
src/core/segment_id.rs
View File

@@ -57,7 +57,7 @@ impl SegmentId {
/// Picking the first 8 chars is ok to identify
/// segments in a display message (e.g. a5c4dfcb).
pub fn short_uuid_string(&self) -> String {
(&self.0.as_simple().to_string()[..8]).to_string()
self.0.as_simple().to_string()[..8].to_string()
}
/// Returns a segment uuid string.

16
src/core/segment_reader.rs
View File

@@ -89,7 +89,7 @@ impl SegmentReader {
&self.fast_fields_readers
}
/// Accessor to the `FacetReader` associated to a given `Field`.
/// Accessor to the `FacetReader` associated with a given `Field`.
pub fn facet_reader(&self, field: Field) -> crate::Result<FacetReader> {
let field_entry = self.schema.get_field_entry(field);
@@ -208,18 +208,18 @@ impl SegmentReader {
})
}
/// Returns a field reader associated to the field given in argument.
/// Returns a field reader associated with the field given in argument.
/// If the field was not present in the index during indexing time,
/// the InvertedIndexReader is empty.
///
/// The field reader is in charge of iterating through the
/// term dictionary associated to a specific field,
/// and opening the posting list associated to any term.
/// term dictionary associated with a specific field,
/// and opening the posting list associated with any term.
///
/// If the field is not marked as index, a warn is logged and an empty `InvertedIndexReader`
/// If the field is not marked as index, a warning is logged and an empty `InvertedIndexReader`
/// is returned.
/// Similarly if the field is marked as indexed but no term has been indexed for the given
/// index. an empty `InvertedIndexReader` is returned (but no warning is logged).
/// Similarly, if the field is marked as indexed but no term has been indexed for the given
/// index, an empty `InvertedIndexReader` is returned (but no warning is logged).
pub fn inverted_index(&self, field: Field) -> crate::Result<Arc<InvertedIndexReader>> {
if let Some(inv_idx_reader) = self
.inv_idx_reader_cache
@@ -241,7 +241,7 @@ impl SegmentReader {
if postings_file_opt.is_none() || record_option_opt.is_none() {
// no documents in the segment contained this field.
// As a result, no data is associated to the inverted index.
// As a result, no data is associated with the inverted index.
//
// Returns an empty inverted index.
let record_option = record_option_opt.unwrap_or(IndexRecordOption::Basic);

51
src/core/single_segment_index_writer.rs Normal file
View File

@@ -0,0 +1,51 @@
use crate::indexer::operation::AddOperation;
use crate::indexer::segment_updater::save_metas;
use crate::indexer::SegmentWriter;
use crate::{Directory, Document, Index, IndexMeta, Opstamp, Segment};
#[doc(hidden)]
pub struct SingleSegmentIndexWriter {
segment_writer: SegmentWriter,
segment: Segment,
opstamp: Opstamp,
}
impl SingleSegmentIndexWriter {
pub fn new(index: Index, mem_budget: usize) -> crate::Result<Self> {
let segment = index.new_segment();
let segment_writer = SegmentWriter::for_segment(mem_budget, segment.clone())?;
Ok(Self {
segment_writer,
segment,
opstamp: 0,
})
}
pub fn mem_usage(&self) -> usize {
self.segment_writer.mem_usage()
}
pub fn add_document(&mut self, document: Document) -> crate::Result<()> {
let opstamp = self.opstamp;
self.opstamp += 1;
self.segment_writer
.add_document(AddOperation { opstamp, document })
}
pub fn finalize(self) -> crate::Result<Index> {
let max_doc = self.segment_writer.max_doc();
self.segment_writer.finalize()?;
let segment: Segment = self.segment.with_max_doc(max_doc);
let index = segment.index();
let index_meta = IndexMeta {
index_settings: index.settings().clone(),
segments: vec![segment.meta().clone()],
schema: index.schema(),
opstamp: 0,
payload: None,
};
save_metas(&index_meta, index.directory())?;
index.directory().sync_directory()?;
Ok(segment.index().clone())
}
}

8
src/directory/composite_file.rs
View File

@@ -154,14 +154,14 @@ impl CompositeFile {
}
}
/// Returns the `FileSlice` associated
/// to a given `Field` and stored in a `CompositeFile`.
/// Returns the `FileSlice` associated with
/// a given `Field` and stored in a `CompositeFile`.
pub fn open_read(&self, field: Field) -> Option<FileSlice> {
self.open_read_with_idx(field, 0)
}
/// Returns the `FileSlice` associated
/// to a given `Field` and stored in a `CompositeFile`.
/// Returns the `FileSlice` associated with
/// a given `Field` and stored in a `CompositeFile`.
pub fn open_read_with_idx(&self, field: Field, idx: usize) -> Option<FileSlice> {
self.offsets_index
.get(&FileAddr { field, idx })

47
src/directory/directory.rs
View File

@@ -39,7 +39,7 @@ impl RetryPolicy {
/// The `DirectoryLock` is an object that represents a file lock.
///
/// It is associated to a lock file, that gets deleted on `Drop.`
/// It is associated with a lock file, that gets deleted on `Drop.`
pub struct DirectoryLock(Box<dyn Send + Sync + 'static>);
struct DirectoryLockGuard {
@@ -55,7 +55,7 @@ impl<T: Send + Sync + 'static> From<Box<T>> for DirectoryLock {
impl Drop for DirectoryLockGuard {
fn drop(&mut self) {
if let Err(e) = self.directory.delete(&*self.path) {
if let Err(e) = self.directory.delete(&self.path) {
error!("Failed to remove the lock file. {:?}", e);
}
}
@@ -117,9 +117,9 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
/// change.
///
/// Specifically, subsequent writes or flushes should
/// have no effect on the returned `FileSlice` object.
/// have no effect on the returned [`FileSlice`] object.
///
/// You should only use this to read files create with [Directory::open_write].
/// You should only use this to read files create with [`Directory::open_write()`].
fn open_read(&self, path: &Path) -> Result<FileSlice, OpenReadError> {
let file_handle = self.get_file_handle(path)?;
Ok(FileSlice::new(file_handle))
@@ -128,27 +128,28 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
/// Removes a file
///
/// Removing a file will not affect an eventual
/// existing FileSlice pointing to it.
/// existing [`FileSlice`] pointing to it.
///
/// Removing a nonexistent file, yields a
/// `DeleteError::DoesNotExist`.
/// Removing a nonexistent file, returns a
/// [`DeleteError::FileDoesNotExist`].
fn delete(&self, path: &Path) -> Result<(), DeleteError>;
/// Returns true if and only if the file exists
fn exists(&self, path: &Path) -> Result<bool, OpenReadError>;
/// Opens a writer for the *virtual file* associated with
/// a Path.
/// a [`Path`].
///
/// Right after this call, for the span of the execution of the program
/// the file should be created and any subsequent call to `open_read` for the
/// same path should return a `FileSlice`.
/// the file should be created and any subsequent call to
/// [`Directory::open_read()`] for the same path should return
/// a [`FileSlice`].
///
/// However, depending on the directory implementation,
/// it might be required to call `sync_directory` to ensure
/// it might be required to call [`Directory::sync_directory()`] to ensure
/// that the file is durably created.
/// (The semantics here are the same when dealing with
/// a posix filesystem.)
/// a POSIX filesystem.)
///
/// Write operations may be aggressively buffered.
/// The client of this trait is responsible for calling flush
@@ -157,19 +158,19 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
///
/// Flush operation should also be persistent.
///
/// The user shall not rely on `Drop` triggering `flush`.
/// Note that `RamDirectory` will panic! if `flush`
/// was not called.
/// The user shall not rely on [`Drop`] triggering `flush`.
/// Note that [`RamDirectory`][crate::directory::RamDirectory] will
/// panic! if `flush` was not called.
///
/// The file may not previously exist.
fn open_write(&self, path: &Path) -> Result<WritePtr, OpenWriteError>;
/// Reads the full content file that has been written using
/// atomic_write.
/// [`Directory::atomic_write()`].
///
/// This should only be used for small files.
///
/// You should only use this to read files create with [Directory::atomic_write].
/// You should only use this to read files create with [`Directory::atomic_write()`].
fn atomic_read(&self, path: &Path) -> Result<Vec<u8>, OpenReadError>;
/// Atomically replace the content of a file with data.
@@ -186,9 +187,9 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
/// effectively stored durably.
fn sync_directory(&self) -> io::Result<()>;
/// Acquire a lock in the given directory.
/// Acquire a lock in the directory given in the [`Lock`].
///
/// The method is blocking or not depending on the `Lock` object.
/// The method is blocking or not depending on the [`Lock`] object.
fn acquire_lock(&self, lock: &Lock) -> Result<DirectoryLock, LockError> {
let mut box_directory = self.box_clone();
let mut retry_policy = retry_policy(lock.is_blocking);
@@ -210,15 +211,15 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
}
/// Registers a callback that will be called whenever a change on the `meta.json`
/// using the `atomic_write` API is detected.
/// using the [`Directory::atomic_write()`] API is detected.
///
/// The behavior when using `.watch()` on a file using [Directory::open_write] is, on the other
/// hand, undefined.
/// The behavior when using `.watch()` on a file using [`Directory::open_write()`] is, on the
/// other hand, undefined.
///
/// The file will be watched for the lifetime of the returned `WatchHandle`. The caller is
/// required to keep it.
/// It does not override previous callbacks. When the file is modified, all callback that are
/// registered (and whose `WatchHandle` is still alive) are triggered.
/// registered (and whose [`WatchHandle`] is still alive) are triggered.
///
/// Internally, tantivy only uses this API to detect new commits to implement the
/// `OnCommit` `ReloadPolicy`. Not implementing watch in a `Directory` only prevents the

18
src/directory/directory_lock.rs
View File

@@ -4,12 +4,14 @@ use once_cell::sync::Lazy;
/// A directory lock.
///
/// A lock is associated to a specific path and some
/// [`LockParams`](./enum.LockParams.html).
/// A lock is associated with a specific path.
///
/// The lock will be passed to [`Directory::acquire_lock`](crate::Directory::acquire_lock).
///
/// Tantivy itself uses only two locks but client application
/// can use the directory facility to define their own locks.
/// - [INDEX_WRITER_LOCK]
/// - [META_LOCK]
/// - [`INDEX_WRITER_LOCK`]
/// - [`META_LOCK`]
///
/// Check out these locks documentation for more information.
#[derive(Debug)]
@@ -18,19 +20,21 @@ pub struct Lock {
/// Depending on the platform, the lock might rely on the creation
/// and deletion of this filepath.
pub filepath: PathBuf,
/// `lock_params` describes whether acquiring the lock is meant
/// `is_blocking` describes whether acquiring the lock is meant
/// to be a blocking operation or a non-blocking.
///
/// Acquiring a blocking lock blocks until the lock is
/// available.
/// Acquiring a blocking lock returns rapidly, either successfully
///
/// Acquiring a non-blocking lock returns rapidly, either successfully
/// or with an error signifying that someone is already holding
/// the lock.
pub is_blocking: bool,
}
/// Only one process should be able to write tantivy's index at a time.
/// This lock file, when present, is in charge of preventing other processes to open an IndexWriter.
/// This lock file, when present, is in charge of preventing other processes to open an
/// `IndexWriter`.
///
/// If the process is killed and this file remains, it is safe to remove it manually.
///

4
src/directory/error.rs
View File

@@ -4,7 +4,9 @@ use std::{fmt, io};
use crate::Version;
/// Error while trying to acquire a directory lock.
/// Error while trying to acquire a directory [lock](crate::directory::Lock).
///
/// This is returned from [`Directory::acquire_lock`](crate::Directory::acquire_lock).
#[derive(Debug, Clone, Error)]
pub enum LockError {
/// Failed to acquired a lock as it is already held by another

9
src/directory/file_slice.rs
View File

@@ -1,5 +1,5 @@
use std::ops::{Deref, Range};
use std::sync::{Arc, Weak};
use std::sync::Arc;
use std::{fmt, io};
use async_trait::async_trait;
@@ -8,16 +8,13 @@ use stable_deref_trait::StableDeref;
use crate::directory::OwnedBytes;
pub type ArcBytes = Arc<dyn Deref<Target = [u8]> + Send + Sync + 'static>;
pub type WeakArcBytes = Weak<dyn Deref<Target = [u8]> + Send + Sync + 'static>;
/// Objects that represents files sections in tantivy.
///
/// By contract, whatever happens to the directory file, as long as a FileHandle
/// is alive, the data associated with it cannot be altered or destroyed.
///
/// The underlying behavior is therefore specific to the `Directory` that created it.
/// Despite its name, a `FileSlice` may or may not directly map to an actual file
/// The underlying behavior is therefore specific to the [`Directory`](crate::Directory) that
/// created it. Despite its name, a [`FileSlice`] may or may not directly map to an actual file
/// on the filesystem.
#[async_trait]

2
src/directory/file_watcher.rs
View File

@@ -9,7 +9,7 @@ use crc32fast::Hasher;
use crate::directory::{WatchCallback, WatchCallbackList, WatchHandle};
pub const POLLING_INTERVAL: Duration = Duration::from_millis(if cfg!(test) { 1 } else { 500 });
const POLLING_INTERVAL: Duration = Duration::from_millis(if cfg!(test) { 1 } else { 500 });
// Watches a file and executes registered callbacks when the file is modified.
pub struct FileWatcher {

85
src/directory/mmap_directory.rs
View File

@@ -3,7 +3,7 @@ use std::fs::{self, File, OpenOptions};
use std::io::{self, BufWriter, Read, Seek, Write};
use std::ops::Deref;
use std::path::{Path, PathBuf};
use std::sync::{Arc, RwLock};
use std::sync::{Arc, RwLock, Weak};
use std::{fmt, result};
use fs2::FileExt;
@@ -18,16 +18,19 @@ use crate::directory::error::{
};
use crate::directory::file_watcher::FileWatcher;
use crate::directory::{
AntiCallToken, ArcBytes, Directory, DirectoryLock, FileHandle, Lock, OwnedBytes,
TerminatingWrite, WatchCallback, WatchHandle, WeakArcBytes, WritePtr,
AntiCallToken, Directory, DirectoryLock, FileHandle, Lock, OwnedBytes, TerminatingWrite,
WatchCallback, WatchHandle, WritePtr,
};
pub type ArcBytes = Arc<dyn Deref<Target = [u8]> + Send + Sync + 'static>;
pub type WeakArcBytes = Weak<dyn Deref<Target = [u8]> + Send + Sync + 'static>;
/// Create a default io error given a string.
pub(crate) fn make_io_err(msg: String) -> io::Error {
io::Error::new(io::ErrorKind::Other, msg)
}
/// Returns None iff the file exists, can be read, but is empty (and hence
/// Returns `None` iff the file exists, can be read, but is empty (and hence
/// cannot be mmapped)
fn open_mmap(full_path: &Path) -> result::Result<Option<Mmap>, OpenReadError> {
let file = File::open(full_path).map_err(|io_err| {
@@ -56,10 +59,10 @@ fn open_mmap(full_path: &Path) -> result::Result<Option<Mmap>, OpenReadError> {
#[derive(Default, Clone, Debug, Serialize, Deserialize)]
pub struct CacheCounters {
// Number of time the cache prevents to call `mmap`
/// Number of time the cache prevents to call `mmap`
pub hit: usize,
// Number of time tantivy had to call `mmap`
// as no entry was in the cache.
/// Number of time tantivy had to call `mmap`
/// as no entry was in the cache.
pub miss: usize,
}
@@ -301,7 +304,7 @@ pub(crate) fn atomic_write(path: &Path, content: &[u8]) -> io::Result<()> {
"Path {:?} does not have parent directory.",
)
})?;
let mut tempfile = tempfile::Builder::new().tempfile_in(&parent_path)?;
let mut tempfile = tempfile::Builder::new().tempfile_in(parent_path)?;
tempfile.write_all(content)?;
tempfile.flush()?;
tempfile.as_file_mut().sync_data()?;
@@ -334,7 +337,7 @@ impl Directory for MmapDirectory {
Ok(Arc::new(owned_bytes))
}
/// Any entry associated to the path in the mmap will be
/// Any entry associated with the path in the mmap will be
/// removed before the file is deleted.
fn delete(&self, path: &Path) -> result::Result<(), DeleteError> {
let full_path = self.resolve_path(path);
@@ -472,6 +475,8 @@ mod tests {
// There are more tests in directory/mod.rs
// The following tests are specific to the MmapDirectory
use std::time::Duration;
use common::HasLen;
use super::*;
@@ -566,9 +571,21 @@ mod tests {
assert_eq!(mmap_directory.get_cache_info().mmapped.len(), 0);
}
fn assert_eventually<P: Fn() -> Option<String>>(predicate: P) {
for _ in 0..30 {
if predicate().is_none() {
break;
}
std::thread::sleep(Duration::from_millis(200));
}
if let Some(error_msg) = predicate() {
panic!("{}", error_msg);
}
}
#[test]
fn test_mmap_released() -> crate::Result<()> {
let mmap_directory = MmapDirectory::create_from_tempdir()?;
fn test_mmap_released() {
let mmap_directory = MmapDirectory::create_from_tempdir().unwrap();
let mut schema_builder: SchemaBuilder = Schema::builder();
let text_field = schema_builder.add_text_field("text", TEXT);
let schema = schema_builder.build();
@@ -577,40 +594,56 @@ mod tests {
let index =
Index::create(mmap_directory.clone(), schema, IndexSettings::default()).unwrap();
let mut index_writer = index.writer_for_tests()?;
let mut index_writer = index.writer_for_tests().unwrap();
let mut log_merge_policy = LogMergePolicy::default();
log_merge_policy.set_min_num_segments(3);
index_writer.set_merge_policy(Box::new(log_merge_policy));
for _num_commits in 0..10 {
for _ in 0..10 {
index_writer.add_document(doc!(text_field=>"abc"))?;
index_writer.add_document(doc!(text_field=>"abc")).unwrap();
}
index_writer.commit()?;
index_writer.commit().unwrap();
}
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::Manual)
.try_into()?;
.try_into()
.unwrap();
for _ in 0..4 {
index_writer.add_document(doc!(text_field=>"abc"))?;
index_writer.commit()?;
reader.reload()?;
index_writer.add_document(doc!(text_field=>"abc")).unwrap();
index_writer.commit().unwrap();
reader.reload().unwrap();
}
index_writer.wait_merging_threads()?;
index_writer.wait_merging_threads().unwrap();
reader.reload()?;
reader.reload().unwrap();
let num_segments = reader.searcher().segment_readers().len();
assert!(num_segments <= 4);
let num_components_except_deletes_and_tempstore =
crate::core::SegmentComponent::iterator().len() - 2;
assert_eq!(
num_segments * num_components_except_deletes_and_tempstore,
mmap_directory.get_cache_info().mmapped.len()
);
let max_num_mmapped = num_components_except_deletes_and_tempstore * num_segments;
assert_eventually(|| {
let num_mmapped = mmap_directory.get_cache_info().mmapped.len();
if num_mmapped > max_num_mmapped {
Some(format!(
"Expected at most {max_num_mmapped} mmapped files, got {num_mmapped}"
))
} else {
None
}
});
}
assert!(mmap_directory.get_cache_info().mmapped.is_empty());
Ok(())
// This test failed on CI. The last Mmap is dropped from the merging thread so there might
// be a race condition indeed.
assert_eventually(|| {
let num_mmapped = mmap_directory.get_cache_info().mmapped.len();
if num_mmapped > 0 {
Some(format!("Expected no mmapped files, got {num_mmapped}"))
} else {
None
}
});
}
}

1
src/directory/mod.rs
View File

@@ -26,7 +26,6 @@ pub use ownedbytes::OwnedBytes;
pub(crate) use self::composite_file::{CompositeFile, CompositeWrite};
pub use self::directory::{Directory, DirectoryClone, DirectoryLock};
pub use self::directory_lock::{Lock, INDEX_WRITER_LOCK, META_LOCK};
pub(crate) use self::file_slice::{ArcBytes, WeakArcBytes};
pub use self::file_slice::{FileHandle, FileSlice};
pub use self::ram_directory::RamDirectory;
pub use self::watch_event_router::{WatchCallback, WatchCallbackList, WatchHandle};

45
src/directory/ram_directory.rs
View File

@@ -15,7 +15,7 @@ use crate::directory::{
WatchHandle, WritePtr,
};
/// Writer associated with the `RamDirectory`
/// Writer associated with the [`RamDirectory`].
///
/// The Writer just writes a buffer.
struct VecWriter {
@@ -136,18 +136,32 @@ impl RamDirectory {
Self::default()
}
/// Deep clones the directory.
///
/// Ulterior writes on one of the copy
/// will not affect the other copy.
pub fn deep_clone(&self) -> RamDirectory {
let inner_clone = InnerDirectory {
fs: self.fs.read().unwrap().fs.clone(),
watch_router: Default::default(),
};
RamDirectory {
fs: Arc::new(RwLock::new(inner_clone)),
}
}
/// Returns the sum of the size of the different files
/// in the RamDirectory.
/// in the [`RamDirectory`].
pub fn total_mem_usage(&self) -> usize {
self.fs.read().unwrap().total_mem_usage()
}
/// Write a copy of all of the files saved in the RamDirectory in the target `Directory`.
/// Write a copy of all of the files saved in the [`RamDirectory`] in the target [`Directory`].
///
/// Files are all written using the `Directory::write` meaning, even if they were
/// written using the `atomic_write` api.
/// Files are all written using the [`Directory::open_write()`] meaning, even if they were
/// written using the [`Directory::atomic_write()`] api.
///
/// If an error is encounterred, files may be persisted partially.
/// If an error is encountered, files may be persisted partially.
pub fn persist(&self, dest: &dyn Directory) -> crate::Result<()> {
let wlock = self.fs.write().unwrap();
for (path, file) in wlock.fs.iter() {
@@ -256,4 +270,23 @@ mod tests {
assert_eq!(directory_copy.atomic_read(path_atomic).unwrap(), msg_atomic);
assert_eq!(directory_copy.atomic_read(path_seq).unwrap(), msg_seq);
}
#[test]
fn test_ram_directory_deep_clone() {
let dir = RamDirectory::default();
let test = Path::new("test");
let test2 = Path::new("test2");
dir.atomic_write(test, b"firstwrite").unwrap();
let dir_clone = dir.deep_clone();
assert_eq!(
dir_clone.atomic_read(test).unwrap(),
dir.atomic_read(test).unwrap()
);
dir.atomic_write(test, b"original").unwrap();
dir_clone.atomic_write(test, b"clone").unwrap();
dir_clone.atomic_write(test2, b"clone2").unwrap();
assert_eq!(dir.atomic_read(test).unwrap(), b"original");
assert_eq!(&dir_clone.atomic_read(test).unwrap(), b"clone");
assert_eq!(&dir_clone.atomic_read(test2).unwrap(), b"clone2");
}
}

26
src/docset.rs
View File

@@ -3,10 +3,10 @@ use std::borrow::{Borrow, BorrowMut};
use crate::fastfield::AliveBitSet;
use crate::DocId;
/// Sentinel value returned when a DocSet has been entirely consumed.
/// Sentinel value returned when a [`DocSet`] has been entirely consumed.
///
/// This is not u32::MAX as one would have expected, due to the lack of SSE2 instructions
/// to compare [u32; 4].
/// This is not `u32::MAX` as one would have expected, due to the lack of SSE2 instructions
/// to compare `[u32; 4]`.
pub const TERMINATED: DocId = i32::MAX as u32;
/// Represents an iterable set of sorted doc ids.
@@ -20,21 +20,21 @@ pub trait DocSet: Send {
/// assert_eq!(doc, docset.doc());
/// ```
///
/// If we reached the end of the DocSet, TERMINATED should be returned.
/// If we reached the end of the `DocSet`, [`TERMINATED`] should be returned.
///
/// Calling `.advance()` on a terminated DocSet should be supported, and TERMINATED should
/// Calling `.advance()` on a terminated `DocSet` should be supported, and [`TERMINATED`] should
/// be returned.
fn advance(&mut self) -> DocId;
/// Advances the DocSet forward until reaching the target, or going to the
/// lowest DocId greater than the target.
/// Advances the `DocSet` forward until reaching the target, or going to the
/// lowest [`DocId`] greater than the target.
///
/// If the end of the DocSet is reached, TERMINATED is returned.
/// If the end of the `DocSet` is reached, [`TERMINATED`] is returned.
///
/// Calling `.seek(target)` on a terminated DocSet is legal. Implementation
/// of DocSet should support it.
/// Calling `.seek(target)` on a terminated `DocSet` is legal. Implementation
/// of `DocSet` should support it.
///
/// Calling `seek(TERMINATED)` is also legal and is the normal way to consume a DocSet.
/// Calling `seek(TERMINATED)` is also legal and is the normal way to consume a `DocSet`.
fn seek(&mut self, target: DocId) -> DocId {
let mut doc = self.doc();
debug_assert!(doc <= target);
@@ -73,9 +73,9 @@ pub trait DocSet: Send {
}
/// Returns the current document
/// Right after creating a new DocSet, the docset points to the first document.
/// Right after creating a new `DocSet`, the docset points to the first document.
///
/// If the DocSet is empty, .doc() should return `TERMINATED`.
/// If the `DocSet` is empty, `.doc()` should return [`TERMINATED`].
fn doc(&self) -> DocId;
/// Returns a best-effort hint of the

7
src/fastfield/bytes/mod.rs
View File

@@ -6,7 +6,7 @@ pub use self::writer::BytesFastFieldWriter;
#[cfg(test)]
mod tests {
use crate::query::TermQuery;
use crate::query::{EnableScoring, TermQuery};
use crate::schema::{BytesOptions, IndexRecordOption, Schema, Value, FAST, INDEXED, STORED};
use crate::{DocAddress, DocSet, Index, Searcher, Term};
@@ -82,7 +82,7 @@ mod tests {
let field = searcher.schema().get_field("string_bytes").unwrap();
let term = Term::from_field_bytes(field, b"lucene".as_ref());
let term_query = TermQuery::new(term, IndexRecordOption::Basic);
let term_weight = term_query.specialized_weight(&searcher, true)?;
let term_weight = term_query.specialized_weight(EnableScoring::Enabled(&searcher))?;
let term_scorer = term_weight.specialized_scorer(searcher.segment_reader(0), 1.0)?;
assert_eq!(term_scorer.doc(), 0u32);
Ok(())
@@ -95,7 +95,8 @@ mod tests {
let field = searcher.schema().get_field("string_bytes").unwrap();
let term = Term::from_field_bytes(field, b"lucene".as_ref());
let term_query = TermQuery::new(term, IndexRecordOption::Basic);
let term_weight_err = term_query.specialized_weight(&searcher, false);
let term_weight_err =
term_query.specialized_weight(EnableScoring::Disabled(searcher.schema()));
assert!(matches!(
term_weight_err,
Err(crate::TantivyError::SchemaError(_))

49
src/fastfield/bytes/reader.rs
View File

@@ -1,5 +1,9 @@
use std::sync::Arc;
use fastfield_codecs::Column;
use crate::directory::{FileSlice, OwnedBytes};
use crate::fastfield::{DynamicFastFieldReader, FastFieldReader, MultiValueLength};
use crate::fastfield::MultiValueIndex;
use crate::DocId;
/// Reader for byte array fast fields
@@ -14,48 +18,41 @@ use crate::DocId;
/// and the start index for the next document, and keeping the bytes in between.
#[derive(Clone)]
pub struct BytesFastFieldReader {
idx_reader: DynamicFastFieldReader<u64>,
idx_reader: MultiValueIndex,
values: OwnedBytes,
}
impl BytesFastFieldReader {
pub(crate) fn open(
idx_reader: DynamicFastFieldReader<u64>,
idx_reader: Arc<dyn Column<u64>>,
values_file: FileSlice,
) -> crate::Result<BytesFastFieldReader> {
let values = values_file.read_bytes()?;
Ok(BytesFastFieldReader { idx_reader, values })
Ok(BytesFastFieldReader {
idx_reader: MultiValueIndex::new(idx_reader),
values,
})
}
fn range(&self, doc: DocId) -> (usize, usize) {
let start = self.idx_reader.get(doc) as usize;
let stop = self.idx_reader.get(doc + 1) as usize;
(start, stop)
/// returns the multivalue index
pub fn get_index_reader(&self) -> &MultiValueIndex {
&self.idx_reader
}
/// Returns the bytes associated to the given `doc`
/// Returns the bytes associated with the given `doc`
pub fn get_bytes(&self, doc: DocId) -> &[u8] {
let (start, stop) = self.range(doc);
&self.values.as_slice()[start..stop]
let range = self.idx_reader.range(doc);
&self.values.as_slice()[range.start as usize..range.end as usize]
}
/// Returns the length of the bytes associated to the given `doc`
pub fn num_bytes(&self, doc: DocId) -> usize {
let (start, stop) = self.range(doc);
stop - start
/// Returns the length of the bytes associated with the given `doc`
pub fn num_bytes(&self, doc: DocId) -> u64 {
let range = self.idx_reader.range(doc);
(range.end - range.start) as u64
}
/// Returns the overall number of bytes in this bytes fast field.
pub fn total_num_bytes(&self) -> usize {
self.values.len()
}
}
impl MultiValueLength for BytesFastFieldReader {
fn get_len(&self, doc_id: DocId) -> u64 {
self.num_bytes(doc_id) as u64
}
fn get_total_len(&self) -> u64 {
self.total_num_bytes() as u64
pub fn total_num_bytes(&self) -> u32 {
self.values.len() as u32
}
}

49
src/fastfield/bytes/writer.rs
View File

@@ -1,6 +1,9 @@
use std::io;
use std::io::{self, Write};
use fastfield_codecs::VecColumn;
use crate::fastfield::serializer::CompositeFastFieldSerializer;
use crate::fastfield::MultivalueStartIndex;
use crate::indexer::doc_id_mapping::DocIdMapping;
use crate::schema::{Document, Field, Value};
use crate::DocId;
@@ -10,16 +13,18 @@ use crate::DocId;
/// This `BytesFastFieldWriter` is only useful for advanced users.
/// The normal way to get your associated bytes in your index
/// is to
/// - declare your field with fast set to `Cardinality::SingleValue`
/// - declare your field with fast set to
/// [`Cardinality::SingleValue`](crate::schema::Cardinality::SingleValue)
/// in your schema
/// - add your document simply by calling `.add_document(...)` with associating bytes to the field.
///
/// The `BytesFastFieldWriter` can be acquired from the
/// fast field writer by calling
/// [`.get_bytes_writer(...)`](./struct.FastFieldsWriter.html#method.get_bytes_writer).
/// [`.get_bytes_writer_mut(...)`](crate::fastfield::FastFieldsWriter::get_bytes_writer_mut).
///
/// Once acquired, writing is done by calling `.add_document_val(&[u8])`
/// once per document, even if there are no bytes associated to it.
/// Once acquired, writing is done by calling
/// [`.add_document_val(&[u8])`](BytesFastFieldWriter::add_document_val)
/// once per document, even if there are no bytes associated with it.
pub struct BytesFastFieldWriter {
field: Field,
vals: Vec<u8>,
@@ -40,7 +45,7 @@ impl BytesFastFieldWriter {
pub fn mem_usage(&self) -> usize {
self.vals.capacity() + self.doc_index.capacity() * std::mem::size_of::<u64>()
}
/// Access the field associated to the `BytesFastFieldWriter`
/// Access the field associated with the `BytesFastFieldWriter`
pub fn field(&self) -> Field {
self.field
}
@@ -52,17 +57,18 @@ impl BytesFastFieldWriter {
/// Shift to the next document and add all of the
/// matching field values present in the document.
pub fn add_document(&mut self, doc: &Document) {
pub fn add_document(&mut self, doc: &Document) -> crate::Result<()> {
self.next_doc();
for field_value in doc.get_all(self.field) {
if let Value::Bytes(ref bytes) = field_value {
self.vals.extend_from_slice(bytes);
return;
return Ok(());
}
}
Ok(())
}
/// Register the bytes associated to a document.
/// Register the bytes associated with a document.
///
/// The method returns the `DocId` of the document that was
/// just written.
@@ -104,22 +110,27 @@ impl BytesFastFieldWriter {
/// Serializes the fast field values by pushing them to the `FastFieldSerializer`.
pub fn serialize(
&self,
mut self,
serializer: &mut CompositeFastFieldSerializer,
doc_id_map: Option<&DocIdMapping>,
) -> io::Result<()> {
// writing the offset index
let mut doc_index_serializer =
serializer.new_u64_fast_field_with_idx(self.field, 0, self.vals.len() as u64, 0)?;
let mut offset = 0;
for vals in self.get_ordered_values(doc_id_map) {
doc_index_serializer.add_val(offset)?;
offset += vals.len() as u64;
{
self.doc_index.push(self.vals.len() as u64);
let col = VecColumn::from(&self.doc_index[..]);
if let Some(doc_id_map) = doc_id_map {
let multi_value_start_index = MultivalueStartIndex::new(&col, doc_id_map);
serializer.create_auto_detect_u64_fast_field_with_idx(
self.field,
multi_value_start_index,
0,
)?;
} else {
serializer.create_auto_detect_u64_fast_field_with_idx(self.field, col, 0)?;
}
}
doc_index_serializer.add_val(self.vals.len() as u64)?;
doc_index_serializer.close_field()?;
// writing the values themselves
let mut value_serializer = serializer.new_bytes_fast_field_with_idx(self.field, 1);
let mut value_serializer = serializer.new_bytes_fast_field(self.field);
// the else could be removed, but this is faster (difference not benchmarked)
if let Some(doc_id_map) = doc_id_map {
for vals in self.get_ordered_values(Some(doc_id_map)) {

6
src/fastfield/facet_reader.rs
View File

@@ -7,7 +7,7 @@ use crate::termdict::{TermDictionary, TermOrdinal};
use crate::DocId;
/// The facet reader makes it possible to access the list of
/// facets associated to a given document in a specific
/// facets associated with a given document in a specific
/// segment.
///
/// Rather than manipulating `Facet` object directly, the API
@@ -58,7 +58,7 @@ impl FacetReader {
&self.term_dict
}
/// Given a term ordinal returns the term associated to it.
/// Given a term ordinal returns the term associated with it.
pub fn facet_from_ord(
&mut self,
facet_ord: TermOrdinal,
@@ -74,7 +74,7 @@ impl FacetReader {
Ok(())
}
/// Return the list of facet ordinals associated to a document.
/// Return the list of facet ordinals associated with a document.
pub fn facet_ords(&self, doc: DocId, output: &mut Vec<u64>) {
self.term_ords.get_vals(doc, output);
}

325
src/fastfield/gcd.rs
View File

@@ -1,325 +0,0 @@
use std::io::{self, Write};
use std::num::NonZeroU64;
use common::BinarySerializable;
use fastdivide::DividerU64;
use fastfield_codecs::FastFieldCodecReader;
use ownedbytes::OwnedBytes;
pub const GCD_DEFAULT: u64 = 1;
/// Wrapper for accessing a fastfield.
///
/// Holds the data and the codec to the read the data.
#[derive(Clone)]
pub struct GCDFastFieldCodec<CodecReader> {
gcd: u64,
min_value: u64,
reader: CodecReader,
}
impl<C: FastFieldCodecReader + Clone> FastFieldCodecReader for GCDFastFieldCodec<C> {
/// Opens a fast field given the bytes.
fn open_from_bytes(bytes: OwnedBytes) -> std::io::Result<Self> {
let footer_offset = bytes.len() - 16;
let (body, mut footer) = bytes.split(footer_offset);
let gcd = u64::deserialize(&mut footer)?;
let min_value = u64::deserialize(&mut footer)?;
let reader = C::open_from_bytes(body)?;
Ok(GCDFastFieldCodec {
gcd,
min_value,
reader,
})
}
#[inline]
fn get_u64(&self, doc: u64) -> u64 {
let mut data = self.reader.get_u64(doc);
data *= self.gcd;
data += self.min_value;
data
}
fn min_value(&self) -> u64 {
self.min_value + self.reader.min_value() * self.gcd
}
fn max_value(&self) -> u64 {
self.min_value + self.reader.max_value() * self.gcd
}
}
pub fn write_gcd_header<W: Write>(field_write: &mut W, min_value: u64, gcd: u64) -> io::Result<()> {
gcd.serialize(field_write)?;
min_value.serialize(field_write)?;
Ok(())
}
/// Compute the gcd of two non null numbers.
///
/// It is recommended, but not required, to feed values such that `large >= small`.
fn compute_gcd(mut large: NonZeroU64, mut small: NonZeroU64) -> NonZeroU64 {
loop {
let rem: u64 = large.get() % small;
if let Some(new_small) = NonZeroU64::new(rem) {
(large, small) = (small, new_small);
} else {
return small;
}
}
}
// Find GCD for iterator of numbers
pub fn find_gcd(numbers: impl Iterator<Item = u64>) -> Option<NonZeroU64> {
let mut numbers = numbers.flat_map(NonZeroU64::new);
let mut gcd: NonZeroU64 = numbers.next()?;
if gcd.get() == 1 {
return Some(gcd);
}
let mut gcd_divider = DividerU64::divide_by(gcd.get());
for val in numbers {
let remainder = val.get() - (gcd_divider.divide(val.get())) * gcd.get();
if remainder == 0 {
continue;
}
gcd = compute_gcd(val, gcd);
if gcd.get() == 1 {
return Some(gcd);
}
gcd_divider = DividerU64::divide_by(gcd.get());
}
Some(gcd)
}
#[cfg(test)]
mod tests {
use std::collections::HashMap;
use std::num::NonZeroU64;
use std::path::Path;
use std::time::{Duration, SystemTime};
use common::HasLen;
use crate::directory::{CompositeFile, RamDirectory, WritePtr};
use crate::fastfield::gcd::compute_gcd;
use crate::fastfield::serializer::FastFieldCodecEnableCheck;
use crate::fastfield::tests::{FIELD, FIELDI64, SCHEMA, SCHEMAI64};
use crate::fastfield::{
find_gcd, CompositeFastFieldSerializer, DynamicFastFieldReader, FastFieldCodecType,
FastFieldReader, FastFieldsWriter, ALL_CODECS,
};
use crate::schema::{Cardinality, Schema};
use crate::{DateOptions, DatePrecision, DateTime, Directory};
fn get_index(
docs: &[crate::Document],
schema: &Schema,
codec_enable_checker: FastFieldCodecEnableCheck,
) -> crate::Result<RamDirectory> {
let directory: RamDirectory = RamDirectory::create();
{
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer =
CompositeFastFieldSerializer::from_write_with_codec(write, codec_enable_checker)
.unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(schema);
for doc in docs {
fast_field_writers.add_document(doc);
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
}
Ok(directory)
}
fn test_fastfield_gcd_i64_with_codec(
code_type: FastFieldCodecType,
num_vals: usize,
) -> crate::Result<()> {
let path = Path::new("test");
let mut docs = vec![];
for i in 1..=num_vals {
let val = (i as i64 - 5) * 1000i64;
docs.push(doc!(*FIELDI64=>val));
}
let directory = get_index(&docs, &SCHEMAI64, code_type.into())?;
let file = directory.open_read(path).unwrap();
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<i64>::open(file)?;
assert_eq!(fast_field_reader.get(0), -4000i64);
assert_eq!(fast_field_reader.get(1), -3000i64);
assert_eq!(fast_field_reader.get(2), -2000i64);
assert_eq!(fast_field_reader.max_value(), (num_vals as i64 - 5) * 1000);
assert_eq!(fast_field_reader.min_value(), -4000i64);
let file = directory.open_read(path).unwrap();
// Can't apply gcd
let path = Path::new("test");
docs.pop();
docs.push(doc!(*FIELDI64=>2001i64));
let directory = get_index(&docs, &SCHEMAI64, code_type.into())?;
let file2 = directory.open_read(path).unwrap();
assert!(file2.len() > file.len());
Ok(())
}
#[test]
fn test_fastfield_gcd_i64() -> crate::Result<()> {
for &code_type in ALL_CODECS {
test_fastfield_gcd_i64_with_codec(code_type, 5005)?;
}
Ok(())
}
fn test_fastfield_gcd_u64_with_codec(
code_type: FastFieldCodecType,
num_vals: usize,
) -> crate::Result<()> {
let path = Path::new("test");
let mut docs = vec![];
for i in 1..=num_vals {
let val = i as u64 * 1000u64;
docs.push(doc!(*FIELD=>val));
}
let directory = get_index(&docs, &SCHEMA, code_type.into())?;
let file = directory.open_read(path).unwrap();
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(file)?;
assert_eq!(fast_field_reader.get(0), 1000u64);
assert_eq!(fast_field_reader.get(1), 2000u64);
assert_eq!(fast_field_reader.get(2), 3000u64);
assert_eq!(fast_field_reader.max_value(), num_vals as u64 * 1000);
assert_eq!(fast_field_reader.min_value(), 1000u64);
let file = directory.open_read(path).unwrap();
// Can't apply gcd
let path = Path::new("test");
docs.pop();
docs.push(doc!(*FIELDI64=>2001u64));
let directory = get_index(&docs, &SCHEMA, code_type.into())?;
let file2 = directory.open_read(path).unwrap();
assert!(file2.len() > file.len());
Ok(())
}
#[test]
fn test_fastfield_gcd_u64() -> crate::Result<()> {
for &code_type in ALL_CODECS {
test_fastfield_gcd_u64_with_codec(code_type, 5005)?;
}
Ok(())
}
#[test]
pub fn test_fastfield2() {
let test_fastfield = DynamicFastFieldReader::<u64>::from(vec![100, 200, 300]);
assert_eq!(test_fastfield.get(0), 100);
assert_eq!(test_fastfield.get(1), 200);
assert_eq!(test_fastfield.get(2), 300);
}
#[test]
pub fn test_gcd_date() -> crate::Result<()> {
let size_prec_sec =
test_gcd_date_with_codec(FastFieldCodecType::Bitpacked, DatePrecision::Seconds)?;
let size_prec_micro =
test_gcd_date_with_codec(FastFieldCodecType::Bitpacked, DatePrecision::Microseconds)?;
assert!(size_prec_sec < size_prec_micro);
let size_prec_sec =
test_gcd_date_with_codec(FastFieldCodecType::Linear, DatePrecision::Seconds)?;
let size_prec_micro =
test_gcd_date_with_codec(FastFieldCodecType::Linear, DatePrecision::Microseconds)?;
assert!(size_prec_sec < size_prec_micro);
Ok(())
}
fn test_gcd_date_with_codec(
codec_type: FastFieldCodecType,
precision: DatePrecision,
) -> crate::Result<usize> {
let time1 = DateTime::from_timestamp_micros(
SystemTime::now()
.duration_since(SystemTime::UNIX_EPOCH)
.unwrap()
.as_secs() as i64,
);
let time2 = DateTime::from_timestamp_micros(
SystemTime::now()
.checked_sub(Duration::from_micros(4111))
.unwrap()
.duration_since(SystemTime::UNIX_EPOCH)
.unwrap()
.as_secs() as i64,
);
let time3 = DateTime::from_timestamp_micros(
SystemTime::now()
.checked_sub(Duration::from_millis(2000))
.unwrap()
.duration_since(SystemTime::UNIX_EPOCH)
.unwrap()
.as_secs() as i64,
);
let mut schema_builder = Schema::builder();
let date_options = DateOptions::default()
.set_fast(Cardinality::SingleValue)
.set_precision(precision);
let field = schema_builder.add_date_field("field", date_options);
let schema = schema_builder.build();
let docs = vec![doc!(field=>time1), doc!(field=>time2), doc!(field=>time3)];
let directory = get_index(&docs, &schema, codec_type.into())?;
let path = Path::new("test");
let file = directory.open_read(path).unwrap();
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(*FIELD).unwrap();
let len = file.len();
let test_fastfield = DynamicFastFieldReader::<DateTime>::open(file)?;
assert_eq!(test_fastfield.get(0), time1.truncate(precision));
assert_eq!(test_fastfield.get(1), time2.truncate(precision));
assert_eq!(test_fastfield.get(2), time3.truncate(precision));
Ok(len)
}
#[test]
fn test_compute_gcd() {
let test_compute_gcd_aux = |large, small, expected| {
let large = NonZeroU64::new(large).unwrap();
let small = NonZeroU64::new(small).unwrap();
let expected = NonZeroU64::new(expected).unwrap();
assert_eq!(compute_gcd(small, large), expected);
assert_eq!(compute_gcd(large, small), expected);
};
test_compute_gcd_aux(1, 4, 1);
test_compute_gcd_aux(2, 4, 2);
test_compute_gcd_aux(10, 25, 5);
test_compute_gcd_aux(25, 25, 25);
}
#[test]
fn find_gcd_test() {
assert_eq!(find_gcd([0].into_iter()), None);
assert_eq!(find_gcd([0, 10].into_iter()), NonZeroU64::new(10));
assert_eq!(find_gcd([10, 0].into_iter()), NonZeroU64::new(10));
assert_eq!(find_gcd([].into_iter()), None);
assert_eq!(find_gcd([15, 30, 5, 10].into_iter()), NonZeroU64::new(5));
assert_eq!(find_gcd([15, 16, 10].into_iter()), NonZeroU64::new(1));
assert_eq!(find_gcd([0, 5, 5, 5].into_iter()), NonZeroU64::new(5));
assert_eq!(find_gcd([0, 0].into_iter()), None);
}
}

662
src/fastfield/mod.rs
View File

@@ -7,237 +7,118 @@
//! It is designed for the fast random access of some document
//! fields given a document id.
//!
//! `FastField` are useful when a field is required for all or most of
//! the `DocSet` : for instance for scoring, grouping, filtering, or faceting.
//! Fast fields are useful when a field is required for all or most of
//! the `DocSet`: for instance for scoring, grouping, aggregation, filtering, or faceting.
//!
//!
//! Fields have to be declared as `FAST` in the schema.
//! Currently supported fields are: u64, i64, f64 and bytes.
//! Fields have to be declared as `FAST` in the schema.
//! Currently supported fields are: u64, i64, f64, bytes and text.
//!
//! u64, i64 and f64 fields are stored in a bit-packed fashion so that
//! their memory usage is directly linear with the amplitude of the
//! values stored.
//! Fast fields are stored in with [different codecs](fastfield_codecs). The best codec is detected
//! automatically, when serializing.
//!
//! Read access performance is comparable to that of an array lookup.
use fastfield_codecs::FastFieldCodecType;
use fastfield_codecs::MonotonicallyMappableToU64;
pub use self::alive_bitset::{intersect_alive_bitsets, write_alive_bitset, AliveBitSet};
pub use self::bytes::{BytesFastFieldReader, BytesFastFieldWriter};
pub use self::error::{FastFieldNotAvailableError, Result};
pub use self::facet_reader::FacetReader;
pub(crate) use self::gcd::{find_gcd, GCDFastFieldCodec, GCD_DEFAULT};
pub use self::multivalued::{MultiValuedFastFieldReader, MultiValuedFastFieldWriter};
pub use self::reader::{DynamicFastFieldReader, FastFieldReader};
pub(crate) use self::multivalued::{get_fastfield_codecs_for_multivalue, MultivalueStartIndex};
pub use self::multivalued::{
MultiValueIndex, MultiValueU128FastFieldWriter, MultiValuedFastFieldReader,
MultiValuedFastFieldWriter, MultiValuedU128FastFieldReader,
};
pub use self::readers::FastFieldReaders;
pub(crate) use self::readers::{type_and_cardinality, FastType};
pub use self::serializer::{CompositeFastFieldSerializer, FastFieldDataAccess, FastFieldStats};
pub use self::serializer::{Column, CompositeFastFieldSerializer};
use self::writer::unexpected_value;
pub use self::writer::{FastFieldsWriter, IntFastFieldWriter};
use crate::schema::{Cardinality, FieldType, Type, Value};
use crate::{DateTime, DocId};
use crate::schema::{Type, Value};
use crate::DateTime;
mod alive_bitset;
mod bytes;
mod error;
mod facet_reader;
mod gcd;
mod multivalued;
mod reader;
mod readers;
mod serializer;
mod writer;
pub(crate) const ALL_CODECS: &[FastFieldCodecType; 3] = &[
FastFieldCodecType::Bitpacked,
FastFieldCodecType::Linear,
FastFieldCodecType::BlockwiseLinear,
];
/// Trait for `BytesFastFieldReader` and `MultiValuedFastFieldReader` to return the length of data
/// for a doc_id
pub trait MultiValueLength {
/// returns the num of values associated to a doc_id
fn get_len(&self, doc_id: DocId) -> u64;
/// returns the sum of num values for all doc_ids
fn get_total_len(&self) -> u64;
}
/// Trait for types that are allowed for fast fields:
/// (u64, i64 and f64, bool, DateTime).
pub trait FastValue: Clone + Copy + Send + Sync + PartialOrd + 'static {
/// Converts a value from u64
///
/// Internally all fast field values are encoded as u64.
/// **Note: To be used for converting encoded Term, Posting values.**
fn from_u64(val: u64) -> Self;
/// Converts a value to u64.
///
/// Internally all fast field values are encoded as u64.
fn to_u64(&self) -> u64;
/// Returns the fast field cardinality that can be extracted from the given
/// `FieldType`.
///
/// If the type is not a fast field, `None` is returned.
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality>;
/// Cast value to `u64`.
/// The value is just reinterpreted in memory.
fn as_u64(&self) -> u64;
pub trait FastValue:
MonotonicallyMappableToU64 + Copy + Send + Sync + PartialOrd + 'static
{
/// Returns the `schema::Type` for this FastValue.
fn to_type() -> Type;
/// Build a default value. This default value is never used, so the value does not
/// really matter.
fn make_zero() -> Self {
Self::from_u64(0i64.to_u64())
Self::from_u64(0u64)
}
/// Returns the `schema::Type` for this FastValue.
fn to_type() -> Type;
}
impl FastValue for u64 {
fn from_u64(val: u64) -> Self {
val
}
fn to_u64(&self) -> u64 {
*self
}
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality> {
match *field_type {
FieldType::U64(ref integer_options) => integer_options.get_fastfield_cardinality(),
FieldType::Facet(_) => Some(Cardinality::MultiValues),
_ => None,
}
}
fn as_u64(&self) -> u64 {
*self
}
fn to_type() -> Type {
Type::U64
}
}
impl FastValue for i64 {
fn from_u64(val: u64) -> Self {
common::u64_to_i64(val)
}
fn to_u64(&self) -> u64 {
common::i64_to_u64(*self)
}
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality> {
match *field_type {
FieldType::I64(ref integer_options) => integer_options.get_fastfield_cardinality(),
_ => None,
}
}
fn as_u64(&self) -> u64 {
*self as u64
}
fn to_type() -> Type {
Type::I64
}
}
impl FastValue for f64 {
fn from_u64(val: u64) -> Self {
common::u64_to_f64(val)
}
fn to_u64(&self) -> u64 {
common::f64_to_u64(*self)
}
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality> {
match *field_type {
FieldType::F64(ref integer_options) => integer_options.get_fastfield_cardinality(),
_ => None,
}
}
fn as_u64(&self) -> u64 {
self.to_bits()
}
fn to_type() -> Type {
Type::F64
}
}
impl FastValue for bool {
fn from_u64(val: u64) -> Self {
val != 0u64
}
fn to_u64(&self) -> u64 {
match self {
false => 0,
true => 1,
}
}
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality> {
match *field_type {
FieldType::Bool(ref integer_options) => integer_options.get_fastfield_cardinality(),
_ => None,
}
}
fn as_u64(&self) -> u64 {
*self as u64
}
fn to_type() -> Type {
Type::Bool
}
}
impl FastValue for DateTime {
/// Converts a timestamp microseconds into DateTime.
///
/// **Note the timestamps is expected to be in microseconds.**
fn from_u64(timestamp_micros_u64: u64) -> Self {
let timestamp_micros = i64::from_u64(timestamp_micros_u64);
Self::from_timestamp_micros(timestamp_micros)
impl MonotonicallyMappableToU64 for DateTime {
fn to_u64(self) -> u64 {
self.timestamp_micros.to_u64()
}
fn to_u64(&self) -> u64 {
common::i64_to_u64(self.into_timestamp_micros())
}
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality> {
match *field_type {
FieldType::Date(ref options) => options.get_fastfield_cardinality(),
_ => None,
}
}
fn as_u64(&self) -> u64 {
self.into_timestamp_micros().as_u64()
}
fn to_type() -> Type {
Type::Date
fn from_u64(val: u64) -> Self {
let timestamp_micros = i64::from_u64(val);
DateTime { timestamp_micros }
}
}
fn value_to_u64(value: &Value) -> u64 {
match value {
impl FastValue for DateTime {
fn to_type() -> Type {
Type::Date
}
fn make_zero() -> Self {
DateTime {
timestamp_micros: 0,
}
}
}
fn value_to_u64(value: &Value) -> crate::Result<u64> {
let value = match value {
Value::U64(val) => val.to_u64(),
Value::I64(val) => val.to_u64(),
Value::F64(val) => val.to_u64(),
Value::Bool(val) => val.to_u64(),
Value::Date(val) => val.to_u64(),
_ => panic!("Expected a u64/i64/f64/bool/date field, got {:?} ", value),
}
_ => return Err(unexpected_value("u64/i64/f64/bool/date", value)),
};
Ok(value)
}
/// The fast field type
@@ -266,17 +147,19 @@ mod tests {
use std::collections::HashMap;
use std::ops::Range;
use std::path::Path;
use std::sync::Arc;
use common::HasLen;
use fastfield_codecs::{open, FastFieldCodecType};
use once_cell::sync::Lazy;
use rand::prelude::SliceRandom;
use rand::rngs::StdRng;
use rand::SeedableRng;
use rand::{Rng, SeedableRng};
use super::*;
use crate::directory::{CompositeFile, Directory, RamDirectory, WritePtr};
use crate::merge_policy::NoMergePolicy;
use crate::schema::{Document, Field, Schema, FAST, STRING, TEXT};
use crate::schema::{Cardinality, Document, Field, Schema, SchemaBuilder, FAST, STRING, TEXT};
use crate::time::OffsetDateTime;
use crate::{DateOptions, DatePrecision, Index, SegmentId, SegmentReader};
@@ -285,22 +168,14 @@ mod tests {
schema_builder.add_u64_field("field", FAST);
schema_builder.build()
});
pub static SCHEMAI64: Lazy<Schema> = Lazy::new(|| {
let mut schema_builder = Schema::builder();
schema_builder.add_i64_field("field", FAST);
schema_builder.build()
});
pub static FIELD: Lazy<Field> = Lazy::new(|| SCHEMA.get_field("field").unwrap());
pub static FIELDI64: Lazy<Field> = Lazy::new(|| SCHEMAI64.get_field("field").unwrap());
#[test]
pub fn test_fastfield() {
let test_fastfield = DynamicFastFieldReader::<u64>::from(vec![100, 200, 300]);
assert_eq!(test_fastfield.get(0), 100);
assert_eq!(test_fastfield.get(1), 200);
assert_eq!(test_fastfield.get(2), 300);
let test_fastfield = fastfield_codecs::serialize_and_load(&[100u64, 200u64, 300u64][..]);
assert_eq!(test_fastfield.get_val(0), 100);
assert_eq!(test_fastfield.get_val(1), 200);
assert_eq!(test_fastfield.get_val(2), 300);
}
#[test]
@@ -317,22 +192,28 @@ mod tests {
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&SCHEMA);
fast_field_writers.add_document(&doc!(*FIELD=>13u64));
fast_field_writers.add_document(&doc!(*FIELD=>14u64));
fast_field_writers.add_document(&doc!(*FIELD=>2u64));
fast_field_writers
.add_document(&doc!(*FIELD=>13u64))
.unwrap();
fast_field_writers
.add_document(&doc!(*FIELD=>14u64))
.unwrap();
fast_field_writers
.add_document(&doc!(*FIELD=>2u64))
.unwrap();
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 37);
assert_eq!(file.len(), 25);
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(file)?;
assert_eq!(fast_field_reader.get(0), 13u64);
assert_eq!(fast_field_reader.get(1), 14u64);
assert_eq!(fast_field_reader.get(2), 2u64);
let fast_field_bytes = composite_file.open_read(*FIELD).unwrap().read_bytes()?;
let fast_field_reader = open::<u64>(fast_field_bytes)?.to_full().unwrap();
assert_eq!(fast_field_reader.get_val(0), 13u64);
assert_eq!(fast_field_reader.get_val(1), 14u64);
assert_eq!(fast_field_reader.get_val(2), 2u64);
Ok(())
}
@@ -344,33 +225,54 @@ mod tests {
let write: WritePtr = directory.open_write(Path::new("test"))?;
let mut serializer = CompositeFastFieldSerializer::from_write(write)?;
let mut fast_field_writers = FastFieldsWriter::from_schema(&SCHEMA);
fast_field_writers.add_document(&doc!(*FIELD=>4u64));
fast_field_writers.add_document(&doc!(*FIELD=>14_082_001u64));
fast_field_writers.add_document(&doc!(*FIELD=>3_052u64));
fast_field_writers.add_document(&doc!(*FIELD=>9_002u64));
fast_field_writers.add_document(&doc!(*FIELD=>15_001u64));
fast_field_writers.add_document(&doc!(*FIELD=>777u64));
fast_field_writers.add_document(&doc!(*FIELD=>1_002u64));
fast_field_writers.add_document(&doc!(*FIELD=>1_501u64));
fast_field_writers.add_document(&doc!(*FIELD=>215u64));
fast_field_writers
.add_document(&doc!(*FIELD=>4u64))
.unwrap();
fast_field_writers
.add_document(&doc!(*FIELD=>14_082_001u64))
.unwrap();
fast_field_writers
.add_document(&doc!(*FIELD=>3_052u64))
.unwrap();
fast_field_writers
.add_document(&doc!(*FIELD=>9_002u64))
.unwrap();
fast_field_writers
.add_document(&doc!(*FIELD=>15_001u64))
.unwrap();
fast_field_writers
.add_document(&doc!(*FIELD=>777u64))
.unwrap();
fast_field_writers
.add_document(&doc!(*FIELD=>1_002u64))
.unwrap();
fast_field_writers
.add_document(&doc!(*FIELD=>1_501u64))
.unwrap();
fast_field_writers
.add_document(&doc!(*FIELD=>215u64))
.unwrap();
fast_field_writers.serialize(&mut serializer, &HashMap::new(), None)?;
serializer.close()?;
}
let file = directory.open_read(path)?;
assert_eq!(file.len(), 62);
assert_eq!(file.len(), 53);
{
let fast_fields_composite = CompositeFile::open(&file)?;
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data)?;
assert_eq!(fast_field_reader.get(0), 4u64);
assert_eq!(fast_field_reader.get(1), 14_082_001u64);
assert_eq!(fast_field_reader.get(2), 3_052u64);
assert_eq!(fast_field_reader.get(3), 9002u64);
assert_eq!(fast_field_reader.get(4), 15_001u64);
assert_eq!(fast_field_reader.get(5), 777u64);
assert_eq!(fast_field_reader.get(6), 1_002u64);
assert_eq!(fast_field_reader.get(7), 1_501u64);
assert_eq!(fast_field_reader.get(8), 215u64);
let data = fast_fields_composite
.open_read(*FIELD)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<u64>(data)?.to_full().unwrap();
assert_eq!(fast_field_reader.get_val(0), 4u64);
assert_eq!(fast_field_reader.get_val(1), 14_082_001u64);
assert_eq!(fast_field_reader.get_val(2), 3_052u64);
assert_eq!(fast_field_reader.get_val(3), 9002u64);
assert_eq!(fast_field_reader.get_val(4), 15_001u64);
assert_eq!(fast_field_reader.get_val(5), 777u64);
assert_eq!(fast_field_reader.get_val(6), 1_002u64);
assert_eq!(fast_field_reader.get_val(7), 1_501u64);
assert_eq!(fast_field_reader.get_val(8), 215u64);
}
Ok(())
}
@@ -385,7 +287,9 @@ mod tests {
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&SCHEMA);
for _ in 0..10_000 {
fast_field_writers.add_document(&doc!(*FIELD=>100_000u64));
fast_field_writers
.add_document(&doc!(*FIELD=>100_000u64))
.unwrap();
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
@@ -393,13 +297,16 @@ mod tests {
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 35);
assert_eq!(file.len(), 26);
{
let fast_fields_composite = CompositeFile::open(&file).unwrap();
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data)?;
let data = fast_fields_composite
.open_read(*FIELD)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<u64>(data)?.to_full().unwrap();
for doc in 0..10_000 {
assert_eq!(fast_field_reader.get(doc), 100_000u64);
assert_eq!(fast_field_reader.get_val(doc), 100_000u64);
}
}
Ok(())
@@ -415,9 +322,13 @@ mod tests {
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&SCHEMA);
// forcing the amplitude to be high
fast_field_writers.add_document(&doc!(*FIELD=>0u64));
fast_field_writers
.add_document(&doc!(*FIELD=>0u64))
.unwrap();
for i in 0u64..10_000u64 {
fast_field_writers.add_document(&doc!(*FIELD=>5_000_000_000_000_000_000u64 + i));
fast_field_writers
.add_document(&doc!(*FIELD=>5_000_000_000_000_000_000u64 + i))
.unwrap();
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
@@ -425,15 +336,18 @@ mod tests {
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 80043);
assert_eq!(file.len(), 80040);
{
let fast_fields_composite = CompositeFile::open(&file)?;
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data)?;
assert_eq!(fast_field_reader.get(0), 0u64);
let data = fast_fields_composite
.open_read(*FIELD)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<u64>(data)?.to_full().unwrap();
assert_eq!(fast_field_reader.get_val(0), 0u64);
for doc in 1..10_001 {
assert_eq!(
fast_field_reader.get(doc),
fast_field_reader.get_val(doc),
5_000_000_000_000_000_000u64 + doc as u64 - 1u64
);
}
@@ -456,7 +370,7 @@ mod tests {
for i in -100i64..10_000i64 {
let mut doc = Document::default();
doc.add_i64(i64_field, i);
fast_field_writers.add_document(&doc);
fast_field_writers.add_document(&doc).unwrap();
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
@@ -464,18 +378,20 @@ mod tests {
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
// assert_eq!(file.len(), 17710 as usize); //bitpacked size
// assert_eq!(file.len(), 10175_usize); // linear interpol size
assert_eq!(file.len(), 75_usize); // linear interpol size after calc improvement
assert_eq!(file.len(), 40_usize);
{
let fast_fields_composite = CompositeFile::open(&file)?;
let data = fast_fields_composite.open_read(i64_field).unwrap();
let fast_field_reader = DynamicFastFieldReader::<i64>::open(data)?;
let data = fast_fields_composite
.open_read(i64_field)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<i64>(data)?.to_full().unwrap();
assert_eq!(fast_field_reader.min_value(), -100i64);
assert_eq!(fast_field_reader.max_value(), 9_999i64);
for (doc, i) in (-100i64..10_000i64).enumerate() {
assert_eq!(fast_field_reader.get(doc as u32), i);
assert_eq!(fast_field_reader.get_val(doc as u32), i);
}
let mut buffer = vec![0i64; 100];
fast_field_reader.get_range(53, &mut buffer[..]);
@@ -499,7 +415,7 @@ mod tests {
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
let doc = Document::default();
fast_field_writers.add_document(&doc);
fast_field_writers.add_document(&doc).unwrap();
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
@@ -509,9 +425,12 @@ mod tests {
let file = directory.open_read(path).unwrap();
{
let fast_fields_composite = CompositeFile::open(&file).unwrap();
let data = fast_fields_composite.open_read(i64_field).unwrap();
let fast_field_reader = DynamicFastFieldReader::<i64>::open(data)?;
assert_eq!(fast_field_reader.get(0u32), 0i64);
let data = fast_fields_composite
.open_read(i64_field)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<i64>(data)?.to_full().unwrap();
assert_eq!(fast_field_reader.get_val(0), 0i64);
}
Ok(())
}
@@ -539,7 +458,7 @@ mod tests {
let mut serializer = CompositeFastFieldSerializer::from_write(write)?;
let mut fast_field_writers = FastFieldsWriter::from_schema(&SCHEMA);
for &x in &permutation {
fast_field_writers.add_document(&doc!(*FIELD=>x));
fast_field_writers.add_document(&doc!(*FIELD=>x)).unwrap();
}
fast_field_writers.serialize(&mut serializer, &HashMap::new(), None)?;
serializer.close()?;
@@ -547,11 +466,14 @@ mod tests {
let file = directory.open_read(path)?;
{
let fast_fields_composite = CompositeFile::open(&file)?;
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data)?;
let data = fast_fields_composite
.open_read(*FIELD)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<u64>(data)?.to_full().unwrap();
for a in 0..n {
assert_eq!(fast_field_reader.get(a as u32), permutation[a as usize]);
assert_eq!(fast_field_reader.get_val(a as u32), permutation[a as usize]);
}
}
Ok(())
@@ -607,7 +529,7 @@ mod tests {
let mut all = vec![];
for doc in docs {
let mut out = vec![];
let mut out: Vec<u64> = vec![];
ff.get_vals(doc, &mut out);
all.extend(out);
}
@@ -804,7 +726,6 @@ mod tests {
#[test]
fn test_datefastfield() -> crate::Result<()> {
use crate::fastfield::FastValue;
let mut schema_builder = Schema::builder();
let date_field = schema_builder.add_date_field(
"date",
@@ -842,19 +763,28 @@ mod tests {
let dates_fast_field = fast_fields.dates(multi_date_field).unwrap();
let mut dates = vec![];
{
assert_eq!(date_fast_field.get(0u32).into_timestamp_micros(), 1i64);
assert_eq!(
date_fast_field.get_val(0).unwrap().into_timestamp_micros(),
1i64
);
dates_fast_field.get_vals(0u32, &mut dates);
assert_eq!(dates.len(), 2);
assert_eq!(dates[0].into_timestamp_micros(), 2i64);
assert_eq!(dates[1].into_timestamp_micros(), 3i64);
}
{
assert_eq!(date_fast_field.get(1u32).into_timestamp_micros(), 4i64);
assert_eq!(
date_fast_field.get_val(1).unwrap().into_timestamp_micros(),
4i64
);
dates_fast_field.get_vals(1u32, &mut dates);
assert!(dates.is_empty());
}
{
assert_eq!(date_fast_field.get(2u32).into_timestamp_micros(), 0i64);
assert_eq!(
date_fast_field.get_val(2).unwrap().into_timestamp_micros(),
0i64
);
dates_fast_field.get_vals(2u32, &mut dates);
assert_eq!(dates.len(), 2);
assert_eq!(dates[0].into_timestamp_micros(), 5i64);
@@ -865,11 +795,12 @@ mod tests {
#[test]
pub fn test_fastfield_bool() {
let test_fastfield = DynamicFastFieldReader::<bool>::from(vec![true, false, true, false]);
assert_eq!(test_fastfield.get(0), true);
assert_eq!(test_fastfield.get(1), false);
assert_eq!(test_fastfield.get(2), true);
assert_eq!(test_fastfield.get(3), false);
let test_fastfield: Arc<dyn Column<bool>> =
fastfield_codecs::serialize_and_load::<bool>(&[true, false, true, false]);
assert_eq!(test_fastfield.get_val(0), true);
assert_eq!(test_fastfield.get_val(1), false);
assert_eq!(test_fastfield.get_val(2), true);
assert_eq!(test_fastfield.get_val(3), false);
}
#[test]
@@ -886,24 +817,28 @@ mod tests {
let write: WritePtr = directory.open_write(path).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
fast_field_writers.add_document(&doc!(field=>true));
fast_field_writers.add_document(&doc!(field=>false));
fast_field_writers.add_document(&doc!(field=>true));
fast_field_writers.add_document(&doc!(field=>false));
fast_field_writers.add_document(&doc!(field=>true)).unwrap();
fast_field_writers
.add_document(&doc!(field=>false))
.unwrap();
fast_field_writers.add_document(&doc!(field=>true)).unwrap();
fast_field_writers
.add_document(&doc!(field=>false))
.unwrap();
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 36);
assert_eq!(file.len(), 24);
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(field).unwrap();
let fast_field_reader = DynamicFastFieldReader::<bool>::open(file)?;
assert_eq!(fast_field_reader.get(0), true);
assert_eq!(fast_field_reader.get(1), false);
assert_eq!(fast_field_reader.get(2), true);
assert_eq!(fast_field_reader.get(3), false);
let data = composite_file.open_read(field).unwrap().read_bytes()?;
let fast_field_reader = open::<bool>(data)?.to_full().unwrap();
assert_eq!(fast_field_reader.get_val(0), true);
assert_eq!(fast_field_reader.get_val(1), false);
assert_eq!(fast_field_reader.get_val(2), true);
assert_eq!(fast_field_reader.get_val(3), false);
Ok(())
}
@@ -923,8 +858,10 @@ mod tests {
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
for _ in 0..50 {
fast_field_writers.add_document(&doc!(field=>true));
fast_field_writers.add_document(&doc!(field=>false));
fast_field_writers.add_document(&doc!(field=>true)).unwrap();
fast_field_writers
.add_document(&doc!(field=>false))
.unwrap();
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
@@ -932,13 +869,13 @@ mod tests {
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 48);
assert_eq!(file.len(), 36);
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(field).unwrap();
let fast_field_reader = DynamicFastFieldReader::<bool>::open(file)?;
let data = composite_file.open_read(field).unwrap().read_bytes()?;
let fast_field_reader = open::<bool>(data)?.to_full().unwrap();
for i in 0..25 {
assert_eq!(fast_field_reader.get(i * 2), true);
assert_eq!(fast_field_reader.get(i * 2 + 1), false);
assert_eq!(fast_field_reader.get_val(i * 2), true);
assert_eq!(fast_field_reader.get_val(i * 2 + 1), false);
}
Ok(())
@@ -950,168 +887,97 @@ mod tests {
let directory: RamDirectory = RamDirectory::create();
let mut schema_builder = Schema::builder();
schema_builder.add_bool_field("field_bool", FAST);
let field = schema_builder.add_bool_field("field_bool", FAST);
let schema = schema_builder.build();
let field = schema.get_field("field_bool").unwrap();
{
let write: WritePtr = directory.open_write(path).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write)?;
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
let doc = Document::default();
fast_field_writers.add_document(&doc);
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
fast_field_writers.add_document(&doc).unwrap();
fast_field_writers.serialize(&mut serializer, &HashMap::new(), None)?;
serializer.close()?;
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 35);
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(field).unwrap();
let fast_field_reader = DynamicFastFieldReader::<bool>::open(file)?;
assert_eq!(fast_field_reader.get(0), false);
assert_eq!(file.len(), 23);
let data = composite_file.open_read(field).unwrap().read_bytes()?;
let fast_field_reader = open::<bool>(data)?.to_full().unwrap();
assert_eq!(fast_field_reader.get_val(0), false);
Ok(())
}
}
#[cfg(all(test, feature = "unstable"))]
mod bench {
use std::collections::HashMap;
use std::path::Path;
use test::{self, Bencher};
use super::tests::{generate_permutation, FIELD, SCHEMA};
use super::*;
use crate::directory::{CompositeFile, Directory, RamDirectory, WritePtr};
use crate::fastfield::tests::generate_permutation_gcd;
use crate::fastfield::FastFieldReader;
#[bench]
fn bench_intfastfield_linear_veclookup(b: &mut Bencher) {
let permutation = generate_permutation();
b.iter(|| {
let n = test::black_box(7000u32);
let mut a = 0u64;
for i in (0u32..n / 7).map(|v| v * 7) {
a ^= permutation[i as usize];
}
a
});
}
#[bench]
fn bench_intfastfield_veclookup(b: &mut Bencher) {
let permutation = generate_permutation();
b.iter(|| {
let n = test::black_box(1000u32);
let mut a = 0u64;
for _ in 0u32..n {
a = permutation[a as usize];
}
a
});
}
#[bench]
fn bench_intfastfield_linear_fflookup(b: &mut Bencher) {
let path = Path::new("test");
let permutation = generate_permutation();
fn get_index(
docs: &[crate::Document],
schema: &Schema,
codec_types: &[FastFieldCodecType],
) -> crate::Result<RamDirectory> {
let directory: RamDirectory = RamDirectory::create();
{
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&SCHEMA);
for &x in &permutation {
fast_field_writers.add_document(&doc!(*FIELD=>x));
let mut serializer =
CompositeFastFieldSerializer::from_write_with_codec(write, codec_types).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(schema);
for doc in docs {
fast_field_writers.add_document(doc).unwrap();
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
}
let file = directory.open_read(&path).unwrap();
{
let fast_fields_composite = CompositeFile::open(&file).unwrap();
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data).unwrap();
b.iter(|| {
let n = test::black_box(7000u32);
let mut a = 0u64;
for i in (0u32..n / 7).map(|val| val * 7) {
a ^= fast_field_reader.get(i);
}
a
});
}
Ok(directory)
}
#[bench]
fn bench_intfastfield_fflookup(b: &mut Bencher) {
let path = Path::new("test");
let permutation = generate_permutation();
let directory: RamDirectory = RamDirectory::create();
{
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&SCHEMA);
for &x in &permutation {
fast_field_writers.add_document(&doc!(*FIELD=>x));
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
}
let file = directory.open_read(&path).unwrap();
{
let fast_fields_composite = CompositeFile::open(&file).unwrap();
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data).unwrap();
b.iter(|| {
let mut a = 0u32;
for i in 0u32..permutation.len() as u32 {
a = fast_field_reader.get(i) as u32;
}
a
});
}
#[test]
pub fn test_gcd_date() -> crate::Result<()> {
let size_prec_sec =
test_gcd_date_with_codec(FastFieldCodecType::Bitpacked, DatePrecision::Seconds)?;
assert_eq!(size_prec_sec, 28 + (1_000 * 13) / 8); // 13 bits per val = ceil(log_2(number of seconds in 2hours);
let size_prec_micro =
test_gcd_date_with_codec(FastFieldCodecType::Bitpacked, DatePrecision::Microseconds)?;
assert_eq!(size_prec_micro, 26 + (1_000 * 33) / 8); // 33 bits per val = ceil(log_2(number of microsecsseconds in 2hours);
Ok(())
}
#[bench]
fn bench_intfastfield_fflookup_gcd(b: &mut Bencher) {
let path = Path::new("test");
let permutation = generate_permutation_gcd();
let directory: RamDirectory = RamDirectory::create();
{
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&SCHEMA);
for &x in &permutation {
fast_field_writers.add_document(&doc!(*FIELD=>x));
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
}
let file = directory.open_read(&path).unwrap();
{
let fast_fields_composite = CompositeFile::open(&file).unwrap();
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data).unwrap();
fn test_gcd_date_with_codec(
codec_type: FastFieldCodecType,
precision: DatePrecision,
) -> crate::Result<usize> {
let mut rng = StdRng::seed_from_u64(2u64);
const T0: i64 = 1_662_345_825_012_529i64;
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.gen_range(-ONE_HOUR_IN_MICROSECS..ONE_HOUR_IN_MICROSECS);
DateTime::from_timestamp_micros(t)
})
.take(1_000)
.collect();
let date_options = DateOptions::default()
.set_fast(Cardinality::SingleValue)
.set_precision(precision);
let mut schema_builder = SchemaBuilder::default();
let field = schema_builder.add_date_field("field", date_options);
let schema = schema_builder.build();
b.iter(|| {
let mut a = 0u32;
for i in 0u32..permutation.len() as u32 {
a = fast_field_reader.get(i) as u32;
}
a
});
let docs: Vec<Document> = times.iter().map(|time| doc!(field=>*time)).collect();
let directory = get_index(&docs[..], &schema, &[codec_type])?;
let path = Path::new("test");
let file = directory.open_read(path).unwrap();
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(*FIELD).unwrap();
let len = file.len();
let test_fastfield = open::<DateTime>(file.read_bytes()?)?
.to_full()
.expect("temp migration solution");
for (i, time) in times.iter().enumerate() {
assert_eq!(test_fastfield.get_val(i as u32), time.truncate(precision));
}
Ok(len)
}
}

148
src/fastfield/multivalued/index.rs Normal file
View File

@@ -0,0 +1,148 @@
use std::ops::Range;
use std::sync::Arc;
use fastfield_codecs::Column;
use crate::DocId;
#[derive(Clone)]
/// Index to resolve value range for given doc_id.
/// Starts at 0.
pub struct MultiValueIndex {
idx: Arc<dyn Column<u64>>,
}
impl MultiValueIndex {
pub(crate) fn new(idx: Arc<dyn Column<u64>>) -> Self {
Self { idx }
}
/// Returns `[start, end)`, such that the values associated with
/// the given document are `start..end`.
#[inline]
pub(crate) fn range(&self, doc: DocId) -> Range<u32> {
let start = self.idx.get_val(doc) as u32;
let end = self.idx.get_val(doc + 1) as u32;
start..end
}
/// Given a range of documents, returns the Range of value offsets fo
/// these documents.
///
/// For instance, `given start_doc..end_doc`,
/// if we assume Document #start_doc end #end_doc both
/// have values, this function returns `start..end`
/// such that `value_column.get(start_doc)` is the first value of
/// `start_doc` (well, if there is one), and `value_column.get(end_doc - 1)`
/// is the last value of `end_doc`.
///
/// The passed end range is allowed to be out of bounds, in which case
/// it will be clipped to make it valid.
#[inline]
pub(crate) fn docid_range_to_position_range(&self, range: Range<DocId>) -> Range<u32> {
let end_docid = range.end.min(self.num_docs() - 1) + 1;
let start_docid = range.start.min(end_docid);
let start = self.idx.get_val(start_docid) as u32;
let end = self.idx.get_val(end_docid) as u32;
assert!(start <= end);
start..end
}
/// returns the num of values associated with a doc_id
pub(crate) fn num_vals_for_doc(&self, doc: DocId) -> u32 {
let range = self.range(doc);
range.end - range.start
}
/// Returns the overall number of values in this field.
#[inline]
pub fn total_num_vals(&self) -> u32 {
self.idx.max_value() as u32
}
/// Returns the number of documents in the index.
#[inline]
pub fn num_docs(&self) -> u32 {
self.idx.num_vals() - 1
}
/// Converts a list of positions of values in a 1:n index to the corresponding list of DocIds.
/// Positions are converted inplace to docids.
///
/// Since there is no index for value pos -> docid, but docid -> value pos range, we scan the
/// index.
///
/// Correctness: positions needs to be sorted. idx_reader needs to contain monotonically
/// increasing positions.
///
///
/// TODO: Instead of a linear scan we can employ a exponential search into binary search to
/// match a docid to its value position.
pub(crate) fn positions_to_docids(&self, doc_id_range: Range<u32>, positions: &mut Vec<u32>) {
if positions.is_empty() {
return;
}
let mut cur_doc = doc_id_range.start;
let mut last_doc = None;
assert!(self.idx.get_val(doc_id_range.start) as u32 <= positions[0]);
let mut write_doc_pos = 0;
for i in 0..positions.len() {
let pos = positions[i];
loop {
let end = self.idx.get_val(cur_doc + 1) as u32;
if end > pos {
positions[write_doc_pos] = cur_doc;
write_doc_pos += if last_doc == Some(cur_doc) { 0 } else { 1 };
last_doc = Some(cur_doc);
break;
}
cur_doc += 1;
}
}
positions.truncate(write_doc_pos);
}
}
#[cfg(test)]
mod tests {
use std::ops::Range;
use std::sync::Arc;
use fastfield_codecs::IterColumn;
use crate::fastfield::MultiValueIndex;
fn index_to_pos_helper(
index: &MultiValueIndex,
doc_id_range: Range<u32>,
positions: &[u32],
) -> Vec<u32> {
let mut positions = positions.to_vec();
index.positions_to_docids(doc_id_range, &mut positions);
positions
}
#[test]
fn test_positions_to_docid() {
let offsets = vec![0, 10, 12, 15, 22, 23]; // docid values are [0..10, 10..12, 12..15, etc.]
let column = IterColumn::from(offsets.into_iter());
let index = MultiValueIndex::new(Arc::new(column));
assert_eq!(index.num_docs(), 5);
{
let positions = vec![10u32, 11, 15, 20, 21, 22];
assert_eq!(index_to_pos_helper(&index, 0..5, &positions), vec![1, 3, 4]);
assert_eq!(index_to_pos_helper(&index, 1..5, &positions), vec![1, 3, 4]);
assert_eq!(index_to_pos_helper(&index, 0..5, &[9]), vec![0]);
assert_eq!(index_to_pos_helper(&index, 1..5, &[10]), vec![1]);
assert_eq!(index_to_pos_helper(&index, 1..5, &[11]), vec![1]);
assert_eq!(index_to_pos_helper(&index, 2..5, &[12]), vec![2]);
assert_eq!(index_to_pos_helper(&index, 2..5, &[12, 14]), vec![2]);
assert_eq!(index_to_pos_helper(&index, 2..5, &[12, 14, 15]), vec![2, 3]);
}
}
}

240
src/fastfield/multivalued/mod.rs
View File

@@ -1,8 +1,23 @@
mod index;
mod reader;
mod writer;
pub use self::reader::MultiValuedFastFieldReader;
pub use self::writer::MultiValuedFastFieldWriter;
use fastfield_codecs::FastFieldCodecType;
pub use index::MultiValueIndex;
pub use self::reader::{MultiValuedFastFieldReader, MultiValuedU128FastFieldReader};
pub(crate) use self::writer::MultivalueStartIndex;
pub use self::writer::{MultiValueU128FastFieldWriter, MultiValuedFastFieldWriter};
/// The valid codecs for multivalue values excludes the linear interpolation codec.
///
/// This limitation is only valid for the values, not the offset index of the multivalue index.
pub(crate) fn get_fastfield_codecs_for_multivalue() -> [FastFieldCodecType; 2] {
[
FastFieldCodecType::Bitpacked,
FastFieldCodecType::BlockwiseLinear,
]
}
#[cfg(test)]
mod tests {
@@ -341,11 +356,13 @@ mod tests {
}
proptest! {
#![proptest_config(proptest::prelude::ProptestConfig::with_cases(5))]
#[test]
fn test_multivalued_proptest(ops in proptest::collection::vec(operation_strategy(), 1..10)) {
assert!(test_multivalued_no_panic(&ops[..]).is_ok());
}
}
#[test]
fn test_multivalued_proptest_gcd() {
use IndexingOp::*;
@@ -384,3 +401,222 @@ mod tests {
Ok(())
}
}
#[cfg(all(test, feature = "unstable"))]
mod bench {
use std::collections::HashMap;
use std::path::Path;
use test::{self, Bencher};
use super::*;
use crate::directory::{CompositeFile, Directory, RamDirectory, WritePtr};
use crate::fastfield::{CompositeFastFieldSerializer, FastFieldsWriter};
use crate::indexer::doc_id_mapping::DocIdMapping;
use crate::schema::{Cardinality, NumericOptions, Schema};
use crate::Document;
fn bench_multi_value_ff_merge_opt(
num_docs: usize,
segments_every_n_docs: usize,
merge_policy: impl crate::indexer::MergePolicy + 'static,
) {
let mut builder = crate::schema::SchemaBuilder::new();
let fast_multi =
crate::schema::NumericOptions::default().set_fast(Cardinality::MultiValues);
let multi_field = builder.add_f64_field("f64s", fast_multi);
let index = crate::Index::create_in_ram(builder.build());
let mut writer = index.writer_for_tests().unwrap();
writer.set_merge_policy(Box::new(merge_policy));
for i in 0..num_docs {
let mut doc = crate::Document::new();
doc.add_f64(multi_field, 0.24);
doc.add_f64(multi_field, 0.27);
doc.add_f64(multi_field, 0.37);
if i % 3 == 0 {
doc.add_f64(multi_field, 0.44);
}
writer.add_document(doc).unwrap();
if i % segments_every_n_docs == 0 {
writer.commit().unwrap();
}
}
{
writer.wait_merging_threads().unwrap();
let mut writer = index.writer_for_tests().unwrap();
let segment_ids = index.searchable_segment_ids().unwrap();
writer.merge(&segment_ids).wait().unwrap();
}
// If a merging thread fails, we should end up with more
// than one segment here
assert_eq!(1, index.searchable_segments().unwrap().len());
}
#[bench]
fn bench_multi_value_ff_merge_many_segments(b: &mut Bencher) {
let num_docs = 100_000;
b.iter(|| {
bench_multi_value_ff_merge_opt(num_docs, 1_000, crate::indexer::NoMergePolicy);
});
}
#[bench]
fn bench_multi_value_ff_merge_many_segments_log_merge(b: &mut Bencher) {
let num_docs = 100_000;
b.iter(|| {
let merge_policy = crate::indexer::LogMergePolicy::default();
bench_multi_value_ff_merge_opt(num_docs, 1_000, merge_policy);
});
}
#[bench]
fn bench_multi_value_ff_merge_few_segments(b: &mut Bencher) {
let num_docs = 100_000;
b.iter(|| {
bench_multi_value_ff_merge_opt(num_docs, 33_000, crate::indexer::NoMergePolicy);
});
}
fn multi_values(num_docs: usize, vals_per_doc: usize) -> Vec<Vec<u64>> {
let mut vals = vec![];
for _i in 0..num_docs {
let mut block = vec![];
for j in 0..vals_per_doc {
block.push(j as u64);
}
vals.push(block);
}
vals
}
#[bench]
fn bench_multi_value_fflookup(b: &mut Bencher) {
let num_docs = 100_000;
let path = Path::new("test");
let directory: RamDirectory = RamDirectory::create();
let field = {
let options = NumericOptions::default().set_fast(Cardinality::MultiValues);
let mut schema_builder = Schema::builder();
let field = schema_builder.add_u64_field("field", options);
let schema = schema_builder.build();
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
for block in &multi_values(num_docs, 3) {
let mut doc = Document::new();
for val in block {
doc.add_u64(field, *val);
}
fast_field_writers.add_document(&doc).unwrap();
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
field
};
let file = directory.open_read(&path).unwrap();
{
let fast_fields_composite = CompositeFile::open(&file).unwrap();
let data_idx = fast_fields_composite
.open_read_with_idx(field, 0)
.unwrap()
.read_bytes()
.unwrap();
let idx_reader = fastfield_codecs::open(data_idx).unwrap().to_full().unwrap();
let data_vals = fast_fields_composite
.open_read_with_idx(field, 1)
.unwrap()
.read_bytes()
.unwrap();
let vals_reader = fastfield_codecs::open(data_vals)
.unwrap()
.to_full()
.unwrap();
let fast_field_reader = MultiValuedFastFieldReader::open(idx_reader, vals_reader);
b.iter(|| {
let mut sum = 0u64;
let mut data = Vec::with_capacity(10);
for i in 0u32..num_docs as u32 {
fast_field_reader.get_vals(i, &mut data);
sum += data.iter().sum::<u64>();
}
sum
});
}
}
#[bench]
fn bench_multi_value_ff_creation(b: &mut Bencher) {
// 3 million ff entries
let num_docs = 1_000_000;
let multi_values = multi_values(num_docs, 3);
b.iter(|| {
let directory: RamDirectory = RamDirectory::create();
let options = NumericOptions::default().set_fast(Cardinality::MultiValues);
let mut schema_builder = Schema::builder();
let field = schema_builder.add_u64_field("field", options);
let schema = schema_builder.build();
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
for block in &multi_values {
let mut doc = Document::new();
for val in block {
doc.add_u64(field, *val);
}
fast_field_writers.add_document(&doc).unwrap();
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
});
}
#[bench]
fn bench_multi_value_ff_creation_with_sorting(b: &mut Bencher) {
// 3 million ff entries
let num_docs = 1_000_000;
let multi_values = multi_values(num_docs, 3);
let doc_id_mapping =
DocIdMapping::from_new_id_to_old_id((0..1_000_000).collect::<Vec<_>>());
b.iter(|| {
let directory: RamDirectory = RamDirectory::create();
let options = NumericOptions::default().set_fast(Cardinality::MultiValues);
let mut schema_builder = Schema::builder();
let field = schema_builder.add_u64_field("field", options);
let schema = schema_builder.build();
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
for block in &multi_values {
let mut doc = Document::new();
for val in block {
doc.add_u64(field, *val);
}
fast_field_writers.add_document(&doc).unwrap();
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), Some(&doc_id_mapping))
.unwrap();
serializer.close().unwrap();
});
}
}

168
src/fastfield/multivalued/reader.rs
View File

@@ -1,6 +1,10 @@
use std::ops::Range;
use std::ops::{Range, RangeInclusive};
use std::sync::Arc;
use crate::fastfield::{DynamicFastFieldReader, FastFieldReader, FastValue, MultiValueLength};
use fastfield_codecs::{Column, MonotonicallyMappableToU128};
use super::MultiValueIndex;
use crate::fastfield::FastValue;
use crate::DocId;
/// Reader for a multivalued `u64` fast field.
@@ -10,47 +14,45 @@ use crate::DocId;
/// The `vals_reader` will access the concatenated list of all
/// values for all reader.
/// The `idx_reader` associated, for each document, the index of its first value.
/// Stores the start position for each document.
#[derive(Clone)]
pub struct MultiValuedFastFieldReader<Item: FastValue> {
idx_reader: DynamicFastFieldReader<u64>,
vals_reader: DynamicFastFieldReader<Item>,
idx_reader: MultiValueIndex,
vals_reader: Arc<dyn Column<Item>>,
}
impl<Item: FastValue> MultiValuedFastFieldReader<Item> {
pub(crate) fn open(
idx_reader: DynamicFastFieldReader<u64>,
vals_reader: DynamicFastFieldReader<Item>,
idx_reader: Arc<dyn Column<u64>>,
vals_reader: Arc<dyn Column<Item>>,
) -> MultiValuedFastFieldReader<Item> {
MultiValuedFastFieldReader {
idx_reader,
idx_reader: MultiValueIndex::new(idx_reader),
vals_reader,
}
}
/// Returns `[start, end)`, such that the values associated
/// to the given document are `start..end`.
/// Returns the array of values associated with the given `doc`.
#[inline]
fn range(&self, doc: DocId) -> Range<u64> {
let start = self.idx_reader.get(doc);
let end = self.idx_reader.get(doc + 1);
start..end
}
/// Returns the array of values associated to the given `doc`.
#[inline]
fn get_vals_for_range(&self, range: Range<u64>, vals: &mut Vec<Item>) {
fn get_vals_for_range(&self, range: Range<u32>, vals: &mut Vec<Item>) {
let len = (range.end - range.start) as usize;
vals.resize(len, Item::make_zero());
self.vals_reader.get_range(range.start, &mut vals[..]);
self.vals_reader
.get_range(range.start as u64, &mut vals[..]);
}
/// Returns the array of values associated to the given `doc`.
/// Returns the array of values associated with the given `doc`.
#[inline]
pub fn get_vals(&self, doc: DocId, vals: &mut Vec<Item>) {
let range = self.range(doc);
let range = self.idx_reader.range(doc);
self.get_vals_for_range(range, vals);
}
/// returns the multivalue index
pub fn get_index_reader(&self) -> &MultiValueIndex {
&self.idx_reader
}
/// Returns the minimum value for this fast field.
///
/// The min value does not take in account of possible
@@ -71,27 +73,129 @@ impl<Item: FastValue> MultiValuedFastFieldReader<Item> {
/// Returns the number of values associated with the document `DocId`.
#[inline]
pub fn num_vals(&self, doc: DocId) -> usize {
let range = self.range(doc);
(range.end - range.start) as usize
pub fn num_vals(&self, doc: DocId) -> u32 {
self.idx_reader.num_vals_for_doc(doc)
}
/// Returns the overall number of values in this field .
/// Returns the overall number of values in this field.
#[inline]
pub fn total_num_vals(&self) -> u64 {
self.idx_reader.max_value()
pub fn total_num_vals(&self) -> u32 {
self.idx_reader.total_num_vals()
}
}
impl<Item: FastValue> MultiValueLength for MultiValuedFastFieldReader<Item> {
fn get_len(&self, doc_id: DocId) -> u64 {
self.num_vals(doc_id) as u64
/// Reader for a multivalued `u128` fast field.
///
/// The reader is implemented as a `u64` fast field for the index and a `u128` fast field.
///
/// The `vals_reader` will access the concatenated list of all
/// values for all reader.
/// The `idx_reader` associated, for each document, the index of its first value.
#[derive(Clone)]
pub struct MultiValuedU128FastFieldReader<T: MonotonicallyMappableToU128> {
idx_reader: MultiValueIndex,
vals_reader: Arc<dyn Column<T>>,
}
impl<T: MonotonicallyMappableToU128> MultiValuedU128FastFieldReader<T> {
pub(crate) fn open(
idx_reader: Arc<dyn Column<u64>>,
vals_reader: Arc<dyn Column<T>>,
) -> MultiValuedU128FastFieldReader<T> {
Self {
idx_reader: MultiValueIndex::new(idx_reader),
vals_reader,
}
}
fn get_total_len(&self) -> u64 {
self.total_num_vals() as u64
/// Returns the array of values associated to the given `doc`.
#[inline]
pub fn get_first_val(&self, doc: DocId) -> Option<T> {
let range = self.idx_reader.range(doc);
if range.is_empty() {
return None;
}
Some(self.vals_reader.get_val(range.start))
}
/// Returns the array of values associated to the given `doc`.
#[inline]
fn get_vals_for_range(&self, range: Range<u32>, vals: &mut Vec<T>) {
let len = (range.end - range.start) as usize;
vals.resize(len, T::from_u128(0));
self.vals_reader
.get_range(range.start as u64, &mut vals[..]);
}
/// Returns the index reader
pub fn get_index_reader(&self) -> &MultiValueIndex {
&self.idx_reader
}
/// Returns the array of values associated to the given `doc`.
#[inline]
pub fn get_vals(&self, doc: DocId, vals: &mut Vec<T>) {
let range = self.idx_reader.range(doc);
self.get_vals_for_range(range, vals);
}
/// Iterates over all elements in the fast field
pub fn iter(&self) -> impl Iterator<Item = T> + '_ {
self.vals_reader.iter()
}
/// Returns the minimum value for this fast field.
///
/// The min value does not take in account of possible
/// deleted document, and should be considered as a lower bound
/// of the actual mimimum value.
pub fn min_value(&self) -> T {
self.vals_reader.min_value()
}
/// Returns the maximum value for this fast field.
///
/// The max value does not take in account of possible
/// deleted document, and should be considered as an upper bound
/// of the actual maximum value.
pub fn max_value(&self) -> T {
self.vals_reader.max_value()
}
/// Returns the number of values associated with the document `DocId`.
#[inline]
pub fn num_vals(&self, doc: DocId) -> u32 {
self.idx_reader.num_vals_for_doc(doc)
}
/// Returns the overall number of values in this field. It does not include deletes.
#[inline]
pub fn total_num_vals(&self) -> u32 {
assert_eq!(
self.vals_reader.num_vals(),
self.get_index_reader().total_num_vals()
);
self.idx_reader.total_num_vals()
}
/// Returns the docids matching given doc_id_range and value_range.
#[inline]
pub fn get_docids_for_value_range(
&self,
value_range: RangeInclusive<T>,
doc_id_range: Range<u32>,
positions: &mut Vec<u32>,
) {
let position_range = self
.get_index_reader()
.docid_range_to_position_range(doc_id_range.clone());
self.vals_reader
.get_docids_for_value_range(value_range, position_range, positions);
self.idx_reader.positions_to_docids(doc_id_range, positions);
}
}
#[cfg(test)]
mod tests {

336
src/fastfield/multivalued/writer.rs
View File

@@ -1,10 +1,13 @@
use std::io;
use fnv::FnvHashMap;
use tantivy_bitpacker::minmax;
use fastfield_codecs::{
Column, MonotonicallyMappableToU128, MonotonicallyMappableToU64, VecColumn,
};
use rustc_hash::FxHashMap;
use crate::fastfield::serializer::BitpackedSerializerLegacy;
use crate::fastfield::{value_to_u64, CompositeFastFieldSerializer, FastFieldType, FastValue};
use super::get_fastfield_codecs_for_multivalue;
use crate::fastfield::writer::unexpected_value;
use crate::fastfield::{value_to_u64, CompositeFastFieldSerializer, FastFieldType};
use crate::indexer::doc_id_mapping::DocIdMapping;
use crate::postings::UnorderedTermId;
use crate::schema::{Document, Field, Value};
@@ -17,17 +20,15 @@ use crate::{DatePrecision, DocId};
/// This `Writer` is only useful for advanced users.
/// The normal way to get your multivalued int in your index
/// is to
/// - declare your field with fast set to `Cardinality::MultiValues`
/// in your schema
/// - declare your field with fast set to
/// [`Cardinality::MultiValues`](crate::schema::Cardinality::MultiValues) in your schema
/// - add your document simply by calling `.add_document(...)`.
///
/// The `MultiValuedFastFieldWriter` can be acquired from the
/// fastfield writer, by calling
/// [`.get_multivalue_writer_mut(...)`](./struct.FastFieldsWriter.html#method.
/// get_multivalue_writer_mut).
/// The `MultiValuedFastFieldWriter` can be acquired from the fastfield writer, by calling
/// [`FastFieldWriter::get_multivalue_writer_mut()`](crate::fastfield::FastFieldsWriter::get_multivalue_writer_mut).
///
/// Once acquired, writing is done by calling
/// [`.add_document_vals(&[u64])`](MultiValuedFastFieldWriter::add_document_vals) once per document.
/// [`.add_document(&Document)`](MultiValuedFastFieldWriter::add_document) once per value.
///
/// The serializer makes it possible to remap all of the values
/// that were pushed to the writer using a mapping.
@@ -64,7 +65,7 @@ impl MultiValuedFastFieldWriter {
+ self.doc_index.capacity() * std::mem::size_of::<u64>()
}
/// Access the field associated to the `MultiValuedFastFieldWriter`
/// Access the field associated with the `MultiValuedFastFieldWriter`
pub fn field(&self) -> Field {
self.field
}
@@ -81,11 +82,11 @@ impl MultiValuedFastFieldWriter {
/// Shift to the next document and adds
/// all of the matching field values present in the document.
pub fn add_document(&mut self, doc: &Document) {
pub fn add_document(&mut self, doc: &Document) -> crate::Result<()> {
self.next_doc();
// facets/texts are indexed in the `SegmentWriter` as we encode their unordered id.
if self.fast_field_type.is_storing_term_ids() {
return;
return Ok(());
}
for field_value in doc.field_values() {
if field_value.field == self.field {
@@ -94,23 +95,14 @@ impl MultiValuedFastFieldWriter {
(Some(precision), Value::Date(date_val)) => {
date_val.truncate(precision).to_u64()
}
_ => value_to_u64(value),
_ => value_to_u64(value)?,
};
self.add_val(value_u64);
}
}
Ok(())
}
/// Register all of the values associated to a document.
///
/// The method returns the `DocId` of the document that was
/// just written.
pub fn add_document_vals(&mut self, vals: &[UnorderedTermId]) -> DocId {
let doc = self.doc_index.len() as DocId;
self.next_doc();
self.vals.extend_from_slice(vals);
doc
}
/// Returns an iterator over values per doc_id in ascending doc_id order.
///
/// Normally the order is simply iterating self.doc_id_index.
@@ -150,73 +142,301 @@ impl MultiValuedFastFieldWriter {
/// `tantivy` builds a mapping to convert this `UnorderedTermId` into
/// term ordinals.
pub fn serialize(
&self,
mut self,
serializer: &mut CompositeFastFieldSerializer,
mapping_opt: Option<&FnvHashMap<UnorderedTermId, TermOrdinal>>,
term_mapping_opt: Option<&FxHashMap<UnorderedTermId, TermOrdinal>>,
doc_id_map: Option<&DocIdMapping>,
) -> io::Result<()> {
{
// writing the offset index
let mut doc_index_serializer =
serializer.new_u64_fast_field_with_idx(self.field, 0, self.vals.len() as u64, 0)?;
let mut offset = 0;
for vals in self.get_ordered_values(doc_id_map) {
doc_index_serializer.add_val(offset)?;
offset += vals.len() as u64;
self.doc_index.push(self.vals.len() as u64);
let col = VecColumn::from(&self.doc_index[..]);
if let Some(doc_id_map) = doc_id_map {
let multi_value_start_index = MultivalueStartIndex::new(&col, doc_id_map);
serializer.create_auto_detect_u64_fast_field_with_idx(
self.field,
multi_value_start_index,
0,
)?;
} else {
serializer.create_auto_detect_u64_fast_field_with_idx(self.field, col, 0)?;
}
doc_index_serializer.add_val(self.vals.len() as u64)?;
doc_index_serializer.close_field()?;
}
{
// writing the values themselves.
let mut value_serializer: BitpackedSerializerLegacy<'_, _>;
if let Some(mapping) = mapping_opt {
value_serializer = serializer.new_u64_fast_field_with_idx(
self.field,
0u64,
mapping.len() as u64,
1,
)?;
// Writing the values themselves.
// TODO FIXME: Use less memory.
let mut values: Vec<u64> = Vec::new();
if let Some(term_mapping) = term_mapping_opt {
if self.fast_field_type.is_facet() {
let mut doc_vals: Vec<u64> = Vec::with_capacity(100);
for vals in self.get_ordered_values(doc_id_map) {
// In the case of facets, we want a vec of facet ord that is sorted.
doc_vals.clear();
let remapped_vals = vals
.iter()
.map(|val| *mapping.get(val).expect("Missing term ordinal"));
.map(|val| *term_mapping.get(val).expect("Missing term ordinal"));
doc_vals.extend(remapped_vals);
doc_vals.sort_unstable();
for &val in &doc_vals {
value_serializer.add_val(val)?;
values.push(val);
}
}
} else {
for vals in self.get_ordered_values(doc_id_map) {
let remapped_vals = vals
.iter()
.map(|val| *mapping.get(val).expect("Missing term ordinal"));
.map(|val| *term_mapping.get(val).expect("Missing term ordinal"));
for val in remapped_vals {
value_serializer.add_val(val)?;
values.push(val);
}
}
}
} else {
let val_min_max = minmax(self.vals.iter().cloned());
let (val_min, val_max) = val_min_max.unwrap_or((0u64, 0u64));
value_serializer =
serializer.new_u64_fast_field_with_idx(self.field, val_min, val_max, 1)?;
for vals in self.get_ordered_values(doc_id_map) {
// sort values in case of remapped doc_ids?
for &val in vals {
value_serializer.add_val(val)?;
values.push(val);
}
}
}
value_serializer.close_field()?;
let col = VecColumn::from(&values[..]);
serializer.create_auto_detect_u64_fast_field_with_idx_and_codecs(
self.field,
col,
1,
&get_fastfield_codecs_for_multivalue(),
)?;
}
Ok(())
}
}
pub(crate) struct MultivalueStartIndex<'a, C: Column> {
column: &'a C,
doc_id_map: &'a DocIdMapping,
min: u64,
max: u64,
}
impl<'a, C: Column> MultivalueStartIndex<'a, C> {
pub fn new(column: &'a C, doc_id_map: &'a DocIdMapping) -> Self {
assert_eq!(column.num_vals(), doc_id_map.num_old_doc_ids() as u32 + 1);
let (min, max) =
tantivy_bitpacker::minmax(iter_remapped_multivalue_index(doc_id_map, column))
.unwrap_or((0u64, 0u64));
MultivalueStartIndex {
column,
doc_id_map,
min,
max,
}
}
}
impl<'a, C: Column> Column for MultivalueStartIndex<'a, C> {
fn get_val(&self, _idx: u32) -> u64 {
unimplemented!()
}
fn min_value(&self) -> u64 {
self.min
}
fn max_value(&self) -> u64 {
self.max
}
fn num_vals(&self) -> u32 {
(self.doc_id_map.num_new_doc_ids() + 1) as u32
}
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(iter_remapped_multivalue_index(
self.doc_id_map,
&self.column,
))
}
}
fn iter_remapped_multivalue_index<'a, C: Column>(
doc_id_map: &'a DocIdMapping,
column: &'a C,
) -> impl Iterator<Item = u64> + 'a {
let mut offset = 0;
std::iter::once(0).chain(doc_id_map.iter_old_doc_ids().map(move |old_doc| {
let num_vals_for_doc = column.get_val(old_doc + 1) - column.get_val(old_doc);
offset += num_vals_for_doc;
offset as u64
}))
}
/// Writer for multi-valued (as in, more than one value per document)
/// int fast field.
///
/// This `Writer` is only useful for advanced users.
/// The normal way to get your multivalued int in your index
/// is to
/// - declare your field with fast set to `Cardinality::MultiValues`
/// in your schema
/// - add your document simply by calling `.add_document(...)`.
///
/// The `MultiValuedFastFieldWriter` can be acquired from the
pub struct MultiValueU128FastFieldWriter {
field: Field,
vals: Vec<u128>,
doc_index: Vec<u64>,
}
impl MultiValueU128FastFieldWriter {
/// Creates a new `U128MultiValueFastFieldWriter`
pub(crate) fn new(field: Field) -> Self {
MultiValueU128FastFieldWriter {
field,
vals: Vec::new(),
doc_index: Vec::new(),
}
}
/// The memory used (inclusive childs)
pub fn mem_usage(&self) -> usize {
self.vals.capacity() * std::mem::size_of::<UnorderedTermId>()
+ self.doc_index.capacity() * std::mem::size_of::<u64>()
}
/// Finalize the current document.
pub(crate) fn next_doc(&mut self) {
self.doc_index.push(self.vals.len() as u64);
}
/// Pushes a new value to the current document.
pub(crate) fn add_val(&mut self, val: u128) {
self.vals.push(val);
}
/// Shift to the next document and adds
/// all of the matching field values present in the document.
pub fn add_document(&mut self, doc: &Document) -> crate::Result<()> {
self.next_doc();
for field_value in doc.field_values() {
if field_value.field == self.field {
let value = field_value.value();
let ip_addr = value
.as_ip_addr()
.ok_or_else(|| unexpected_value("ip", value))?;
let ip_addr_u128 = ip_addr.to_u128();
self.add_val(ip_addr_u128);
}
}
Ok(())
}
/// Returns an iterator over values per doc_id in ascending doc_id order.
///
/// Normally the order is simply iterating self.doc_id_index.
/// With doc_id_map it accounts for the new mapping, returning values in the order of the
/// new doc_ids.
fn get_ordered_values<'a: 'b, 'b>(
&'a self,
doc_id_map: Option<&'b DocIdMapping>,
) -> impl Iterator<Item = &'b [u128]> {
get_ordered_values(&self.vals, &self.doc_index, doc_id_map)
}
/// Serializes fast field values.
pub fn serialize(
mut self,
serializer: &mut CompositeFastFieldSerializer,
doc_id_map: Option<&DocIdMapping>,
) -> io::Result<()> {
{
// writing the offset index
//
self.doc_index.push(self.vals.len() as u64);
let col = VecColumn::from(&self.doc_index[..]);
if let Some(doc_id_map) = doc_id_map {
let multi_value_start_index = MultivalueStartIndex::new(&col, doc_id_map);
serializer.create_auto_detect_u64_fast_field_with_idx(
self.field,
multi_value_start_index,
0,
)?;
} else {
serializer.create_auto_detect_u64_fast_field_with_idx(self.field, col, 0)?;
}
}
{
let iter_gen = || self.get_ordered_values(doc_id_map).flatten().cloned();
serializer.create_u128_fast_field_with_idx(
self.field,
iter_gen,
self.vals.len() as u32,
1,
)?;
}
Ok(())
}
}
/// Returns an iterator over values per doc_id in ascending doc_id order.
///
/// Normally the order is simply iterating self.doc_id_index.
/// With doc_id_map it accounts for the new mapping, returning values in the order of the
/// new doc_ids.
fn get_ordered_values<'a: 'b, 'b, T>(
vals: &'a [T],
doc_index: &'a [u64],
doc_id_map: Option<&'b DocIdMapping>,
) -> impl Iterator<Item = &'b [T]> {
let doc_id_iter: Box<dyn Iterator<Item = u32>> = if let Some(doc_id_map) = doc_id_map {
Box::new(doc_id_map.iter_old_doc_ids())
} else {
let max_doc = doc_index.len() as DocId;
Box::new(0..max_doc)
};
doc_id_iter.map(move |doc_id| get_values_for_doc_id(doc_id, vals, doc_index))
}
/// returns all values for a doc_id
fn get_values_for_doc_id<'a, T>(doc_id: u32, vals: &'a [T], doc_index: &'a [u64]) -> &'a [T] {
let start_pos = doc_index[doc_id as usize] as usize;
let end_pos = doc_index
.get(doc_id as usize + 1)
.cloned()
.unwrap_or(vals.len() as u64) as usize; // special case, last doc_id has no offset information
&vals[start_pos..end_pos]
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_multivalue_start_index() {
let doc_id_mapping = DocIdMapping::from_new_id_to_old_id(vec![4, 1, 2]);
assert_eq!(doc_id_mapping.num_old_doc_ids(), 5);
let col = VecColumn::from(&[0u64, 3, 5, 10, 12, 16][..]);
let multivalue_start_index = MultivalueStartIndex::new(
&col, // 3, 2, 5, 2, 4
&doc_id_mapping,
);
assert_eq!(multivalue_start_index.num_vals(), 4);
assert_eq!(
multivalue_start_index.iter().collect::<Vec<u64>>(),
vec![0, 4, 6, 11]
); // 4, 2, 5
}
#[test]
fn test_multivalue_get_vals() {
let doc_id_mapping =
DocIdMapping::from_new_id_to_old_id(vec![0, 1, 2, 3, 4, 5, 6, 7, 8, 9]);
assert_eq!(doc_id_mapping.num_old_doc_ids(), 10);
let col = VecColumn::from(&[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55][..]);
let multivalue_start_index = MultivalueStartIndex::new(&col, &doc_id_mapping);
assert_eq!(
multivalue_start_index.iter().collect::<Vec<u64>>(),
vec![0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
);
assert_eq!(multivalue_start_index.num_vals(), 11);
}
}

338
src/fastfield/reader.rs
View File

@@ -1,338 +0,0 @@
use std::collections::HashMap;
use std::marker::PhantomData;
use std::path::Path;
use common::BinarySerializable;
use fastfield_codecs::bitpacked::BitpackedReader;
use fastfield_codecs::blockwise_linear::BlockwiseLinearReader;
use fastfield_codecs::linear::LinearReader;
use fastfield_codecs::{FastFieldCodecReader, FastFieldCodecType};
use super::{FastValue, GCDFastFieldCodec};
use crate::directory::{CompositeFile, Directory, FileSlice, OwnedBytes, RamDirectory, WritePtr};
use crate::error::DataCorruption;
use crate::fastfield::{CompositeFastFieldSerializer, FastFieldsWriter};
use crate::schema::{Schema, FAST};
use crate::DocId;
/// FastFieldReader is the trait to access fast field data.
pub trait FastFieldReader<Item: FastValue>: Clone {
/// Return the value associated to the given document.
///
/// This accessor should return as fast as possible.
///
/// # Panics
///
/// May panic if `doc` is greater than the segment
fn get(&self, doc: DocId) -> Item;
/// Fills an output buffer with the fast field values
/// associated with the `DocId` going from
/// `start` to `start + output.len()`.
///
/// Regardless of the type of `Item`, this method works
/// - transmuting the output array
/// - extracting the `Item`s as if they were `u64`
/// - possibly converting the `u64` value to the right type.
///
/// # Panics
///
/// May panic if `start + output.len()` is greater than
/// the segment's `maxdoc`.
fn get_range(&self, start: u64, output: &mut [Item]);
/// Returns the minimum value for this fast field.
///
/// The min value does not take in account of possible
/// deleted document, and should be considered as a lower bound
/// of the actual minimum value.
fn min_value(&self) -> Item;
/// Returns the maximum value for this fast field.
///
/// The max value does not take in account of possible
/// deleted document, and should be considered as an upper bound
/// of the actual maximum value.
fn max_value(&self) -> Item;
}
#[derive(Clone)]
/// DynamicFastFieldReader wraps different readers to access
/// the various encoded fastfield data
pub enum DynamicFastFieldReader<Item: FastValue> {
/// Bitpacked compressed fastfield data.
Bitpacked(FastFieldReaderCodecWrapper<Item, BitpackedReader>),
/// Linear interpolated values + bitpacked
Linear(FastFieldReaderCodecWrapper<Item, LinearReader>),
/// Blockwise linear interpolated values + bitpacked
BlockwiseLinear(FastFieldReaderCodecWrapper<Item, BlockwiseLinearReader>),
/// GCD and Bitpacked compressed fastfield data.
BitpackedGCD(FastFieldReaderCodecWrapper<Item, GCDFastFieldCodec<BitpackedReader>>),
/// GCD and Linear interpolated values + bitpacked
LinearGCD(FastFieldReaderCodecWrapper<Item, GCDFastFieldCodec<LinearReader>>),
/// GCD and Blockwise linear interpolated values + bitpacked
BlockwiseLinearGCD(FastFieldReaderCodecWrapper<Item, GCDFastFieldCodec<BlockwiseLinearReader>>),
}
impl<Item: FastValue> DynamicFastFieldReader<Item> {
/// Returns correct the reader wrapped in the `DynamicFastFieldReader` enum for the data.
pub fn open_from_id(
mut bytes: OwnedBytes,
codec_type: FastFieldCodecType,
) -> crate::Result<DynamicFastFieldReader<Item>> {
let reader = match codec_type {
FastFieldCodecType::Bitpacked => {
DynamicFastFieldReader::Bitpacked(FastFieldReaderCodecWrapper::<
Item,
BitpackedReader,
>::open_from_bytes(bytes)?)
}
FastFieldCodecType::Linear => DynamicFastFieldReader::Linear(
FastFieldReaderCodecWrapper::<Item, LinearReader>::open_from_bytes(bytes)?,
),
FastFieldCodecType::BlockwiseLinear => {
DynamicFastFieldReader::BlockwiseLinear(FastFieldReaderCodecWrapper::<
Item,
BlockwiseLinearReader,
>::open_from_bytes(bytes)?)
}
FastFieldCodecType::Gcd => {
let codec_type = FastFieldCodecType::deserialize(&mut bytes)?;
match codec_type {
FastFieldCodecType::Bitpacked => {
DynamicFastFieldReader::BitpackedGCD(FastFieldReaderCodecWrapper::<
Item,
GCDFastFieldCodec<BitpackedReader>,
>::open_from_bytes(
bytes
)?)
}
FastFieldCodecType::Linear => {
DynamicFastFieldReader::LinearGCD(FastFieldReaderCodecWrapper::<
Item,
GCDFastFieldCodec<LinearReader>,
>::open_from_bytes(
bytes
)?)
}
FastFieldCodecType::BlockwiseLinear => {
DynamicFastFieldReader::BlockwiseLinearGCD(FastFieldReaderCodecWrapper::<
Item,
GCDFastFieldCodec<BlockwiseLinearReader>,
>::open_from_bytes(
bytes
)?)
}
FastFieldCodecType::Gcd => {
return Err(DataCorruption::comment_only(
"Gcd codec wrapped into another gcd codec. This combination is not \
allowed.",
)
.into())
}
}
}
};
Ok(reader)
}
/// Returns correct the reader wrapped in the `DynamicFastFieldReader` enum for the data.
pub fn open(file: FileSlice) -> crate::Result<DynamicFastFieldReader<Item>> {
let mut bytes = file.read_bytes()?;
let codec_type = FastFieldCodecType::deserialize(&mut bytes)?;
Self::open_from_id(bytes, codec_type)
}
}
impl<Item: FastValue> FastFieldReader<Item> for DynamicFastFieldReader<Item> {
#[inline]
fn get(&self, doc: DocId) -> Item {
match self {
Self::Bitpacked(reader) => reader.get(doc),
Self::Linear(reader) => reader.get(doc),
Self::BlockwiseLinear(reader) => reader.get(doc),
Self::BitpackedGCD(reader) => reader.get(doc),
Self::LinearGCD(reader) => reader.get(doc),
Self::BlockwiseLinearGCD(reader) => reader.get(doc),
}
}
#[inline]
fn get_range(&self, start: u64, output: &mut [Item]) {
match self {
Self::Bitpacked(reader) => reader.get_range(start, output),
Self::Linear(reader) => reader.get_range(start, output),
Self::BlockwiseLinear(reader) => reader.get_range(start, output),
Self::BitpackedGCD(reader) => reader.get_range(start, output),
Self::LinearGCD(reader) => reader.get_range(start, output),
Self::BlockwiseLinearGCD(reader) => reader.get_range(start, output),
}
}
fn min_value(&self) -> Item {
match self {
Self::Bitpacked(reader) => reader.min_value(),
Self::Linear(reader) => reader.min_value(),
Self::BlockwiseLinear(reader) => reader.min_value(),
Self::BitpackedGCD(reader) => reader.min_value(),
Self::LinearGCD(reader) => reader.min_value(),
Self::BlockwiseLinearGCD(reader) => reader.min_value(),
}
}
fn max_value(&self) -> Item {
match self {
Self::Bitpacked(reader) => reader.max_value(),
Self::Linear(reader) => reader.max_value(),
Self::BlockwiseLinear(reader) => reader.max_value(),
Self::BitpackedGCD(reader) => reader.max_value(),
Self::LinearGCD(reader) => reader.max_value(),
Self::BlockwiseLinearGCD(reader) => reader.max_value(),
}
}
}
/// Wrapper for accessing a fastfield.
///
/// Holds the data and the codec to the read the data.
#[derive(Clone)]
pub struct FastFieldReaderCodecWrapper<Item: FastValue, CodecReader> {
reader: CodecReader,
_phantom: PhantomData<Item>,
}
impl<Item: FastValue, C: FastFieldCodecReader> FastFieldReaderCodecWrapper<Item, C> {
/// Opens a fast field given a file.
pub fn open(file: FileSlice) -> crate::Result<Self> {
let mut bytes = file.read_bytes()?;
let codec_code = bytes.read_u8();
let codec_type = FastFieldCodecType::from_code(codec_code).ok_or_else(|| {
DataCorruption::comment_only("Unknown codec code does not exist `{codec_code}`")
})?;
assert_eq!(
FastFieldCodecType::Bitpacked,
codec_type,
"Tried to open fast field as bitpacked encoded (id=1), but got serializer with \
different id"
);
Self::open_from_bytes(bytes)
}
/// Opens a fast field given the bytes.
pub fn open_from_bytes(bytes: OwnedBytes) -> crate::Result<Self> {
let reader = C::open_from_bytes(bytes)?;
Ok(FastFieldReaderCodecWrapper {
reader,
_phantom: PhantomData,
})
}
#[inline]
pub(crate) fn get_u64(&self, doc: u64) -> Item {
let data = self.reader.get_u64(doc);
Item::from_u64(data)
}
/// Internally `multivalued` also use SingleValue Fast fields.
/// It works as follows... A first column contains the list of start index
/// for each document, a second column contains the actual values.
///
/// The values associated to a given doc, are then
/// `second_column[first_column.get(doc)..first_column.get(doc+1)]`.
///
/// Which means single value fast field reader can be indexed internally with
/// something different from a `DocId`. For this use case, we want to use `u64`
/// values.
///
/// See `get_range` for an actual documentation about this method.
pub(crate) fn get_range_u64(&self, start: u64, output: &mut [Item]) {
for (i, out) in output.iter_mut().enumerate() {
*out = self.get_u64(start + (i as u64));
}
}
}
impl<Item: FastValue, C: FastFieldCodecReader + Clone> FastFieldReader<Item>
for FastFieldReaderCodecWrapper<Item, C>
{
/// Return the value associated to the given document.
///
/// This accessor should return as fast as possible.
///
/// # Panics
///
/// May panic if `doc` is greater than the segment
// `maxdoc`.
fn get(&self, doc: DocId) -> Item {
self.get_u64(u64::from(doc))
}
/// Fills an output buffer with the fast field values
/// associated with the `DocId` going from
/// `start` to `start + output.len()`.
///
/// Regardless of the type of `Item`, this method works
/// - transmuting the output array
/// - extracting the `Item`s as if they were `u64`
/// - possibly converting the `u64` value to the right type.
///
/// # Panics
///
/// May panic if `start + output.len()` is greater than
/// the segment's `maxdoc`.
fn get_range(&self, start: u64, output: &mut [Item]) {
self.get_range_u64(start, output);
}
/// Returns the minimum value for this fast field.
///
/// The max value does not take in account of possible
/// deleted document, and should be considered as an upper bound
/// of the actual maximum value.
fn min_value(&self) -> Item {
Item::from_u64(self.reader.min_value())
}
/// Returns the maximum value for this fast field.
///
/// The max value does not take in account of possible
/// deleted document, and should be considered as an upper bound
/// of the actual maximum value.
fn max_value(&self) -> Item {
Item::from_u64(self.reader.max_value())
}
}
impl<Item: FastValue> From<Vec<Item>> for DynamicFastFieldReader<Item> {
fn from(vals: Vec<Item>) -> DynamicFastFieldReader<Item> {
let mut schema_builder = Schema::builder();
let field = schema_builder.add_u64_field("field", FAST);
let schema = schema_builder.build();
let path = Path::new("__dummy__");
let directory: RamDirectory = RamDirectory::create();
{
let write: WritePtr = directory
.open_write(path)
.expect("With a RamDirectory, this should never fail.");
let mut serializer = CompositeFastFieldSerializer::from_write(write)
.expect("With a RamDirectory, this should never fail.");
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
{
let fast_field_writer = fast_field_writers
.get_field_writer_mut(field)
.expect("With a RamDirectory, this should never fail.");
for val in vals {
fast_field_writer.add_val(val.to_u64());
}
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
}
let file = directory.open_read(path).expect("Failed to open the file");
let composite_file = CompositeFile::open(&file).expect("Failed to read the composite file");
let field_file = composite_file
.open_read(field)
.expect("File component not found");
DynamicFastFieldReader::open(field_file).unwrap()
}
}

147
src/fastfield/readers.rs
View File

@@ -1,4 +1,9 @@
use super::reader::DynamicFastFieldReader;
use std::net::Ipv6Addr;
use std::sync::Arc;
use fastfield_codecs::{open, open_u128, Column, OptionalColumn};
use super::multivalued::MultiValuedU128FastFieldReader;
use crate::directory::{CompositeFile, FileSlice};
use crate::fastfield::{
BytesFastFieldReader, FastFieldNotAvailableError, FastValue, MultiValuedFastFieldReader,
@@ -20,6 +25,7 @@ pub struct FastFieldReaders {
pub(crate) enum FastType {
I64,
U64,
U128,
F64,
Bool,
Date,
@@ -46,6 +52,9 @@ pub(crate) fn type_and_cardinality(field_type: &FieldType) -> Option<(FastType,
FieldType::Str(options) if options.is_fast() => {
Some((FastType::U64, Cardinality::MultiValues))
}
FieldType::IpAddr(options) => options
.get_fastfield_cardinality()
.map(|cardinality| (FastType::U128, cardinality)),
_ => None,
}
}
@@ -109,14 +118,17 @@ impl FastFieldReaders {
&self,
field: Field,
index: usize,
) -> crate::Result<DynamicFastFieldReader<TFastValue>> {
) -> crate::Result<Arc<dyn OptionalColumn<TFastValue>>> {
let fast_field_slice = self.fast_field_data(field, index)?;
DynamicFastFieldReader::open(fast_field_slice)
let bytes = fast_field_slice.read_bytes()?;
let column = fastfield_codecs::open(bytes)?;
Ok(column)
}
pub(crate) fn typed_fast_field_reader<TFastValue: FastValue>(
&self,
field: Field,
) -> crate::Result<DynamicFastFieldReader<TFastValue>> {
) -> crate::Result<Arc<dyn OptionalColumn<TFastValue>>> {
self.typed_fast_field_reader_with_idx(field, 0)
}
@@ -126,59 +138,130 @@ impl FastFieldReaders {
) -> crate::Result<MultiValuedFastFieldReader<TFastValue>> {
let idx_reader = self.typed_fast_field_reader(field)?;
let vals_reader = self.typed_fast_field_reader_with_idx(field, 1)?;
Ok(MultiValuedFastFieldReader::open(idx_reader, vals_reader))
Ok(MultiValuedFastFieldReader::open(
idx_reader
.to_full()
.expect("multivalue fast field are always full"),
vals_reader
.to_full()
.expect("multivalue fast field are always full"),
))
}
/// Returns the `u64` fast field reader reader associated to `field`.
/// Returns the `u64` fast field reader reader associated with `field`.
///
/// If `field` is not a u64 fast field, this method returns an Error.
pub fn u64(&self, field: Field) -> crate::Result<DynamicFastFieldReader<u64>> {
pub fn u64(&self, field: Field) -> crate::Result<Arc<dyn OptionalColumn<u64>>> {
self.check_type(field, FastType::U64, Cardinality::SingleValue)?;
self.typed_fast_field_reader(field)
}
/// Returns the `u64` fast field reader reader associated to `field`, regardless of whether the
/// given field is effectively of type `u64` or not.
/// Returns the `ip` fast field reader reader associated to `field`.
///
/// If not, the fastfield reader will returns the u64-value associated to the original
/// If `field` is not a u128 fast field, this method returns an Error.
pub fn ip_addr(&self, field: Field) -> crate::Result<Arc<dyn OptionalColumn<Ipv6Addr>>> {
self.check_type(field, FastType::U128, Cardinality::SingleValue)?;
let bytes = self.fast_field_data(field, 0)?.read_bytes()?;
Ok(open_u128::<Ipv6Addr>(bytes)?)
}
/// Returns the `ip` fast field reader reader associated to `field`.
///
/// If `field` is not a u128 fast field, this method returns an Error.
pub fn ip_addrs(
&self,
field: Field,
) -> crate::Result<MultiValuedU128FastFieldReader<Ipv6Addr>> {
self.check_type(field, FastType::U128, Cardinality::MultiValues)?;
let idx_reader: Arc<dyn Column<u64>> = self
.typed_fast_field_reader(field)?
.to_full()
.expect("multivalue fast fields are always full");
let bytes = self.fast_field_data(field, 1)?.read_bytes()?;
let vals_reader = open_u128::<Ipv6Addr>(bytes)?
.to_full()
.expect("multivalue fields are always full");
Ok(MultiValuedU128FastFieldReader::open(
idx_reader,
vals_reader,
))
}
/// Returns the `u128` fast field reader reader associated to `field`.
///
/// If `field` is not a u128 base type fast field, this method returns an Error.
/// Ip addresses use u128 as base type.
pub(crate) fn u128(&self, field: Field) -> crate::Result<Arc<dyn OptionalColumn<u128>>> {
self.check_type(field, FastType::U128, Cardinality::SingleValue)?;
let bytes = self.fast_field_data(field, 0)?.read_bytes()?;
Ok(open_u128::<u128>(bytes)?)
}
/// Returns the `u128` multi-valued fast field reader reader associated to `field`.
///
/// If `field` is not a u128 multi-valued fast field, this method returns an Error.
pub fn u128s(&self, field: Field) -> crate::Result<MultiValuedU128FastFieldReader<u128>> {
self.check_type(field, FastType::U128, Cardinality::MultiValues)?;
let idx_reader: Arc<dyn Column<u64>> = self
.typed_fast_field_reader(field)?
.to_full()
.expect("multivalue fast fields are always full");
let bytes = self.fast_field_data(field, 1)?.read_bytes()?;
let vals_reader = open_u128::<u128>(bytes)?
.to_full()
.expect("multivalue fast fields are always full");
Ok(MultiValuedU128FastFieldReader::open(
idx_reader,
vals_reader,
))
}
/// Returns the `u64` fast field reader reader associated with `field`, regardless of whether
/// the given field is effectively of type `u64` or not.
///
/// If not, the fastfield reader will returns the u64-value associated with the original
/// FastValue.
pub fn u64_lenient(&self, field: Field) -> crate::Result<DynamicFastFieldReader<u64>> {
pub fn u64_lenient(&self, field: Field) -> crate::Result<Arc<dyn OptionalColumn<u64>>> {
self.typed_fast_field_reader(field)
}
/// Returns the `i64` fast field reader reader associated to `field`.
/// Returns the `i64` fast field reader reader associated with `field`.
///
/// If `field` is not a i64 fast field, this method returns an Error.
pub fn i64(&self, field: Field) -> crate::Result<DynamicFastFieldReader<i64>> {
pub fn i64(&self, field: Field) -> crate::Result<Arc<dyn OptionalColumn<i64>>> {
self.check_type(field, FastType::I64, Cardinality::SingleValue)?;
self.typed_fast_field_reader(field)
}
/// Returns the `date` fast field reader reader associated to `field`.
/// Returns the `date` fast field reader reader associated with `field`.
///
/// If `field` is not a date fast field, this method returns an Error.
pub fn date(&self, field: Field) -> crate::Result<DynamicFastFieldReader<DateTime>> {
pub fn date(&self, field: Field) -> crate::Result<Arc<dyn OptionalColumn<DateTime>>> {
self.check_type(field, FastType::Date, Cardinality::SingleValue)?;
self.typed_fast_field_reader(field)
}
/// Returns the `f64` fast field reader reader associated to `field`.
/// Returns the `f64` fast field reader reader associated with `field`.
///
/// If `field` is not a f64 fast field, this method returns an Error.
pub fn f64(&self, field: Field) -> crate::Result<DynamicFastFieldReader<f64>> {
pub fn f64(&self, field: Field) -> crate::Result<Arc<dyn OptionalColumn<f64>>> {
self.check_type(field, FastType::F64, Cardinality::SingleValue)?;
self.typed_fast_field_reader(field)
}
/// Returns the `bool` fast field reader reader associated to `field`.
/// Returns the `bool` fast field reader reader associated with `field`.
///
/// If `field` is not a bool fast field, this method returns an Error.
pub fn bool(&self, field: Field) -> crate::Result<DynamicFastFieldReader<bool>> {
pub fn bool(&self, field: Field) -> crate::Result<Arc<dyn OptionalColumn<bool>>> {
self.check_type(field, FastType::Bool, Cardinality::SingleValue)?;
self.typed_fast_field_reader(field)
}
/// Returns a `u64s` multi-valued fast field reader reader associated to `field`.
/// Returns a `u64s` multi-valued fast field reader reader associated with `field`.
///
/// If `field` is not a u64 multi-valued fast field, this method returns an Error.
pub fn u64s(&self, field: Field) -> crate::Result<MultiValuedFastFieldReader<u64>> {
@@ -186,15 +269,15 @@ impl FastFieldReaders {
self.typed_fast_field_multi_reader(field)
}
/// Returns a `u64s` multi-valued fast field reader reader associated to `field`, regardless of
/// whether the given field is effectively of type `u64` or not.
/// Returns a `u64s` multi-valued fast field reader reader associated with `field`, regardless
/// of whether the given field is effectively of type `u64` or not.
///
/// If `field` is not a u64 multi-valued fast field, this method returns an Error.
pub fn u64s_lenient(&self, field: Field) -> crate::Result<MultiValuedFastFieldReader<u64>> {
self.typed_fast_field_multi_reader(field)
}
/// Returns a `i64s` multi-valued fast field reader reader associated to `field`.
/// Returns a `i64s` multi-valued fast field reader reader associated with `field`.
///
/// If `field` is not a i64 multi-valued fast field, this method returns an Error.
pub fn i64s(&self, field: Field) -> crate::Result<MultiValuedFastFieldReader<i64>> {
@@ -202,7 +285,7 @@ impl FastFieldReaders {
self.typed_fast_field_multi_reader(field)
}
/// Returns a `f64s` multi-valued fast field reader reader associated to `field`.
/// Returns a `f64s` multi-valued fast field reader reader associated with `field`.
///
/// If `field` is not a f64 multi-valued fast field, this method returns an Error.
pub fn f64s(&self, field: Field) -> crate::Result<MultiValuedFastFieldReader<f64>> {
@@ -210,7 +293,7 @@ impl FastFieldReaders {
self.typed_fast_field_multi_reader(field)
}
/// Returns a `bools` multi-valued fast field reader reader associated to `field`.
/// Returns a `bools` multi-valued fast field reader reader associated with `field`.
///
/// If `field` is not a bool multi-valued fast field, this method returns an Error.
pub fn bools(&self, field: Field) -> crate::Result<MultiValuedFastFieldReader<bool>> {
@@ -218,7 +301,7 @@ impl FastFieldReaders {
self.typed_fast_field_multi_reader(field)
}
/// Returns a `time::OffsetDateTime` multi-valued fast field reader reader associated to
/// Returns a `time::OffsetDateTime` multi-valued fast field reader reader associated with
/// `field`.
///
/// If `field` is not a `time::OffsetDateTime` multi-valued fast field, this method returns an
@@ -228,7 +311,7 @@ impl FastFieldReaders {
self.typed_fast_field_multi_reader(field)
}
/// Returns the `bytes` fast field reader associated to `field`.
/// Returns the `bytes` fast field reader associated with `field`.
///
/// If `field` is not a bytes fast field, returns an Error.
pub fn bytes(&self, field: Field) -> crate::Result<BytesFastFieldReader> {
@@ -241,9 +324,15 @@ impl FastFieldReaders {
)));
}
let fast_field_idx_file = self.fast_field_data(field, 0)?;
let idx_reader = DynamicFastFieldReader::open(fast_field_idx_file)?;
let fast_field_idx_bytes = fast_field_idx_file.read_bytes()?;
let idx_reader = open(fast_field_idx_bytes)?;
let data = self.fast_field_data(field, 1)?;
BytesFastFieldReader::open(idx_reader, data)
BytesFastFieldReader::open(
idx_reader
.to_full()
.expect("multivalue fields are always full"),
data,
)
} else {
Err(FastFieldNotAvailableError::new(field_entry).into())
}

295
src/fastfield/serializer/mod.rs
View File

@@ -1,17 +1,9 @@
use std::io::{self, Write};
use std::num::NonZeroU64;
use common::{BinarySerializable, CountingWriter};
use fastdivide::DividerU64;
pub use fastfield_codecs::bitpacked::{BitpackedSerializer, BitpackedSerializerLegacy};
use fastfield_codecs::blockwise_linear::BlockwiseLinearSerializer;
use fastfield_codecs::linear::LinearSerializer;
use fastfield_codecs::FastFieldCodecType;
pub use fastfield_codecs::{FastFieldCodecSerializer, FastFieldDataAccess, FastFieldStats};
pub use fastfield_codecs::Column;
use fastfield_codecs::{FastFieldCodecType, MonotonicallyMappableToU64, ALL_CODEC_TYPES};
use super::{find_gcd, ALL_CODECS, GCD_DEFAULT};
use crate::directory::{CompositeWrite, WritePtr};
use crate::fastfield::gcd::write_gcd_header;
use crate::schema::Field;
/// `CompositeFastFieldSerializer` is in charge of serializing
@@ -23,274 +15,97 @@ use crate::schema::Field;
/// the serializer.
/// The serializer expects to receive the following calls.
///
/// * `new_u64_fast_field(...)`
/// * `add_val(...)`
/// * `add_val(...)`
/// * `add_val(...)`
/// * `create_auto_detect_u64_fast_field(...)`
/// * `create_auto_detect_u64_fast_field(...)`
/// * ...
/// * `close_field()`
/// * `new_u64_fast_field(...)`
/// * `add_val(...)`
/// * `let bytes_fastfield = new_bytes_fast_field(...)`
/// * `bytes_fastfield.write_all(...)`
/// * `bytes_fastfield.write_all(...)`
/// * `bytes_fastfield.flush()`
/// * ...
/// * `close_field()`
/// * `close()`
pub struct CompositeFastFieldSerializer {
composite_write: CompositeWrite<WritePtr>,
codec_enable_checker: FastFieldCodecEnableCheck,
}
#[derive(Debug, Clone)]
pub struct FastFieldCodecEnableCheck {
enabled_codecs: Vec<FastFieldCodecType>,
}
impl FastFieldCodecEnableCheck {
fn allow_all() -> Self {
FastFieldCodecEnableCheck {
enabled_codecs: ALL_CODECS.to_vec(),
}
}
fn is_enabled(&self, code_type: FastFieldCodecType) -> bool {
self.enabled_codecs.contains(&code_type)
}
}
impl From<FastFieldCodecType> for FastFieldCodecEnableCheck {
fn from(code_type: FastFieldCodecType) -> Self {
FastFieldCodecEnableCheck {
enabled_codecs: vec![code_type],
}
}
}
// use this, when this is merged and stabilized explicit_generic_args_with_impl_trait
// https://github.com/rust-lang/rust/pull/86176
fn codec_estimation<T: FastFieldCodecSerializer, A: FastFieldDataAccess>(
fastfield_accessor: &A,
estimations: &mut Vec<(f32, FastFieldCodecType)>,
) {
if !T::is_applicable(fastfield_accessor) {
return;
}
let ratio = T::estimate(fastfield_accessor);
estimations.push((ratio, T::CODEC_TYPE));
codec_types: Vec<FastFieldCodecType>,
}
impl CompositeFastFieldSerializer {
/// Constructor
/// New fast field serializer with all codec types
pub fn from_write(write: WritePtr) -> io::Result<CompositeFastFieldSerializer> {
Self::from_write_with_codec(write, FastFieldCodecEnableCheck::allow_all())
Self::from_write_with_codec(write, &ALL_CODEC_TYPES)
}
/// Constructor
/// New fast field serializer with allowed codec types
pub fn from_write_with_codec(
write: WritePtr,
codec_enable_checker: FastFieldCodecEnableCheck,
codec_types: &[FastFieldCodecType],
) -> io::Result<CompositeFastFieldSerializer> {
// just making room for the pointer to header.
let composite_write = CompositeWrite::wrap(write);
Ok(CompositeFastFieldSerializer {
composite_write,
codec_enable_checker,
codec_types: codec_types.to_vec(),
})
}
/// Serialize data into a new u64 fast field. The best compression codec will be chosen
/// automatically.
pub fn create_auto_detect_u64_fast_field(
pub fn create_auto_detect_u64_fast_field<T: MonotonicallyMappableToU64>(
&mut self,
field: Field,
fastfield_accessor: impl FastFieldDataAccess,
fastfield_accessor: impl Column<T>,
) -> io::Result<()> {
self.create_auto_detect_u64_fast_field_with_idx(field, fastfield_accessor, 0)
}
/// Serialize data into a new u64 fast field. The best compression codec will be chosen
/// automatically.
pub fn write_header<W: Write>(
field_write: &mut W,
codec_type: FastFieldCodecType,
) -> io::Result<()> {
codec_type.to_code().serialize(field_write)?;
Ok(())
}
/// Serialize data into a new u64 fast field. The best compression codec will be chosen
/// automatically.
pub fn create_auto_detect_u64_fast_field_with_idx(
pub fn create_auto_detect_u64_fast_field_with_idx<T: MonotonicallyMappableToU64>(
&mut self,
field: Field,
fastfield_accessor: impl FastFieldDataAccess,
fastfield_accessor: impl Column<T>,
idx: usize,
) -> io::Result<()> {
let min_value = fastfield_accessor.min_value();
let field_write = self.composite_write.for_field_with_idx(field, idx);
let gcd = find_gcd(fastfield_accessor.iter().map(|val| val - min_value))
.map(NonZeroU64::get)
.unwrap_or(GCD_DEFAULT);
if gcd == 1 {
return Self::create_auto_detect_u64_fast_field_with_idx_gcd(
self.codec_enable_checker.clone(),
field,
field_write,
fastfield_accessor,
);
}
Self::write_header(field_write, FastFieldCodecType::Gcd)?;
struct GCDWrappedFFAccess<T: FastFieldDataAccess> {
fastfield_accessor: T,
base_value: u64,
max_value: u64,
num_vals: u64,
gcd: DividerU64,
}
impl<T: FastFieldDataAccess> FastFieldDataAccess for GCDWrappedFFAccess<T> {
fn get_val(&self, position: u64) -> u64 {
self.gcd
.divide(self.fastfield_accessor.get_val(position) - self.base_value)
}
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(
self.fastfield_accessor
.iter()
.map(|val| self.gcd.divide(val - self.base_value)),
)
}
fn min_value(&self) -> u64 {
0
}
fn max_value(&self) -> u64 {
self.max_value
}
fn num_vals(&self) -> u64 {
self.num_vals
}
}
let num_vals = fastfield_accessor.num_vals();
let base_value = fastfield_accessor.min_value();
let max_value = (fastfield_accessor.max_value() - fastfield_accessor.min_value()) / gcd;
let fastfield_accessor = GCDWrappedFFAccess {
fastfield_accessor,
base_value,
max_value,
num_vals,
gcd: DividerU64::divide_by(gcd),
};
Self::create_auto_detect_u64_fast_field_with_idx_gcd(
self.codec_enable_checker.clone(),
field,
field_write,
fastfield_accessor,
)?;
write_gcd_header(field_write, base_value, gcd)?;
fastfield_codecs::serialize(fastfield_accessor, field_write, &self.codec_types)?;
Ok(())
}
/// Serialize data into a new u64 fast field. The best compression codec will be chosen
/// automatically.
pub fn create_auto_detect_u64_fast_field_with_idx_gcd<W: Write>(
codec_enable_checker: FastFieldCodecEnableCheck,
/// Serialize data into a new u64 fast field. The best compression codec of the the provided
/// will be chosen.
pub fn create_auto_detect_u64_fast_field_with_idx_and_codecs<T: MonotonicallyMappableToU64>(
&mut self,
field: Field,
field_write: &mut CountingWriter<W>,
fastfield_accessor: impl FastFieldDataAccess,
fastfield_accessor: impl Column<T>,
idx: usize,
codec_types: &[FastFieldCodecType],
) -> io::Result<()> {
let mut estimations = vec![];
let field_write = self.composite_write.for_field_with_idx(field, idx);
fastfield_codecs::serialize(fastfield_accessor, field_write, codec_types)?;
Ok(())
}
if codec_enable_checker.is_enabled(FastFieldCodecType::Bitpacked) {
codec_estimation::<BitpackedSerializer, _>(&fastfield_accessor, &mut estimations);
}
if codec_enable_checker.is_enabled(FastFieldCodecType::Linear) {
codec_estimation::<LinearSerializer, _>(&fastfield_accessor, &mut estimations);
}
if codec_enable_checker.is_enabled(FastFieldCodecType::BlockwiseLinear) {
codec_estimation::<BlockwiseLinearSerializer, _>(&fastfield_accessor, &mut estimations);
}
if let Some(broken_estimation) = estimations.iter().find(|estimation| estimation.0.is_nan())
{
warn!(
"broken estimation for fast field codec {:?}",
broken_estimation.1
);
}
// removing nan values for codecs with broken calculations, and max values which disables
// codecs
estimations.retain(|estimation| !estimation.0.is_nan() && estimation.0 != f32::MAX);
estimations.sort_by(|a, b| a.0.partial_cmp(&b.0).unwrap());
let (_ratio, codec_type) = estimations[0];
debug!("choosing fast field codec {codec_type:?} for field_id {field:?}"); // todo print actual field name
Self::write_header(field_write, codec_type)?;
match codec_type {
FastFieldCodecType::Bitpacked => {
BitpackedSerializer::serialize(field_write, &fastfield_accessor)?;
}
FastFieldCodecType::Linear => {
LinearSerializer::serialize(field_write, &fastfield_accessor)?;
}
FastFieldCodecType::BlockwiseLinear => {
BlockwiseLinearSerializer::serialize(field_write, &fastfield_accessor)?;
}
FastFieldCodecType::Gcd => {
return Err(io::Error::new(
io::ErrorKind::InvalidData,
"GCD codec not supported.",
));
}
}
field_write.flush()?;
/// Serialize data into a new u128 fast field. The codec will be compact space compressor,
/// which is optimized for scanning the fast field for a given range.
pub fn create_u128_fast_field_with_idx<F: Fn() -> I, I: Iterator<Item = u128>>(
&mut self,
field: Field,
iter_gen: F,
num_vals: u32,
idx: usize,
) -> io::Result<()> {
let field_write = self.composite_write.for_field_with_idx(field, idx);
fastfield_codecs::serialize_u128(iter_gen, num_vals, field_write)?;
Ok(())
}
/// Start serializing a new u64 fast field
pub fn serialize_into(
&mut self,
field: Field,
min_value: u64,
max_value: u64,
) -> io::Result<BitpackedSerializerLegacy<'_, CountingWriter<WritePtr>>> {
self.new_u64_fast_field_with_idx(field, min_value, max_value, 0)
}
/// Start serializing a new u64 fast field
pub fn new_u64_fast_field(
&mut self,
field: Field,
min_value: u64,
max_value: u64,
) -> io::Result<BitpackedSerializerLegacy<'_, CountingWriter<WritePtr>>> {
self.new_u64_fast_field_with_idx(field, min_value, max_value, 0)
}
/// Start serializing a new u64 fast field
pub fn new_u64_fast_field_with_idx(
&mut self,
field: Field,
min_value: u64,
max_value: u64,
idx: usize,
) -> io::Result<BitpackedSerializerLegacy<'_, CountingWriter<WritePtr>>> {
let field_write = self.composite_write.for_field_with_idx(field, idx);
// Prepend codec id to field data for compatibility with DynamicFastFieldReader.
FastFieldCodecType::Bitpacked.serialize(field_write)?;
BitpackedSerializerLegacy::open(field_write, min_value, max_value)
}
/// Start serializing a new [u8] fast field
pub fn new_bytes_fast_field_with_idx(
&mut self,
field: Field,
idx: usize,
) -> FastBytesFieldSerializer<'_, CountingWriter<WritePtr>> {
let field_write = self.composite_write.for_field_with_idx(field, idx);
FastBytesFieldSerializer { write: field_write }
/// Start serializing a new [u8] fast field. Use the returned writer to write data into the
/// bytes field. To associate the bytes with documents a seperate index must be created on
/// index 0. See bytes/writer.rs::serialize for an example.
///
/// The bytes will be stored as is, no compression will be applied.
pub fn new_bytes_fast_field(&mut self, field: Field) -> impl Write + '_ {
self.composite_write.for_field_with_idx(field, 1)
}
/// Closes the serializer
@@ -300,17 +115,3 @@ impl CompositeFastFieldSerializer {
self.composite_write.close()
}
}
pub struct FastBytesFieldSerializer<'a, W: Write> {
write: &'a mut W,
}
impl<'a, W: Write> FastBytesFieldSerializer<'a, W> {
pub fn write_all(&mut self, vals: &[u8]) -> io::Result<()> {
self.write.write_all(vals)
}
pub fn flush(&mut self) -> io::Result<()> {
self.write.flush()
}
}

237
src/fastfield/writer.rs
View File

@@ -2,12 +2,12 @@ use std::collections::HashMap;
use std::io;
use common;
use fnv::FnvHashMap;
use fastfield_codecs::{Column, MonotonicallyMappableToU128, MonotonicallyMappableToU64};
use rustc_hash::FxHashMap;
use tantivy_bitpacker::BlockedBitpacker;
use super::multivalued::MultiValuedFastFieldWriter;
use super::serializer::FastFieldStats;
use super::{FastFieldDataAccess, FastFieldType, FastValue};
use super::multivalued::{MultiValueU128FastFieldWriter, MultiValuedFastFieldWriter};
use super::FastFieldType;
use crate::fastfield::{BytesFastFieldWriter, CompositeFastFieldSerializer};
use crate::indexer::doc_id_mapping::DocIdMapping;
use crate::postings::UnorderedTermId;
@@ -19,10 +19,19 @@ use crate::DatePrecision;
pub struct FastFieldsWriter {
term_id_writers: Vec<MultiValuedFastFieldWriter>,
single_value_writers: Vec<IntFastFieldWriter>,
u128_value_writers: Vec<U128FastFieldWriter>,
u128_multi_value_writers: Vec<MultiValueU128FastFieldWriter>,
multi_values_writers: Vec<MultiValuedFastFieldWriter>,
bytes_value_writers: Vec<BytesFastFieldWriter>,
}
pub(crate) fn unexpected_value(expected: &str, actual: &Value) -> crate::TantivyError {
crate::TantivyError::SchemaError(format!(
"Expected a {:?} in fast field, but got {:?}",
expected, actual
))
}
fn fast_field_default_value(field_entry: &FieldEntry) -> u64 {
match *field_entry.field_type() {
FieldType::I64(_) | FieldType::Date(_) => common::i64_to_u64(0i64),
@@ -34,6 +43,8 @@ fn fast_field_default_value(field_entry: &FieldEntry) -> u64 {
impl FastFieldsWriter {
/// Create all `FastFieldWriter` required by the schema.
pub fn from_schema(schema: &Schema) -> FastFieldsWriter {
let mut u128_value_writers = Vec::new();
let mut u128_multi_value_writers = Vec::new();
let mut single_value_writers = Vec::new();
let mut term_id_writers = Vec::new();
let mut multi_values_writers = Vec::new();
@@ -97,10 +108,27 @@ impl FastFieldsWriter {
bytes_value_writers.push(fast_field_writer);
}
}
FieldType::IpAddr(opt) => {
if opt.is_fast() {
match opt.get_fastfield_cardinality() {
Some(Cardinality::SingleValue) => {
let fast_field_writer = U128FastFieldWriter::new(field);
u128_value_writers.push(fast_field_writer);
}
Some(Cardinality::MultiValues) => {
let fast_field_writer = MultiValueU128FastFieldWriter::new(field);
u128_multi_value_writers.push(fast_field_writer);
}
None => {}
}
}
}
FieldType::Str(_) | FieldType::JsonObject(_) => {}
}
}
FastFieldsWriter {
u128_value_writers,
u128_multi_value_writers,
term_id_writers,
single_value_writers,
multi_values_writers,
@@ -129,9 +157,19 @@ impl FastFieldsWriter {
.iter()
.map(|w| w.mem_usage())
.sum::<usize>()
+ self
.u128_value_writers
.iter()
.map(|w| w.mem_usage())
.sum::<usize>()
+ self
.u128_multi_value_writers
.iter()
.map(|w| w.mem_usage())
.sum::<usize>()
}
/// Get the `FastFieldWriter` associated to a field.
/// Get the `FastFieldWriter` associated with a field.
pub fn get_term_id_writer(&self, field: Field) -> Option<&MultiValuedFastFieldWriter> {
// TODO optimize
self.term_id_writers
@@ -139,7 +177,7 @@ impl FastFieldsWriter {
.find(|field_writer| field_writer.field() == field)
}
/// Get the `FastFieldWriter` associated to a field.
/// Get the `FastFieldWriter` associated with a field.
pub fn get_field_writer(&self, field: Field) -> Option<&IntFastFieldWriter> {
// TODO optimize
self.single_value_writers
@@ -147,7 +185,7 @@ impl FastFieldsWriter {
.find(|field_writer| field_writer.field() == field)
}
/// Get the `FastFieldWriter` associated to a field.
/// Get the `FastFieldWriter` associated with a field.
pub fn get_field_writer_mut(&mut self, field: Field) -> Option<&mut IntFastFieldWriter> {
// TODO optimize
self.single_value_writers
@@ -155,7 +193,7 @@ impl FastFieldsWriter {
.find(|field_writer| field_writer.field() == field)
}
/// Get the `FastFieldWriter` associated to a field.
/// Get the `FastFieldWriter` associated with a field.
pub fn get_term_id_writer_mut(
&mut self,
field: Field,
@@ -168,7 +206,7 @@ impl FastFieldsWriter {
/// Returns the fast field multi-value writer for the given field.
///
/// Returns None if the field does not exist, or is not
/// Returns `None` if the field does not exist, or is not
/// configured as a multivalued fastfield in the schema.
pub fn get_multivalue_writer_mut(
&mut self,
@@ -182,7 +220,7 @@ impl FastFieldsWriter {
/// Returns the bytes fast field writer for the given field.
///
/// Returns None if the field does not exist, or is not
/// Returns `None` if the field does not exist, or is not
/// configured as a bytes fastfield in the schema.
pub fn get_bytes_writer_mut(&mut self, field: Field) -> Option<&mut BytesFastFieldWriter> {
// TODO optimize
@@ -190,32 +228,38 @@ impl FastFieldsWriter {
.iter_mut()
.find(|field_writer| field_writer.field() == field)
}
/// Indexes all of the fastfields of a new document.
pub fn add_document(&mut self, doc: &Document) {
pub fn add_document(&mut self, doc: &Document) -> crate::Result<()> {
for field_writer in &mut self.term_id_writers {
field_writer.add_document(doc);
field_writer.add_document(doc)?;
}
for field_writer in &mut self.single_value_writers {
field_writer.add_document(doc);
field_writer.add_document(doc)?;
}
for field_writer in &mut self.multi_values_writers {
field_writer.add_document(doc);
field_writer.add_document(doc)?;
}
for field_writer in &mut self.bytes_value_writers {
field_writer.add_document(doc);
field_writer.add_document(doc)?;
}
for field_writer in &mut self.u128_value_writers {
field_writer.add_document(doc)?;
}
for field_writer in &mut self.u128_multi_value_writers {
field_writer.add_document(doc)?;
}
Ok(())
}
/// Serializes all of the `FastFieldWriter`s by pushing them in
/// order to the fast field serializer.
pub fn serialize(
&self,
self,
serializer: &mut CompositeFastFieldSerializer,
mapping: &HashMap<Field, FnvHashMap<UnorderedTermId, TermOrdinal>>,
mapping: &HashMap<Field, FxHashMap<UnorderedTermId, TermOrdinal>>,
doc_id_map: Option<&DocIdMapping>,
) -> io::Result<()> {
for field_writer in &self.term_id_writers {
for field_writer in self.term_id_writers {
let field = field_writer.field();
field_writer.serialize(serializer, mapping.get(&field), doc_id_map)?;
}
@@ -223,13 +267,115 @@ impl FastFieldsWriter {
field_writer.serialize(serializer, doc_id_map)?;
}
for field_writer in &self.multi_values_writers {
for field_writer in self.multi_values_writers {
let field = field_writer.field();
field_writer.serialize(serializer, mapping.get(&field), doc_id_map)?;
}
for field_writer in &self.bytes_value_writers {
for field_writer in self.bytes_value_writers {
field_writer.serialize(serializer, doc_id_map)?;
}
for field_writer in self.u128_value_writers {
field_writer.serialize(serializer, doc_id_map)?;
}
for field_writer in self.u128_multi_value_writers {
field_writer.serialize(serializer, doc_id_map)?;
}
Ok(())
}
}
/// Fast field writer for u128 values.
/// The fast field writer just keeps the values in memory.
///
/// Only when the segment writer can be closed and
/// persisted on disk, the fast field writer is
/// sent to a `FastFieldSerializer` via the `.serialize(...)`
/// method.
///
/// We cannot serialize earlier as the values are
/// compressed to a compact number space and the number of
/// bits required for bitpacking can only been known once
/// we have seen all of the values.
pub struct U128FastFieldWriter {
field: Field,
vals: Vec<u128>,
val_count: u32,
}
impl U128FastFieldWriter {
/// Creates a new `IntFastFieldWriter`
pub fn new(field: Field) -> Self {
Self {
field,
vals: vec![],
val_count: 0,
}
}
/// The memory used (inclusive childs)
pub fn mem_usage(&self) -> usize {
self.vals.len() * 16
}
/// Records a new value.
///
/// The n-th value being recorded is implicitely
/// associated to the document with the `DocId` n.
/// (Well, `n-1` actually because of 0-indexing)
pub fn add_val(&mut self, val: u128) {
self.vals.push(val);
}
/// Extract the fast field value from the document
/// (or use the default value) and records it.
///
/// Extract the value associated to the fast field for
/// this document.
pub fn add_document(&mut self, doc: &Document) -> crate::Result<()> {
match doc.get_first(self.field) {
Some(v) => {
let ip_addr = v.as_ip_addr().ok_or_else(|| unexpected_value("ip", v))?;
let value = ip_addr.to_u128();
self.add_val(value);
}
None => {
self.add_val(0); // TODO fix null handling
}
};
self.val_count += 1;
Ok(())
}
/// Push the fast fields value to the `FastFieldWriter`.
pub fn serialize(
&self,
serializer: &mut CompositeFastFieldSerializer,
doc_id_map: Option<&DocIdMapping>,
) -> io::Result<()> {
if let Some(doc_id_map) = doc_id_map {
let iter_gen = || {
doc_id_map
.iter_old_doc_ids()
.map(|idx| self.vals[idx as usize])
};
serializer.create_u128_fast_field_with_idx(
self.field,
iter_gen,
self.val_count as u32,
0,
)?;
} else {
let iter_gen = || self.vals.iter().cloned();
serializer.create_u128_fast_field_with_idx(
self.field,
iter_gen,
self.val_count as u32,
0,
)?;
}
Ok(())
}
}
@@ -238,7 +384,7 @@ impl FastFieldsWriter {
/// The fast field writer just keeps the values in memory.
///
/// Only when the segment writer can be closed and
/// persisted on disc, the fast field writer is
/// persisted on disk, the fast field writer is
/// sent to a `FastFieldSerializer` via the `.serialize(...)`
/// method.
///
@@ -294,7 +440,7 @@ impl IntFastFieldWriter {
/// Records a new value.
///
/// The n-th value being recorded is implicitly
/// associated to the document with the `DocId` n.
/// associated with the document with the `DocId` n.
/// (Well, `n-1` actually because of 0-indexing)
pub fn add_val(&mut self, val: u64) {
self.vals.add(val);
@@ -313,7 +459,7 @@ impl IntFastFieldWriter {
/// (or use the default value) and records it.
///
///
/// Extract the value associated to the fast field for
/// Extract the value associated with the fast field for
/// this document.
///
/// i64 and f64 are remapped to u64 using the logic
@@ -325,14 +471,14 @@ impl IntFastFieldWriter {
/// only the first one is taken in account.
///
/// Values on text fast fields are skipped.
pub fn add_document(&mut self, doc: &Document) {
pub fn add_document(&mut self, doc: &Document) -> crate::Result<()> {
match doc.get_first(self.field) {
Some(v) => {
let value = match (self.precision_opt, v) {
(Some(precision), Value::Date(date_val)) => {
date_val.truncate(precision).to_u64()
}
_ => super::value_to_u64(v),
_ => super::value_to_u64(v)?,
};
self.add_val(value);
}
@@ -340,6 +486,7 @@ impl IntFastFieldWriter {
self.add_val(self.val_if_missing);
}
};
Ok(())
}
/// get iterator over the data
@@ -359,16 +506,12 @@ impl IntFastFieldWriter {
(self.val_min, self.val_max)
};
let stats = FastFieldStats {
min_value: min,
max_value: max,
num_vals: self.val_count as u64,
};
let fastfield_accessor = WriterFastFieldAccessProvider {
doc_id_map,
vals: &self.vals,
stats,
min_value: min,
max_value: max,
num_vals: self.val_count as u32,
};
serializer.create_auto_detect_u64_fast_field(self.field, fastfield_accessor)?;
@@ -381,10 +524,13 @@ impl IntFastFieldWriter {
struct WriterFastFieldAccessProvider<'map, 'bitp> {
doc_id_map: Option<&'map DocIdMapping>,
vals: &'bitp BlockedBitpacker,
stats: FastFieldStats,
min_value: u64,
max_value: u64,
num_vals: u32,
}
impl<'map, 'bitp> FastFieldDataAccess for WriterFastFieldAccessProvider<'map, 'bitp> {
/// Return the value associated to the given doc.
impl<'map, 'bitp> Column for WriterFastFieldAccessProvider<'map, 'bitp> {
/// Return the value associated with the given doc.
///
/// Whenever possible use the Iterator passed to the fastfield creation instead, for performance
/// reasons.
@@ -392,15 +538,8 @@ impl<'map, 'bitp> FastFieldDataAccess for WriterFastFieldAccessProvider<'map, 'b
/// # Panics
///
/// May panic if `doc` is greater than the index.
fn get_val(&self, doc: u64) -> u64 {
if let Some(doc_id_map) = self.doc_id_map {
self.vals
.get(doc_id_map.get_old_doc_id(doc as u32) as usize) // consider extra
// FastFieldReader wrapper for
// non doc_id_map
} else {
self.vals.get(doc as usize)
}
fn get_val(&self, _doc: u32) -> u64 {
unimplemented!()
}
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
@@ -416,14 +555,14 @@ impl<'map, 'bitp> FastFieldDataAccess for WriterFastFieldAccessProvider<'map, 'b
}
fn min_value(&self) -> u64 {
self.stats.min_value
self.min_value
}
fn max_value(&self) -> u64 {
self.stats.max_value
self.max_value
}
fn num_vals(&self) -> u64 {
self.stats.num_vals
fn num_vals(&self) -> u32 {
self.num_vals
}
}

8
src/fieldnorm/mod.rs
View File

@@ -1,4 +1,4 @@
//! The fieldnorm represents the length associated to
//! The fieldnorm represents the length associated with
//! a given Field of a given document.
//!
//! This metric is important to compute the score of a
@@ -34,7 +34,7 @@ mod tests {
use crate::directory::{CompositeFile, Directory, RamDirectory, WritePtr};
use crate::fieldnorm::{FieldNormReader, FieldNormsSerializer, FieldNormsWriter};
use crate::query::{Query, TermQuery};
use crate::query::{EnableScoring, Query, TermQuery};
use crate::schema::{
Field, IndexRecordOption, Schema, TextFieldIndexing, TextOptions, STORED, TEXT,
};
@@ -112,7 +112,7 @@ mod tests {
Term::from_field_text(text, "hello"),
IndexRecordOption::WithFreqs,
);
let weight = query.weight(&searcher, true)?;
let weight = query.weight(EnableScoring::Enabled(&searcher))?;
let mut scorer = weight.scorer(searcher.segment_reader(0), 1.0f32)?;
assert_eq!(scorer.doc(), 0);
assert!((scorer.score() - 0.22920431).abs() < 0.001f32);
@@ -141,7 +141,7 @@ mod tests {
Term::from_field_text(text, "hello"),
IndexRecordOption::WithFreqs,
);
let weight = query.weight(&searcher, true)?;
let weight = query.weight(EnableScoring::Enabled(&searcher))?;
let mut scorer = weight.scorer(searcher.segment_reader(0), 1.0f32)?;
assert_eq!(scorer.doc(), 0);
assert!((scorer.score() - 0.22920431).abs() < 0.001f32);

8
src/fieldnorm/reader.rs
View File

@@ -47,9 +47,9 @@ impl FieldNormReaders {
}
}
/// Reads the fieldnorm associated to a document.
/// Reads the fieldnorm associated with a document.
///
/// The [fieldnorm](FieldNormReader::fieldnorm) represents the length associated to
/// The [fieldnorm](FieldNormReader::fieldnorm) represents the length associated with
/// a given Field of a given document.
#[derive(Clone)]
pub struct FieldNormReader(ReaderImplEnum);
@@ -104,7 +104,7 @@ impl FieldNormReader {
}
}
/// Returns the `fieldnorm` associated to a doc id.
/// Returns the `fieldnorm` associated with a doc id.
/// The fieldnorm is a value approximating the number
/// of tokens in a given field of the `doc_id`.
///
@@ -123,7 +123,7 @@ impl FieldNormReader {
}
}
/// Returns the `fieldnorm_id` associated to a document.
/// Returns the `fieldnorm_id` associated with a document.
#[inline]
pub fn fieldnorm_id(&self, doc_id: DocId) -> u8 {
match &self.0 {

2
src/fieldnorm/writer.rs
View File

@@ -9,7 +9,7 @@ use crate::DocId;
/// The `FieldNormsWriter` is in charge of tracking the fieldnorm byte
/// of each document for each field with field norms.
///
/// `FieldNormsWriter` stores a Vec<u8> for each tracked field, using a
/// `FieldNormsWriter` stores a `Vec<u8>` for each tracked field, using a
/// byte per document per field.
pub struct FieldNormsWriter {
fieldnorms_buffers: Vec<Option<Vec<u8>>>,

27
src/indexer/delete_queue.rs
View File

@@ -178,7 +178,7 @@ pub struct DeleteCursor {
impl DeleteCursor {
/// Skips operations and position it so that
/// - either all of the delete operation currently in the queue are consume and the next get
/// will return None.
/// will return `None`.
/// - the next get will return the first operation with an
/// `opstamp >= target_opstamp`.
pub fn skip_to(&mut self, target_opstamp: Opstamp) {
@@ -188,7 +188,7 @@ impl DeleteCursor {
}
}
#[cfg_attr(feature = "cargo-clippy", allow(clippy::wrong_self_convention))]
#[allow(clippy::wrong_self_convention)]
fn is_behind_opstamp(&mut self, target_opstamp: Opstamp) -> bool {
self.get()
.map(|operation| operation.opstamp < target_opstamp)
@@ -246,18 +246,27 @@ impl DeleteCursor {
mod tests {
use super::{DeleteOperation, DeleteQueue};
use crate::schema::{Field, Term};
use crate::query::{Explanation, Scorer, Weight};
use crate::{DocId, Score, SegmentReader};
struct DummyWeight;
impl Weight for DummyWeight {
fn scorer(&self, _reader: &SegmentReader, _boost: Score) -> crate::Result<Box<dyn Scorer>> {
Err(crate::TantivyError::InternalError("dummy impl".to_owned()))
}
fn explain(&self, _reader: &SegmentReader, _doc: DocId) -> crate::Result<Explanation> {
Err(crate::TantivyError::InternalError("dummy impl".to_owned()))
}
}
#[test]
fn test_deletequeue() {
let delete_queue = DeleteQueue::new();
let make_op = |i: usize| {
let field = Field::from_field_id(1u32);
DeleteOperation {
opstamp: i as u64,
term: Term::from_field_u64(field, i as u64),
}
let make_op = |i: usize| DeleteOperation {
opstamp: i as u64,
target: Box::new(DummyWeight),
};
delete_queue.push(make_op(1));

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