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base: rust:0.19.1
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:columnar-merge3
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

83 Commits
0.19.1 ... columnar-m

Author SHA1 Message Date
Paul Masurel
e9af721e60 Fixing compile 2023-02-05 18:05:29 +01:00
Paul Masurel
88ed3d8b48 Switching back to iterable. 2023-02-02 14:02:10 +01:00
Paul Masurel
aa8408a979 Updated TODO 2023-02-02 08:30:14 +01:00
Paul Masurel
4319d8c1bd Reenabling bench 2023-02-02 13:09:19 +09:00
Paul Masurel
33d18d0424 Plugged fastfield merge 
Fixing unit tests.
Fixing gcd
stats isolation
 2023-02-02 12:07:56 +09:00
Pascal Seitz
3de018c49f add merge for bytes/str column 2023-02-01 12:13:25 +08:00
Paul Masurel
96485f21d6 Added merge code for trivial mapping u64 & u128 
Added rank
 2023-01-30 10:05:40 +09:00
Pascal Seitz
1330e6f10d prepare for merge 2023-01-25 11:32:08 +09:00
Paul Masurel
5086914304 Integration of columnar 2023-01-24 18:18:05 +09:00
Paul Masurel
d7a8053cc2 Introduced a select cursor. 2023-01-20 23:27:39 +09:00
Paul Masurel
9548570e88 Fixing broken test build 2023-01-20 18:18:32 +09:00
Paul Masurel
9a296b29b7 Renamed dense file to dense.rs 2023-01-20 17:22:25 +09:00
PSeitz
b31fd389d8 collect columns for merge (#1812) 
* collect columns for merge

* return column_type from, fix visibility

* fix

Co-authored-by: Paul Masurel <paul@quickwit.io>
 2023-01-20 07:58:29 +01:00
Paul Masurel
89cec79813 Make it possible to force a column type and intricate bugfix. (#1815) 2023-01-20 14:30:56 +09:00
PSeitz
d09d91a856 fix tests (#1813) 2023-01-19 23:41:21 +09:00
PSeitz
50d8a8bc32 Update README (#1804) 
Some parts are outdated

For the debugging tutorial, debugging is really easy now with VSCode, and there are plenty of other sources for debugging rust
 2023-01-19 18:09:45 +09:00
Paul Masurel
08919a2900 Improvement on the scalar / random bitpacker code. (#1781) 
* Improvement on the scalar / random bitpacker code.

Added proptesting
Added simple benchmark
Added assert and comments on the very non trivial hidden contract
Remove the need for an extra padding.

The last point introduces a small performance regression (~10%).

* Fixing unit tests
 2023-01-19 18:09:13 +09:00
Lonre Wang
8ba333f1b4 Typo fix (#1803) 
* Update text_options.rs

* Update src/schema/text_options.rs

Co-authored-by: Paul Masurel <paul@quickwit.io>
 2023-01-19 17:56:05 +09:00
PSeitz
a2ca12995e update aggregation docs (#1807) 2023-01-19 09:52:47 +01:00
Paul Masurel
e3d504d833 Minor code cleanup (#1810) 2023-01-19 17:47:26 +09:00
Paul Masurel
5a42c5aae9 Add support for multivalues (#1809) 2023-01-19 16:55:01 +09:00
Paul Masurel
a86b104a40 Differentiating between str and bytes, + unit test 2023-01-19 14:38:12 +09:00
PSeitz
f9abd256b7 add ip addr to columnar (#1805) 2023-01-19 05:36:06 +01:00
Paul Masurel
9f42b6440a Completed unit test for dictionary encoded column 2023-01-19 12:15:27 +09:00
Paul Masurel
c723ed3f0b Columnar merge (#1806) 2023-01-19 11:52:27 +09:00
trinity-1686a
d72ea7d353 modify getters for sstable metadata (#1793) 
* add way to get up to `limit` terms from sstable

* make some function of sstable load less data

* add some tests to sstable

* add tests on sstable dictionary

* fix some bugs with sstable
 2023-01-18 14:42:55 +01:00
Paul Masurel
5180b612ef Removing the demuxer code (#1799) 2023-01-18 16:12:35 +09:00
PSeitz
f687b3a5aa start migrate Field to &str (#1772) 
start migrate Field to &str in preparation of columnar
return Result for get_field
 2023-01-18 16:12:07 +09:00
PSeitz
c4af63e588 add rename (#1797) 2023-01-18 13:28:37 +09:00
Adrien Guillo
4b343b3189 Merge pull request #1802 from quickwit-oss/guilload/clippy-fixes 
Fix some Clippy warnings
 2023-01-17 10:39:55 -05:00
Adrien Guillo
c51d9f9f83 Fix some Clippy warnings 2023-01-17 10:17:51 -05:00
Adrien Guillo
c9cb3d04bf Merge pull request #1788 from quickwit-oss/guilload/remove-std-dev-from-stats-agg 
Remove standard deviation from stats aggregation
 2023-01-16 23:16:36 -05:00
Adrien Guillo
0caaf13a90 Remove standard deviation from stats aggregation 2023-01-16 22:58:23 -05:00
Adrien Guillo
a59bd965cc Merge pull request #1794 from quickwit-oss/guilload/count-min-max-sum-aggs 
Add count, min, max, and sum aggregations
 2023-01-16 22:45:01 -05:00
Adrien Guillo
f2dad194ea Add count, min, max, and sum aggregations 2023-01-16 12:22:20 -05:00
Paul Masurel
25bad784ad Integrated fastfield codecs into columnar. (#1782) 
Introduced asymetric OptionalCodec / SerializableOptionalCodec
Removed cardinality from the columnar sstable.
Added DynamicColumn
Reorganized all files
Change DenseCodec serialization logic.
Renamed methods to rank/select
Moved versioning footer to the columnar level
 2023-01-16 17:24:49 +09:00
PSeitz
4bac945709 add ip field example (#1775) 2023-01-16 06:06:11 +01:00
trinity-1686a
16b704e190 make file_slice_for_range on sstable public (#1784) 2023-01-16 13:59:57 +09:00
PSeitz
6ca9a477f3 reuse stats for average (#1785) 
* reuse stats for average

* fix count type
 2023-01-13 23:32:27 +08:00
Shikhar Bhushan
2650111b76 EnableScoring::Disabled - optional Searcher (#1780) 2023-01-12 09:26:50 -05:00
PSeitz
1176555eff handle user input on get_docid_for_value_range (#1760) 
* handle user input on get_docid_for_value_range

fixes #1757

* pass range as parameter
 2023-01-12 14:20:16 +01:00
Adrien Guillo
f8d111a75e Merge pull request #1777 from quickwit-oss/guilload/ff-range-query-on-not-indexed-fields 
Allow range queries via fast fields on non-indexed fields
 2023-01-11 10:14:32 -05:00
Adrien Guillo
e17996f2fd Allow range queries via fast fields on non-indexed fields 2023-01-11 09:56:13 -05:00
Adrien Guillo
f3621c0487 Add license to tokenizer-api crate (#1778) 2023-01-11 05:26:41 +01:00
Adrien Guillo
14222a47a3 Fix typo (#1776) 2023-01-11 00:49:13 +09:00
Adam Reichold
8312c882a5 More cosmetic fixes for upcoming Clippy lints. (#1771) 2023-01-10 10:32:45 +01:00
Paul Masurel
7a8fce0ae7 Minor mini fixes 2023-01-10 14:15:30 +09:00
Michael Kleen
196e42f33e Add regex tokenizer (#1759) 
This adds a regex tokenizer which tokenizes the text by using a
regex pattern to split.

Co-authored-by: Michael Kleen <mkleen@gmailw.com>
 2023-01-10 13:38:37 +09:00
Adam Reichold
82a183bc2d Bump dependency on lru to from version 0.7.5 to version 0.9.0. (#1755) 2023-01-10 13:35:37 +09:00
dependabot[bot]
3090d49615 Update base64 requirement from 0.20.0 to 0.21.0 (#1769) 
Updates the requirements on [base64](https://github.com/marshallpierce/rust-base64) to permit the latest version.
- [Release notes](https://github.com/marshallpierce/rust-base64/releases)
- [Changelog](https://github.com/marshallpierce/rust-base64/blob/master/RELEASE-NOTES.md)
- [Commits](https://github.com/marshallpierce/rust-base64/compare/v0.20.0...v0.21.0)

---
updated-dependencies:
- dependency-name: base64
  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>
 2023-01-10 13:35:05 +09:00
PSeitz
7c6cc818ae enable range query on fast field for u64 compatible types (#1762) 
* enable range query on fast field for u64 compatible types

* rename, update benches
 2023-01-10 04:08:26 +01:00
PSeitz
514d23a20c move tokenizer API to seperate crate (#1767) 
closes #1766

Finding tantivy tokenizers is a frustrating experience currently, since
they need be updated for each tantivy version. That's unnecessary since
the API is rather stable anyway.
 2023-01-09 06:37:38 +01:00
Paul Masurel
4f9efe654c Support for columnar (#1734) 
* Added support for dynamic fast field.

See README for more information.

* Apply suggestions from code review

Co-authored-by: PSeitz <PSeitz@users.noreply.github.com>
 2023-01-07 17:37:00 +09:00
Adam Reichold
1afa5bf3db Make construction of LevenshteinAutomatonBuilder for FuzzyTermQuery instances lazy. (#1756) 2023-01-06 12:44:49 +09:00
PSeitz
07a51eb7c8 refactor multivalue fastfield, refactor range query (#1749) 
Introduce MakeZero trait, remove make_zero from FastValue
Merge two multivalue fastfield implementations into one
prepare range query on fastfield for different types
 2023-01-05 12:09:50 +01:00
Adam Reichold
2080c370c2 Enable usage of FuzzyTermQuery for specific fields via QueryParser (#1750) 
* Make nightly Clippy mostly happy.

* Document how to produce TermSetQuery queries using QueryParser.

* Enable construction of queries using FuzzyTermQuery via the QueryParser

* Use FxHashMap instead of HashMap in the QueryParser as these hash tables are not exposed to DoS attacks.

* Use a struct instead of a tuple to improve readability.
 2023-01-04 18:11:27 +09:00
Daw-Chih Liou
b22f96624e doc: update comments in the faceted search example (#1737) 
* doc: update comments in the faceted search example

* chore: format
 2023-01-02 11:07:30 +01:00
pinkforest(she/her)
b78dc5e313 Bump prettytables (#1746) 2022-12-31 15:01:39 +01:00
Paul Masurel
3f915925af Fixing unit tests 2022-12-27 12:02:16 +09:00
Paul Masurel
9c5fef5af7 Fixing sstable proptest (#1743) 2022-12-26 16:29:33 +09:00
Paul Masurel
9948a84ebe Simplifies the count_ones definition. (#1742) 2022-12-26 16:08:01 +09:00
PSeitz
45156fd869 use group_by in translate_codec_idx_to_original_id (#1736) 2022-12-26 06:13:29 +01:00
Paul Masurel
bc959006fa Ooops. Removing ordered_floats. 2022-12-22 19:50:34 +09:00
Paul Masurel
7385a8f80c Supporting PartialCmp in VectorColumn. (#1735) 
* Supporting PartialCmp in VectorColumn.
* Apply suggestions from code review

Co-authored-by: PSeitz <PSeitz@users.noreply.github.com>
 2022-12-22 17:47:25 +09:00
Paul Masurel
13b89cba17 Adding inlines. 2022-12-22 14:29:41 +09:00
Hasnain Lakhani
f4804ce2f5 Adjust spelling of "returns" in docs for DisjunctionMaxQuery (#1733) 2022-12-22 14:04:07 +09:00
Paul Masurel
2a6d1eaf78 Added missing license. 2022-12-22 12:47:43 +09:00
Paul Masurel
540a9972bd Support for NotNaN in fast fields 2022-12-22 12:28:25 +09:00
Paul Masurel
bb48c3e488 Refactoring to prepare for the addition of dynamic fast field (#1730) 
* Refactoring to prepare for the addition of dynamic fast field

- Exposing insert_key / insert_value
- Renamed SSTable::{Reader/Writer}-> SSTable::{ValueReader/ValueWriter}
- Added a generic Dictionary object in the sstable crate
- Removing the TermDictionary wrapper from tantivy, relying directly on
  an alias of the generic Dictionary object.
- dropped the use of byteorder in sstable.
- Stopped scanning / reading the entire dictionary when streaming a range.

* Added a benchmark for streaming sstable ranges.

* CR comments.

Rename deserialize_u64 -> deserialize_vint_u64

* Removed needless allocation, split serialize into serialize and clear.
 2022-12-22 12:25:46 +09:00
Paul Masurel
3339a3ec05 Removed feature(quickwit) in tantivy-common. 2022-12-22 10:19:57 +09:00
Paul Masurel
f39165e1e7 Moving FileSlice to tantivy-common (#1729) 2022-12-21 16:35:11 +09:00
Paul Masurel
32cb1d22da Removed AsyncIoResult. (#1728) 2022-12-21 16:01:17 +09:00
Paul Masurel
4a6bf50e78 Clippy 2022-12-21 15:43:34 +09:00
PSeitz
2ac1cc2fc0 add sparse codec (#1723) 
* add sparse codec

* Apply suggestions from code review

Co-authored-by: Paul Masurel <paul@quickwit.io>

* Apply suggestions from code review

Co-authored-by: Paul Masurel <paul@quickwit.io>

* Apply suggestions from code review

Co-authored-by: Paul Masurel <paul@quickwit.io>

* add the -1 u16 fix for metadata num_vals

* add dense block encoding to sparse codec

* add comment, refactor u16 reading

Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-12-20 15:30:33 +01:00
PSeitz
f9171a3981 fix clippy (#1725) 
* fix clippy

* fix clippy fastfield codecs

* fix clippy bitpacker

* fix clippy common

* fix clippy stacker

* fix clippy sstable

* fmt
 2022-12-20 07:30:06 +01:00
PSeitz
a2cf6a79b4 Sparse dense index (#1716) 
* add dense codec

* benchmark fix and important optimisation

* move code to DenseIndexBlock

improve benchmark

* Apply suggestions from code review

Co-authored-by: Paul Masurel <paul@quickwit.io>

* Apply suggestions from code review

Co-authored-by: Paul Masurel <paul@quickwit.io>

* extend benchmarks

* Apply suggestions from code review

Co-authored-by: Paul Masurel <paul@quickwit.io>

Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-12-13 07:50:09 +01:00
Paul Masurel
f6e87a5319 Cargo fmt 2022-12-13 12:30:40 +09:00
Paul Masurel
f9971e15fe Fixing unit test with sstable test. 2022-12-13 12:22:44 +09:00
PSeitz
3cdc8e7472 pass index info to serialize (#1719) 2022-12-13 04:20:31 +01:00
dependabot[bot]
fbb0f8b55d Update base64 requirement from 0.13.0 to 0.20.0 (#1720) 
Updates the requirements on [base64](https://github.com/marshallpierce/rust-base64) to permit the latest version.
- [Release notes](https://github.com/marshallpierce/rust-base64/releases)
- [Changelog](https://github.com/marshallpierce/rust-base64/blob/master/RELEASE-NOTES.md)
- [Commits](https://github.com/marshallpierce/rust-base64/compare/v0.13.0...v0.20.0)

---
updated-dependencies:
- dependency-name: base64
  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>
 2022-12-13 11:46:23 +09:00
Paul Masurel
136a8f4124 Isolating sstable and stacker in independant crates. (#1718) 
Both crate will be used in the new (optional + dynamic) fastfield work.
 2022-12-13 11:44:17 +09:00
PSeitz
5d4535de83 Changelog fix (#1717) 2022-12-12 14:28:42 +09:00
PSeitz
2c50b02eb3 Fix max bucket limit in histogram (#1703) 
* Fix max bucket limit in histogram

The max bucket limit in histogram was broken, since some code introduced temporary filtering of buckets, which then resulted into an incorrect increment on the bucket count.
The provided solution covers more scenarios, but there are still some scenarios unhandled (See #1702).

* Apply suggestions from code review

Co-authored-by: Paul Masurel <paul@quickwit.io>

Co-authored-by: Paul Masurel <paul@quickwit.io>
 2022-12-12 04:40:15 +01:00
260 changed files with 16436 additions and 10561 deletions
Expand all files Collapse all files

11
CHANGELOG.md
View File

@@ -2,22 +2,21 @@ Tantivy 0.19
================================
#### Bugfixes
- Fix missing fieldnorms for u64, i64, f64, bool, bytes and date [#1620](https://github.com/quickwit-oss/tantivy/pull/1620) (@PSeitz)
- Fix interpolation overflow in linear interpolation fastfield codec [#1480](https://github.com/quickwit-oss/tantivy/pull/1480 (@PSeitz @fulmicoton)
- Fix interpolation overflow in linear interpolation fastfield codec [#1480](https://github.com/quickwit-oss/tantivy/pull/1480) (@PSeitz @fulmicoton)
#### Features/Improvements
- Add support for `IN` in queryparser , e.g. `field: IN [val1 val2 val3]` [#1683](https://github.com/quickwit-oss/tantivy/pull/1683) (@trinity-1686a)
- 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)
- 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). (@evanxg852000)
- 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) [#1396](https://github.com/quickwit-oss/tantivy/pull/1396) (@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)
- Validate settings on create [#1570](https://github.com/quickwit-oss/tantivy/pull/1570) (@PSeitz)
- 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)
- 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)

18
Cargo.toml
View File

@@ -15,7 +15,7 @@ rust-version = "1.62"
[dependencies]
oneshot = "0.1.5"
base64 = "0.13.0"
base64 = "0.21.0"
byteorder = "1.4.3"
crc32fast = "1.3.2"
once_cell = "1.10.0"
@@ -36,7 +36,6 @@ 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"
stable_deref_trait = "1.2.0"
rust-stemmers = "1.2.0"
downcast-rs = "1.2.0"
bitpacking = { version = "0.8.4", default-features = false, features = ["bitpacker4x"] }
@@ -49,19 +48,20 @@ murmurhash32 = "0.2.0"
time = { version = "0.3.10", features = ["serde-well-known"] }
smallvec = "1.8.0"
rayon = "1.5.2"
lru = "0.7.5"
lru = "0.9.0"
fastdivide = "0.4.0"
itertools = "0.10.3"
measure_time = "0.8.2"
ciborium = { version = "0.2", optional = true}
async-trait = "0.1.53"
arc-swap = "1.5.0"
sstable = { version="0.1", path="./sstable", package ="tantivy-sstable", optional = true }
stacker = { version="0.1", path="./stacker", package ="tantivy-stacker" }
tantivy-query-grammar = { version= "0.19.0", path="./query-grammar" }
tantivy-bitpacker = { version= "0.3", path="./bitpacker" }
common = { version= "0.4", path = "./common/", package = "tantivy-common" }
fastfield_codecs = { version= "0.3", path="./fastfield_codecs", default-features = false }
ownedbytes = { version= "0.4", path="./ownedbytes" }
columnar = { version= "0.1", path="./columnar", package="tantivy-columnar" }
common = { version= "0.5", path = "./common/", package = "tantivy-common" }
tokenizer-api = { version="0.1", path="./tokenizer-api", package="tantivy-tokenizer-api" }
[target.'cfg(windows)'.dependencies]
winapi = "0.3.9"
@@ -104,10 +104,10 @@ zstd-compression = ["zstd"]
failpoints = ["fail/failpoints"]
unstable = [] # useful for benches.
quickwit = ["ciborium"]
quickwit = ["sstable"]
[workspace]
members = ["query-grammar", "bitpacker", "common", "fastfield_codecs", "ownedbytes"]
members = ["query-grammar", "bitpacker", "common", "ownedbytes", "stacker", "sstable", "tokenizer-api", "columnar"]
# Following the "fail" crate best practises, we isolate
# tests that define specific behavior in fail check points

51
README.md
View File

@@ -29,7 +29,7 @@ Your mileage WILL vary depending on the nature of queries and their load.
# Features
- Full-text search
- Configurable tokenizer (stemming available for 17 Latin languages with third party support for Chinese ([tantivy-jieba](https://crates.io/crates/tantivy-jieba) and [cang-jie](https://crates.io/crates/cang-jie)), Japanese ([lindera](https://github.com/lindera-morphology/lindera-tantivy), [Vaporetto](https://crates.io/crates/vaporetto_tantivy), and [tantivy-tokenizer-tiny-segmenter](https://crates.io/crates/tantivy-tokenizer-tiny-segmenter)) and Korean ([lindera](https://github.com/lindera-morphology/lindera-tantivy) + [lindera-ko-dic-builder](https://github.com/lindera-morphology/lindera-ko-dic-builder))
- Configurable tokenizer (stemming available for 17 Latin languages) with third party support for Chinese ([tantivy-jieba](https://crates.io/crates/tantivy-jieba) and [cang-jie](https://crates.io/crates/cang-jie)), Japanese ([lindera](https://github.com/lindera-morphology/lindera-tantivy), [Vaporetto](https://crates.io/crates/vaporetto_tantivy), and [tantivy-tokenizer-tiny-segmenter](https://crates.io/crates/tantivy-tokenizer-tiny-segmenter)) and Korean ([lindera](https://github.com/lindera-morphology/lindera-tantivy) + [lindera-ko-dic-builder](https://github.com/lindera-morphology/lindera-ko-dic-builder))
- Fast (check out the :racehorse: :sparkles: [benchmark](https://tantivy-search.github.io/bench/) :sparkles: :racehorse:)
- Tiny startup time (<10ms), perfect for command-line tools
- BM25 scoring (the same as Lucene)
@@ -41,13 +41,13 @@ Your mileage WILL vary depending on the nature of queries and their load.
- SIMD integer compression when the platform/CPU includes the SSE2 instruction set
- Single valued and multivalued u64, i64, and f64 fast fields (equivalent of doc values in Lucene)
- `&[u8]` fast fields
- Text, i64, u64, f64, dates, and hierarchical facet fields
- LZ4 compressed document store
- Text, i64, u64, f64, dates, ip, bool, and hierarchical facet fields
- Compressed document store (LZ4, Zstd, None, Brotli, Snap)
- Range queries
- Faceted search
- Configurable indexing (optional term frequency and position indexing)
- JSON Field
- Aggregation Collector: range buckets, average, and stats metrics
- Aggregation Collector: histogram, range buckets, average, and stats metrics
- LogMergePolicy with deletes
- Searcher Warmer API
- Cheesy logo with a horse
@@ -80,10 +80,11 @@ There are many ways to support this project.
# Contributing code
We use the GitHub Pull Request workflow: reference a GitHub ticket and/or include a comprehensive commit message when opening a PR.
Feel free to update CHANGELOG.md with your contribution.
## Minimum supported Rust version
## Tokenizer
Tantivy currently requires at least Rust 1.62 or later to compile.
When implementing a tokenizer for tantivy depend on the `tantivy-tokenizer-api` crate.
## Clone and build locally
@@ -91,41 +92,9 @@ Tantivy compiles on stable Rust.
To check out and run tests, you can simply run:
```bash
git clone https://github.com/quickwit-oss/tantivy.git
cd tantivy
cargo build
```
## Run tests
Some tests will not run with just `cargo test` because of `fail-rs`.
To run the tests exhaustively, run `./run-tests.sh`.
## Debug
You might find it useful to step through the programme with a debugger.
### A failing test
Make sure you haven't run `cargo clean` after the most recent `cargo test` or `cargo build` to guarantee that the `target/` directory exists. Use this bash script to find the name of the most recent debug build of Tantivy and run it under `rust-gdb`:
```bash
find target/debug/ -maxdepth 1 -executable -type f -name "tantivy*" -printf '%TY-%Tm-%Td %TT %p\n' | sort -r | cut -d " " -f 3 | xargs -I RECENT_DBG_TANTIVY rust-gdb RECENT_DBG_TANTIVY
```
Now that you are in `rust-gdb`, you can set breakpoints on lines and methods that match your source code and run the debug executable with flags that you normally pass to `cargo test` like this:
```bash
$gdb run --test-threads 1 --test $NAME_OF_TEST
```
### An example
By default, `rustc` compiles everything in the `examples/` directory in debug mode. This makes it easy for you to make examples to reproduce bugs:
```bash
rust-gdb target/debug/examples/$EXAMPLE_NAME
$ gdb run
git clone https://github.com/quickwit-oss/tantivy.git
cd tantivy
cargo test
```
# Companies Using Tantivy

18
TODO.txt Normal file
View File

@@ -0,0 +1,18 @@
Make schema_builder API fluent.
fix doc serialization and prevent compression problems
u64 , etc. shoudl return Resutl<Option> now that we support optional missing a column is really not an error
remove fastfield codecs
ditch the first_or_default trick. if it is still useful, improve its implementation.
rename FastFieldReaders::open to load
remove fast field reader
find a way to unify the two DateTime.
readd type check in the filter wrapper
add unit test on columnar list columns.
make sure sort works

12
benches/index-bench.rs
View File

@@ -34,7 +34,7 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
let index = Index::create_in_ram(schema.clone());
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
for _ in 0..NUM_REPEATS {
for doc_json in HDFS_LOGS.trim().split("\n") {
for doc_json in HDFS_LOGS.trim().split('\n') {
let doc = schema.parse_document(doc_json).unwrap();
index_writer.add_document(doc).unwrap();
}
@@ -46,7 +46,7 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
let index = Index::create_in_ram(schema.clone());
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
for _ in 0..NUM_REPEATS {
for doc_json in HDFS_LOGS.trim().split("\n") {
for doc_json in HDFS_LOGS.trim().split('\n') {
let doc = schema.parse_document(doc_json).unwrap();
index_writer.add_document(doc).unwrap();
}
@@ -59,7 +59,7 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
let index = Index::create_in_ram(schema_with_store.clone());
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
for _ in 0..NUM_REPEATS {
for doc_json in HDFS_LOGS.trim().split("\n") {
for doc_json in HDFS_LOGS.trim().split('\n') {
let doc = schema.parse_document(doc_json).unwrap();
index_writer.add_document(doc).unwrap();
}
@@ -71,7 +71,7 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
let index = Index::create_in_ram(schema_with_store.clone());
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
for _ in 0..NUM_REPEATS {
for doc_json in HDFS_LOGS.trim().split("\n") {
for doc_json in HDFS_LOGS.trim().split('\n') {
let doc = schema.parse_document(doc_json).unwrap();
index_writer.add_document(doc).unwrap();
}
@@ -85,7 +85,7 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
let json_field = dynamic_schema.get_field("json").unwrap();
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
for _ in 0..NUM_REPEATS {
for doc_json in HDFS_LOGS.trim().split("\n") {
for doc_json in HDFS_LOGS.trim().split('\n') {
let json_val: serde_json::Map<String, serde_json::Value> =
serde_json::from_str(doc_json).unwrap();
let doc = tantivy::doc!(json_field=>json_val);
@@ -101,7 +101,7 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
let json_field = dynamic_schema.get_field("json").unwrap();
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
for _ in 0..NUM_REPEATS {
for doc_json in HDFS_LOGS.trim().split("\n") {
for doc_json in HDFS_LOGS.trim().split('\n') {
let json_val: serde_json::Map<String, serde_json::Value> =
serde_json::from_str(doc_json).unwrap();
let doc = tantivy::doc!(json_field=>json_val);

4
bitpacker/Cargo.toml
View File

@@ -15,3 +15,7 @@ homepage = "https://github.com/quickwit-oss/tantivy"
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[dependencies]
[dev-dependencies]
rand = "0.8"
proptest = "1"

36
bitpacker/benches/bench.rs
View File

@@ -4,9 +4,39 @@ extern crate test;
#[cfg(test)]
mod tests {
use tantivy_bitpacker::BlockedBitpacker;
use rand::seq::IteratorRandom;
use rand::thread_rng;
use tantivy_bitpacker::{BitPacker, BitUnpacker, BlockedBitpacker};
use test::Bencher;
#[inline(never)]
fn create_bitpacked_data(bit_width: u8, num_els: u32) -> Vec<u8> {
let mut bitpacker = BitPacker::new();
let mut buffer = Vec::new();
for _ in 0..num_els {
// the values do not matter.
bitpacker.write(0u64, bit_width, &mut buffer).unwrap();
bitpacker.flush(&mut buffer).unwrap();
}
buffer
}
#[bench]
fn bench_bitpacking_read(b: &mut Bencher) {
let bit_width = 3;
let num_els = 1_000_000u32;
let bit_unpacker = BitUnpacker::new(bit_width);
let data = create_bitpacked_data(bit_width, num_els);
let idxs: Vec<u32> = (0..num_els).choose_multiple(&mut thread_rng(), 100_000);
b.iter(|| {
let mut out = 0u64;
for &idx in &idxs {
out = out.wrapping_add(bit_unpacker.get(idx, &data[..]));
}
out
});
}
#[bench]
fn bench_blockedbitp_read(b: &mut Bencher) {
let mut blocked_bitpacker = BlockedBitpacker::new();
@@ -14,9 +44,9 @@ mod tests {
blocked_bitpacker.add(val * val);
}
b.iter(|| {
let mut out = 0;
let mut out = 0u64;
for val in 0..=21500 {
out = blocked_bitpacker.get(val);
out = out.wrapping_add(blocked_bitpacker.get(val));
}
out
});

112
bitpacker/src/bitpacker.rs
View File

@@ -19,21 +19,20 @@ impl BitPacker {
}
#[inline]
pub fn write<TWrite: io::Write>(
pub fn write<TWrite: io::Write + ?Sized>(
&mut self,
val: u64,
num_bits: u8,
output: &mut TWrite,
) -> io::Result<()> {
let val_u64 = val as u64;
let num_bits = num_bits as usize;
if self.mini_buffer_written + num_bits > 64 {
self.mini_buffer |= val_u64.wrapping_shl(self.mini_buffer_written as u32);
self.mini_buffer |= val.wrapping_shl(self.mini_buffer_written as u32);
output.write_all(self.mini_buffer.to_le_bytes().as_ref())?;
self.mini_buffer = val_u64.wrapping_shr((64 - self.mini_buffer_written) as u32);
self.mini_buffer = val.wrapping_shr((64 - self.mini_buffer_written) as u32);
self.mini_buffer_written = self.mini_buffer_written + num_bits - 64;
} else {
self.mini_buffer |= val_u64 << self.mini_buffer_written;
self.mini_buffer |= val << self.mini_buffer_written;
self.mini_buffer_written += num_bits;
if self.mini_buffer_written == 64 {
output.write_all(self.mini_buffer.to_le_bytes().as_ref())?;
@@ -44,7 +43,7 @@ impl BitPacker {
Ok(())
}
pub fn flush<TWrite: io::Write>(&mut self, output: &mut TWrite) -> io::Result<()> {
pub fn flush<TWrite: io::Write + ?Sized>(&mut self, output: &mut TWrite) -> io::Result<()> {
if self.mini_buffer_written > 0 {
let num_bytes = (self.mini_buffer_written + 7) / 8;
let bytes = self.mini_buffer.to_le_bytes();
@@ -55,29 +54,33 @@ impl BitPacker {
Ok(())
}
pub fn close<TWrite: io::Write>(&mut self, output: &mut TWrite) -> io::Result<()> {
pub fn close<TWrite: io::Write + ?Sized>(&mut self, output: &mut TWrite) -> io::Result<()> {
self.flush(output)?;
// Padding the write file to simplify reads.
output.write_all(&[0u8; 7])?;
Ok(())
}
}
#[derive(Clone, Debug, Default)]
#[derive(Clone, Debug, Default, Copy)]
pub struct BitUnpacker {
num_bits: u64,
num_bits: u32,
mask: u64,
}
impl BitUnpacker {
/// Creates a bit unpacker, that assumes the same bitwidth for all values.
///
/// The bitunpacker works by doing an unaligned read of 8 bytes.
/// For this reason, values of `num_bits` between
/// [57..63] are forbidden.
pub fn new(num_bits: u8) -> BitUnpacker {
assert!(num_bits <= 7 * 8 || num_bits == 64);
let mask: u64 = if num_bits == 64 {
!0u64
} else {
(1u64 << num_bits) - 1u64
};
BitUnpacker {
num_bits: u64::from(num_bits),
num_bits: u32::from(num_bits),
mask,
}
}
@@ -88,21 +91,31 @@ impl BitUnpacker {
#[inline]
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 = (addr_in_bits >> 3) as usize;
if addr + 8 > data.len() {
if self.num_bits == 0 {
return 0;
}
let bit_shift = addr_in_bits & 7;
return self.get_slow_path(addr, bit_shift, data);
}
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 u32,
"The fast field field should have been padded with 7 bytes."
);
let bytes: [u8; 8] = (&data[(addr as usize)..(addr as usize) + 8])
.try_into()
.unwrap();
let bytes: [u8; 8] = (&data[addr..addr + 8]).try_into().unwrap();
let val_unshifted_unmasked: u64 = u64::from_le_bytes(bytes);
let val_shifted = (val_unshifted_unmasked >> bit_shift) as u64;
let val_shifted = val_unshifted_unmasked >> bit_shift;
val_shifted & self.mask
}
#[inline(never)]
fn get_slow_path(&self, addr: usize, bit_shift: u32, data: &[u8]) -> u64 {
let mut bytes: [u8; 8] = [0u8; 8];
let available_bytes = data.len() - addr;
// This function is meant to only be called if we did not have 8 bytes to load.
debug_assert!(available_bytes < 8);
bytes[..available_bytes].copy_from_slice(&data[addr..]);
let val_unshifted_unmasked: u64 = u64::from_le_bytes(bytes);
let val_shifted = val_unshifted_unmasked >> bit_shift;
val_shifted & self.mask
}
}
@@ -111,7 +124,7 @@ impl BitUnpacker {
mod test {
use super::{BitPacker, BitUnpacker};
fn create_fastfield_bitpacker(len: usize, num_bits: u8) -> (BitUnpacker, Vec<u64>, Vec<u8>) {
fn create_bitpacker(len: usize, num_bits: u8) -> (BitUnpacker, Vec<u64>, Vec<u8>) {
let mut data = Vec::new();
let mut bitpacker = BitPacker::new();
let max_val: u64 = (1u64 << num_bits as u64) - 1u64;
@@ -122,13 +135,13 @@ mod test {
bitpacker.write(val, num_bits, &mut data).unwrap();
}
bitpacker.close(&mut data).unwrap();
assert_eq!(data.len(), ((num_bits as usize) * len + 7) / 8 + 7);
assert_eq!(data.len(), ((num_bits as usize) * len + 7) / 8);
let bitunpacker = BitUnpacker::new(num_bits);
(bitunpacker, vals, data)
}
fn test_bitpacker_util(len: usize, num_bits: u8) {
let (bitunpacker, vals, data) = create_fastfield_bitpacker(len, num_bits);
let (bitunpacker, vals, data) = create_bitpacker(len, num_bits);
for (i, val) in vals.iter().enumerate() {
assert_eq!(bitunpacker.get(i as u32, &data), *val);
}
@@ -142,4 +155,49 @@ mod test {
test_bitpacker_util(6, 14);
test_bitpacker_util(1000, 14);
}
use proptest::prelude::*;
fn num_bits_strategy() -> impl Strategy<Value = u8> {
prop_oneof!(Just(0), Just(1), 2u8..56u8, Just(56), Just(64),)
}
fn vals_strategy() -> impl Strategy<Value = (u8, Vec<u64>)> {
(num_bits_strategy(), 0usize..100usize).prop_flat_map(|(num_bits, len)| {
let max_val = if num_bits == 64 {
u64::MAX
} else {
(1u64 << num_bits as u32) - 1
};
let vals = proptest::collection::vec(0..=max_val, len);
vals.prop_map(move |vals| (num_bits, vals))
})
}
fn test_bitpacker_aux(num_bits: u8, vals: &[u64]) {
let mut buffer: Vec<u8> = Vec::new();
let mut bitpacker = BitPacker::new();
for &val in vals {
bitpacker.write(val, num_bits, &mut buffer).unwrap();
}
bitpacker.flush(&mut buffer).unwrap();
assert_eq!(buffer.len(), (vals.len() * num_bits as usize + 7) / 8);
let bitunpacker = BitUnpacker::new(num_bits);
let max_val = if num_bits == 64 {
u64::MAX
} else {
(1u64 << num_bits) - 1
};
for (i, val) in vals.iter().copied().enumerate() {
assert!(val <= max_val);
assert_eq!(bitunpacker.get(i as u32, &buffer), val);
}
}
proptest::proptest! {
#[test]
fn test_bitpacker_proptest((num_bits, vals) in vals_strategy()) {
test_bitpacker_aux(num_bits, &vals);
}
}
}

6
bitpacker/src/blocked_bitpacker.rs
View File

@@ -84,7 +84,7 @@ impl BlockedBitpacker {
#[inline]
pub fn add(&mut self, val: u64) {
self.buffer.push(val);
if self.buffer.len() == BLOCK_SIZE as usize {
if self.buffer.len() == BLOCK_SIZE {
self.flush();
}
}
@@ -126,8 +126,8 @@ impl BlockedBitpacker {
}
#[inline]
pub fn get(&self, idx: usize) -> u64 {
let metadata_pos = idx / BLOCK_SIZE as usize;
let pos_in_block = idx % BLOCK_SIZE as usize;
let metadata_pos = idx / BLOCK_SIZE;
let pos_in_block = idx % BLOCK_SIZE;
if let Some(metadata) = self.offset_and_bits.get(metadata_pos) {
let unpacked = BitUnpacker::new(metadata.num_bits()).get(
pos_in_block as u32,

122
bitpacker/src/lib.rs
View File

@@ -1,6 +1,8 @@
mod bitpacker;
mod blocked_bitpacker;
use std::cmp::Ordering;
pub use crate::bitpacker::{BitPacker, BitUnpacker};
pub use crate::blocked_bitpacker::BlockedBitpacker;
@@ -37,44 +39,104 @@ pub fn compute_num_bits(n: u64) -> u8 {
}
}
/// Computes the (min, max) of an iterator of `PartialOrd` values.
///
/// For values implementing `Ord` (in a way consistent to their `PartialOrd` impl),
/// this function behaves as expected.
///
/// For values with partial ordering, the behavior is non-trivial and may
/// depends on the order of the values.
/// For floats however, it simply returns the same results as if NaN were
/// skipped.
pub fn minmax<I, T>(mut vals: I) -> Option<(T, T)>
where
I: Iterator<Item = T>,
T: Copy + Ord,
T: Copy + PartialOrd,
{
if let Some(first_el) = vals.next() {
return Some(vals.fold((first_el, first_el), |(min_val, max_val), el| {
(min_val.min(el), max_val.max(el))
}));
let first_el = vals.find(|val| {
// We use this to make sure we skip all NaN values when
// working with a float type.
val.partial_cmp(val) == Some(Ordering::Equal)
})?;
let mut min_so_far: T = first_el;
let mut max_so_far: T = first_el;
for val in vals {
if val.partial_cmp(&min_so_far) == Some(Ordering::Less) {
min_so_far = val;
}
if val.partial_cmp(&max_so_far) == Some(Ordering::Greater) {
max_so_far = val;
}
}
None
Some((min_so_far, max_so_far))
}
#[test]
fn test_compute_num_bits() {
assert_eq!(compute_num_bits(1), 1u8);
assert_eq!(compute_num_bits(0), 0u8);
assert_eq!(compute_num_bits(2), 2u8);
assert_eq!(compute_num_bits(3), 2u8);
assert_eq!(compute_num_bits(4), 3u8);
assert_eq!(compute_num_bits(255), 8u8);
assert_eq!(compute_num_bits(256), 9u8);
assert_eq!(compute_num_bits(5_000_000_000), 33u8);
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_minmax_empty() {
let vals: Vec<u32> = vec![];
assert_eq!(minmax(vals.into_iter()), None);
}
#[test]
fn test_compute_num_bits() {
assert_eq!(compute_num_bits(1), 1u8);
assert_eq!(compute_num_bits(0), 0u8);
assert_eq!(compute_num_bits(2), 2u8);
assert_eq!(compute_num_bits(3), 2u8);
assert_eq!(compute_num_bits(4), 3u8);
assert_eq!(compute_num_bits(255), 8u8);
assert_eq!(compute_num_bits(256), 9u8);
assert_eq!(compute_num_bits(5_000_000_000), 33u8);
}
#[test]
fn test_minmax_one() {
assert_eq!(minmax(vec![1].into_iter()), Some((1, 1)));
}
#[test]
fn test_minmax_empty() {
let vals: Vec<u32> = vec![];
assert_eq!(minmax(vals.into_iter()), None);
}
#[test]
fn test_minmax_two() {
assert_eq!(minmax(vec![1, 2].into_iter()), Some((1, 2)));
assert_eq!(minmax(vec![2, 1].into_iter()), Some((1, 2)));
#[test]
fn test_minmax_one() {
assert_eq!(minmax(vec![1].into_iter()), Some((1, 1)));
}
#[test]
fn test_minmax_two() {
assert_eq!(minmax(vec![1, 2].into_iter()), Some((1, 2)));
assert_eq!(minmax(vec![2, 1].into_iter()), Some((1, 2)));
}
#[test]
fn test_minmax_nan() {
assert_eq!(
minmax(vec![f64::NAN, 1f64, 2f64].into_iter()),
Some((1f64, 2f64))
);
assert_eq!(
minmax(vec![2f64, f64::NAN, 1f64].into_iter()),
Some((1f64, 2f64))
);
assert_eq!(
minmax(vec![2f64, 1f64, f64::NAN].into_iter()),
Some((1f64, 2f64))
);
}
#[test]
fn test_minmax_inf() {
assert_eq!(
minmax(vec![f64::INFINITY, 1f64, 2f64].into_iter()),
Some((1f64, f64::INFINITY))
);
assert_eq!(
minmax(vec![-f64::INFINITY, 1f64, 2f64].into_iter()),
Some((-f64::INFINITY, 2f64))
);
assert_eq!(
minmax(vec![2f64, f64::INFINITY, 1f64].into_iter()),
Some((1f64, f64::INFINITY))
);
assert_eq!(
minmax(vec![2f64, 1f64, -f64::INFINITY].into_iter()),
Some((-f64::INFINITY, 2f64))
);
}
}

28
columnar/Cargo.toml Normal file
View File

@@ -0,0 +1,28 @@
[package]
name = "tantivy-columnar"
version = "0.1.0"
edition = "2021"
license = "MIT"
[dependencies]
stacker = { path = "../stacker", package="tantivy-stacker"}
serde_json = "1"
thiserror = "1"
fnv = "1"
sstable = { path = "../sstable", package = "tantivy-sstable" }
common = { path = "../common", package = "tantivy-common" }
itertools = "0.10"
log = "0.4"
tantivy-bitpacker = { version= "0.3", path = "../bitpacker/" }
prettytable-rs = {version="0.10.0", optional= true}
rand = {version="0.8.3", optional= true}
fastdivide = "0.4"
measure_time = { version="0.8.2", optional=true}
[dev-dependencies]
proptest = "1"
more-asserts = "0.3.0"
rand = "0.8.3"
[features]
unstable = []

6
columnar/Makefile Normal file
View File

@@ -0,0 +1,6 @@
test:
echo "Run test only... No examples."
cargo test --tests --lib
fmt:
cargo +nightly fmt --all

109
columnar/README.md Normal file
View File

@@ -0,0 +1,109 @@
# Columnar format
This crate describes columnar format used in tantivy.
## Goals
This format is special in the following way.
- it needs to be compact
- accessing a specific column does not require to load the entire columnar. It can be done in 2 to 3 random access.
- columns of several types can be associated with the same column name.
- it needs to support columns with different types `(str, u64, i64, f64)`
and different cardinality `(required, optional, multivalued)`.
- columns, once loaded, offer cheap random access.
- it is designed to allow range queries.
# Coercion rules
Users can create a columnar by inserting rows to a `ColumnarWriter`,
and serializing it into a `Write` object.
Nothing prevents a user from recording values with different type to the same `column_name`.
In that case, `tantivy-columnar`'s behavior is as follows:
- JsonValues are grouped into 3 types (String, Number, bool).
Values that corresponds to different groups are mapped to different columns. For instance, String values are treated independently
from Number or boolean values. `tantivy-columnar` will simply emit several columns associated to a given column_name.
- Only one column for a given json value type is emitted. If number values with different number types are recorded (e.g. u64, i64, f64),
`tantivy-columnar` will pick the first type that can represents the set of appended value, with the following prioriy order (`i64`, `u64`, `f64`).
`i64` is picked over `u64` as it is likely to yield less change of types. Most use cases strictly requiring `u64` show the
restriction on 50% of the values (e.g. a 64-bit hash). On the other hand, a lot of use cases can show rare negative value.
# Columnar format
This columnar format may have more than one column (with different types) associated to the same `column_name` (see [Coercion rules](#coercion-rules) above).
The `(column_name, columne_type)` couple however uniquely identifies a column.
That couple is serialized as a column `column_key`. The format of that key is:
`[column_name][ZERO_BYTE][column_type_header: u8]`
```
COLUMNAR:=
[COLUMNAR_DATA]
[COLUMNAR_KEY_TO_DATA_INDEX]
[COLUMNAR_FOOTER];
# Columns are sorted by their column key.
COLUMNAR_DATA:=
[COLUMN_DATA]+;
COLUMNAR_FOOTER := [RANGE_SSTABLE_BYTES_LEN: 8 bytes little endian]
```
The columnar file starts by the actual column data, concatenated one after the other,
sorted by column key.
A sstable associates
`(column name, column_cardinality, column_type) to range of bytes.
Column name may not contain the zero byte `\0`.
Listing all columns associated to `column_name` can therefore
be done by listing all keys prefixed by
`[column_name][ZERO_BYTE]`
The associated range of bytes refer to a range of bytes
This crate exposes a columnar format for tantivy.
This format is described in README.md
The crate introduces the following concepts.
`Columnar` is an equivalent of a dataframe.
It maps `column_key` to `Column`.
A `Column<T>` asssociates a `RowId` (u32) to any
number of values.
This is made possible by wrapping a `ColumnIndex` and a `ColumnValue` object.
The `ColumnValue<T>` represents a mapping that associates each `RowId` to
exactly one single value.
The `ColumnIndex` then maps each RowId to a set of `RowId` in the
`ColumnValue`.
For optimization, and compression purposes, the `ColumnIndex` has three
possible representation, each for different cardinalities.
- Full
All RowId have exactly one value. The ColumnIndex is the trivial mapping.
- Optional
All RowIds can have at most one value. The ColumnIndex is the trivial mapping `ColumnRowId -> Option<ColumnValueRowId>`.
- Multivalued
All RowIds can have any number of values.
The column index is mapping values to a range.
All these objects are implemented an unit tested independently
in their own module:
- columnar
- column_index
- column_values
- column

129
columnar/benches/bench_u128.rs Normal file
View File

@@ -0,0 +1,129 @@
#![feature(test)]
use std::ops::RangeInclusive;
use std::sync::Arc;
use common::OwnedBytes;
use rand::rngs::StdRng;
use rand::seq::SliceRandom;
use rand::{random, Rng, SeedableRng};
use tantivy_columnar::ColumnValues;
use test::Bencher;
extern crate test;
// TODO does this make sense for IPv6 ?
fn generate_random() -> Vec<u64> {
let mut permutation: Vec<u64> = (0u64..100_000u64)
.map(|el| el + random::<u16>() as u64)
.collect();
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
fn get_u128_column_random() -> Arc<dyn ColumnValues<u128>> {
let permutation = generate_random();
let permutation = permutation.iter().map(|el| *el as u128).collect::<Vec<_>>();
get_u128_column_from_data(&permutation)
}
fn get_u128_column_from_data(data: &[u128]) -> Arc<dyn ColumnValues<u128>> {
let mut out = vec![];
tantivy_columnar::column_values::serialize_column_values_u128(
&(|| data.iter().copied()),
data.len() as u32,
&mut out,
)
.unwrap();
let out = OwnedBytes::new(out);
tantivy_columnar::column_values::open_u128_mapped::<u128>(out).unwrap()
}
const FIFTY_PERCENT_RANGE: RangeInclusive<u64> = 1..=50;
const SINGLE_ITEM: u64 = 90;
const SINGLE_ITEM_RANGE: RangeInclusive<u64> = 90..=90;
const ONE_PERCENT_ITEM_RANGE: RangeInclusive<u64> = 49..=49;
fn get_data_50percent_item() -> Vec<u128> {
let mut rng = StdRng::from_seed([1u8; 32]);
let mut data = vec![];
for _ in 0..300_000 {
let val = rng.gen_range(1..=100);
data.push(val);
}
data.push(SINGLE_ITEM);
data.shuffle(&mut rng);
let data = data.iter().map(|el| *el as u128).collect::<Vec<_>>();
data
}
#[bench]
fn bench_intfastfield_getrange_u128_50percent_hit(b: &mut Bencher) {
let 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(
*FIFTY_PERCENT_RANGE.start() as u128..=*FIFTY_PERCENT_RANGE.end() as u128,
0..data.len() as u32,
&mut positions,
);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u128_single_hit(b: &mut Bencher) {
let 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(
*SINGLE_ITEM_RANGE.start() as u128..=*SINGLE_ITEM_RANGE.end() as u128,
0..data.len() as u32,
&mut positions,
);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u128_hit_all(b: &mut Bencher) {
let 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
});
}
// U128 RANGE END
#[bench]
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_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
});
}

213
columnar/benches/bench_u64.rs Normal file
View File

@@ -0,0 +1,213 @@
#![feature(test)]
extern crate test;
use std::ops::RangeInclusive;
use std::sync::Arc;
use rand::prelude::*;
use tantivy_columnar::column_values::{
serialize_and_load_u64_based_column_values, CodecType, ALL_U64_CODEC_TYPES,
};
use tantivy_columnar::*;
use test::Bencher;
// 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();
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(column: &[u64], codec_type: CodecType) -> Arc<dyn ColumnValues<u64>> {
serialize_and_load_u64_based_column_values(&column, &[codec_type])
}
#[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_bitpacked(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&permutation, CodecType::Bitpacked);
b.iter(|| {
let mut a = 0u64;
for _ in 0..n {
a = column.get_val(a as u32);
}
a
});
}
const FIFTY_PERCENT_RANGE: RangeInclusive<u64> = 1..=50;
const SINGLE_ITEM: u64 = 90;
const SINGLE_ITEM_RANGE: RangeInclusive<u64> = 90..=90;
const ONE_PERCENT_ITEM_RANGE: RangeInclusive<u64> = 49..=49;
fn get_data_50percent_item() -> Vec<u128> {
let mut rng = StdRng::from_seed([1u8; 32]);
let mut data = vec![];
for _ in 0..300_000 {
let val = rng.gen_range(1..=100);
data.push(val);
}
data.push(SINGLE_ITEM);
data.shuffle(&mut rng);
let data = data.iter().map(|el| *el as u128).collect::<Vec<_>>();
data
}
// U64 RANGE START
#[bench]
fn bench_intfastfield_getrange_u64_50percent_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&data, CodecType::Bitpacked);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(
FIFTY_PERCENT_RANGE,
0..data.len() as u32,
&mut positions,
);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u64_1percent_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&data, CodecType::Bitpacked);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(
ONE_PERCENT_ITEM_RANGE,
0..data.len() as u32,
&mut positions,
);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u64_single_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&data, CodecType::Bitpacked);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(SINGLE_ITEM_RANGE, 0..data.len() as u32, &mut positions);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u64_hit_all(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&data, CodecType::Bitpacked);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(0..=u64::MAX, 0..data.len() as u32, &mut positions);
positions
});
}
// U64 RANGE END
#[bench]
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_intfastfield_stride7_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&permutation, CodecType::Bitpacked);
b.iter(|| {
let mut a = 0;
for i in (0..n / 7).map(|val| val * 7) {
a += column.get_val(i as u32);
}
a
});
}
#[bench]
fn bench_intfastfield_scan_all_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&permutation, CodecType::Bitpacked);
let column_ref = column.as_ref();
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 ColumnValues<u64>> = serialize_and_load(&permutation, CodecType::Bitpacked);
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
});
}

45
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# zero to one
* merges with non trivial mapping (deletes / sort)
* emission of the sort mapping.
+ muttivaued range queries restrat frm the beginning all of the time.
* revisit line codec
* removal of all rows of a column in the schema due to deletes
* Plugging JSON
replug examples
# Perf and Size
* re-add ZSTD compression for dictionaries
no systematic monotonic mapping
consider removing multilinear
f32?
adhoc solution for bool?
add metrics helper for aggregate. sum(row_id)
review inline absence/presence
improv perf of select using PDEP
compare with roaring bitmap/elias fano etc etc.
SIMD range? (see blog post)
Add alignment?
Consider another codec to bridge the gap between few and 5k elements
# Cleanup and rationalization
in benchmark, unify percent vs ratio, f32 vs f64.
investigate if should have better errors? io::Error is overused at the moment.
rename rank/select in unit tests
Review the public API via cargo doc
go through TODOs
remove all doc_id occurences -> row_id
use the rank & select naming in unit tests branch.
multi-linear -> blockwise
linear codec -> simply a multiplication for the index column
rename columnar to something more explicit, like column_dictionary or columnar_table
rename fastfield -> column
document changes
rationalization FastFieldValue, HasColumnType
isolate u128_based and uniform naming
# Other
fix enhance column-cli
# Santa claus
autodetect datetime ipaddr, plug customizable tokenizer.

102
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use std::io;
use std::ops::Deref;
use std::sync::Arc;
use sstable::{Dictionary, VoidSSTable};
use crate::column::Column;
use crate::RowId;
/// Dictionary encoded column.
///
/// The column simply gives access to a regular u64-column that, in
/// which the values are term-ordinals.
///
/// These ordinals are ids uniquely identify the bytes that are stored in
/// the column. These ordinals are small, and sorted in the same order
/// as the term_ord_column.
#[derive(Clone)]
pub struct BytesColumn {
pub(crate) dictionary: Arc<Dictionary<VoidSSTable>>,
pub(crate) term_ord_column: Column<u64>,
}
impl BytesColumn {
/// Fills the given `output` buffer with the term associated to the ordinal `ord`.
///
/// Returns `false` if the term does not exist (e.g. `term_ord` is greater or equal to the
/// overll number of terms).
pub fn ord_to_bytes(&self, ord: u64, output: &mut Vec<u8>) -> io::Result<bool> {
self.dictionary.ord_to_term(ord, output)
}
/// Returns the number of rows in the column.
pub fn num_rows(&self) -> RowId {
self.term_ord_column.num_rows()
}
pub fn term_ords(&self, row_id: RowId) -> impl Iterator<Item = u64> + '_ {
self.term_ord_column.values(row_id)
}
/// Returns the column of ordinals
pub fn ords(&self) -> &Column<u64> {
&self.term_ord_column
}
pub fn num_terms(&self) -> usize {
self.dictionary.num_terms()
}
pub fn dictionary(&self) -> &Dictionary<VoidSSTable> {
self.dictionary.as_ref()
}
}
#[derive(Clone)]
pub struct StrColumn(BytesColumn);
impl From<BytesColumn> for StrColumn {
fn from(bytes_col: BytesColumn) -> Self {
StrColumn(bytes_col)
}
}
impl From<StrColumn> for BytesColumn {
fn from(str_column: StrColumn) -> BytesColumn {
str_column.0
}
}
impl StrColumn {
pub fn dictionary(&self) -> &Dictionary<VoidSSTable> {
self.0.dictionary.as_ref()
}
/// Fills the buffer
pub fn ord_to_str(&self, term_ord: u64, output: &mut String) -> io::Result<bool> {
unsafe {
let buf = output.as_mut_vec();
if !self.0.dictionary.ord_to_term(term_ord, buf)? {
return Ok(false);
}
// TODO consider remove checks if it hurts performance.
if std::str::from_utf8(buf.as_slice()).is_err() {
buf.clear();
return Err(io::Error::new(
io::ErrorKind::InvalidData,
"Not valid utf-8",
));
}
}
Ok(true)
}
}
impl Deref for StrColumn {
type Target = BytesColumn;
fn deref(&self) -> &Self::Target {
&self.0
}
}

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mod dictionary_encoded;
mod serialize;
use std::fmt::Debug;
use std::io::Write;
use std::ops::Deref;
use std::sync::Arc;
use common::BinarySerializable;
pub use dictionary_encoded::{BytesColumn, StrColumn};
pub use serialize::{
open_column_bytes, open_column_u128, open_column_u64, serialize_column_mappable_to_u128,
serialize_column_mappable_to_u64,
};
use crate::column_index::ColumnIndex;
use crate::column_values::monotonic_mapping::StrictlyMonotonicMappingToInternal;
use crate::column_values::{monotonic_map_column, ColumnValues};
use crate::{Cardinality, MonotonicallyMappableToU64, RowId};
#[derive(Clone)]
pub struct Column<T = u64> {
pub idx: ColumnIndex,
pub values: Arc<dyn ColumnValues<T>>,
}
impl<T: MonotonicallyMappableToU64> Column<T> {
pub fn to_u64_monotonic(self) -> Column<u64> {
let values = Arc::new(monotonic_map_column(
self.values,
StrictlyMonotonicMappingToInternal::<T>::new(),
));
Column {
idx: self.idx,
values,
}
}
}
impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
pub fn get_cardinality(&self) -> Cardinality {
self.idx.get_cardinality()
}
pub fn num_rows(&self) -> RowId {
match &self.idx {
ColumnIndex::Full => self.values.num_vals() as u32,
ColumnIndex::Optional(optional_index) => optional_index.num_rows(),
ColumnIndex::Multivalued(col_index) => {
// The multivalued index contains all value start row_id,
// and one extra value at the end with the overall number of rows.
col_index.num_rows()
}
}
}
pub fn min_value(&self) -> T {
self.values.min_value()
}
pub fn max_value(&self) -> T {
self.values.max_value()
}
pub fn first(&self, row_id: RowId) -> Option<T> {
self.values(row_id).next()
}
pub fn values(&self, row_id: RowId) -> impl Iterator<Item = T> + '_ {
self.value_row_ids(row_id)
.map(|value_row_id: RowId| self.values.get_val(value_row_id))
}
pub fn first_or_default_col(self, default_value: T) -> Arc<dyn ColumnValues<T>> {
Arc::new(FirstValueWithDefault {
column: self,
default_value,
})
}
}
impl<T> Deref for Column<T> {
type Target = ColumnIndex;
fn deref(&self) -> &Self::Target {
&self.idx
}
}
impl BinarySerializable for Cardinality {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> std::io::Result<()> {
self.to_code().serialize(writer)
}
fn deserialize<R: std::io::Read>(reader: &mut R) -> std::io::Result<Self> {
let cardinality_code = u8::deserialize(reader)?;
let cardinality = Cardinality::try_from_code(cardinality_code)?;
Ok(cardinality)
}
}
// TODO simplify or optimize
struct FirstValueWithDefault<T: Copy> {
column: Column<T>,
default_value: T,
}
impl<T: PartialOrd + Debug + Send + Sync + Copy + 'static> ColumnValues<T>
for FirstValueWithDefault<T>
{
fn get_val(&self, idx: u32) -> T {
self.column.first(idx).unwrap_or(self.default_value)
}
fn min_value(&self) -> T {
self.column.values.min_value()
}
fn max_value(&self) -> T {
self.column.values.max_value()
}
fn num_vals(&self) -> u32 {
match &self.column.idx {
ColumnIndex::Full => self.column.values.num_vals(),
ColumnIndex::Optional(optional_idx) => optional_idx.num_rows(),
ColumnIndex::Multivalued(_) => todo!(),
}
}
}

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use std::fmt::Debug;
use std::io;
use std::io::Write;
use std::sync::Arc;
use common::OwnedBytes;
use sstable::Dictionary;
use crate::column::{BytesColumn, Column};
use crate::column_index::{serialize_column_index, SerializableColumnIndex};
use crate::column_values::serialize::serialize_column_values_u128;
use crate::column_values::u64_based::{serialize_u64_based_column_values, CodecType};
use crate::column_values::{MonotonicallyMappableToU128, MonotonicallyMappableToU64};
use crate::iterable::Iterable;
pub fn serialize_column_mappable_to_u128<T: MonotonicallyMappableToU128>(
column_index: SerializableColumnIndex<'_>,
iterable: &dyn Iterable<T>,
num_vals: u32,
output: &mut impl Write,
) -> io::Result<()> {
let column_index_num_bytes = serialize_column_index(column_index, output)?;
serialize_column_values_u128(iterable, num_vals, output)?;
output.write_all(&column_index_num_bytes.to_le_bytes())?;
Ok(())
}
pub fn serialize_column_mappable_to_u64<T: MonotonicallyMappableToU64 + Debug>(
column_index: SerializableColumnIndex<'_>,
column_values: &impl Iterable<T>,
output: &mut impl Write,
) -> io::Result<()> {
let column_index_num_bytes = serialize_column_index(column_index, output)?;
serialize_u64_based_column_values(
column_values,
&[CodecType::Bitpacked, CodecType::BlockwiseLinear],
output,
)?;
output.write_all(&column_index_num_bytes.to_le_bytes())?;
Ok(())
}
pub fn open_column_u64<T: MonotonicallyMappableToU64>(bytes: OwnedBytes) -> io::Result<Column<T>> {
let (body, column_index_num_bytes_payload) = bytes.rsplit(4);
let column_index_num_bytes = u32::from_le_bytes(
column_index_num_bytes_payload
.as_slice()
.try_into()
.unwrap(),
);
let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
let column_index = crate::column_index::open_column_index(column_index_data)?;
let column_values =
crate::column_values::u64_based::load_u64_based_column_values(column_values_data)?;
Ok(Column {
idx: column_index,
values: column_values,
})
}
pub fn open_column_u128<T: MonotonicallyMappableToU128>(
bytes: OwnedBytes,
) -> io::Result<Column<T>> {
let (body, column_index_num_bytes_payload) = bytes.rsplit(4);
let column_index_num_bytes = u32::from_le_bytes(
column_index_num_bytes_payload
.as_slice()
.try_into()
.unwrap(),
);
let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
let column_index = crate::column_index::open_column_index(column_index_data)?;
let column_values = crate::column_values::open_u128_mapped(column_values_data)?;
Ok(Column {
idx: column_index,
values: column_values,
})
}
pub fn open_column_bytes<T: From<BytesColumn>>(data: OwnedBytes) -> io::Result<T> {
let (body, dictionary_len_bytes) = data.rsplit(4);
let dictionary_len = u32::from_le_bytes(dictionary_len_bytes.as_slice().try_into().unwrap());
let (dictionary_bytes, column_bytes) = body.split(dictionary_len as usize);
let dictionary = Arc::new(Dictionary::from_bytes(dictionary_bytes)?);
let term_ord_column = crate::column::open_column_u64::<u64>(column_bytes)?;
let bytes_column = BytesColumn {
dictionary,
term_ord_column,
};
Ok(bytes_column.into())
}

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use std::iter;
use crate::column_index::{
multivalued_index, serialize_column_index, SerializableColumnIndex, Set,
};
use crate::iterable::Iterable;
use crate::{Cardinality, ColumnIndex, MergeRowOrder, RowId, StackMergeOrder};
fn detect_cardinality(columns: &[Option<ColumnIndex>]) -> Cardinality {
columns
.iter()
.flatten()
.map(ColumnIndex::get_cardinality)
.max()
.unwrap_or(Cardinality::Full)
}
pub fn stack_column_index<'a>(
columns: &'a [Option<ColumnIndex>],
merge_row_order: &'a MergeRowOrder,
) -> SerializableColumnIndex<'a> {
let MergeRowOrder::Stack(stack_merge_order) = merge_row_order else {
panic!("only supporting stacking at the moment.");
};
let cardinality = detect_cardinality(columns);
match cardinality {
Cardinality::Full => SerializableColumnIndex::Full,
Cardinality::Optional => SerializableColumnIndex::Optional {
non_null_row_ids: Box::new(StackedOptionalIndex {
columns,
stack_merge_order,
}),
num_rows: stack_merge_order.num_rows(),
},
Cardinality::Multivalued => {
let stacked_multivalued_index = StackedMultivaluedIndex {
columns,
stack_merge_order,
};
SerializableColumnIndex::Multivalued(Box::new(stacked_multivalued_index))
}
}
}
struct StackedOptionalIndex<'a> {
columns: &'a [Option<ColumnIndex>],
stack_merge_order: &'a StackMergeOrder,
}
impl<'a> Iterable<RowId> for StackedOptionalIndex<'a> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = RowId> + 'a> {
Box::new(
self.columns
.iter()
.enumerate()
.flat_map(|(columnar_id, column_index_opt)| {
let columnar_row_range = self.stack_merge_order.columnar_range(columnar_id);
let rows_it: Box<dyn Iterator<Item = RowId>> = match column_index_opt {
Some(ColumnIndex::Full) => Box::new(columnar_row_range),
Some(ColumnIndex::Optional(optional_index)) => Box::new(
optional_index
.iter_rows()
.map(move |row_id: RowId| row_id + columnar_row_range.start),
),
Some(ColumnIndex::Multivalued(_)) => {
panic!("No multivalued index is allowed when stacking column index");
}
None => Box::new(std::iter::empty()),
};
rows_it
}),
)
}
}
#[derive(Clone, Copy)]
struct StackedMultivaluedIndex<'a> {
columns: &'a [Option<ColumnIndex>],
stack_merge_order: &'a StackMergeOrder,
}
fn convert_column_opt_to_multivalued_index<'a>(
column_index_opt: Option<&'a ColumnIndex>,
num_rows: RowId,
) -> Box<dyn Iterator<Item = RowId> + 'a> {
match column_index_opt {
None => Box::new(iter::repeat(0u32).take(num_rows as usize + 1)),
Some(ColumnIndex::Full) => Box::new(0..num_rows + 1),
Some(ColumnIndex::Optional(optional_index)) => {
Box::new(
(0..num_rows)
// TODO optimize
.map(|row_id| optional_index.rank(row_id))
.chain(std::iter::once(optional_index.num_non_nulls())),
)
}
Some(ColumnIndex::Multivalued(multivalued_index)) => {
multivalued_index.start_index_column.iter()
}
}
}
impl<'a> Iterable<RowId> for StackedMultivaluedIndex<'a> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = RowId> + '_> {
let multivalued_indexes =
self.columns
.iter()
.map(Option::as_ref)
.enumerate()
.map(|(columnar_id, column_opt)| {
let num_rows =
self.stack_merge_order.columnar_range(columnar_id).len() as RowId;
convert_column_opt_to_multivalued_index(column_opt, num_rows)
});
stack_multivalued_indexes(multivalued_indexes)
}
}
// Refactor me
fn stack_multivalued_indexes<'a>(
mut multivalued_indexes: impl Iterator<Item = Box<dyn Iterator<Item = RowId> + 'a>> + 'a,
) -> Box<dyn Iterator<Item = RowId> + 'a> {
let mut offset = 0;
let mut last_row_id = 0;
let mut current_it = multivalued_indexes.next();
Box::new(std::iter::from_fn(move || loop {
let Some(multivalued_index) = current_it.as_mut() else {
return None;
};
if let Some(row_id) = multivalued_index.next() {
last_row_id = offset + row_id;
return Some(last_row_id);
}
offset = last_row_id;
loop {
current_it = multivalued_indexes.next();
if current_it.as_mut()?.next().is_some() {
break;
}
}
}))
}
fn stack_multivalued_index<'a>(
columns: &'a [Option<ColumnIndex>],
stack_merge_order: &StackMergeOrder,
) -> Box<dyn Iterable<RowId> + 'a> {
todo!()
}
#[cfg(test)]
mod tests {
use crate::RowId;
fn it<'a>(row_ids: &'a [RowId]) -> Box<dyn Iterator<Item = RowId> + 'a> {
Box::new(row_ids.iter().copied())
}
#[test]
fn test_stack() {
let columns = [
it(&[0u32, 0u32]),
it(&[0u32, 1u32, 1u32, 4u32]),
it(&[0u32, 3u32, 5u32]),
it(&[0u32, 4u32]),
]
.into_iter();
let start_offsets: Vec<RowId> = super::stack_multivalued_indexes(columns).collect();
assert_eq!(start_offsets, &[0, 0, 1, 1, 4, 7, 9, 13]);
}
}

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mod merge;
mod multivalued_index;
mod optional_index;
mod serialize;
use std::ops::Range;
pub use merge::stack_column_index;
pub use optional_index::{OptionalIndex, Set};
pub use serialize::{open_column_index, serialize_column_index, SerializableColumnIndex};
use crate::column_index::multivalued_index::MultiValueIndex;
use crate::{Cardinality, RowId};
#[derive(Clone)]
pub enum ColumnIndex {
Full,
Optional(OptionalIndex),
/// In addition, at index num_rows, an extra value is added
/// containing the overal number of values.
Multivalued(MultiValueIndex),
}
impl ColumnIndex {
pub fn get_cardinality(&self) -> Cardinality {
match self {
ColumnIndex::Full => Cardinality::Full,
ColumnIndex::Optional(_) => Cardinality::Optional,
ColumnIndex::Multivalued(_) => Cardinality::Multivalued,
}
}
pub fn value_row_ids(&self, row_id: RowId) -> Range<RowId> {
match self {
ColumnIndex::Full => row_id..row_id + 1,
ColumnIndex::Optional(optional_index) => {
if let Some(val) = optional_index.rank_if_exists(row_id) {
val..val + 1
} else {
0..0
}
}
ColumnIndex::Multivalued(multivalued_index) => multivalued_index.range(row_id),
}
}
pub fn select_batch_in_place(&self, rank_ids: &mut Vec<RowId>) {
match self {
ColumnIndex::Full => {
// No need to do anything:
// value_idx and row_idx are the same.
}
ColumnIndex::Optional(optional_index) => {
optional_index.select_batch(&mut rank_ids[..]);
}
ColumnIndex::Multivalued(multivalued_index) => {
// TODO important: avoid using 0u32, and restart from the beginning all of the time.
multivalued_index.select_batch_in_place(0u32, rank_ids)
}
}
}
}

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use std::io;
use std::io::Write;
use std::ops::Range;
use std::sync::Arc;
use common::OwnedBytes;
use crate::column_values::u64_based::CodecType;
use crate::column_values::ColumnValues;
use crate::iterable::Iterable;
use crate::RowId;
pub fn serialize_multivalued_index(
multivalued_index: &dyn Iterable<RowId>,
output: &mut impl Write,
) -> io::Result<()> {
crate::column_values::u64_based::serialize_u64_based_column_values(
multivalued_index,
&[CodecType::Bitpacked, CodecType::Linear],
output,
)?;
Ok(())
}
pub fn open_multivalued_index(bytes: OwnedBytes) -> io::Result<MultiValueIndex> {
let start_index_column: Arc<dyn ColumnValues<RowId>> =
crate::column_values::u64_based::load_u64_based_column_values(bytes)?;
Ok(MultiValueIndex { start_index_column })
}
#[derive(Clone)]
/// Index to resolve value range for given doc_id.
/// Starts at 0.
pub struct MultiValueIndex {
pub start_index_column: Arc<dyn crate::ColumnValues<RowId>>,
}
impl From<Arc<dyn ColumnValues<RowId>>> for MultiValueIndex {
fn from(start_index_column: Arc<dyn ColumnValues<RowId>>) -> Self {
MultiValueIndex { start_index_column }
}
}
impl MultiValueIndex {
/// Returns `[start, end)`, such that the values associated with
/// the given document are `start..end`.
#[inline]
pub(crate) fn range(&self, row_id: RowId) -> Range<RowId> {
let start = self.start_index_column.get_val(row_id);
let end = self.start_index_column.get_val(row_id + 1);
start..end
}
/// Returns the number of documents in the index.
#[inline]
pub fn num_rows(&self) -> u32 {
self.start_index_column.num_vals() - 1
}
/// Converts a list of ranks (row ids of values) in a 1:n index to the corresponding list of
/// row_ids. 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.
#[allow(clippy::bool_to_int_with_if)]
pub(crate) fn select_batch_in_place(&self, row_start: RowId, ranks: &mut Vec<u32>) {
if ranks.is_empty() {
return;
}
let mut cur_doc = row_start;
let mut last_doc = None;
assert!(self.start_index_column.get_val(row_start) as u32 <= ranks[0]);
let mut write_doc_pos = 0;
for i in 0..ranks.len() {
let pos = ranks[i];
loop {
let end = self.start_index_column.get_val(cur_doc + 1) as u32;
if end > pos {
ranks[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;
}
}
ranks.truncate(write_doc_pos);
}
}
#[cfg(test)]
mod tests {
use std::ops::Range;
use std::sync::Arc;
use super::MultiValueIndex;
use crate::column_values::IterColumn;
use crate::{ColumnValues, RowId};
fn index_to_pos_helper(
index: &MultiValueIndex,
doc_id_range: Range<u32>,
positions: &[u32],
) -> Vec<u32> {
let mut positions = positions.to_vec();
index.select_batch_in_place(doc_id_range.start, &mut positions);
positions
}
#[test]
fn test_positions_to_docid() {
let offsets: Vec<RowId> = vec![0, 10, 12, 15, 22, 23]; // docid values are [0..10, 10..12, 12..15, etc.]
let column: Arc<dyn ColumnValues<RowId>> = Arc::new(IterColumn::from(offsets.into_iter()));
let index = MultiValueIndex::from(column);
assert_eq!(index.num_rows(), 5);
let positions = &[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]);
}
}

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use std::io::{self, Write};
use std::sync::Arc;
mod set;
mod set_block;
use common::{BinarySerializable, OwnedBytes, VInt};
pub use set::{SelectCursor, Set, SetCodec};
use set_block::{
DenseBlock, DenseBlockCodec, SparseBlock, SparseBlockCodec, DENSE_BLOCK_NUM_BYTES,
};
use crate::iterable::Iterable;
use crate::{InvalidData, RowId};
/// The threshold for for number of elements after which we switch to dense block encoding.
///
/// We simply pick the value that minimize the size of the blocks.
const DENSE_BLOCK_THRESHOLD: u32 =
set_block::DENSE_BLOCK_NUM_BYTES / std::mem::size_of::<u16>() as u32; //< 5_120
const ELEMENTS_PER_BLOCK: u32 = u16::MAX as u32 + 1;
const BLOCK_SIZE: RowId = 1 << 16;
#[derive(Copy, Clone, Debug)]
struct BlockMeta {
non_null_rows_before_block: u32,
start_byte_offset: u32,
block_variant: BlockVariant,
}
#[derive(Clone, Copy, Debug)]
enum BlockVariant {
Dense,
Sparse { num_vals: u16 },
}
impl BlockVariant {
pub fn empty() -> Self {
Self::Sparse { num_vals: 0 }
}
pub fn num_bytes_in_block(&self) -> u32 {
match *self {
BlockVariant::Dense => set_block::DENSE_BLOCK_NUM_BYTES,
BlockVariant::Sparse { num_vals } => num_vals as u32 * 2,
}
}
}
/// This codec is inspired by roaring bitmaps.
/// In the dense blocks, however, in order to accelerate `select`
/// we interleave an offset over two bytes. (more on this lower)
///
/// The lower 16 bits of doc ids are stored as u16 while the upper 16 bits are given by the block
/// id. Each block contains 1<<16 docids.
///
/// # Serialized Data Layout
/// The data starts with the block data. Each block is either dense or sparse encoded, depending on
/// the number of values in the block. A block is sparse when it contains less than
/// DENSE_BLOCK_THRESHOLD (6144) values.
/// [Sparse data block | dense data block, .. #repeat*; Desc: Either a sparse or dense encoded
/// block]
/// ### Sparse block data
/// [u16 LE, .. #repeat*; Desc: Positions with values in a block]
/// ### Dense block data
/// [Dense codec for the whole block; Desc: Similar to a bitvec(0..ELEMENTS_PER_BLOCK) + Metadata
/// for faster lookups. See dense.rs]
///
/// The data is followed by block metadata, to know which area of the raw block data belongs to
/// which block. Only metadata for blocks with elements is recorded to
/// keep the overhead low for scenarios with many very sparse columns. The block metadata consists
/// of the block index and the number of values in the block. Since we don't store empty blocks
/// num_vals is incremented by 1, e.g. 0 means 1 value.
///
/// The last u16 is storing the number of metadata blocks.
/// [u16 LE, .. #repeat*; Desc: Positions with values in a block][(u16 LE, u16 LE), .. #repeat*;
/// Desc: (Block Id u16, Num Elements u16)][u16 LE; Desc: num blocks with values u16]
///
/// # Opening
/// When opening the data layout, the data is expanded to `Vec<SparseCodecBlockVariant>`, where the
/// index is the block index. For each block `byte_start` and `offset` is computed.
#[derive(Clone)]
pub struct OptionalIndex {
num_rows: RowId,
num_non_null_rows: RowId,
block_data: OwnedBytes,
block_metas: Arc<[BlockMeta]>,
}
impl OptionalIndex {
pub fn num_rows(&self) -> RowId {
self.num_rows
}
pub fn num_non_nulls(&self) -> RowId {
self.num_non_null_rows
}
pub fn iter_rows<'a>(&'a self) -> impl Iterator<Item = RowId> + 'a {
// TODO optimize
let mut select_batch = self.select_cursor();
(0..self.num_non_null_rows).map(move |rank| select_batch.select(rank))
}
}
/// Splits a value address into lower and upper 16bits.
/// The lower 16 bits are the value in the block
/// The upper 16 bits are the block index
#[derive(Copy, Debug, Clone)]
struct RowAddr {
block_id: u16,
in_block_row_id: u16,
}
#[inline(always)]
fn row_addr_from_row_id(row_id: RowId) -> RowAddr {
RowAddr {
block_id: (row_id / BLOCK_SIZE) as u16,
in_block_row_id: (row_id % BLOCK_SIZE) as u16,
}
}
enum BlockSelectCursor<'a> {
Dense(<DenseBlock<'a> as Set<u16>>::SelectCursor<'a>),
Sparse(<SparseBlock<'a> as Set<u16>>::SelectCursor<'a>),
}
impl<'a> BlockSelectCursor<'a> {
fn select(&mut self, rank: u16) -> u16 {
match self {
BlockSelectCursor::Dense(dense_select_cursor) => dense_select_cursor.select(rank),
BlockSelectCursor::Sparse(sparse_select_cursor) => sparse_select_cursor.select(rank),
}
}
}
pub struct OptionalIndexSelectCursor<'a> {
current_block_cursor: BlockSelectCursor<'a>,
current_block_id: u16,
// The current block is guaranteed to contain ranks < end_rank.
current_block_end_rank: RowId,
optional_index: &'a OptionalIndex,
block_doc_idx_start: RowId,
num_null_rows_before_block: RowId,
}
impl<'a> OptionalIndexSelectCursor<'a> {
fn search_and_load_block(&mut self, rank: RowId) {
if rank < self.current_block_end_rank {
// we are already in the right block
return;
}
self.current_block_id = self.optional_index.find_block(rank, self.current_block_id);
self.current_block_end_rank = self
.optional_index
.block_metas
.get(self.current_block_id as usize + 1)
.map(|block_meta| block_meta.non_null_rows_before_block)
.unwrap_or(u32::MAX);
self.block_doc_idx_start = (self.current_block_id as u32) * ELEMENTS_PER_BLOCK;
let block_meta = self.optional_index.block_metas[self.current_block_id as usize];
self.num_null_rows_before_block = block_meta.non_null_rows_before_block;
let block: Block<'_> = self.optional_index.block(block_meta);
self.current_block_cursor = match block {
Block::Dense(dense_block) => BlockSelectCursor::Dense(dense_block.select_cursor()),
Block::Sparse(sparse_block) => BlockSelectCursor::Sparse(sparse_block.select_cursor()),
};
}
}
impl<'a> SelectCursor<RowId> for OptionalIndexSelectCursor<'a> {
fn select(&mut self, rank: RowId) -> RowId {
self.search_and_load_block(rank);
let index_in_block = (rank - self.num_null_rows_before_block) as u16;
self.current_block_cursor.select(index_in_block) as RowId + self.block_doc_idx_start
}
}
impl Set<RowId> for OptionalIndex {
type SelectCursor<'b> = OptionalIndexSelectCursor<'b> where Self: 'b;
// Check if value at position is not null.
#[inline]
fn contains(&self, row_id: RowId) -> bool {
let RowAddr {
block_id,
in_block_row_id,
} = row_addr_from_row_id(row_id);
let block_meta = self.block_metas[block_id as usize];
match self.block(block_meta) {
Block::Dense(dense_block) => dense_block.contains(in_block_row_id),
Block::Sparse(sparse_block) => sparse_block.contains(in_block_row_id),
}
}
#[inline]
fn rank(&self, row_id: RowId) -> RowId {
let RowAddr {
block_id,
in_block_row_id,
} = row_addr_from_row_id(row_id);
let block_meta = self.block_metas[block_id as usize];
let block = self.block(block_meta);
let block_offset_row_id = match block {
Block::Dense(dense_block) => dense_block.rank(in_block_row_id),
Block::Sparse(sparse_block) => sparse_block.rank(in_block_row_id),
} as u32;
block_meta.non_null_rows_before_block + block_offset_row_id
}
#[inline]
fn rank_if_exists(&self, row_id: RowId) -> Option<RowId> {
let RowAddr {
block_id,
in_block_row_id,
} = row_addr_from_row_id(row_id);
let block_meta = self.block_metas[block_id as usize];
let block = self.block(block_meta);
let block_offset_row_id = match block {
Block::Dense(dense_block) => dense_block.rank_if_exists(in_block_row_id),
Block::Sparse(sparse_block) => sparse_block.rank_if_exists(in_block_row_id),
}? as u32;
Some(block_meta.non_null_rows_before_block + block_offset_row_id)
}
#[inline]
fn select(&self, rank: RowId) -> RowId {
let block_pos = self.find_block(rank, 0);
let block_doc_idx_start = (block_pos as u32) * ELEMENTS_PER_BLOCK;
let block_meta = self.block_metas[block_pos as usize];
let block: Block<'_> = self.block(block_meta);
let index_in_block = (rank - block_meta.non_null_rows_before_block) as u16;
let in_block_rank = match block {
Block::Dense(dense_block) => dense_block.select(index_in_block),
Block::Sparse(sparse_block) => sparse_block.select(index_in_block),
};
block_doc_idx_start + in_block_rank as u32
}
fn select_cursor<'b>(&'b self) -> OptionalIndexSelectCursor<'b> {
OptionalIndexSelectCursor {
current_block_cursor: BlockSelectCursor::Sparse(
SparseBlockCodec::open(b"").select_cursor(),
),
current_block_id: 0u16,
current_block_end_rank: 0u32, //< this is sufficient to force the first load
optional_index: self,
block_doc_idx_start: 0u32,
num_null_rows_before_block: 0u32,
}
}
}
impl OptionalIndex {
pub fn select_batch(&self, ranks: &mut [RowId]) {
let mut select_cursor = self.select_cursor();
for rank in ranks.iter_mut() {
*rank = select_cursor.select(*rank);
}
}
#[inline]
fn block<'a>(&'a self, block_meta: BlockMeta) -> Block<'a> {
let BlockMeta {
start_byte_offset,
block_variant,
..
} = block_meta;
let start_byte_offset = start_byte_offset as usize;
let bytes = self.block_data.as_slice();
match block_variant {
BlockVariant::Dense => Block::Dense(DenseBlockCodec::open(
&bytes[start_byte_offset..start_byte_offset + DENSE_BLOCK_NUM_BYTES as usize],
)),
BlockVariant::Sparse { num_vals } => {
let end_byte_offset = start_byte_offset + num_vals as usize * 2;
let sparse_bytes = &bytes[start_byte_offset..end_byte_offset];
Block::Sparse(SparseBlockCodec::open(sparse_bytes))
}
}
}
#[inline]
fn find_block(&self, dense_idx: u32, start_block_pos: u16) -> u16 {
for block_pos in start_block_pos..self.block_metas.len() as u16 {
let offset = self.block_metas[block_pos as usize].non_null_rows_before_block;
if offset > dense_idx {
return block_pos - 1u16;
}
}
self.block_metas.len() as u16 - 1u16
}
// TODO Add a good API for the codec_idx to original_idx translation.
// The Iterator API is a probably a bad idea
}
#[derive(Copy, Clone)]
enum Block<'a> {
Dense(DenseBlock<'a>),
Sparse(SparseBlock<'a>),
}
#[derive(Debug, Copy, Clone)]
enum OptionalIndexCodec {
Dense = 0,
Sparse = 1,
}
impl OptionalIndexCodec {
fn to_code(self) -> u8 {
self as u8
}
fn try_from_code(code: u8) -> Result<Self, InvalidData> {
match code {
0 => Ok(Self::Dense),
1 => Ok(Self::Sparse),
_ => Err(InvalidData),
}
}
}
impl BinarySerializable for OptionalIndexCodec {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
writer.write_all(&[self.to_code()])
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let optional_codec_code = u8::deserialize(reader)?;
let optional_codec = Self::try_from_code(optional_codec_code)?;
Ok(optional_codec)
}
}
fn serialize_optional_index_block(block_els: &[u16], out: &mut impl io::Write) -> io::Result<()> {
let is_sparse = is_sparse(block_els.len() as u32);
if is_sparse {
SparseBlockCodec::serialize(block_els.iter().copied(), out)?;
} else {
DenseBlockCodec::serialize(block_els.iter().copied(), out)?;
}
Ok(())
}
pub fn serialize_optional_index<'a, W: io::Write>(
non_null_rows: &dyn Iterable<RowId>,
num_rows: RowId,
output: &mut W,
) -> io::Result<()> {
VInt(num_rows as u64).serialize(output)?;
let mut rows_it = non_null_rows.boxed_iter();
let mut block_metadata: Vec<SerializedBlockMeta> = Vec::new();
let mut current_block = Vec::new();
// This if-statement for the first element ensures that
// `block_metadata` is not empty in the loop below.
let Some(idx) = rows_it.next() else {
output.write_all(&0u16.to_le_bytes())?;
return Ok(());
};
let row_addr = row_addr_from_row_id(idx);
let mut current_block_id = row_addr.block_id;
current_block.push(row_addr.in_block_row_id);
for idx in rows_it {
let value_addr = row_addr_from_row_id(idx);
if current_block_id != value_addr.block_id {
serialize_optional_index_block(&current_block[..], output)?;
block_metadata.push(SerializedBlockMeta {
block_id: current_block_id,
num_non_null_rows: current_block.len() as u32,
});
current_block.clear();
current_block_id = value_addr.block_id;
}
current_block.push(value_addr.in_block_row_id);
}
// handle last block
serialize_optional_index_block(&current_block[..], output)?;
block_metadata.push(SerializedBlockMeta {
block_id: current_block_id,
num_non_null_rows: current_block.len() as u32,
});
for block in &block_metadata {
output.write_all(&block.to_bytes())?;
}
output.write_all((block_metadata.len() as u16).to_le_bytes().as_ref())?;
Ok(())
}
const SERIALIZED_BLOCK_META_NUM_BYTES: usize = 4;
#[derive(Clone, Copy, Debug)]
struct SerializedBlockMeta {
block_id: u16,
num_non_null_rows: u32, //< takes values in 1..=u16::MAX
}
// TODO unit tests
impl SerializedBlockMeta {
#[inline]
fn from_bytes(bytes: [u8; SERIALIZED_BLOCK_META_NUM_BYTES]) -> SerializedBlockMeta {
let block_id = u16::from_le_bytes(bytes[0..2].try_into().unwrap());
let num_non_null_rows: u32 =
u16::from_le_bytes(bytes[2..4].try_into().unwrap()) as u32 + 1u32;
SerializedBlockMeta {
block_id,
num_non_null_rows,
}
}
#[inline]
fn to_bytes(&self) -> [u8; SERIALIZED_BLOCK_META_NUM_BYTES] {
assert!(self.num_non_null_rows > 0);
let mut bytes = [0u8; SERIALIZED_BLOCK_META_NUM_BYTES];
bytes[0..2].copy_from_slice(&self.block_id.to_le_bytes());
// We don't store empty blocks, therefore we can subtract 1.
// This way we will be able to use u16 when the number of elements is 1 << 16 or u16::MAX+1
bytes[2..4].copy_from_slice(&((self.num_non_null_rows - 1u32) as u16).to_le_bytes());
bytes
}
}
#[inline]
fn is_sparse(num_rows_in_block: u32) -> bool {
num_rows_in_block < DENSE_BLOCK_THRESHOLD as u32
}
fn deserialize_optional_index_block_metadatas(
data: &[u8],
num_rows: u32,
) -> (Box<[BlockMeta]>, u32) {
let num_blocks = data.len() / SERIALIZED_BLOCK_META_NUM_BYTES;
let mut block_metas = Vec::with_capacity(num_blocks as usize + 1);
let mut start_byte_offset = 0;
let mut non_null_rows_before_block = 0;
for block_meta_bytes in data.chunks_exact(SERIALIZED_BLOCK_META_NUM_BYTES) {
let block_meta_bytes: [u8; SERIALIZED_BLOCK_META_NUM_BYTES] =
block_meta_bytes.try_into().unwrap();
let SerializedBlockMeta {
block_id,
num_non_null_rows,
} = SerializedBlockMeta::from_bytes(block_meta_bytes);
block_metas.resize(
block_id as usize,
BlockMeta {
non_null_rows_before_block,
start_byte_offset,
block_variant: BlockVariant::empty(),
},
);
let block_variant = if is_sparse(num_non_null_rows) {
BlockVariant::Sparse {
num_vals: num_non_null_rows as u16,
}
} else {
BlockVariant::Dense
};
block_metas.push(BlockMeta {
non_null_rows_before_block,
start_byte_offset,
block_variant,
});
start_byte_offset += block_variant.num_bytes_in_block();
non_null_rows_before_block += num_non_null_rows as u32;
}
block_metas.resize(
((num_rows + BLOCK_SIZE - 1) / BLOCK_SIZE) as usize,
BlockMeta {
non_null_rows_before_block,
start_byte_offset,
block_variant: BlockVariant::empty(),
},
);
(block_metas.into_boxed_slice(), non_null_rows_before_block)
}
pub fn open_optional_index(bytes: OwnedBytes) -> io::Result<OptionalIndex> {
let (mut bytes, num_non_empty_blocks_bytes) = bytes.rsplit(2);
let num_non_empty_block_bytes =
u16::from_le_bytes(num_non_empty_blocks_bytes.as_slice().try_into().unwrap());
let num_rows = VInt::deserialize_u64(&mut bytes)? as u32;
let block_metas_num_bytes =
num_non_empty_block_bytes as usize * SERIALIZED_BLOCK_META_NUM_BYTES;
let (block_data, block_metas) = bytes.rsplit(block_metas_num_bytes);
let (block_metas, num_non_null_rows) =
deserialize_optional_index_block_metadatas(block_metas.as_slice(), num_rows).into();
let optional_index = OptionalIndex {
num_rows,
num_non_null_rows,
block_data,
block_metas: block_metas.into(),
};
Ok(optional_index)
}
#[cfg(test)]
mod tests;

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use std::io;
/// A codec makes it possible to serialize a set of
/// elements, and open the resulting Set representation.
pub trait SetCodec {
type Item: Copy + TryFrom<usize> + Eq + std::hash::Hash + std::fmt::Debug;
type Reader<'a>: Set<Self::Item>;
/// Serializes a set of unique sorted u16 elements.
///
/// May panic if the elements are not sorted.
fn serialize(els: impl Iterator<Item = Self::Item>, wrt: impl io::Write) -> io::Result<()>;
fn open<'a>(data: &'a [u8]) -> Self::Reader<'a>;
}
/// Stateful object that makes it possible to compute several select in a row,
/// provided the rank passed as argument are increasing.
pub trait SelectCursor<T> {
// May panic if rank is greater than the number of elements in the Set,
// or if rank is < than value provided in the previous call.
fn select(&mut self, rank: T) -> T;
}
pub trait Set<T> {
type SelectCursor<'b>: SelectCursor<T>
where Self: 'b;
/// Returns true if the elements is contained in the Set
fn contains(&self, el: T) -> bool;
/// Returns the number of rows in the set that are < `el`
fn rank(&self, el: T) -> T;
/// If the set contains `el` returns the element rank.
/// If the set does not contain the element, it returns `None`.
fn rank_if_exists(&self, el: T) -> Option<T>;
/// Return the rank-th value stored in this bitmap.
///
/// # Panics
///
/// May panic if rank is greater than the number of elements in the Set.
fn select(&self, rank: T) -> T;
/// Creates a brand new select cursor.
fn select_cursor<'b>(&'b self) -> Self::SelectCursor<'b>;
}

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use std::convert::TryInto;
use std::io::{self, Write};
use common::BinarySerializable;
use crate::column_index::optional_index::{SelectCursor, Set, SetCodec, ELEMENTS_PER_BLOCK};
#[inline(always)]
fn get_bit_at(input: u64, n: u16) -> bool {
input & (1 << n) != 0
}
#[inline]
fn set_bit_at(input: &mut u64, n: u16) {
*input |= 1 << n;
}
/// For the `DenseCodec`, `data` which contains the encoded blocks.
/// Each block consists of [u8; 12]. The first 8 bytes is a bitvec for 64 elements.
/// The last 4 bytes are the offset, the number of set bits so far.
///
/// When translating the original index to a dense index, the correct block can be computed
/// directly `orig_idx/64`. Inside the block the position is `orig_idx%64`.
///
/// When translating a dense index to the original index, we can use the offset to find the correct
/// block. Direct computation is not possible, but we can employ a linear or binary search.
const ELEMENTS_PER_MINI_BLOCK: u16 = 64;
const MINI_BLOCK_BITVEC_NUM_BYTES: usize = 8;
const MINI_BLOCK_OFFSET_NUM_BYTES: usize = 2;
pub const MINI_BLOCK_NUM_BYTES: usize = MINI_BLOCK_BITVEC_NUM_BYTES + MINI_BLOCK_OFFSET_NUM_BYTES;
/// Number of bytes in a dense block.
pub const DENSE_BLOCK_NUM_BYTES: u32 =
(ELEMENTS_PER_BLOCK as u32 / ELEMENTS_PER_MINI_BLOCK as u32) * MINI_BLOCK_NUM_BYTES as u32;
pub struct DenseBlockCodec;
impl SetCodec for DenseBlockCodec {
type Item = u16;
type Reader<'a> = DenseBlock<'a>;
fn serialize(els: impl Iterator<Item = u16>, wrt: impl io::Write) -> io::Result<()> {
serialize_dense_codec(els, wrt)
}
#[inline]
fn open<'a>(data: &'a [u8]) -> Self::Reader<'a> {
assert_eq!(data.len(), DENSE_BLOCK_NUM_BYTES as usize);
DenseBlock(data)
}
}
/// Interpreting the bitvec as a set of integer within 0..=63
/// and given an element, returns the number of elements in the
/// set lesser than the element.
///
/// # Panics
///
/// May panic or return a wrong result if el <= 64.
#[inline(always)]
fn rank_u64(bitvec: u64, el: u16) -> u16 {
debug_assert!(el < 64);
let mask = (1u64 << el) - 1;
let masked_bitvec = bitvec & mask;
masked_bitvec.count_ones() as u16
}
#[inline(always)]
fn select_u64(mut bitvec: u64, rank: u16) -> u16 {
for _ in 0..rank {
bitvec &= bitvec - 1;
}
bitvec.trailing_zeros() as u16
}
// TODO test the following solution on Intel... on Ryzen Zen <3 it is a catastrophy.
// #[target_feature(enable = "bmi2")]
// unsafe fn select_bitvec_unsafe(bitvec: u64, rank: u16) -> u16 {
// let pdep = _pdep_u64(1u64 << rank, bitvec);
// pdep.trailing_zeros() as u16
// }
#[derive(Clone, Copy, Debug)]
struct DenseMiniBlock {
bitvec: u64,
rank: u16,
}
impl DenseMiniBlock {
fn from_bytes(data: [u8; MINI_BLOCK_NUM_BYTES]) -> Self {
let bitvec = u64::from_le_bytes(data[..MINI_BLOCK_BITVEC_NUM_BYTES].try_into().unwrap());
let rank = u16::from_le_bytes(data[MINI_BLOCK_BITVEC_NUM_BYTES..].try_into().unwrap());
Self { bitvec, rank }
}
fn to_bytes(&self) -> [u8; MINI_BLOCK_NUM_BYTES] {
let mut bytes = [0u8; MINI_BLOCK_NUM_BYTES];
bytes[..MINI_BLOCK_BITVEC_NUM_BYTES].copy_from_slice(&self.bitvec.to_le_bytes());
bytes[MINI_BLOCK_BITVEC_NUM_BYTES..].copy_from_slice(&self.rank.to_le_bytes());
bytes
}
}
#[derive(Copy, Clone)]
pub struct DenseBlock<'a>(&'a [u8]);
pub struct DenseBlockSelectCursor<'a> {
block_id: u16,
dense_block: DenseBlock<'a>,
}
impl<'a> SelectCursor<u16> for DenseBlockSelectCursor<'a> {
#[inline]
fn select(&mut self, rank: u16) -> u16 {
self.block_id = self
.dense_block
.find_miniblock_containing_rank(rank, self.block_id)
.unwrap();
let index_block = self.dense_block.mini_block(self.block_id);
let in_block_rank = rank - index_block.rank;
self.block_id * ELEMENTS_PER_MINI_BLOCK + select_u64(index_block.bitvec, in_block_rank)
}
}
impl<'a> Set<u16> for DenseBlock<'a> {
type SelectCursor<'b> = DenseBlockSelectCursor<'a> where Self: 'b;
#[inline(always)]
fn contains(&self, el: u16) -> bool {
let mini_block_id = el / ELEMENTS_PER_MINI_BLOCK;
let bitvec = self.mini_block(mini_block_id).bitvec;
let pos_in_bitvec = el % ELEMENTS_PER_MINI_BLOCK;
get_bit_at(bitvec, pos_in_bitvec)
}
#[inline(always)]
fn rank_if_exists(&self, el: u16) -> Option<u16> {
let block_pos = el / ELEMENTS_PER_MINI_BLOCK;
let index_block = self.mini_block(block_pos);
let pos_in_block_bit_vec = el % ELEMENTS_PER_MINI_BLOCK;
let ones_in_block = rank_u64(index_block.bitvec, pos_in_block_bit_vec);
let rank = index_block.rank + ones_in_block;
if get_bit_at(index_block.bitvec, pos_in_block_bit_vec) {
Some(rank)
} else {
None
}
}
#[inline(always)]
fn rank(&self, el: u16) -> u16 {
let block_pos = el / ELEMENTS_PER_MINI_BLOCK;
let index_block = self.mini_block(block_pos);
let pos_in_block_bit_vec = el % ELEMENTS_PER_MINI_BLOCK;
let ones_in_block = rank_u64(index_block.bitvec, pos_in_block_bit_vec);
index_block.rank + ones_in_block
}
#[inline(always)]
fn select(&self, rank: u16) -> u16 {
let block_id = self.find_miniblock_containing_rank(rank, 0).unwrap();
let index_block = self.mini_block(block_id);
let in_block_rank = rank - index_block.rank;
block_id * ELEMENTS_PER_MINI_BLOCK + select_u64(index_block.bitvec, in_block_rank)
}
#[inline(always)]
fn select_cursor<'b>(&'b self) -> Self::SelectCursor<'b> {
DenseBlockSelectCursor {
block_id: 0,
dense_block: *self,
}
}
}
impl<'a> DenseBlock<'a> {
#[inline]
fn mini_block(&self, mini_block_id: u16) -> DenseMiniBlock {
let data_start_pos = mini_block_id as usize * MINI_BLOCK_NUM_BYTES;
DenseMiniBlock::from_bytes(
self.0[data_start_pos..data_start_pos + MINI_BLOCK_NUM_BYTES]
.try_into()
.unwrap(),
)
}
#[inline]
fn iter_miniblocks(
&self,
from_block_id: u16,
) -> impl Iterator<Item = (u16, DenseMiniBlock)> + '_ {
self.0
.chunks_exact(MINI_BLOCK_NUM_BYTES)
.enumerate()
.skip(from_block_id as usize)
.map(|(block_id, bytes)| {
let mini_block = DenseMiniBlock::from_bytes(bytes.try_into().unwrap());
(block_id as u16, mini_block)
})
}
/// Finds the block position containing the dense_idx.
///
/// # Correctness
/// dense_idx needs to be smaller than the number of values in the index
///
/// The last offset number is equal to the number of values in the index.
#[inline]
fn find_miniblock_containing_rank(&self, rank: u16, from_block_id: u16) -> Option<u16> {
self.iter_miniblocks(from_block_id)
.take_while(|(_, block)| block.rank <= rank)
.map(|(block_id, _)| block_id)
.last()
}
}
/// Iterator over all values, true if set, otherwise false
pub fn serialize_dense_codec(
els: impl Iterator<Item = u16>,
mut output: impl Write,
) -> io::Result<()> {
let mut non_null_rows_before: u16 = 0u16;
let mut block = 0u64;
let mut current_block_id = 0u16;
for el in els {
let block_id = el / ELEMENTS_PER_MINI_BLOCK;
let in_offset = el % ELEMENTS_PER_MINI_BLOCK;
while block_id > current_block_id {
let dense_mini_block = DenseMiniBlock {
bitvec: block,
rank: non_null_rows_before as u16,
};
output.write_all(&dense_mini_block.to_bytes())?;
non_null_rows_before += block.count_ones() as u16;
block = 0u64;
current_block_id += 1u16;
}
set_bit_at(&mut block, in_offset);
}
while current_block_id <= u16::MAX / ELEMENTS_PER_MINI_BLOCK {
block.serialize(&mut output)?;
non_null_rows_before.serialize(&mut output)?;
// This will overflow to 0 exactly if all bits are set.
// This is however not problem as we won't use this last value.
non_null_rows_before = non_null_rows_before.wrapping_add(block.count_ones() as u16);
block = 0u64;
current_block_id += 1u16;
}
Ok(())
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_select_bitvec() {
assert_eq!(select_u64(1u64, 0), 0);
assert_eq!(select_u64(2u64, 0), 1);
assert_eq!(select_u64(4u64, 0), 2);
assert_eq!(select_u64(8u64, 0), 3);
assert_eq!(select_u64(1 | 8u64, 0), 0);
assert_eq!(select_u64(1 | 8u64, 1), 3);
}
#[test]
fn test_count_ones() {
for i in 0..=63 {
assert_eq!(rank_u64(u64::MAX, i), i);
}
}
#[test]
fn test_dense() {
assert_eq!(DENSE_BLOCK_NUM_BYTES, 10_240);
}
}

8
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mod dense;
mod sparse;
pub use dense::{DenseBlock, DenseBlockCodec, DENSE_BLOCK_NUM_BYTES};
pub use sparse::{SparseBlock, SparseBlockCodec};
#[cfg(test)]
mod tests;

111
columnar/src/column_index/optional_index/set_block/sparse.rs Normal file
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use crate::column_index::optional_index::{SelectCursor, Set, SetCodec};
pub struct SparseBlockCodec;
impl SetCodec for SparseBlockCodec {
type Item = u16;
type Reader<'a> = SparseBlock<'a>;
fn serialize(
els: impl Iterator<Item = u16>,
mut wrt: impl std::io::Write,
) -> std::io::Result<()> {
for el in els {
wrt.write_all(&el.to_le_bytes())?;
}
Ok(())
}
fn open<'a>(data: &'a [u8]) -> Self::Reader<'a> {
SparseBlock(data)
}
}
#[derive(Copy, Clone)]
pub struct SparseBlock<'a>(&'a [u8]);
impl<'a> SelectCursor<u16> for SparseBlock<'a> {
#[inline]
fn select(&mut self, rank: u16) -> u16 {
<SparseBlock<'a> as Set<u16>>::select(self, rank)
}
}
impl<'a> Set<u16> for SparseBlock<'a> {
type SelectCursor<'b> = Self where Self: 'b;
#[inline(always)]
fn contains(&self, el: u16) -> bool {
self.binary_search(el).is_ok()
}
#[inline(always)]
fn rank_if_exists(&self, el: u16) -> Option<u16> {
self.binary_search(el).ok()
}
#[inline(always)]
fn rank(&self, el: u16) -> u16 {
self.binary_search(el).unwrap_or_else(|el| el)
}
#[inline(always)]
fn select(&self, rank: u16) -> u16 {
let offset = rank as usize * 2;
u16::from_le_bytes(self.0[offset..offset + 2].try_into().unwrap())
}
#[inline(always)]
fn select_cursor<'b>(&'b self) -> Self::SelectCursor<'b> {
*self
}
}
#[inline(always)]
fn get_u16(data: &[u8], byte_position: usize) -> u16 {
let bytes: [u8; 2] = data[byte_position..byte_position + 2].try_into().unwrap();
u16::from_le_bytes(bytes)
}
impl<'a> SparseBlock<'a> {
#[inline(always)]
fn value_at_idx(&self, data: &[u8], idx: u16) -> u16 {
let start_offset: usize = idx as usize * 2;
get_u16(data, start_offset)
}
#[inline]
fn num_vals(&self) -> u16 {
(self.0.len() / 2) as u16
}
#[inline]
#[allow(clippy::comparison_chain)]
// Looks for the element in the block. Returns the positions if found.
fn binary_search(&self, target: u16) -> Result<u16, u16> {
let data = &self.0;
let mut size = self.num_vals();
let mut left = 0;
let mut right = size;
// TODO try different implem.
// e.g. exponential search into binary search
while left < right {
let mid = left + size / 2;
// TODO do boundary check only once, and then use an
// unsafe `value_at_idx`
let mid_val = self.value_at_idx(data, mid);
if target > mid_val {
left = mid + 1;
} else if target < mid_val {
right = mid;
} else {
return Ok(mid);
}
size = right - left;
}
Err(left)
}
}

109
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use std::collections::HashMap;
use crate::column_index::optional_index::set_block::dense::DENSE_BLOCK_NUM_BYTES;
use crate::column_index::optional_index::set_block::{DenseBlockCodec, SparseBlockCodec};
use crate::column_index::optional_index::{SelectCursor, Set, SetCodec};
fn test_set_helper<C: SetCodec<Item = u16>>(vals: &[u16]) -> usize {
let mut buffer = Vec::new();
C::serialize(vals.iter().copied(), &mut buffer).unwrap();
let tested_set = C::open(buffer.as_slice());
let hash_set: HashMap<C::Item, C::Item> = vals
.iter()
.copied()
.enumerate()
.map(|(ord, val)| (val, C::Item::try_from(ord).ok().unwrap()))
.collect();
for val in 0u16..=u16::MAX {
assert_eq!(tested_set.contains(val), hash_set.contains_key(&val));
assert_eq!(tested_set.rank_if_exists(val), hash_set.get(&val).copied());
assert_eq!(
tested_set.rank(val),
vals.iter().cloned().take_while(|v| *v < val).count() as u16
);
}
for rank in 0..vals.len() {
assert_eq!(tested_set.select(rank as u16), vals[rank]);
}
buffer.len()
}
#[test]
fn test_dense_block_set_u16_empty() {
let buffer_len = test_set_helper::<DenseBlockCodec>(&[]);
assert_eq!(buffer_len, DENSE_BLOCK_NUM_BYTES as usize);
}
#[test]
fn test_dense_block_set_u16_max() {
let buffer_len = test_set_helper::<DenseBlockCodec>(&[u16::MAX]);
assert_eq!(buffer_len, DENSE_BLOCK_NUM_BYTES as usize);
}
#[test]
fn test_sparse_block_set_u16_empty() {
let buffer_len = test_set_helper::<SparseBlockCodec>(&[]);
assert_eq!(buffer_len, 0);
}
#[test]
fn test_sparse_block_set_u16_max() {
let buffer_len = test_set_helper::<SparseBlockCodec>(&[u16::MAX]);
assert_eq!(buffer_len, 2);
}
use proptest::prelude::*;
proptest! {
#![proptest_config(ProptestConfig::with_cases(1))]
#[test]
fn test_prop_test_dense(els in proptest::collection::btree_set(0..=u16::MAX, 0..=u16::MAX as usize)) {
let vals: Vec<u16> = els.into_iter().collect();
let buffer_len = test_set_helper::<DenseBlockCodec>(&vals);
assert_eq!(buffer_len, DENSE_BLOCK_NUM_BYTES as usize);
}
#[test]
fn test_prop_test_sparse(els in proptest::collection::btree_set(0..=u16::MAX, 0..=u16::MAX as usize)) {
let vals: Vec<u16> = els.into_iter().collect();
let buffer_len = test_set_helper::<SparseBlockCodec>(&vals);
assert_eq!(buffer_len, vals.len() * 2);
}
}
#[test]
fn test_simple_translate_codec_codec_idx_to_original_idx_dense() {
let mut buffer = Vec::new();
DenseBlockCodec::serialize([1, 3, 17, 32, 30_000, 30_001].iter().copied(), &mut buffer)
.unwrap();
let tested_set = DenseBlockCodec::open(buffer.as_slice());
assert!(tested_set.contains(1));
let mut select_cursor = tested_set.select_cursor();
assert_eq!(select_cursor.select(0), 1);
assert_eq!(select_cursor.select(1), 3);
assert_eq!(select_cursor.select(2), 17);
}
#[test]
fn test_simple_translate_codec_idx_to_original_idx_sparse() {
let mut buffer = Vec::new();
SparseBlockCodec::serialize([1, 3, 17].iter().copied(), &mut buffer).unwrap();
let tested_set = SparseBlockCodec::open(buffer.as_slice());
assert!(tested_set.contains(1));
let mut select_cursor = tested_set.select_cursor();
assert_eq!(SelectCursor::select(&mut select_cursor, 0), 1);
assert_eq!(SelectCursor::select(&mut select_cursor, 1), 3);
assert_eq!(SelectCursor::select(&mut select_cursor, 2), 17);
}
#[test]
fn test_simple_translate_codec_idx_to_original_idx_dense() {
let mut buffer = Vec::new();
DenseBlockCodec::serialize(0u16..150u16, &mut buffer).unwrap();
let tested_set = DenseBlockCodec::open(buffer.as_slice());
assert!(tested_set.contains(1));
let mut select_cursor = tested_set.select_cursor();
for i in 0..150 {
assert_eq!(i, select_cursor.select(i));
}
}

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use proptest::prelude::{any, prop, *};
use proptest::strategy::Strategy;
use proptest::{prop_oneof, proptest};
use super::*;
#[test]
fn test_dense_block_threshold() {
assert_eq!(super::DENSE_BLOCK_THRESHOLD, 5_120);
}
fn random_bitvec() -> BoxedStrategy<Vec<bool>> {
prop_oneof![
1 => prop::collection::vec(proptest::bool::weighted(1.0), 0..100),
1 => prop::collection::vec(proptest::bool::weighted(0.00), 0..(ELEMENTS_PER_BLOCK as usize * 3)), // empty blocks
1 => prop::collection::vec(proptest::bool::weighted(1.00), 0..(ELEMENTS_PER_BLOCK as usize + 10)), // full block
1 => prop::collection::vec(proptest::bool::weighted(0.01), 0..100),
1 => prop::collection::vec(proptest::bool::weighted(0.01), 0..u16::MAX as usize),
8 => vec![any::<bool>()],
]
.boxed()
}
proptest! {
#![proptest_config(ProptestConfig::with_cases(50))]
#[test]
fn test_with_random_bitvecs(bitvec1 in random_bitvec(), bitvec2 in random_bitvec(), bitvec3 in random_bitvec()) {
let mut bitvec = Vec::new();
bitvec.extend_from_slice(&bitvec1);
bitvec.extend_from_slice(&bitvec2);
bitvec.extend_from_slice(&bitvec3);
test_null_index(&bitvec[..]);
}
}
#[test]
fn test_with_random_sets_simple() {
let vals = 10..BLOCK_SIZE * 2;
let mut out: Vec<u8> = Vec::new();
serialize_optional_index(&vals.clone(), 100, &mut out).unwrap();
let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
let ranks: Vec<u32> = (65_472u32..65_473u32).collect();
let els: Vec<u32> = ranks.iter().copied().map(|rank| rank + 10).collect();
let mut select_cursor = null_index.select_cursor();
for (rank, el) in ranks.iter().copied().zip(els.iter().copied()) {
assert_eq!(select_cursor.select(rank), el);
}
}
#[test]
fn test_optional_index_trailing_empty_blocks() {
test_null_index(&[false]);
}
#[test]
fn test_optional_index_one_block_false() {
let mut iter = vec![false; ELEMENTS_PER_BLOCK as usize];
iter.push(true);
test_null_index(&iter[..]);
}
#[test]
fn test_optional_index_one_block_true() {
let mut iter = vec![true; ELEMENTS_PER_BLOCK as usize];
iter.push(true);
test_null_index(&iter[..]);
}
impl<'a> Iterable<RowId> for &'a [bool] {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = RowId> + 'a> {
Box::new(
self.iter()
.cloned()
.enumerate()
.filter(|(_pos, val)| *val)
.map(|(pos, _val)| pos as u32),
)
}
}
fn test_null_index(data: &[bool]) {
let mut out: Vec<u8> = Vec::new();
serialize_optional_index(&data, data.len() as RowId, &mut out).unwrap();
let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
let orig_idx_with_value: Vec<u32> = data
.iter()
.enumerate()
.filter(|(_pos, val)| **val)
.map(|(pos, _val)| pos as u32)
.collect();
let mut select_iter = null_index.select_cursor();
for i in 0..orig_idx_with_value.len() {
assert_eq!(select_iter.select(i as u32), orig_idx_with_value[i]);
}
let step_size = (orig_idx_with_value.len() / 100).max(1);
for (dense_idx, orig_idx) in orig_idx_with_value.iter().enumerate().step_by(step_size) {
assert_eq!(null_index.rank_if_exists(*orig_idx), Some(dense_idx as u32));
}
// 100 samples
let step_size = (data.len() / 100).max(1);
for (pos, value) in data.iter().enumerate().step_by(step_size) {
assert_eq!(null_index.contains(pos as u32), *value);
}
}
#[test]
fn test_optional_index_test_translation() {
let mut out = vec![];
let iter = &[true, false, true, false];
serialize_optional_index(&&iter[..], iter.len() as u32, &mut out).unwrap();
let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
let mut select_cursor = null_index.select_cursor();
assert_eq!(select_cursor.select(0), 0);
assert_eq!(select_cursor.select(1), 2);
}
#[test]
fn test_optional_index_translate() {
let mut out = vec![];
let iter = &[true, false, true, false];
serialize_optional_index(&&iter[..], iter.len() as RowId, &mut out).unwrap();
let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
assert_eq!(null_index.rank_if_exists(0), Some(0));
assert_eq!(null_index.rank_if_exists(2), Some(1));
}
#[test]
fn test_optional_index_small() {
let mut out = vec![];
let iter = &[true, false, true, false];
serialize_optional_index(&&iter[..], iter.len() as RowId, &mut out).unwrap();
let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
assert!(null_index.contains(0));
assert!(!null_index.contains(1));
assert!(null_index.contains(2));
assert!(!null_index.contains(3));
}
#[test]
fn test_optional_index_large() {
let mut docs = vec![];
docs.extend((0..ELEMENTS_PER_BLOCK).map(|_idx| false));
docs.extend((0..=1).map(|_idx| true));
let mut out = vec![];
serialize_optional_index(&&docs[..], docs.len() as RowId, &mut out).unwrap();
let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
assert!(!null_index.contains(0));
assert!(!null_index.contains(100));
assert!(!null_index.contains(ELEMENTS_PER_BLOCK - 1));
assert!(null_index.contains(ELEMENTS_PER_BLOCK));
assert!(null_index.contains(ELEMENTS_PER_BLOCK + 1));
}
fn test_optional_index_iter_aux(row_ids: &[RowId], num_rows: RowId) {
let mut buffer: Vec<u8> = Vec::new();
serialize_optional_index(&row_ids, num_rows, &mut buffer).unwrap();
let null_index = open_optional_index(OwnedBytes::new(buffer)).unwrap();
assert_eq!(null_index.num_rows(), num_rows);
assert!(null_index.iter_rows().eq(row_ids.iter().copied()));
}
#[test]
fn test_optional_index_iter_empty() {
test_optional_index_iter_aux(&[], 0u32);
}
fn test_optional_index_rank_aux(row_ids: &[RowId]) {
let mut buffer: Vec<u8> = Vec::new();
let num_rows = row_ids.last().copied().unwrap_or(0u32) + 1;
serialize_optional_index(&row_ids, num_rows, &mut buffer).unwrap();
let null_index = open_optional_index(OwnedBytes::new(buffer)).unwrap();
assert_eq!(null_index.num_rows(), num_rows);
for (row_id, row_val) in row_ids.iter().copied().enumerate() {
assert_eq!(null_index.rank(row_val), row_id as u32);
assert_eq!(null_index.rank_if_exists(row_val), Some(row_id as u32));
if row_val > 0 && !null_index.contains(&row_val - 1) {
assert_eq!(null_index.rank(row_val - 1), row_id as u32);
}
assert_eq!(null_index.rank(row_val + 1), row_id as u32 + 1);
}
}
#[test]
fn test_optional_index_rank() {
test_optional_index_rank_aux(&[1u32]);
test_optional_index_rank_aux(&[0u32, 1u32]);
let mut block = Vec::new();
block.push(3u32);
block.extend((0..BLOCK_SIZE).map(|i| i + BLOCK_SIZE + 1));
test_optional_index_rank_aux(&block);
}
#[test]
fn test_optional_index_iter_empty_one() {
test_optional_index_iter_aux(&[1], 2u32);
test_optional_index_iter_aux(&[100_000], 200_000u32);
}
#[test]
fn test_optional_index_iter_dense_block() {
let mut block = Vec::new();
block.push(3u32);
block.extend((0..BLOCK_SIZE).map(|i| i + BLOCK_SIZE + 1));
test_optional_index_iter_aux(&block, 3 * BLOCK_SIZE);
}
#[cfg(all(test, feature = "unstable"))]
mod bench {
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use test::Bencher;
use super::*;
const TOTAL_NUM_VALUES: u32 = 1_000_000;
fn gen_bools(fill_ratio: f64) -> OptionalIndex {
let mut out = Vec::new();
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let vals: Vec<bool> = (0..TOTAL_NUM_VALUES)
.map(|_| rng.gen_bool(fill_ratio))
.collect();
serialize_optional_index(&&vals[..], &mut out).unwrap();
let codec = open_optional_index(OwnedBytes::new(out)).unwrap();
codec
}
fn random_range_iterator(
start: u32,
end: u32,
avg_step_size: u32,
avg_deviation: u32,
) -> impl Iterator<Item = u32> {
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let mut current = start;
std::iter::from_fn(move || {
current += rng.gen_range(avg_step_size - avg_deviation..=avg_step_size + avg_deviation);
if current >= end {
None
} else {
Some(current)
}
})
}
fn n_percent_step_iterator(percent: f32, num_values: u32) -> impl Iterator<Item = u32> {
let ratio = percent as f32 / 100.0;
let step_size = (1f32 / ratio) as u32;
let deviation = step_size - 1;
random_range_iterator(0, num_values, step_size, deviation)
}
fn walk_over_data(codec: &OptionalIndex, avg_step_size: u32) -> Option<u32> {
walk_over_data_from_positions(
codec,
random_range_iterator(0, TOTAL_NUM_VALUES, avg_step_size, 0),
)
}
fn walk_over_data_from_positions(
codec: &OptionalIndex,
positions: impl Iterator<Item = u32>,
) -> Option<u32> {
let mut dense_idx: Option<u32> = None;
for idx in positions {
dense_idx = dense_idx.or(codec.rank_if_exists(idx));
}
dense_idx
}
#[bench]
fn bench_translate_orig_to_codec_1percent_filled_10percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_5percent_filled_10percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.05f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_5percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.05f64);
bench.iter(|| walk_over_data(&codec, 1000));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_1percent_filled(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_10percent_filled(bench: &mut Bencher) {
let codec = gen_bools(0.1f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_90percent_filled(bench: &mut Bencher) {
let codec = gen_bools(0.9f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_10percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.1f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_50percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.5f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_90percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.9f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_0comma005percent_hit(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.01f64, 0.005f32, bench);
}
#[bench]
fn bench_translate_codec_to_orig_10percent_filled_0comma005percent_hit(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.1f64, 0.005f32, bench);
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_10percent_hit(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.01f64, 10f32, bench);
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_full_scan(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.01f64, 100f32, bench);
}
fn bench_translate_codec_to_orig_util(
percent_filled: f64,
percent_hit: f32,
bench: &mut Bencher,
) {
let codec = gen_bools(percent_filled);
let num_non_nulls = codec.num_non_nulls();
let idxs: Vec<u32> = if percent_hit == 100.0f32 {
(0..num_non_nulls).collect()
} else {
n_percent_step_iterator(percent_hit, num_non_nulls).collect()
};
let mut output = vec![0u32; idxs.len()];
bench.iter(|| {
output.copy_from_slice(&idxs[..]);
codec.select_batch(&mut output);
});
}
#[bench]
fn bench_translate_codec_to_orig_90percent_filled_0comma005percent_hit(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.9f64, 0.005, bench);
}
#[bench]
fn bench_translate_codec_to_orig_90percent_filled_full_scan(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.9f64, 100.0f32, bench);
}
}

77
columnar/src/column_index/serialize.rs Normal file
View File

@@ -0,0 +1,77 @@
use std::io;
use std::io::Write;
use common::{CountingWriter, OwnedBytes};
use crate::column_index::multivalued_index::serialize_multivalued_index;
use crate::column_index::optional_index::serialize_optional_index;
use crate::column_index::ColumnIndex;
use crate::iterable::Iterable;
use crate::{Cardinality, RowId};
pub enum SerializableColumnIndex<'a> {
Full,
Optional {
non_null_row_ids: Box<dyn Iterable<RowId> + 'a>,
num_rows: RowId,
},
// TODO remove the Arc<dyn> apart from serialization this is not
// dynamic at all.
Multivalued(Box<dyn Iterable<RowId> + 'a>),
}
impl<'a> SerializableColumnIndex<'a> {
pub fn get_cardinality(&self) -> Cardinality {
match self {
SerializableColumnIndex::Full => Cardinality::Full,
SerializableColumnIndex::Optional { .. } => Cardinality::Optional,
SerializableColumnIndex::Multivalued(_) => Cardinality::Multivalued,
}
}
}
pub fn serialize_column_index(
column_index: SerializableColumnIndex,
output: &mut impl Write,
) -> io::Result<u32> {
let mut output = CountingWriter::wrap(output);
let cardinality = column_index.get_cardinality().to_code();
output.write_all(&[cardinality])?;
match column_index {
SerializableColumnIndex::Full => {}
SerializableColumnIndex::Optional {
non_null_row_ids,
num_rows,
} => serialize_optional_index(non_null_row_ids.as_ref(), num_rows, &mut output)?,
SerializableColumnIndex::Multivalued(multivalued_index) => {
serialize_multivalued_index(&*multivalued_index, &mut output)?
}
}
let column_index_num_bytes = output.written_bytes() as u32;
Ok(column_index_num_bytes)
}
pub fn open_column_index(mut bytes: OwnedBytes) -> io::Result<ColumnIndex> {
if bytes.is_empty() {
return Err(io::Error::new(
io::ErrorKind::UnexpectedEof,
"Failed to deserialize column index. Empty buffer.",
));
}
let cardinality_code = bytes[0];
let cardinality = Cardinality::try_from_code(cardinality_code)?;
bytes.advance(1);
match cardinality {
Cardinality::Full => Ok(ColumnIndex::Full),
Cardinality::Optional => {
let optional_index = super::optional_index::open_optional_index(bytes)?;
Ok(ColumnIndex::Optional(optional_index))
}
Cardinality::Multivalued => {
let multivalue_index = super::multivalued_index::open_multivalued_index(bytes)?;
Ok(ColumnIndex::Multivalued(multivalue_index))
}
}
}
// TODO unit tests

92
fastfield_codecs/src/column.rs → columnar/src/column_values/column.rs
View File

@@ -1,12 +1,17 @@
use std::fmt::Debug;
use std::marker::PhantomData;
use std::ops::{Range, RangeInclusive};
use std::sync::Arc;
use tantivy_bitpacker::minmax;
use crate::monotonic_mapping::StrictlyMonotonicFn;
use crate::column_values::monotonic_mapping::StrictlyMonotonicFn;
use crate::iterable::Iterable;
/// `Column` provides columnar access on a field.
pub trait Column<T: PartialOrd = u64>: Send + Sync {
/// `ColumnValues` provides access to a dense field column.
///
/// `Column` are just a wrapper over `ColumnValues` and a `ColumnIndex`.
pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
/// Return the value associated with the given idx.
///
/// This accessor should return as fast as possible.
@@ -24,7 +29,7 @@ pub trait Column<T: PartialOrd = u64>: Send + Sync {
///
/// Must panic if `start + output.len()` is greater than
/// the segment's `maxdoc`.
#[inline]
#[inline(always)]
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);
@@ -34,7 +39,7 @@ pub trait Column<T: PartialOrd = u64>: Send + Sync {
/// Get the positions of values which are in the provided value range.
///
/// Note that position == docid for single value fast fields
#[inline]
#[inline(always)]
fn get_docids_for_value_range(
&self,
value_range: RangeInclusive<T>,
@@ -42,7 +47,6 @@ pub trait Column<T: PartialOrd = u64>: Send + Sync {
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) {
@@ -76,14 +80,45 @@ pub trait Column<T: PartialOrd = u64>: Send + Sync {
}
}
/// VecColumn provides `Column` over a slice.
pub struct VecColumn<'a, T = u64> {
values: &'a [T],
min_value: T,
max_value: T,
impl<'a, T: PartialOrd> Iterable<T> for &'a [Arc<dyn ColumnValues<T>>] {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
Box::new(self.iter().flat_map(|column_value| column_value.iter()))
}
}
impl<'a, C: Column<T>, T: Copy + PartialOrd> Column<T> for &'a C {
impl<T: Copy + PartialOrd + Debug> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
#[inline(always)]
fn get_val(&self, idx: u32) -> T {
self.as_ref().get_val(idx)
}
#[inline(always)]
fn min_value(&self) -> T {
self.as_ref().min_value()
}
#[inline(always)]
fn max_value(&self) -> T {
self.as_ref().max_value()
}
#[inline(always)]
fn num_vals(&self) -> u32 {
self.as_ref().num_vals()
}
#[inline(always)]
fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = T> + 'b> {
self.as_ref().iter()
}
#[inline(always)]
fn get_range(&self, start: u64, output: &mut [T]) {
self.as_ref().get_range(start, output)
}
}
impl<'a, C: ColumnValues<T> + ?Sized, T: Copy + PartialOrd + Debug> ColumnValues<T> for &'a C {
fn get_val(&self, idx: u32) -> T {
(*self).get_val(idx)
}
@@ -109,7 +144,14 @@ impl<'a, C: Column<T>, T: Copy + PartialOrd> Column<T> for &'a C {
}
}
impl<'a, T: Copy + PartialOrd + Send + Sync> Column<T> for VecColumn<'a, T> {
/// VecColumn provides `Column` over a slice.
pub struct VecColumn<'a, T = u64> {
pub(crate) values: &'a [T],
pub(crate) min_value: T,
pub(crate) max_value: T,
}
impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> ColumnValues<T> for VecColumn<'a, T> {
fn get_val(&self, position: u32) -> T {
self.values[position as usize]
}
@@ -135,7 +177,7 @@ impl<'a, T: Copy + PartialOrd + Send + Sync> Column<T> for VecColumn<'a, T> {
}
}
impl<'a, T: Copy + Ord + Default, V> From<&'a V> for VecColumn<'a, T>
impl<'a, T: Copy + PartialOrd + Default, V> From<&'a V> for VecColumn<'a, T>
where V: AsRef<[T]> + ?Sized
{
fn from(values: &'a V) -> Self {
@@ -173,12 +215,12 @@ struct MonotonicMappingColumn<C, T, Input> {
pub fn monotonic_map_column<C, T, Input, Output>(
from_column: C,
monotonic_mapping: T,
) -> impl Column<Output>
) -> impl ColumnValues<Output>
where
C: Column<Input>,
C: ColumnValues<Input>,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
Input: PartialOrd + Send + Sync + Clone,
Output: PartialOrd + Send + Sync + Clone,
Input: PartialOrd + Debug + Send + Sync + Clone,
Output: PartialOrd + Debug + Send + Sync + Clone,
{
MonotonicMappingColumn {
from_column,
@@ -187,12 +229,12 @@ where
}
}
impl<C, T, Input, Output> Column<Output> for MonotonicMappingColumn<C, T, Input>
impl<C, T, Input, Output> ColumnValues<Output> for MonotonicMappingColumn<C, T, Input>
where
C: Column<Input>,
C: ColumnValues<Input>,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
Input: PartialOrd + Send + Sync + Clone,
Output: PartialOrd + Send + Sync + Clone,
Input: PartialOrd + Send + Debug + Sync + Clone,
Output: PartialOrd + Send + Debug + Sync + Clone,
{
#[inline]
fn get_val(&self, idx: u32) -> Output {
@@ -251,10 +293,10 @@ where T: Iterator + Clone + ExactSizeIterator
}
}
impl<T> Column<T::Item> for IterColumn<T>
impl<T> ColumnValues<T::Item> for IterColumn<T>
where
T: Iterator + Clone + ExactSizeIterator + Send + Sync,
T::Item: PartialOrd,
T::Item: PartialOrd + Debug,
{
fn get_val(&self, idx: u32) -> T::Item {
self.0.clone().nth(idx as usize).unwrap()
@@ -280,7 +322,7 @@ where
#[cfg(test)]
mod tests {
use super::*;
use crate::monotonic_mapping::{
use crate::column_values::monotonic_mapping::{
StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternalBaseval,
StrictlyMonotonicMappingToInternalGCDBaseval,
};

0
fastfield_codecs/src/compact_space/blank_range.rs → columnar/src/column_values/compact_space/blank_range.rs
View File

2
fastfield_codecs/src/compact_space/build_compact_space.rs → columnar/src/column_values/compact_space/build_compact_space.rs
View File

@@ -208,7 +208,7 @@ impl CompactSpaceBuilder {
};
let covered_range_len = range_mapping.range_length();
ranges_mapping.push(range_mapping);
compact_start += covered_range_len as u64;
compact_start += covered_range_len;
}
// println!("num ranges {}", ranges_mapping.len());
CompactSpace { ranges_mapping }

754
fastfield_codecs/src/compact_space/mod.rs → columnar/src/column_values/compact_space/mod.rs
View File

@@ -17,12 +17,11 @@ use std::{
ops::{Range, RangeInclusive},
};
use common::{BinarySerializable, CountingWriter, VInt, VIntU128};
use ownedbytes::OwnedBytes;
use common::{BinarySerializable, CountingWriter, OwnedBytes, VInt, VIntU128};
use tantivy_bitpacker::{self, BitPacker, BitUnpacker};
use crate::compact_space::build_compact_space::get_compact_space;
use crate::Column;
use crate::column_values::compact_space::build_compact_space::get_compact_space;
use crate::column_values::ColumnValues;
mod blank_range;
mod build_compact_space;
@@ -56,7 +55,7 @@ impl RangeMapping {
}
impl BinarySerializable for CompactSpace {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: io::Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.ranges_mapping.len() as u64).serialize(writer)?;
let mut prev_value = 0;
@@ -97,7 +96,7 @@ impl BinarySerializable for CompactSpace {
};
let range_length = range_mapping.range_length();
ranges_mapping.push(range_mapping);
compact_start += range_length as u64;
compact_start += range_length;
}
Ok(Self { ranges_mapping })
@@ -248,7 +247,7 @@ pub struct CompactSpaceDecompressor {
}
impl BinarySerializable for IPCodecParams {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: io::Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
// header flags for future optional dictionary encoding
let footer_flags = 0u64;
footer_flags.serialize(writer)?;
@@ -282,7 +281,7 @@ impl BinarySerializable for IPCodecParams {
}
}
impl Column<u128> for CompactSpaceDecompressor {
impl ColumnValues<u128> for CompactSpaceDecompressor {
#[inline]
fn get_val(&self, doc: u32) -> u128 {
self.get(doc)
@@ -407,10 +406,10 @@ impl CompactSpaceDecompressor {
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);
let val1 = get_val(idx1);
let val2 = get_val(idx2);
let val3 = get_val(idx3);
let val4 = get_val(idx4);
push_if_in_range(idx1, val1);
push_if_in_range(idx2, val2);
push_if_in_range(idx3, val3);
@@ -419,14 +418,13 @@ impl CompactSpaceDecompressor {
// handle rest
for idx in cutoff..position_range.end {
push_if_in_range(idx, get_val(idx as u32));
push_if_in_range(idx, get_val(idx));
}
}
#[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)
(0..self.params.num_vals).map(move |idx| self.params.bit_unpacker.get(idx, &self.data))
}
#[inline]
@@ -452,368 +450,364 @@ impl CompactSpaceDecompressor {
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::format_version::read_format_version;
use crate::null_index_footer::read_null_index_footer;
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);
let (data, _format_version) = read_format_version(data).unwrap();
let (data, _null_index_footer) = read_null_index_footer(data).unwrap();
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();
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);
}
}
}
// TODO reenable what can be reenabled.
// #[cfg(test)]
// mod tests {
//
// use super::*;
// use crate::column::format_version::read_format_version;
// use crate::column::column_footer::read_null_index_footer;
// use crate::column::serialize::U128Header;
// use crate::column::{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);
// let (data, _format_version) = read_format_version(data).unwrap();
// let (data, _null_index_footer) = read_null_index_footer(data).unwrap();
// 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;
// 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: Vec<u32> = get_positions_for_value_range_helper(&decomp, 0..=1, 1..u32::MAX);
// assert!(positions.is_empty());
//
// 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()
// ),
// &[3]
// );
// assert!(get_positions_for_value_range_helper(
// &decomp,
// 99998u128..=99998u128,
// complete_range.clone()
// )
// .is_empty());
// assert_eq!(
// &get_positions_for_value_range_helper(
// &decomp,
// 333u128..=333u128,
// complete_range.clone()
// ),
// &[8]
// );
// assert_eq!(
// &get_positions_for_value_range_helper(
// &decomp,
// 332u128..=333u128,
// complete_range.clone()
// ),
// &[8]
// );
// assert_eq!(
// &get_positions_for_value_range_helper(
// &decomp,
// 332u128..=334u128,
// complete_range.clone()
// ),
// &[8]
// );
// assert_eq!(
// &get_positions_for_value_range_helper(
// &decomp,
// 333u128..=334u128,
// complete_range.clone()
// ),
// &[8]
// );
//
// assert_eq!(
// &get_positions_for_value_range_helper(
// &decomp,
// 4_000_211_221u128..=5_000_000_000u128,
// complete_range
// ),
// &[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!(
// &get_positions_for_value_range_helper(&decomp, 0..=5, complete_range.clone())
// .is_empty(),
// );
// assert_eq!(
// &get_positions_for_value_range_helper(&decomp, 0..=100, complete_range.clone()),
// &[0]
// );
// assert_eq!(
// &get_positions_for_value_range_helper(&decomp, 0..=105, complete_range),
// &[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();
// 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),
// 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);
// }
// }
// }
//

2
fastfield_codecs/src/main.rs → columnar/src/column_values/main.rs
View File

@@ -6,10 +6,10 @@ use std::io::BufRead;
use std::net::{IpAddr, Ipv6Addr};
use std::str::FromStr;
use common::OwnedBytes;
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]) {

213
columnar/src/column_values/mod.rs Normal file
View File

@@ -0,0 +1,213 @@
#![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
use std::fmt::Debug;
use std::io;
use std::io::Write;
use std::sync::Arc;
use common::{BinarySerializable, OwnedBytes};
use compact_space::CompactSpaceDecompressor;
pub use monotonic_mapping::{MonotonicallyMappableToU64, StrictlyMonotonicFn};
use monotonic_mapping::{StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternal};
pub use monotonic_mapping_u128::MonotonicallyMappableToU128;
use serialize::U128Header;
mod compact_space;
pub(crate) mod monotonic_mapping;
pub(crate) mod monotonic_mapping_u128;
mod stats;
pub(crate) mod u64_based;
mod column;
pub mod serialize;
pub use serialize::serialize_column_values_u128;
pub use stats::Stats;
pub use u64_based::{
load_u64_based_column_values, serialize_and_load_u64_based_column_values,
serialize_u64_based_column_values, CodecType, ALL_U64_CODEC_TYPES,
};
pub use self::column::{monotonic_map_column, ColumnValues, IterColumn, VecColumn};
#[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 + ?Sized>(&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_mapped<T: MonotonicallyMappableToU128 + Debug>(
mut bytes: OwnedBytes,
) -> io::Result<Arc<dyn ColumnValues<T>>> {
let header = U128Header::deserialize(&mut bytes)?;
assert_eq!(header.codec_type, U128FastFieldCodecType::CompactSpace);
let reader = CompactSpaceDecompressor::open(bytes)?;
let inverted: StrictlyMonotonicMappingInverter<StrictlyMonotonicMappingToInternal<T>> =
StrictlyMonotonicMappingToInternal::<T>::new().into();
Ok(Arc::new(monotonic_map_column(reader, inverted)))
}
#[cfg(all(test, feature = "unstable"))]
mod bench {
use std::sync::Arc;
use common::OwnedBytes;
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use test::{self, Bencher};
use super::*;
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 = 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 ColumnValues>) {
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);
}
}

52
fastfield_codecs/src/monotonic_mapping.rs → columnar/src/column_values/monotonic_mapping.rs
View File

@@ -1,12 +1,14 @@
use std::fmt::Debug;
use std::marker::PhantomData;
use fastdivide::DividerU64;
use crate::MonotonicallyMappableToU128;
use super::MonotonicallyMappableToU128;
use crate::RowId;
/// 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 {
pub trait MonotonicallyMappableToU64: 'static + PartialOrd + Debug + Copy + Send + Sync {
/// Converts a value to u64.
///
/// Internally all fast field values are encoded as u64.
@@ -56,10 +58,12 @@ impl<T> From<T> for StrictlyMonotonicMappingInverter<T> {
impl<From, To, T> StrictlyMonotonicFn<To, From> for StrictlyMonotonicMappingInverter<T>
where T: StrictlyMonotonicFn<From, To>
{
#[inline(always)]
fn mapping(&self, val: To) -> From {
self.orig_mapping.inverse(val)
}
#[inline(always)]
fn inverse(&self, val: From) -> To {
self.orig_mapping.mapping(val)
}
@@ -82,10 +86,12 @@ impl<External: MonotonicallyMappableToU128, T: MonotonicallyMappableToU128>
StrictlyMonotonicFn<External, u128> for StrictlyMonotonicMappingToInternal<T>
where T: MonotonicallyMappableToU128
{
#[inline(always)]
fn mapping(&self, inp: External) -> u128 {
External::to_u128(inp)
}
#[inline(always)]
fn inverse(&self, out: u128) -> External {
External::from_u128(out)
}
@@ -95,10 +101,12 @@ impl<External: MonotonicallyMappableToU64, T: MonotonicallyMappableToU64>
StrictlyMonotonicFn<External, u64> for StrictlyMonotonicMappingToInternal<T>
where T: MonotonicallyMappableToU64
{
#[inline(always)]
fn mapping(&self, inp: External) -> u64 {
External::to_u64(inp)
}
#[inline(always)]
fn inverse(&self, out: u64) -> External {
External::from_u64(out)
}
@@ -126,11 +134,13 @@ impl StrictlyMonotonicMappingToInternalGCDBaseval {
impl<External: MonotonicallyMappableToU64> StrictlyMonotonicFn<External, u64>
for StrictlyMonotonicMappingToInternalGCDBaseval
{
#[inline(always)]
fn mapping(&self, inp: External) -> u64 {
self.gcd_divider
.divide(External::to_u64(inp) - self.min_value)
}
#[inline(always)]
fn inverse(&self, out: u64) -> External {
External::from_u64(self.min_value + out * self.gcd)
}
@@ -141,6 +151,7 @@ pub(crate) struct StrictlyMonotonicMappingToInternalBaseval {
min_value: u64,
}
impl StrictlyMonotonicMappingToInternalBaseval {
#[inline(always)]
pub(crate) fn new(min_value: u64) -> Self {
Self { min_value }
}
@@ -149,20 +160,24 @@ impl StrictlyMonotonicMappingToInternalBaseval {
impl<External: MonotonicallyMappableToU64> StrictlyMonotonicFn<External, u64>
for StrictlyMonotonicMappingToInternalBaseval
{
#[inline(always)]
fn mapping(&self, val: External) -> u64 {
External::to_u64(val) - self.min_value
}
#[inline(always)]
fn inverse(&self, val: u64) -> External {
External::from_u64(self.min_value + val)
}
}
impl MonotonicallyMappableToU64 for u64 {
#[inline(always)]
fn to_u64(self) -> u64 {
self
}
#[inline(always)]
fn from_u64(val: u64) -> Self {
val
}
@@ -180,6 +195,20 @@ impl MonotonicallyMappableToU64 for i64 {
}
}
impl MonotonicallyMappableToU64 for crate::DateTime {
#[inline(always)]
fn to_u64(self) -> u64 {
common::i64_to_u64(self.timestamp_micros)
}
#[inline(always)]
fn from_u64(val: u64) -> Self {
crate::DateTime {
timestamp_micros: common::u64_to_i64(val),
}
}
}
impl MonotonicallyMappableToU64 for bool {
#[inline(always)]
fn to_u64(self) -> u64 {
@@ -192,11 +221,27 @@ impl MonotonicallyMappableToU64 for bool {
}
}
impl MonotonicallyMappableToU64 for RowId {
#[inline(always)]
fn to_u64(self) -> u64 {
u64::from(self)
}
#[inline(always)]
fn from_u64(val: u64) -> RowId {
val as RowId
}
}
// TODO remove me.
// Tantivy should refuse NaN values and work with NotNaN internally.
impl MonotonicallyMappableToU64 for f64 {
#[inline(always)]
fn to_u64(self) -> u64 {
common::f64_to_u64(self)
}
#[inline(always)]
fn from_u64(val: u64) -> Self {
common::u64_to_f64(val)
}
@@ -213,8 +258,9 @@ mod tests {
test_round_trip(&StrictlyMonotonicMappingToInternal::<u64>::new(), 100u64);
// round trip to i64
test_round_trip(&StrictlyMonotonicMappingToInternal::<i64>::new(), 100u64);
// TODO
// identity mapping
test_round_trip(&StrictlyMonotonicMappingToInternal::<u128>::new(), 100u128);
// test_round_trip(&StrictlyMonotonicMappingToInternal::<u128>::new(), 100u128);
// base value to i64 round trip
let mapping = StrictlyMonotonicMappingToInternalBaseval::new(100);

3
fastfield_codecs/src/monotonic_mapping_u128.rs → columnar/src/column_values/monotonic_mapping_u128.rs
View File

@@ -1,8 +1,9 @@
use std::fmt::Debug;
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 {
pub trait MonotonicallyMappableToU128: 'static + PartialOrd + Copy + Debug + Send + Sync {
/// Converts a value to u128.
///
/// Internally all fast field values are encoded as u64.

140
columnar/src/column_values/serialize.rs Normal file
View File

@@ -0,0 +1,140 @@
use std::fmt::Debug;
use std::io;
use common::{BinarySerializable, VInt};
use crate::column_values::compact_space::CompactSpaceCompressor;
use crate::column_values::U128FastFieldCodecType;
use crate::iterable::Iterable;
use crate::MonotonicallyMappableToU128;
/// 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, PartialEq, Eq)]
pub(crate) struct U128Header {
pub num_vals: u32,
pub codec_type: U128FastFieldCodecType,
}
impl BinarySerializable for U128Header {
fn serialize<W: io::Write + ?Sized>(&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,
})
}
}
/// Serializes u128 values with the compact space codec.
pub fn serialize_column_values_u128<T: MonotonicallyMappableToU128>(
iterable: &dyn Iterable<T>,
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(
iterable
.boxed_iter()
.map(MonotonicallyMappableToU128::to_u128),
num_vals,
);
compressor.compress_into(
iterable
.boxed_iter()
.map(MonotonicallyMappableToU128::to_u128),
output,
)?;
Ok(())
}
#[cfg(test)]
pub mod tests {
use super::*;
use crate::column_values::u64_based::{
self, serialize_and_load_u64_based_column_values, serialize_u64_based_column_values,
ALL_U64_CODEC_TYPES,
};
use crate::column_values::CodecType;
#[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_u64_based_column_values(&&original[..], &ALL_U64_CODEC_TYPES)
.iter()
.collect();
assert_eq!(&restored, &original[..]);
}
#[test]
fn test_fastfield_bool_size_bitwidth_1() {
let mut buffer = Vec::new();
serialize_u64_based_column_values::<bool>(
&&[false, true][..],
&ALL_U64_CODEC_TYPES,
&mut buffer,
)
.unwrap();
// TODO put the header as a footer so that it serves as a padding.
// 5 bytes of header, 1 byte of value, 7 bytes of padding.
assert_eq!(buffer.len(), 5 + 1);
}
#[test]
fn test_fastfield_bool_bit_size_bitwidth_0() {
let mut buffer = Vec::new();
serialize_u64_based_column_values::<bool>(
&&[false, true][..],
&ALL_U64_CODEC_TYPES,
&mut buffer,
)
.unwrap();
// 6 bytes of header, 0 bytes of value, 7 bytes of padding.
assert_eq!(buffer.len(), 6);
}
#[test]
fn test_fastfield_gcd() {
let mut buffer = Vec::new();
let vals: Vec<u64> = (0..80).map(|val| (val % 7) * 1_000u64).collect();
serialize_u64_based_column_values(&&vals[..], &[CodecType::Bitpacked], &mut buffer)
.unwrap();
// Values are stored over 3 bits.
assert_eq!(buffer.len(), 6 + (3 * 80 / 8));
}
}

96
columnar/src/column_values/stats.rs Normal file
View File

@@ -0,0 +1,96 @@
use std::io;
use std::io::Write;
use std::num::NonZeroU64;
use common::{BinarySerializable, VInt};
use crate::RowId;
#[derive(Debug, Clone, Eq, PartialEq)]
pub struct Stats {
pub gcd: NonZeroU64,
pub min_value: u64,
pub max_value: u64,
pub num_rows: RowId,
}
impl Stats {
pub fn amplitude(&self) -> u64 {
self.max_value - self.min_value
}
}
impl BinarySerializable for Stats {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.min_value).serialize(writer)?;
VInt(self.gcd.get()).serialize(writer)?;
VInt(self.amplitude() / self.gcd).serialize(writer)?;
VInt(self.num_rows as u64).serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let min_value = VInt::deserialize(reader)?.0;
let gcd = VInt::deserialize(reader)?.0;
let gcd = NonZeroU64::new(gcd)
.ok_or_else(|| io::Error::new(io::ErrorKind::InvalidData, "GCD of 0 is forbidden"))?;
let amplitude = VInt::deserialize(reader)?.0 * gcd.get();
let max_value = min_value + amplitude;
let num_rows = VInt::deserialize(reader)?.0 as RowId;
Ok(Stats {
min_value,
max_value,
num_rows,
gcd,
})
}
}
#[cfg(test)]
mod tests {
use std::num::NonZeroU64;
use common::BinarySerializable;
use crate::column_values::Stats;
#[track_caller]
fn test_stats_ser_deser_aux(stats: &Stats, num_bytes: usize) {
let mut buffer: Vec<u8> = Vec::new();
stats.serialize(&mut buffer).unwrap();
assert_eq!(buffer.len(), num_bytes);
let deser_stats = Stats::deserialize(&mut &buffer[..]).unwrap();
assert_eq!(stats, &deser_stats);
}
#[test]
fn test_stats_serialization() {
test_stats_ser_deser_aux(
&(Stats {
gcd: NonZeroU64::new(3).unwrap(),
min_value: 1,
max_value: 3001,
num_rows: 10,
}),
5,
);
test_stats_ser_deser_aux(
&(Stats {
gcd: NonZeroU64::new(1_000).unwrap(),
min_value: 1,
max_value: 3001,
num_rows: 10,
}),
5,
);
test_stats_ser_deser_aux(
&(Stats {
gcd: NonZeroU64::new(1).unwrap(),
min_value: 0,
max_value: 0,
num_rows: 0,
}),
4,
);
}
}

127
columnar/src/column_values/u64_based/bitpacked.rs Normal file
View File

@@ -0,0 +1,127 @@
use std::io::{self, Write};
use common::{BinarySerializable, OwnedBytes};
use fastdivide::DividerU64;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, Stats};
use crate::{ColumnValues, RowId};
/// Depending on the field type, a different
/// fast field is required.
#[derive(Clone)]
pub struct BitpackedReader {
data: OwnedBytes,
bit_unpacker: BitUnpacker,
stats: Stats,
}
impl ColumnValues for BitpackedReader {
#[inline(always)]
fn get_val(&self, doc: u32) -> u64 {
self.stats.min_value + self.stats.gcd.get() * self.bit_unpacker.get(doc, &self.data)
}
#[inline]
fn min_value(&self) -> u64 {
self.stats.min_value
}
#[inline]
fn max_value(&self) -> u64 {
self.stats.max_value
}
#[inline]
fn num_vals(&self) -> RowId {
self.stats.num_rows
}
}
fn num_bits(stats: &Stats) -> u8 {
compute_num_bits(stats.amplitude() / stats.gcd)
}
#[derive(Default)]
pub struct BitpackedCodecEstimator;
impl ColumnCodecEstimator for BitpackedCodecEstimator {
fn collect(&mut self, _value: u64) {}
fn estimate(&self, stats: &Stats) -> Option<u64> {
let num_bits_per_value = num_bits(stats);
Some(stats.num_bytes() + (stats.num_rows as u64 * (num_bits_per_value as u64) + 7) / 8)
}
fn serialize(
&self,
stats: &Stats,
vals: &mut dyn Iterator<Item = u64>,
wrt: &mut dyn Write,
) -> io::Result<()> {
stats.serialize(wrt)?;
let num_bits = num_bits(stats);
let mut bit_packer = BitPacker::new();
let divider = DividerU64::divide_by(stats.gcd.get());
for val in vals {
bit_packer.write(divider.divide(val - stats.min_value), num_bits, wrt)?;
}
bit_packer.close(wrt)?;
Ok(())
}
}
pub struct BitpackedCodec;
impl ColumnCodec for BitpackedCodec {
type Reader = BitpackedReader;
type Estimator = BitpackedCodecEstimator;
/// Opens a fast field given a file.
fn load(mut data: OwnedBytes) -> io::Result<Self::Reader> {
let stats = Stats::deserialize(&mut data)?;
let num_bits = num_bits(&stats);
let bit_unpacker = BitUnpacker::new(num_bits);
Ok(BitpackedReader {
data,
bit_unpacker,
stats,
})
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::column_values::u64_based::tests::create_and_validate;
#[test]
fn test_with_codec_data_sets_simple() {
create_and_validate::<BitpackedCodec>(&[4, 3, 12], "name");
}
#[test]
fn test_with_codec_data_sets_simple_gcd() {
create_and_validate::<BitpackedCodec>(&[1000, 2000, 3000], "name");
}
#[test]
fn test_with_codec_data_sets() {
let data_sets = crate::column_values::u64_based::tests::get_codec_test_datasets();
for (mut data, name) in data_sets {
create_and_validate::<BitpackedCodec>(&data, name);
data.reverse();
create_and_validate::<BitpackedCodec>(&data, name);
}
}
#[test]
fn bitpacked_fast_field_rand() {
for _ in 0..500 {
let mut data = (0..1 + rand::random::<u8>() as usize)
.map(|_| rand::random::<i64>() as u64 / 2)
.collect::<Vec<_>>();
create_and_validate::<BitpackedCodec>(&data, "rand");
data.reverse();
create_and_validate::<BitpackedCodec>(&data, "rand");
}
}
}

281
columnar/src/column_values/u64_based/blockwise_linear.rs Normal file
View File

@@ -0,0 +1,281 @@
use std::io::Write;
use std::sync::Arc;
use std::{io, iter};
use common::{BinarySerializable, CountingWriter, DeserializeFrom, OwnedBytes};
use fastdivide::DividerU64;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::column_values::u64_based::line::Line;
use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, Stats};
use crate::column_values::{ColumnValues, VecColumn};
use crate::MonotonicallyMappableToU64;
const BLOCK_SIZE: u32 = 512u32;
#[derive(Debug, Default)]
struct Block {
line: Line,
bit_unpacker: BitUnpacker,
data_start_offset: usize,
}
impl BinarySerializable for Block {
fn serialize<W: Write + ?Sized>(&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(Block {
line,
bit_unpacker: BitUnpacker::new(bit_width),
data_start_offset: 0,
})
}
}
fn compute_num_blocks(num_vals: u32) -> u32 {
(num_vals + BLOCK_SIZE - 1) / BLOCK_SIZE
}
pub struct BlockwiseLinearEstimator {
block: Vec<u64>,
values_num_bytes: u64,
meta_num_bytes: u64,
}
impl Default for BlockwiseLinearEstimator {
fn default() -> Self {
Self {
block: Vec::with_capacity(BLOCK_SIZE as usize),
values_num_bytes: 0u64,
meta_num_bytes: 0u64,
}
}
}
impl BlockwiseLinearEstimator {
fn flush_block_estimate(&mut self) {
if self.block.is_empty() {
return;
}
let line = Line::train(&VecColumn::from(&self.block));
let mut max_value = 0u64;
for (i, buffer_val) in self.block.iter().enumerate() {
let interpolated_val = line.eval(i as u32);
let val = buffer_val.wrapping_sub(interpolated_val);
max_value = val.max(max_value);
}
let bit_width = compute_num_bits(max_value) as usize;
self.values_num_bytes += (bit_width * self.block.len() + 7) as u64 / 8;
self.meta_num_bytes += 1 + line.num_bytes();
}
}
impl ColumnCodecEstimator for BlockwiseLinearEstimator {
fn collect(&mut self, value: u64) {
self.block.push(value);
if self.block.len() == BLOCK_SIZE as usize {
self.flush_block_estimate();
self.block.clear();
}
}
fn estimate(&self, stats: &Stats) -> Option<u64> {
let mut estimate = 4 + stats.num_bytes() + self.meta_num_bytes + self.values_num_bytes;
if stats.gcd.get() > 1 {
let estimate_gain_from_gcd =
(stats.gcd.get() as f32).log2().floor() * stats.num_rows as f32 / 8.0f32;
estimate = estimate.saturating_sub(estimate_gain_from_gcd as u64);
}
Some(estimate)
}
fn finalize(&mut self) {
self.flush_block_estimate();
}
fn serialize(
&self,
stats: &Stats,
mut vals: &mut dyn Iterator<Item = u64>,
wrt: &mut dyn Write,
) -> io::Result<()> {
stats.serialize(wrt)?;
let mut buffer = Vec::with_capacity(BLOCK_SIZE as usize);
let num_blocks = compute_num_blocks(stats.num_rows) as usize;
let mut blocks = Vec::with_capacity(num_blocks);
let mut bit_packer = BitPacker::new();
let gcd_divider = DividerU64::divide_by(stats.gcd.get());
for _ in 0..num_blocks {
buffer.clear();
buffer.extend(
(&mut vals)
.map(MonotonicallyMappableToU64::to_u64)
.take(BLOCK_SIZE as usize),
);
for buffer_val in buffer.iter_mut() {
*buffer_val = gcd_divider.divide(*buffer_val - stats.min_value);
}
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,
});
}
bit_packer.close(wrt)?;
assert_eq!(blocks.len(), num_blocks);
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(())
}
}
pub struct BlockwiseLinearCodec;
impl ColumnCodec<u64> for BlockwiseLinearCodec {
type Reader = BlockwiseLinearReader;
type Estimator = BlockwiseLinearEstimator;
fn load(mut bytes: OwnedBytes) -> io::Result<Self::Reader> {
let stats = Stats::deserialize(&mut bytes)?;
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 num_blocks = compute_num_blocks(stats.num_rows);
let mut blocks: Vec<Block> = iter::repeat_with(|| Block::deserialize(&mut footer))
.take(num_blocks as usize)
.collect::<io::Result<_>>()?;
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) * BLOCK_SIZE as usize / 8;
}
Ok(BlockwiseLinearReader {
blocks: blocks.into_boxed_slice().into(),
data,
stats,
})
}
}
#[derive(Clone)]
pub struct BlockwiseLinearReader {
blocks: Arc<[Block]>,
data: OwnedBytes,
stats: Stats,
}
impl ColumnValues for BlockwiseLinearReader {
#[inline(always)]
fn get_val(&self, idx: u32) -> u64 {
let block_id = (idx / BLOCK_SIZE as u32) as usize;
let idx_within_block = idx % (BLOCK_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);
// TODO optimize me! the line parameters could be tweaked to include the multiplication and
// remove the dependency.
self.stats.min_value
+ self
.stats
.gcd
.get()
.wrapping_mul(interpoled_val.wrapping_add(bitpacked_diff))
}
#[inline(always)]
fn min_value(&self) -> u64 {
self.stats.min_value
}
#[inline(always)]
fn max_value(&self) -> u64 {
self.stats.max_value
}
#[inline(always)]
fn num_vals(&self) -> u32 {
self.stats.num_rows
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::column_values::u64_based::tests::create_and_validate;
#[test]
fn test_with_codec_data_sets_simple() {
create_and_validate::<BlockwiseLinearCodec>(
&[11, 20, 40, 20, 10, 10, 10, 10, 10, 10],
"simple test",
)
.unwrap();
}
#[test]
fn test_with_codec_data_sets_simple_gcd() {
let (_, actual_compression_rate) = create_and_validate::<BlockwiseLinearCodec>(
&[10, 20, 40, 20, 10, 10, 10, 10, 10, 10],
"name",
)
.unwrap();
assert_eq!(actual_compression_rate, 0.175);
}
#[test]
fn test_with_codec_data_sets() {
let data_sets = crate::column_values::u64_based::tests::get_codec_test_datasets();
for (mut data, name) in data_sets {
create_and_validate::<BlockwiseLinearCodec>(&data, name);
data.reverse();
create_and_validate::<BlockwiseLinearCodec>(&data, name);
}
}
#[test]
fn test_blockwise_linear_fast_field_rand() {
for _ in 0..500 {
let mut data = (0..1 + rand::random::<u8>() as usize)
.map(|_| rand::random::<i64>() as u64 / 2)
.collect::<Vec<_>>();
create_and_validate::<BlockwiseLinearCodec>(&data, "rand");
data.reverse();
create_and_validate::<BlockwiseLinearCodec>(&data, "rand");
}
}
}

15
fastfield_codecs/src/line.rs → columnar/src/column_values/u64_based/line.rs
View File

@@ -3,7 +3,7 @@ use std::num::NonZeroU32;
use common::{BinarySerializable, VInt};
use crate::Column;
use crate::column_values::ColumnValues;
const MID_POINT: u64 = (1u64 << 32) - 1u64;
@@ -17,8 +17,8 @@ const MID_POINT: u64 = (1u64 << 32) - 1u64;
/// `y = m * x >> 32 + b`
#[derive(Debug, Clone, Copy, Default)]
pub struct Line {
slope: u64,
intercept: u64,
pub(crate) slope: u64,
pub(crate) intercept: u64,
}
/// Compute the line slope.
@@ -81,7 +81,7 @@ impl Line {
}
// Intercept is only computed from provided positions
fn train_from(
pub fn train_from(
first_val: u64,
last_val: u64,
num_vals: u32,
@@ -145,7 +145,8 @@ impl Line {
///
/// 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 {
/// TODO USE array
pub fn train(ys: &dyn ColumnValues) -> Self {
let first_val = ys.iter().next().unwrap();
let last_val = ys.iter().nth(ys.num_vals() as usize - 1).unwrap();
Self::train_from(
@@ -158,7 +159,7 @@ impl Line {
}
impl BinarySerializable for Line {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: io::Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.slope).serialize(writer)?;
VInt(self.intercept).serialize(writer)?;
Ok(())
@@ -174,7 +175,7 @@ impl BinarySerializable for Line {
#[cfg(test)]
mod tests {
use super::*;
use crate::VecColumn;
use crate::column_values::VecColumn;
/// Test training a line and ensuring that the maximum difference between
/// the data points and the line is `expected`.

277
columnar/src/column_values/u64_based/linear.rs Normal file
View File

@@ -0,0 +1,277 @@
use std::io;
use common::{BinarySerializable, OwnedBytes};
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use super::line::Line;
use super::ColumnValues;
use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, Stats};
use crate::column_values::VecColumn;
use crate::{MonotonicallyMappableToU64, RowId};
const HALF_SPACE: u64 = u64::MAX / 2;
const LINE_ESTIMATION_BLOCK_LEN: usize = 512;
/// Depending on the field type, a different
/// fast field is required.
#[derive(Clone)]
pub struct LinearReader {
data: OwnedBytes,
linear_params: LinearParams,
stats: Stats,
}
impl ColumnValues for LinearReader {
#[inline]
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(always)]
fn min_value(&self) -> u64 {
self.stats.min_value
}
#[inline(always)]
fn max_value(&self) -> u64 {
self.stats.max_value
}
#[inline]
fn num_vals(&self) -> u32 {
self.stats.num_rows
}
}
/// Fastfield serializer, which tries to guess values by linear interpolation
/// and stores the difference bitpacked.
pub struct LinearCodec;
#[derive(Debug, Clone)]
struct LinearParams {
line: Line,
bit_unpacker: BitUnpacker,
}
impl BinarySerializable for LinearParams {
fn serialize<W: io::Write + ?Sized>(&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),
})
}
}
pub struct LinearCodecEstimator {
block: Vec<u64>,
line: Option<Line>,
row_id: RowId,
min_deviation: u64,
max_deviation: u64,
first_val: u64,
last_val: u64,
}
impl Default for LinearCodecEstimator {
fn default() -> LinearCodecEstimator {
LinearCodecEstimator {
block: Vec::with_capacity(LINE_ESTIMATION_BLOCK_LEN),
line: None,
row_id: 0,
min_deviation: u64::MAX,
max_deviation: u64::MIN,
first_val: 0u64,
last_val: 0u64,
}
}
}
impl ColumnCodecEstimator for LinearCodecEstimator {
fn finalize(&mut self) {
if let Some(line) = self.line.as_mut() {
line.intercept = line
.intercept
.wrapping_add(self.min_deviation)
.wrapping_sub(HALF_SPACE);
}
}
fn estimate(&self, stats: &Stats) -> Option<u64> {
let line = self.line?;
let amplitude = self.max_deviation - self.min_deviation;
let num_bits = compute_num_bits(amplitude);
let linear_params = LinearParams {
line,
bit_unpacker: BitUnpacker::new(num_bits),
};
Some(
stats.num_bytes()
+ linear_params.num_bytes()
+ (num_bits as u64 * stats.num_rows as u64 + 7) / 8,
)
}
fn serialize(
&self,
stats: &Stats,
vals: &mut dyn Iterator<Item = u64>,
wrt: &mut dyn io::Write,
) -> io::Result<()> {
stats.serialize(wrt)?;
let line = self.line.unwrap();
let amplitude = self.max_deviation - self.min_deviation;
let num_bits = compute_num_bits(amplitude);
let linear_params = LinearParams {
line,
bit_unpacker: BitUnpacker::new(num_bits),
};
linear_params.serialize(wrt)?;
let mut bit_packer = BitPacker::new();
for (pos, value) in vals.enumerate() {
let calculated_value = line.eval(pos as u32);
let offset = value.wrapping_sub(calculated_value);
bit_packer.write(offset, num_bits, wrt)?;
}
bit_packer.close(wrt)?;
Ok(())
}
fn collect(&mut self, value: u64) {
if let Some(line) = self.line {
self.collect_after_line_estimation(&line, value);
} else {
self.collect_before_line_estimation(value);
}
}
}
impl LinearCodecEstimator {
#[inline]
fn collect_after_line_estimation(&mut self, line: &Line, value: u64) {
let interpoled_val: u64 = line.eval(self.row_id);
let deviation = value.wrapping_add(HALF_SPACE).wrapping_sub(interpoled_val);
self.min_deviation = self.min_deviation.min(deviation);
self.max_deviation = self.max_deviation.max(deviation);
if self.row_id == 0 {
self.first_val = value;
}
self.last_val = value;
self.row_id += 1u32;
}
#[inline]
fn collect_before_line_estimation(&mut self, value: u64) {
self.block.push(value);
if self.block.len() == LINE_ESTIMATION_BLOCK_LEN {
let line = Line::train(&VecColumn::from(&self.block));
let block = std::mem::take(&mut self.block);
for val in block {
self.collect_after_line_estimation(&line, val);
}
self.line = Some(line);
}
}
}
impl ColumnCodec for LinearCodec {
type Reader = LinearReader;
type Estimator = LinearCodecEstimator;
fn load(mut data: OwnedBytes) -> io::Result<Self::Reader> {
let stats = Stats::deserialize(&mut data)?;
let linear_params = LinearParams::deserialize(&mut data)?;
Ok(LinearReader {
stats,
linear_params,
data,
})
}
}
#[cfg(test)]
mod tests {
use rand::RngCore;
use super::*;
use crate::column_values::u64_based::tests::{create_and_validate, get_codec_test_datasets};
#[test]
fn test_compression_simple() {
let vals = (100u64..)
.take(super::LINE_ESTIMATION_BLOCK_LEN)
.collect::<Vec<_>>();
create_and_validate::<LinearCodec>(&vals, "simple monotonically large").unwrap();
}
#[test]
fn test_compression() {
let data = (10..=6_000_u64).collect::<Vec<_>>();
let (estimate, actual_compression) =
create_and_validate::<LinearCodec>(&data, "simple monotonically large").unwrap();
assert_le!(actual_compression, 0.001);
assert_le!(estimate, 0.02);
}
#[test]
fn test_with_codec_datasets() {
let data_sets = get_codec_test_datasets();
for (mut data, name) in data_sets {
create_and_validate::<LinearCodec>(&data, name);
data.reverse();
create_and_validate::<LinearCodec>(&data, name);
}
}
#[test]
fn linear_interpol_fast_field_test_large_amplitude() {
let data = vec![
i64::MAX as u64 / 2,
i64::MAX as u64 / 3,
i64::MAX as u64 / 2,
];
create_and_validate::<LinearCodec>(&data, "large amplitude");
}
#[test]
fn overflow_error_test() {
let data = vec![1572656989877777, 1170935903116329, 720575940379279, 0];
create_and_validate::<LinearCodec>(&data, "overflow test");
}
#[test]
fn linear_interpol_fast_concave_data() {
let data = vec![0, 1, 2, 5, 8, 10, 20, 50];
create_and_validate::<LinearCodec>(&data, "concave data");
}
#[test]
fn linear_interpol_fast_convex_data() {
let data = vec![0, 40, 60, 70, 75, 77];
create_and_validate::<LinearCodec>(&data, "convex data");
}
#[test]
fn linear_interpol_fast_field_test_simple() {
let data = (10..=20_u64).collect::<Vec<_>>();
create_and_validate::<LinearCodec>(&data, "simple monotonically");
}
#[test]
fn linear_interpol_fast_field_rand() {
let mut rng = rand::thread_rng();
for _ in 0..50 {
let mut data = (0..10_000).map(|_| rng.next_u64()).collect::<Vec<_>>();
create_and_validate::<LinearCodec>(&data, "random");
data.reverse();
create_and_validate::<LinearCodec>(&data, "random");
}
}
}

182
columnar/src/column_values/u64_based/mod.rs Normal file
View File

@@ -0,0 +1,182 @@
mod bitpacked;
mod blockwise_linear;
mod line;
mod linear;
mod stats_collector;
use std::io;
use std::io::Write;
use std::sync::Arc;
use common::{BinarySerializable, OwnedBytes};
use crate::column_values::monotonic_mapping::{
StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternal,
};
use crate::column_values::u64_based::bitpacked::BitpackedCodec;
use crate::column_values::u64_based::blockwise_linear::BlockwiseLinearCodec;
use crate::column_values::u64_based::linear::LinearCodec;
use crate::column_values::u64_based::stats_collector::StatsCollector;
use crate::column_values::{monotonic_map_column, Stats};
use crate::iterable::Iterable;
use crate::{ColumnValues, MonotonicallyMappableToU64};
pub trait ColumnCodecEstimator<T = u64>: 'static {
fn collect(&mut self, value: u64);
fn estimate(&self, stats: &Stats) -> Option<u64>;
fn finalize(&mut self) {}
fn serialize(
&self,
stats: &Stats,
vals: &mut dyn Iterator<Item = T>,
wrt: &mut dyn io::Write,
) -> io::Result<()>;
}
pub trait ColumnCodec<T: PartialOrd = u64> {
type Reader: ColumnValues<T> + 'static;
type Estimator: ColumnCodecEstimator + Default;
fn load(bytes: OwnedBytes) -> io::Result<Self::Reader>;
fn estimator() -> Self::Estimator {
Self::Estimator::default()
}
fn boxed_estimator() -> Box<dyn ColumnCodecEstimator> {
Box::new(Self::estimator())
}
}
/// Available codecs to use to encode the u64 (via [`MonotonicallyMappableToU64`]) converted data.
#[derive(PartialEq, Eq, PartialOrd, Ord, Debug, Clone, Copy)]
#[repr(u8)]
pub enum CodecType {
/// Bitpack all values in the value range. The number of bits is defined by the amplitude
/// `column.max_value() - column.min_value()`
Bitpacked = 0u8,
/// 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 = 1u8,
/// Same as [`CodecType::Linear`], but encodes in blocks of 512 elements.
BlockwiseLinear = 2u8,
}
pub const ALL_U64_CODEC_TYPES: [CodecType; 3] = [
CodecType::Bitpacked,
CodecType::Linear,
CodecType::BlockwiseLinear,
];
impl CodecType {
fn to_code(self) -> u8 {
self as u8
}
fn try_from_code(code: u8) -> Option<CodecType> {
match code {
0u8 => Some(CodecType::Bitpacked),
1u8 => Some(CodecType::Linear),
2u8 => Some(CodecType::BlockwiseLinear),
_ => None,
}
}
fn load<T: MonotonicallyMappableToU64>(
&self,
bytes: OwnedBytes,
) -> io::Result<Arc<dyn ColumnValues<T>>> {
match self {
CodecType::Bitpacked => load_specific_codec::<BitpackedCodec, T>(bytes),
CodecType::Linear => load_specific_codec::<LinearCodec, T>(bytes),
CodecType::BlockwiseLinear => load_specific_codec::<BlockwiseLinearCodec, T>(bytes),
}
}
}
fn load_specific_codec<C: ColumnCodec, T: MonotonicallyMappableToU64>(
bytes: OwnedBytes,
) -> io::Result<Arc<dyn ColumnValues<T>>> {
let reader = C::load(bytes)?;
let reader_typed = monotonic_map_column(
reader,
StrictlyMonotonicMappingInverter::from(StrictlyMonotonicMappingToInternal::<T>::new()),
);
Ok(Arc::new(reader_typed))
}
impl CodecType {
pub fn estimator(&self) -> Box<dyn ColumnCodecEstimator> {
match self {
CodecType::Bitpacked => BitpackedCodec::boxed_estimator(),
CodecType::Linear => LinearCodec::boxed_estimator(),
CodecType::BlockwiseLinear => BlockwiseLinearCodec::boxed_estimator(),
}
}
}
pub fn serialize_u64_based_column_values<'a, T: MonotonicallyMappableToU64>(
vals: &dyn Iterable<T>,
codec_types: &[CodecType],
wrt: &mut dyn Write,
) -> io::Result<()> {
let mut stats_collector = StatsCollector::default();
let mut estimators: Vec<(CodecType, Box<dyn ColumnCodecEstimator>)> =
Vec::with_capacity(codec_types.len());
for &codec_type in codec_types {
estimators.push((codec_type, codec_type.estimator()));
}
for val in vals.boxed_iter() {
let val_u64 = val.to_u64();
stats_collector.collect(val_u64);
for (_, estimator) in &mut estimators {
estimator.collect(val_u64);
}
}
for (_, estimator) in &mut estimators {
estimator.finalize();
}
let stats = stats_collector.stats();
let (_, best_codec, best_codec_estimator) = estimators
.into_iter()
.flat_map(|(codec_type, estimator)| {
let num_bytes = estimator.estimate(&stats)?;
Some((num_bytes, codec_type, estimator))
})
.min_by_key(|(num_bytes, _, _)| *num_bytes)
.ok_or_else(|| {
io::Error::new(io::ErrorKind::InvalidData, "No available applicable codec.")
})?;
best_codec.to_code().serialize(wrt)?;
best_codec_estimator.serialize(
&stats,
&mut vals.boxed_iter().map(MonotonicallyMappableToU64::to_u64),
wrt,
)?;
Ok(())
}
pub fn load_u64_based_column_values<T: MonotonicallyMappableToU64>(
mut bytes: OwnedBytes,
) -> io::Result<Arc<dyn ColumnValues<T>>> {
let codec_type: CodecType = bytes
.get(0)
.copied()
.and_then(CodecType::try_from_code)
.ok_or_else(|| io::Error::new(io::ErrorKind::InvalidData, "Failed to read codec type"))?;
bytes.advance(1);
codec_type.load(bytes)
}
/// Helper function to serialize a column (autodetect from all codecs) and then open it
pub fn serialize_and_load_u64_based_column_values<T: MonotonicallyMappableToU64>(
vals: &dyn Iterable,
codec_types: &[CodecType],
) -> Arc<dyn ColumnValues<T>> {
let mut buffer = Vec::new();
serialize_u64_based_column_values(vals, codec_types, &mut buffer).unwrap();
load_u64_based_column_values::<T>(OwnedBytes::new(buffer)).unwrap()
}
#[cfg(test)]
mod tests;

200
columnar/src/column_values/u64_based/stats_collector.rs Normal file
View File

@@ -0,0 +1,200 @@
use std::num::NonZeroU64;
use fastdivide::DividerU64;
use crate::column_values::Stats;
use crate::RowId;
/// 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;
}
}
}
#[derive(Default)]
pub struct StatsCollector {
min_max_opt: Option<(u64, u64)>,
num_rows: RowId,
// We measure the GCD of the difference between the values and the minimal value.
// This is the same as computing the difference between the values and the first value.
//
// This way, we can compress i64-converted-to-u64 (e.g. timestamp that were supplied in
// seconds, only to be converted in microseconds).
increment_gcd_opt: Option<(NonZeroU64, DividerU64)>,
first_value_opt: Option<u64>,
}
impl StatsCollector {
pub fn stats(&self) -> Stats {
let (min_value, max_value) = self.min_max_opt.unwrap_or((0u64, 0u64));
let increment_gcd = if let Some((increment_gcd, _)) = self.increment_gcd_opt {
increment_gcd
} else {
NonZeroU64::new(1u64).unwrap()
};
Stats {
min_value,
max_value,
num_rows: self.num_rows,
gcd: increment_gcd,
}
}
#[inline]
fn update_increment_gcd(&mut self, value: u64) {
let Some(first_value) = self.first_value_opt else {
// We set the first value and just quit.
self.first_value_opt = Some(value);
return;
};
let Some(non_zero_value) = NonZeroU64::new(value.abs_diff(first_value)) else {
// We can simply skip 0 values.
return;
};
let Some((gcd, gcd_divider)) = self.increment_gcd_opt else {
self.set_increment_gcd(non_zero_value);
return;
};
if gcd.get() == 1 {
// It won't see any update now.
return;
}
let remainder =
non_zero_value.get() - (gcd_divider.divide(non_zero_value.get())) * gcd.get();
if remainder == 0 {
return;
}
let new_gcd = compute_gcd(non_zero_value, gcd);
self.set_increment_gcd(new_gcd);
}
fn set_increment_gcd(&mut self, gcd: NonZeroU64) {
let new_divider = DividerU64::divide_by(gcd.get());
self.increment_gcd_opt = Some((gcd, new_divider));
}
pub fn collect(&mut self, value: u64) {
self.min_max_opt = Some(if let Some((min, max)) = self.min_max_opt {
(min.min(value), max.max(value))
} else {
(value, value)
});
self.num_rows += 1;
self.update_increment_gcd(value);
}
}
#[cfg(test)]
mod tests {
use std::num::NonZeroU64;
use crate::column_values::u64_based::stats_collector::{compute_gcd, StatsCollector};
use crate::column_values::u64_based::Stats;
fn compute_stats(vals: impl Iterator<Item = u64>) -> Stats {
let mut stats_collector = StatsCollector::default();
for val in vals {
stats_collector.collect(val);
}
stats_collector.stats()
}
fn find_gcd(vals: impl Iterator<Item = u64>) -> u64 {
compute_stats(vals).gcd.get()
}
#[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 test_gcd() {
assert_eq!(find_gcd([0].into_iter()), 1);
assert_eq!(find_gcd([0, 10].into_iter()), 10);
assert_eq!(find_gcd([10, 0].into_iter()), 10);
assert_eq!(find_gcd([].into_iter()), 1);
assert_eq!(find_gcd([15, 30, 5, 10].into_iter()), 5);
assert_eq!(find_gcd([15, 16, 10].into_iter()), 1);
assert_eq!(find_gcd([0, 5, 5, 5].into_iter()), 5);
assert_eq!(find_gcd([0, 0].into_iter()), 1);
assert_eq!(find_gcd([1, 10, 4, 1, 7, 10].into_iter()), 3);
assert_eq!(find_gcd([1, 10, 0, 4, 1, 7, 10].into_iter()), 1);
}
#[test]
fn test_stats() {
assert_eq!(
compute_stats([].into_iter()),
Stats {
gcd: NonZeroU64::new(1).unwrap(),
min_value: 0,
max_value: 0,
num_rows: 0
}
);
assert_eq!(
compute_stats([0, 1].into_iter()),
Stats {
gcd: NonZeroU64::new(1).unwrap(),
min_value: 0,
max_value: 1,
num_rows: 2
}
);
assert_eq!(
compute_stats([0, 1].into_iter()),
Stats {
gcd: NonZeroU64::new(1).unwrap(),
min_value: 0,
max_value: 1,
num_rows: 2
}
);
assert_eq!(
compute_stats([10, 20, 30].into_iter()),
Stats {
gcd: NonZeroU64::new(10).unwrap(),
min_value: 10,
max_value: 30,
num_rows: 3
}
);
assert_eq!(
compute_stats([10, 50, 10, 30].into_iter()),
Stats {
gcd: NonZeroU64::new(20).unwrap(),
min_value: 10,
max_value: 50,
num_rows: 4
}
);
assert_eq!(
compute_stats([10, 0, 30].into_iter()),
Stats {
gcd: NonZeroU64::new(10).unwrap(),
min_value: 0,
max_value: 30,
num_rows: 3
}
);
}
}

345
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use proptest::prelude::*;
use proptest::strategy::Strategy;
use proptest::{prop_oneof, proptest};
#[test]
fn test_serialize_and_load_simple() {
let mut buffer = Vec::new();
let vals = &[1u64, 2u64, 5u64];
serialize_u64_based_column_values(
&&vals[..],
&[CodecType::Bitpacked, CodecType::BlockwiseLinear],
&mut buffer,
)
.unwrap();
assert_eq!(buffer.len(), 7);
let col = load_u64_based_column_values::<u64>(OwnedBytes::new(buffer)).unwrap();
assert_eq!(col.num_vals(), 3);
assert_eq!(col.get_val(0), 1);
assert_eq!(col.get_val(1), 2);
assert_eq!(col.get_val(2), 5);
}
pub(crate) fn create_and_validate<TColumnCodec: ColumnCodec>(
vals: &[u64],
name: &str,
) -> Option<(f32, f32)> {
let mut stats_collector = StatsCollector::default();
let mut codec_estimator: TColumnCodec::Estimator = Default::default();
for val in vals.boxed_iter() {
stats_collector.collect(val);
codec_estimator.collect(val);
}
codec_estimator.finalize();
let stats = stats_collector.stats();
let estimation = codec_estimator.estimate(&stats)?;
let mut buffer = Vec::new();
codec_estimator
.serialize(&stats, vals.boxed_iter().as_mut(), &mut buffer)
.unwrap();
let actual_compression = buffer.len() as u64;
let reader = TColumnCodec::load(OwnedBytes::new(buffer)).unwrap();
assert_eq!(reader.num_vals(), vals.len() as u32);
for (doc, orig_val) in vals.iter().copied().enumerate() {
let val = reader.get_val(doc as u32);
assert_eq!(
val, orig_val,
"val `{val}` does not match orig_val {orig_val:?}, in data set {name}, data `{vals:?}`",
);
}
if !vals.is_empty() {
let test_rand_idx = rand::thread_rng().gen_range(0..=vals.len() - 1);
let expected_positions: Vec<u32> = vals
.iter()
.enumerate()
.filter(|(_, el)| **el == vals[test_rand_idx])
.map(|(pos, _)| pos as u32)
.collect();
let mut positions = Vec::new();
reader.get_docids_for_value_range(
vals[test_rand_idx]..=vals[test_rand_idx],
0..vals.len() as u32,
&mut positions,
);
assert_eq!(expected_positions, positions);
}
if actual_compression > 1000 {
assert!(relative_difference(estimation, actual_compression) < 0.10f32);
}
Some((
compression_rate(estimation, stats.num_rows),
compression_rate(actual_compression, stats.num_rows),
))
}
fn compression_rate(num_bytes: u64, num_values: u32) -> f32 {
num_bytes as f32 / (num_values as f32 * 8.0)
}
fn relative_difference(left: u64, right: u64) -> f32 {
let left = left as f32;
let right = right as f32;
2.0f32 * (left - right).abs() / (left + right)
}
proptest! {
#![proptest_config(ProptestConfig::with_cases(100))]
#[test]
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_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");
}
}
#[test]
fn test_small_blockwise_linear_example() {
create_and_validate::<BlockwiseLinearCodec>(
&[9223372036854775808, 9223370937344622593],
"proptest multilinearinterpol",
);
}
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..=10_000_u64).collect::<Vec<_>>();
data_and_names.push((data, "simple monotonically increasing"));
data_and_names.push((
vec![5, 6, 7, 8, 9, 10, 99, 100],
"offset in linear interpol",
));
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<C: ColumnCodec>() {
let codec_name = std::any::type_name::<C>();
for (data, dataset_name) in get_codec_test_datasets() {
let estimate_actual_opt: Option<(f32, f32)> =
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::<BitpackedCodec>();
}
#[test]
fn test_codec_interpolation() {
test_codec::<LinearCodec>();
}
#[test]
fn test_codec_multi_interpolation() {
test_codec::<BlockwiseLinearCodec>();
}
use super::*;
fn estimate<C: ColumnCodec>(vals: &[u64]) -> Option<f32> {
let mut stats_collector = StatsCollector::default();
let mut estimator = C::Estimator::default();
for &val in vals {
stats_collector.collect(val);
estimator.collect(val);
}
estimator.finalize();
let stats = stats_collector.stats();
let num_bytes = estimator.estimate(&stats)?;
if stats.num_rows == 0 {
return None;
}
Some(num_bytes as f32 / (8.0 * stats.num_rows as f32))
}
#[test]
fn estimation_good_interpolation_case() {
let data = (10..=20000_u64).collect::<Vec<_>>();
let linear_interpol_estimation = estimate::<LinearCodec>(&data).unwrap();
assert_le!(linear_interpol_estimation, 0.01);
let multi_linear_interpol_estimation = estimate::<BlockwiseLinearCodec>(&data).unwrap();
assert_le!(multi_linear_interpol_estimation, 0.2);
assert_lt!(linear_interpol_estimation, multi_linear_interpol_estimation);
let bitpacked_estimation = estimate::<BitpackedCodec>(&data).unwrap();
assert_lt!(linear_interpol_estimation, bitpacked_estimation);
}
#[test]
fn estimation_test_bad_interpolation_case_monotonically_increasing() {
let mut data: Vec<u64> = (201..=20000_u64).collect();
data.push(1_000_000);
// 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 = estimate::<LinearCodec>(&data[..]).unwrap();
assert_le!(linear_interpol_estimation, 0.35);
let bitpacked_estimation = estimate::<BitpackedCodec>(&data).unwrap();
assert_le!(bitpacked_estimation, 0.32);
assert_le!(bitpacked_estimation, linear_interpol_estimation);
}
#[test]
fn test_fast_field_codec_type_to_code() {
let mut count_codec = 0;
for code in 0..=255 {
if let Some(codec_type) = CodecType::try_from_code(code) {
assert_eq!(codec_type.to_code(), code);
count_codec += 1;
}
}
assert_eq!(count_codec, 3);
}
fn test_fastfield_gcd_i64_with_codec(codec_type: CodecType, 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::column_values::serialize_u64_based_column_values(
&&vals[..],
&[codec_type],
&mut buffer,
)?;
let buffer = OwnedBytes::new(buffer);
let column = crate::column_values::load_u64_based_column_values::<i64>(buffer.clone())?;
assert_eq!(column.get_val(0), -4000i64);
assert_eq!(column.get_val(1), -3000i64);
assert_eq!(column.get_val(2), -2000i64);
assert_eq!(column.max_value(), (num_vals as i64 - 5) * 1000);
assert_eq!(column.min_value(), -4000i64);
// Can't apply gcd
let mut buffer_without_gcd = Vec::new();
vals.pop();
vals.push(1001i64);
crate::column_values::serialize_u64_based_column_values(
&&vals[..],
&[codec_type],
&mut buffer_without_gcd,
)?;
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 &[
CodecType::Bitpacked,
CodecType::BlockwiseLinear,
CodecType::Linear,
] {
test_fastfield_gcd_i64_with_codec(codec_type, 5500)?;
}
Ok(())
}
fn test_fastfield_gcd_u64_with_codec(codec_type: CodecType, 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::column_values::serialize_u64_based_column_values(
&&vals[..],
&[codec_type],
&mut buffer,
)?;
let buffer = OwnedBytes::new(buffer);
let column = crate::column_values::load_u64_based_column_values::<u64>(buffer.clone())?;
assert_eq!(column.get_val(0), 1000u64);
assert_eq!(column.get_val(1), 2000u64);
assert_eq!(column.get_val(2), 3000u64);
assert_eq!(column.max_value(), num_vals as u64 * 1000);
assert_eq!(column.min_value(), 1000u64);
// Can't apply gcd
let mut buffer_without_gcd = Vec::new();
vals.pop();
vals.push(1001u64);
crate::column_values::serialize_u64_based_column_values(
&&vals[..],
&[codec_type],
&mut buffer_without_gcd,
)?;
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 &[
CodecType::Bitpacked,
CodecType::BlockwiseLinear,
CodecType::Linear,
] {
test_fastfield_gcd_u64_with_codec(codec_type, 5500)?;
}
Ok(())
}
#[test]
pub fn test_fastfield2() {
let test_fastfield = crate::column_values::serialize_and_load_u64_based_column_values::<u64>(
&&[100u64, 200u64, 300u64][..],
&ALL_U64_CODEC_TYPES,
);
assert_eq!(test_fastfield.get_val(0), 100);
assert_eq!(test_fastfield.get_val(1), 200);
assert_eq!(test_fastfield.get_val(2), 300);
}

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use std::fmt::Debug;
use std::net::Ipv6Addr;
use crate::value::NumericalType;
use crate::InvalidData;
/// The column type represents the column type and can fit on 6-bits.
///
/// - bits[0..3]: Column category type.
/// - bits[3..6]: Numerical type if necessary.
#[derive(Hash, Eq, PartialEq, Debug, Clone, Copy, Ord, PartialOrd)]
#[repr(u8)]
pub enum ColumnType {
I64 = 0u8,
U64 = 1u8,
F64 = 2u8,
Bytes = 10u8,
Str = 14u8,
Bool = 18u8,
IpAddr = 22u8,
DateTime = 26u8,
}
#[cfg(test)]
const COLUMN_TYPES: [ColumnType; 8] = [
ColumnType::I64,
ColumnType::U64,
ColumnType::F64,
ColumnType::Bytes,
ColumnType::Str,
ColumnType::Bool,
ColumnType::IpAddr,
ColumnType::DateTime,
];
impl ColumnType {
pub fn to_code(self) -> u8 {
self as u8
}
pub(crate) fn try_from_code(code: u8) -> Result<ColumnType, InvalidData> {
use ColumnType::*;
match code {
0u8 => Ok(I64),
1u8 => Ok(U64),
2u8 => Ok(F64),
10u8 => Ok(Bytes),
14u8 => Ok(Str),
18u8 => Ok(Bool),
22u8 => Ok(IpAddr),
26u8 => Ok(Self::DateTime),
_ => Err(InvalidData),
}
}
}
impl From<NumericalType> for ColumnType {
fn from(numerical_type: NumericalType) -> Self {
match numerical_type {
NumericalType::I64 => ColumnType::I64,
NumericalType::U64 => ColumnType::U64,
NumericalType::F64 => ColumnType::F64,
}
}
}
impl ColumnType {
pub fn numerical_type(&self) -> Option<NumericalType> {
match self {
ColumnType::I64 => Some(NumericalType::I64),
ColumnType::U64 => Some(NumericalType::U64),
ColumnType::F64 => Some(NumericalType::F64),
ColumnType::Bytes
| ColumnType::Str
| ColumnType::Bool
| ColumnType::IpAddr
| ColumnType::DateTime => None,
}
}
}
// TODO remove if possible
pub trait HasAssociatedColumnType: 'static + Debug + Send + Sync + Copy + PartialOrd {
fn column_type() -> ColumnType;
fn default_value() -> Self;
}
impl HasAssociatedColumnType for u64 {
fn column_type() -> ColumnType {
ColumnType::U64
}
fn default_value() -> Self {
0u64
}
}
impl HasAssociatedColumnType for i64 {
fn column_type() -> ColumnType {
ColumnType::I64
}
fn default_value() -> Self {
0i64
}
}
impl HasAssociatedColumnType for f64 {
fn column_type() -> ColumnType {
ColumnType::F64
}
fn default_value() -> Self {
Default::default()
}
}
impl HasAssociatedColumnType for bool {
fn column_type() -> ColumnType {
ColumnType::Bool
}
fn default_value() -> Self {
Default::default()
}
}
impl HasAssociatedColumnType for crate::DateTime {
fn column_type() -> ColumnType {
ColumnType::DateTime
}
fn default_value() -> Self {
Default::default()
}
}
impl HasAssociatedColumnType for Ipv6Addr {
fn column_type() -> ColumnType {
ColumnType::IpAddr
}
fn default_value() -> Self {
Ipv6Addr::from([0u8; 16])
}
}
/// Column types are grouped into different categories that
/// corresponds to the different types of `JsonValue` types.
///
/// The columnar writer will apply coercion rules to make sure that
/// at most one column exist per `ColumnTypeCategory`.
///
/// See also [README.md].
#[derive(Copy, Clone, Ord, PartialOrd, Eq, PartialEq, Hash, Debug)]
#[repr(u8)]
pub enum ColumnTypeCategory {
Bool,
Str,
Numerical,
DateTime,
Bytes,
IpAddr,
}
impl From<ColumnType> for ColumnTypeCategory {
fn from(column_type: ColumnType) -> Self {
match column_type {
ColumnType::I64 => ColumnTypeCategory::Numerical,
ColumnType::U64 => ColumnTypeCategory::Numerical,
ColumnType::F64 => ColumnTypeCategory::Numerical,
ColumnType::Bytes => ColumnTypeCategory::Bytes,
ColumnType::Str => ColumnTypeCategory::Str,
ColumnType::Bool => ColumnTypeCategory::Bool,
ColumnType::IpAddr => ColumnTypeCategory::IpAddr,
ColumnType::DateTime => ColumnTypeCategory::DateTime,
}
}
}
#[cfg(test)]
mod tests {
use std::collections::HashSet;
use super::*;
use crate::Cardinality;
#[test]
fn test_column_type_to_code() {
let mut column_type_set: HashSet<ColumnType> = HashSet::new();
for code in u8::MIN..=u8::MAX {
if let Ok(column_type) = ColumnType::try_from_code(code) {
assert_eq!(column_type.to_code(), code);
assert!(column_type_set.insert(column_type));
}
}
assert_eq!(column_type_set.len(), super::COLUMN_TYPES.len());
}
#[test]
fn test_column_category_sort_consistent_with_column_type_sort() {
// This is a very important property because we
// we need to serialize colunmn in the right order.
let mut column_types: Vec<ColumnType> = super::COLUMN_TYPES.iter().copied().collect();
column_types.sort_by_key(|col| col.to_code());
let column_categories: Vec<ColumnTypeCategory> = column_types
.into_iter()
.map(ColumnTypeCategory::from)
.collect();
for (prev, next) in column_categories.iter().zip(column_categories.iter()) {
assert!(prev <= next);
}
}
#[test]
fn test_cardinality_to_code() {
let mut num_cardinality = 0;
for code in u8::MIN..=u8::MAX {
if let Ok(cardinality) = Cardinality::try_from_code(code) {
assert_eq!(cardinality.to_code(), code);
num_cardinality += 1;
}
}
assert_eq!(num_cardinality, 3);
}
}

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use crate::InvalidData;
pub const VERSION_FOOTER_NUM_BYTES: usize = MAGIC_BYTES.len() + std::mem::size_of::<u32>();
/// We end the file by these 4 bytes just to somewhat identify that
/// this is indeed a columnar file.
const MAGIC_BYTES: [u8; 4] = [2, 113, 119, 066];
pub fn footer() -> [u8; VERSION_FOOTER_NUM_BYTES] {
let mut footer_bytes = [0u8; VERSION_FOOTER_NUM_BYTES];
footer_bytes[0..4].copy_from_slice(&Version::V1.to_bytes());
footer_bytes[4..8].copy_from_slice(&MAGIC_BYTES[..]);
footer_bytes
}
pub fn parse_footer(footer_bytes: [u8; VERSION_FOOTER_NUM_BYTES]) -> Result<Version, InvalidData> {
if footer_bytes[4..8] != MAGIC_BYTES {
return Err(InvalidData);
}
Version::try_from_bytes(footer_bytes[0..4].try_into().unwrap())
}
#[derive(Debug, Copy, Clone, Eq, PartialEq)]
#[repr(u32)]
pub enum Version {
V1 = 1u32,
}
impl Version {
fn to_bytes(&self) -> [u8; 4] {
(*self as u32).to_le_bytes()
}
fn try_from_bytes(bytes: [u8; 4]) -> Result<Version, InvalidData> {
let code = u32::from_le_bytes(bytes);
match code {
1u32 => Ok(Version::V1),
_ => Err(InvalidData),
}
}
}
#[cfg(test)]
mod tests {
use std::collections::HashSet;
use super::*;
#[test]
fn test_footer_dserialization() {
let parsed_version: Version = parse_footer(footer()).unwrap();
assert_eq!(Version::V1, parsed_version);
}
#[test]
fn test_version_serialization() {
let version_to_tests: Vec<u32> = [0, 1 << 8, 1 << 16, 1 << 24]
.iter()
.copied()
.flat_map(|offset| (0..255).map(move |el| el + offset))
.collect();
let mut valid_versions: HashSet<u32> = HashSet::default();
for &i in &version_to_tests {
let version_res = Version::try_from_bytes(i.to_le_bytes());
if let Ok(version) = version_res {
assert_eq!(version, Version::V1);
assert_eq!(version.to_bytes(), i.to_le_bytes());
valid_versions.insert(i);
}
}
assert_eq!(valid_versions.len(), 1);
}
}

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columnar/src/columnar/merge/merge_dict_column.rs Normal file
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use std::io::{self, Write};
use common::CountingWriter;
use sstable::{SSTable, TermOrdinal};
use super::term_merger::TermMerger;
use crate::column::serialize_column_mappable_to_u64;
use crate::column_index::SerializableColumnIndex;
use crate::iterable::Iterable;
use crate::BytesColumn;
// Serialize [Dictionary, Column, dictionary num bytes U32::LE]
// Column: [Column Index, Column Values, column index num bytes U32::LE]
pub fn merge_bytes_or_str_column(
column_index: SerializableColumnIndex<'_>,
bytes_columns: &[BytesColumn],
output: &mut impl Write,
) -> io::Result<()> {
// Serialize dict and generate mapping for values
let mut output = CountingWriter::wrap(output);
let term_ord_mapping = serialize_merged_dict(bytes_columns, &mut output)?;
let dictionary_num_bytes: u32 = output.written_bytes() as u32;
let output = output.finish();
let remapped_term_ordinals_values = RemappedTermOrdinalsValues {
bytes_columns,
term_ord_mapping: &term_ord_mapping,
};
serialize_column_mappable_to_u64(column_index, &remapped_term_ordinals_values, output)?;
// serialize_bytes_or_str_column(column_index, bytes_columns, &term_ord_mapping, output)?;
output.write_all(&dictionary_num_bytes.to_le_bytes())?;
Ok(())
}
struct RemappedTermOrdinalsValues<'a> {
bytes_columns: &'a [BytesColumn],
term_ord_mapping: &'a TermOrdinalMapping,
}
impl<'a> Iterable for RemappedTermOrdinalsValues<'a> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
let iter = self
.bytes_columns
.iter()
.enumerate()
.flat_map(|(segment_ord, byte_column)| {
let segment_ord = self.term_ord_mapping.get_segment(segment_ord);
byte_column
.ords()
.values
.iter()
.map(move |term_ord| segment_ord[term_ord as usize])
});
// TODO see if we can better decompose the mapping / and the stacking
Box::new(iter)
}
}
fn serialize_merged_dict(
bytes_columns: &[BytesColumn],
output: &mut impl Write,
) -> io::Result<TermOrdinalMapping> {
let mut term_ord_mapping = TermOrdinalMapping::default();
let mut field_term_streams = Vec::new();
for column in bytes_columns {
term_ord_mapping.add_segment(column.dictionary.num_terms());
let terms = column.dictionary.stream()?;
field_term_streams.push(terms);
}
let mut merged_terms = TermMerger::new(field_term_streams);
let mut sstable_builder = sstable::VoidSSTable::writer(output);
let mut current_term_ord = 0;
while merged_terms.advance() {
let term_bytes: &[u8] = merged_terms.key();
sstable_builder.insert(term_bytes, &())?;
for (segment_ord, from_term_ord) in merged_terms.matching_segments() {
term_ord_mapping.register_from_to(segment_ord, from_term_ord, current_term_ord);
}
current_term_ord += 1;
}
sstable_builder.finish()?;
Ok(term_ord_mapping)
}
#[derive(Default)]
struct TermOrdinalMapping {
per_segment_new_term_ordinals: Vec<Vec<TermOrdinal>>,
}
impl TermOrdinalMapping {
fn add_segment(&mut self, max_term_ord: usize) {
self.per_segment_new_term_ordinals
.push(vec![TermOrdinal::default(); max_term_ord as usize]);
}
fn register_from_to(&mut self, segment_ord: usize, from_ord: TermOrdinal, to_ord: TermOrdinal) {
self.per_segment_new_term_ordinals[segment_ord][from_ord as usize] = to_ord;
}
fn get_segment(&self, segment_ord: usize) -> &[TermOrdinal] {
&(self.per_segment_new_term_ordinals[segment_ord])[..]
}
}

60
columnar/src/columnar/merge/merge_mapping.rs Normal file
View File

@@ -0,0 +1,60 @@
use std::ops::Range;
use crate::{column, ColumnarReader, RowId};
pub struct StackMergeOrder {
// This does not start at 0. The first row is the number of
// rows in the first columnar.
cumulated_row_ids: Vec<RowId>,
}
impl StackMergeOrder {
pub fn stack(columnars: &[&ColumnarReader]) -> StackMergeOrder {
let mut cumulated_row_ids: Vec<RowId> = Vec::with_capacity(columnars.len());
let mut cumulated_row_id = 0;
for columnar in columnars {
cumulated_row_id += columnar.num_rows();
cumulated_row_ids.push(cumulated_row_id);
}
StackMergeOrder { cumulated_row_ids }
}
pub fn num_rows(&self) -> RowId {
self.cumulated_row_ids.last().copied().unwrap_or(0)
}
pub fn offset(&self, columnar_id: usize) -> RowId {
if columnar_id == 0 {
return 0;
}
self.cumulated_row_ids[columnar_id - 1]
}
pub fn columnar_range(&self, columnar_id: usize) -> Range<RowId> {
self.offset(columnar_id)..self.offset(columnar_id + 1)
}
}
pub enum MergeRowOrder {
/// Columnar tables are simply stacked one above the other.
/// If the i-th columnar_readers has n_rows_i rows, then
/// in the resulting columnar,
/// rows [r0..n_row_0) contains the row of columnar_readers[0], in ordder
/// rows [n_row_0..n_row_0 + n_row_1 contains the row of columnar_readers[1], in order.
/// ..
Stack(StackMergeOrder),
/// Some more complex mapping, that can interleaves rows from the different readers and
/// possibly drop rows.
Complex(()),
}
impl MergeRowOrder {
pub fn num_rows(&self) -> RowId {
match self {
MergeRowOrder::Stack(stack_row_order) => stack_row_order.num_rows(),
MergeRowOrder::Complex(_) => {
todo!()
}
}
}
}

225
columnar/src/columnar/merge/mod.rs Normal file
View File

@@ -0,0 +1,225 @@
mod merge_dict_column;
mod merge_mapping;
mod term_merger;
// mod sorted_doc_id_column;
use std::collections::{BTreeMap, HashMap, HashSet};
use std::io;
use std::net::Ipv6Addr;
use std::sync::Arc;
pub use merge_mapping::{MergeRowOrder, StackMergeOrder};
use super::writer::ColumnarSerializer;
use crate::column::{serialize_column_mappable_to_u128, serialize_column_mappable_to_u64};
use crate::column_index::stack_column_index;
use crate::columnar::column_type::ColumnTypeCategory;
use crate::columnar::merge::merge_dict_column::merge_bytes_or_str_column;
use crate::columnar::writer::CompatibleNumericalTypes;
use crate::columnar::ColumnarReader;
use crate::dynamic_column::DynamicColumn;
use crate::{
BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, MonotonicallyMappableToU128,
NumericalType, NumericalValue,
};
pub fn merge_columnar(
columnar_readers: &[&ColumnarReader],
mapping: MergeRowOrder,
output: &mut impl io::Write,
) -> io::Result<()> {
let mut serializer = ColumnarSerializer::new(output);
let columns_to_merge = group_columns_for_merge(columnar_readers)?;
for ((column_name, column_type), columns) in columns_to_merge {
let mut column_serializer =
serializer.serialize_column(column_name.as_bytes(), column_type);
merge_column(column_type, columns, &mapping, &mut column_serializer)?;
}
serializer.finalize(mapping.num_rows())?;
Ok(())
}
fn dynamic_column_to_u64_monotonic(dynamic_column: DynamicColumn) -> Option<Column<u64>> {
match dynamic_column {
DynamicColumn::Bool(column) => Some(column.to_u64_monotonic()),
DynamicColumn::I64(column) => Some(column.to_u64_monotonic()),
DynamicColumn::U64(column) => Some(column.to_u64_monotonic()),
DynamicColumn::F64(column) => Some(column.to_u64_monotonic()),
DynamicColumn::DateTime(column) => Some(column.to_u64_monotonic()),
DynamicColumn::IpAddr(_) | DynamicColumn::Bytes(_) | DynamicColumn::Str(_) => None,
}
}
pub fn merge_column(
column_type: ColumnType,
columns: Vec<Option<DynamicColumn>>,
merge_row_order: &MergeRowOrder,
wrt: &mut impl io::Write,
) -> io::Result<()> {
match column_type {
ColumnType::I64
| ColumnType::U64
| ColumnType::F64
| ColumnType::DateTime
| ColumnType::Bool => {
let mut column_indexes: Vec<Option<ColumnIndex>> = Vec::with_capacity(columns.len());
let mut column_values: Vec<Arc<dyn ColumnValues>> = Vec::with_capacity(columns.len());
for dynamic_column_opt in columns {
if let Some(Column { idx, values }) =
dynamic_column_opt.and_then(dynamic_column_to_u64_monotonic)
{
column_indexes.push(Some(idx));
column_values.push(values);
} else {
column_indexes.push(None);
}
}
let merged_column_index =
crate::column_index::stack_column_index(&column_indexes[..], merge_row_order);
serialize_column_mappable_to_u64(merged_column_index, &&column_values[..], wrt)?;
}
ColumnType::IpAddr => {
let mut column_indexes: Vec<Option<ColumnIndex>> = Vec::with_capacity(columns.len());
let mut column_values: Vec<Arc<dyn ColumnValues<Ipv6Addr>>> =
Vec::with_capacity(columns.len());
let mut num_values = 0;
for dynamic_column_opt in columns {
if let Some(DynamicColumn::IpAddr(Column { idx, values })) = dynamic_column_opt {
num_values += values.num_vals();
column_indexes.push(Some(idx));
column_values.push(values);
} else {
column_indexes.push(None);
}
}
let merged_column_index =
crate::column_index::stack_column_index(&column_indexes[..], merge_row_order);
serialize_column_mappable_to_u128(
merged_column_index,
&&column_values[..],
num_values,
wrt,
)?;
}
ColumnType::Bytes | ColumnType::Str => {
let mut column_indexes: Vec<Option<ColumnIndex>> = Vec::with_capacity(columns.len());
let mut bytes_columns: Vec<BytesColumn> = Vec::with_capacity(columns.len());
for dynamic_column_opt in columns {
match dynamic_column_opt {
Some(DynamicColumn::Str(str_column)) => {
column_indexes.push(Some(str_column.term_ord_column.idx.clone()));
bytes_columns.push(str_column.into());
}
Some(DynamicColumn::Bytes(bytes_column)) => {
column_indexes.push(Some(bytes_column.term_ord_column.idx.clone()));
bytes_columns.push(bytes_column);
}
_ => column_indexes.push(None),
}
}
let merged_column_index =
crate::column_index::stack_column_index(&column_indexes[..], merge_row_order);
merge_bytes_or_str_column(merged_column_index, &bytes_columns, wrt)?;
}
}
Ok(())
}
fn group_columns_for_merge(
columnar_readers: &[&ColumnarReader],
) -> io::Result<BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>>> {
// Each column name may have multiple types of column associated.
// For merging we are interested in the same column type category since they can be merged.
let mut columns_grouped: HashMap<(String, ColumnTypeCategory), Vec<Option<DynamicColumn>>> =
HashMap::new();
let num_columnars = columnar_readers.len();
for (columnar_id, columnar_reader) in columnar_readers.iter().enumerate() {
let column_name_and_handle = columnar_reader.list_columns()?;
for (column_name, handle) in column_name_and_handle {
let column_type_category: ColumnTypeCategory = handle.column_type().into();
let columns = columns_grouped
.entry((column_name, column_type_category))
.or_insert_with(|| vec![None; num_columnars]);
let column = handle.open()?;
columns[columnar_id] = Some(column);
}
}
let mut merge_columns: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
BTreeMap::default();
for ((column_name, col_category), mut columns) in columns_grouped {
if col_category == ColumnTypeCategory::Numerical {
coerce_numerical_columns_to_same_type(&mut columns);
}
let column_type = columns
.iter()
.flatten()
.map(|col| col.column_type())
.next()
.unwrap();
merge_columns.insert((column_name, column_type), columns);
}
Ok(merge_columns)
}
/// Coerce a set of numerical columns to the same type.
///
/// If all columns are already from the same type, keep this type
/// (even if they could all be coerced to i64).
fn coerce_numerical_columns_to_same_type(columns: &mut [Option<DynamicColumn>]) {
let mut column_types: HashSet<NumericalType> = HashSet::default();
let mut compatible_numerical_types = CompatibleNumericalTypes::default();
for column in columns.iter().flatten() {
let min_value: NumericalValue;
let max_value: NumericalValue;
match column {
DynamicColumn::I64(column) => {
min_value = column.min_value().into();
max_value = column.max_value().into();
}
DynamicColumn::U64(column) => {
min_value = column.min_value().into();
max_value = column.min_value().into();
}
DynamicColumn::F64(column) => {
min_value = column.min_value().into();
max_value = column.min_value().into();
}
DynamicColumn::Bool(_)
| DynamicColumn::IpAddr(_)
| DynamicColumn::DateTime(_)
| DynamicColumn::Bytes(_)
| DynamicColumn::Str(_) => {
panic!("We expected only numerical columns.");
}
}
column_types.insert(column.column_type().numerical_type().unwrap());
compatible_numerical_types.accept_value(min_value);
compatible_numerical_types.accept_value(max_value);
}
if column_types.len() <= 1 {
// No need to do anything. The columns are already all from the same type.
// This is necessary to let use force a given type.
// TODO This works in a world where we do not allow a change of schema,
// but in the future, we will have to pass some kind of schema to enforce
// the logic.
return;
}
let coerce_type = compatible_numerical_types.to_numerical_type();
for column_opt in columns.iter_mut() {
if let Some(column) = column_opt.take() {
*column_opt = column.coerce_numerical(coerce_type);
}
}
}
#[cfg(test)]
mod tests;

3
src/indexer/sorted_doc_id_column.rs → columnar/src/columnar/merge/sorted_doc_id_column.rs
View File

@@ -4,7 +4,6 @@ use fastfield_codecs::Column;
use itertools::Itertools;
use crate::indexer::doc_id_mapping::SegmentDocIdMapping;
use crate::schema::Field;
use crate::SegmentReader;
pub(crate) struct RemappedDocIdColumn<'a> {
@@ -41,7 +40,7 @@ impl<'a> RemappedDocIdColumn<'a> {
pub(crate) fn new(
readers: &'a [SegmentReader],
doc_id_mapping: &'a SegmentDocIdMapping,
field: Field,
field: &str,
) -> Self {
let (min_value, max_value) = readers
.iter()

3
src/indexer/sorted_doc_id_multivalue_column.rs → columnar/src/columnar/merge/sorted_doc_id_multivalue_column.rs
View File

@@ -5,7 +5,6 @@ use fastfield_codecs::Column;
use super::flat_map_with_buffer::FlatMapWithBufferIter;
use crate::fastfield::{MultiValueIndex, MultiValuedFastFieldReader};
use crate::indexer::doc_id_mapping::SegmentDocIdMapping;
use crate::schema::Field;
use crate::{DocAddress, SegmentReader};
pub(crate) struct RemappedDocIdMultiValueColumn<'a> {
@@ -20,7 +19,7 @@ impl<'a> RemappedDocIdMultiValueColumn<'a> {
pub(crate) fn new(
readers: &'a [SegmentReader],
doc_id_mapping: &'a SegmentDocIdMapping,
field: Field,
field: &str,
) -> Self {
// Our values are bitpacked and we need to know what should be
// our bitwidth and our minimum value before serializing any values.

107
columnar/src/columnar/merge/term_merger.rs Normal file
View File

@@ -0,0 +1,107 @@
use std::cmp::Ordering;
use std::collections::BinaryHeap;
use sstable::TermOrdinal;
use crate::Streamer;
pub struct HeapItem<'a> {
pub streamer: Streamer<'a>,
pub segment_ord: usize,
}
impl<'a> PartialEq for HeapItem<'a> {
fn eq(&self, other: &Self) -> bool {
self.segment_ord == other.segment_ord
}
}
impl<'a> Eq for HeapItem<'a> {}
impl<'a> PartialOrd for HeapItem<'a> {
fn partial_cmp(&self, other: &HeapItem<'a>) -> Option<Ordering> {
Some(self.cmp(other))
}
}
impl<'a> Ord for HeapItem<'a> {
fn cmp(&self, other: &HeapItem<'a>) -> Ordering {
(&other.streamer.key(), &other.segment_ord).cmp(&(&self.streamer.key(), &self.segment_ord))
}
}
/// Given a list of sorted term streams,
/// returns an iterator over sorted unique terms.
///
/// The item yield is actually a pair with
/// - the term
/// - a slice with the ordinal of the segments containing
/// the terms.
pub struct TermMerger<'a> {
heap: BinaryHeap<HeapItem<'a>>,
current_streamers: Vec<HeapItem<'a>>,
}
impl<'a> TermMerger<'a> {
/// Stream of merged term dictionary
pub fn new(streams: Vec<Streamer<'a>>) -> TermMerger<'a> {
TermMerger {
heap: BinaryHeap::new(),
current_streamers: streams
.into_iter()
.enumerate()
.map(|(ord, streamer)| HeapItem {
streamer,
segment_ord: ord,
})
.collect(),
}
}
pub(crate) fn matching_segments<'b: 'a>(
&'b self,
) -> impl 'b + Iterator<Item = (usize, TermOrdinal)> {
self.current_streamers
.iter()
.map(|heap_item| (heap_item.segment_ord, heap_item.streamer.term_ord()))
}
fn advance_segments(&mut self) {
let streamers = &mut self.current_streamers;
let heap = &mut self.heap;
for mut heap_item in streamers.drain(..) {
if heap_item.streamer.advance() {
heap.push(heap_item);
}
}
}
/// Advance the term iterator to the next term.
/// Returns true if there is indeed another term
/// False if there is none.
pub fn advance(&mut self) -> bool {
self.advance_segments();
if let Some(head) = self.heap.pop() {
self.current_streamers.push(head);
while let Some(next_streamer) = self.heap.peek() {
if self.current_streamers[0].streamer.key() != next_streamer.streamer.key() {
break;
}
let next_heap_it = self.heap.pop().unwrap(); // safe : we peeked beforehand
self.current_streamers.push(next_heap_it);
}
true
} else {
false
}
}
/// Returns the current term.
///
/// This method may be called
/// if and only if advance() has been called before
/// and "true" was returned.
pub fn key(&self) -> &[u8] {
self.current_streamers[0].streamer.key()
}
}

252
columnar/src/columnar/merge/tests.rs Normal file
View File

@@ -0,0 +1,252 @@
use super::*;
use crate::{Cardinality, ColumnarWriter, HasAssociatedColumnType, RowId};
fn make_columnar<T: Into<NumericalValue> + HasAssociatedColumnType + Copy>(
column_name: &str,
vals: &[T],
) -> ColumnarReader {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_column_type(column_name, T::column_type(), false);
for (row_id, val) in vals.iter().copied().enumerate() {
dataframe_writer.record_numerical(row_id as RowId, column_name, val.into());
}
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer
.serialize(vals.len() as RowId, &mut buffer)
.unwrap();
ColumnarReader::open(buffer).unwrap()
}
#[test]
fn test_column_coercion_to_u64() {
// i64 type
let columnar1 = make_columnar("numbers", &[1i64]);
// u64 type
let columnar2 = make_columnar("numbers", &[u64::MAX]);
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
assert_eq!(column_map.len(), 1);
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
}
#[test]
fn test_column_no_coercion_if_all_the_same() {
let columnar1 = make_columnar("numbers", &[1u64]);
let columnar2 = make_columnar("numbers", &[2u64]);
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
assert_eq!(column_map.len(), 1);
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
}
#[test]
fn test_column_coercion_to_i64() {
let columnar1 = make_columnar("numbers", &[-1i64]);
let columnar2 = make_columnar("numbers", &[2u64]);
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
assert_eq!(column_map.len(), 1);
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
}
#[test]
fn test_missing_column() {
let columnar1 = make_columnar("numbers", &[-1i64]);
let columnar2 = make_columnar("numbers2", &[2u64]);
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
assert_eq!(column_map.len(), 2);
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
{
let columns = column_map
.get(&("numbers".to_string(), ColumnType::I64))
.unwrap();
assert!(columns[0].is_some());
assert!(columns[1].is_none());
}
{
let columns = column_map
.get(&("numbers2".to_string(), ColumnType::U64))
.unwrap();
assert!(columns[0].is_none());
assert!(columns[1].is_some());
}
}
fn make_numerical_columnar_multiple_columns(
columns: &[(&str, &[&[NumericalValue]])],
) -> ColumnarReader {
let mut dataframe_writer = ColumnarWriter::default();
for (column_name, column_values) in columns {
for (row_id, vals) in column_values.iter().enumerate() {
for val in vals.iter() {
dataframe_writer.record_numerical(row_id as u32, column_name, *val);
}
}
}
let num_rows = columns
.iter()
.map(|(_, val_rows)| val_rows.len() as RowId)
.max()
.unwrap_or(0u32);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
ColumnarReader::open(buffer).unwrap()
}
fn make_byte_columnar_multiple_columns(columns: &[(&str, &[&[&[u8]]])]) -> ColumnarReader {
let mut dataframe_writer = ColumnarWriter::default();
for (column_name, column_values) in columns {
for (row_id, vals) in column_values.iter().enumerate() {
for val in vals.iter() {
dataframe_writer.record_bytes(row_id as u32, column_name, *val);
}
}
}
let num_rows = columns
.iter()
.map(|(_, val_rows)| val_rows.len() as RowId)
.max()
.unwrap_or(0u32);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
ColumnarReader::open(buffer).unwrap()
}
fn make_text_columnar_multiple_columns(columns: &[(&str, &[&[&str]])]) -> ColumnarReader {
let mut dataframe_writer = ColumnarWriter::default();
for (column_name, column_values) in columns {
for (row_id, vals) in column_values.iter().enumerate() {
for val in vals.iter() {
dataframe_writer.record_str(row_id as u32, column_name, *val);
}
}
}
let num_rows = columns
.iter()
.map(|(_, val_rows)| val_rows.len() as RowId)
.max()
.unwrap_or(0u32);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
ColumnarReader::open(buffer).unwrap()
}
#[test]
fn test_merge_columnar_numbers() {
let columnar1 =
make_numerical_columnar_multiple_columns(&[("numbers", &[&[NumericalValue::from(-1f64)]])]);
let columnar2 = make_numerical_columnar_multiple_columns(&[(
"numbers",
&[&[], &[NumericalValue::from(-3f64)]],
)]);
let mut buffer = Vec::new();
let columnars = &[&columnar1, &columnar2];
let stack_merge_order = StackMergeOrder::stack(columnars);
crate::columnar::merge_columnar(
columnars,
MergeRowOrder::Stack(stack_merge_order),
&mut buffer,
)
.unwrap();
let columnar_reader = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar_reader.num_rows(), 3);
assert_eq!(columnar_reader.num_columns(), 1);
let cols = columnar_reader.read_columns("numbers").unwrap();
let dynamic_column = cols[0].open().unwrap();
let DynamicColumn::F64(vals) = dynamic_column else { panic!() };
assert_eq!(vals.get_cardinality(), Cardinality::Optional);
assert_eq!(vals.first(0u32), Some(-1f64));
assert_eq!(vals.first(1u32), None);
assert_eq!(vals.first(2u32), Some(-3f64));
}
#[test]
fn test_merge_columnar_texts() {
let columnar1 = make_text_columnar_multiple_columns(&[("texts", &[&["a"]])]);
let columnar2 = make_text_columnar_multiple_columns(&[("texts", &[&[], &["b"]])]);
let mut buffer = Vec::new();
let columnars = &[&columnar1, &columnar2];
let stack_merge_order = StackMergeOrder::stack(columnars);
crate::columnar::merge_columnar(
columnars,
MergeRowOrder::Stack(stack_merge_order),
&mut buffer,
)
.unwrap();
let columnar_reader = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar_reader.num_rows(), 3);
assert_eq!(columnar_reader.num_columns(), 1);
let cols = columnar_reader.read_columns("texts").unwrap();
let dynamic_column = cols[0].open().unwrap();
let DynamicColumn::Str(vals) = dynamic_column else { panic!() };
let get_str_for_ord = |ord| {
let mut out = String::new();
vals.ord_to_str(ord, &mut out).unwrap();
out
};
assert_eq!(vals.dictionary.num_terms(), 2);
assert_eq!(get_str_for_ord(0), "a");
assert_eq!(get_str_for_ord(1), "b");
let get_str_for_row = |row_id| {
let term_ords: Vec<u64> = vals.term_ords(row_id).collect();
assert!(term_ords.len() <= 1);
let mut out = String::new();
if term_ords.len() == 1 {
vals.ord_to_str(term_ords[0], &mut out).unwrap();
}
out
};
assert_eq!(get_str_for_row(0), "a");
assert_eq!(get_str_for_row(1), "");
assert_eq!(get_str_for_row(2), "b");
}
#[test]
fn test_merge_columnar_byte() {
let columnar1 = make_byte_columnar_multiple_columns(&[("bytes", &[&[b"bbbb"], &[b"baaa"]])]);
let columnar2 = make_byte_columnar_multiple_columns(&[("bytes", &[&[], &[b"a"]])]);
let mut buffer = Vec::new();
let columnars = &[&columnar1, &columnar2];
let stack_merge_order = StackMergeOrder::stack(columnars);
crate::columnar::merge_columnar(
columnars,
MergeRowOrder::Stack(stack_merge_order),
&mut buffer,
)
.unwrap();
let columnar_reader = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar_reader.num_rows(), 4);
assert_eq!(columnar_reader.num_columns(), 1);
let cols = columnar_reader.read_columns("bytes").unwrap();
let dynamic_column = cols[0].open().unwrap();
let DynamicColumn::Bytes(vals) = dynamic_column else { panic!() };
let get_bytes_for_ord = |ord| {
let mut out = Vec::new();
vals.ord_to_bytes(ord, &mut out).unwrap();
out
};
assert_eq!(vals.dictionary.num_terms(), 3);
assert_eq!(get_bytes_for_ord(0), b"a");
assert_eq!(get_bytes_for_ord(1), b"baaa");
assert_eq!(get_bytes_for_ord(2), b"bbbb");
let get_bytes_for_row = |row_id| {
let term_ords: Vec<u64> = vals.term_ords(row_id).collect();
assert!(term_ords.len() <= 1);
let mut out = Vec::new();
if term_ords.len() == 1 {
vals.ord_to_bytes(term_ords[0], &mut out).unwrap();
}
out
};
assert_eq!(get_bytes_for_row(0), b"bbbb");
assert_eq!(get_bytes_for_row(1), b"baaa");
assert_eq!(get_bytes_for_row(2), b"");
assert_eq!(get_bytes_for_row(3), b"a");
}

1
columnar/src/columnar/merge_index.rs Normal file
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11
columnar/src/columnar/mod.rs Normal file
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mod column_type;
mod format_version;
mod merge;
mod merge_index;
mod reader;
mod writer;
pub use column_type::{ColumnType, HasAssociatedColumnType};
pub use merge::{merge_columnar, MergeRowOrder, StackMergeOrder};
pub use reader::ColumnarReader;
pub use writer::ColumnarWriter;

171
columnar/src/columnar/reader/mod.rs Normal file
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use std::{io, mem};
use common::file_slice::FileSlice;
use common::BinarySerializable;
use sstable::{Dictionary, RangeSSTable};
use crate::columnar::{format_version, ColumnType};
use crate::dynamic_column::DynamicColumnHandle;
use crate::RowId;
fn io_invalid_data(msg: String) -> io::Error {
io::Error::new(io::ErrorKind::InvalidData, msg)
}
/// The ColumnarReader makes it possible to access a set of columns
/// associated to field names.
#[derive(Clone)]
pub struct ColumnarReader {
column_dictionary: Dictionary<RangeSSTable>,
column_data: FileSlice,
num_rows: RowId,
}
impl ColumnarReader {
/// Opens a new Columnar file.
pub fn open<F>(file_slice: F) -> io::Result<ColumnarReader>
where FileSlice: From<F> {
Self::open_inner(file_slice.into())
}
fn open_inner(file_slice: FileSlice) -> io::Result<ColumnarReader> {
let (file_slice_without_sstable_len, footer_slice) = file_slice
.split_from_end(mem::size_of::<u64>() + 4 + format_version::VERSION_FOOTER_NUM_BYTES);
let footer_bytes = footer_slice.read_bytes()?;
let sstable_len = u64::deserialize(&mut &footer_bytes[0..8])?;
let num_rows = u32::deserialize(&mut &footer_bytes[8..12])?;
let version_footer_bytes: [u8; format_version::VERSION_FOOTER_NUM_BYTES] =
footer_bytes[12..].try_into().unwrap();
let _version = format_version::parse_footer(version_footer_bytes)?;
let (column_data, sstable) =
file_slice_without_sstable_len.split_from_end(sstable_len as usize);
let column_dictionary = Dictionary::open(sstable)?;
Ok(ColumnarReader {
column_dictionary,
column_data,
num_rows,
})
}
pub fn num_rows(&self) -> RowId {
self.num_rows
}
// TODO Add unit tests
pub fn list_columns(&self) -> io::Result<Vec<(String, DynamicColumnHandle)>> {
let mut stream = self.column_dictionary.stream()?;
let mut results = Vec::new();
while stream.advance() {
let key_bytes: &[u8] = stream.key();
let column_code: u8 = key_bytes.last().cloned().unwrap();
let column_type: ColumnType = ColumnType::try_from_code(column_code)
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
let range = stream.value().clone();
let column_name =
// The last two bytes are respectively the 0u8 separator and the column_type.
String::from_utf8_lossy(&key_bytes[..key_bytes.len() - 2]).to_string();
let file_slice = self
.column_data
.slice(range.start as usize..range.end as usize);
let column_handle = DynamicColumnHandle {
file_slice,
column_type,
};
results.push((column_name, column_handle));
}
Ok(results)
}
/// Get all columns for the given column name.
///
/// There can be more than one column associated to a given column name, provided they have
/// different types.
pub fn read_columns(&self, column_name: &str) -> io::Result<Vec<DynamicColumnHandle>> {
// Each column is a associated to a given `column_key`,
// that starts by `column_name\0column_header`.
//
// Listing the columns associated to the given column name is therefore equivalent to
// listing `column_key` with the prefix `column_name\0`.
//
// This is in turn equivalent to searching for the range
// `[column_name,\0`..column_name\1)`.
// TODO can we get some more generic `prefix(..)` logic in the dictioanry.
let mut start_key = column_name.to_string();
start_key.push('\0');
let mut end_key = column_name.to_string();
end_key.push(1u8 as char);
let mut stream = self
.column_dictionary
.range()
.ge(start_key.as_bytes())
.lt(end_key.as_bytes())
.into_stream()?;
let mut results = Vec::new();
while stream.advance() {
let key_bytes: &[u8] = stream.key();
assert!(key_bytes.starts_with(start_key.as_bytes()));
let column_code: u8 = key_bytes.last().cloned().unwrap();
let column_type = ColumnType::try_from_code(column_code)
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
let range = stream.value().clone();
let file_slice = self
.column_data
.slice(range.start as usize..range.end as usize);
let dynamic_column_handle = DynamicColumnHandle {
file_slice,
column_type,
};
results.push(dynamic_column_handle);
}
Ok(results)
}
/// Return the number of columns in the columnar.
pub fn num_columns(&self) -> usize {
self.column_dictionary.num_terms()
}
}
#[cfg(test)]
mod tests {
use crate::{ColumnType, ColumnarReader, ColumnarWriter};
#[test]
fn test_list_columns() {
let mut columnar_writer = ColumnarWriter::default();
columnar_writer.record_column_type("col1", ColumnType::Str, false);
columnar_writer.record_column_type("col2", ColumnType::U64, false);
let mut buffer = Vec::new();
columnar_writer.serialize(1, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
let columns = columnar.list_columns().unwrap();
assert_eq!(columns.len(), 2);
assert_eq!(&columns[0].0, "col1");
assert_eq!(columns[0].1.column_type(), ColumnType::Str);
assert_eq!(&columns[1].0, "col2");
assert_eq!(columns[1].1.column_type(), ColumnType::U64);
}
#[test]
fn test_list_columns_strict_typing_prevents_coercion() {
let mut columnar_writer = ColumnarWriter::default();
columnar_writer.record_column_type("count", ColumnType::U64, false);
columnar_writer.record_numerical(1, "count", 1u64);
let mut buffer = Vec::new();
columnar_writer.serialize(2, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
let columns = columnar.list_columns().unwrap();
assert_eq!(columns.len(), 1);
assert_eq!(&columns[0].0, "count");
assert_eq!(columns[0].1.column_type(), ColumnType::U64);
}
#[test]
#[should_panic(expect = "Input type forbidden")]
fn test_list_columns_strict_typing_panics_on_wrong_types() {
let mut columnar_writer = ColumnarWriter::default();
columnar_writer.record_column_type("count", ColumnType::U64, false);
columnar_writer.record_numerical(1, "count", 1i64);
}
}

360
columnar/src/columnar/writer/column_operation.rs Normal file
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use std::net::Ipv6Addr;
use crate::dictionary::UnorderedId;
use crate::utils::{place_bits, pop_first_byte, select_bits};
use crate::value::NumericalValue;
use crate::{InvalidData, NumericalType, RowId};
/// When we build a columnar dataframe, we first just group
/// all mutations per column, and appends them in append-only buffer
/// in the stacker.
///
/// These ColumnOperation<T> are therefore serialize/deserialized
/// in memory.
///
/// We represents all of these operations as `ColumnOperation`.
#[derive(Eq, PartialEq, Debug, Clone, Copy)]
pub(super) enum ColumnOperation<T> {
NewDoc(RowId),
Value(T),
}
#[derive(Copy, Clone, Eq, PartialEq, Debug)]
struct ColumnOperationMetadata {
op_type: ColumnOperationType,
len: u8,
}
impl ColumnOperationMetadata {
fn to_code(self) -> u8 {
place_bits::<0, 6>(self.len) | place_bits::<6, 8>(self.op_type.to_code())
}
fn try_from_code(code: u8) -> Result<Self, InvalidData> {
let len = select_bits::<0, 6>(code);
let typ_code = select_bits::<6, 8>(code);
let column_type = ColumnOperationType::try_from_code(typ_code)?;
Ok(ColumnOperationMetadata {
op_type: column_type,
len,
})
}
}
#[derive(Copy, Clone, Eq, PartialEq, Debug)]
#[repr(u8)]
enum ColumnOperationType {
NewDoc = 0u8,
AddValue = 1u8,
}
impl ColumnOperationType {
pub fn to_code(self) -> u8 {
self as u8
}
pub fn try_from_code(code: u8) -> Result<Self, InvalidData> {
match code {
0 => Ok(Self::NewDoc),
1 => Ok(Self::AddValue),
_ => Err(InvalidData),
}
}
}
impl<V: SymbolValue> ColumnOperation<V> {
pub(super) fn serialize(self) -> impl AsRef<[u8]> {
let mut minibuf = MiniBuffer::default();
let column_op_metadata = match self {
ColumnOperation::NewDoc(new_doc) => {
let symbol_len = new_doc.serialize(&mut minibuf.bytes[1..]);
ColumnOperationMetadata {
op_type: ColumnOperationType::NewDoc,
len: symbol_len,
}
}
ColumnOperation::Value(val) => {
let symbol_len = val.serialize(&mut minibuf.bytes[1..]);
ColumnOperationMetadata {
op_type: ColumnOperationType::AddValue,
len: symbol_len,
}
}
};
minibuf.bytes[0] = column_op_metadata.to_code();
// +1 for the metadata
minibuf.len = 1 + column_op_metadata.len;
minibuf
}
/// Deserialize a colummn operation.
/// Returns None if the buffer is empty.
///
/// Panics if the payload is invalid:
/// this deserialize method is meant to target in memory.
pub(super) fn deserialize(bytes: &mut &[u8]) -> Option<Self> {
let column_op_metadata_byte = pop_first_byte(bytes)?;
let column_op_metadata = ColumnOperationMetadata::try_from_code(column_op_metadata_byte)
.expect("Invalid op metadata byte");
let symbol_bytes: &[u8];
(symbol_bytes, *bytes) = bytes.split_at(column_op_metadata.len as usize);
match column_op_metadata.op_type {
ColumnOperationType::NewDoc => {
let new_doc = u32::deserialize(symbol_bytes);
Some(ColumnOperation::NewDoc(new_doc))
}
ColumnOperationType::AddValue => {
let value = V::deserialize(symbol_bytes);
Some(ColumnOperation::Value(value))
}
}
}
}
impl<T> From<T> for ColumnOperation<T> {
fn from(value: T) -> Self {
ColumnOperation::Value(value)
}
}
// Serialization trait very local to the writer.
// As we write fast fields, we accumulate them in "in memory".
// In order to limit memory usage, and in order
// to benefit from the stacker, we do this by serialization our data
// as "Symbols".
#[allow(clippy::from_over_into)]
pub(super) trait SymbolValue: Clone + Copy {
// Serializes the symbol into the given buffer.
// Returns the number of bytes written into the buffer.
/// # Panics
/// May not exceed 9bytes
fn serialize(self, buffer: &mut [u8]) -> u8;
// Panics if invalid
fn deserialize(bytes: &[u8]) -> Self;
}
impl SymbolValue for bool {
fn serialize(self, buffer: &mut [u8]) -> u8 {
buffer[0] = u8::from(self);
1u8
}
fn deserialize(bytes: &[u8]) -> Self {
bytes[0] == 1u8
}
}
impl SymbolValue for Ipv6Addr {
fn serialize(self, buffer: &mut [u8]) -> u8 {
buffer[0..16].copy_from_slice(&self.octets());
16
}
fn deserialize(bytes: &[u8]) -> Self {
let octets: [u8; 16] = bytes[0..16].try_into().unwrap();
Ipv6Addr::from(octets)
}
}
#[derive(Default)]
struct MiniBuffer {
pub bytes: [u8; 17],
pub len: u8,
}
impl AsRef<[u8]> for MiniBuffer {
fn as_ref(&self) -> &[u8] {
&self.bytes[..self.len as usize]
}
}
impl SymbolValue for NumericalValue {
fn deserialize(mut bytes: &[u8]) -> Self {
let type_code = pop_first_byte(&mut bytes).unwrap();
let symbol_type = NumericalType::try_from_code(type_code).unwrap();
let mut octet: [u8; 8] = [0u8; 8];
octet[..bytes.len()].copy_from_slice(bytes);
match symbol_type {
NumericalType::U64 => {
let val: u64 = u64::from_le_bytes(octet);
NumericalValue::U64(val)
}
NumericalType::I64 => {
let encoded: u64 = u64::from_le_bytes(octet);
let val: i64 = decode_zig_zag(encoded);
NumericalValue::I64(val)
}
NumericalType::F64 => {
debug_assert_eq!(bytes.len(), 8);
let val: f64 = f64::from_le_bytes(octet);
NumericalValue::F64(val)
}
}
}
/// F64: Serialize with a fixed size of 9 bytes
/// U64: Serialize without leading zeroes
/// I64: ZigZag encoded and serialize without leading zeroes
fn serialize(self, output: &mut [u8]) -> u8 {
match self {
NumericalValue::F64(val) => {
output[0] = NumericalType::F64 as u8;
output[1..9].copy_from_slice(&val.to_le_bytes());
9u8
}
NumericalValue::U64(val) => {
let len = compute_num_bytes_for_u64(val) as u8;
output[0] = NumericalType::U64 as u8;
output[1..9].copy_from_slice(&val.to_le_bytes());
len + 1u8
}
NumericalValue::I64(val) => {
let zig_zag_encoded = encode_zig_zag(val);
let len = compute_num_bytes_for_u64(zig_zag_encoded) as u8;
output[0] = NumericalType::I64 as u8;
output[1..9].copy_from_slice(&zig_zag_encoded.to_le_bytes());
len + 1u8
}
}
}
}
impl SymbolValue for u32 {
fn serialize(self, output: &mut [u8]) -> u8 {
let len = compute_num_bytes_for_u64(self as u64);
output[0..4].copy_from_slice(&self.to_le_bytes());
len as u8
}
fn deserialize(bytes: &[u8]) -> Self {
let mut quartet: [u8; 4] = [0u8; 4];
quartet[..bytes.len()].copy_from_slice(bytes);
u32::from_le_bytes(quartet)
}
}
impl SymbolValue for UnorderedId {
fn serialize(self, output: &mut [u8]) -> u8 {
self.0.serialize(output)
}
fn deserialize(bytes: &[u8]) -> Self {
UnorderedId(u32::deserialize(bytes))
}
}
fn compute_num_bytes_for_u64(val: u64) -> usize {
let msb = (64u32 - val.leading_zeros()) as usize;
(msb + 7) / 8
}
fn encode_zig_zag(n: i64) -> u64 {
((n << 1) ^ (n >> 63)) as u64
}
fn decode_zig_zag(n: u64) -> i64 {
((n >> 1) as i64) ^ (-((n & 1) as i64))
}
#[cfg(test)]
mod tests {
use super::*;
#[track_caller]
fn test_zig_zag_aux(val: i64) {
let encoded = super::encode_zig_zag(val);
assert_eq!(decode_zig_zag(encoded), val);
if let Some(abs_val) = val.checked_abs() {
let abs_val = abs_val as u64;
assert!(encoded <= abs_val * 2);
}
}
#[test]
fn test_zig_zag() {
assert_eq!(encode_zig_zag(0i64), 0u64);
assert_eq!(encode_zig_zag(-1i64), 1u64);
assert_eq!(encode_zig_zag(1i64), 2u64);
test_zig_zag_aux(0i64);
test_zig_zag_aux(i64::MIN);
test_zig_zag_aux(i64::MAX);
}
use proptest::prelude::any;
use proptest::proptest;
proptest! {
#[test]
fn test_proptest_zig_zag(val in any::<i64>()) {
test_zig_zag_aux(val);
}
}
#[test]
fn test_column_op_metadata_byte_serialization() {
for len in 0..=15 {
for op_type in [ColumnOperationType::AddValue, ColumnOperationType::NewDoc] {
let column_op_metadata = ColumnOperationMetadata { op_type, len };
let column_op_metadata_code = column_op_metadata.to_code();
let serdeser_metadata =
ColumnOperationMetadata::try_from_code(column_op_metadata_code).unwrap();
assert_eq!(column_op_metadata, serdeser_metadata);
}
}
}
#[track_caller]
fn ser_deser_symbol(column_op: ColumnOperation<NumericalValue>) {
let buf = column_op.serialize();
let mut buffer = buf.as_ref().to_vec();
buffer.extend_from_slice(b"234234");
let mut bytes = &buffer[..];
let serdeser_symbol = ColumnOperation::deserialize(&mut bytes).unwrap();
assert_eq!(bytes.len() + buf.as_ref().len() as usize, buffer.len());
assert_eq!(column_op, serdeser_symbol);
}
#[test]
fn test_compute_num_bytes_for_u64() {
assert_eq!(compute_num_bytes_for_u64(0), 0);
assert_eq!(compute_num_bytes_for_u64(1), 1);
assert_eq!(compute_num_bytes_for_u64(255), 1);
assert_eq!(compute_num_bytes_for_u64(256), 2);
assert_eq!(compute_num_bytes_for_u64((1 << 16) - 1), 2);
assert_eq!(compute_num_bytes_for_u64(1 << 16), 3);
}
#[test]
fn test_symbol_serialization() {
ser_deser_symbol(ColumnOperation::NewDoc(0));
ser_deser_symbol(ColumnOperation::NewDoc(3));
ser_deser_symbol(ColumnOperation::Value(NumericalValue::I64(0i64)));
ser_deser_symbol(ColumnOperation::Value(NumericalValue::I64(1i64)));
ser_deser_symbol(ColumnOperation::Value(NumericalValue::U64(257u64)));
ser_deser_symbol(ColumnOperation::Value(NumericalValue::I64(-257i64)));
ser_deser_symbol(ColumnOperation::Value(NumericalValue::I64(i64::MIN)));
ser_deser_symbol(ColumnOperation::Value(NumericalValue::U64(0u64)));
ser_deser_symbol(ColumnOperation::Value(NumericalValue::U64(u64::MIN)));
ser_deser_symbol(ColumnOperation::Value(NumericalValue::U64(u64::MAX)));
}
fn test_column_operation_unordered_aux(val: u32, expected_len: usize) {
let column_op = ColumnOperation::Value(UnorderedId(val));
let minibuf = column_op.serialize();
assert_eq!(minibuf.as_ref().len() as usize, expected_len);
let mut buf = minibuf.as_ref().to_vec();
buf.extend_from_slice(&[2, 2, 2, 2, 2, 2]);
let mut cursor = &buf[..];
let column_op_serdeser: ColumnOperation<UnorderedId> =
ColumnOperation::deserialize(&mut cursor).unwrap();
assert_eq!(column_op_serdeser, ColumnOperation::Value(UnorderedId(val)));
assert_eq!(cursor.len() + expected_len, buf.len());
}
#[test]
fn test_column_operation_unordered() {
test_column_operation_unordered_aux(300u32, 3);
test_column_operation_unordered_aux(1u32, 2);
test_column_operation_unordered_aux(0u32, 1);
}
}

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columnar/src/columnar/writer/column_writers.rs Normal file
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use std::cmp::Ordering;
use stacker::{ExpUnrolledLinkedList, MemoryArena};
use crate::columnar::writer::column_operation::{ColumnOperation, SymbolValue};
use crate::dictionary::{DictionaryBuilder, UnorderedId};
use crate::{Cardinality, NumericalType, NumericalValue, RowId};
#[derive(Copy, Clone, Debug, Eq, PartialEq)]
#[repr(u8)]
enum DocumentStep {
Same = 0,
Next = 1,
Skipped = 2,
}
#[inline(always)]
fn delta_with_last_doc(last_doc_opt: Option<u32>, doc: u32) -> DocumentStep {
let expected_next_doc = last_doc_opt.map(|last_doc| last_doc + 1).unwrap_or(0u32);
match doc.cmp(&expected_next_doc) {
Ordering::Less => DocumentStep::Same,
Ordering::Equal => DocumentStep::Next,
Ordering::Greater => DocumentStep::Skipped,
}
}
#[derive(Copy, Clone, Default)]
pub struct ColumnWriter {
// Detected cardinality of the column so far.
cardinality: Cardinality,
// Last document inserted.
// None if no doc has been added yet.
last_doc_opt: Option<u32>,
// Buffer containing the serialized values.
values: ExpUnrolledLinkedList,
}
impl ColumnWriter {
/// Returns an iterator over the Symbol that have been recorded
/// for the given column.
pub(super) fn operation_iterator<'a, V: SymbolValue>(
&self,
arena: &MemoryArena,
buffer: &'a mut Vec<u8>,
) -> impl Iterator<Item = ColumnOperation<V>> + 'a {
buffer.clear();
self.values.read_to_end(arena, buffer);
let mut cursor: &[u8] = &buffer[..];
std::iter::from_fn(move || ColumnOperation::deserialize(&mut cursor))
}
/// Records a change of the document being recorded.
///
/// This function will also update the cardinality of the column
/// if necessary.
pub(super) fn record<S: SymbolValue>(&mut self, doc: RowId, value: S, arena: &mut MemoryArena) {
// Difference between `doc` and the last doc.
match delta_with_last_doc(self.last_doc_opt, doc) {
DocumentStep::Same => {
// This is the last encounterred document.
self.cardinality = Cardinality::Multivalued;
}
DocumentStep::Next => {
self.last_doc_opt = Some(doc);
self.write_symbol::<S>(ColumnOperation::NewDoc(doc), arena);
}
DocumentStep::Skipped => {
self.cardinality = self.cardinality.max(Cardinality::Optional);
self.last_doc_opt = Some(doc);
self.write_symbol::<S>(ColumnOperation::NewDoc(doc), arena);
}
}
self.write_symbol(ColumnOperation::Value(value), arena);
}
// Get the cardinality.
// The overall number of docs in the column is necessary to
// deal with the case where the all docs contain 1 value, except some documents
// at the end of the column.
pub(crate) fn get_cardinality(&self, num_docs: RowId) -> Cardinality {
match delta_with_last_doc(self.last_doc_opt, num_docs) {
DocumentStep::Same | DocumentStep::Next => self.cardinality,
DocumentStep::Skipped => self.cardinality.max(Cardinality::Optional),
}
}
/// Appends a new symbol to the `ColumnWriter`.
fn write_symbol<V: SymbolValue>(
&mut self,
column_operation: ColumnOperation<V>,
arena: &mut MemoryArena,
) {
self.values
.writer(arena)
.extend_from_slice(column_operation.serialize().as_ref());
}
}
#[derive(Clone, Copy, Default)]
pub(crate) struct NumericalColumnWriter {
compatible_numerical_types: CompatibleNumericalTypes,
column_writer: ColumnWriter,
}
impl NumericalColumnWriter {
pub fn force_numerical_type(&mut self, numerical_type: NumericalType) {
assert!(self
.compatible_numerical_types
.is_type_accepted(numerical_type));
self.compatible_numerical_types = CompatibleNumericalTypes::StaticType(numerical_type);
}
}
/// State used to store what types are still acceptable
/// after having seen a set of numerical values.
#[derive(Clone, Copy)]
pub(crate) enum CompatibleNumericalTypes {
Dynamic {
all_values_within_i64_range: bool,
all_values_within_u64_range: bool,
},
StaticType(NumericalType),
}
impl Default for CompatibleNumericalTypes {
fn default() -> CompatibleNumericalTypes {
CompatibleNumericalTypes::Dynamic {
all_values_within_i64_range: true,
all_values_within_u64_range: true,
}
}
}
impl CompatibleNumericalTypes {
pub fn is_type_accepted(&self, numerical_type: NumericalType) -> bool {
match self {
CompatibleNumericalTypes::Dynamic {
all_values_within_i64_range,
all_values_within_u64_range,
} => match numerical_type {
NumericalType::I64 => *all_values_within_i64_range,
NumericalType::U64 => *all_values_within_u64_range,
NumericalType::F64 => true,
},
CompatibleNumericalTypes::StaticType(static_numerical_type) => {
*static_numerical_type == numerical_type
}
}
}
pub fn accept_value(&mut self, numerical_value: NumericalValue) {
match self {
CompatibleNumericalTypes::Dynamic {
all_values_within_i64_range,
all_values_within_u64_range,
} => match numerical_value {
NumericalValue::I64(val_i64) => {
let value_within_u64_range = val_i64 >= 0i64;
*all_values_within_u64_range &= value_within_u64_range;
}
NumericalValue::U64(val_u64) => {
let value_within_i64_range = val_u64 < i64::MAX as u64;
*all_values_within_i64_range &= value_within_i64_range;
}
NumericalValue::F64(_) => {
*all_values_within_i64_range = false;
*all_values_within_u64_range = false;
}
},
CompatibleNumericalTypes::StaticType(typ) => {
assert_eq!(
numerical_value.numerical_type(),
*typ,
"Input type forbidden. This column has been forced to type {typ:?}, received \
{numerical_value:?}"
);
}
}
}
pub fn to_numerical_type(self) -> NumericalType {
for numerical_type in [NumericalType::I64, NumericalType::U64] {
if self.is_type_accepted(numerical_type) {
return numerical_type;
}
}
NumericalType::F64
}
}
impl NumericalColumnWriter {
pub fn column_type_and_cardinality(&self, num_docs: RowId) -> (NumericalType, Cardinality) {
let numerical_type = self.compatible_numerical_types.to_numerical_type();
let cardinality = self.column_writer.get_cardinality(num_docs);
(numerical_type, cardinality)
}
pub fn record_numerical_value(
&mut self,
doc: RowId,
value: NumericalValue,
arena: &mut MemoryArena,
) {
self.compatible_numerical_types.accept_value(value);
self.column_writer.record(doc, value, arena);
}
pub(super) fn operation_iterator<'a>(
self,
arena: &MemoryArena,
buffer: &'a mut Vec<u8>,
) -> impl Iterator<Item = ColumnOperation<NumericalValue>> + 'a {
self.column_writer.operation_iterator(arena, buffer)
}
}
#[derive(Copy, Clone)]
pub(crate) struct StrOrBytesColumnWriter {
pub(crate) dictionary_id: u32,
pub(crate) column_writer: ColumnWriter,
// If true, when facing a multivalued cardinality,
// values associated to a given document will be sorted.
//
// This is useful for facets.
//
// If false, the order of appearance in the document will be
// observed.
pub(crate) sort_values_within_row: bool,
}
impl StrOrBytesColumnWriter {
pub(crate) fn with_dictionary_id(dictionary_id: u32) -> StrOrBytesColumnWriter {
StrOrBytesColumnWriter {
dictionary_id,
column_writer: Default::default(),
sort_values_within_row: false,
}
}
pub(crate) fn record_bytes(
&mut self,
doc: RowId,
bytes: &[u8],
dictionaries: &mut [DictionaryBuilder],
arena: &mut MemoryArena,
) {
let unordered_id = dictionaries[self.dictionary_id as usize].get_or_allocate_id(bytes);
self.column_writer.record(doc, unordered_id, arena);
}
pub(super) fn operation_iterator<'a>(
&self,
arena: &MemoryArena,
byte_buffer: &'a mut Vec<u8>,
) -> impl Iterator<Item = ColumnOperation<UnorderedId>> + 'a {
self.column_writer.operation_iterator(arena, byte_buffer)
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_delta_with_last_doc() {
assert_eq!(delta_with_last_doc(None, 0u32), DocumentStep::Next);
assert_eq!(delta_with_last_doc(None, 1u32), DocumentStep::Skipped);
assert_eq!(delta_with_last_doc(None, 2u32), DocumentStep::Skipped);
assert_eq!(delta_with_last_doc(Some(0u32), 0u32), DocumentStep::Same);
assert_eq!(delta_with_last_doc(Some(1u32), 1u32), DocumentStep::Same);
assert_eq!(delta_with_last_doc(Some(1u32), 2u32), DocumentStep::Next);
assert_eq!(delta_with_last_doc(Some(1u32), 3u32), DocumentStep::Skipped);
assert_eq!(delta_with_last_doc(Some(1u32), 4u32), DocumentStep::Skipped);
}
#[track_caller]
fn test_column_writer_coercion_iter_aux(
values: impl Iterator<Item = NumericalValue>,
expected_numerical_type: NumericalType,
) {
let mut compatible_numerical_types = CompatibleNumericalTypes::default();
for value in values {
compatible_numerical_types.accept_value(value);
}
assert_eq!(
compatible_numerical_types.to_numerical_type(),
expected_numerical_type
);
}
#[track_caller]
fn test_column_writer_coercion_aux(
values: &[NumericalValue],
expected_numerical_type: NumericalType,
) {
test_column_writer_coercion_iter_aux(values.iter().copied(), expected_numerical_type);
test_column_writer_coercion_iter_aux(values.iter().rev().copied(), expected_numerical_type);
}
#[test]
fn test_column_writer_coercion() {
test_column_writer_coercion_aux(&[], NumericalType::I64);
test_column_writer_coercion_aux(&[1i64.into()], NumericalType::I64);
test_column_writer_coercion_aux(&[1u64.into()], NumericalType::I64);
// We don't detect exact integer at the moment. We could!
test_column_writer_coercion_aux(&[1f64.into()], NumericalType::F64);
test_column_writer_coercion_aux(&[u64::MAX.into()], NumericalType::U64);
test_column_writer_coercion_aux(&[(i64::MAX as u64).into()], NumericalType::U64);
test_column_writer_coercion_aux(&[(1u64 << 63).into()], NumericalType::U64);
test_column_writer_coercion_aux(&[1i64.into(), 1u64.into()], NumericalType::I64);
test_column_writer_coercion_aux(&[u64::MAX.into(), (-1i64).into()], NumericalType::F64);
}
#[test]
#[should_panic]
fn test_compatible_numerical_types_static_incompatible_type() {
let mut compatible_numerical_types =
CompatibleNumericalTypes::StaticType(NumericalType::U64);
compatible_numerical_types.accept_value(NumericalValue::I64(1i64));
}
#[test]
fn test_compatible_numerical_types_static_different_type_forbidden() {
let mut compatible_numerical_types =
CompatibleNumericalTypes::StaticType(NumericalType::U64);
compatible_numerical_types.accept_value(NumericalValue::U64(u64::MAX));
}
#[test]
fn test_compatible_numerical_types_static() {
for typ in [NumericalType::I64, NumericalType::I64, NumericalType::F64] {
let compatible_numerical_types = CompatibleNumericalTypes::StaticType(typ);
assert_eq!(compatible_numerical_types.to_numerical_type(), typ);
}
}
}

786
columnar/src/columnar/writer/mod.rs Normal file
View File

@@ -0,0 +1,786 @@
mod column_operation;
mod column_writers;
mod serializer;
mod value_index;
use std::io;
use std::net::Ipv6Addr;
use column_operation::ColumnOperation;
pub(crate) use column_writers::CompatibleNumericalTypes;
use common::CountingWriter;
pub(crate) use serializer::ColumnarSerializer;
use stacker::{Addr, ArenaHashMap, MemoryArena};
use crate::column_index::SerializableColumnIndex;
use crate::column_values::{
ColumnValues, MonotonicallyMappableToU128, MonotonicallyMappableToU64, VecColumn,
};
use crate::columnar::column_type::{ColumnType, ColumnTypeCategory};
use crate::columnar::writer::column_writers::{
ColumnWriter, NumericalColumnWriter, StrOrBytesColumnWriter,
};
use crate::columnar::writer::value_index::{IndexBuilder, PreallocatedIndexBuilders};
use crate::dictionary::{DictionaryBuilder, TermIdMapping, UnorderedId};
use crate::value::{Coerce, NumericalType, NumericalValue};
use crate::{Cardinality, RowId};
/// This is a set of buffers that are used to temporarily write the values into before passing them
/// to the fast field codecs.
#[derive(Default)]
struct SpareBuffers {
value_index_builders: PreallocatedIndexBuilders,
u64_values: Vec<u64>,
ip_addr_values: Vec<Ipv6Addr>,
}
/// Makes it possible to create a new columnar.
///
/// ```rust
/// use tantivy_columnar::ColumnarWriter;
///
/// let mut columnar_writer = ColumnarWriter::default();
/// columnar_writer.record_str(0u32 /* doc id */, "product_name", "Red backpack");
/// columnar_writer.record_numerical(0u32 /* doc id */, "price", 10u64);
/// columnar_writer.record_str(1u32 /* doc id */, "product_name", "Apple");
/// columnar_writer.record_numerical(0u32 /* doc id */, "price", 10.5f64); //< uh oh we ended up mixing integer and floats.
/// let mut wrt: Vec<u8> = Vec::new();
/// columnar_writer.serialize(2u32, &mut wrt).unwrap();
/// ```
pub struct ColumnarWriter {
numerical_field_hash_map: ArenaHashMap,
datetime_field_hash_map: ArenaHashMap,
bool_field_hash_map: ArenaHashMap,
ip_addr_field_hash_map: ArenaHashMap,
bytes_field_hash_map: ArenaHashMap,
str_field_hash_map: ArenaHashMap,
arena: MemoryArena,
// Dictionaries used to store dictionary-encoded values.
dictionaries: Vec<DictionaryBuilder>,
buffers: SpareBuffers,
}
impl Default for ColumnarWriter {
fn default() -> Self {
ColumnarWriter {
numerical_field_hash_map: ArenaHashMap::new(10_000),
bool_field_hash_map: ArenaHashMap::new(10_000),
ip_addr_field_hash_map: ArenaHashMap::new(10_000),
bytes_field_hash_map: ArenaHashMap::new(10_000),
str_field_hash_map: ArenaHashMap::new(10_000),
datetime_field_hash_map: ArenaHashMap::new(10_000),
dictionaries: Vec::new(),
arena: MemoryArena::default(),
buffers: SpareBuffers::default(),
}
}
}
#[inline]
fn mutate_or_create_column<V, TMutator>(
arena_hash_map: &mut ArenaHashMap,
column_name: &str,
updater: TMutator,
) where
V: Copy + 'static,
TMutator: FnMut(Option<V>) -> V,
{
assert!(
!column_name.as_bytes().contains(&0u8),
"key may not contain the 0 byte"
);
arena_hash_map.mutate_or_create(column_name.as_bytes(), updater);
}
impl ColumnarWriter {
pub fn mem_usage(&self) -> usize {
// TODO add dictionary builders.
self.arena.mem_usage()
+ self.numerical_field_hash_map.mem_usage()
+ self.bool_field_hash_map.mem_usage()
+ self.bytes_field_hash_map.mem_usage()
+ self.str_field_hash_map.mem_usage()
+ self.ip_addr_field_hash_map.mem_usage()
+ self.datetime_field_hash_map.mem_usage()
}
/// Records a column type. This is useful to bypass the coercion process,
/// makes sure the empty is present in the resulting columnar, or set
/// the `sort_values_within_row`.
///
/// `sort_values_within_row` is only allowed for `Bytes` or `Str` columns.
pub fn record_column_type(
&mut self,
column_name: &str,
column_type: ColumnType,
sort_values_within_row: bool,
) {
if sort_values_within_row {
assert!(
column_type == ColumnType::Bytes || column_type == ColumnType::Str,
"sort_values_within_row is only allowed for Bytes and Str columns",
);
}
match column_type {
ColumnType::Str | ColumnType::Bytes => {
let (hash_map, dictionaries) = (
if column_type == ColumnType::Str {
&mut self.str_field_hash_map
} else {
&mut self.bytes_field_hash_map
},
&mut self.dictionaries,
);
mutate_or_create_column(
hash_map,
column_name,
|column_opt: Option<StrOrBytesColumnWriter>| {
let mut column_writer = if let Some(column_writer) = column_opt {
column_writer
} else {
let dictionary_id = dictionaries.len() as u32;
dictionaries.push(DictionaryBuilder::default());
StrOrBytesColumnWriter::with_dictionary_id(dictionary_id)
};
column_writer.sort_values_within_row = sort_values_within_row;
column_writer
},
);
}
ColumnType::Bool => {
mutate_or_create_column(
&mut self.bool_field_hash_map,
column_name,
|column_opt: Option<ColumnWriter>| column_opt.unwrap_or_default(),
);
}
ColumnType::DateTime => {
mutate_or_create_column(
&mut self.datetime_field_hash_map,
column_name,
|column_opt: Option<ColumnWriter>| column_opt.unwrap_or_default(),
);
}
ColumnType::I64 | ColumnType::F64 | ColumnType::U64 => {
let numerical_type = column_type.numerical_type().unwrap();
mutate_or_create_column(
&mut self.numerical_field_hash_map,
column_name,
|column_opt: Option<NumericalColumnWriter>| {
let mut column: NumericalColumnWriter = column_opt.unwrap_or_default();
column.force_numerical_type(numerical_type);
column
},
);
}
ColumnType::IpAddr => mutate_or_create_column(
&mut self.ip_addr_field_hash_map,
column_name,
|column_opt: Option<ColumnWriter>| column_opt.unwrap_or_default(),
),
}
}
pub fn record_numerical<T: Into<NumericalValue> + Copy>(
&mut self,
doc: RowId,
column_name: &str,
numerical_value: T,
) {
let (hash_map, arena) = (&mut self.numerical_field_hash_map, &mut self.arena);
mutate_or_create_column(
hash_map,
column_name,
|column_opt: Option<NumericalColumnWriter>| {
let mut column: NumericalColumnWriter = column_opt.unwrap_or_default();
column.record_numerical_value(doc, numerical_value.into(), arena);
column
},
);
}
pub fn record_ip_addr(&mut self, doc: RowId, column_name: &str, ip_addr: Ipv6Addr) {
assert!(
!column_name.as_bytes().contains(&0u8),
"key may not contain the 0 byte"
);
let (hash_map, arena) = (&mut self.ip_addr_field_hash_map, &mut self.arena);
hash_map.mutate_or_create(
column_name.as_bytes(),
|column_opt: Option<ColumnWriter>| {
let mut column: ColumnWriter = column_opt.unwrap_or_default();
column.record(doc, ip_addr, arena);
column
},
);
}
pub fn record_bool(&mut self, doc: RowId, column_name: &str, val: bool) {
let (hash_map, arena) = (&mut self.bool_field_hash_map, &mut self.arena);
mutate_or_create_column(hash_map, column_name, |column_opt: Option<ColumnWriter>| {
let mut column: ColumnWriter = column_opt.unwrap_or_default();
column.record(doc, val, arena);
column
});
}
pub fn record_datetime(&mut self, doc: RowId, column_name: &str, datetime: crate::DateTime) {
let (hash_map, arena) = (&mut self.datetime_field_hash_map, &mut self.arena);
mutate_or_create_column(hash_map, column_name, |column_opt: Option<ColumnWriter>| {
let mut column: ColumnWriter = column_opt.unwrap_or_default();
column.record(doc, NumericalValue::I64(datetime.timestamp_micros), arena);
column
});
}
pub fn record_str(&mut self, doc: RowId, column_name: &str, value: &str) {
let (hash_map, arena, dictionaries) = (
&mut self.str_field_hash_map,
&mut self.arena,
&mut self.dictionaries,
);
hash_map.mutate_or_create(
column_name.as_bytes(),
|column_opt: Option<StrOrBytesColumnWriter>| {
let mut column: StrOrBytesColumnWriter = column_opt.unwrap_or_else(|| {
// Each column has its own dictionary
let dictionary_id = dictionaries.len() as u32;
dictionaries.push(DictionaryBuilder::default());
StrOrBytesColumnWriter::with_dictionary_id(dictionary_id)
});
column.record_bytes(doc, value.as_bytes(), dictionaries, arena);
column
},
);
}
pub fn record_bytes(&mut self, doc: RowId, column_name: &str, value: &[u8]) {
assert!(
!column_name.as_bytes().contains(&0u8),
"key may not contain the 0 byte"
);
let (hash_map, arena, dictionaries) = (
&mut self.bytes_field_hash_map,
&mut self.arena,
&mut self.dictionaries,
);
hash_map.mutate_or_create(
column_name.as_bytes(),
|column_opt: Option<StrOrBytesColumnWriter>| {
let mut column: StrOrBytesColumnWriter = column_opt.unwrap_or_else(|| {
// Each column has its own dictionary
let dictionary_id = dictionaries.len() as u32;
dictionaries.push(DictionaryBuilder::default());
StrOrBytesColumnWriter::with_dictionary_id(dictionary_id)
});
column.record_bytes(doc, value, dictionaries, arena);
column
},
);
}
pub fn serialize(&mut self, num_docs: RowId, wrt: &mut dyn io::Write) -> io::Result<()> {
let mut serializer = ColumnarSerializer::new(wrt);
let mut columns: Vec<(&[u8], ColumnTypeCategory, Addr)> = self
.numerical_field_hash_map
.iter()
.map(|(column_name, addr, _)| (column_name, ColumnTypeCategory::Numerical, addr))
.collect();
columns.extend(
self.bytes_field_hash_map
.iter()
.map(|(term, addr, _)| (term, ColumnTypeCategory::Bytes, addr)),
);
columns.extend(
self.str_field_hash_map
.iter()
.map(|(column_name, addr, _)| (column_name, ColumnTypeCategory::Str, addr)),
);
columns.extend(
self.bool_field_hash_map
.iter()
.map(|(column_name, addr, _)| (column_name, ColumnTypeCategory::Bool, addr)),
);
columns.extend(
self.ip_addr_field_hash_map
.iter()
.map(|(column_name, addr, _)| (column_name, ColumnTypeCategory::IpAddr, addr)),
);
columns.extend(
self.datetime_field_hash_map
.iter()
.map(|(column_name, addr, _)| (column_name, ColumnTypeCategory::DateTime, addr)),
);
columns.sort_unstable_by_key(|(column_name, col_type, _)| (*column_name, *col_type));
let (arena, buffers, dictionaries) = (&self.arena, &mut self.buffers, &self.dictionaries);
let mut symbol_byte_buffer: Vec<u8> = Vec::new();
for (column_name, column_type, addr) in columns {
match column_type {
ColumnTypeCategory::Bool => {
let column_writer: ColumnWriter = self.bool_field_hash_map.read(addr);
let cardinality = column_writer.get_cardinality(num_docs);
let mut column_serializer =
serializer.serialize_column(column_name, ColumnType::Bool);
serialize_bool_column(
cardinality,
num_docs,
column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
buffers,
&mut column_serializer,
)?;
}
ColumnTypeCategory::IpAddr => {
let column_writer: ColumnWriter = self.ip_addr_field_hash_map.read(addr);
let cardinality = column_writer.get_cardinality(num_docs);
let mut column_serializer =
serializer.serialize_column(column_name, ColumnType::IpAddr);
serialize_ip_addr_column(
cardinality,
num_docs,
column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
buffers,
&mut column_serializer,
)?;
}
ColumnTypeCategory::Bytes | ColumnTypeCategory::Str => {
let (column_type, str_column_writer): (ColumnType, StrOrBytesColumnWriter) =
if column_type == ColumnTypeCategory::Bytes {
(ColumnType::Bytes, self.bytes_field_hash_map.read(addr))
} else {
(ColumnType::Str, self.str_field_hash_map.read(addr))
};
let dictionary_builder =
&dictionaries[str_column_writer.dictionary_id as usize];
let cardinality = str_column_writer.column_writer.get_cardinality(num_docs);
let mut column_serializer =
serializer.serialize_column(column_name, column_type);
serialize_bytes_or_str_column(
cardinality,
num_docs,
str_column_writer.sort_values_within_row,
dictionary_builder,
str_column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
buffers,
&mut column_serializer,
)?;
}
ColumnTypeCategory::Numerical => {
let numerical_column_writer: NumericalColumnWriter =
self.numerical_field_hash_map.read(addr);
let (numerical_type, cardinality) =
numerical_column_writer.column_type_and_cardinality(num_docs);
let mut column_serializer =
serializer.serialize_column(column_name, ColumnType::from(numerical_type));
serialize_numerical_column(
cardinality,
num_docs,
numerical_type,
numerical_column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
buffers,
&mut column_serializer,
)?;
}
ColumnTypeCategory::DateTime => {
let column_writer: ColumnWriter = self.datetime_field_hash_map.read(addr);
let cardinality = column_writer.get_cardinality(num_docs);
let mut column_serializer =
serializer.serialize_column(column_name, ColumnType::DateTime);
serialize_numerical_column(
cardinality,
num_docs,
NumericalType::I64,
column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
buffers,
&mut column_serializer,
)?;
}
};
}
serializer.finalize(num_docs)?;
Ok(())
}
}
// Serialize [Dictionary, Column, dictionary num bytes U32::LE]
// Column: [Column Index, Column Values, column index num bytes U32::LE]
fn serialize_bytes_or_str_column(
cardinality: Cardinality,
num_docs: RowId,
sort_values_within_row: bool,
dictionary_builder: &DictionaryBuilder,
operation_it: impl Iterator<Item = ColumnOperation<UnorderedId>>,
buffers: &mut SpareBuffers,
wrt: impl io::Write,
) -> io::Result<()> {
let SpareBuffers {
value_index_builders,
u64_values,
..
} = buffers;
let mut counting_writer = CountingWriter::wrap(wrt);
let term_id_mapping: TermIdMapping = dictionary_builder.serialize(&mut counting_writer)?;
let dictionary_num_bytes: u32 = counting_writer.written_bytes() as u32;
let mut wrt = counting_writer.finish();
let operation_iterator = operation_it.map(|symbol: ColumnOperation<UnorderedId>| {
// We map unordered ids to ordered ids.
match symbol {
ColumnOperation::Value(unordered_id) => {
let ordered_id = term_id_mapping.to_ord(unordered_id);
ColumnOperation::Value(ordered_id.0 as u64)
}
ColumnOperation::NewDoc(doc) => ColumnOperation::NewDoc(doc),
}
});
send_to_serialize_column_mappable_to_u64(
operation_iterator,
cardinality,
num_docs,
sort_values_within_row,
value_index_builders,
u64_values,
&mut wrt,
)?;
wrt.write_all(&dictionary_num_bytes.to_le_bytes()[..])?;
Ok(())
}
fn serialize_numerical_column(
cardinality: Cardinality,
num_docs: RowId,
numerical_type: NumericalType,
op_iterator: impl Iterator<Item = ColumnOperation<NumericalValue>>,
buffers: &mut SpareBuffers,
wrt: &mut impl io::Write,
) -> io::Result<()> {
let SpareBuffers {
value_index_builders,
u64_values,
..
} = buffers;
match numerical_type {
NumericalType::I64 => {
send_to_serialize_column_mappable_to_u64(
coerce_numerical_symbol::<i64>(op_iterator),
cardinality,
num_docs,
false,
value_index_builders,
u64_values,
wrt,
)?;
}
NumericalType::U64 => {
send_to_serialize_column_mappable_to_u64(
coerce_numerical_symbol::<u64>(op_iterator),
cardinality,
num_docs,
false,
value_index_builders,
u64_values,
wrt,
)?;
}
NumericalType::F64 => {
send_to_serialize_column_mappable_to_u64(
coerce_numerical_symbol::<f64>(op_iterator),
cardinality,
num_docs,
false,
value_index_builders,
u64_values,
wrt,
)?;
}
};
Ok(())
}
fn serialize_bool_column(
cardinality: Cardinality,
num_docs: RowId,
column_operations_it: impl Iterator<Item = ColumnOperation<bool>>,
buffers: &mut SpareBuffers,
wrt: &mut impl io::Write,
) -> io::Result<()> {
let SpareBuffers {
value_index_builders,
u64_values,
..
} = buffers;
send_to_serialize_column_mappable_to_u64(
column_operations_it.map(|bool_column_operation| match bool_column_operation {
ColumnOperation::NewDoc(doc) => ColumnOperation::NewDoc(doc),
ColumnOperation::Value(bool_val) => ColumnOperation::Value(bool_val.to_u64()),
}),
cardinality,
num_docs,
false,
value_index_builders,
u64_values,
wrt,
)?;
Ok(())
}
fn serialize_ip_addr_column(
cardinality: Cardinality,
num_docs: RowId,
column_operations_it: impl Iterator<Item = ColumnOperation<Ipv6Addr>>,
buffers: &mut SpareBuffers,
wrt: &mut impl io::Write,
) -> io::Result<()> {
let SpareBuffers {
value_index_builders,
ip_addr_values,
..
} = buffers;
send_to_serialize_column_mappable_to_u128(
column_operations_it,
cardinality,
num_docs,
value_index_builders,
ip_addr_values,
wrt,
)?;
Ok(())
}
fn send_to_serialize_column_mappable_to_u128<
T: Copy + Ord + std::fmt::Debug + Send + Sync + MonotonicallyMappableToU128 + PartialOrd,
>(
op_iterator: impl Iterator<Item = ColumnOperation<T>>,
cardinality: Cardinality,
num_rows: RowId,
value_index_builders: &mut PreallocatedIndexBuilders,
values: &mut Vec<T>,
mut wrt: impl io::Write,
) -> io::Result<()>
where
for<'a> VecColumn<'a, T>: ColumnValues<T>,
{
values.clear();
// TODO: split index and values
let serializable_column_index = match cardinality {
Cardinality::Full => {
consume_operation_iterator(
op_iterator,
value_index_builders.borrow_required_index_builder(),
values,
);
SerializableColumnIndex::Full
}
Cardinality::Optional => {
let optional_index_builder = value_index_builders.borrow_optional_index_builder();
consume_operation_iterator(op_iterator, optional_index_builder, values);
let optional_index = optional_index_builder.finish(num_rows);
SerializableColumnIndex::Optional {
num_rows,
non_null_row_ids: Box::new(optional_index),
}
}
Cardinality::Multivalued => {
let multivalued_index_builder = value_index_builders.borrow_multivalued_index_builder();
consume_operation_iterator(op_iterator, multivalued_index_builder, values);
let multivalued_index = multivalued_index_builder.finish(num_rows);
SerializableColumnIndex::Multivalued(Box::new(multivalued_index))
}
};
crate::column::serialize_column_mappable_to_u128(
serializable_column_index,
&&values[..],
values.len() as u32,
&mut wrt,
)?;
Ok(())
}
fn sort_values_within_row_in_place(multivalued_index: &[RowId], values: &mut Vec<u64>) {
let mut start_index: usize = 0;
for end_index in multivalued_index.iter().copied() {
let end_index = end_index as usize;
values[start_index..end_index].sort_unstable();
start_index = end_index;
}
}
fn send_to_serialize_column_mappable_to_u64(
op_iterator: impl Iterator<Item = ColumnOperation<u64>>,
cardinality: Cardinality,
num_rows: RowId,
sort_values_within_row: bool,
value_index_builders: &mut PreallocatedIndexBuilders,
values: &mut Vec<u64>,
mut wrt: impl io::Write,
) -> io::Result<()>
where
for<'a> VecColumn<'a, u64>: ColumnValues<u64>,
{
values.clear();
let serializable_column_index = match cardinality {
Cardinality::Full => {
consume_operation_iterator(
op_iterator,
value_index_builders.borrow_required_index_builder(),
values,
);
SerializableColumnIndex::Full
}
Cardinality::Optional => {
let optional_index_builder = value_index_builders.borrow_optional_index_builder();
consume_operation_iterator(op_iterator, optional_index_builder, values);
let optional_index = optional_index_builder.finish(num_rows);
SerializableColumnIndex::Optional {
non_null_row_ids: Box::new(optional_index),
num_rows,
}
}
Cardinality::Multivalued => {
let multivalued_index_builder = value_index_builders.borrow_multivalued_index_builder();
consume_operation_iterator(op_iterator, multivalued_index_builder, values);
let multivalued_index = multivalued_index_builder.finish(num_rows);
if sort_values_within_row {
sort_values_within_row_in_place(multivalued_index, values);
}
SerializableColumnIndex::Multivalued(Box::new(multivalued_index))
}
};
crate::column::serialize_column_mappable_to_u64(
serializable_column_index,
&&values[..],
&mut wrt,
)?;
Ok(())
}
fn coerce_numerical_symbol<T>(
operation_iterator: impl Iterator<Item = ColumnOperation<NumericalValue>>,
) -> impl Iterator<Item = ColumnOperation<u64>>
where T: Coerce + MonotonicallyMappableToU64 {
operation_iterator.map(|symbol| match symbol {
ColumnOperation::NewDoc(doc) => ColumnOperation::NewDoc(doc),
ColumnOperation::Value(numerical_value) => {
ColumnOperation::Value(T::coerce(numerical_value).to_u64())
}
})
}
fn consume_operation_iterator<T: Ord, TIndexBuilder: IndexBuilder>(
operation_iterator: impl Iterator<Item = ColumnOperation<T>>,
index_builder: &mut TIndexBuilder,
values: &mut Vec<T>,
) {
for symbol in operation_iterator {
match symbol {
ColumnOperation::NewDoc(doc) => {
index_builder.record_row(doc);
}
ColumnOperation::Value(value) => {
index_builder.record_value();
values.push(value);
}
}
}
}
#[cfg(test)]
mod tests {
use stacker::MemoryArena;
use crate::columnar::writer::column_operation::ColumnOperation;
use crate::{Cardinality, NumericalValue};
#[test]
fn test_column_writer_required_simple() {
let mut arena = MemoryArena::default();
let mut column_writer = super::ColumnWriter::default();
column_writer.record(0u32, NumericalValue::from(14i64), &mut arena);
column_writer.record(1u32, NumericalValue::from(15i64), &mut arena);
column_writer.record(2u32, NumericalValue::from(-16i64), &mut arena);
assert_eq!(column_writer.get_cardinality(3), Cardinality::Full);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&mut arena, &mut buffer)
.collect();
assert_eq!(symbols.len(), 6);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
assert!(matches!(
symbols[1],
ColumnOperation::Value(NumericalValue::I64(14i64))
));
assert!(matches!(symbols[2], ColumnOperation::NewDoc(1u32)));
assert!(matches!(
symbols[3],
ColumnOperation::Value(NumericalValue::I64(15i64))
));
assert!(matches!(symbols[4], ColumnOperation::NewDoc(2u32)));
assert!(matches!(
symbols[5],
ColumnOperation::Value(NumericalValue::I64(-16i64))
));
}
#[test]
fn test_column_writer_optional_cardinality_missing_first() {
let mut arena = MemoryArena::default();
let mut column_writer = super::ColumnWriter::default();
column_writer.record(1u32, NumericalValue::from(15i64), &mut arena);
column_writer.record(2u32, NumericalValue::from(-16i64), &mut arena);
assert_eq!(column_writer.get_cardinality(3), Cardinality::Optional);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&mut arena, &mut buffer)
.collect();
assert_eq!(symbols.len(), 4);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(1u32)));
assert!(matches!(
symbols[1],
ColumnOperation::Value(NumericalValue::I64(15i64))
));
assert!(matches!(symbols[2], ColumnOperation::NewDoc(2u32)));
assert!(matches!(
symbols[3],
ColumnOperation::Value(NumericalValue::I64(-16i64))
));
}
#[test]
fn test_column_writer_optional_cardinality_missing_last() {
let mut arena = MemoryArena::default();
let mut column_writer = super::ColumnWriter::default();
column_writer.record(0u32, NumericalValue::from(15i64), &mut arena);
assert_eq!(column_writer.get_cardinality(2), Cardinality::Optional);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&mut arena, &mut buffer)
.collect();
assert_eq!(symbols.len(), 2);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
assert!(matches!(
symbols[1],
ColumnOperation::Value(NumericalValue::I64(15i64))
));
}
#[test]
fn test_column_writer_multivalued() {
let mut arena = MemoryArena::default();
let mut column_writer = super::ColumnWriter::default();
column_writer.record(0u32, NumericalValue::from(16i64), &mut arena);
column_writer.record(0u32, NumericalValue::from(17i64), &mut arena);
assert_eq!(column_writer.get_cardinality(1), Cardinality::Multivalued);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&mut arena, &mut buffer)
.collect();
assert_eq!(symbols.len(), 3);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
assert!(matches!(
symbols[1],
ColumnOperation::Value(NumericalValue::I64(16i64))
));
assert!(matches!(
symbols[2],
ColumnOperation::Value(NumericalValue::I64(17i64))
));
}
}

108
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use std::io;
use std::io::Write;
use common::{BinarySerializable, CountingWriter};
use sstable::value::RangeValueWriter;
use sstable::RangeSSTable;
use crate::columnar::ColumnType;
use crate::RowId;
pub struct ColumnarSerializer<W: io::Write> {
wrt: CountingWriter<W>,
sstable_range: sstable::Writer<Vec<u8>, RangeValueWriter>,
prepare_key_buffer: Vec<u8>,
}
/// Returns a key consisting of the concatenation of the key and the column_type_and_cardinality
/// code.
fn prepare_key(key: &[u8], column_type: ColumnType, buffer: &mut Vec<u8>) {
buffer.clear();
buffer.extend_from_slice(key);
buffer.push(0u8);
buffer.push(column_type.to_code());
}
impl<W: io::Write> ColumnarSerializer<W> {
pub(crate) fn new(wrt: W) -> ColumnarSerializer<W> {
let sstable_range: sstable::Writer<Vec<u8>, RangeValueWriter> =
sstable::Dictionary::<RangeSSTable>::builder(Vec::with_capacity(100_000)).unwrap();
ColumnarSerializer {
wrt: CountingWriter::wrap(wrt),
sstable_range,
prepare_key_buffer: Vec::new(),
}
}
pub fn serialize_column<'a>(
&'a mut self,
column_name: &[u8],
column_type: ColumnType,
) -> impl io::Write + 'a {
let start_offset = self.wrt.written_bytes();
prepare_key(column_name, column_type, &mut self.prepare_key_buffer);
ColumnSerializer {
columnar_serializer: self,
start_offset,
}
}
pub(crate) fn finalize(mut self, num_rows: RowId) -> io::Result<()> {
let sstable_bytes: Vec<u8> = self.sstable_range.finish()?;
let sstable_num_bytes: u64 = sstable_bytes.len() as u64;
self.wrt.write_all(&sstable_bytes)?;
self.wrt.write_all(&sstable_num_bytes.to_le_bytes()[..])?;
num_rows.serialize(&mut self.wrt)?;
self.wrt
.write_all(&super::super::format_version::footer())?;
self.wrt.flush()?;
Ok(())
}
}
struct ColumnSerializer<'a, W: io::Write> {
columnar_serializer: &'a mut ColumnarSerializer<W>,
start_offset: u64,
}
impl<'a, W: io::Write> Drop for ColumnSerializer<'a, W> {
fn drop(&mut self) {
let end_offset: u64 = self.columnar_serializer.wrt.written_bytes();
let byte_range = self.start_offset..end_offset;
self.columnar_serializer.sstable_range.insert_cannot_fail(
&self.columnar_serializer.prepare_key_buffer[..],
&byte_range,
);
self.columnar_serializer.prepare_key_buffer.clear();
}
}
impl<'a, W: io::Write> io::Write for ColumnSerializer<'a, W> {
fn write(&mut self, buf: &[u8]) -> io::Result<usize> {
self.columnar_serializer.wrt.write(buf)
}
fn flush(&mut self) -> io::Result<()> {
self.columnar_serializer.wrt.flush()
}
fn write_all(&mut self, buf: &[u8]) -> io::Result<()> {
self.columnar_serializer.wrt.write_all(buf)
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::columnar::column_type::ColumnType;
#[test]
fn test_prepare_key_bytes() {
let mut buffer: Vec<u8> = b"somegarbage".to_vec();
prepare_key(b"root\0child", ColumnType::Str, &mut buffer);
assert_eq!(buffer.len(), 12);
assert_eq!(&buffer[..10], b"root\0child");
assert_eq!(buffer[10], 0u8);
assert_eq!(buffer[11], ColumnType::Str.to_code());
}
}

173
columnar/src/columnar/writer/value_index.rs Normal file
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use crate::iterable::Iterable;
use crate::RowId;
/// The `IndexBuilder` interprets a sequence of
/// calls of the form:
/// (record_doc,record_value+)*
/// and can then serialize the results into an index to associate docids with their value[s].
///
/// It has different implementation depending on whether the
/// cardinality is required, optional, or multivalued.
pub(crate) trait IndexBuilder {
fn record_row(&mut self, doc: RowId);
#[inline]
fn record_value(&mut self) {}
}
/// The FullIndexBuilder does nothing.
#[derive(Default)]
pub struct FullIndexBuilder;
impl IndexBuilder for FullIndexBuilder {
#[inline(always)]
fn record_row(&mut self, _doc: RowId) {}
}
#[derive(Default)]
pub struct OptionalIndexBuilder {
docs: Vec<RowId>,
}
impl OptionalIndexBuilder {
pub fn finish<'a>(&'a mut self, num_rows: RowId) -> impl Iterable<RowId> + 'a {
debug_assert!(self
.docs
.last()
.copied()
.map(|last_doc| last_doc < num_rows)
.unwrap_or(true));
&self.docs[..]
}
fn reset(&mut self) {
self.docs.clear();
}
}
impl IndexBuilder for OptionalIndexBuilder {
#[inline(always)]
fn record_row(&mut self, doc: RowId) {
debug_assert!(self
.docs
.last()
.copied()
.map(|prev_doc| doc > prev_doc)
.unwrap_or(true));
self.docs.push(doc);
}
}
#[derive(Default)]
pub struct MultivaluedIndexBuilder {
start_offsets: Vec<RowId>,
total_num_vals_seen: u32,
}
impl MultivaluedIndexBuilder {
pub fn finish(&mut self, num_docs: RowId) -> &[u32] {
self.start_offsets
.resize(num_docs as usize + 1, self.total_num_vals_seen);
&self.start_offsets[..]
}
fn reset(&mut self) {
self.start_offsets.clear();
self.start_offsets.push(0u32);
self.total_num_vals_seen = 0;
}
}
impl IndexBuilder for MultivaluedIndexBuilder {
fn record_row(&mut self, row_id: RowId) {
self.start_offsets
.resize(row_id as usize + 1, self.total_num_vals_seen);
}
fn record_value(&mut self) {
self.total_num_vals_seen += 1;
}
}
/// The `SpareIndexBuilders` is there to avoid allocating a
/// new index builder for every single column.
#[derive(Default)]
pub struct PreallocatedIndexBuilders {
required_index_builder: FullIndexBuilder,
optional_index_builder: OptionalIndexBuilder,
multivalued_index_builder: MultivaluedIndexBuilder,
}
impl PreallocatedIndexBuilders {
pub fn borrow_required_index_builder(&mut self) -> &mut FullIndexBuilder {
&mut self.required_index_builder
}
pub fn borrow_optional_index_builder(&mut self) -> &mut OptionalIndexBuilder {
self.optional_index_builder.reset();
&mut self.optional_index_builder
}
pub fn borrow_multivalued_index_builder(&mut self) -> &mut MultivaluedIndexBuilder {
self.multivalued_index_builder.reset();
&mut self.multivalued_index_builder
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_optional_value_index_builder() {
let mut opt_value_index_builder = OptionalIndexBuilder::default();
opt_value_index_builder.record_row(0u32);
opt_value_index_builder.record_value();
assert_eq!(
&opt_value_index_builder
.finish(1u32)
.boxed_iter()
.collect::<Vec<u32>>(),
&[0]
);
opt_value_index_builder.reset();
opt_value_index_builder.record_row(1u32);
opt_value_index_builder.record_value();
assert_eq!(
&opt_value_index_builder
.finish(2u32)
.boxed_iter()
.collect::<Vec<u32>>(),
&[1]
);
}
#[test]
fn test_multivalued_value_index_builder() {
let mut multivalued_value_index_builder = MultivaluedIndexBuilder::default();
multivalued_value_index_builder.record_row(1u32);
multivalued_value_index_builder.record_value();
multivalued_value_index_builder.record_value();
multivalued_value_index_builder.record_row(2u32);
multivalued_value_index_builder.record_value();
assert_eq!(
multivalued_value_index_builder
.finish(4u32)
.iter()
.copied()
.collect::<Vec<u32>>(),
vec![0, 0, 2, 3, 3]
);
multivalued_value_index_builder.reset();
multivalued_value_index_builder.record_row(2u32);
multivalued_value_index_builder.record_value();
multivalued_value_index_builder.record_value();
assert_eq!(
multivalued_value_index_builder
.finish(4u32)
.iter()
.copied()
.collect::<Vec<u32>>(),
vec![0, 0, 0, 2, 2]
);
}
}

84
columnar/src/dictionary.rs Normal file
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use std::io;
use fnv::FnvHashMap;
use sstable::SSTable;
pub(crate) struct TermIdMapping {
unordered_to_ord: Vec<OrderedId>,
}
impl TermIdMapping {
pub fn to_ord(&self, unordered: UnorderedId) -> OrderedId {
self.unordered_to_ord[unordered.0 as usize]
}
}
/// When we add values, we cannot know their ordered id yet.
/// For this reason, we temporarily assign them a `UnorderedId`
/// that will be mapped to an `OrderedId` upon serialization.
#[derive(Clone, Copy, Debug, Hash, PartialEq, Eq)]
pub struct UnorderedId(pub u32);
#[derive(Clone, Copy, Hash, PartialEq, Eq, Debug)]
pub struct OrderedId(pub u32);
/// `DictionaryBuilder` for dictionary encoding.
///
/// It stores the different terms encounterred and assigns them a temporary value
/// we call unordered id.
///
/// Upon serialization, we will sort the ids and hence build a `UnorderedId -> Term ordinal`
/// mapping.
#[derive(Default)]
pub(crate) struct DictionaryBuilder {
dict: FnvHashMap<Vec<u8>, UnorderedId>,
}
impl DictionaryBuilder {
/// Get or allocate an unordered id.
/// (This ID is simply an auto-incremented id.)
pub fn get_or_allocate_id(&mut self, term: &[u8]) -> UnorderedId {
if let Some(term_id) = self.dict.get(term) {
return *term_id;
}
let new_id = UnorderedId(self.dict.len() as u32);
self.dict.insert(term.to_vec(), new_id);
new_id
}
/// Serialize the dictionary into an fst, and returns the
/// `UnorderedId -> TermOrdinal` map.
pub fn serialize<'a, W: io::Write + 'a>(&self, wrt: &mut W) -> io::Result<TermIdMapping> {
let mut terms: Vec<(&[u8], UnorderedId)> =
self.dict.iter().map(|(k, v)| (k.as_slice(), *v)).collect();
terms.sort_unstable_by_key(|(key, _)| *key);
// TODO Remove the allocation.
let mut unordered_to_ord: Vec<OrderedId> = vec![OrderedId(0u32); terms.len()];
let mut sstable_builder = sstable::VoidSSTable::writer(wrt);
for (ord, (key, unordered_id)) in terms.into_iter().enumerate() {
let ordered_id = OrderedId(ord as u32);
sstable_builder.insert(key, &())?;
unordered_to_ord[unordered_id.0 as usize] = ordered_id;
}
sstable_builder.finish()?;
Ok(TermIdMapping { unordered_to_ord })
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_dictionary_builder() {
let mut dictionary_builder = DictionaryBuilder::default();
let hello_uid = dictionary_builder.get_or_allocate_id(b"hello");
let happy_uid = dictionary_builder.get_or_allocate_id(b"happy");
let tax_uid = dictionary_builder.get_or_allocate_id(b"tax");
let mut buffer = Vec::new();
let id_mapping = dictionary_builder.serialize(&mut buffer).unwrap();
assert_eq!(id_mapping.to_ord(hello_uid), OrderedId(1));
assert_eq!(id_mapping.to_ord(happy_uid), OrderedId(0));
assert_eq!(id_mapping.to_ord(tax_uid), OrderedId(2));
}
}

261
columnar/src/dynamic_column.rs Normal file
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use std::io;
use std::net::Ipv6Addr;
use std::sync::Arc;
use common::file_slice::FileSlice;
use common::{HasLen, OwnedBytes};
use crate::column::{BytesColumn, Column, StrColumn};
use crate::column_values::{monotonic_map_column, StrictlyMonotonicFn};
use crate::columnar::ColumnType;
use crate::{Cardinality, DateTime, NumericalType};
#[derive(Clone)]
pub enum DynamicColumn {
Bool(Column<bool>),
I64(Column<i64>),
U64(Column<u64>),
F64(Column<f64>),
IpAddr(Column<Ipv6Addr>),
DateTime(Column<DateTime>),
Bytes(BytesColumn),
Str(StrColumn),
}
impl DynamicColumn {
pub fn get_cardinality(&self) -> Cardinality {
match self {
DynamicColumn::Bool(c) => c.get_cardinality(),
DynamicColumn::I64(c) => c.get_cardinality(),
DynamicColumn::U64(c) => c.get_cardinality(),
DynamicColumn::F64(c) => c.get_cardinality(),
DynamicColumn::IpAddr(c) => c.get_cardinality(),
DynamicColumn::DateTime(c) => c.get_cardinality(),
DynamicColumn::Bytes(c) => c.ords().get_cardinality(),
DynamicColumn::Str(c) => c.ords().get_cardinality(),
}
}
pub fn column_type(&self) -> ColumnType {
match self {
DynamicColumn::Bool(_) => ColumnType::Bool,
DynamicColumn::I64(_) => ColumnType::I64,
DynamicColumn::U64(_) => ColumnType::U64,
DynamicColumn::F64(_) => ColumnType::F64,
DynamicColumn::IpAddr(_) => ColumnType::IpAddr,
DynamicColumn::DateTime(_) => ColumnType::DateTime,
DynamicColumn::Bytes(_) => ColumnType::Bytes,
DynamicColumn::Str(_) => ColumnType::Str,
}
}
pub fn coerce_numerical(self, target_numerical_type: NumericalType) -> Option<Self> {
match target_numerical_type {
NumericalType::I64 => self.coerce_to_i64(),
NumericalType::U64 => self.coerce_to_u64(),
NumericalType::F64 => self.coerce_to_f64(),
}
}
pub fn is_numerical(&self) -> bool {
self.column_type().numerical_type().is_some()
}
pub fn is_f64(&self) -> bool {
self.column_type().numerical_type() == Some(NumericalType::F64)
}
pub fn is_i64(&self) -> bool {
self.column_type().numerical_type() == Some(NumericalType::I64)
}
pub fn is_u64(&self) -> bool {
self.column_type().numerical_type() == Some(NumericalType::U64)
}
fn coerce_to_f64(self) -> Option<DynamicColumn> {
match self {
DynamicColumn::I64(column) => Some(DynamicColumn::F64(Column {
idx: column.idx,
values: Arc::new(monotonic_map_column(column.values, MapI64ToF64)),
})),
DynamicColumn::U64(column) => Some(DynamicColumn::F64(Column {
idx: column.idx,
values: Arc::new(monotonic_map_column(column.values, MapU64ToF64)),
})),
DynamicColumn::F64(_) => Some(self),
_ => None,
}
}
fn coerce_to_i64(self) -> Option<DynamicColumn> {
match self {
DynamicColumn::U64(column) => {
if column.max_value() > i64::MAX as u64 {
return None;
}
Some(DynamicColumn::I64(Column {
idx: column.idx,
values: Arc::new(monotonic_map_column(column.values, MapU64ToI64)),
}))
}
DynamicColumn::I64(_) => Some(self),
_ => None,
}
}
fn coerce_to_u64(self) -> Option<DynamicColumn> {
match self {
DynamicColumn::I64(column) => {
if column.min_value() < 0 {
return None;
}
Some(DynamicColumn::U64(Column {
idx: column.idx,
values: Arc::new(monotonic_map_column(column.values, MapI64ToU64)),
}))
}
DynamicColumn::U64(_) => Some(self),
_ => None,
}
}
}
struct MapI64ToF64;
impl StrictlyMonotonicFn<i64, f64> for MapI64ToF64 {
#[inline(always)]
fn mapping(&self, inp: i64) -> f64 {
inp as f64
}
#[inline(always)]
fn inverse(&self, out: f64) -> i64 {
out as i64
}
}
struct MapU64ToF64;
impl StrictlyMonotonicFn<u64, f64> for MapU64ToF64 {
#[inline(always)]
fn mapping(&self, inp: u64) -> f64 {
inp as f64
}
#[inline(always)]
fn inverse(&self, out: f64) -> u64 {
out as u64
}
}
struct MapU64ToI64;
impl StrictlyMonotonicFn<u64, i64> for MapU64ToI64 {
#[inline(always)]
fn mapping(&self, inp: u64) -> i64 {
inp as i64
}
#[inline(always)]
fn inverse(&self, out: i64) -> u64 {
out as u64
}
}
struct MapI64ToU64;
impl StrictlyMonotonicFn<i64, u64> for MapI64ToU64 {
#[inline(always)]
fn mapping(&self, inp: i64) -> u64 {
inp as u64
}
#[inline(always)]
fn inverse(&self, out: u64) -> i64 {
out as i64
}
}
macro_rules! static_dynamic_conversions {
($typ:ty, $enum_name:ident) => {
impl Into<Option<$typ>> for DynamicColumn {
fn into(self) -> Option<$typ> {
if let DynamicColumn::$enum_name(col) = self {
Some(col)
} else {
None
}
}
}
impl From<$typ> for DynamicColumn {
fn from(typed_column: $typ) -> Self {
DynamicColumn::$enum_name(typed_column)
}
}
};
}
static_dynamic_conversions!(Column<bool>, Bool);
static_dynamic_conversions!(Column<u64>, U64);
static_dynamic_conversions!(Column<i64>, I64);
static_dynamic_conversions!(Column<f64>, F64);
static_dynamic_conversions!(Column<crate::DateTime>, DateTime);
static_dynamic_conversions!(StrColumn, Str);
static_dynamic_conversions!(BytesColumn, Bytes);
static_dynamic_conversions!(Column<Ipv6Addr>, IpAddr);
#[derive(Clone)]
pub struct DynamicColumnHandle {
pub(crate) file_slice: FileSlice,
pub(crate) column_type: ColumnType,
}
impl DynamicColumnHandle {
// TODO rename load
pub fn open(&self) -> io::Result<DynamicColumn> {
let column_bytes: OwnedBytes = self.file_slice.read_bytes()?;
self.open_internal(column_bytes)
}
// TODO rename load_async
pub async fn open_async(&self) -> io::Result<DynamicColumn> {
let column_bytes: OwnedBytes = self.file_slice.read_bytes_async().await?;
self.open_internal(column_bytes)
}
/// Returns the `u64` fast field reader reader associated with `fields` of types
/// Str, u64, i64, f64, or datetime.
///
/// If not, the fastfield reader will returns the u64-value associated with the original
/// FastValue.
pub fn open_u64_lenient(&self) -> io::Result<Option<Column<u64>>> {
let column_bytes = self.file_slice.read_bytes()?;
match self.column_type {
ColumnType::Str | ColumnType::Bytes => {
let column: BytesColumn = crate::column::open_column_bytes(column_bytes)?;
Ok(Some(column.term_ord_column))
}
ColumnType::Bool => Ok(None),
ColumnType::IpAddr => Ok(None),
ColumnType::I64 | ColumnType::U64 | ColumnType::F64 | ColumnType::DateTime => {
let column = crate::column::open_column_u64::<u64>(column_bytes)?;
Ok(Some(column))
}
}
}
fn open_internal(&self, column_bytes: OwnedBytes) -> io::Result<DynamicColumn> {
let dynamic_column: DynamicColumn = match self.column_type {
ColumnType::Bytes => {
crate::column::open_column_bytes::<BytesColumn>(column_bytes)?.into()
}
ColumnType::Str => crate::column::open_column_bytes::<StrColumn>(column_bytes)?.into(),
ColumnType::I64 => crate::column::open_column_u64::<i64>(column_bytes)?.into(),
ColumnType::U64 => crate::column::open_column_u64::<u64>(column_bytes)?.into(),
ColumnType::F64 => crate::column::open_column_u64::<f64>(column_bytes)?.into(),
ColumnType::Bool => crate::column::open_column_u64::<bool>(column_bytes)?.into(),
ColumnType::IpAddr => crate::column::open_column_u128::<Ipv6Addr>(column_bytes)?.into(),
ColumnType::DateTime => {
crate::column::open_column_u64::<crate::DateTime>(column_bytes)?.into()
}
};
Ok(dynamic_column)
}
pub fn num_bytes(&self) -> usize {
self.file_slice.len()
}
pub fn column_type(&self) -> ColumnType {
self.column_type
}
}

19
columnar/src/iterable.rs Normal file
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@@ -0,0 +1,19 @@
use std::ops::Range;
pub trait Iterable<T = u64> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_>;
}
impl<'a, T: Copy> Iterable<T> for &'a [T] {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
Box::new(self.iter().copied())
}
}
impl<T: Copy> Iterable<T> for Range<T>
where Range<T>: Iterator<Item = T>
{
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
Box::new(self.clone())
}
}

91
columnar/src/lib.rs Normal file
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@@ -0,0 +1,91 @@
#![cfg_attr(all(feature = "unstable", test), feature(test))]
#[cfg(test)]
#[macro_use]
extern crate more_asserts;
#[cfg(all(test, feature = "unstable"))]
extern crate test;
use std::io;
mod column;
mod column_index;
pub mod column_values;
mod columnar;
mod dictionary;
mod dynamic_column;
mod iterable;
pub(crate) mod utils;
mod value;
pub use column::{BytesColumn, Column, StrColumn};
pub use column_index::ColumnIndex;
pub use column_values::{ColumnValues, MonotonicallyMappableToU128, MonotonicallyMappableToU64};
pub use columnar::{
merge_columnar, ColumnType, ColumnarReader, ColumnarWriter, HasAssociatedColumnType,
MergeRowOrder, StackMergeOrder,
};
use sstable::VoidSSTable;
pub use value::{NumericalType, NumericalValue};
pub use self::dynamic_column::{DynamicColumn, DynamicColumnHandle};
pub type RowId = u32;
pub use sstable::Dictionary;
pub type Streamer<'a> = sstable::Streamer<'a, VoidSSTable>;
#[derive(Clone, Copy, PartialOrd, PartialEq, Default, Debug)]
pub struct DateTime {
pub timestamp_micros: i64,
}
#[derive(Copy, Clone, Debug)]
pub struct InvalidData;
impl From<InvalidData> for io::Error {
fn from(_: InvalidData) -> Self {
io::Error::new(io::ErrorKind::InvalidData, "Invalid data")
}
}
/// Enum describing the number of values that can exist per document
/// (or per row if you will).
///
/// The cardinality must fit on 2 bits.
#[derive(Clone, Copy, Hash, Default, Debug, PartialEq, Eq, PartialOrd, Ord)]
#[repr(u8)]
pub enum Cardinality {
/// All documents contain exactly one value.
/// `Full` is the default for auto-detecting the Cardinality, since it is the most strict.
#[default]
Full = 0,
/// All documents contain at most one value.
Optional = 1,
/// All documents may contain any number of values.
Multivalued = 2,
}
impl Cardinality {
pub fn is_optional(&self) -> bool {
matches!(self, Cardinality::Optional)
}
pub fn is_multivalue(&self) -> bool {
matches!(self, Cardinality::Multivalued)
}
pub(crate) fn to_code(self) -> u8 {
self as u8
}
pub(crate) fn try_from_code(code: u8) -> Result<Cardinality, InvalidData> {
match code {
0 => Ok(Cardinality::Full),
1 => Ok(Cardinality::Optional),
2 => Ok(Cardinality::Multivalued),
_ => Err(InvalidData),
}
}
}
#[cfg(test)]
mod tests;

212
columnar/src/tests.rs Normal file
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@@ -0,0 +1,212 @@
use std::net::Ipv6Addr;
use crate::column_values::MonotonicallyMappableToU128;
use crate::columnar::ColumnType;
use crate::dynamic_column::{DynamicColumn, DynamicColumnHandle};
use crate::value::NumericalValue;
use crate::{Cardinality, ColumnarReader, ColumnarWriter};
#[test]
fn test_dataframe_writer_str() {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_str(1u32, "my_string", "hello");
dataframe_writer.record_str(3u32, "my_string", "helloeee");
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
assert_eq!(cols.len(), 1);
assert_eq!(cols[0].num_bytes(), 158);
}
#[test]
fn test_dataframe_writer_bytes() {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_bytes(1u32, "my_string", b"hello");
dataframe_writer.record_bytes(3u32, "my_string", b"helloeee");
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
assert_eq!(cols.len(), 1);
assert_eq!(cols[0].num_bytes(), 158);
}
#[test]
fn test_dataframe_writer_bool() {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_bool(1u32, "bool.value", false);
dataframe_writer.record_bool(3u32, "bool.value", true);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("bool.value").unwrap();
assert_eq!(cols.len(), 1);
assert_eq!(cols[0].num_bytes(), 22);
assert_eq!(cols[0].column_type(), ColumnType::Bool);
let dyn_bool_col = cols[0].open().unwrap();
let DynamicColumn::Bool(bool_col) = dyn_bool_col else { panic!(); };
let vals: Vec<Option<bool>> = (0..5).map(|row_id| bool_col.first(row_id)).collect();
assert_eq!(&vals, &[None, Some(false), None, Some(true), None,]);
}
#[test]
fn test_dataframe_writer_u64_multivalued() {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_numerical(2u32, "divisor", 2u64);
dataframe_writer.record_numerical(3u32, "divisor", 3u64);
dataframe_writer.record_numerical(4u32, "divisor", 2u64);
dataframe_writer.record_numerical(5u32, "divisor", 5u64);
dataframe_writer.record_numerical(6u32, "divisor", 2u64);
dataframe_writer.record_numerical(6u32, "divisor", 3u64);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(7, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("divisor").unwrap();
assert_eq!(cols.len(), 1);
assert_eq!(cols[0].num_bytes(), 29);
let dyn_i64_col = cols[0].open().unwrap();
let DynamicColumn::I64(divisor_col) = dyn_i64_col else { panic!(); };
assert_eq!(
divisor_col.get_cardinality(),
crate::Cardinality::Multivalued
);
assert_eq!(divisor_col.num_rows(), 7);
}
#[test]
fn test_dataframe_writer_ip_addr() {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_ip_addr(1, "ip_addr", Ipv6Addr::from_u128(1001));
dataframe_writer.record_ip_addr(3, "ip_addr", Ipv6Addr::from_u128(1050));
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("ip_addr").unwrap();
assert_eq!(cols.len(), 1);
assert_eq!(cols[0].num_bytes(), 42);
assert_eq!(cols[0].column_type(), ColumnType::IpAddr);
let dyn_bool_col = cols[0].open().unwrap();
let DynamicColumn::IpAddr(ip_col) = dyn_bool_col else { panic!(); };
let vals: Vec<Option<Ipv6Addr>> = (0..5).map(|row_id| ip_col.first(row_id)).collect();
assert_eq!(
&vals,
&[
None,
Some(Ipv6Addr::from_u128(1001)),
None,
Some(Ipv6Addr::from_u128(1050)),
None,
]
);
}
#[test]
fn test_dataframe_writer_numerical() {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_numerical(1u32, "srical.value", NumericalValue::U64(12u64));
dataframe_writer.record_numerical(2u32, "srical.value", NumericalValue::U64(13u64));
dataframe_writer.record_numerical(4u32, "srical.value", NumericalValue::U64(15u64));
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(6, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("srical.value").unwrap();
assert_eq!(cols.len(), 1);
// Right now this 31 bytes are spent as follows
//
// - header 14 bytes
// - vals 8 //< due to padding? could have been 1byte?.
// - null footer 6 bytes
assert_eq!(cols[0].num_bytes(), 33);
let column = cols[0].open().unwrap();
let DynamicColumn::I64(column_i64) = column else { panic!(); };
assert_eq!(column_i64.idx.get_cardinality(), Cardinality::Optional);
assert_eq!(column_i64.first(0), None);
assert_eq!(column_i64.first(1), Some(12i64));
assert_eq!(column_i64.first(2), Some(13i64));
assert_eq!(column_i64.first(3), None);
assert_eq!(column_i64.first(4), Some(15i64));
assert_eq!(column_i64.first(5), None);
assert_eq!(column_i64.first(6), None); //< we can change the spec for that one.
}
#[test]
fn test_dictionary_encoded_str() {
let mut buffer = Vec::new();
let mut columnar_writer = ColumnarWriter::default();
columnar_writer.record_str(1, "my.column", "a");
columnar_writer.record_str(3, "my.column", "c");
columnar_writer.record_str(3, "my.column2", "different_column!");
columnar_writer.record_str(4, "my.column", "b");
columnar_writer.serialize(5, &mut buffer).unwrap();
let columnar_reader = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar_reader.num_columns(), 2);
let col_handles = columnar_reader.read_columns("my.column").unwrap();
assert_eq!(col_handles.len(), 1);
let DynamicColumn::Str(str_col) = col_handles[0].open().unwrap() else { panic!(); };
let index: Vec<Option<u64>> = (0..5).map(|row_id| str_col.ords().first(row_id)).collect();
assert_eq!(index, &[None, Some(0), None, Some(2), Some(1)]);
assert_eq!(str_col.num_rows(), 5);
let mut term_buffer = String::new();
let term_ords = str_col.ords();
assert_eq!(term_ords.first(0), None);
assert_eq!(term_ords.first(1), Some(0));
str_col.ord_to_str(0u64, &mut term_buffer).unwrap();
assert_eq!(term_buffer, "a");
assert_eq!(term_ords.first(2), None);
assert_eq!(term_ords.first(3), Some(2));
str_col.ord_to_str(2u64, &mut term_buffer).unwrap();
assert_eq!(term_buffer, "c");
assert_eq!(term_ords.first(4), Some(1));
str_col.ord_to_str(1u64, &mut term_buffer).unwrap();
assert_eq!(term_buffer, "b");
}
#[test]
fn test_dictionary_encoded_bytes() {
let mut buffer = Vec::new();
let mut columnar_writer = ColumnarWriter::default();
columnar_writer.record_bytes(1, "my.column", b"a");
columnar_writer.record_bytes(3, "my.column", b"c");
columnar_writer.record_bytes(3, "my.column2", b"different_column!");
columnar_writer.record_bytes(4, "my.column", b"b");
columnar_writer.serialize(5, &mut buffer).unwrap();
let columnar_reader = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar_reader.num_columns(), 2);
let col_handles = columnar_reader.read_columns("my.column").unwrap();
assert_eq!(col_handles.len(), 1);
let DynamicColumn::Bytes(bytes_col) = col_handles[0].open().unwrap() else { panic!(); };
let index: Vec<Option<u64>> = (0..5)
.map(|row_id| bytes_col.ords().first(row_id))
.collect();
assert_eq!(index, &[None, Some(0), None, Some(2), Some(1)]);
assert_eq!(bytes_col.num_rows(), 5);
let mut term_buffer = Vec::new();
let term_ords = bytes_col.ords();
assert_eq!(term_ords.first(0), None);
assert_eq!(term_ords.first(1), Some(0));
bytes_col
.dictionary
.ord_to_term(0u64, &mut term_buffer)
.unwrap();
assert_eq!(term_buffer, b"a");
assert_eq!(term_ords.first(2), None);
assert_eq!(term_ords.first(3), Some(2));
bytes_col
.dictionary
.ord_to_term(2u64, &mut term_buffer)
.unwrap();
assert_eq!(term_buffer, b"c");
assert_eq!(term_ords.first(4), Some(1));
bytes_col
.dictionary
.ord_to_term(1u64, &mut term_buffer)
.unwrap();
assert_eq!(term_buffer, b"b");
}

76
columnar/src/utils.rs Normal file
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@@ -0,0 +1,76 @@
const fn compute_mask(num_bits: u8) -> u8 {
if num_bits == 8 {
u8::MAX
} else {
(1u8 << num_bits) - 1
}
}
#[inline(always)]
#[must_use]
pub(crate) fn select_bits<const START: u8, const END: u8>(code: u8) -> u8 {
assert!(START <= END);
assert!(END <= 8);
let num_bits: u8 = END - START;
let mask: u8 = compute_mask(num_bits);
(code >> START) & mask
}
#[inline(always)]
#[must_use]
pub(crate) fn place_bits<const START: u8, const END: u8>(code: u8) -> u8 {
assert!(START <= END);
assert!(END <= 8);
let num_bits: u8 = END - START;
let mask: u8 = compute_mask(num_bits);
assert!(code <= mask);
code << START
}
/// Pop-front one bytes from a slice of bytes.
#[inline(always)]
pub fn pop_first_byte(bytes: &mut &[u8]) -> Option<u8> {
if bytes.is_empty() {
return None;
}
let first_byte = bytes[0];
*bytes = &bytes[1..];
Some(first_byte)
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_select_bits() {
assert_eq!(255u8, select_bits::<0, 8>(255u8));
assert_eq!(0u8, select_bits::<0, 0>(255u8));
assert_eq!(8u8, select_bits::<0, 4>(8u8));
assert_eq!(4u8, select_bits::<1, 4>(8u8));
assert_eq!(0u8, select_bits::<1, 3>(8u8));
}
#[test]
fn test_place_bits() {
assert_eq!(255u8, place_bits::<0, 8>(255u8));
assert_eq!(4u8, place_bits::<2, 3>(1u8));
assert_eq!(0u8, place_bits::<2, 2>(0u8));
}
#[test]
#[should_panic]
fn test_place_bits_overflows() {
let _ = place_bits::<1, 4>(8u8);
}
#[test]
fn test_pop_first_byte() {
let mut cursor: &[u8] = &b"abcd"[..];
assert_eq!(pop_first_byte(&mut cursor), Some(b'a'));
assert_eq!(pop_first_byte(&mut cursor), Some(b'b'));
assert_eq!(pop_first_byte(&mut cursor), Some(b'c'));
assert_eq!(pop_first_byte(&mut cursor), Some(b'd'));
assert_eq!(pop_first_byte(&mut cursor), None);
}
}

129
columnar/src/value.rs Normal file
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@@ -0,0 +1,129 @@
use crate::InvalidData;
#[derive(Copy, Clone, PartialEq, Debug)]
pub enum NumericalValue {
I64(i64),
U64(u64),
F64(f64),
}
impl NumericalValue {
pub fn numerical_type(&self) -> NumericalType {
match self {
NumericalValue::I64(_) => NumericalType::I64,
NumericalValue::U64(_) => NumericalType::U64,
NumericalValue::F64(_) => NumericalType::F64,
}
}
}
impl From<u64> for NumericalValue {
fn from(val: u64) -> NumericalValue {
NumericalValue::U64(val)
}
}
impl From<i64> for NumericalValue {
fn from(val: i64) -> Self {
NumericalValue::I64(val)
}
}
impl From<f64> for NumericalValue {
fn from(val: f64) -> Self {
NumericalValue::F64(val)
}
}
#[derive(Clone, Copy, Debug, Default, Hash, Eq, PartialEq)]
#[repr(u8)]
pub enum NumericalType {
#[default]
I64 = 0,
U64 = 1,
F64 = 2,
}
impl NumericalType {
pub fn to_code(self) -> u8 {
self as u8
}
pub fn try_from_code(code: u8) -> Result<NumericalType, InvalidData> {
match code {
0 => Ok(NumericalType::I64),
1 => Ok(NumericalType::U64),
2 => Ok(NumericalType::F64),
_ => Err(InvalidData),
}
}
}
/// We voluntarily avoid using `Into` here to keep this
/// implementation quirk as private as possible.
///
/// # Panics
/// This coercion trait actually panics if it is used
/// to convert a loose types to a stricter type.
///
/// The level is strictness is somewhat arbitrary.
/// - i64
/// - u64
/// - f64.
pub(crate) trait Coerce {
fn coerce(numerical_value: NumericalValue) -> Self;
}
impl Coerce for i64 {
fn coerce(value: NumericalValue) -> Self {
match value {
NumericalValue::I64(val) => val,
NumericalValue::U64(val) => val as i64,
NumericalValue::F64(_) => unreachable!(),
}
}
}
impl Coerce for u64 {
fn coerce(value: NumericalValue) -> Self {
match value {
NumericalValue::I64(val) => val as u64,
NumericalValue::U64(val) => val,
NumericalValue::F64(_) => unreachable!(),
}
}
}
impl Coerce for f64 {
fn coerce(value: NumericalValue) -> Self {
match value {
NumericalValue::I64(val) => val as f64,
NumericalValue::U64(val) => val as f64,
NumericalValue::F64(val) => val,
}
}
}
impl Coerce for crate::DateTime {
fn coerce(value: NumericalValue) -> Self {
let timestamp_micros = i64::coerce(value);
crate::DateTime { timestamp_micros }
}
}
#[cfg(test)]
mod tests {
use super::NumericalType;
#[test]
fn test_numerical_type_code() {
let mut num_numerical_type = 0;
for code in u8::MIN..=u8::MAX {
if let Ok(numerical_type) = NumericalType::try_from_code(code) {
assert_eq!(numerical_type.to_code(), code);
num_numerical_type += 1;
}
}
assert_eq!(num_numerical_type, 3);
}
}

5
common/Cargo.toml
View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-common"
version = "0.4.0"
version = "0.5.0"
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
license = "MIT"
edition = "2021"
@@ -14,7 +14,8 @@ repository = "https://github.com/quickwit-oss/tantivy"
[dependencies]
byteorder = "1.4.3"
ownedbytes = { version= "0.4", path="../ownedbytes" }
ownedbytes = { version= "0.5", path="../ownedbytes" }
async-trait = "0.1"
[dev-dependencies]
proptest = "1.0.0"

6
common/src/bitset.rs
View File

@@ -151,7 +151,7 @@ impl TinySet {
if self.is_empty() {
None
} else {
let lowest = self.0.trailing_zeros() as u32;
let lowest = self.0.trailing_zeros();
self.0 ^= TinySet::singleton(lowest).0;
Some(lowest)
}
@@ -421,7 +421,7 @@ mod tests {
bitset.serialize(&mut out).unwrap();
let bitset = ReadOnlyBitSet::open(OwnedBytes::new(out));
assert_eq!(bitset.len() as usize, i as usize);
assert_eq!(bitset.len(), i as usize);
}
}
@@ -432,7 +432,7 @@ mod tests {
bitset.serialize(&mut out).unwrap();
let bitset = ReadOnlyBitSet::open(OwnedBytes::new(out));
assert_eq!(bitset.len() as usize, 64);
assert_eq!(bitset.len(), 64);
}
#[test]

99
src/directory/file_slice.rs → common/src/file_slice.rs
View File

@@ -1,19 +1,18 @@
use std::ops::{Deref, Range};
use std::ops::{Deref, Range, RangeBounds};
use std::sync::Arc;
use std::{fmt, io};
use async_trait::async_trait;
use common::HasLen;
use stable_deref_trait::StableDeref;
use ownedbytes::{OwnedBytes, StableDeref};
use crate::directory::OwnedBytes;
use crate::HasLen;
/// 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`](crate::Directory) that
/// 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
/// on the filesystem.
@@ -24,13 +23,12 @@ pub trait FileHandle: 'static + Send + Sync + HasLen + fmt::Debug {
/// This method may panic if the range requested is invalid.
fn read_bytes(&self, range: Range<usize>) -> io::Result<OwnedBytes>;
#[cfg(feature = "quickwit")]
#[doc(hidden)]
async fn read_bytes_async(
&self,
_byte_range: Range<usize>,
) -> crate::AsyncIoResult<OwnedBytes> {
Err(crate::error::AsyncIoError::AsyncUnsupported)
async fn read_bytes_async(&self, _byte_range: Range<usize>) -> io::Result<OwnedBytes> {
Err(io::Error::new(
io::ErrorKind::Unsupported,
"Async read is not supported.",
))
}
}
@@ -41,8 +39,7 @@ impl FileHandle for &'static [u8] {
Ok(OwnedBytes::new(bytes))
}
#[cfg(feature = "quickwit")]
async fn read_bytes_async(&self, byte_range: Range<usize>) -> crate::AsyncIoResult<OwnedBytes> {
async fn read_bytes_async(&self, byte_range: Range<usize>) -> io::Result<OwnedBytes> {
Ok(self.read_bytes(byte_range)?)
}
}
@@ -70,6 +67,34 @@ impl fmt::Debug for FileSlice {
}
}
/// Takes a range, a `RangeBounds` object, and returns
/// a `Range` that corresponds to the relative application of the
/// `RangeBounds` object to the original `Range`.
///
/// For instance, combine_ranges(`[2..11)`, `[5..7]`) returns `[7..10]`
/// as it reads, what is the sub-range that starts at the 5 element of
/// `[2..11)` and ends at the 9th element included.
///
/// This function panics, if the result would suggest something outside
/// of the bounds of the original range.
fn combine_ranges<R: RangeBounds<usize>>(orig_range: Range<usize>, rel_range: R) -> Range<usize> {
let start: usize = orig_range.start
+ match rel_range.start_bound().cloned() {
std::ops::Bound::Included(rel_start) => rel_start,
std::ops::Bound::Excluded(rel_start) => rel_start + 1,
std::ops::Bound::Unbounded => 0,
};
assert!(start <= orig_range.end);
let end: usize = match rel_range.end_bound().cloned() {
std::ops::Bound::Included(rel_end) => orig_range.start + rel_end + 1,
std::ops::Bound::Excluded(rel_end) => orig_range.start + rel_end,
std::ops::Bound::Unbounded => orig_range.end,
};
assert!(end >= start);
assert!(end <= orig_range.end);
start..end
}
impl FileSlice {
/// Wraps a FileHandle.
pub fn new(file_handle: Arc<dyn FileHandle>) -> Self {
@@ -93,11 +118,11 @@ impl FileSlice {
///
/// Panics if `byte_range.end` exceeds the filesize.
#[must_use]
pub fn slice(&self, byte_range: Range<usize>) -> FileSlice {
assert!(byte_range.end <= self.len());
#[inline]
pub fn slice<R: RangeBounds<usize>>(&self, byte_range: R) -> FileSlice {
FileSlice {
data: self.data.clone(),
range: self.range.start + byte_range.start..self.range.start + byte_range.end,
range: combine_ranges(self.range.clone(), byte_range),
}
}
@@ -117,9 +142,8 @@ impl FileSlice {
self.data.read_bytes(self.range.clone())
}
#[cfg(feature = "quickwit")]
#[doc(hidden)]
pub async fn read_bytes_async(&self) -> crate::AsyncIoResult<OwnedBytes> {
pub async fn read_bytes_async(&self) -> io::Result<OwnedBytes> {
self.data.read_bytes_async(self.range.clone()).await
}
@@ -137,12 +161,8 @@ impl FileSlice {
.read_bytes(self.range.start + range.start..self.range.start + range.end)
}
#[cfg(feature = "quickwit")]
#[doc(hidden)]
pub async fn read_bytes_slice_async(
&self,
byte_range: Range<usize>,
) -> crate::AsyncIoResult<OwnedBytes> {
pub async fn read_bytes_slice_async(&self, byte_range: Range<usize>) -> io::Result<OwnedBytes> {
assert!(
self.range.start + byte_range.end <= self.range.end,
"`to` exceeds the fileslice length"
@@ -204,8 +224,7 @@ impl FileHandle for FileSlice {
self.read_bytes_slice(range)
}
#[cfg(feature = "quickwit")]
async fn read_bytes_async(&self, byte_range: Range<usize>) -> crate::AsyncIoResult<OwnedBytes> {
async fn read_bytes_async(&self, byte_range: Range<usize>) -> io::Result<OwnedBytes> {
self.read_bytes_slice_async(byte_range).await
}
}
@@ -222,21 +241,20 @@ impl FileHandle for OwnedBytes {
Ok(self.slice(range))
}
#[cfg(feature = "quickwit")]
async fn read_bytes_async(&self, range: Range<usize>) -> crate::AsyncIoResult<OwnedBytes> {
let bytes = self.read_bytes(range)?;
Ok(bytes)
async fn read_bytes_async(&self, range: Range<usize>) -> io::Result<OwnedBytes> {
self.read_bytes(range)
}
}
#[cfg(test)]
mod tests {
use std::io;
use std::ops::Bound;
use std::sync::Arc;
use common::HasLen;
use super::{FileHandle, FileSlice};
use crate::file_slice::combine_ranges;
use crate::HasLen;
#[test]
fn test_file_slice() -> io::Result<()> {
@@ -307,4 +325,23 @@ mod tests {
b"bcd"
);
}
#[test]
fn test_combine_range() {
assert_eq!(combine_ranges(1..3, 0..1), 1..2);
assert_eq!(combine_ranges(1..3, 1..), 2..3);
assert_eq!(combine_ranges(1..4, ..2), 1..3);
assert_eq!(combine_ranges(3..10, 2..5), 5..8);
assert_eq!(combine_ranges(2..11, 5..=7), 7..10);
assert_eq!(
combine_ranges(2..11, (Bound::Excluded(5), Bound::Unbounded)),
8..11
);
}
#[test]
#[should_panic]
fn test_combine_range_panics() {
let _ = combine_ranges(3..5, 1..4);
}
}

166
common/src/group_by.rs Normal file
View File

@@ -0,0 +1,166 @@
use std::cell::RefCell;
use std::iter::Peekable;
use std::rc::Rc;
pub trait GroupByIteratorExtended: Iterator {
/// Return an `Iterator` that groups iterator elements. Consecutive elements that map to the
/// same key are assigned to the same group.
///
/// The returned Iterator item is `(K, impl Iterator)`, where Iterator are the items of the
/// group.
///
/// ```
/// use tantivy_common::GroupByIteratorExtended;
///
/// // group data into blocks of larger than zero or not.
/// let data: Vec<i32> = vec![1, 3, -2, -2, 1, 0, 1, 2];
/// // groups: |---->|------>|--------->|
///
/// let mut data_grouped = Vec::new();
/// // Note: group is an iterator
/// for (key, group) in data.into_iter().group_by(|val| *val >= 0) {
/// data_grouped.push((key, group.collect()));
/// }
/// assert_eq!(data_grouped, vec![(true, vec![1, 3]), (false, vec![-2, -2]), (true, vec![1, 0, 1, 2])]);
/// ```
fn group_by<K, F>(self, key: F) -> GroupByIterator<Self, F, K>
where
Self: Sized,
F: FnMut(&Self::Item) -> K,
K: PartialEq + Copy,
Self::Item: Copy,
{
GroupByIterator::new(self, key)
}
}
impl<I: Iterator> GroupByIteratorExtended for I {}
pub struct GroupByIterator<I, F, K: Copy>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
{
// I really would like to avoid the Rc<RefCell>, but the Iterator is shared between
// `GroupByIterator` and `GroupIter`. In practice they are used consecutive and
// `GroupByIter` is finished before calling next on `GroupByIterator`. I'm not sure there
// is a solution with lifetimes for that, because we would need to enforce it in the usage
// somehow.
//
// One potential solution would be to replace the iterator approach with something similar.
inner: Rc<RefCell<GroupByShared<I, F, K>>>,
}
struct GroupByShared<I, F, K: Copy>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
{
iter: Peekable<I>,
group_by_fn: F,
}
impl<I, F, K> GroupByIterator<I, F, K>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
K: Copy,
{
fn new(inner: I, group_by_fn: F) -> Self {
let inner = GroupByShared {
iter: inner.peekable(),
group_by_fn,
};
Self {
inner: Rc::new(RefCell::new(inner)),
}
}
}
impl<I, F, K> Iterator for GroupByIterator<I, F, K>
where
I: Iterator,
I::Item: Copy,
F: FnMut(&I::Item) -> K,
K: Copy,
{
type Item = (K, GroupIterator<I, F, K>);
fn next(&mut self) -> Option<Self::Item> {
let mut inner = self.inner.borrow_mut();
let value = *inner.iter.peek()?;
let key = (inner.group_by_fn)(&value);
let inner = self.inner.clone();
let group_iter = GroupIterator {
inner,
group_key: key,
};
Some((key, group_iter))
}
}
pub struct GroupIterator<I, F, K: Copy>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
{
inner: Rc<RefCell<GroupByShared<I, F, K>>>,
group_key: K,
}
impl<I, F, K: PartialEq + Copy> Iterator for GroupIterator<I, F, K>
where
I: Iterator,
I::Item: Copy,
F: FnMut(&I::Item) -> K,
{
type Item = I::Item;
fn next(&mut self) -> Option<Self::Item> {
let mut inner = self.inner.borrow_mut();
// peek if next value is in group
let peek_val = *inner.iter.peek()?;
if (inner.group_by_fn)(&peek_val) == self.group_key {
inner.iter.next()
} else {
None
}
}
}
#[cfg(test)]
mod tests {
use super::*;
fn group_by_collect<I: Iterator<Item = u32>>(iter: I) -> Vec<(I::Item, Vec<I::Item>)> {
iter.group_by(|val| val / 10)
.map(|(el, iter)| (el, iter.collect::<Vec<_>>()))
.collect::<Vec<_>>()
}
#[test]
fn group_by_two_groups() {
let vals = vec![1u32, 4, 15];
let grouped_vals = group_by_collect(vals.into_iter());
assert_eq!(grouped_vals, vec![(0, vec![1, 4]), (1, vec![15])]);
}
#[test]
fn group_by_test_empty() {
let vals = vec![];
let grouped_vals = group_by_collect(vals.into_iter());
assert_eq!(grouped_vals, vec![]);
}
#[test]
fn group_by_three_groups() {
let vals = vec![1u32, 4, 15, 1];
let grouped_vals = group_by_collect(vals.into_iter());
assert_eq!(
grouped_vals,
vec![(0, vec![1, 4]), (1, vec![15]), (0, vec![1])]
);
}
}

5
common/src/lib.rs
View File

@@ -5,11 +5,14 @@ use std::ops::Deref;
pub use byteorder::LittleEndian as Endianness;
mod bitset;
pub mod file_slice;
mod group_by;
mod serialize;
mod vint;
mod writer;
pub use bitset::*;
pub use group_by::GroupByIteratorExtended;
pub use ownedbytes::{OwnedBytes, StableDeref};
pub use serialize::{BinarySerializable, DeserializeFrom, FixedSize};
pub use vint::{
deserialize_vint_u128, read_u32_vint, read_u32_vint_no_advance, serialize_vint_u128,

53
common/src/serialize.rs
View File

@@ -5,12 +5,37 @@ use byteorder::{ReadBytesExt, WriteBytesExt};
use crate::{Endianness, VInt};
#[derive(Default)]
struct Counter(u64);
impl io::Write for Counter {
fn write(&mut self, buf: &[u8]) -> io::Result<usize> {
self.0 += buf.len() as u64;
Ok(buf.len())
}
fn write_all(&mut self, buf: &[u8]) -> io::Result<()> {
self.0 += buf.len() as u64;
Ok(())
}
fn flush(&mut self) -> io::Result<()> {
Ok(())
}
}
/// Trait for a simple binary serialization.
pub trait BinarySerializable: fmt::Debug + Sized {
/// Serialize
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()>;
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()>;
/// Deserialize
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self>;
fn num_bytes(&self) -> u64 {
let mut counter = Counter::default();
self.serialize(&mut counter).unwrap();
counter.0
}
}
pub trait DeserializeFrom<T: BinarySerializable> {
@@ -34,7 +59,7 @@ pub trait FixedSize: BinarySerializable {
}
impl BinarySerializable for () {
fn serialize<W: Write>(&self, _: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, _: &mut W) -> io::Result<()> {
Ok(())
}
fn deserialize<R: Read>(_: &mut R) -> io::Result<Self> {
@@ -47,7 +72,7 @@ impl FixedSize for () {
}
impl<T: BinarySerializable> BinarySerializable for Vec<T> {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.len() as u64).serialize(writer)?;
for it in self {
it.serialize(writer)?;
@@ -66,7 +91,7 @@ impl<T: BinarySerializable> BinarySerializable for Vec<T> {
}
impl<Left: BinarySerializable, Right: BinarySerializable> BinarySerializable for (Left, Right) {
fn serialize<W: Write>(&self, write: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, write: &mut W) -> io::Result<()> {
self.0.serialize(write)?;
self.1.serialize(write)
}
@@ -81,7 +106,7 @@ impl<Left: BinarySerializable + FixedSize, Right: BinarySerializable + FixedSize
}
impl BinarySerializable for u32 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
writer.write_u32::<Endianness>(*self)
}
@@ -95,7 +120,7 @@ impl FixedSize for u32 {
}
impl BinarySerializable for u16 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
writer.write_u16::<Endianness>(*self)
}
@@ -109,7 +134,7 @@ impl FixedSize for u16 {
}
impl BinarySerializable for u64 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
writer.write_u64::<Endianness>(*self)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
@@ -122,7 +147,7 @@ impl FixedSize for u64 {
}
impl BinarySerializable for u128 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
writer.write_u128::<Endianness>(*self)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
@@ -135,7 +160,7 @@ impl FixedSize for u128 {
}
impl BinarySerializable for f32 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
writer.write_f32::<Endianness>(*self)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
@@ -148,7 +173,7 @@ impl FixedSize for f32 {
}
impl BinarySerializable for i64 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
writer.write_i64::<Endianness>(*self)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
@@ -161,7 +186,7 @@ impl FixedSize for i64 {
}
impl BinarySerializable for f64 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
writer.write_f64::<Endianness>(*self)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
@@ -174,7 +199,7 @@ impl FixedSize for f64 {
}
impl BinarySerializable for u8 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
writer.write_u8(*self)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<u8> {
@@ -187,7 +212,7 @@ impl FixedSize for u8 {
}
impl BinarySerializable for bool {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
writer.write_u8(u8::from(*self))
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<bool> {
@@ -208,7 +233,7 @@ impl FixedSize for bool {
}
impl BinarySerializable for String {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
let data: &[u8] = self.as_bytes();
VInt(data.len() as u64).serialize(writer)?;
writer.write_all(data)

4
common/src/vint.rs
View File

@@ -44,7 +44,7 @@ pub fn deserialize_vint_u128(data: &[u8]) -> io::Result<(u128, &[u8])> {
pub struct VIntU128(pub u128);
impl BinarySerializable for VIntU128 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
let mut buffer = vec![];
serialize_vint_u128(self.0, &mut buffer);
writer.write_all(&buffer)
@@ -211,7 +211,7 @@ impl VInt {
}
impl BinarySerializable for VInt {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
let mut buffer = [0u8; 10];
let num_bytes = self.serialize_into(&mut buffer);
writer.write_all(&buffer[0..num_bytes])

10
examples/aggregation.rs → examples-disabled/aggregation.rs
View File

@@ -13,7 +13,7 @@ use tantivy::aggregation::agg_result::AggregationResults;
use tantivy::aggregation::metric::AverageAggregation;
use tantivy::aggregation::AggregationCollector;
use tantivy::query::TermQuery;
use tantivy::schema::{self, Cardinality, IndexRecordOption, Schema, TextFieldIndexing};
use tantivy::schema::{self, IndexRecordOption, Schema, TextFieldIndexing};
use tantivy::{doc, Index, Term};
fn main() -> tantivy::Result<()> {
@@ -25,9 +25,9 @@ fn main() -> tantivy::Result<()> {
.set_stored();
let text_field = schema_builder.add_text_field("text", text_fieldtype);
let score_fieldtype =
crate::schema::NumericOptions::default().set_fast(Cardinality::SingleValue);
crate::schema::NumericOptions::default().set_fast();
let highscore_field = schema_builder.add_f64_field("highscore", score_fieldtype.clone());
let price_field = schema_builder.add_f64_field("price", score_fieldtype.clone());
let price_field = schema_builder.add_f64_field("price", score_fieldtype);
let schema = schema_builder.build();
@@ -112,7 +112,7 @@ fn main() -> tantivy::Result<()> {
],
..Default::default()
}),
sub_aggregation: sub_agg_req_1.clone(),
sub_aggregation: sub_agg_req_1,
}),
)]
.into_iter()
@@ -123,7 +123,7 @@ fn main() -> tantivy::Result<()> {
let searcher = reader.searcher();
let agg_res: AggregationResults = searcher.search(&term_query, &collector).unwrap();
let res: Value = serde_json::to_value(&agg_res)?;
let res: Value = serde_json::to_value(agg_res)?;
println!("{}", serde_json::to_string_pretty(&res)?);
Ok(())

0
examples/basic_search.rs → examples-disabled/basic_search.rs
View File

12
examples/custom_collector.rs → examples-disabled/custom_collector.rs
View File

@@ -14,7 +14,7 @@ use fastfield_codecs::Column;
// Importing tantivy...
use tantivy::collector::{Collector, SegmentCollector};
use tantivy::query::QueryParser;
use tantivy::schema::{Field, Schema, FAST, INDEXED, TEXT};
use tantivy::schema::{Schema, FAST, INDEXED, TEXT};
use tantivy::{doc, Index, Score, SegmentReader};
#[derive(Default)]
@@ -52,11 +52,11 @@ impl Stats {
}
struct StatsCollector {
field: Field,
field: String,
}
impl StatsCollector {
fn with_field(field: Field) -> StatsCollector {
fn with_field(field: String) -> StatsCollector {
StatsCollector { field }
}
}
@@ -73,7 +73,7 @@ impl Collector for StatsCollector {
_segment_local_id: u32,
segment_reader: &SegmentReader,
) -> tantivy::Result<StatsSegmentCollector> {
let fast_field_reader = segment_reader.fast_fields().u64(self.field)?;
let fast_field_reader = segment_reader.fast_fields().u64(&self.field)?;
Ok(StatsSegmentCollector {
fast_field_reader,
stats: Stats::default(),
@@ -171,7 +171,9 @@ fn main() -> tantivy::Result<()> {
// here we want to get a hit on the 'ken' in Frankenstein
let query = query_parser.parse_query("broom")?;
if let Some(stats) = searcher.search(&query, &StatsCollector::with_field(price))? {
if let Some(stats) =
searcher.search(&query, &StatsCollector::with_field("price".to_string()))?
{
println!("count: {}", stats.count());
println!("mean: {}", stats.mean());
println!("standard deviation: {}", stats.standard_deviation());

0
examples/custom_tokenizer.rs → examples-disabled/custom_tokenizer.rs
View File

4
examples/date_time_field.rs → examples-disabled/date_time_field.rs
View File

@@ -4,7 +4,7 @@
use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::{Cardinality, DateOptions, Schema, Value, INDEXED, STORED, STRING};
use tantivy::schema::{DateOptions, Schema, Value, INDEXED, STORED, STRING};
use tantivy::Index;
fn main() -> tantivy::Result<()> {
@@ -12,7 +12,7 @@ fn main() -> tantivy::Result<()> {
let mut schema_builder = Schema::builder();
let opts = DateOptions::from(INDEXED)
.set_stored()
.set_fast(Cardinality::SingleValue)
.set_fast()
.set_precision(tantivy::DatePrecision::Seconds);
let occurred_at = schema_builder.add_date_field("occurred_at", opts);
let event_type = schema_builder.add_text_field("event", STRING | STORED);

0
examples/deleting_updating_documents.rs → examples-disabled/deleting_updating_documents.rs
View File

20
examples/faceted_search.rs → examples-disabled/faceted_search.rs
View File

@@ -1,15 +1,17 @@
// # Basic Example
// # Faceted Search
//
// This example covers the basic functionalities of
// This example covers the faceted search functionalities of
// tantivy.
//
// We will :
// - define our schema
// = create an index in a directory
// - index few documents in our index
// - search for the best document matchings "sea whale"
// - retrieve the best document original content.
// - define a text field "name" in our schema
// - define a facet field "classification" in our schema
// - create an index in memory
// - index few documents with respective facets in our index
// - search and count the number of documents that the classifications start the facet "/Felidae"
// - Search the facet "/Felidae/Pantherinae" and count the number of documents that the
// classifications include the facet.
//
// ---
// Importing tantivy...
use tantivy::collector::FacetCollector;
@@ -21,7 +23,7 @@ fn main() -> tantivy::Result<()> {
// Let's create a temporary directory for the sake of this example
let mut schema_builder = Schema::builder();
let name = schema_builder.add_text_field("felin_name", TEXT | STORED);
let name = schema_builder.add_text_field("name", TEXT | STORED);
// this is our faceted field: its scientific classification
let classification = schema_builder.add_facet_field("classification", FacetOptions::default());

0
examples/faceted_search_with_tweaked_score.rs → examples-disabled/faceted_search_with_tweaked_score.rs
View File

2
examples/integer_range_search.rs → examples-disabled/integer_range_search.rs
View File

@@ -27,7 +27,7 @@ fn main() -> Result<()> {
reader.reload()?;
let searcher = reader.searcher();
// The end is excluded i.e. here we are searching up to 1969
let docs_in_the_sixties = RangeQuery::new_u64(year_field, 1960..1970);
let docs_in_the_sixties = RangeQuery::new_u64("year".to_string(), 1960..1970);
// Uses a Count collector to sum the total number of docs in the range
let num_60s_books = searcher.search(&docs_in_the_sixties, &Count)?;
assert_eq!(num_60s_books, 10);

73
examples-disabled/ip_field.rs Normal file
View File

@@ -0,0 +1,73 @@
// # IP Address example
//
// This example shows how the ip field can be used
// with IpV6 and IpV4.
use tantivy::collector::{Count, TopDocs};
use tantivy::query::QueryParser;
use tantivy::schema::{Schema, FAST, INDEXED, STORED, STRING};
use tantivy::Index;
fn main() -> tantivy::Result<()> {
// # Defining the schema
let mut schema_builder = Schema::builder();
let event_type = schema_builder.add_text_field("event_type", STRING | STORED);
let ip = schema_builder.add_ip_addr_field("ip", STORED | INDEXED | FAST);
let schema = schema_builder.build();
// # Indexing documents
let index = Index::create_in_ram(schema.clone());
let mut index_writer = index.writer(50_000_000)?;
let doc = schema.parse_document(
r#"{
"ip": "192.168.0.33",
"event_type": "login"
}"#,
)?;
index_writer.add_document(doc)?;
let doc = schema.parse_document(
r#"{
"ip": "192.168.0.80",
"event_type": "checkout"
}"#,
)?;
index_writer.add_document(doc)?;
let doc = schema.parse_document(
r#"{
"ip": "2001:0db8:85a3:0000:0000:8a2e:0370:7334",
"event_type": "checkout"
}"#,
)?;
index_writer.add_document(doc)?;
index_writer.commit()?;
let reader = index.reader()?;
let searcher = reader.searcher();
let query_parser = QueryParser::for_index(&index, vec![event_type, ip]);
{
let query = query_parser.parse_query("ip:[192.168.0.0 TO 192.168.0.100]")?;
let count_docs = searcher.search(&*query, &TopDocs::with_limit(5))?;
assert_eq!(count_docs.len(), 2);
}
{
let query = query_parser.parse_query("ip:[192.168.1.0 TO 192.168.1.100]")?;
let count_docs = searcher.search(&*query, &TopDocs::with_limit(2))?;
assert_eq!(count_docs.len(), 0);
}
{
let query = query_parser.parse_query("ip:192.168.0.80")?;
let count_docs = searcher.search(&*query, &Count)?;
assert_eq!(count_docs, 1);
}
{
// IpV6 needs to be escaped because it contains `:`
let query = query_parser.parse_query("ip:\"2001:0db8:85a3:0000:0000:8a2e:0370:7334\"")?;
let count_docs = searcher.search(&*query, &Count)?;
assert_eq!(count_docs, 1);
}
Ok(())
}

0
examples/iterating_docs_and_positions.rs → examples-disabled/iterating_docs_and_positions.rs
View File

0
examples/json_field.rs → examples-disabled/json_field.rs
View File

0
examples/multiple_producer.rs → examples-disabled/multiple_producer.rs
View File

0
examples/pre_tokenized_text.rs → examples-disabled/pre_tokenized_text.rs
View File

0
examples/snippet.rs → examples-disabled/snippet.rs
View File

0
examples/stop_words.rs → examples-disabled/stop_words.rs
View File

10
examples/warmer.rs → examples-disabled/warmer.rs
View File

@@ -4,7 +4,7 @@ use std::sync::{Arc, RwLock, Weak};
use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::{Field, Schema, FAST, TEXT};
use tantivy::schema::{Schema, FAST, TEXT};
use tantivy::{
doc, DocAddress, DocId, Index, IndexReader, Opstamp, Searcher, SearcherGeneration, SegmentId,
SegmentReader, Warmer,
@@ -25,13 +25,13 @@ pub trait PriceFetcher: Send + Sync + 'static {
}
struct DynamicPriceColumn {
field: Field,
field: String,
price_cache: RwLock<HashMap<(SegmentId, Option<Opstamp>), Arc<Vec<Price>>>>,
price_fetcher: Box<dyn PriceFetcher>,
}
impl DynamicPriceColumn {
pub fn with_product_id_field<T: PriceFetcher>(field: Field, price_fetcher: T) -> Self {
pub fn with_product_id_field<T: PriceFetcher>(field: String, price_fetcher: T) -> Self {
DynamicPriceColumn {
field,
price_cache: Default::default(),
@@ -48,7 +48,7 @@ impl Warmer for DynamicPriceColumn {
fn warm(&self, searcher: &Searcher) -> tantivy::Result<()> {
for segment in searcher.segment_readers() {
let key = (segment.segment_id(), segment.delete_opstamp());
let product_id_reader = segment.fast_fields().u64(self.field)?;
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_val(doc))
@@ -123,7 +123,7 @@ fn main() -> tantivy::Result<()> {
let price_table = ExternalPriceTable::default();
let price_dynamic_column = Arc::new(DynamicPriceColumn::with_product_id_field(
product_id,
"product_id".to_string(),
price_table.clone(),
));
price_table.update_price(OLIVE_OIL, 12);

0
examples/working_with_json.rs → examples-disabled/working_with_json.rs
View File

34
fastfield_codecs/Cargo.toml
View File

@@ -1,34 +0,0 @@
[package]
name = "fastfield_codecs"
version = "0.3.0"
authors = ["Pascal Seitz <pascal@quickwit.io>"]
license = "MIT"
edition = "2021"
description = "Fast field codecs used by tantivy"
documentation = "https://docs.rs/fastfield_codecs/"
homepage = "https://github.com/quickwit-oss/tantivy"
repository = "https://github.com/quickwit-oss/tantivy"
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[dependencies]
common = { version = "0.4", path = "../common/", package = "tantivy-common" }
tantivy-bitpacker = { version= "0.3", path = "../bitpacker/" }
ownedbytes = { version = "0.4.0", 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"
proptest = "1.0.0"
rand = "0.8.3"
[features]
bin = ["prettytable-rs", "rand", "measure_time"]
default = ["bin"]
unstable = []

68
fastfield_codecs/README.md
View File

@@ -1,68 +0,0 @@
# Fast Field Codecs
This crate contains various fast field codecs, used to compress/decompress fast field data in tantivy.
## Contributing
Contributing is pretty straightforward. Since the bitpacking is the simplest compressor, you can check it for reference.
A codec needs to implement 2 traits:
- A reader implementing `FastFieldCodecReader` to read the codec.
- A serializer implementing `FastFieldCodecSerializer` for compression estimation and codec name + id.
### Tests
Once the traits are implemented test and benchmark integration is pretty easy (see `test_with_codec_data_sets` and `bench.rs`).
Make sure to add the codec to the main.rs, which tests the compression ratio and estimation against different data sets. You can run it with:
```
cargo run --features bin
```
### TODO
- Add real world data sets in comparison
- Add codec to cover sparse data sets
### Codec Comparison
```
+----------------------------------+-------------------+------------------------+
| | Compression Ratio | Compression Estimation |
+----------------------------------+-------------------+------------------------+
| Autoincrement | | |
+----------------------------------+-------------------+------------------------+
| LinearInterpol | 0.000039572664 | 0.000004396963 |
+----------------------------------+-------------------+------------------------+
| MultiLinearInterpol | 0.1477348 | 0.17275847 |
+----------------------------------+-------------------+------------------------+
| Bitpacked | 0.28126493 | 0.28125 |
+----------------------------------+-------------------+------------------------+
| Monotonically increasing concave | | |
+----------------------------------+-------------------+------------------------+
| LinearInterpol | 0.25003937 | 0.26562938 |
+----------------------------------+-------------------+------------------------+
| MultiLinearInterpol | 0.190665 | 0.1883836 |
+----------------------------------+-------------------+------------------------+
| Bitpacked | 0.31251436 | 0.3125 |
+----------------------------------+-------------------+------------------------+
| Monotonically increasing convex | | |
+----------------------------------+-------------------+------------------------+
| LinearInterpol | 0.25003937 | 0.28125438 |
+----------------------------------+-------------------+------------------------+
| MultiLinearInterpol | 0.18676 | 0.2040086 |
+----------------------------------+-------------------+------------------------+
| Bitpacked | 0.31251436 | 0.3125 |
+----------------------------------+-------------------+------------------------+
| Almost monotonically increasing | | |
+----------------------------------+-------------------+------------------------+
| LinearInterpol | 0.14066513 | 0.1562544 |
+----------------------------------+-------------------+------------------------+
| MultiLinearInterpol | 0.16335973 | 0.17275847 |
+----------------------------------+-------------------+------------------------+
| Bitpacked | 0.28126493 | 0.28125 |
+----------------------------------+-------------------+------------------------+
```

246
fastfield_codecs/benches/bench.rs
View File

@@ -1,246 +0,0 @@
#![feature(test)]
extern crate test;
#[cfg(test)]
mod tests {
use std::iter;
use std::sync::Arc;
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();
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()
}
#[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 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 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 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()
}
#[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(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(
major_item..=major_item,
0..data.len() as u32,
&mut positions,
);
positions
});
}
#[bench]
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_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_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_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_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_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
});
}
#[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
});
}
}

116
fastfield_codecs/src/bitpacked.rs
View File

@@ -1,116 +0,0 @@
use std::io::{self, Write};
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::serialize::NormalizedHeader;
use crate::{Column, FastFieldCodec, FastFieldCodecType};
/// Depending on the field type, a different
/// fast field is required.
#[derive(Clone)]
pub struct BitpackedReader {
data: OwnedBytes,
bit_unpacker: BitUnpacker,
normalized_header: NormalizedHeader,
}
impl Column for BitpackedReader {
#[inline]
fn get_val(&self, doc: u32) -> u64 {
self.bit_unpacker.get(doc, &self.data)
}
#[inline]
fn min_value(&self) -> u64 {
// The BitpackedReader assumes a normalized vector.
0
}
#[inline]
fn max_value(&self) -> u64 {
self.normalized_header.max_value
}
#[inline]
fn num_vals(&self) -> u32 {
self.normalized_header.num_vals
}
}
pub struct BitpackedCodec;
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 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.
///
/// 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)?;
}
bit_packer.close(write)?;
Ok(())
}
fn estimate(column: &dyn Column) -> Option<f32> {
let num_bits = compute_num_bits(column.max_value());
let num_bits_uncompressed = 64;
Some(num_bits as f32 / num_bits_uncompressed as f32)
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::tests::get_codec_test_datasets;
fn create_and_validate(data: &[u64], name: &str) {
crate::tests::create_and_validate::<BitpackedCodec>(data, name);
}
#[test]
fn test_with_codec_data_sets() {
let data_sets = get_codec_test_datasets();
for (mut data, name) in data_sets {
create_and_validate(&data, name);
data.reverse();
create_and_validate(&data, name);
}
}
#[test]
fn bitpacked_fast_field_rand() {
for _ in 0..500 {
let mut data = (0..1 + rand::random::<u8>() as usize)
.map(|_| rand::random::<i64>() as u64 / 2)
.collect::<Vec<_>>();
create_and_validate(&data, "rand");
data.reverse();
create_and_validate(&data, "rand");
}
}
}

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