ad hoc
d5ddc6b080
fix 2 typos word derivation bug
2022-04-01 10:51:22 +02:00
ad hoc
3e34981d9b
add test for authorize_typos in update
2022-03-31 14:12:00 +02:00
ad hoc
6ef3bb9d83
fmt
2022-03-31 14:06:23 +02:00
ad hoc
f782fe2062
add authorize_typo_test
2022-03-31 10:08:39 +02:00
ad hoc
c4653347fd
add authorize typo setting
2022-03-31 10:05:44 +02:00
Clémentine Urquizar
ddf78a735b
Update version (v0.24.1)
2022-03-24 16:39:45 +01:00
Irevoire
86dd88698d
bump tokenizer
2022-03-23 14:25:58 +01:00
Irevoire
5dc464b9a7
rollback meilisearch-tokenizer version
2022-03-21 17:29:10 +01:00
bors[bot]
90276d9a2d
Merge #472
...
472: Remove useless variables in proximity r=Kerollmops a=ManyTheFish
Was passing by plane sweep algorithm to find some inspiration, and I discover that we have useless variables that were not detected because of the recursive function.
Co-authored-by: ManyTheFish <many@meilisearch.com>
2022-03-16 15:33:11 +00:00
ManyTheFish
49d59d88c2
Remove useless variables in proximity
2022-03-16 16:12:52 +01:00
Bruno Casali
adc71742c8
Move string concat to the struct instead of in the calling
2022-03-16 10:26:12 -03:00
Bruno Casali
4822fe1beb
Add a better error message when the filterable attrs are empty
...
Fixes https://github.com/meilisearch/meilisearch/issues/2140
2022-03-15 18:13:59 -03:00
bors[bot]
f04ab67083
Merge #466
...
466: Bump version to 0.23.1 r=curquiza a=Kerollmops
This PR bumps the crate versions to 0.23.1. Nothing seems to be breaking in the next release.
Co-authored-by: Kerollmops <clement@meilisearch.com>
2022-03-15 17:19:05 +00:00
bors[bot]
ad4c982c68
Merge #439
...
439: Optimize typo criterion r=Kerollmops a=MarinPostma
This pr implements a couple of optimization for the typo criterion:
- clamp max typo on concatenated query words to 1: By considering that a concatenated query word is a typo, we clamp the max number of typos allowed o it to 1. This is useful because we noticed that concatenated query words often introduced words with 2 typos in queries that otherwise didn't allow for 2 typo words.
- Make typos on the first letter count for 2. This change is a big performance gain: by considering the typos on the first letter to count as 2 typos, we drastically restrict the search space for 1 typo, and if we reach 2 typos, the search space is reduced as well, as we only consider: (2 typos ∩ correct first letter) ∪ (wrong first letter ∩ 1 typo) instead of 2 typos anywhere in the word.
## benches
```
group main typo
----- ---- ----
smol-songs.csv: asc + default/Notstandskomitee 2.51 5.8±0.01ms ? ?/sec 1.00 2.3±0.01ms ? ?/sec
smol-songs.csv: asc + default/charles 2.48 3.0±0.01ms ? ?/sec 1.00 1190.9±1.29µs ? ?/sec
smol-songs.csv: asc + default/charles mingus 5.56 10.8±0.01ms ? ?/sec 1.00 1935.3±1.00µs ? ?/sec
smol-songs.csv: asc + default/david 1.65 3.9±0.00ms ? ?/sec 1.00 2.4±0.01ms ? ?/sec
smol-songs.csv: asc + default/david bowie 3.34 12.5±0.02ms ? ?/sec 1.00 3.7±0.00ms ? ?/sec
smol-songs.csv: asc + default/john 1.00 1849.7±3.74µs ? ?/sec 1.01 1875.1±4.65µs ? ?/sec
smol-songs.csv: asc + default/marcus miller 4.32 15.7±0.01ms ? ?/sec 1.00 3.6±0.01ms ? ?/sec
smol-songs.csv: asc + default/michael jackson 3.31 12.5±0.01ms ? ?/sec 1.00 3.8±0.00ms ? ?/sec
smol-songs.csv: asc + default/tamo 1.05 565.4±0.86µs ? ?/sec 1.00 539.3±1.22µs ? ?/sec
smol-songs.csv: asc + default/thelonious monk 3.49 11.5±0.01ms ? ?/sec 1.00 3.3±0.00ms ? ?/sec
smol-songs.csv: asc/Notstandskomitee 2.59 5.6±0.02ms ? ?/sec 1.00 2.2±0.01ms ? ?/sec
smol-songs.csv: asc/charles 6.05 2.1±0.00ms ? ?/sec 1.00 347.8±0.60µs ? ?/sec
smol-songs.csv: asc/charles mingus 14.46 9.4±0.01ms ? ?/sec 1.00 649.2±0.97µs ? ?/sec
smol-songs.csv: asc/david 3.87 2.4±0.00ms ? ?/sec 1.00 618.2±0.69µs ? ?/sec
smol-songs.csv: asc/david bowie 10.14 9.8±0.01ms ? ?/sec 1.00 970.8±1.55µs ? ?/sec
smol-songs.csv: asc/john 1.00 546.5±1.10µs ? ?/sec 1.00 547.1±2.11µs ? ?/sec
smol-songs.csv: asc/marcus miller 11.45 10.4±0.06ms ? ?/sec 1.00 907.9±1.37µs ? ?/sec
smol-songs.csv: asc/michael jackson 10.56 9.7±0.01ms ? ?/sec 1.00 919.6±1.03µs ? ?/sec
smol-songs.csv: asc/tamo 1.03 43.3±0.18µs ? ?/sec 1.00 42.2±0.23µs ? ?/sec
smol-songs.csv: asc/thelonious monk 4.16 10.7±0.02ms ? ?/sec 1.00 2.6±0.00ms ? ?/sec
smol-songs.csv: basic filter: <=/Notstandskomitee 1.00 95.7±0.20µs ? ?/sec 1.15 109.6±10.40µs ? ?/sec
smol-songs.csv: basic filter: <=/charles 1.00 27.8±0.15µs ? ?/sec 1.01 27.9±0.18µs ? ?/sec
smol-songs.csv: basic filter: <=/charles mingus 1.72 119.2±0.67µs ? ?/sec 1.00 69.1±0.13µs ? ?/sec
smol-songs.csv: basic filter: <=/david 1.00 22.3±0.33µs ? ?/sec 1.05 23.4±0.19µs ? ?/sec
smol-songs.csv: basic filter: <=/david bowie 1.59 86.9±0.79µs ? ?/sec 1.00 54.5±0.31µs ? ?/sec
smol-songs.csv: basic filter: <=/john 1.00 17.9±0.06µs ? ?/sec 1.06 18.9±0.15µs ? ?/sec
smol-songs.csv: basic filter: <=/marcus miller 1.65 102.7±1.63µs ? ?/sec 1.00 62.3±0.18µs ? ?/sec
smol-songs.csv: basic filter: <=/michael jackson 1.76 128.2±1.85µs ? ?/sec 1.00 72.9±0.19µs ? ?/sec
smol-songs.csv: basic filter: <=/tamo 1.00 17.9±0.13µs ? ?/sec 1.05 18.7±0.20µs ? ?/sec
smol-songs.csv: basic filter: <=/thelonious monk 1.53 157.5±2.38µs ? ?/sec 1.00 102.8±0.88µs ? ?/sec
smol-songs.csv: basic filter: TO/Notstandskomitee 1.00 100.9±4.36µs ? ?/sec 1.04 105.0±8.25µs ? ?/sec
smol-songs.csv: basic filter: TO/charles 1.00 28.4±0.36µs ? ?/sec 1.03 29.4±0.33µs ? ?/sec
smol-songs.csv: basic filter: TO/charles mingus 1.71 118.1±1.08µs ? ?/sec 1.00 68.9±0.26µs ? ?/sec
smol-songs.csv: basic filter: TO/david 1.00 24.0±0.26µs ? ?/sec 1.03 24.6±0.43µs ? ?/sec
smol-songs.csv: basic filter: TO/david bowie 1.72 95.2±0.30µs ? ?/sec 1.00 55.2±0.14µs ? ?/sec
smol-songs.csv: basic filter: TO/john 1.00 18.8±0.09µs ? ?/sec 1.06 19.8±0.17µs ? ?/sec
smol-songs.csv: basic filter: TO/marcus miller 1.61 102.4±1.65µs ? ?/sec 1.00 63.4±0.24µs ? ?/sec
smol-songs.csv: basic filter: TO/michael jackson 1.77 132.1±1.41µs ? ?/sec 1.00 74.5±0.59µs ? ?/sec
smol-songs.csv: basic filter: TO/tamo 1.00 18.2±0.14µs ? ?/sec 1.05 19.2±0.46µs ? ?/sec
smol-songs.csv: basic filter: TO/thelonious monk 1.49 150.8±1.92µs ? ?/sec 1.00 101.3±0.44µs ? ?/sec
smol-songs.csv: basic placeholder/ 1.00 27.3±0.07µs ? ?/sec 1.03 28.0±0.05µs ? ?/sec
smol-songs.csv: basic with quote/"Notstandskomitee" 1.00 122.4±0.17µs ? ?/sec 1.03 125.6±0.16µs ? ?/sec
smol-songs.csv: basic with quote/"charles" 1.00 88.8±0.30µs ? ?/sec 1.00 88.4±0.15µs ? ?/sec
smol-songs.csv: basic with quote/"charles" "mingus" 1.00 685.2±0.74µs ? ?/sec 1.01 689.4±6.07µs ? ?/sec
smol-songs.csv: basic with quote/"david" 1.00 161.6±0.42µs ? ?/sec 1.01 162.6±0.17µs ? ?/sec
smol-songs.csv: basic with quote/"david" "bowie" 1.00 731.7±0.73µs ? ?/sec 1.02 743.1±0.77µs ? ?/sec
smol-songs.csv: basic with quote/"john" 1.00 267.1±0.33µs ? ?/sec 1.01 270.9±0.33µs ? ?/sec
smol-songs.csv: basic with quote/"marcus" "miller" 1.00 138.7±0.31µs ? ?/sec 1.02 140.9±0.13µs ? ?/sec
smol-songs.csv: basic with quote/"michael" "jackson" 1.01 841.4±0.72µs ? ?/sec 1.00 833.8±0.92µs ? ?/sec
smol-songs.csv: basic with quote/"tamo" 1.01 189.2±0.26µs ? ?/sec 1.00 188.2±0.71µs ? ?/sec
smol-songs.csv: basic with quote/"thelonious" "monk" 1.00 1100.5±1.36µs ? ?/sec 1.01 1111.7±2.17µs ? ?/sec
smol-songs.csv: basic without quote/Notstandskomitee 3.40 7.9±0.02ms ? ?/sec 1.00 2.3±0.02ms ? ?/sec
smol-songs.csv: basic without quote/charles 2.57 494.4±0.89µs ? ?/sec 1.00 192.5±0.18µs ? ?/sec
smol-songs.csv: basic without quote/charles mingus 1.29 2.8±0.02ms ? ?/sec 1.00 2.1±0.01ms ? ?/sec
smol-songs.csv: basic without quote/david 1.95 623.8±0.90µs ? ?/sec 1.00 319.2±1.22µs ? ?/sec
smol-songs.csv: basic without quote/david bowie 1.12 5.9±0.00ms ? ?/sec 1.00 5.2±0.00ms ? ?/sec
smol-songs.csv: basic without quote/john 1.24 1340.9±2.25µs ? ?/sec 1.00 1084.7±7.76µs ? ?/sec
smol-songs.csv: basic without quote/marcus miller 7.97 14.6±0.01ms ? ?/sec 1.00 1826.0±6.84µs ? ?/sec
smol-songs.csv: basic without quote/michael jackson 1.19 3.9±0.00ms ? ?/sec 1.00 3.3±0.00ms ? ?/sec
smol-songs.csv: basic without quote/tamo 1.65 737.7±3.58µs ? ?/sec 1.00 446.7±0.51µs ? ?/sec
smol-songs.csv: basic without quote/thelonious monk 1.16 4.5±0.02ms ? ?/sec 1.00 3.9±0.04ms ? ?/sec
smol-songs.csv: big filter/Notstandskomitee 3.27 7.6±0.02ms ? ?/sec 1.00 2.3±0.01ms ? ?/sec
smol-songs.csv: big filter/charles 8.26 1957.5±1.37µs ? ?/sec 1.00 236.8±0.34µs ? ?/sec
smol-songs.csv: big filter/charles mingus 18.49 11.2±0.06ms ? ?/sec 1.00 607.7±3.03µs ? ?/sec
smol-songs.csv: big filter/david 3.78 2.4±0.00ms ? ?/sec 1.00 622.8±0.80µs ? ?/sec
smol-songs.csv: big filter/david bowie 9.00 12.0±0.01ms ? ?/sec 1.00 1336.0±3.17µs ? ?/sec
smol-songs.csv: big filter/john 1.00 554.2±0.95µs ? ?/sec 1.01 560.4±0.79µs ? ?/sec
smol-songs.csv: big filter/marcus miller 18.09 12.0±0.01ms ? ?/sec 1.00 664.7±0.60µs ? ?/sec
smol-songs.csv: big filter/michael jackson 8.43 12.0±0.01ms ? ?/sec 1.00 1421.6±1.37µs ? ?/sec
smol-songs.csv: big filter/tamo 1.00 86.3±0.14µs ? ?/sec 1.01 87.3±0.21µs ? ?/sec
smol-songs.csv: big filter/thelonious monk 5.55 14.3±0.02ms ? ?/sec 1.00 2.6±0.01ms ? ?/sec
smol-songs.csv: desc + default/Notstandskomitee 2.52 5.8±0.01ms ? ?/sec 1.00 2.3±0.01ms ? ?/sec
smol-songs.csv: desc + default/charles 3.04 2.7±0.01ms ? ?/sec 1.00 893.4±1.08µs ? ?/sec
smol-songs.csv: desc + default/charles mingus 6.77 10.3±0.01ms ? ?/sec 1.00 1520.8±1.90µs ? ?/sec
smol-songs.csv: desc + default/david 1.39 5.7±0.00ms ? ?/sec 1.00 4.1±0.00ms ? ?/sec
smol-songs.csv: desc + default/david bowie 2.34 15.8±0.02ms ? ?/sec 1.00 6.7±0.01ms ? ?/sec
smol-songs.csv: desc + default/john 1.00 2.5±0.00ms ? ?/sec 1.02 2.6±0.01ms ? ?/sec
smol-songs.csv: desc + default/marcus miller 5.06 14.5±0.02ms ? ?/sec 1.00 2.9±0.01ms ? ?/sec
smol-songs.csv: desc + default/michael jackson 2.64 14.1±0.05ms ? ?/sec 1.00 5.4±0.00ms ? ?/sec
smol-songs.csv: desc + default/tamo 1.00 567.0±0.65µs ? ?/sec 1.00 565.7±0.97µs ? ?/sec
smol-songs.csv: desc + default/thelonious monk 3.55 11.6±0.02ms ? ?/sec 1.00 3.3±0.00ms ? ?/sec
smol-songs.csv: desc/Notstandskomitee 2.58 5.6±0.02ms ? ?/sec 1.00 2.2±0.02ms ? ?/sec
smol-songs.csv: desc/charles 6.04 2.1±0.00ms ? ?/sec 1.00 348.1±0.57µs ? ?/sec
smol-songs.csv: desc/charles mingus 14.51 9.4±0.01ms ? ?/sec 1.00 646.7±0.99µs ? ?/sec
smol-songs.csv: desc/david 3.86 2.4±0.00ms ? ?/sec 1.00 620.7±2.46µs ? ?/sec
smol-songs.csv: desc/david bowie 10.10 9.8±0.01ms ? ?/sec 1.00 973.9±3.31µs ? ?/sec
smol-songs.csv: desc/john 1.00 545.5±0.78µs ? ?/sec 1.00 547.2±0.48µs ? ?/sec
smol-songs.csv: desc/marcus miller 11.39 10.3±0.01ms ? ?/sec 1.00 903.7±0.95µs ? ?/sec
smol-songs.csv: desc/michael jackson 10.51 9.7±0.01ms ? ?/sec 1.00 924.7±2.02µs ? ?/sec
smol-songs.csv: desc/tamo 1.01 43.2±0.33µs ? ?/sec 1.00 42.6±0.35µs ? ?/sec
smol-songs.csv: desc/thelonious monk 4.19 10.8±0.03ms ? ?/sec 1.00 2.6±0.00ms ? ?/sec
smol-songs.csv: prefix search/a 1.00 1008.7±1.00µs ? ?/sec 1.00 1005.5±0.91µs ? ?/sec
smol-songs.csv: prefix search/b 1.00 885.0±0.70µs ? ?/sec 1.01 890.6±1.11µs ? ?/sec
smol-songs.csv: prefix search/i 1.00 1051.8±1.25µs ? ?/sec 1.00 1056.6±4.12µs ? ?/sec
smol-songs.csv: prefix search/s 1.00 724.7±1.77µs ? ?/sec 1.00 721.6±0.59µs ? ?/sec
smol-songs.csv: prefix search/x 1.01 212.4±0.21µs ? ?/sec 1.00 210.9±0.38µs ? ?/sec
smol-songs.csv: proximity/7000 Danses Un Jour Dans Notre Vie 18.55 48.5±0.09ms ? ?/sec 1.00 2.6±0.03ms ? ?/sec
smol-songs.csv: proximity/The Disneyland Sing-Along Chorus 8.41 56.7±0.45ms ? ?/sec 1.00 6.7±0.05ms ? ?/sec
smol-songs.csv: proximity/Under Great Northern Lights 15.74 38.9±0.14ms ? ?/sec 1.00 2.5±0.00ms ? ?/sec
smol-songs.csv: proximity/black saint sinner lady 11.82 40.1±0.13ms ? ?/sec 1.00 3.4±0.02ms ? ?/sec
smol-songs.csv: proximity/les dangeureuses 1960 6.90 26.1±0.13ms ? ?/sec 1.00 3.8±0.04ms ? ?/sec
smol-songs.csv: typo/Arethla Franklin 14.93 5.8±0.01ms ? ?/sec 1.00 390.1±1.89µs ? ?/sec
smol-songs.csv: typo/Disnaylande 3.18 7.3±0.01ms ? ?/sec 1.00 2.3±0.00ms ? ?/sec
smol-songs.csv: typo/dire straights 5.55 15.2±0.02ms ? ?/sec 1.00 2.7±0.00ms ? ?/sec
smol-songs.csv: typo/fear of the duck 28.03 20.0±0.03ms ? ?/sec 1.00 713.3±1.54µs ? ?/sec
smol-songs.csv: typo/indochie 19.25 1851.4±2.38µs ? ?/sec 1.00 96.2±0.13µs ? ?/sec
smol-songs.csv: typo/indochien 14.66 1887.7±3.18µs ? ?/sec 1.00 128.8±0.18µs ? ?/sec
smol-songs.csv: typo/klub des loopers 37.73 18.0±0.02ms ? ?/sec 1.00 476.7±0.73µs ? ?/sec
smol-songs.csv: typo/michel depech 10.17 5.8±0.01ms ? ?/sec 1.00 565.8±1.16µs ? ?/sec
smol-songs.csv: typo/mongus 15.33 1897.4±3.44µs ? ?/sec 1.00 123.8±0.13µs ? ?/sec
smol-songs.csv: typo/stromal 14.63 1859.3±2.40µs ? ?/sec 1.00 127.1±0.29µs ? ?/sec
smol-songs.csv: typo/the white striper 10.83 9.4±0.01ms ? ?/sec 1.00 866.0±0.98µs ? ?/sec
smol-songs.csv: typo/thelonius monk 14.40 3.8±0.00ms ? ?/sec 1.00 261.5±1.30µs ? ?/sec
smol-songs.csv: words/7000 Danses / Le Baiser / je me trompe de mots 5.54 70.8±0.09ms ? ?/sec 1.00 12.8±0.03ms ? ?/sec
smol-songs.csv: words/Bring Your Daughter To The Slaughter but now this is not part of the title 3.48 119.8±0.14ms ? ?/sec 1.00 34.4±0.04ms ? ?/sec
smol-songs.csv: words/The Disneyland Children's Sing-Alone song 8.98 71.9±0.12ms ? ?/sec 1.00 8.0±0.01ms ? ?/sec
smol-songs.csv: words/les liaisons dangeureuses 1793 11.88 37.4±0.07ms ? ?/sec 1.00 3.1±0.01ms ? ?/sec
smol-songs.csv: words/seven nation mummy 22.86 23.4±0.04ms ? ?/sec 1.00 1024.8±1.57µs ? ?/sec
smol-songs.csv: words/the black saint and the sinner lady and the good doggo 2.76 124.4±0.15ms ? ?/sec 1.00 45.1±0.09ms ? ?/sec
smol-songs.csv: words/whathavenotnsuchforth and a good amount of words to pop to match the first one 2.52 107.0±0.23ms ? ?/sec 1.00 42.4±0.66ms ? ?/sec
group main-wiki typo-wiki
----- --------- ---------
smol-wiki-articles.csv: basic placeholder/ 1.02 13.7±0.02µs ? ?/sec 1.00 13.4±0.03µs ? ?/sec
smol-wiki-articles.csv: basic with quote/"film" 1.02 409.8±0.67µs ? ?/sec 1.00 402.6±0.48µs ? ?/sec
smol-wiki-articles.csv: basic with quote/"france" 1.00 325.9±0.91µs ? ?/sec 1.00 326.4±0.49µs ? ?/sec
smol-wiki-articles.csv: basic with quote/"japan" 1.00 218.4±0.26µs ? ?/sec 1.01 220.5±0.20µs ? ?/sec
smol-wiki-articles.csv: basic with quote/"machine" 1.00 143.0±0.12µs ? ?/sec 1.04 148.8±0.21µs ? ?/sec
smol-wiki-articles.csv: basic with quote/"miles" "davis" 1.00 11.7±0.06ms ? ?/sec 1.00 11.8±0.01ms ? ?/sec
smol-wiki-articles.csv: basic with quote/"mingus" 1.00 4.4±0.03ms ? ?/sec 1.00 4.4±0.00ms ? ?/sec
smol-wiki-articles.csv: basic with quote/"rock" "and" "roll" 1.00 43.5±0.08ms ? ?/sec 1.01 43.8±0.06ms ? ?/sec
smol-wiki-articles.csv: basic with quote/"spain" 1.00 137.3±0.35µs ? ?/sec 1.05 144.4±0.23µs ? ?/sec
smol-wiki-articles.csv: basic without quote/film 1.00 125.3±0.30µs ? ?/sec 1.06 133.1±0.37µs ? ?/sec
smol-wiki-articles.csv: basic without quote/france 1.21 1782.6±1.65µs ? ?/sec 1.00 1477.0±1.39µs ? ?/sec
smol-wiki-articles.csv: basic without quote/japan 1.28 1363.9±0.80µs ? ?/sec 1.00 1064.3±1.79µs ? ?/sec
smol-wiki-articles.csv: basic without quote/machine 1.73 760.3±0.81µs ? ?/sec 1.00 439.6±0.75µs ? ?/sec
smol-wiki-articles.csv: basic without quote/miles davis 1.03 17.0±0.03ms ? ?/sec 1.00 16.5±0.02ms ? ?/sec
smol-wiki-articles.csv: basic without quote/mingus 1.07 5.3±0.01ms ? ?/sec 1.00 5.0±0.00ms ? ?/sec
smol-wiki-articles.csv: basic without quote/rock and roll 1.01 63.9±0.18ms ? ?/sec 1.00 63.0±0.07ms ? ?/sec
smol-wiki-articles.csv: basic without quote/spain 2.07 667.4±0.93µs ? ?/sec 1.00 322.8±0.29µs ? ?/sec
smol-wiki-articles.csv: prefix search/c 1.00 343.1±0.47µs ? ?/sec 1.00 344.0±0.34µs ? ?/sec
smol-wiki-articles.csv: prefix search/g 1.00 374.4±3.42µs ? ?/sec 1.00 374.1±0.44µs ? ?/sec
smol-wiki-articles.csv: prefix search/j 1.00 359.9±0.31µs ? ?/sec 1.00 361.2±0.79µs ? ?/sec
smol-wiki-articles.csv: prefix search/q 1.01 102.0±0.12µs ? ?/sec 1.00 101.4±0.32µs ? ?/sec
smol-wiki-articles.csv: prefix search/t 1.00 536.7±1.39µs ? ?/sec 1.00 534.3±0.84µs ? ?/sec
smol-wiki-articles.csv: prefix search/x 1.00 400.9±1.00µs ? ?/sec 1.00 399.5±0.45µs ? ?/sec
smol-wiki-articles.csv: proximity/april paris 3.86 14.4±0.01ms ? ?/sec 1.00 3.7±0.01ms ? ?/sec
smol-wiki-articles.csv: proximity/diesel engine 12.98 10.4±0.01ms ? ?/sec 1.00 803.5±1.13µs ? ?/sec
smol-wiki-articles.csv: proximity/herald sings 1.00 12.7±0.06ms ? ?/sec 5.29 67.1±0.09ms ? ?/sec
smol-wiki-articles.csv: proximity/tea two 6.48 1452.1±2.78µs ? ?/sec 1.00 224.1±0.38µs ? ?/sec
smol-wiki-articles.csv: typo/Disnaylande 3.89 8.5±0.01ms ? ?/sec 1.00 2.2±0.01ms ? ?/sec
smol-wiki-articles.csv: typo/aritmetric 3.78 10.3±0.01ms ? ?/sec 1.00 2.7±0.00ms ? ?/sec
smol-wiki-articles.csv: typo/linax 8.91 1426.7±0.97µs ? ?/sec 1.00 160.1±0.18µs ? ?/sec
smol-wiki-articles.csv: typo/migrosoft 7.48 1417.3±5.84µs ? ?/sec 1.00 189.5±0.88µs ? ?/sec
smol-wiki-articles.csv: typo/nympalidea 3.96 7.2±0.01ms ? ?/sec 1.00 1810.1±2.03µs ? ?/sec
smol-wiki-articles.csv: typo/phytogropher 3.71 7.2±0.01ms ? ?/sec 1.00 1934.3±6.51µs ? ?/sec
smol-wiki-articles.csv: typo/sisan 6.44 1497.2±1.38µs ? ?/sec 1.00 232.7±0.94µs ? ?/sec
smol-wiki-articles.csv: typo/the fronce 6.92 2.9±0.00ms ? ?/sec 1.00 418.0±1.76µs ? ?/sec
smol-wiki-articles.csv: words/Abraham machin 16.63 10.8±0.01ms ? ?/sec 1.00 649.7±1.08µs ? ?/sec
smol-wiki-articles.csv: words/Idaho Bellevue pizza 27.15 25.6±0.03ms ? ?/sec 1.00 944.2±5.07µs ? ?/sec
smol-wiki-articles.csv: words/Kameya Tokujirō mingus monk 26.87 40.7±0.05ms ? ?/sec 1.00 1515.3±2.73µs ? ?/sec
smol-wiki-articles.csv: words/Ulrich Hensel meilisearch milli 11.99 48.8±0.10ms ? ?/sec 1.00 4.1±0.02ms ? ?/sec
smol-wiki-articles.csv: words/the black saint and the sinner lady and the good doggo 4.90 110.0±0.15ms ? ?/sec 1.00 22.4±0.03ms ? ?/sec
```
Co-authored-by: mpostma <postma.marin@protonmail.com>
Co-authored-by: ad hoc <postma.marin@protonmail.com>
2022-03-15 16:43:36 +00:00
ad hoc
3f24555c3d
custom fst automatons
2022-03-15 17:38:35 +01:00
ad hoc
628c835a22
fix tests
2022-03-15 17:38:34 +01:00
bors[bot]
8efac33b53
Merge #467
...
467: optimize prefix database r=Kerollmops a=MarinPostma
This pr introduces two optimizations that greatly improve the speed of computing prefix databases.
- The time that it takes to create the prefix FST has been divided by 5 by inverting the way we iterated over the words FST.
- We unconditionally and needlessly checked for documents to remove in `word_prefix_pair`, which caused an iteration over the whole database.
Co-authored-by: ad hoc <postma.marin@protonmail.com>
2022-03-15 16:14:35 +00:00
ad hoc
d127c57f2d
review edits
2022-03-15 17:12:48 +01:00
ad hoc
d633ac5b9d
optimize word prefix pair
2022-03-15 16:37:22 +01:00
ad hoc
d68fe2b3c7
optimize word prefix fst
2022-03-15 16:36:48 +01:00
Kerollmops
08a06b49f0
Bump version to 0.23.1
2022-03-15 15:50:28 +01:00
Clément Renault
0c5f4ed7de
Apply suggestions
...
Co-authored-by: Many <many@meilisearch.com>
2022-03-15 14:18:29 +01:00
Kerollmops
21ec334dcc
Fix the compilation error of the dependency versions
2022-03-15 11:17:45 +01:00
Kerollmops
63682c2c9a
Upgrade the dependencies
2022-03-15 11:17:44 +01:00
Kerollmops
288a879411
Remove three useless dependencies
2022-03-15 11:17:44 +01:00
psvnl sai kumar
5e08fac729
fixes for rustfmt pass
2022-03-14 19:22:41 +05:30
psvnl sai kumar
92e2e09434
exporting heed to avoid having different versions of Heed in Meilisearch
2022-03-14 01:01:58 +05:30
Kerollmops
1ae13c1374
Avoid iterating on big databases when useless
2022-03-09 15:43:54 +01:00
Bruno Casali
66c6d5e1ef
Add a new error message when the valid_fields is empty
...
> "Attribute `{}` is not sortable. This index doesn't have configured sortable attributes."
> "Attribute `{}` is not sortable. Available sortable attributes are: `{}`."
coexist in the error handling
2022-03-05 10:38:18 -03:00
Clémentine Urquizar
d9ed9de2b0
Update heed link in cargo toml
2022-03-01 19:45:29 +01:00
Kerollmops
d5b8b5a2f8
Replace the ugly unwraps by clean if let Somes
2022-02-28 16:31:33 +01:00
Kerollmops
8d26f3040c
Remove a useless grenad file merging
2022-02-28 16:31:33 +01:00
Clément Renault
04b1bbf932
Reintroduce appending sorted entries when possible
2022-02-24 14:50:45 +01:00
bors[bot]
25123af3b8
Merge #436
...
436: Speed up the word prefix databases computation time r=Kerollmops a=Kerollmops
This PR depends on the fixes done in #431 and must be merged after it.
In this PR we will bring the `WordPrefixPairProximityDocids`, `WordPrefixDocids` and, `WordPrefixPositionDocids` update structures to a new era, a better era, where computing the word prefix pair proximities costs much fewer CPU cycles, an era where this update structure can use the, previously computed, set of new word docids from the newly indexed batch of documents.
---
The `WordPrefixPairProximityDocids` is an update structure, which means that it is an object that we feed with some parameters and which modifies the LMDB database of an index when asked for. This structure specifically computes the list of word prefix pair proximities, which correspond to a list of pairs of words associated with a proximity (the distance between both words) where the second word is not a word but a prefix e.g. `s`, `se`, `a`. This word prefix pair proximity is associated with the list of documents ids which contains the pair of words and prefix at the given proximity.
The origin of the performances issue that this struct brings is related to the fact that it starts its job from the beginning, it clears the LMDB database before rewriting everything from scratch, using the other LMDB databases to achieve that. I hope you understand that this is absolutely not an optimized way of doing things.
Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Kerollmops <clement@meilisearch.com>
2022-02-16 15:41:14 +00:00
Clément Renault
ff8d7a810d
Change the behavior of the as_cloneable_grenad by taking a ref
2022-02-16 15:40:08 +01:00
Clément Renault
f367cc2e75
Finally bump grenad to v0.4.1
2022-02-16 15:28:48 +01:00
Irevoire
0defeb268c
bump milli
2022-02-16 13:27:41 +01:00
Irevoire
48542ac8fd
get rid of chrono in favor of time
2022-02-15 11:41:55 +01:00
Clémentine Urquizar
d03b3ceb58
Update version for the next release (v0.22.1)
2022-02-07 18:39:29 +01:00
bors[bot]
5d58cb7449
Merge #442
...
442: fix phrase search r=curquiza a=MarinPostma
Run the exact match search on 7 words windows instead of only two. This makes false positive very very unlikely, and impossible on phrase query that are less than seven words.
Co-authored-by: ad hoc <postma.marin@protonmail.com>
2022-02-07 16:18:20 +00:00
ad hoc
bd2262ceea
allow null values in csv
2022-02-03 16:03:01 +01:00
ad hoc
13de251047
rewrite word pair distance gathering
2022-02-03 15:57:20 +01:00
Many
d59bcea749
Revert "Revert "Change chunk size to 4MiB to fit more the end user usage""
2022-02-02 17:01:13 +01:00
mpostma
7541ab99cd
review changes
2022-02-02 12:59:01 +01:00
mpostma
d0aabde502
optimize 2 typos case
2022-02-02 12:56:09 +01:00
mpostma
55e6cb9c7b
typos on first letter counts as 2
2022-02-02 12:56:09 +01:00
mpostma
642c01d0dc
set max typos on ngram to 1
2022-02-02 12:56:08 +01:00
ad hoc
d852dc0d2b
fix phrase search
2022-02-01 20:21:33 +01:00
Kerollmops
fb79c32430
Compute the new, common and, deleted prefix words fst once
2022-01-27 11:00:18 +01:00
Clément Renault
51d1e64b23
Remove, now useless, the WriteMethod enum
2022-01-27 10:08:35 +01:00
Clément Renault
e9c02173cf
Rework the WordsPrefixPositionDocids update to compute a subset of the database
2022-01-27 10:08:35 +01:00
Clément Renault
dbba5fd461
Create a function to simplify the word prefix pair proximity docids compute
2022-01-27 10:08:35 +01:00
Clément Renault
e760e02737
Fix the computation of the newly added and common prefix pair proximity words
2022-01-27 10:08:35 +01:00
Clément Renault
d59e559317
Fix the computation of the newly added and common prefix words
2022-01-27 10:08:34 +01:00
Clément Renault
2ec8542105
Rework the WordPrefixDocids update to compute a subset of the database
2022-01-27 10:08:34 +01:00
Clément Renault
28692f65be
Rework the WordPrefixDocids update to compute a subset of the database
2022-01-27 10:08:34 +01:00
Clément Renault
5404bc02dd
Move the fst_stream_into_hashset method in the helper methods
2022-01-27 10:06:00 +01:00
Clément Renault
c90fa95f93
Only compute the word prefix pairs on the created word pair proximities
2022-01-27 10:06:00 +01:00
Clément Renault
822f67e9ad
Bring the newly created word pair proximity docids
2022-01-27 10:06:00 +01:00
Clément Renault
d28f18658e
Retrieve the previous version of the words prefixes FST
2022-01-27 10:05:59 +01:00
bors[bot]
38d23546a5
Merge #431
...
431: Fix and improve word prefix pair proximity r=ManyTheFish a=Kerollmops
This PR first fixes the algorithm we used to select and compute the word prefix pair proximity database. The previous version was skipping nearly all of the prefixes. The issue is that this fix made this method to take more time and we were trying to reduce the time spent in it.
With `@ManyTheFish` we found out that we could skip some of the work we were doing by:
- discarding the prefixes that were shorter than a specific threshold (default: 2).
- discarding the word prefix pairs with proximity bigger than a specific threshold (default: 4).
- remove the unused threshold that was specifying a minimum amount of word docids to merge.
We will take more time to do some more optimization, like stop clearing and recomputing from scratch the database, we will compute the subsets of keys to create, keep and merge. This change is a little bit more complex than what this PR does.
I keep this PR as a draft as I want to further test the real gain if it is enough or not if it is valid or not. I advise reviewers to review commit by commit to see the changes bit by bit, reviewing the whole PR can be hard.
Co-authored-by: Clément Renault <clement@meilisearch.com>
2022-01-27 07:04:56 +00:00
Clément Renault
f9b214f34e
Apply suggestions from code review
...
Co-authored-by: Many <legendre.maxime.isn@gmail.com>
2022-01-26 11:28:11 +01:00
bors[bot]
e1cc025cbd
Merge #440
...
440: fix(fuzzer): fix the fuzzer after #430 r=Kerollmops a=irevoire
Co-authored-by: Tamo <tamo@meilisearch.com>
2022-01-25 16:33:57 +00:00
Clément Renault
f04cd19886
Introduce a max prefix length parameter to the word prefix pair proximity update
2022-01-25 17:04:23 +01:00
Clément Renault
1514dfa1b7
Introduce a max proximity parameter to the word prefix pair proximity update
2022-01-25 17:04:23 +01:00
Clément Renault
23ea3ad738
Remove the useless threshold when computing the word prefix pair proximity
2022-01-25 17:04:23 +01:00
Clément Renault
e3c34684c6
Fix a bug where we were skipping most of the prefix pairs
2022-01-25 17:04:23 +01:00
Tamo
fb51d511be
fix(fuzzer): fix the fuzzer after #430
2022-01-25 12:08:47 +01:00
bors[bot]
9f2ff71581
Merge #434
...
434: bump milli to v0.22.0 r=curquiza a=irevoire
This is breaking because of this PR:
98a365aaaehttps://github.com/meilisearch/milli/pull/433 ) for https://github.com/meilisearch/MeiliSearch/issues/2082 (which is non-breaking)?
Co-authored-by: Tamo <tamo@meilisearch.com>
2022-01-24 17:31:20 +00:00
bors[bot]
fd177b63f8
Merge #423
...
423: Remove an unused file r=irevoire a=irevoire
This empty file is not included anywhere
Co-authored-by: Tamo <tamo@meilisearch.com>
2022-01-19 14:18:05 +00:00
Marin Postma
0c84a40298
document batch support
...
reusable transform
rework update api
add indexer config
fix tests
review changes
Co-authored-by: Clément Renault <clement@meilisearch.com>
fmt
2022-01-19 12:40:20 +01:00
Tamo
01968d7ca7
ensure we get no documents and no error when filtering on an empty db
2022-01-18 11:40:30 +01:00
Tamo
367f403693
bump milli
2022-01-17 16:41:34 +01:00
bors[bot]
8f4499090b
Merge #433
...
433: fix(filter): Fix two bugs. r=Kerollmops a=irevoire
- Stop lowercasing the field when looking in the field id map
- When a field id does not exist it means there is currently zero
documents containing this field thus we return an empty RoaringBitmap
instead of throwing an internal error
Will fix https://github.com/meilisearch/MeiliSearch/issues/2082 once meilisearch is released
Co-authored-by: Tamo <tamo@meilisearch.com>
2022-01-17 14:06:53 +00:00
bors[bot]
4c516c00da
Merge #426
...
426: Fix search highlight for non-unicode chars r=ManyTheFish a=Samyak2
# Pull Request
## What does this PR do?
Fixes https://github.com/meilisearch/MeiliSearch/issues/1480
<!-- Please link the issue you're trying to fix with this PR, if none then please create an issue first. -->
## PR checklist
Please check if your PR fulfills the following requirements:
- [x] Does this PR fix an existing issue?
- [x] Have you read the contributing guidelines?
- [x] Have you made sure that the title is accurate and descriptive of the changes?
## Changes
The `matching_bytes` function takes a `&Token` now and:
- gets the number of bytes to highlight (unchanged).
- uses `Token.num_graphemes_from_bytes` to get the number of grapheme clusters to highlight.
In essence, the `matching_bytes` function now returns the number of matching grapheme clusters instead of bytes.
Added proper highlighting in the HTTP UI:
- requires dependency on `unicode-segmentation` to extract grapheme clusters from tokens
- `<mark>` tag is put around only the matched part
- before this change, the entire word was highlighted even if only a part of it matched
## Questions
Since `matching_bytes` does not return number of bytes but grapheme clusters, should it be renamed to something like `matching_chars` or `matching_graphemes`? Will this break the API?
Thank you very much `@ManyTheFish` for helping 😄
Co-authored-by: Samyak S Sarnayak <samyak201@gmail.com>
2022-01-17 13:39:00 +00:00
Tamo
d1ac40ea14
fix(filter): Fix two bugs.
...
- Stop lowercasing the field when looking in the field id map
- When a field id does not exist it means there is currently zero
documents containing this field thus we returns an empty RoaringBitmap
instead of throwing an internal error
2022-01-17 13:51:46 +01:00
Samyak S Sarnayak
2d7607734e
Run cargo fmt on matching_words.rs
2022-01-17 13:04:33 +05:30
Samyak S Sarnayak
5ab505be33
Fix highlight by replacing num_graphemes_from_bytes
...
num_graphemes_from_bytes has been renamed in the tokenizer to
num_chars_from_bytes.
Highlight now works correctly!
2022-01-17 13:02:55 +05:30
Samyak S Sarnayak
c10f58b7bd
Update tokenizer to v0.2.7
2022-01-17 13:02:00 +05:30
Samyak S Sarnayak
e752bd06f7
Fix matching_words tests to compile successfully
...
The tests still fail due to a bug in https://github.com/meilisearch/tokenizer/pull/59
2022-01-17 11:37:45 +05:30
Samyak S Sarnayak
30247d70cd
Fix search highlight for non-unicode chars
...
The `matching_bytes` function takes a `&Token` now and:
- gets the number of bytes to highlight (unchanged).
- uses `Token.num_graphemes_from_bytes` to get the number of grapheme
clusters to highlight.
In essence, the `matching_bytes` function returns the number of matching
grapheme clusters instead of bytes. Should this function be renamed
then?
Added proper highlighting in the HTTP UI:
- requires dependency on `unicode-segmentation` to extract grapheme
clusters from tokens
- `<mark>` tag is put around only the matched part
- before this change, the entire word was highlighted even if only a
part of it matched
2022-01-17 11:37:44 +05:30
Tamo
0605c0ac68
apply review comments
2022-01-13 18:51:08 +01:00
Tamo
b22c80106f
add some settings to the fuzzed milli and use the published version of arbitrary json
2022-01-13 15:35:24 +01:00
Tamo
c94952e25d
update the readme + dependencies
2022-01-12 18:30:11 +01:00
Tamo
e1053989c0
add a fuzzer on milli
2022-01-12 17:57:54 +01:00
Tamo
98a365aaae
store the geopoint in three dimensions
2021-12-14 12:21:24 +01:00
Tamo
d671d6f0f1
remove an unused file
2021-12-13 19:27:34 +01:00
Clément Renault
25faef67d0
Remove the database setup in the filter_depth test
2021-12-09 11:57:53 +01:00
Clément Renault
65519bc04b
Test that empty filters return a None
2021-12-09 11:57:53 +01:00
Clément Renault
ef59762d8e
Prefer returning None instead of the Empty Filter state
2021-12-09 11:57:52 +01:00
Clément Renault
ee856a7a46
Limit the max filter depth to 2000
2021-12-07 17:36:45 +01:00
Clément Renault
32bd9f091f
Detect the filters that are too deep and return an error
2021-12-07 17:20:11 +01:00
Clément Renault
90f49eab6d
Check the filter max depth limit and reject the invalid ones
2021-12-07 16:32:48 +01:00
many
1b3923b5ce
Update all packages to 0.21.0
2021-11-29 12:17:59 +01:00
many
8970246bc4
Sort positions before iterating over them during word pair proximity extraction
2021-11-22 18:16:54 +01:00
Marin Postma
6e977dd8e8
change visibility of DocumentDeletionResult
2021-11-22 15:44:44 +01:00
many
35f9499638
Export tokenizer from milli
2021-11-18 16:57:12 +01:00
many
64ef5869d7
Update tokenizer v0.2.6
2021-11-18 16:56:05 +01:00
Marin Postma
6eb47ab792
remove update_id in UpdateBuilder
2021-11-16 13:07:04 +01:00
Marin Postma
09b4281cff
improve document addition returned metaimprove document addition
...
returned metaimprove document addition returned metaimprove document
addition returned metaimprove document addition returned metaimprove
document addition returned metaimprove document addition returned
metaimprove document addition returned meta
2021-11-10 14:08:36 +01:00
