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769 Commits

Author SHA1 Message Date
ManyTheFish
d96e72e5dc Create formater with some tests 2022-04-05 17:41:32 +02:00
ad hoc
201fea0fda
limit extract_word_docids memory usage 2022-04-05 14:14:15 +02:00
ad hoc
5cfd3d8407
add exact attributes documentation 2022-04-05 14:10:22 +02:00
ad hoc
b85cd4983e
remove field_id_from_position 2022-04-05 09:50:34 +02:00
ad hoc
ab185a59b5
fix infos 2022-04-05 09:46:56 +02:00
ad hoc
1810927dbd
rephrase exact_attributes doc 2022-04-04 21:04:49 +02:00
ad hoc
b7694c34f5
remove println 2022-04-04 21:00:07 +02:00
ad hoc
6cabd47c32
fix typo in comment 2022-04-04 20:59:20 +02:00
ad hoc
6b2c2509b2
fix bug in exact search 2022-04-04 20:54:03 +02:00
ad hoc
56b4f5dce2
add exact prefix to query_docids 2022-04-04 20:54:03 +02:00
ad hoc
21ae4143b1
add exact_word_prefix to Context 2022-04-04 20:54:03 +02:00
ad hoc
e8f06f6c06
extract exact_word_prefix_docids 2022-04-04 20:54:03 +02:00
ad hoc
6dd2e4ffbd
introduce exact_word_prefix database in index 2022-04-04 20:54:03 +02:00
ad hoc
ba0bb29cd8
refactor WordPrefixDocids to take dbs instead of indexes 2022-04-04 20:54:02 +02:00
ad hoc
c4c6e35352
query exact_word_docids in resolve_query_tree 2022-04-04 20:54:02 +02:00
ad hoc
8d46a5b0b5
extract exact word docids 2022-04-04 20:54:02 +02:00
ad hoc
0a77be4ec0
introduce exact_word_docids db 2022-04-04 20:54:02 +02:00
ad hoc
5f9f82757d
refactor spawn_extraction_task 2022-04-04 20:54:02 +02:00
ad hoc
f82d4b36eb
introduce exact attribute setting 2022-04-04 20:54:02 +02:00
ad hoc
c882d8daf0
add test for exact words 2022-04-04 20:54:01 +02:00
ad hoc
7e9d56a9e7
disable typos on exact words 2022-04-04 20:54:01 +02:00
ad hoc
30a2711bac
rename serde module to serde_impl module 
needed because of issues with rustfmt
 2022-04-04 20:10:55 +02:00
ad hoc
0fd55db21c
fmt 2022-04-04 20:10:55 +02:00
ad hoc
559e46be5e
fix bad rebase bug 2022-04-04 20:10:55 +02:00
ad hoc
8b1e5d9c6d
add test for exact words 2022-04-04 20:10:55 +02:00
ad hoc
774fa8f065
disable typos on exact words 2022-04-04 20:10:55 +02:00
ad hoc
9bbffb8fee
add exact words setting 2022-04-04 20:10:54 +02:00
ad hoc
853b4a520f
fmt 2022-04-04 10:41:46 +02:00
ad hoc
1941072bb2
implement Copy on Setting 2022-04-04 10:41:46 +02:00
ad hoc
fdaf45aab2
replace hardcoded value with constant in TestContext 2022-04-04 10:41:46 +02:00
ad hoc
950a740bd4
refactor typos for readability 2022-04-04 10:41:46 +02:00
ad hoc
66020cd923
rename min_word_len* to use plain letter numbers 2022-04-04 10:41:46 +02:00
ad hoc
4c4b336ecb
rename min word len for typo error 2022-04-01 11:17:03 +02:00
ad hoc
286dd7b2e4
rename min_word_len_2_typo 2022-04-01 11:17:03 +02:00
ad hoc
55af85db3c
add tests for min_word_len_for_typo 2022-04-01 11:17:02 +02:00
ad hoc
9102de5500
fix error message 2022-04-01 11:17:02 +02:00
ad hoc
a1a3a49bc9
dynamic minimum word len for typos in query tree builder 2022-04-01 11:17:02 +02:00
ad hoc
5a24e60572
introduce word len for typo setting 2022-04-01 11:17:02 +02:00
ad hoc
9fe40df960
add word derivations tests 2022-04-01 11:05:18 +02:00
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
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]
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
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
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
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
48542ac8fd
get rid of chrono in favor of time 2022-02-15 11:41:55 +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
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
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
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
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
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
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
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
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
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
Marin Postma
721fc294be improve document deletion returned meta 
returns both the remaining number of documents and the number of deleted
documents.
 2021-11-10 14:08:18 +01:00
Irevoire
0ea0146e04
implement deref &str on the tokens 2021-11-09 11:34:10 +01:00
Tamo
7483c7513a
fix the filterable fields 2021-11-07 01:52:19 +01:00
Tamo
e5af3ac65c
rename the filter_condition.rs to filter.rs 2021-11-06 16:37:55 +01:00
Tamo
6831c23449
merge with main 2021-11-06 16:34:30 +01:00
Tamo
b249989bef
fix most of the tests 2021-11-06 01:32:12 +01:00
Tamo
27a6a26b4b
makes the parse function part of the filter_parser 2021-11-05 10:46:54 +01:00
Tamo
76d961cc77
implements the last errors 2021-11-04 17:42:06 +01:00
Tamo
8234f9fdf3
recreate most filter error except for the geosearch 2021-11-04 17:24:55 +01:00
Tamo
07a5ffb04c
update http-ui 2021-11-04 15:52:22 +01:00
Tamo
a58bc5bebb
update milli with the new parser_filter 2021-11-04 15:02:36 +01:00
many
7b3bac46a0
Change Attribute and Ranking rules errors 2021-11-04 13:19:32 +01:00
many
0c0038488c
Change last error messages 2021-11-03 11:24:06 +01:00
Tamo
76a2adb7c3
re-enable the tests in the parser and start the creation of an error type 2021-11-02 17:35:17 +01:00
bors[bot]
08ae47e475
Merge #405 
405: Change some error messages r=ManyTheFish a=ManyTheFish



Co-authored-by: many <maxime@meilisearch.com>
 2021-10-28 13:35:55 +00:00
many
9f1e0d2a49
Refine asc/desc error messages 2021-10-28 14:47:17 +02:00
many
ed6db19681
Fix PR comments 2021-10-28 11:18:32 +02:00
marin postma
183d3dada7
return document count from builder 2021-10-28 10:33:04 +02:00
many
2be755ce75
Lower error check, already check in meilisearch 2021-10-27 19:50:41 +02:00
many
3599df77f0
Change some error messages 2021-10-27 19:33:01 +02:00
bors[bot]
d7943fe225
Merge #402 
402: Optimize document transform r=MarinPostma a=MarinPostma

This pr optimizes the transform of documents additions in the obkv format. Instead on accepting any serializable objects, we instead treat json and CSV specifically:
- For json, we build a serde `Visitor`, that transform the json straight into obkv without intermediate representation.
- For csv, we directly write the lines in the obkv, applying other optimization as well.

Co-authored-by: marin postma <postma.marin@protonmail.com>
 2021-10-26 09:55:28 +00:00
marin postma
baddd80069
implement review suggestions 2021-10-25 18:29:12 +02:00
marin postma
f9445c1d90
return float parsing error context in csv 2021-10-25 17:27:10 +02:00
Clémentine Urquizar
208903ddde
Revert "Replacing pest with nom " 2021-10-25 11:58:00 +02:00
marin postma
3fcccc31b5
add document builder example 2021-10-25 10:26:43 +02:00
marin postma
430e9b13d3
add csv builder tests 2021-10-25 10:26:43 +02:00
marin postma
53c79e85f2
document errors 2021-10-25 10:26:43 +02:00
marin postma
2e62925a6e
fix tests 2021-10-25 10:26:42 +02:00
marin postma
0f86d6b28f
implement csv serialization 2021-10-25 10:26:42 +02:00
marin postma
8d70b01714
optimize document deserialization 2021-10-25 10:26:42 +02:00
Tamo
1327807caa
add some error messages 2021-10-22 19:00:33 +02:00
Tamo
c8d03046bf
add a check on the fid in the geosearch 2021-10-22 18:08:18 +02:00
Tamo
3942b3732f
re-implement the geosearch 2021-10-22 18:03:39 +02:00
Tamo
7cd9109e2f
lowercase value extracted from Token 2021-10-22 17:50:15 +02:00
Tamo
e25ca9776f
start updating the exposed function to makes other modules happy 2021-10-22 17:23:22 +02:00
Tamo
6c9165b6a8
provide a helper to parse the token but to not handle the errors 2021-10-22 16:52:13 +02:00
Tamo
efb2f8b325
convert the errors 2021-10-22 16:38:35 +02:00
Tamo
c27870e765
integrate a first version without any error handling 2021-10-22 14:33:18 +02:00
Tamo
01dedde1c9
update some names and move some parser out of the lib.rs 2021-10-22 01:59:38 +02:00
Tamo
c634d43ac5
add a simple test on the filters with an integer 2021-10-21 17:10:27 +02:00
Tamo
6c15f50899
rewrite the parser logic 2021-10-21 16:45:42 +02:00
Tamo
e1d81342cf
add test on the or and and operator 2021-10-21 13:01:25 +02:00
Tamo
423baac08b
fix the tests 2021-10-21 12:45:40 +02:00
Tamo
36281a653f
write all the simple tests 2021-10-21 12:40:11 +02:00
Tamo
661bc21af5
Fix the filter parser 
And add a bunch of tests on the filter::from_array
 2021-10-21 11:45:03 +02:00
bors[bot]
59cc59e93e
Merge #358 
358: Replacing pest with nom  r=Kerollmops a=CNLHC



Co-authored-by: 刘瀚骋 <cn_lhc@qq.com>
 2021-10-16 20:44:38 +00:00
刘瀚骋
7666e4f34a follow the suggestions 2021-10-14 21:37:59 +08:00
刘瀚骋
2ea2f7570c use nightly cargo to format the code 2021-10-14 16:46:13 +08:00
刘瀚骋
e750465e15 check logic for geolocation. 2021-10-14 16:12:00 +08:00
bors[bot]
aa5e099718
Merge #390 
390: Add helper methods on the settings r=Kerollmops a=irevoire

This would be a good addition to look at the content of a setting without consuming it.
It’s useful for analytics.

Co-authored-by: Irevoire <tamo@meilisearch.com>
 2021-10-13 20:36:30 +00:00
bors[bot]
c7db4176f3
Merge #384 
384: Replace memmap with memmap2 r=Kerollmops a=palfrey

[memmap is unmaintained](https://rustsec.org/advisories/RUSTSEC-2020-0077.html) and needs replacing. memmap2 is a drop-in replacement fork that's well maintained. Note that the version numbers got reset on fork, hence the lower values.

Co-authored-by: Tom Parker-Shemilt <palfrey@tevp.net>
 2021-10-13 13:47:23 +00:00
Irevoire
a3e7c468cd
add helper methods on the settings 2021-10-13 13:05:07 +02:00
刘瀚骋
cd359cd96e WIP: extract the error trait bound to new trait. 2021-10-13 18:04:15 +08:00
刘瀚骋
5de5dd80a3 WIP: remove '_nom' suffix/redundant error enum/... 2021-10-13 11:06:15 +08:00
刘瀚骋
2c65781d91 format 2021-10-12 22:20:22 +08:00
bors[bot]
6e3b869e6a
Merge #388 
388: fix primary key inference r=MarinPostma a=MarinPostma

The primary key is was infered from a hashtable index of the field. For this reason the order in which the fields were interated upon was not deterministic, and the primary key was chosed ffrom the first field containing "id".

This fix sorts the the index by field_id when infering the primary key.


Co-authored-by: mpostma <postma.marin@protonmail.com>
 2021-10-12 09:25:16 +00:00
mpostma
86ead92ed5 infer primary key on sorted fields 2021-10-12 11:15:11 +02:00
mpostma
9a266a531b test correct primary key inference 2021-10-12 11:08:53 +02:00
many
c5a6075484
Make max_position_per_attributes changable 2021-10-12 10:10:50 +02:00
many
360c5ff3df
Remove limit of 1000 position per attribute 
Instead of using an arbitrary limit we encode the absolute position in a u32
using one strong u16 for the field id and a weak u16 for the relative position in the attribute.
 2021-10-12 10:10:50 +02:00
刘瀚骋
d323e35001 add a test case 2021-10-12 13:30:40 +08:00
刘瀚骋
70f576d5d3 error handling 2021-10-12 13:30:40 +08:00
刘瀚骋
28f9be8d7c support syntax 2021-10-12 13:30:40 +08:00
刘瀚骋
469d92c569 tweak error handling 2021-10-12 13:30:40 +08:00
刘瀚骋
7a90a101ee reorganize parser logic 2021-10-12 13:30:40 +08:00
刘瀚骋
f7796edc7e remove everything about pest 2021-10-12 13:30:40 +08:00
刘瀚骋
ac1df9d9d7 fix typo and remove pest 2021-10-12 13:30:40 +08:00
刘瀚骋
50ad750ec1 enhance error handling 2021-10-12 13:30:40 +08:00
刘瀚骋
8748df2ca4 draft without error handling 2021-10-12 13:30:40 +08:00
mpostma
99889a0ed0 add obkv document serialization test 2021-10-11 15:13:17 +02:00
mpostma
799f3d43c8 fix serialization to obkv format 2021-10-11 15:04:47 +02:00
Tom Parker-Shemilt
2dfe24f067 memmap -> memmap2 2021-10-10 22:47:12 +01:00
Irevoire
b65aa7b5ac
Apply suggestions from code review 
Co-authored-by: Clément Renault <clement@meilisearch.com>
 2021-10-07 17:51:52 +02:00
Tamo
11dfe38761
Update the check on the latitude and longitude 
Latitude are not supposed to go beyound 90 degrees or below -90.
The same goes for longitude with 180 or -180.

This was badly implemented in the filters, and was not implemented for the AscDesc rules.
 2021-10-07 16:10:43 +02:00
many
085bc6440c
Apply PR comments 2021-10-06 11:12:26 +02:00
many
1bd15d849b
Reduce candidates threshold 2021-10-05 18:52:14 +02:00
many
ea4bd29d14
Apply PR comments 2021-10-05 17:35:07 +02:00
many
3296bb243c
Simplify word level position DB into a word position DB 2021-10-05 12:15:02 +02:00
many
75d341d928
Re-implement set based algorithm for attribute criterion 2021-10-05 12:14:50 +02:00
Tamo
d9eba9d145
improve and test the sort error message 2021-09-30 14:38:27 +02:00
Tamo
0ee67bb7d1
improve the reserved keyword error message for the filters 2021-09-30 14:38:27 +02:00
bors[bot]
22551d0941
Merge #379 
379: Revert "Change chunk size to 4MiB to fit more the end user usage" r=curquiza a=ManyTheFish

Reverts meilisearch/milli#370

Co-authored-by: Many <legendre.maxime.isn@gmail.com>
 2021-09-29 13:20:53 +00:00
Many
26b5dad042
Revert "Change chunk size to 4MiB to fit more the end user usage" 2021-09-29 15:08:39 +02:00
Many
2e49230ca2
Update milli/src/search/criteria/attribute.rs 
Co-authored-by: Clément Renault <clement@meilisearch.com>
 2021-09-29 14:49:45 +02:00