ad hoc
2e0089d5ff
normalize exact words
2022-04-21 15:38:40 +02:00
ad hoc
3a2451fcba
add test normalize exact words
2022-04-21 13:52:09 +02:00
Clément Renault
eb5830aa40
Add a test to make sure that long words are handled
2022-04-21 13:45:28 +02:00
ad hoc
8b14090927
fix min-word-len-for-typo not reset properly
2022-04-19 15:20:16 +02:00
bors[bot]
ea4bb9402f
Merge #483
...
483: Enhance matching words r=Kerollmops a=ManyTheFish
# Summary
Enhance milli word-matcher making it handle match computing and cropping.
# Implementation
## Computing best matches for cropping
Before we were considering that the first match of the attribute was the best one, this was accurate when only one word was searched but was missing the target when more than one word was searched.
Now we are searching for the best matches interval to crop around, the chosen interval is the one:
1) that have the highest count of unique matches
> for example, if we have a query `split the world`, then the interval `the split the split the` has 5 matches but only 2 unique matches (1 for `split` and 1 for `the`) where the interval `split of the world` has 3 matches and 3 unique matches. So the interval `split of the world` is considered better.
2) that have the minimum distance between matches
> for example, if we have a query `split the world`, then the interval `split of the world` has a distance of 3 (2 between `split` and `the`, and 1 between `the` and `world`) where the interval `split the world` has a distance of 2. So the interval `split the world` is considered better.
3) that have the highest count of ordered matches
> for example, if we have a query `split the world`, then the interval `the world split` has 2 ordered words where the interval `split the world` has 3. So the interval `split the world` is considered better.
## Cropping around the best matches interval
Before we were cropping around the interval without checking the context.
Now we are cropping around words in the same context as matching words.
This means that we will keep words that are farther from the matching words but are in the same phrase, than words that are nearer but separated by a dot.
> For instance, for the matching word `Split` the text:
`Natalie risk her future. Split The World is a book written by Emily Henry. I never read it.`
will be cropped like:
`…. Split The World is a book written by Emily Henry. …`
and not like:
`Natalie risk her future. Split The World is a book …`
Co-authored-by: ManyTheFish <many@meilisearch.com>
2022-04-19 11:42:32 +00:00
ManyTheFish
f1115e274f
Use Copy impl of FormatOption instead of clonning
2022-04-19 10:35:50 +02:00
Tamo
00f78d6b5a
Apply code suggestions
...
Co-authored-by: Clément Renault <clement@meilisearch.com>
2022-04-14 11:14:08 +02:00
Tamo
399fba16bb
only flatten an object if it's nested
2022-04-14 11:14:08 +02:00
Tamo
ee64f4a936
Use smartstring to store the external id in our hashmap
...
We need to store all the external id (primary key) in a hashmap
associated to their internal id during.
The smartstring remove heap allocation / memory usage and should
improve the cache locality.
2022-04-13 21:22:07 +02:00
ad hoc
dda28d7415
exclude excluded canditates from search result candidates
2022-04-13 12:10:35 +02:00
ad hoc
bbb6728d2f
add distinct attributes to cli
2022-04-13 12:10:35 +02:00
ManyTheFish
5809d3ae0d
Add first benchmarks on formatting
2022-04-12 16:31:58 +02:00
ManyTheFish
827cedcd15
Add format option structure
2022-04-12 13:42:14 +02:00
ManyTheFish
011f8210ed
Make compute_matches more rust idiomatic
2022-04-12 10:19:02 +02:00
ManyTheFish
a16de5de84
Symplify format and remove intermediate function
2022-04-08 11:20:41 +02:00
ManyTheFish
a769e09dfa
Make token_crop_bounds more rust idiomatic
2022-04-07 20:15:14 +02:00
ManyTheFish
c8ed1675a7
Add some documentation
2022-04-07 17:32:13 +02:00
ManyTheFish
b1905dfa24
Make split_best_frequency returns references instead of owned data
2022-04-07 17:05:44 +02:00
Irevoire
4f3ce6d9cd
nested fields
2022-04-07 16:58:46 +02:00
ad hoc
b799f3326b
rename merge_nothing to merge_ignore_values
2022-04-05 18:44:35 +02:00
ManyTheFish
fa7d3a37c0
Make some cleaning and add comments
2022-04-05 17:48:56 +02:00
ManyTheFish
3bb1e35ada
Fix match count
2022-04-05 17:48:45 +02:00
ManyTheFish
56e0edd621
Put crop markers direclty around words
2022-04-05 17:41:32 +02:00
ManyTheFish
a93cd8c61c
Fix prefix highlight with special chars
2022-04-05 17:41:32 +02:00
ManyTheFish
b3f0f39106
Make some cleaning
2022-04-05 17:41:32 +02:00
ManyTheFish
6dc345bc53
Test and Fix prefix highlight
2022-04-05 17:41:32 +02:00
ManyTheFish
bd30ee97b8
Keep separators at start of the croped string
2022-04-05 17:41:32 +02:00
ManyTheFish
29c5f76d7f
Use new matcher in http-ui
2022-04-05 17:41:32 +02:00
ManyTheFish
734d0899d3
Publish Matcher
2022-04-05 17:41:32 +02:00
ManyTheFish
4428cb5909
Add some tests and fix some corner cases
2022-04-05 17:41:32 +02:00
ManyTheFish
844f546a8b
Add matches algorithm V1
2022-04-05 17:41:32 +02:00
ManyTheFish
3be1790803
Add crop algorithm with naive match algorithm
2022-04-05 17:41:32 +02:00
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
