many
59f58c15f7
Implement attribute criterion
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* Implement WordLevelIterator
* Implement QueryLevelIterator
* Implement set algorithm based on iterators
Not tested + Some TODO to fix
2021-04-27 14:39:52 +02:00
Clément Renault
361193099f
Reduce the amount of branches when query tree flattened
2021-04-27 14:39:52 +02:00
Kerollmops
7ff4a2a708
Display the number of entries in the infos crate
2021-04-27 14:39:52 +02:00
Kerollmops
1aad66bdaa
Compute stats about the word prefix level positions database in the infos crate
2021-04-27 14:39:52 +02:00
Kerollmops
e65bad16cc
Compute the words prefixes at the end of an update
2021-04-27 14:39:52 +02:00
many
ab92c814c3
Fix attributes score
2021-04-27 14:35:43 +02:00
Clément Renault
0ad9499b93
Fix an indexing bug in the words level positions
2021-04-27 14:35:43 +02:00
Clément Renault
7aa5753ed2
Make the attribute positions range bounds to be fixed
2021-04-27 14:35:43 +02:00
Clément Renault
658f316511
Introduce the Initial Criterion
2021-04-27 14:35:43 +02:00
Kerollmops
89ee2cf576
Introduce the TreeLevel struct
2021-04-27 14:25:35 +02:00
Kerollmops
bd1a371c62
Compute the WordsLevelPositions only once
2021-04-27 14:25:34 +02:00
Kerollmops
8bd4f5d93e
Compute the biggest values of the words_level_positions_docids
2021-04-27 14:25:34 +02:00
Kerollmops
f713828406
Implement the clear and delete documents for the word-level-positions database
2021-04-27 14:25:34 +02:00
Kerollmops
3069bf4f4a
Fix and improve the words-level-positions computation
2021-04-27 14:25:34 +02:00
Kerollmops
6b1b42b928
Introduce an infos wordsLevelPositionsDocids subcommand
2021-04-27 14:25:34 +02:00
Kerollmops
e8cc7f9cee
Expose a route in the http-ui to update the WordsLevelPositions
2021-04-27 14:25:34 +02:00
Kerollmops
3a25137ee4
Expose and use the WordsLevelPositions update
2021-04-27 14:25:34 +02:00
Kerollmops
c765f277a3
Introduce the WordsLevelPositions update
2021-04-27 14:25:34 +02:00
Kerollmops
9242f2f1d4
Store the first word positions levels
2021-04-27 14:25:34 +02:00
Kerollmops
b0a417f342
Introduce the word_level_position_docids Index database
2021-04-27 14:25:34 +02:00
many
75e7b1e3da
Implement test Context methods
2021-04-27 14:25:34 +02:00
many
4ff67ec2ee
Implement attribute criterion for small amounts of candidates
2021-04-27 14:25:34 +02:00
Kerollmops
0f4c0beffd
Introduce the Attribute criterion
2021-04-27 14:25:34 +02:00
Clément Renault
3bcc1c0560
Merge pull request #164 from meilisearch/clippy-fixes
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Make clippy happy
2021-04-21 13:32:29 +02:00
tamo
f8dee1b402
[makes clippy happy] search/criteria/proximity.rs
2021-04-21 12:36:45 +02:00
tamo
7fa3a1d23e
makes clippy happy http-ui
2021-04-21 12:36:45 +02:00
Clément Renault
28a8df2f0a
Merge pull request #160 from shekhirin/query-words-limit
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Support query words limit
2021-04-21 11:14:09 +02:00
Alexey Shekhirin
6fa00c61d2
feat(search): support words_limit
2021-04-20 12:22:04 +03:00
Clément Renault
726fcf015a
Merge pull request #146 from meilisearch/facet-float-integer-becomes-number
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Facet float-integer becomes facet number
2021-04-20 10:31:47 +02:00
Kerollmops
c9b2d3ae1a
Warn instead of returning an error when a conversion fails
2021-04-20 10:23:31 +02:00
Kerollmops
2aeef09316
Remove debug logs while iterating through the facet levels
2021-04-20 10:23:31 +02:00
Kerollmops
51767725b2
Simplify integer and float functions trait bounds
2021-04-20 10:23:31 +02:00
Kerollmops
efbfa81fa7
Merge the Float and Integer enum variant into the Number one
2021-04-20 10:23:30 +02:00
Clément Renault
f5ec14c54c
Merge pull request #163 from meilisearch/next-release-v0.1.1
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Update version for the next release (v0.1.1)
2021-04-19 15:52:13 +02:00
Clémentine Urquizar
127d3d028e
Update version for the next release (v0.1.1)
2021-04-19 14:48:13 +02:00
Clément Renault
1095874e7e
Merge pull request #158 from shekhirin/synonyms
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Support synonyms
2021-04-18 11:00:13 +02:00
Alexey Shekhirin
33860bc3b7
test(update, settings): set & reset synonyms
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fixes after review
more fixes after review
2021-04-18 11:24:17 +03:00
Alexey Shekhirin
e39aabbfe6
feat(search, update): synonyms
2021-04-18 11:24:17 +03:00
Clément Renault
995d1a07d4
Merge pull request #162 from michaelchiche/patch-1
2021-04-17 09:47:08 +02:00
Michael Chiche
f6b06d6e5d
typo: wrong command in example
2021-04-16 20:08:43 +02:00
Clément Renault
19b6620a92
Merge pull request #125 from meilisearch/distinct
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Implement distinct attribute
2021-04-15 16:33:49 +02:00
Marin Postma
9c4660d3d6
add tests
2021-04-15 16:25:56 +02:00
Marin Postma
75464a1baa
review fixes
2021-04-15 16:25:56 +02:00
Marin Postma
2f73fa55ae
add documentation
2021-04-15 16:25:55 +02:00
Marin Postma
45c45e11dd
implement distinct attribute
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distinct can return error
facet distinct on numbers
return distinct error
review fixes
make get_facet_value more generic
fixes
2021-04-15 16:25:55 +02:00
Clément Renault
6e126c96a9
Merge pull request #159 from meilisearch/upd-tokenizer-v0.2.1
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Update Tokenizer version to v0.2.1
2021-04-14 19:02:36 +02:00
Clémentine Urquizar
2c5c79d68e
Update Tokenizer version to v0.2.1
2021-04-14 18:54:04 +02:00
Clément Renault
c2df51aa95
Merge pull request #156 from meilisearch/stop-words
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Stop words
2021-04-14 17:33:06 +02:00
tamo
dcb00b2e54
test a new implementation of the stop_words
2021-04-12 18:35:33 +02:00
tamo
da036dcc3e
Revert "Integrate the stop_words in the querytree"
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This reverts commit 12fb509d84#150 .
The initial algorithm we implemented for the stop_words was:
1. remove the stop_words from the dataset
2. keep the stop_words in the query to see if we can generate new words by
integrating typos or if the word was a prefix
=> This was causing the bug since, in the case of “The hobbit”, we were
**always** looking for something starting with “t he” or “th e”
instead of ignoring the word completely.
For now we are going to fix the bug by completely ignoring the
stop_words in the query.
This could cause another problem were someone mistyped a normal word and
ended up typing a stop_word.
For example imagine someone searching for the music “Won't he do it”.
If that person misplace one space and write “Won' the do it” then we
will loose a part of the request.
One fix would be to update our query tree to something like that:
---------------------
OR
OR
TOLERANT hobbit # the first option is to ignore the stop_word
AND
CONSECUTIVE # the second option is to do as we are doing
EXACT t # currently
EXACT he
TOLERANT hobbit
---------------------
This would increase drastically the size of our query tree on request
with a lot of stop_words. For example think of “The Lord Of The Rings”.
For now whatsoever we decided we were going to ignore this problem and consider
that it doesn't reduce too much the relevancy of the search to do that
while it improves the performances.
2021-04-12 18:35:33 +02:00
