Commit Graph

1098 Commits

Author SHA1 Message Date
ManyTheFish
993aa1321c Fix query tree building 2022-08-18 17:56:06 +02:00
ManyTheFish
bff9653050 Fix remove count 2022-08-18 17:36:30 +02:00
ManyTheFish
9640976c79 Rename TermMatchingPolicies 2022-08-18 17:36:08 +02:00
bors[bot]
afc10acd19
Merge #596
596: Filter operators: NOT + IN[..] r=irevoire a=loiclec

# Pull Request

## What does this PR do?
Implements the changes described in https://github.com/meilisearch/meilisearch/issues/2580
It is based on top of #556 

Co-authored-by: Loïc Lecrenier <loic@meilisearch.com>
2022-08-18 11:24:32 +00:00
Loïc Lecrenier
9b6602cba2 Avoid cloning FilterCondition in filter array parsing 2022-08-18 13:06:57 +02:00
Loïc Lecrenier
c51dcad51b Don't recompute filterable fields in evaluation of IN[] filter 2022-08-18 10:59:21 +02:00
Irevoire
4aae07d5f5
expose the size methods 2022-08-17 17:07:38 +02:00
Irevoire
e96b852107
bump heed 2022-08-17 17:05:50 +02:00
bors[bot]
087da5621a
Merge #587
587: Word prefix pair proximity docids indexation refactor r=Kerollmops a=loiclec

# Pull Request

## What does this PR do?
Refactor the code of `WordPrefixPairProximityDocIds` to make it much faster, fix a bug, and add a unit test.

## Why is it faster?
Because we avoid using a sorter to insert the (`word1`, `prefix`, `proximity`) keys and their associated bitmaps, and thus we don't have to sort a potentially very big set of data. I have also added a couple of other optimisations: 

1. reusing allocations
2. using a prefix trie instead of an array of prefixes to get all the prefixes of a word
3. inserting directly into the database instead of putting the data in an intermediary grenad when possible. Also avoid checking for pre-existing values in the database when we know for certain that they do not exist. 

## What bug was fixed?
When reindexing, the `new_prefix_fst_words` prefixes may look like:
```
["ant",  "axo", "bor"]
```
which we group by first letter:
```
[["ant", "axo"], ["bor"]]
```

Later in the code, if we have the word2 "axolotl", we try to find which subarray of prefixes contains its prefixes. This check is done with `word2.starts_with(subarray_prefixes[0])`, but `"axolotl".starts_with("ant")` is false, and thus we wrongly think that there are no prefixes in `new_prefix_fst_words` that are prefixes of `axolotl`.

## StrStrU8Codec
I had to change the encoding of `StrStrU8Codec` to make the second string null-terminated as well. I don't think this should be a problem, but I may have missed some nuances about the impacts of this change.

## Requests when reviewing this PR
I have explained what the code does in the module documentation of `word_pair_proximity_prefix_docids`. It would be nice if someone could read it and give their opinion on whether it is a clear explanation or not. 

I also have a couple questions regarding the code itself:
- Should we clean up and factor out the `PrefixTrieNode` code to try and make broader use of it outside this module? For now, the prefixes undergo a few transformations: from FST, to array, to prefix trie. It seems like it could be simplified.
- I wrote a function called `write_into_lmdb_database_without_merging`. (1) Are we okay with such a function existing? (2) Should it be in `grenad_helpers` instead?

## Benchmark Results

We reduce the time it takes to index about 8% in most cases, but it varies between -3% and -20%. 

```
group                                                                     indexing_main_ce90fc62                  indexing_word-prefix-pair-proximity-docids-refactor_cbad2023
-----                                                                     ----------------------                  ------------------------------------------------------------
indexing/-geo-delete-facetedNumber-facetedGeo-searchable-                 1.00  1893.0±233.03µs        ? ?/sec    1.01  1921.2±260.79µs        ? ?/sec
indexing/-movies-delete-facetedString-facetedNumber-searchable-           1.05      9.4±3.51ms        ? ?/sec     1.00      9.0±2.14ms        ? ?/sec
indexing/-movies-delete-facetedString-facetedNumber-searchable-nested-    1.22    18.3±11.42ms        ? ?/sec     1.00     15.0±5.79ms        ? ?/sec
indexing/-songs-delete-facetedString-facetedNumber-searchable-            1.00     41.4±4.20ms        ? ?/sec     1.28    53.0±13.97ms        ? ?/sec
indexing/-wiki-delete-searchable-                                         1.00   285.6±18.12ms        ? ?/sec     1.03   293.1±16.09ms        ? ?/sec
indexing/Indexing geo_point                                               1.03      60.8±0.45s        ? ?/sec     1.00      58.8±0.68s        ? ?/sec
indexing/Indexing movies in three batches                                 1.14      16.5±0.30s        ? ?/sec     1.00      14.5±0.24s        ? ?/sec
indexing/Indexing movies with default settings                            1.11      13.7±0.07s        ? ?/sec     1.00      12.3±0.28s        ? ?/sec
indexing/Indexing nested movies with default settings                     1.10      10.6±0.11s        ? ?/sec     1.00       9.6±0.15s        ? ?/sec
indexing/Indexing nested movies without any facets                        1.11       9.4±0.15s        ? ?/sec     1.00       8.5±0.10s        ? ?/sec
indexing/Indexing songs in three batches with default settings            1.18      66.2±0.39s        ? ?/sec     1.00      56.0±0.67s        ? ?/sec
indexing/Indexing songs with default settings                             1.07      58.7±1.26s        ? ?/sec     1.00      54.7±1.71s        ? ?/sec
indexing/Indexing songs without any facets                                1.08      53.1±0.88s        ? ?/sec     1.00      49.3±1.43s        ? ?/sec
indexing/Indexing songs without faceted numbers                           1.08      57.7±1.33s        ? ?/sec     1.00      53.3±0.98s        ? ?/sec
indexing/Indexing wiki                                                    1.06   1051.1±21.46s        ? ?/sec     1.00    989.6±24.55s        ? ?/sec
indexing/Indexing wiki in three batches                                   1.20    1184.8±8.93s        ? ?/sec     1.00     989.7±7.06s        ? ?/sec
indexing/Reindexing geo_point                                             1.04      67.5±0.75s        ? ?/sec     1.00      64.9±0.32s        ? ?/sec
indexing/Reindexing movies with default settings                          1.12      13.9±0.17s        ? ?/sec     1.00      12.4±0.13s        ? ?/sec
indexing/Reindexing songs with default settings                           1.05      60.6±0.84s        ? ?/sec     1.00      57.5±0.99s        ? ?/sec
indexing/Reindexing wiki                                                  1.07   1725.0±17.92s        ? ?/sec     1.00    1611.4±9.90s        ? ?/sec
```

Co-authored-by: Loïc Lecrenier <loic@meilisearch.com>
2022-08-17 14:06:12 +00:00
bors[bot]
fb95e67a2a
Merge #608
608: Fix soft deleted documents r=ManyTheFish a=ManyTheFish

When we replaced or updated some documents, the indexing was skipping the replaced documents.

Related to https://github.com/meilisearch/meilisearch/issues/2672

Co-authored-by: ManyTheFish <many@meilisearch.com>
2022-08-17 13:38:10 +00:00
bors[bot]
e4a52e6e45
Merge #594
594: Fix(Search): Fix phrase search candidates computation r=Kerollmops a=ManyTheFish

This bug is an old bug but was hidden by the proximity criterion,
Phrase searches were always returning an empty candidates list when the proximity criterion is deactivated.

Before the fix, we were trying to find any words[n] near words[n]
instead of finding  any words[n] near words[n+1], for example:

for a phrase search '"Hello world"' we were searching for "hello" near "hello" first, instead of "hello" near "world".



Co-authored-by: ManyTheFish <many@meilisearch.com>
2022-08-17 13:22:52 +00:00
ManyTheFish
8c3f1a9c39 Remove useless lifetime declaration 2022-08-17 15:20:43 +02:00
ManyTheFish
e9e2349ce6 Fix typo in comment 2022-08-17 15:09:48 +02:00
ManyTheFish
2668f841d1 Fix update indexing 2022-08-17 15:03:37 +02:00
ManyTheFish
7384650d85 Update test to showcase the bug 2022-08-17 15:03:08 +02:00
bors[bot]
39869be23b
Merge #590
590: Optimise facets indexing r=Kerollmops a=loiclec

# Pull Request

## What does this PR do?
Fixes #589 

## Notes
I added documentation for the whole module which attempts to explain the shape of the databases and their purpose. However, I realise there is already some documentation about this, so I am not sure if we want to keep it.

## Benchmarks

We get a ~1.15x speed up on the geo_point benchmark.

```
group                                                                     indexing_main_57042355                  indexing_optimise-facets-indexation_5728619a
-----                                                                     ----------------------                  --------------------------------------------
indexing/-geo-delete-facetedNumber-facetedGeo-searchable-                 1.00  1862.7±294.45µs        ? ?/sec    1.58      2.9±1.32ms        ? ?/sec
indexing/-movies-delete-facetedString-facetedNumber-searchable-           1.11      8.9±2.44ms        ? ?/sec     1.00      8.0±1.42ms        ? ?/sec
indexing/-movies-delete-facetedString-facetedNumber-searchable-nested-    1.00     12.8±3.32ms        ? ?/sec     1.32     16.9±6.98ms        ? ?/sec
indexing/-songs-delete-facetedString-facetedNumber-searchable-            1.09     43.8±4.78ms        ? ?/sec     1.00     40.3±3.79ms        ? ?/sec
indexing/-wiki-delete-searchable-                                         1.08   287.4±28.72ms        ? ?/sec     1.00    264.9±9.46ms        ? ?/sec
indexing/Indexing geo_point                                               1.14      61.2±0.39s        ? ?/sec     1.00      53.8±0.57s        ? ?/sec
indexing/Indexing movies in three batches                                 1.00      16.6±0.12s        ? ?/sec     1.00      16.5±0.10s        ? ?/sec
indexing/Indexing movies with default settings                            1.00      14.1±0.30s        ? ?/sec     1.00      14.0±0.28s        ? ?/sec
indexing/Indexing nested movies with default settings                     1.10      10.9±0.50s        ? ?/sec     1.00      10.0±0.10s        ? ?/sec
indexing/Indexing nested movies without any facets                        1.01       9.6±0.23s        ? ?/sec     1.00       9.5±0.06s        ? ?/sec
indexing/Indexing songs in three batches with default settings            1.07      66.3±0.55s        ? ?/sec     1.00      61.8±0.63s        ? ?/sec
indexing/Indexing songs with default settings                             1.03      58.8±0.82s        ? ?/sec     1.00      57.1±1.22s        ? ?/sec
indexing/Indexing songs without any facets                                1.00      53.6±1.09s        ? ?/sec     1.01      54.0±0.58s        ? ?/sec
indexing/Indexing songs without faceted numbers                           1.02      58.0±1.29s        ? ?/sec     1.00      57.1±1.43s        ? ?/sec
indexing/Indexing wiki                                                    1.00   1064.1±21.20s        ? ?/sec     1.00   1068.0±20.49s        ? ?/sec
indexing/Indexing wiki in three batches                                   1.00    1182.5±9.62s        ? ?/sec     1.01   1191.2±10.96s        ? ?/sec
indexing/Reindexing geo_point                                             1.12      68.0±0.21s        ? ?/sec     1.00      60.5±0.82s        ? ?/sec
indexing/Reindexing movies with default settings                          1.01      14.1±0.21s        ? ?/sec     1.00      14.0±0.26s        ? ?/sec
indexing/Reindexing songs with default settings                           1.04      61.6±0.57s        ? ?/sec     1.00      59.2±0.87s        ? ?/sec
indexing/Reindexing wiki                                                  1.00   1734.0±11.38s        ? ?/sec     1.01   1746.6±22.48s        ? ?/sec
```


Co-authored-by: Loïc Lecrenier <loic@meilisearch.com>
2022-08-17 11:46:55 +00:00
Loïc Lecrenier
6cc975704d Add some documentation to facets.rs 2022-08-17 12:59:52 +02:00
Loïc Lecrenier
93252769af Apply review suggestions 2022-08-17 12:41:22 +02:00
Loïc Lecrenier
196f79115a Run cargo fmt 2022-08-17 12:28:33 +02:00
Loïc Lecrenier
d10d78d520 Add integration tests for the IN filter 2022-08-17 12:28:33 +02:00
Loïc Lecrenier
ca97cb0eda Implement the IN filter operator 2022-08-17 12:28:33 +02:00
Loïc Lecrenier
cc7415bb31 Simplify FilterCondition code, made possible by the new NOT operator 2022-08-17 12:28:33 +02:00
Loïc Lecrenier
44744d9e67 Implement the simplified NOT operator 2022-08-17 12:28:33 +02:00
Loïc Lecrenier
01675771d5 Reimplement != filter to select all docids not selected by = 2022-08-17 12:28:33 +02:00
Loïc Lecrenier
258c3dd563 Make AND+OR filters n-ary (store a vector of subfilters instead of 2)
NOTE: The token_at_depth is method is a bit useless now, as the only
cases where there would be a toke at depth 1000 are the cases where
the parser already stack-overflowed earlier.

Example: (((((... (x=1) ...)))))
2022-08-17 12:28:33 +02:00
Loïc Lecrenier
39687908f1 Add documentation and comments to facets.rs 2022-08-17 12:26:49 +02:00
Loïc Lecrenier
8d4b21a005 Switch string facet levels indexation to new algo
Write the algorithm once for both numbers and strings
2022-08-17 12:26:49 +02:00
Loïc Lecrenier
cf0cd92ed4 Refactor Facets::execute to increase performance 2022-08-17 12:26:49 +02:00
bors[bot]
cd2635ccfc
Merge #602
602: Use mimalloc as the default allocator r=Kerollmops a=loiclec

## What does this PR do?
Use mimalloc as the global allocator for milli's benchmarks on macOS.

## Why?
On Linux, we use jemalloc, which is a very fast allocator. But on macOS, we currently use the system allocator, which is very slow. In practice, this difference in allocator speed means that it is difficult to gain insight into milli's performance by running benchmarks locally on the Mac.

By using mimalloc, which is another excellent allocator, we reduce the speed difference between the two platforms.

Co-authored-by: Loïc Lecrenier <loic@meilisearch.com>
2022-08-17 10:26:13 +00:00
Loïc Lecrenier
78d9f0622d cargo fmt 2022-08-17 12:21:24 +02:00
Loïc Lecrenier
4f9edf13d7 Remove commented-out function 2022-08-17 12:21:24 +02:00
Loïc Lecrenier
405555b401 Add some documentation to PrefixTrieNode 2022-08-17 12:21:24 +02:00
Loïc Lecrenier
1bc4788e59 Remove cached Allocations struct from wpppd indexing 2022-08-17 12:18:22 +02:00
Loïc Lecrenier
ef75a77464 Fix undefined behaviour caused by reusing key from the database
New full snapshot:
---
source: milli/src/update/word_prefix_pair_proximity_docids.rs
---
5                a    1  [101, ]
5                a    2  [101, ]
5                am   1  [101, ]
5                b    4  [101, ]
5                be   4  [101, ]
am               a    3  [101, ]
amazing          a    1  [100, ]
amazing          a    2  [100, ]
amazing          a    3  [100, ]
amazing          an   1  [100, ]
amazing          an   2  [100, ]
amazing          b    2  [100, ]
amazing          be   2  [100, ]
an               a    1  [100, ]
an               a    2  [100, 202, ]
an               am   1  [100, ]
an               an   2  [100, ]
an               b    3  [100, ]
an               be   3  [100, ]
and              a    2  [100, ]
and              a    3  [100, ]
and              a    4  [100, ]
and              am   2  [100, ]
and              an   3  [100, ]
and              b    1  [100, ]
and              be   1  [100, ]
at               a    1  [100, 202, ]
at               a    2  [100, 101, ]
at               a    3  [100, ]
at               am   2  [100, 101, ]
at               an   1  [100, 202, ]
at               an   3  [100, ]
at               b    3  [101, ]
at               b    4  [100, ]
at               be   3  [101, ]
at               be   4  [100, ]
beautiful        a    2  [100, ]
beautiful        a    3  [100, ]
beautiful        a    4  [100, ]
beautiful        am   3  [100, ]
beautiful        an   2  [100, ]
beautiful        an   4  [100, ]
bell             a    2  [101, ]
bell             a    4  [101, ]
bell             am   4  [101, ]
extraordinary    a    2  [202, ]
extraordinary    a    3  [202, ]
extraordinary    an   2  [202, ]
house            a    3  [100, 202, ]
house            a    4  [100, 202, ]
house            am   4  [100, ]
house            an   3  [100, 202, ]
house            b    2  [100, ]
house            be   2  [100, ]
rings            a    1  [101, ]
rings            a    3  [101, ]
rings            am   3  [101, ]
rings            b    2  [101, ]
rings            be   2  [101, ]
the              a    3  [101, ]
the              b    1  [101, ]
the              be   1  [101, ]
2022-08-17 12:17:45 +02:00
Loïc Lecrenier
7309111433 Don't run block code in doc tests of word_pair_proximity_docids 2022-08-17 12:17:18 +02:00
Loïc Lecrenier
f6f8f543e1 Run cargo fmt 2022-08-17 12:17:18 +02:00
Loïc Lecrenier
34c991ea02 Add newlines in documentation of word_prefix_pair_proximity_docids 2022-08-17 12:17:18 +02:00
Loïc Lecrenier
06f3fd8c6d Add more comments to WordPrefixPairProximityDocids::execute 2022-08-17 12:17:18 +02:00
Loïc Lecrenier
474500362c Update wpppd snapshots
New snapshot (yes, it's wrong as well, it will get fixed later):

---
source: milli/src/update/word_prefix_pair_proximity_docids.rs
---
5                a    1  [101, ]
5                a    2  [101, ]
5                am   1  [101, ]
5                b    4  [101, ]
5                be   4  [101, ]
am               a    3  [101, ]
amazing          a    1  [100, ]
amazing          a    2  [100, ]
amazing          a    3  [100, ]
amazing          an   1  [100, ]
amazing          an   2  [100, ]
amazing          b    2  [100, ]
amazing          be   2  [100, ]
an               a    1  [100, ]
an               a    2  [100, 202, ]
an               am   1  [100, ]
an               b    3  [100, ]
an               be   3  [100, ]
and              a    2  [100, ]
and              a    3  [100, ]
and              a    4  [100, ]
and              b    1  [100, ]
and              be   1  [100, ]
                 d\0  0  [100, 202, ]
an               an   2  [100, ]
and              am   2  [100, ]
and              an   3  [100, ]
at               a    2  [100, 101, ]
at               a    3  [100, ]
at               am   2  [100, 101, ]
at               an   1  [100, 202, ]
at               an   3  [100, ]
at               b    3  [101, ]
at               b    4  [100, ]
at               be   3  [101, ]
at               be   4  [100, ]
beautiful        a    2  [100, ]
beautiful        a    3  [100, ]
beautiful        a    4  [100, ]
beautiful        am   3  [100, ]
beautiful        an   2  [100, ]
beautiful        an   4  [100, ]
bell             a    2  [101, ]
bell             a    4  [101, ]
bell             am   4  [101, ]
extraordinary    a    2  [202, ]
extraordinary    a    3  [202, ]
extraordinary    an   2  [202, ]
house            a    4  [100, 202, ]
house            a    4  [100, ]
house            am   4  [100, ]
house            an   3  [100, 202, ]
house            b    2  [100, ]
house            be   2  [100, ]
rings            a    1  [101, ]
rings            a    3  [101, ]
rings            am   3  [101, ]
rings            b    2  [101, ]
rings            be   2  [101, ]
the              a    3  [101, ]
the              b    1  [101, ]
the              be   1  [101, ]
2022-08-17 12:17:18 +02:00
Loïc Lecrenier
ea4a96761c Move content of readme for WordPrefixPairProximityDocids into the code 2022-08-17 12:05:37 +02:00
Loïc Lecrenier
220921628b Simplify and document WordPrefixPairProximityDocIds::execute 2022-08-17 11:59:19 +02:00
Loïc Lecrenier
044356d221 Optimise WordPrefixPairProximityDocIds merge operation 2022-08-17 11:59:18 +02:00
Loïc Lecrenier
d350114159 Add tests for WordPrefixPairProximityDocIds 2022-08-17 11:59:15 +02:00
Loïc Lecrenier
86807ca848 Refactor word prefix pair proximity indexation further 2022-08-17 11:59:13 +02:00
Loïc Lecrenier
306593144d Refactor word prefix pair proximity indexation 2022-08-17 11:59:00 +02:00
Loïc Lecrenier
20be69e1b9 Always use mimalloc as the global allocator 2022-08-16 20:09:36 +02:00
Loïc Lecrenier
dea00311b6 Add type annotations to remove compiler error 2022-08-16 09:19:30 +02:00
Loïc Lecrenier
6f49126223 Fix db_snap macro with inline parameter 2022-08-10 15:55:22 +02:00
Loïc Lecrenier
12920f2a4f Fix paths of snapshot tests 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
4b7fd4dfae Update insta version 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
ce560fdcb5 Add documentation for db_snap! 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
748bb86b5b cargo fmt 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
051f24f674 Switch to snapshot tests for search/matches/mod.rs 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
d2e01528a6 Switch to snapshot tests for search/criteria/typo.rs 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
a9c7d82693 Switch to snapshot tests for search/criteria/attribute.rs 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
4bba2f41d7 Switch to snapshot tests for query_tree.rs 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
8ac24d3114 Cargo fmt + fix compiler warnings/error 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
6066256689 Add snapshot tests for indexing of word_prefix_pair_proximity_docids 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
3a734af159 Add snapshot tests for Facets::execute 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
b9907997e4 Remove old snapshot tests code 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
ef889ade5d Refactor snapshot tests 2022-08-10 15:53:46 +02:00
Loïc Lecrenier
334098a7e0 Add index snapshot test helper function 2022-08-10 15:53:46 +02:00
ManyTheFish
b389be48a0 Factorize phrase computation 2022-08-08 10:37:31 +02:00
Loïc Lecrenier
58cb1c1bda Simplify unit tests in facet/filter.rs 2022-08-04 12:03:44 +02:00
Loïc Lecrenier
acff17fb88 Simplify indexing tests 2022-08-04 12:03:13 +02:00
bors[bot]
21284cf235
Merge #556
556: Add EXISTS filter r=loiclec a=loiclec

## What does this PR do?

Fixes issue [#2484](https://github.com/meilisearch/meilisearch/issues/2484) in the meilisearch repo.

It creates a `field EXISTS` filter which selects all documents containing the `field` key. 
For example, with the following documents:
```json
[{
	"id": 0,
	"colour": []
},
{
	"id": 1,
	"colour": ["blue", "green"]
},
{
	"id": 2,
	"colour": 145238
},
{
	"id": 3,
	"colour": null
},
{
	"id": 4,
	"colour": {
		"green": []
	}
},
{
	"id": 5,
	"colour": {}
},
{
	"id": 6
}]
```
Then the filter `colour EXISTS` selects the ids `[0, 1, 2, 3, 4, 5]`. The filter `colour NOT EXISTS` selects `[6]`.

## Details
There is a new database named `facet-id-exists-docids`. Its keys are field ids and its values are bitmaps of all the document ids where the corresponding field exists.

To create this database, the indexing part of milli had to be adapted. The implementation there is basically copy/pasted from the code handling the `facet-id-f64-docids` database, with appropriate modifications in place.

There was an issue involving the flattening of documents during (re)indexing. Previously, the following JSON:
```json
{
    "id": 0,
    "colour": [],
    "size": {}
}
```
would be flattened to:
```json
{
    "id": 0
}
```
prior to being given to the extraction pipeline.

This transformation would lose the information that is needed to populate the `facet-id-exists-docids` database. Therefore, I have also changed the implementation of the `flatten-serde-json` crate. Now, as it traverses the Json, it keeps track of which key was encountered. Then, at the end, if a previously encountered key is not present in the flattened object, it adds that key to the object with an empty array as value. For example:
```json
{
    "id": 0,
    "colour": {
        "green": [],
        "blue": 1
    },
    "size": {}
} 
```
becomes
```json
{
    "id": 0,
    "colour": [],
    "colour.green": [],
    "colour.blue": 1,
    "size": []
} 
```


Co-authored-by: Kerollmops <clement@meilisearch.com>
2022-08-04 09:46:06 +00:00
bors[bot]
50f6524ff2
Merge #579
579: Stop reindexing already indexed documents r=ManyTheFish a=irevoire

```
 % ./compare.sh indexing_stop-reindexing-unchanged-documents_cb5a1669.json indexing_main_eeba1960.json
group                                                                     indexing_main_eeba1960                 indexing_stop-reindexing-unchanged-documents_cb5a1669
-----                                                                     ----------------------                 -----------------------------------------------------
indexing/-geo-delete-facetedNumber-facetedGeo-searchable-                 1.03      2.0±0.22ms        ? ?/sec    1.00  1955.4±336.24µs        ? ?/sec
indexing/-movies-delete-facetedString-facetedNumber-searchable-           1.08     11.0±2.93ms        ? ?/sec    1.00     10.2±4.04ms        ? ?/sec
indexing/-movies-delete-facetedString-facetedNumber-searchable-nested-    1.00     15.1±3.89ms        ? ?/sec    1.14     17.1±5.18ms        ? ?/sec
indexing/-songs-delete-facetedString-facetedNumber-searchable-            1.26    59.2±12.01ms        ? ?/sec    1.00     47.1±8.52ms        ? ?/sec
indexing/-wiki-delete-searchable-                                         1.08   316.6±31.53ms        ? ?/sec    1.00   293.6±17.00ms        ? ?/sec
indexing/Indexing geo_point                                               1.01      60.9±0.31s        ? ?/sec    1.00      60.6±0.36s        ? ?/sec
indexing/Indexing movies in three batches                                 1.04      20.0±0.30s        ? ?/sec    1.00      19.2±0.25s        ? ?/sec
indexing/Indexing movies with default settings                            1.02      19.1±0.18s        ? ?/sec    1.00      18.7±0.24s        ? ?/sec
indexing/Indexing nested movies with default settings                     1.02      26.2±0.29s        ? ?/sec    1.00      25.9±0.22s        ? ?/sec
indexing/Indexing nested movies without any facets                        1.02      25.3±0.32s        ? ?/sec    1.00      24.7±0.26s        ? ?/sec
indexing/Indexing songs in three batches with default settings            1.00      66.7±0.41s        ? ?/sec    1.01      67.1±0.86s        ? ?/sec
indexing/Indexing songs with default settings                             1.00      58.3±0.90s        ? ?/sec    1.01      58.8±1.32s        ? ?/sec
indexing/Indexing songs without any facets                                1.00      54.5±1.43s        ? ?/sec    1.01      55.2±1.29s        ? ?/sec
indexing/Indexing songs without faceted numbers                           1.00      57.9±1.20s        ? ?/sec    1.01      58.4±0.93s        ? ?/sec
indexing/Indexing wiki                                                    1.00   1052.0±10.95s        ? ?/sec    1.02   1069.4±20.38s        ? ?/sec
indexing/Indexing wiki in three batches                                   1.00    1193.1±8.83s        ? ?/sec    1.00    1189.5±9.40s        ? ?/sec
indexing/Reindexing geo_point                                             3.22      67.5±0.73s        ? ?/sec    1.00      21.0±0.16s        ? ?/sec
indexing/Reindexing movies with default settings                          3.75      19.4±0.28s        ? ?/sec    1.00       5.2±0.05s        ? ?/sec
indexing/Reindexing songs with default settings                           8.90      61.4±0.91s        ? ?/sec    1.00       6.9±0.07s        ? ?/sec
indexing/Reindexing wiki                                                  1.00   1748.2±35.68s        ? ?/sec    1.00   1750.5±18.53s        ? ?/sec
```

tldr: We do not lose any performance on the normal indexing benchmark, but we get between 3 and 8 times faster on the reindexing benchmarks 👍 

Co-authored-by: Tamo <tamo@meilisearch.com>
2022-08-04 08:10:37 +00:00
ManyTheFish
d6f9a60a32 fix: Remove whitespace trimming during document id validation
fix #592
2022-08-03 11:38:40 +02:00
Tamo
7fc35c5586
remove the useless prints 2022-08-02 10:31:22 +02:00
Tamo
f156d7dd3b
Stop reindexing already indexed documents 2022-08-02 10:31:20 +02:00
Loïc Lecrenier
07003704a8 Merge branch 'filter/field-exist' 2022-07-21 14:51:41 +02:00
Clémentine Urquizar
d5e9b7305b
Update version for next release (v0.32.0) 2022-07-21 13:20:02 +04:00
ManyTheFish
cbb3b25459 Fix(Search): Fix phrase search candidates computation
This bug is an old bug but was hidden by the proximity criterion,
Phrase search were always returning an empty candidates list.

Before the fix, we were trying to find any words[n] near words[n]
instead of finding  any words[n] near words[n+1], for example:

for a phrase search '"Hello world"' we were searching for "hello" near "hello" first, instead of "hello" near "world".
2022-07-21 10:04:30 +02:00
bors[bot]
941af58239
Merge #561
561: Enriched documents batch reader r=curquiza a=Kerollmops

~This PR is based on #555 and must be rebased on main after it has been merged to ease the review.~
This PR contains the work in #555 and can be merged on main as soon as reviewed and approved.

- [x] Create an `EnrichedDocumentsBatchReader` that contains the external documents id.
- [x] Extract the primary key name and make it accessible in the `EnrichedDocumentsBatchReader`.
- [x] Use the external id from the `EnrichedDocumentsBatchReader` in the `Transform::read_documents`.
- [x] Remove the `update_primary_key` from the _transform.rs_ file.
- [x] Really generate the auto-generated documents ids.
- [x] Insert the (auto-generated) document ids in the document while processing it in `Transform::read_documents`.

Co-authored-by: Kerollmops <clement@meilisearch.com>
2022-07-21 07:08:50 +00:00
Loïc Lecrenier
41a0ce07cb
Add a code comment, as suggested in PR review
Co-authored-by: Many the fish <many@meilisearch.com>
2022-07-20 16:20:35 +02:00
Loïc Lecrenier
1506683705 Avoid using too much memory when indexing facet-exists-docids 2022-07-19 14:42:35 +02:00
Loïc Lecrenier
d0eee5ff7a Fix compiler error 2022-07-19 13:54:30 +02:00
Loïc Lecrenier
aed8c69bcb Refactor indexation of the "facet-id-exists-docids" database
The idea is to directly create a sorted and merged list of bitmaps
in the form of a BTreeMap<FieldId, RoaringBitmap> instead of creating
a grenad::Reader where the keys are field_id and the values are docids.

Then we send that BTreeMap to the thing that handles TypedChunks, which
inserts its content into the database.
2022-07-19 10:07:33 +02:00
Loïc Lecrenier
1eb1e73bb3 Add integration tests for the EXISTS filter 2022-07-19 10:07:33 +02:00
Loïc Lecrenier
4f0bd317df Remove custom implementation of BytesEncode/Decode for the FieldId 2022-07-19 10:07:33 +02:00
Loïc Lecrenier
80b962b4f4 Run cargo fmt 2022-07-19 10:07:33 +02:00
Loïc Lecrenier
c17d616250 Refactor index_documents_check_exists_database tests 2022-07-19 10:07:33 +02:00
Loïc Lecrenier
30bd4db0fc Simplify indexing task for facet_exists_docids database 2022-07-19 10:07:33 +02:00
Loïc Lecrenier
392472f4bb Apply suggestions from code review
Co-authored-by: Tamo <tamo@meilisearch.com>
2022-07-19 10:07:33 +02:00
Loïc Lecrenier
0388b2d463 Run cargo fmt 2022-07-19 10:07:33 +02:00
Loïc Lecrenier
dc64170a69 Improve syntax of EXISTS filter, allow “value NOT EXISTS” 2022-07-19 10:07:33 +02:00
Loïc Lecrenier
72452f0cb2 Implements the EXIST filter operator 2022-07-19 10:07:33 +02:00
Loïc Lecrenier
453d593ce8 Add a database containing the docids where each field exists 2022-07-19 10:07:33 +02:00
Many the fish
2d79720f5d
Update milli/src/search/matches/mod.rs 2022-07-18 17:48:04 +02:00
Many the fish
8ddb4e750b
Update milli/src/search/matches/mod.rs 2022-07-18 17:47:39 +02:00
Many the fish
a277daa1f2
Update milli/src/search/matches/mod.rs 2022-07-18 17:47:13 +02:00
Many the fish
fb794c6b5e
Update milli/src/search/matches/mod.rs 2022-07-18 17:46:00 +02:00
Many the fish
1237cfc249
Update milli/src/search/matches/mod.rs 2022-07-18 17:45:37 +02:00
Many the fish
d7fd5c58cd
Update milli/src/search/matches/mod.rs 2022-07-18 17:45:06 +02:00
Loïc Lecrenier
fc9f3f31e7 Change DocumentsBatchReader to access cursor and index at same time
Otherwise it is not possible to iterate over all documents while
using the fields index at the same time.
2022-07-18 16:08:14 +02:00
Loïc Lecrenier
ab1571cdec Simplify Transform::read_documents, enabled by enriched documents reader 2022-07-18 12:45:47 +02:00
Many the fish
e261ef64d7
Update milli/src/search/matches/mod.rs
Co-authored-by: Clément Renault <clement@meilisearch.com>
2022-07-18 10:18:51 +02:00
Many the fish
1da4ab5918
Update milli/src/search/matches/mod.rs
Co-authored-by: Clément Renault <clement@meilisearch.com>
2022-07-18 10:18:03 +02:00
Kerollmops
448114cc1c
Fix the benchmarks with the new indexation API 2022-07-12 15:22:09 +02:00
Kerollmops
25e768f31c
Fix another issue with the nested primary key selector 2022-07-12 15:14:07 +02:00
Kerollmops
192793ee38
Add some tests to check for the nested documents ids 2022-07-12 15:14:07 +02:00
Kerollmops
a892a4a79c
Introduce a function to extend from a JSON array of objects 2022-07-12 15:14:06 +02:00
Kerollmops
dc61105554
Fix the nested document id fetching function 2022-07-12 15:14:06 +02:00
Kerollmops
2eec290424
Check the validity of the latitute and longitude numbers 2022-07-12 15:14:06 +02:00
Kerollmops
5d149d631f
Remove tests for a function that no more exists 2022-07-12 15:14:06 +02:00
Kerollmops
0bbcc7b180
Expose the DocumentId struct to be sure to inject the generated ids 2022-07-12 15:14:06 +02:00
Kerollmops
d1a4da9812
Generate a real UUIDv4 when ids are auto-generated 2022-07-12 15:14:06 +02:00
Kerollmops
c8ebf0de47
Rename the validate function as an enriching function 2022-07-12 15:14:06 +02:00
Kerollmops
905af2a2e9
Use the primary key and external id in the transform 2022-07-12 15:14:05 +02:00
Kerollmops
742543091e
Constify the default primary key name 2022-07-12 14:55:52 +02:00
Kerollmops
5f1bfb73ee
Extract the primary key name and make it accessible 2022-07-12 14:55:52 +02:00
Kerollmops
6a0a0ae94f
Make the Transform read from an EnrichedDocumentsBatchReader 2022-07-12 14:55:52 +02:00
Kerollmops
dc3f092d07
Do not leak an internal grenad Error 2022-07-12 14:55:52 +02:00
Kerollmops
8ebf5eed0d
Make the nested primary key work 2022-07-12 14:55:52 +02:00
Kerollmops
19eb3b4708
Make sur that we do not accept floats as documents ids 2022-07-12 14:55:52 +02:00
Kerollmops
2ceeb51c37
Support the auto-generated ids when validating documents 2022-07-12 14:55:51 +02:00
Kerollmops
399eec5c01
Fix the indexation tests 2022-07-12 14:55:51 +02:00
Kerollmops
fcfc4caf8c
Move the Object type in the lib.rs file and use it everywhere 2022-07-12 14:55:51 +02:00
Kerollmops
0146175fe6
Introduce the validate_documents_batch function 2022-07-12 14:55:51 +02:00
Kerollmops
cefffde9af
Improve the .gitignore of the fuzz crate 2022-07-12 14:55:51 +02:00
Kerollmops
bdc4263883
Introduce the validate_documents_batch function 2022-07-12 14:55:51 +02:00
Kerollmops
6d0498df24
Fix the fuzz tests 2022-07-12 14:52:56 +02:00
Kerollmops
e8297ad27e
Fix the tests for the new DocumentsBatchBuilder/Reader 2022-07-12 14:52:56 +02:00
Kerollmops
419ce3966c
Rework the DocumentsBatchBuilder/Reader to use grenad 2022-07-12 14:52:55 +02:00
Kerollmops
eb63af1f10
Update grenad to 0.4.2 2022-07-12 14:52:55 +02:00
Kerollmops
048e174efb
Do not allocate when parsing CSV headers 2022-07-12 14:52:55 +02:00
ManyTheFish
5d79617a56 Chores: Enhance smart-crop code comments 2022-07-07 16:28:09 +02:00
bors[bot]
ebddfdb9a3
Merge #578
578: Bump uuid to 1.1.2 r=ManyTheFish a=Kerollmops

Just to [align the version with Meilisearch](https://github.com/meilisearch/meilisearch/pull/2584).

Co-authored-by: Kerollmops <clement@meilisearch.com>
2022-07-05 14:56:08 +00:00
Kerollmops
1bfdcfc84f
Bump uuid to 1.1.2 2022-07-05 16:23:36 +02:00
Tamo
250be9fe6c
put the threshold back to 10k 2022-07-05 15:57:44 +02:00
Tamo
b61efd09fc
Makes the internal soft deleted error a UserError 2022-07-05 15:34:45 +02:00
Tamo
eaf28b0628
Apply review suggestions
Co-authored-by: Clément Renault <clement@meilisearch.com>
2022-07-05 15:30:33 +02:00
Tamo
3b309f654a
Fasten the document deletion
When a document deletion occurs, instead of deleting the document we mark it as deleted
in the new “soft deleted” bitmap. It is then removed from the search, and all the other
endpoints.
2022-07-05 15:30:33 +02:00
Tamo
446439e8be
bump charabia 2022-07-05 12:19:30 +02:00
Dmytro Gordon
3ff03a3f5f Fix not equal filter when field contains both number and strings 2022-06-27 15:55:17 +03:00
Kerollmops
cc48992e79
Bump the milli version to 0.31.1 2022-06-22 17:05:51 +02:00
Kerollmops
238692a8e7
Introduce the copy_to_path method on the Index 2022-06-22 16:49:47 +02:00
bors[bot]
290a40b7a5
Merge #564
564: Rename the limitedTo parameter into maxTotalHits r=curquiza a=Kerollmops

This PR is related to https://github.com/meilisearch/meilisearch/issues/2542, it renames the `limitedTo` parameter into `maxTotalHits`.

Co-authored-by: Kerollmops <clement@meilisearch.com>
2022-06-22 13:48:33 +00:00
bors[bot]
d546f6f40e
Merge #563
563: Improve the `estimatedNbHits` when a `distinctAttribute` is specified r=irevoire a=Kerollmops

This PR is related to https://github.com/meilisearch/meilisearch/issues/2532 but it doesn't fix it entirely. It improves it by computing the excluded documents (the ones with an already-seen distinct value) before stopping the loop, I think it was a mistake and should always have been this way.

The reason it doesn't fix the issue is that Meilisearch is lazy, just to be sure not to compute too many things and answer by taking too much time. When we deduplicate the documents by their distinct value we must do it along the water, everytime we see a new document we check that its distinct value of it doesn't collide with an already returned document. 

The reason we can see the correct result when enough documents are fetched is that we were lucky to see all of the different distinct values possible in the dataset and all of the deduplication was done, no document can be returned.

If we wanted to implement that to have a correct `extimatedNbHits` every time we should have done a pass on the whole set of possible distinct values for the distinct attribute and do a big intersection, this could cost a lot of CPU cycles.

Co-authored-by: Kerollmops <clement@meilisearch.com>
2022-06-22 12:39:44 +00:00
Kerollmops
f5c3b951bc
Bump the milli version to 0.31.0 2022-06-22 12:08:16 +02:00
Kerollmops
d7c248042b
Rename the limitedTo parameter into maxTotalHits 2022-06-22 12:00:48 +02:00
Kerollmops
d2f84a9d9e
Improve the estimatedNbHits when distinct is enabled 2022-06-22 11:39:21 +02:00
bors[bot]
4f547eff02
Merge #560
560: Update version for next release (v0.30.0) r=curquiza a=curquiza



Co-authored-by: Clémentine Urquizar <clementine@meilisearch.com>
2022-06-20 12:37:01 +00:00
Clémentine Urquizar
31f749b5d8
Update version for next release (v0.30.0) 2022-06-20 12:09:57 +02:00
ManyTheFish
a0ab90a4d7 Avoid having an ending separator before crop marker 2022-06-16 18:23:57 +02:00
ManyTheFish
177154828c Extends deletion tests 2022-06-13 17:34:16 +02:00
ManyTheFish
0d1d354052 Ensure that Index methods are not bypassed by Meilisearch 2022-06-13 17:34:11 +02:00
bors[bot]
f1d848bb9a
Merge #552
552: Fix escaped quotes in filter r=Kerollmops a=irevoire

Will fix https://github.com/meilisearch/meilisearch/issues/2380

The issue was that in the evaluation of the filter, I was using the deref implementation instead of calling the `value` method of my token.

To avoid the problem happening again, I removed the deref implementation; now, you need to either call the `lexeme` or the `value` methods but can't rely on a « default » implementation to get a string out of a token.

Co-authored-by: Tamo <tamo@meilisearch.com>
2022-06-09 14:56:44 +00:00
Tamo
676187ba43
bump milli version 2022-06-09 16:53:32 +02:00
Tamo
90afde435b
fix escaped quotes in filter 2022-06-09 16:03:49 +02:00