Commit Graph

2024 Commits

Author SHA1 Message Date
Loïc Lecrenier
238a7be58d Fix filter parser handling of keywords and surrounding spaces
Now the following fragments are allowed:

AND(field =

AND'field' =

AND"field" =
2022-08-17 16:53:40 +02:00
Loïc Lecrenier
b09a8f1b91 Filters: add explicit error message when using a keyword as value 2022-08-17 16:07:00 +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
4ecfb95d0c Improve syntax errors for IN filter 2022-08-17 12:28:33 +02:00
Loïc Lecrenier
2fd20fadfc Implement the NOT IN syntax for negated 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
90a304cb07 Fix tests after simplification of NOT filter 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
5d59bfde8a Sort Cargo.toml dependencies 2022-08-17 11:46:56 +02:00
bors[bot]
f55034ed54
Merge #606
606: Make binaries faster on release profile through better compile options r=Kerollmops a=loiclec

Using `codegen-units = 1` and `lto = 'thin'` makes the compile time a bit longer, but also produces faster binaries.

I'd like to run milli's benchmark with these options, so that we can see whether it is worth enabling on meilisearch.

Co-authored-by: Loïc Lecrenier <loic@meilisearch.com>
2022-08-17 08:57:24 +00:00
Loïc Lecrenier
03e679b634 Make binaries faster on release profile through better compile options 2022-08-17 10:29:33 +02:00
Loïc Lecrenier
f20e588ec1 Make sure there is one newline at eof in cargo.toml 2022-08-17 07:44:33 +02:00
Loïc Lecrenier
20be69e1b9 Always use mimalloc as the global allocator 2022-08-16 20:09:36 +02:00
bors[bot]
293a246af8
Merge #601
601: Introduce snapshot tests r=Kerollmops a=loiclec

# Pull Request
## What does this PR do?
Introduce snapshot tests into milli, by using the `insta` crate. This implements the idea described by #597 

See: [insta.rs](https://insta.rs)

## Design
There is now a new file, `snapshot_tests.rs`, which is compiled only under `#[cfg(test)]`. It exposes the `db_snap!` macro, which is used to snapshot the content of a database.

When running `cargo test`, `insta` will check that the value of the current snapshot is the same as the previous one (on the file system). If they are the same, the test passes. If they are different, the test fails and you are asked to review the new snapshot to approve or reject it.

We don't want to save very large snapshots to the file system, because it will pollute the git repository and increase its size too much. Instead, we only save their `md5` hashes under the name `<snapshot_name>.hash.snap`. There is a new environment variable called `MILLI_TEST_FULL_SNAPS` which can be set to `true` in order to *also* save the full content of the snapshot under the name `<snapshot_name>.full.snap`. However, snapshots with the extension `.full.snap` are never saved to the git repository.

## Example
```rust
// In e.g. facets.rs
#[test]
fn my_test() {
    // create an index
    let index = TempIndex::new():
    index.add_documents(...);
    index.update_settings(|settings| ...);
    
    // then snapshot the content of one of its databases
    // the snapshot will be saved at the current folder under facets.rs/my_test/facet_id_string_docids.snap
    db_snap!(index, facet_id_string_docids);

    index.add_documents(...);   

    // we can also name the snapshot to ensure there is no conflict
    // this snapshot will be saved at facets.rs/my_test/updated/facet_id_string_docids.snap
    db_snap!(index, facet_id_string, docids, "updated");
    
    // and we can also use "inline" snapshots, which insert their content in the given string literal
    db_snap!(index, field_distributions, `@"");`
    // once the snapshot is approved, it will automatically get transformed to, e.g.:
    // db_snap!(index, field_distributions, `@"`
    // my_facet        21
    // other_field     3
    // ");
    
    // now let's add **many** documents
    index.add_documents(...);
    
    // because the snapshot is too big, its hash is saved instead
    // if the MILLI_TEST_FULL_SNAPS env variable is set to true, then the full snapshot will also be saved
    // at facets.rs/my_test/large/facet_id_string_docids.full.snap
    db_snap!(index, facet_id_string_docids, "large", `@"5348bbc46b5384455b6a900666d2a502");`
}
```

Co-authored-by: Loïc Lecrenier <loic@meilisearch.com>
2022-08-16 11:57:09 +00:00
Loïc Lecrenier
dea00311b6 Add type annotations to remove compiler error 2022-08-16 09:19:30 +02:00
Loïc Lecrenier
fb2b6c0c28 Use mimalloc for benchmarks on all platforms 2022-08-10 16:56:42 +02:00