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>
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>
600: Simplify some unit tests r=ManyTheFish a=loiclec
# Pull Request
## What does this PR do?
Simplify the code that is used in unit tests to create and modify an index. Basically, the following code:
```rust
let path = tempfile::tempdir().unwrap();
let mut options = EnvOpenOptions::new();
options.map_size(10 * 1024 * 1024); // 10 MB
let index = Index::new(options, &path).unwrap();
let mut wtxn = index.write_txn().unwrap();
let content = documents!([
{ "id": 0, "name": "kevin" },
]);
let config = IndexerConfig::default();
let indexing_config = IndexDocumentsConfig::default();
let builder =
IndexDocuments::new(&mut wtxn, &index, &config, indexing_config, |_| ()).unwrap();
let (builder, user_error) = builder.add_documents(content).unwrap();
user_error.unwrap();
builder.execute().unwrap();
wtxn.commit.unwrap();
let mut wtxn = index.write_txn().unwrap();
let config = IndexerConfig::default();
let mut builder = Settings::new(&mut wtxn, &index, &config);
builder.set_primary_key(S("docid"));
builder.set_filterable_fields(hashset! { S("label") });
builder.execute(|_| ()).unwrap();
wtxn.commit().unwrap();
```
becomes:
```rust
let index = TempIndex::new():
index.add_documents(documents!(
{ "id": 0, "name": "kevin" },
)).unwrap();
index.update_settings(|settings| {
settings.set_primary_key(S("docid"));
settings.set_filterable_fields(hashset! { S("label") });
}).unwrap();
```
Then there is a bunch of options to modify the indexing configs, the map size, to reuse a transaction, etc. For example:
```rust
let mut index = TempIndex::new_with_map_size(1000 * 4096 * 10);
index.index_documents_config.autogenerate_docids = true;
let mut wtxn = index.write_txn().unwrap();
index.update_settings_using_wtxn(&mut wtxn, |settings| {
settings.set_primary_key(S("docids"));
}).unwrap();
wtxn.commit().unwrap();
```
Co-authored-by: Loïc Lecrenier <loic@meilisearch.com>
Co-authored-by: Loïc Lecrenier <loic.lecrenier@me.com>
Co-authored-by: bors[bot] <26634292+bors[bot]@users.noreply.github.com>
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>
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".
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>
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.
