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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>
Milli
Fuzzing milli
Currently you can only fuzz the indexation. To execute the fuzzer run:
cargo +nightly fuzz run indexing
To execute the fuzzer on multiple thread you can also run:
cargo +nightly fuzz run -j4 indexing
Since the fuzzer is going to create a lot of temporary file to let milli index its documents I would also recommand to execute it on a ramdisk. Here is how to setup a ramdisk on linux:
sudo mount -t tmpfs none path/to/your/ramdisk
And then set the TMPDIR environment variable to make the fuzzer create its file in it:
export TMPDIR=path/to/your/ramdisk