Benchmarks ========== ## TOC - [Run the benchmarks](#run-the-benchmarks) - [Comparison between benchmarks](#comparison-between-benchmarks) - [Datasets](#datasets) ## Run the benchmarks ### On our private server The Meili team has self-hosted his own GitHub runner to run benchmarks on our dedicated bare metal server. To trigger the benchmark workflow: - Go to the `Actions` tab of this repository. - Select the `Benchmarks` workflow on the left. - Click on `Run workflow` in the blue banner. - Select the branch on which you want to run the benchmarks and select the dataset you want (default: `songs`). - Finally, click on `Run workflow`. This GitHub workflow will run the benchmarks and push the `critcmp` report to a DigitalOcean Space (= S3). The name of the uploaded file is displayed in the workflow. _[More about critcmp](https://github.com/BurntSushi/critcmp)._ 💡 To compare the just-uploaded benchmark with another one, check out the [next section](#comparison-between-benchmarks). ### On your machine To run all the benchmarks (~5h): ```bash cargo bench ``` To run only the `search_songs` (~1h), `search_wiki` (~3h), `search_geo` (~20m) or `indexing` (~2h) benchmark: ```bash cargo bench --bench <dataset name> ``` By default, the benchmarks will be downloaded and uncompressed automatically in the target directory.<br> If you don't want to download the datasets every time you update something on the code, you can specify a custom directory with the environment variable `MILLI_BENCH_DATASETS_PATH`: ```bash mkdir ~/datasets MILLI_BENCH_DATASETS_PATH=~/datasets cargo bench --bench search_songs # the four datasets are downloaded touch build.rs MILLI_BENCH_DATASETS_PATH=~/datasets cargo bench --bench songs # the code is compiled again but the datasets are not downloaded ``` ## Comparison between benchmarks The benchmark reports we push are generated with `critcmp`. Thus, we use `critcmp` to show the result of a benchmark, or compare results between multiple benchmarks. We provide a script to download and display the comparison report. Requirements: - `grep` - `curl` - [`critcmp`](https://github.com/BurntSushi/critcmp) List the available file in the DO Space: ```bash ./benchmarks/script/list.sh ``` ```bash songs_main_09a4321.json songs_geosearch_24ec456.json search_songs_main_cb45a10b.json ``` Run the comparison script: ```bash # we get the result of ONE benchmark, this give you an idea of how much time an operation took ./benchmarks/scripts/compare.sh son songs_geosearch_24ec456.json # we compare two benchmarks ./benchmarks/scripts/compare.sh songs_main_09a4321.json songs_geosearch_24ec456.json # we compare three benchmarks ./benchmarks/scripts/compare.sh songs_main_09a4321.json songs_geosearch_24ec456.json search_songs_main_cb45a10b.json ``` ## Datasets The benchmarks uses the following datasets: - `smol-songs` - `smol-wiki` - `movies` - `smol-all-countries` ### Songs `smol-songs` is a subset of the [`songs.csv` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/songs.csv.gz). It was generated with this command: ```bash xsv sample --seed 42 1000000 songs.csv -o smol-songs.csv ``` _[Download the generated `smol-songs` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/smol-songs.csv.gz)._ ### Wiki `smol-wiki` is a subset of the [`wikipedia-articles.csv` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/wiki-articles.csv.gz). It was generated with the following command: ```bash xsv sample --seed 42 500000 wiki-articles.csv -o smol-wiki-articles.csv ``` _[Download the `smol-wiki` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/smol-wiki-articles.csv.gz)._ ### Movies `movies` is a really small dataset we uses as our example in the [getting started](https://www.meilisearch.com/docs/learn/getting_started/quick_start) _[Download the `movies` dataset](https://www.meilisearch.com/movies.json)._ ### All Countries `smol-all-countries` is a subset of the [`all-countries.csv` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/all-countries.csv.gz) It has been converted to jsonlines and then edited so it matches our format for the `_geo` field. It was generated with the following command: ```bash bat all-countries.csv.gz | gunzip | xsv sample --seed 42 1000000 | csv2json-lite | sd '"latitude":"(.*?)","longitude":"(.*?)"' '"_geo": { "lat": $1, "lng": $2 }' | sd '\[|\]|,$' '' | gzip > smol-all-countries.jsonl.gz ``` _[Download the `smol-all-countries` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/smol-all-countries.jsonl.gz)._