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Benchmarks
==========
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## TOC
- [Run the benchmarks ](#run-the-benchmarks )
- [Comparison between benchmarks ](#comparison-between-benchmarks )
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- [Datasets ](#datasets )
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## 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).
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The name of the uploaded file is displayed in the workflow.
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_[More about critcmp](https://github.com/BurntSushi/critcmp)._
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💡 To compare the just-uploaded benchmark with another one, check out the [next section ](#comparison-between-benchmarks ).
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### On your machine
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To run all the benchmarks (~5h):
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```bash
cargo bench
```
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To run only the `search_songs` (~1h), `search_wiki` (~3h), `search_geo` (~20m) or `indexing` (~2h) benchmark:
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```bash
cargo bench --bench < dataset name >
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```
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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
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mkdir ~/datasets
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MILLI_BENCH_DATASETS_PATH=~/datasets cargo bench --bench search_songs # the four datasets are downloaded
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touch build.rs
MILLI_BENCH_DATASETS_PATH=~/datasets cargo bench --bench songs # the code is compiled again but the datasets are not downloaded
```
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## Comparison between benchmarks
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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.
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We provide a script to download and display the comparison report.
Requirements:
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- `grep`
- `curl`
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- [`critcmp` ](https://github.com/BurntSushi/critcmp )
List the available file in the DO Space:
```bash
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./benchmarks/script/list.sh
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```
```bash
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songs_main_09a4321.json
songs_geosearch_24ec456.json
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search_songs_main_cb45a10b.json
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```
Run the comparison script:
```bash
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# 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
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./benchmarks/scripts/compare.sh songs_main_09a4321.json songs_geosearch_24ec456.json
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# we compare three benchmarks
./benchmarks/scripts/compare.sh songs_main_09a4321.json songs_geosearch_24ec456.json search_songs_main_cb45a10b.json
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```
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## Datasets
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The benchmarks uses the following datasets:
- `smol-songs`
- `smol-wiki`
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- `movies`
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- `smol-all-countries`
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### Songs
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`smol-songs` is a subset of the [`songs.csv` dataset ](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/songs.csv.gz ).
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It was generated with this command:
```bash
xsv sample --seed 42 1000000 songs.csv -o smol-songs.csv
```
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_[Download the generated `smol-songs` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/smol-songs.csv.gz)._
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### Wiki
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`smol-wiki` is a subset of the [`wikipedia-articles.csv` dataset ](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/wiki-articles.csv.gz ).
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It was generated with the following command:
```bash
xsv sample --seed 42 500000 wiki-articles.csv -o smol-wiki-articles.csv
```
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_[Download the `smol-wiki` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/smol-wiki-articles.csv.gz)._
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### Movies
`movies` is a really small dataset we uses as our example in the [getting started ](https://docs.meilisearch.com/learn/getting_started/ )
_[Download the `movies` dataset](https://docs.meilisearch.com/movies.json)._
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### All Countries
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`smol-all-countries` is a subset of the [`all-countries.csv` dataset ](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/all-countries.csv.gz )
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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)._