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700318dc62
357: Add benchmarks for the geosearch r=Kerollmops a=irevoire closes #336 Should I merge this PR in #322 and then we merge everything in `main` or should we wait for #322 to be merged and then merge this one in `main` later? Co-authored-by: Tamo <tamo@meilisearch.com> Co-authored-by: Irevoire <tamo@meilisearch.com>
139 lines
4.5 KiB
Markdown
139 lines
4.5 KiB
Markdown
Benchmarks
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==========
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## TOC
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- [Run the benchmarks](#run-the-benchmarks)
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- [Comparison between benchmarks](#comparison-between-benchmarks)
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- [Datasets](#datasets)
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## Run the benchmarks
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### On our private server
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The Meili team has self-hosted his own GitHub runner to run benchmarks on our dedicated bare metal server.
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To trigger the benchmark workflow:
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- Go to the `Actions` tab of this repository.
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- Select the `Benchmarks` workflow on the left.
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- Click on `Run workflow` in the blue banner.
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- Select the branch on which you want to run the benchmarks and select the dataset you want (default: `songs`).
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- Finally, click on `Run workflow`.
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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
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cargo bench
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```
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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
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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>
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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`:
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```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
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MILLI_BENCH_DATASETS_PATH=~/datasets cargo bench --bench songs # the code is compiled again but the datasets are not downloaded
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```
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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.
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Requirements:
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- `grep`
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- `curl`
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- [`critcmp`](https://github.com/BurntSushi/critcmp)
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List the available file in the DO Space:
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```bash
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./benchmarks/script/list.sh
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```
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```bash
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songs_main_09a4321.json
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songs_geosearch_24ec456.json
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search_songs_main_cb45a10b.json
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```
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Run the comparison script:
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```bash
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# we get the result of ONE benchmark, this give you an idea of how much time an operation took
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./benchmarks/scripts/compare.sh son songs_geosearch_24ec456.json
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# 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
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./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:
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- `smol-songs`
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- `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:
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```bash
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xsv sample --seed 42 1000000 songs.csv -o smol-songs.csv
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```
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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:
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```bash
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xsv sample --seed 42 500000 wiki-articles.csv -o smol-wiki-articles.csv
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```
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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
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`movies` is a really small dataset we uses as our example in the [getting started](https://docs.meilisearch.com/learn/getting_started/)
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_[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.
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It was generated with the following command:
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```bash
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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
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```
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_[Download the `smol-all-countries` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/smol-all-countries.jsonl.gz)._
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