meilisearch/milli/benches/utils.rs

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Rust
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use std::{fs::{File, create_dir_all, remove_dir_all}, time::Duration};
use heed::EnvOpenOptions;
use criterion::BenchmarkId;
use milli::{FacetCondition, Index, update::{IndexDocumentsMethod, Settings, UpdateBuilder, UpdateFormat}};
pub struct Conf<'a> {
/// where we are going to create our database.mmdb directory
/// each benchmark will first try to delete it and then recreate it
pub database_name: &'a str,
/// the dataset to be used, it must be an uncompressed csv
pub dataset: &'a str,
pub group_name: &'a str,
pub queries: &'a[&'a str],
/// here you can change which criterion are used and in which order.
/// - if you specify something all the base configuration will be thrown out
/// - if you don't specify anything (None) the default configuration will be kept
pub criterion: Option<&'a [&'a str]>,
/// the last chance to configure your database as you want
pub configure: fn(&mut Settings),
pub facet_condition: Option<FacetCondition>,
/// enable or disable the optional words on the query
pub optional_words: bool,
}
impl Conf<'_> {
fn nop(_builder: &mut Settings) {}
fn songs_conf(builder: &mut Settings) {
let displayed_fields = [
"id", "title", "album", "artist", "genre", "country", "released", "duration",
]
.iter()
.map(|s| s.to_string())
.collect();
builder.set_displayed_fields(displayed_fields);
let searchable_fields = ["title", "album", "artist"]
.iter()
.map(|s| s.to_string())
.collect();
builder.set_searchable_fields(searchable_fields);
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let faceted_fields = [
("released-timestamp", "integer"),
("duration-float", "float"),
("genre", "string"),
("country", "string"),
("artist", "string"),
]
.iter()
.map(|(a, b)| (a.to_string(), b.to_string()))
.collect();
builder.set_faceted_fields(faceted_fields);
}
pub const BASE: Self = Conf {
database_name: "benches.mmdb",
dataset: "",
group_name: "",
queries: &[],
criterion: None,
configure: Self::nop,
facet_condition: None,
optional_words: true,
};
pub const BASE_SONGS: Self = Conf {
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dataset: "smol-songs.csv",
configure: Self::songs_conf,
..Self::BASE
};
}
pub fn base_setup(conf: &Conf) -> Index {
match remove_dir_all(&conf.database_name) {
Ok(_) => (),
Err(e) if e.kind() == std::io::ErrorKind::NotFound => (),
Err(e) => panic!("{}", e),
}
create_dir_all(&conf.database_name).unwrap();
let mut options = EnvOpenOptions::new();
options.map_size(100 * 1024 * 1024 * 1024); // 100 GB
options.max_readers(10);
let index = Index::new(options, conf.database_name).unwrap();
let update_builder = UpdateBuilder::new(0);
let mut wtxn = index.write_txn().unwrap();
let mut builder = update_builder.settings(&mut wtxn, &index);
if let Some(criterion) = conf.criterion {
builder.reset_faceted_fields();
builder.reset_criteria();
builder.reset_stop_words();
let criterion = criterion.iter().map(|s| s.to_string()).collect();
builder.set_criteria(criterion);
}
(conf.configure)(&mut builder);
builder.execute(|_, _| ()).unwrap();
wtxn.commit().unwrap();
let update_builder = UpdateBuilder::new(0);
let mut wtxn = index.write_txn().unwrap();
let mut builder = update_builder.index_documents(&mut wtxn, &index);
builder.update_format(UpdateFormat::Csv);
builder.index_documents_method(IndexDocumentsMethod::ReplaceDocuments);
// we called from cargo the current directory is supposed to be milli/milli
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let dataset_path = format!("benches/{}", conf.dataset);
let reader = File::open(&dataset_path).expect(&format!("could not find the dataset in: {}", &dataset_path));
builder.execute(reader, |_, _| ()).unwrap();
wtxn.commit().unwrap();
index
}
pub fn run_benches(c: &mut criterion::Criterion, confs: &[Conf]) {
for conf in confs {
let index = base_setup(conf);
let mut group = c.benchmark_group(&format!("{}: {}", conf.dataset, conf.group_name));
group.measurement_time(Duration::from_secs(10));
for &query in conf.queries {
group.bench_with_input(BenchmarkId::from_parameter(query), &query, |b, &query| {
b.iter(|| {
let rtxn = index.read_txn().unwrap();
let mut search = index.search(&rtxn);
search.query(query).optional_words(conf.optional_words);
if let Some(facet_condition) = conf.facet_condition.clone() {
search.facet_condition(facet_condition);
}
let _ids = search.execute().unwrap();
});
});
}
group.finish();
}
}