MeiliSearch/milli/tests/search/mod.rs
2021-10-25 10:26:42 +02:00

232 lines
8.7 KiB
Rust

use std::cmp::Reverse;
use std::collections::HashSet;
use std::io::Cursor;
use big_s::S;
use either::{Either, Left, Right};
use heed::EnvOpenOptions;
use maplit::{hashmap, hashset};
use milli::documents::{DocumentBatchBuilder, DocumentBatchReader};
use milli::update::{Settings, UpdateBuilder};
use milli::{AscDesc, Criterion, DocumentId, Index, Member};
use serde::Deserialize;
use slice_group_by::GroupBy;
mod distinct;
mod filters;
mod query_criteria;
mod sort;
pub const TEST_QUERY: &'static str = "hello world america";
pub const EXTERNAL_DOCUMENTS_IDS: &[&str; 17] =
&["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q"];
pub const CONTENT: &str = include_str!("../assets/test_set.ndjson");
pub fn setup_search_index_with_criteria(criteria: &[Criterion]) -> Index {
let path = tempfile::tempdir().unwrap();
let mut options = EnvOpenOptions::new();
options.map_size(10 * 1024 * 1024); // 10 MB
let index = Index::new(options, &path).unwrap();
let mut wtxn = index.write_txn().unwrap();
let mut builder = Settings::new(&mut wtxn, &index, 0);
let criteria = criteria.iter().map(|c| c.to_string()).collect();
builder.set_criteria(criteria);
builder.set_filterable_fields(hashset! {
S("tag"),
S("asc_desc_rank"),
S("_geo"),
});
builder.set_sortable_fields(hashset! {
S("tag"),
S("asc_desc_rank"),
});
builder.set_synonyms(hashmap! {
S("hello") => vec![S("good morning")],
S("world") => vec![S("earth")],
S("america") => vec![S("the united states")],
});
builder.set_searchable_fields(vec![S("title"), S("description")]);
builder.execute(|_, _| ()).unwrap();
// index documents
let mut builder = UpdateBuilder::new(0);
builder.max_memory(10 * 1024 * 1024); // 10MiB
let mut builder = builder.index_documents(&mut wtxn, &index);
builder.enable_autogenerate_docids();
let mut cursor = Cursor::new(Vec::new());
let mut documents_builder = DocumentBatchBuilder::new(&mut cursor).unwrap();
let reader = Cursor::new(CONTENT.as_bytes());
todo!();
//for doc in serde_json::Deserializer::from_reader(reader).into_iter::<serde_json::Value>() {
//documents_builder.add_documents(doc.unwrap()).unwrap();
//}
documents_builder.finish().unwrap();
cursor.set_position(0);
// index documents
let content = DocumentBatchReader::from_reader(cursor).unwrap();
builder.execute(content, |_, _| ()).unwrap();
wtxn.commit().unwrap();
index
}
pub fn internal_to_external_ids(index: &Index, internal_ids: &[DocumentId]) -> Vec<String> {
let mut rtxn = index.read_txn().unwrap();
let docid_map = index.external_documents_ids(&mut rtxn).unwrap();
let docid_map: std::collections::HashMap<_, _> =
EXTERNAL_DOCUMENTS_IDS.iter().map(|id| (docid_map.get(id).unwrap(), id)).collect();
internal_ids.iter().map(|id| docid_map.get(id).unwrap().to_string()).collect()
}
pub fn expected_order(
criteria: &[Criterion],
authorize_typo: bool,
optional_words: bool,
sort_by: &[AscDesc],
) -> Vec<TestDocument> {
let dataset =
serde_json::Deserializer::from_str(CONTENT).into_iter().map(|r| r.unwrap()).collect();
let mut groups: Vec<Vec<TestDocument>> = vec![dataset];
for criterion in criteria {
let mut new_groups = Vec::new();
for group in groups.iter_mut() {
match criterion {
Criterion::Attribute => {
group.sort_by_key(|d| d.attribute_rank);
new_groups
.extend(group.linear_group_by_key(|d| d.attribute_rank).map(Vec::from));
}
Criterion::Exactness => {
group.sort_by_key(|d| d.exact_rank);
new_groups.extend(group.linear_group_by_key(|d| d.exact_rank).map(Vec::from));
}
Criterion::Proximity => {
group.sort_by_key(|d| d.proximity_rank);
new_groups
.extend(group.linear_group_by_key(|d| d.proximity_rank).map(Vec::from));
}
Criterion::Sort if sort_by == [AscDesc::Asc(Member::Field(S("tag")))] => {
group.sort_by_key(|d| d.sort_by_rank);
new_groups.extend(group.linear_group_by_key(|d| d.sort_by_rank).map(Vec::from));
}
Criterion::Sort if sort_by == [AscDesc::Desc(Member::Field(S("tag")))] => {
group.sort_by_key(|d| Reverse(d.sort_by_rank));
new_groups.extend(group.linear_group_by_key(|d| d.sort_by_rank).map(Vec::from));
}
Criterion::Typo => {
group.sort_by_key(|d| d.typo_rank);
new_groups.extend(group.linear_group_by_key(|d| d.typo_rank).map(Vec::from));
}
Criterion::Words => {
group.sort_by_key(|d| d.word_rank);
new_groups.extend(group.linear_group_by_key(|d| d.word_rank).map(Vec::from));
}
Criterion::Asc(field_name) if field_name == "asc_desc_rank" => {
group.sort_by_key(|d| d.asc_desc_rank);
new_groups
.extend(group.linear_group_by_key(|d| d.asc_desc_rank).map(Vec::from));
}
Criterion::Desc(field_name) if field_name == "asc_desc_rank" => {
group.sort_by_key(|d| Reverse(d.asc_desc_rank));
new_groups
.extend(group.linear_group_by_key(|d| d.asc_desc_rank).map(Vec::from));
}
Criterion::Asc(_) | Criterion::Desc(_) | Criterion::Sort => {
new_groups.push(group.clone())
}
}
}
groups = std::mem::take(&mut new_groups);
}
if authorize_typo && optional_words {
groups.into_iter().flatten().collect()
} else if optional_words {
groups.into_iter().flatten().filter(|d| d.typo_rank == 0).collect()
} else if authorize_typo {
groups.into_iter().flatten().filter(|d| d.word_rank == 0).collect()
} else {
groups.into_iter().flatten().filter(|d| d.word_rank == 0 && d.typo_rank == 0).collect()
}
}
fn execute_filter(filter: &str, document: &TestDocument) -> Option<String> {
let mut id = None;
if let Some((field, filter)) = filter.split_once("=") {
if field == "tag" && document.tag == filter {
id = Some(document.id.clone())
} else if field == "asc_desc_rank"
&& document.asc_desc_rank == filter.parse::<u32>().unwrap()
{
id = Some(document.id.clone())
}
} else if let Some(("asc_desc_rank", filter)) = filter.split_once("<") {
if document.asc_desc_rank < filter.parse().unwrap() {
id = Some(document.id.clone())
}
} else if let Some(("asc_desc_rank", filter)) = filter.split_once(">") {
if document.asc_desc_rank > filter.parse().unwrap() {
id = Some(document.id.clone())
}
} else if filter.starts_with("_geoRadius") {
id = (document.geo_rank < 100000).then(|| document.id.clone());
} else if filter.starts_with("NOT _geoRadius") {
id = (document.geo_rank > 1000000).then(|| document.id.clone());
}
id
}
pub fn expected_filtered_ids(filters: Vec<Either<Vec<&str>, &str>>) -> HashSet<String> {
let dataset: HashSet<TestDocument> =
serde_json::Deserializer::from_str(CONTENT).into_iter().map(|r| r.unwrap()).collect();
let mut filtered_ids: HashSet<_> = dataset.iter().map(|d| d.id.clone()).collect();
for either in filters {
let ids = match either {
Left(array) => array
.into_iter()
.map(|f| {
let ids: HashSet<String> =
dataset.iter().filter_map(|d| execute_filter(f, d)).collect();
ids
})
.reduce(|a, b| a.union(&b).cloned().collect())
.unwrap(),
Right(filter) => {
let ids: HashSet<String> =
dataset.iter().filter_map(|d| execute_filter(filter, d)).collect();
ids
}
};
filtered_ids = filtered_ids.intersection(&ids).cloned().collect();
}
filtered_ids
}
#[derive(Debug, Clone, Deserialize, PartialEq, Eq, Hash)]
pub struct TestDocument {
pub id: String,
pub word_rank: u32,
pub typo_rank: u32,
pub proximity_rank: u32,
pub attribute_rank: u32,
pub exact_rank: u32,
pub asc_desc_rank: u32,
pub sort_by_rank: u32,
pub geo_rank: u32,
pub title: String,
pub description: String,
pub tag: String,
}