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::() { //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 { 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 { let dataset = serde_json::Deserializer::from_str(CONTENT).into_iter().map(|r| r.unwrap()).collect(); let mut groups: Vec> = 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 { 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::().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, &str>>) -> HashSet { let dataset: HashSet = 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 = 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 = 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, }