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Add more search tests

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This commit is contained in:
Loïc Lecrenier 2023-04-04 18:02:46 +02:00
parent 62b9c6fbee
commit 959e4607bb
7 changed files with 957 additions and 2 deletions
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2
milli/src/search/new/distinct.rs
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@ -41,7 +41,7 @@ pub fn apply_distinct_rule(
}
/// Apply the distinct rule defined by [`apply_distinct_rule`] for a single document id.
fn distinct_single_docid(
pub fn distinct_single_docid(
index: &Index,
txn: &RoTxn,
field_id: u16,

4
milli/src/search/new/mod.rs
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@ -1,3 +1,4 @@
mod bucket_sort;
mod db_cache;
mod distinct;
mod graph_based_ranking_rule;
@ -31,7 +32,8 @@ pub use logger::detailed::DetailedSearchLogger;
pub use logger::{DefaultSearchLogger, SearchLogger};
use query_graph::{QueryGraph, QueryNode};
use query_term::{located_query_terms_from_string, Phrase, QueryTerm};
use ranking_rules::{bucket_sort, PlaceholderQuery, RankingRuleOutput, RankingRuleQueryTrait};
use ranking_rules::{PlaceholderQuery, RankingRuleOutput, RankingRuleQueryTrait};
use bucket_sort::bucket_sort;
use resolve_query_graph::PhraseDocIdsCache;
use roaring::RoaringBitmap;
use words::Words;

590
milli/src/search/new/tests/distinct.rs Normal file
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@ -0,0 +1,590 @@
/*!
This module tests the "distinct attribute" feature, and its
interaction with other ranking rules.
1. no duplicate distinct attributes are ever returned
2. only the best document (according to the search rules) for each distinct value appears in the result
3. if a document does not have a distinct attribute, then the distinct rule does not apply to it
It doesn't test properly:
- combination of distinct + exhaustive_nbr_hits (because we know it's incorrect)
- distinct attributes with arrays (because we know it's incorrect as well)
*/
use std::collections::HashSet;
use big_s::S;
use heed::RoTxn;
use maplit::hashset;
use crate::{
index::tests::TempIndex, AscDesc, Criterion, Index, Member, Search, SearchResult,
TermsMatchingStrategy,
};
use super::collect_field_values;
fn create_index() -> TempIndex {
let index = TempIndex::new();
index
.update_settings(|s| {
s.set_primary_key("id".to_owned());
s.set_searchable_fields(vec!["text".to_owned()]);
s.set_sortable_fields(hashset! { S("rank1"), S("letter") });
s.set_distinct_field("letter".to_owned());
s.set_criteria(vec![Criterion::Words]);
})
.unwrap();
index
.add_documents(documents!([
{
"id": 0,
"letter": "A",
"rank1": 0,
"text": "the quick brown fox jamps over the lazy dog",
},
{
"id": 1,
"letter": "A",
"rank1": 1,
"text": "the quick brown fox jumpes over the lazy dog",
},
{
"id": 2,
"letter": "B",
"rank1": 0,
"text": "the quick brown foxjumps over the lazy dog",
},
{
"id": 3,
"letter": "B",
"rank1": 1,
"text": "the quick brown fox jumps over the lazy dog",
},
{
"id": 4,
"letter": "B",
"rank1": 2,
"text": "the quick brown fox jumps over the lazy",
},
{
"id": 5,
"letter": "C",
"rank1": 0,
"text": "the quickbrownfox jumps over the lazy",
},
{
"id": 6,
"letter": "C",
"rank1": 1,
"text": "the quick brown fox jumpss over the lazy",
},
{
"id": 7,
"letter": "C",
"rank1": 2,
"text": "the quick brown fox jumps over the lazy",
},
{
"id": 8,
"letter": "D",
"rank1": 0,
"text": "the quick brown fox jumps over the lazy",
},
{
"id": 9,
"letter": "E",
"rank1": 0,
"text": "the quick brown fox jumps over the lazy",
},
{
"id": 10,
"letter": "E",
"rank1": 1,
"text": "the quackbrown foxjunps over",
},
{
"id": 11,
"letter": "E",
"rank1": 2,
"text": "the quicko browno fox junps over",
},
{
"id": 12,
"letter": "E",
"rank1": 3,
"text": "the quicko browno fox jumps over",
},
{
"id": 13,
"letter": "E",
"rank1": 4,
"text": "the quick brewn fox jumps over",
},
{
"id": 14,
"letter": "E",
"rank1": 5,
"text": "the quick brown fox jumps over",
},
{
"id": 15,
"letter": "F",
"rank1": 0,
"text": "the quick brownf fox jumps over",
},
{
"id": 16,
"letter": "F",
"rank1": 1,
"text": "the quic brown fox jamps over",
},
{
"id": 17,
"letter": "F",
"rank1": 2,
"text": "thequick browns fox jimps",
},
{
"id": 18,
"letter": "G",
"rank1": 0,
"text": "the qick brown fox jumps",
},
{
"id": 19,
"letter": "G",
"rank1": 1,
"text": "the quick brownfoxjumps",
},
{
"id": 20,
"letter": "H",
"rank1": 0,
"text": "the quick brow fox jumps",
},
{
"id": 21,
"letter": "I",
"rank1": 0,
"text": "the quick brown fox jpmps",
},
{
"id": 22,
"letter": "I",
"rank1": 1,
"text": "the quick brown fox jumps",
},
{
"id": 23,
"letter": "I",
"rank1": 2,
"text": "the quick",
},
{
"id": 24,
"rank1": 0,
"text": "the quick",
},
{
"id": 25,
"rank1": 1,
"text": "the quick brown",
},
{
"id": 26,
"rank1": 2,
"text": "the quick brown fox",
},
{
"id": 26,
"rank1": 3,
"text": "the quick brown fox jumps over the lazy dog",
},
]))
.unwrap();
index
}
fn verify_distinct(index: &Index, txn: &RoTxn, docids: &[u32]) -> Vec<String> {
let vs = collect_field_values(index, txn, index.distinct_field(txn).unwrap().unwrap(), docids);
let mut unique = HashSet::new();
for v in vs.iter() {
if v == "__does_not_exist__" {
continue;
}
assert!(unique.insert(v.clone()));
}
vs
}
#[test]
fn test_distinct_placeholder_no_ranking_rules() {
let index = create_index();
let txn = index.read_txn().unwrap();
let s = Search::new(&txn, &index);
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[0, 2, 5, 8, 9, 15, 18, 20, 21, 24, 25, 26]");
let distinct_values = verify_distinct(&index, &txn, &documents_ids);
insta::assert_debug_snapshot!(distinct_values, @r###"
[
"\"A\"",
"\"B\"",
"\"C\"",
"\"D\"",
"\"E\"",
"\"F\"",
"\"G\"",
"\"H\"",
"\"I\"",
"__does_not_exist__",
"__does_not_exist__",
"__does_not_exist__",
]
"###);
}
#[test]
fn test_distinct_placeholder_sort() {
let index = create_index();
index
.update_settings(|s| {
s.set_criteria(vec![Criterion::Sort]);
})
.unwrap();
let txn = index.read_txn().unwrap();
let mut s = Search::new(&txn, &index);
s.sort_criteria(vec![AscDesc::Desc(Member::Field(S("rank1")))]);
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[14, 26, 4, 7, 17, 23, 1, 19, 25, 8, 20, 24]");
let distinct_values = verify_distinct(&index, &txn, &documents_ids);
insta::assert_debug_snapshot!(distinct_values, @r###"
[
"\"E\"",
"__does_not_exist__",
"\"B\"",
"\"C\"",
"\"F\"",
"\"I\"",
"\"A\"",
"\"G\"",
"__does_not_exist__",
"\"D\"",
"\"H\"",
"__does_not_exist__",
]
"###);
let rank_values = collect_field_values(&index, &txn, "rank1", &documents_ids);
insta::assert_debug_snapshot!(rank_values, @r###"
[
"5",
"3",
"2",
"2",
"2",
"2",
"1",
"1",
"1",
"0",
"0",
"0",
]
"###);
let mut s = Search::new(&txn, &index);
s.sort_criteria(vec![AscDesc::Desc(Member::Field(S("letter")))]);
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[21, 20, 18, 15, 9, 8, 5, 2, 0, 24, 25, 26]");
let distinct_values = verify_distinct(&index, &txn, &documents_ids);
insta::assert_debug_snapshot!(distinct_values, @r###"
[
"\"I\"",
"\"H\"",
"\"G\"",
"\"F\"",
"\"E\"",
"\"D\"",
"\"C\"",
"\"B\"",
"\"A\"",
"__does_not_exist__",
"__does_not_exist__",
"__does_not_exist__",
]
"###);
let rank_values = collect_field_values(&index, &txn, "rank1", &documents_ids);
insta::assert_debug_snapshot!(rank_values, @r###"
[
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"1",
"3",
]
"###);
let mut s = Search::new(&txn, &index);
s.sort_criteria(vec![
AscDesc::Desc(Member::Field(S("letter"))),
AscDesc::Desc(Member::Field(S("rank1"))),
]);
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[23, 20, 19, 17, 14, 8, 7, 4, 1, 26, 25, 24]");
let distinct_values = verify_distinct(&index, &txn, &documents_ids);
insta::assert_debug_snapshot!(distinct_values, @r###"
[
"\"I\"",
"\"H\"",
"\"G\"",
"\"F\"",
"\"E\"",
"\"D\"",
"\"C\"",
"\"B\"",
"\"A\"",
"__does_not_exist__",
"__does_not_exist__",
"__does_not_exist__",
]
"###);
let rank_values = collect_field_values(&index, &txn, "rank1", &documents_ids);
insta::assert_debug_snapshot!(rank_values, @r###"
[
"2",
"0",
"1",
"2",
"5",
"0",
"2",
"2",
"1",
"3",
"1",
"0",
]
"###);
}
#[test]
fn test_distinct_words() {
let index = create_index();
index
.update_settings(|s| {
s.set_criteria(vec![Criterion::Words]);
})
.unwrap();
let txn = index.read_txn().unwrap();
let mut s = Search::new(&txn, &index);
s.terms_matching_strategy(TermsMatchingStrategy::Last);
s.query("the quick brown fox jumps over the lazy dog");
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[0, 2, 26, 5, 8, 9, 15, 18, 20, 21, 25, 24]");
let distinct_values = verify_distinct(&index, &txn, &documents_ids);
insta::assert_debug_snapshot!(distinct_values, @r###"
[
"\"A\"",
"\"B\"",
"__does_not_exist__",
"\"C\"",
"\"D\"",
"\"E\"",
"\"F\"",
"\"G\"",
"\"H\"",
"\"I\"",
"__does_not_exist__",
"__does_not_exist__",
]
"###);
let text_values = collect_field_values(&index, &txn, "text", &documents_ids);
insta::assert_debug_snapshot!(text_values, @r###"
[
"\"the quick brown fox jamps over the lazy dog\"",
"\"the quick brown foxjumps over the lazy dog\"",
"\"the quick brown fox jumps over the lazy dog\"",
"\"the quickbrownfox jumps over the lazy\"",
"\"the quick brown fox jumps over the lazy\"",
"\"the quick brown fox jumps over the lazy\"",
"\"the quick brownf fox jumps over\"",
"\"the qick brown fox jumps\"",
"\"the quick brow fox jumps\"",
"\"the quick brown fox jpmps\"",
"\"the quick brown\"",
"\"the quick\"",
]
"###);
}
#[test]
fn test_distinct_sort_words() {
let index = create_index();
index
.update_settings(|s| {
s.set_criteria(vec![Criterion::Sort, Criterion::Words, Criterion::Desc(S("rank1"))]);
})
.unwrap();
let txn = index.read_txn().unwrap();
let mut s = Search::new(&txn, &index);
s.terms_matching_strategy(TermsMatchingStrategy::Last);
s.query("the quick brown fox jumps over the lazy dog");
s.sort_criteria(vec![AscDesc::Desc(Member::Field(S("letter")))]);
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[22, 20, 19, 16, 9, 8, 7, 3, 1, 26, 25, 24]");
let distinct_values = verify_distinct(&index, &txn, &documents_ids);
insta::assert_debug_snapshot!(distinct_values, @r###"
[
"\"I\"",
"\"H\"",
"\"G\"",
"\"F\"",
"\"E\"",
"\"D\"",
"\"C\"",
"\"B\"",
"\"A\"",
"__does_not_exist__",
"__does_not_exist__",
"__does_not_exist__",
]
"###);
let rank_values = collect_field_values(&index, &txn, "rank1", &documents_ids);
insta::assert_debug_snapshot!(rank_values, @r###"
[
"1",
"0",
"1",
"1",
"0",
"0",
"2",
"1",
"1",
"3",
"1",
"0",
]
"###);
let text_values = collect_field_values(&index, &txn, "text", &documents_ids);
insta::assert_debug_snapshot!(text_values, @r###"
[
"\"the quick brown fox jumps\"",
"\"the quick brow fox jumps\"",
"\"the quick brownfoxjumps\"",
"\"the quic brown fox jamps over\"",
"\"the quick brown fox jumps over the lazy\"",
"\"the quick brown fox jumps over the lazy\"",
"\"the quick brown fox jumps over the lazy\"",
"\"the quick brown fox jumps over the lazy dog\"",
"\"the quick brown fox jumpes over the lazy dog\"",
"\"the quick brown fox jumps over the lazy dog\"",
"\"the quick brown\"",
"\"the quick\"",
]
"###);
}
#[test]
fn test_distinct_all_candidates() {
let index = create_index();
index
.update_settings(|s| {
s.set_criteria(vec![Criterion::Sort]);
})
.unwrap();
let txn = index.read_txn().unwrap();
let mut s = Search::new(&txn, &index);
s.terms_matching_strategy(TermsMatchingStrategy::Last);
s.sort_criteria(vec![AscDesc::Desc(Member::Field(S("rank1")))]);
s.exhaustive_number_hits(true);
let SearchResult { documents_ids, candidates, .. } = s.execute().unwrap();
let candidates = candidates.iter().collect::<Vec<_>>();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[14, 26, 4, 7, 17, 23, 1, 19, 25, 8, 20, 24]");
// TODO: this is incorrect!
insta::assert_snapshot!(format!("{candidates:?}"), @"[0, 2, 5, 8, 9, 15, 18, 20, 21, 24, 25, 26]");
}
#[test]
fn test_distinct_typo() {
let index = create_index();
index
.update_settings(|s| {
s.set_criteria(vec![Criterion::Words, Criterion::Typo]);
})
.unwrap();
let txn = index.read_txn().unwrap();
let mut s = Search::new(&txn, &index);
s.query("the quick brown fox jumps over the lazy dog");
s.terms_matching_strategy(TermsMatchingStrategy::Last);
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[3, 26, 0, 7, 8, 9, 15, 22, 18, 20, 25, 24]");
let distinct_values = verify_distinct(&index, &txn, &documents_ids);
insta::assert_debug_snapshot!(distinct_values, @r###"
[
"\"B\"",
"__does_not_exist__",
"\"A\"",
"\"C\"",
"\"D\"",
"\"E\"",
"\"F\"",
"\"I\"",
"\"G\"",
"\"H\"",
"__does_not_exist__",
"__does_not_exist__",
]
"###);
let text_values = collect_field_values(&index, &txn, "text", &documents_ids);
insta::assert_debug_snapshot!(text_values, @r###"
[
"\"the quick brown fox jumps over the lazy dog\"",
"\"the quick brown fox jumps over the lazy dog\"",
"\"the quick brown fox jamps over the lazy dog\"",
"\"the quick brown fox jumps over the lazy\"",
"\"the quick brown fox jumps over the lazy\"",
"\"the quick brown fox jumps over the lazy\"",
"\"the quick brownf fox jumps over\"",
"\"the quick brown fox jumps\"",
"\"the qick brown fox jumps\"",
"\"the quick brow fox jumps\"",
"\"the quick brown\"",
"\"the quick\"",
]
"###);
}

22
milli/src/search/new/tests/language.rs Normal file
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@ -0,0 +1,22 @@
use crate::{index::tests::TempIndex, Search, SearchResult};
#[test]
fn test_kanji_language_detection() {
let index = TempIndex::new();
index
.add_documents(documents!([
{ "id": 0, "title": "The quick (\"brown\") fox can't jump 32.3 feet, right? Brr, it's 29.3°F!" },
{ "id": 1, "title": "東京のお寿司。" },
{ "id": 2, "title": "הַשּׁוּעָל הַמָּהִיר (״הַחוּם״) לֹא יָכוֹל לִקְפֹּץ 9.94 מֶטְרִים, נָכוֹן? ברר, 1.5°C- בַּחוּץ!" }
]))
.unwrap();
let txn = index.write_txn().unwrap();
let mut search = Search::new(&txn, &index);
search.query("東京");
let SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![1]);
}

25
milli/src/search/new/tests/mod.rs
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@ -1,3 +1,28 @@
pub mod distinct;
#[cfg(feature = "default")]
pub mod language;
pub mod ngram_split_words;
pub mod proximity;
pub mod sort;
pub mod typo;
pub mod words_tms;
fn collect_field_values(
index: &crate::Index,
txn: &heed::RoTxn,
fid: &str,
docids: &[u32],
) -> Vec<String> {
let mut values = vec![];
let fid = index.fields_ids_map(txn).unwrap().id(fid).unwrap();
for doc in index.documents(txn, docids.iter().copied()).unwrap() {
if let Some(v) = doc.1.get(fid) {
let v: serde_json::Value = serde_json::from_slice(v).unwrap();
let v = v.to_string();
values.push(v);
} else {
values.push("__does_not_exist__".to_owned());
}
}
values
}

0
milli/src/search/new/tests/proximity.rs Normal file
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316
milli/src/search/new/tests/sort.rs Normal file
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@ -0,0 +1,316 @@
/*!
This module tests the `sort` ranking rule:
1. an error is returned if the sort ranking rule exists but no fields-to-sort were given at search time
2. an error is returned if the fields-to-sort are not sortable
3. it is possible to add multiple fields-to-sort at search time
4. custom sort ranking rules can be added to the settings, they interact with the generic `sort` ranking rule as expected
5. numbers appear before strings
6. documents with either: (1) no value, (2) null, or (3) an object for the field-to-sort appear at the end of the bucket
7. boolean values are translated to strings
8. if a field contains an array, it is sorted by the best value in the array according to the sort rule
*/
use big_s::S;
use maplit::hashset;
use crate::{
index::tests::TempIndex, search::new::tests::collect_field_values, AscDesc, Criterion, Member,
Search, SearchResult, TermsMatchingStrategy,
};
fn create_index() -> TempIndex {
let index = TempIndex::new();
index
.update_settings(|s| {
s.set_primary_key("id".to_owned());
s.set_searchable_fields(vec!["text".to_owned()]);
s.set_sortable_fields(hashset! { S("rank"), S("vague"), S("letter") });
s.set_criteria(vec![Criterion::Sort]);
})
.unwrap();
index
.add_documents(documents!([
{
"id": 0,
"letter": "A",
"rank": 0,
"vague": 0,
},
{
"id": 1,
"letter": "A",
"rank": 1,
"vague": "0",
},
{
"id": 2,
"letter": "B",
"rank": 0,
"vague": 1,
},
{
"id": 3,
"letter": "B",
"rank": 1,
"vague": "1",
},
{
"id": 4,
"letter": "B",
"rank": 2,
"vague": [1, 2],
},
{
"id": 5,
"letter": "C",
"rank": 0,
"vague": [1, "2"],
},
{
"id": 6,
"letter": "C",
"rank": 1,
},
{
"id": 7,
"letter": "C",
"rank": 2,
"vague": null,
},
{
"id": 8,
"letter": "D",
"rank": 0,
"vague": [null, null, ""]
},
{
"id": 9,
"letter": "E",
"rank": 0,
"vague": ""
},
{
"id": 10,
"letter": "E",
"rank": 1,
"vague": {
"sub": 0,
}
},
{
"id": 11,
"letter": "E",
"rank": 2,
"vague": true,
},
{
"id": 12,
"letter": "E",
"rank": 3,
"vague": false,
},
{
"id": 13,
"letter": "E",
"rank": 4,
"vague": 1.5673,
},
{
"id": 14,
"letter": "E",
"rank": 5,
},
{
"id": 15,
"letter": "F",
"rank": 0,
},
{
"id": 16,
"letter": "F",
"rank": 1,
},
{
"id": 17,
"letter": "F",
"rank": 2,
},
{
"id": 18,
"letter": "G",
"rank": 0,
},
{
"id": 19,
"letter": "G",
"rank": 1,
},
{
"id": 20,
"letter": "H",
"rank": 0,
"vague": true,
},
{
"id": 21,
"letter": "I",
"rank": 0,
"vague": false,
},
{
"id": 22,
"letter": "I",
"rank": 1,
"vague": [1.1367, "help", null]
},
{
"id": 23,
"letter": "I",
"rank": 2,
"vague": [1.2367, "hello"]
},
]))
.unwrap();
index
}
#[test]
fn test_sort() {
let index = create_index();
let txn = index.read_txn().unwrap();
let mut s = Search::new(&txn, &index);
s.terms_matching_strategy(TermsMatchingStrategy::Last);
s.sort_criteria(vec![AscDesc::Desc(Member::Field(S("letter")))]);
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[21, 22, 23, 20, 18, 19, 15, 16, 17, 9, 10, 11, 12, 13, 14, 8, 5, 6, 7, 2]");
let letter_values = collect_field_values(&index, &txn, "letter", &documents_ids);
insta::assert_debug_snapshot!(letter_values, @r###"
[
"\"I\"",
"\"I\"",
"\"I\"",
"\"H\"",
"\"G\"",
"\"G\"",
"\"F\"",
"\"F\"",
"\"F\"",
"\"E\"",
"\"E\"",
"\"E\"",
"\"E\"",
"\"E\"",
"\"E\"",
"\"D\"",
"\"C\"",
"\"C\"",
"\"C\"",
"\"B\"",
]
"###);
let mut s = Search::new(&txn, &index);
s.terms_matching_strategy(TermsMatchingStrategy::Last);
s.sort_criteria(vec![AscDesc::Desc(Member::Field(S("rank")))]);
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[14, 13, 12, 4, 7, 11, 17, 23, 1, 3, 6, 10, 16, 19, 22, 0, 2, 5, 8, 9]");
let rank_values = collect_field_values(&index, &txn, "rank", &documents_ids);
insta::assert_debug_snapshot!(rank_values, @r###"
[
"5",
"4",
"3",
"2",
"2",
"2",
"2",
"2",
"1",
"1",
"1",
"1",
"1",
"1",
"1",
"0",
"0",
"0",
"0",
"0",
]
"###);
let mut s = Search::new(&txn, &index);
s.terms_matching_strategy(TermsMatchingStrategy::Last);
s.sort_criteria(vec![AscDesc::Asc(Member::Field(S("vague")))]);
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[0, 2, 4, 5, 22, 23, 13, 1, 3, 12, 21, 11, 20, 6, 7, 8, 9, 10, 14, 15]");
let vague_values = collect_field_values(&index, &txn, "vague", &documents_ids);
insta::assert_debug_snapshot!(vague_values, @r###"
[
"0",
"1",
"[1,2]",
"[1,\"2\"]",
"[1.1367,\"help\",null]",
"[1.2367,\"hello\"]",
"1.5673",
"\"0\"",
"\"1\"",
"false",
"false",
"true",
"true",
"__does_not_exist___",
"null",
"[null,null,\"\"]",
"\"\"",
"{\"sub\":0}",
"__does_not_exist___",
"__does_not_exist___",
]
"###);
let mut s = Search::new(&txn, &index);
s.terms_matching_strategy(TermsMatchingStrategy::Last);
s.sort_criteria(vec![AscDesc::Desc(Member::Field(S("vague")))]);
let SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[4, 13, 23, 22, 2, 5, 0, 11, 20, 12, 21, 3, 1, 6, 7, 8, 9, 10, 14, 15]");
let vague_values = collect_field_values(&index, &txn, "vague", &documents_ids);
insta::assert_debug_snapshot!(vague_values, @r###"
[
"[1,2]",
"1.5673",
"[1.2367,\"hello\"]",
"[1.1367,\"help\",null]",
"1",
"[1,\"2\"]",
"0",
"true",
"true",
"false",
"false",
"\"1\"",
"\"0\"",
"__does_not_exist___",
"null",
"[null,null,\"\"]",
"\"\"",
"{\"sub\":0}",
"__does_not_exist___",
"__does_not_exist___",
]
"###);
}