mirror of
https://github.com/meilisearch/meilisearch.git
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212: Introduce integration test on criteria r=Kerollmops a=ManyTheFish - add pre-ranked dataset - test each criterion 1 by 1 - test all criteria in several order 222: Move the `UpdateStore` into the http-ui crate r=Kerollmops a=Kerollmops We no more need to have the `UpdateStore` inside of the mill crate as this is the job of the caller to stack the updates and sequentially give them to milli. 223: Update dataset links r=Kerollmops a=curquiza Co-authored-by: many <maxime@meilisearch.com> Co-authored-by: Many <legendre.maxime.isn@gmail.com> Co-authored-by: Kerollmops <clement@meilisearch.com> Co-authored-by: Clémentine Urquizar <clementine@meilisearch.com>
This commit is contained in:
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commit
afb4133bd2
2
Cargo.lock
generated
2
Cargo.lock
generated
@ -961,6 +961,7 @@ dependencies = [
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"askama_warp",
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"byte-unit",
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"bytes 0.5.6",
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"crossbeam-channel",
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"either",
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"flate2",
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"fst",
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@ -1365,7 +1366,6 @@ dependencies = [
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"bstr",
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"byteorder",
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"chrono",
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"crossbeam-channel",
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"csv",
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"either",
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"flate2",
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@ -87,7 +87,7 @@ The benchmarks are available for the following datasets:
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### Songs
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`songs` is a subset of the [`songs.csv` dataset](https://meili-datasets.s3.fr-par.scw.cloud/songs.csv.gz).
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`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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@ -95,11 +95,11 @@ It was generated with this command:
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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 `songs` dataset](https://meili-datasets.s3.fr-par.scw.cloud/benchmarks/smol-songs.csv.gz)._
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_[Download the generated `songs` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/smol-songs.csv.gz)._
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### Wiki
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`wiki` is a subset of the [`wikipedia-articles.csv` dataset](https://meili-datasets.s3.fr-par.scw.cloud/wiki-articles.csv.gz).
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`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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@ -107,5 +107,5 @@ It was generated with the following command:
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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 generated `wiki` dataset](https://meili-datasets.s3.fr-par.scw.cloud/benchmarks/smol-wiki-articles.csv.gz)._
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_[Download the generated `wiki` dataset](https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets/smol-wiki-articles.csv.gz)._
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@ -10,7 +10,7 @@ use convert_case::{Case, Casing};
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use flate2::read::GzDecoder;
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use reqwest::IntoUrl;
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const BASE_URL: &str = "https://meili-datasets.s3.fr-par.scw.cloud/benchmarks";
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const BASE_URL: &str = "https://milli-benchmarks.fra1.digitaloceanspaces.com/datasets";
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const DATASET_SONGS: &str = "smol-songs";
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const DATASET_WIKI: &str = "smol-wiki-articles";
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@ -8,6 +8,7 @@ edition = "2018"
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[dependencies]
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anyhow = "1.0.38"
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byte-unit = { version = "4.0.9", default-features = false, features = ["std"] }
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crossbeam-channel = "0.5.0"
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grenad = { git = "https://github.com/Kerollmops/grenad.git", rev = "3adcb26" }
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heed = "0.10.6"
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meilisearch-tokenizer = { git = "https://github.com/meilisearch/Tokenizer.git", tag = "v0.2.2" }
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@ -1,3 +1,5 @@
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mod update_store;
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use std::{io, mem};
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use std::collections::{BTreeMap, BTreeSet, HashMap, HashSet};
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use std::fmt::Display;
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@ -29,10 +31,12 @@ use tokio::sync::broadcast;
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use warp::{Filter, http::Response};
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use warp::filters::ws::Message;
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use milli::{FilterCondition, Index, MatchingWords, obkv_to_json, SearchResult, UpdateStore};
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use milli::{FilterCondition, Index, MatchingWords, obkv_to_json, SearchResult};
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use milli::update::{IndexDocumentsMethod, Setting, UpdateBuilder, UpdateFormat};
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use milli::update::UpdateIndexingStep::*;
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use self::update_store::UpdateStore;
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static GLOBAL_THREAD_POOL: OnceCell<ThreadPool> = OnceCell::new();
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#[derive(Debug, StructOpt)]
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@ -1,3 +1,5 @@
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#![allow(unused)]
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use std::path::Path;
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use std::sync::Arc;
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@ -6,7 +8,7 @@ use heed::types::{OwnedType, DecodeIgnore, SerdeJson, ByteSlice};
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use heed::{EnvOpenOptions, Env, Database};
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use serde::{Serialize, Deserialize};
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use crate::BEU64;
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pub type BEU64 = heed::zerocopy::U64<heed::byteorder::BE>;
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#[derive(Clone)]
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pub struct UpdateStore<M, N> {
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@ -9,7 +9,6 @@ anyhow = "1.0.38"
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bstr = "0.2.15"
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byteorder = "1.4.2"
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chrono = { version = "0.4.19", features = ["serde"] }
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crossbeam-channel = "0.5.0"
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csv = "1.1.5"
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either = "1.6.1"
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flate2 = "1.0.20"
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@ -4,7 +4,6 @@ mod criterion;
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mod external_documents_ids;
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mod fields_ids_map;
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mod search;
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mod update_store;
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pub mod facet;
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pub mod heed_codec;
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pub mod index;
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@ -29,7 +28,6 @@ pub use self::heed_codec::{RoaringBitmapLenCodec, BoRoaringBitmapLenCodec, CboRo
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pub use self::index::Index;
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pub use self::search::{Search, FacetDistribution, FilterCondition, SearchResult, MatchingWords};
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pub use self::tree_level::TreeLevel;
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pub use self::update_store::UpdateStore;
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pub type FastMap4<K, V> = HashMap<K, V, BuildHasherDefault<FxHasher32>>;
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pub type FastMap8<K, V> = HashMap<K, V, BuildHasherDefault<FxHasher64>>;
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17
milli/tests/assets/test_set.ndjson
Normal file
17
milli/tests/assets/test_set.ndjson
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@ -0,0 +1,17 @@
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{"id":"A","word_rank":0,"typo_rank":1,"proximity_rank":15,"attribute_rank":505,"exact_rank":5,"asc_desc_rank":0,"title":"hell o","description":"hell o is the fourteenth episode of the american television series glee performing songs with this word","tag":"blue","":""}
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{"id":"B","word_rank":2,"typo_rank":0,"proximity_rank":0,"attribute_rank":0,"exact_rank":4,"asc_desc_rank":1,"title":"hello","description":"hello is a song recorded by english singer songwriter adele","tag":"red","":""}
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{"id":"C","word_rank":0,"typo_rank":1,"proximity_rank":8,"attribute_rank":336,"exact_rank":4,"asc_desc_rank":2,"title":"hell on earth","description":"hell on earth is the third studio album by american hip hop duo mobb deep","tag":"blue","":""}
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{"id":"D","word_rank":0,"typo_rank":1,"proximity_rank":10,"attribute_rank":757,"exact_rank":4,"asc_desc_rank":3,"title":"hell on wheels tv series","description":"the construction of the first transcontinental railroad across the united states in the world","tag":"red","":""}
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{"id":"E","word_rank":2,"typo_rank":0,"proximity_rank":0,"attribute_rank":0,"exact_rank":1,"asc_desc_rank":4,"title":"hello kitty","description":"also known by her full name kitty white is a fictional character produced by the japanese company sanrio","tag":"green","":""}
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{"id":"F","word_rank":2,"typo_rank":1,"proximity_rank":0,"attribute_rank":1017,"exact_rank":5,"asc_desc_rank":5,"title":"laptop orchestra","description":"a laptop orchestra lork or lo is a chamber music ensemble consisting primarily of laptops like helo huddersfield experimental laptop orchestra","tag":"blue","":""}
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{"id":"G","word_rank":1,"typo_rank":0,"proximity_rank":0,"attribute_rank":0,"exact_rank":3,"asc_desc_rank":5,"title":"hello world film","description":"hello world is a 2019 japanese animated sci fi romantic drama film directed by tomohiko ito and produced by graphinica","tag":"red","":""}
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{"id":"H","word_rank":1,"typo_rank":0,"proximity_rank":1,"attribute_rank":0,"exact_rank":3,"asc_desc_rank":4,"title":"world hello day","description":"holiday observed on november 21 to express that conflicts should be resolved through communication rather than the use of force","tag":"green","":""}
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{"id":"I","word_rank":0,"typo_rank":0,"proximity_rank":8,"attribute_rank":338,"exact_rank":3,"asc_desc_rank":3,"title":"hello world song","description":"hello world is a song written by tom douglas tony lane and david lee and recorded by american country music group lady antebellum","tag":"blue","":""}
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{"id":"J","word_rank":1,"typo_rank":0,"proximity_rank":1,"attribute_rank":1,"exact_rank":3,"asc_desc_rank":2,"title":"hello cruel world","description":"hello cruel world is an album by new zealand band tall dwarfs","tag":"green","":""}
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{"id":"K","word_rank":0,"typo_rank":2,"proximity_rank":9,"attribute_rank":670,"exact_rank":5,"asc_desc_rank":1,"title":"ello creation system","description":"in few word ello was a construction toy created by the american company mattel to engage girls in construction play","tag":"red","":""}
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{"id":"L","word_rank":0,"typo_rank":0,"proximity_rank":2,"attribute_rank":250,"exact_rank":4,"asc_desc_rank":0,"title":"good morning world","description":"good morning world is an american sitcom broadcast on cbs tv during the 1967 1968 season","tag":"blue","":""}
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{"id":"M","word_rank":0,"typo_rank":0,"proximity_rank":0,"attribute_rank":0,"exact_rank":0,"asc_desc_rank":0,"title":"hello world america","description":"a perfect match for a perfect engine using the query hello world america","tag":"red","":""}
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{"id":"N","word_rank":0,"typo_rank":0,"proximity_rank":0,"attribute_rank":0,"exact_rank":1,"asc_desc_rank":4,"title":"hello world america unleashed","description":"a very good match for a very good engine using the query hello world america","tag":"green","":""}
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{"id":"O","word_rank":0,"typo_rank":0,"proximity_rank":0,"attribute_rank":10,"exact_rank":0,"asc_desc_rank":6,"title":"a perfect match for a perfect engine using the query hello world america","description":"hello world america","tag":"blue","":""}
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{"id":"P","word_rank":0,"typo_rank":0,"proximity_rank":0,"attribute_rank":12,"exact_rank":1,"asc_desc_rank":3,"title":"a very good match for a very good engine using the query hello world america","description":"hello world america unleashed","tag":"red","":""}
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{"id":"Q","word_rank":1,"typo_rank":0,"proximity_rank":0,"attribute_rank":0,"exact_rank":3,"asc_desc_rank":2,"title":"hello world","description":"a hello world program generally is a computer program that outputs or displays the message hello world","tag":"green","":""}
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1
milli/tests/mod.rs
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1
milli/tests/mod.rs
Normal file
@ -0,0 +1 @@
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mod search;
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125
milli/tests/search/mod.rs
Normal file
125
milli/tests/search/mod.rs
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@ -0,0 +1,125 @@
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use milli::{Criterion, Index, DocumentId};
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use milli::update::{IndexDocuments, UpdateFormat, Settings};
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use big_s::S;
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use heed::EnvOpenOptions;
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use maplit::{hashmap, hashset};
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use serde::Deserialize;
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use slice_group_by::GroupBy;
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mod query_criteria;
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pub const TEST_QUERY: &'static str = "hello world america";
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pub const EXTERNAL_DOCUMENTS_IDS: &[&str; 17] = &["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q"];
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pub const CONTENT: &str = include_str!("../assets/test_set.ndjson");
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pub fn setup_search_index_with_criteria(criteria: &[Criterion]) -> Index {
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let path = tempfile::tempdir().unwrap();
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let mut options = EnvOpenOptions::new();
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options.map_size(10 * 1024 * 1024); // 10 MB
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let index = Index::new(options, &path).unwrap();
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let mut wtxn = index.write_txn().unwrap();
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let mut builder = Settings::new(&mut wtxn, &index, 0);
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let criteria = criteria.iter().map(|c| c.to_string()).collect();
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builder.set_criteria(criteria);
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builder.set_filterable_fields(hashset!{
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S("tag"),
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S("asc_desc_rank"),
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});
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builder.set_synonyms(hashmap!{
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S("hello") => vec![S("good morning")],
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S("world") => vec![S("earth")],
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S("america") => vec![S("the united states")],
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});
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builder.set_searchable_fields(vec![S("title"),S("description")]);
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builder.execute(|_, _| ()).unwrap();
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// index documents
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let mut builder = IndexDocuments::new(&mut wtxn, &index, 0);
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builder.update_format(UpdateFormat::JsonStream);
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builder.enable_autogenerate_docids();
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builder.execute(CONTENT.as_bytes(), |_, _| ()).unwrap();
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wtxn.commit().unwrap();
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index
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}
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pub fn internal_to_external_ids(index: &Index, internal_ids: &[DocumentId]) -> Vec<String> {
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let mut rtxn = index.read_txn().unwrap();
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let docid_map = index.external_documents_ids(&mut rtxn).unwrap();
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let docid_map: std::collections::HashMap<_, _> = EXTERNAL_DOCUMENTS_IDS.iter().map(|id| (docid_map.get(id).unwrap(), id)).collect();
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internal_ids.iter().map(|id| docid_map.get(id).unwrap().to_string()).collect()
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}
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pub fn expected_order(criteria: &[Criterion], authorize_typo: bool, optional_words: bool) -> Vec<TestDocument> {
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let dataset = serde_json::Deserializer::from_str(CONTENT).into_iter().map(|r| r.unwrap()).collect();
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let mut groups: Vec<Vec<TestDocument>> = vec![dataset];
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for criterion in criteria {
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let mut new_groups = Vec::new();
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for group in groups.iter_mut() {
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match criterion {
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Criterion::Attribute => {
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group.sort_by_key(|d| d.attribute_rank);
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new_groups.extend(group.linear_group_by_key(|d| d.attribute_rank).map(Vec::from));
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},
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Criterion::Exactness => {
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group.sort_by_key(|d| d.exact_rank);
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new_groups.extend(group.linear_group_by_key(|d| d.exact_rank).map(Vec::from));
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},
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Criterion::Proximity => {
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group.sort_by_key(|d| d.proximity_rank);
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new_groups.extend(group.linear_group_by_key(|d| d.proximity_rank).map(Vec::from));
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},
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Criterion::Typo => {
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group.sort_by_key(|d| d.typo_rank);
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new_groups.extend(group.linear_group_by_key(|d| d.typo_rank).map(Vec::from));
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},
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Criterion::Words => {
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group.sort_by_key(|d| d.word_rank);
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new_groups.extend(group.linear_group_by_key(|d| d.word_rank).map(Vec::from));
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},
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Criterion::Asc(field_name) if field_name == "asc_desc_rank" => {
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group.sort_by_key(|d| d.asc_desc_rank);
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new_groups.extend(group.linear_group_by_key(|d| d.asc_desc_rank).map(Vec::from));
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},
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Criterion::Desc(field_name) if field_name == "asc_desc_rank" => {
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group.sort_by_key(|d| std::cmp::Reverse(d.asc_desc_rank));
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new_groups.extend(group.linear_group_by_key(|d| d.asc_desc_rank).map(Vec::from));
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},
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Criterion::Asc(_) | Criterion::Desc(_) => new_groups.push(group.clone()),
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}
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}
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groups = std::mem::take(&mut new_groups);
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}
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if authorize_typo && optional_words {
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groups.into_iter().flatten().collect()
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} else if optional_words {
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groups.into_iter().flatten().filter(|d| d.typo_rank == 0).collect()
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} else if authorize_typo {
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groups.into_iter().flatten().filter(|d| d.word_rank == 0).collect()
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} else {
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groups.into_iter().flatten().filter(|d| d.word_rank == 0 && d.typo_rank == 0).collect()
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}
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}
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#[derive(Debug, Clone, Deserialize)]
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pub struct TestDocument {
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pub id: String,
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pub word_rank: u32,
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pub typo_rank: u32,
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pub proximity_rank: u32,
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pub attribute_rank: u32,
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pub exact_rank: u32,
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pub asc_desc_rank: u32,
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pub title: String,
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pub description: String,
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pub tag: String,
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}
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213
milli/tests/search/query_criteria.rs
Normal file
213
milli/tests/search/query_criteria.rs
Normal file
@ -0,0 +1,213 @@
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use milli::{Search, SearchResult, Criterion};
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use big_s::S;
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use crate::search::{self, EXTERNAL_DOCUMENTS_IDS};
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use Criterion::*;
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const ALLOW_TYPOS: bool = true;
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const DISALLOW_TYPOS: bool = false;
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const ALLOW_OPTIONAL_WORDS: bool = true;
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const DISALLOW_OPTIONAL_WORDS: bool = false;
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macro_rules! test_criterion {
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($func:ident, $optional_word:ident, $authorize_typos:ident $(, $criterion:expr)?) => {
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#[test]
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fn $func() {
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let criteria = vec![$($criterion)?];
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let index = search::setup_search_index_with_criteria(&criteria);
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let mut rtxn = index.read_txn().unwrap();
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let mut search = Search::new(&mut rtxn, &index);
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search.query(search::TEST_QUERY);
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search.limit(EXTERNAL_DOCUMENTS_IDS.len());
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search.authorize_typos($authorize_typos);
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search.optional_words($optional_word);
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let SearchResult { documents_ids, .. } = search.execute().unwrap();
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let expected_external_ids: Vec<_> = search::expected_order(&criteria, $authorize_typos, $optional_word)
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.into_iter()
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.map(|d| d.id).collect();
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let documents_ids = search::internal_to_external_ids(&index, &documents_ids);
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assert_eq!(documents_ids, expected_external_ids);
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}
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}
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}
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test_criterion!(none_allow_typo, ALLOW_OPTIONAL_WORDS, ALLOW_TYPOS);
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test_criterion!(none_disallow_typo, DISALLOW_OPTIONAL_WORDS, DISALLOW_TYPOS);
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test_criterion!(words_allow_typo, ALLOW_OPTIONAL_WORDS, ALLOW_TYPOS, Words);
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test_criterion!(attribute_allow_typo, DISALLOW_OPTIONAL_WORDS, ALLOW_TYPOS, Attribute);
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test_criterion!(attribute_disallow_typo, DISALLOW_OPTIONAL_WORDS, DISALLOW_TYPOS, Attribute);
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test_criterion!(exactness_allow_typo, DISALLOW_OPTIONAL_WORDS, ALLOW_TYPOS, Exactness);
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test_criterion!(exactness_disallow_typo, DISALLOW_OPTIONAL_WORDS, DISALLOW_TYPOS, Exactness);
|
||||
test_criterion!(proximity_allow_typo, DISALLOW_OPTIONAL_WORDS, ALLOW_TYPOS, Proximity);
|
||||
test_criterion!(proximity_disallow_typo, DISALLOW_OPTIONAL_WORDS, DISALLOW_TYPOS, Proximity);
|
||||
test_criterion!(asc_allow_typo, DISALLOW_OPTIONAL_WORDS, ALLOW_TYPOS, Asc(S("asc_desc_rank")));
|
||||
test_criterion!(asc_disallow_typo, DISALLOW_OPTIONAL_WORDS, DISALLOW_TYPOS, Asc(S("asc_desc_rank")));
|
||||
test_criterion!(desc_allow_typo, DISALLOW_OPTIONAL_WORDS, ALLOW_TYPOS, Desc(S("asc_desc_rank")));
|
||||
test_criterion!(desc_disallow_typo, DISALLOW_OPTIONAL_WORDS, DISALLOW_TYPOS, Desc(S("asc_desc_rank")));
|
||||
test_criterion!(asc_unexisting_field_allow_typo, DISALLOW_OPTIONAL_WORDS, ALLOW_TYPOS, Asc(S("unexisting_field")));
|
||||
test_criterion!(asc_unexisting_field_disallow_typo, DISALLOW_OPTIONAL_WORDS, DISALLOW_TYPOS, Asc(S("unexisting_field")));
|
||||
test_criterion!(desc_unexisting_field_allow_typo, DISALLOW_OPTIONAL_WORDS, ALLOW_TYPOS, Desc(S("unexisting_field")));
|
||||
test_criterion!(desc_unexisting_field_disallow_typo, DISALLOW_OPTIONAL_WORDS, DISALLOW_TYPOS, Desc(S("unexisting_field")));
|
||||
|
||||
#[test]
|
||||
fn criteria_mixup() {
|
||||
use Criterion::*;
|
||||
let index = search::setup_search_index_with_criteria(&vec![Words, Attribute, Desc(S("asc_desc_rank")), Exactness, Proximity, Typo]);
|
||||
|
||||
let criteria_mix = {
|
||||
// Criterion doesn't implement Copy, we create a new Criterion using a closure
|
||||
let desc = || Desc(S("asc_desc_rank"));
|
||||
// all possible criteria order
|
||||
vec![
|
||||
vec![Words, Attribute, desc(), Exactness, Proximity, Typo],
|
||||
vec![Words, Attribute, desc(), Exactness, Typo, Proximity],
|
||||
vec![Words, Attribute, desc(), Proximity, Exactness, Typo],
|
||||
vec![Words, Attribute, desc(), Proximity, Typo, Exactness],
|
||||
vec![Words, Attribute, desc(), Typo, Exactness, Proximity],
|
||||
vec![Words, Attribute, desc(), Typo, Proximity, Exactness],
|
||||
vec![Words, Attribute, Exactness, desc(), Proximity, Typo],
|
||||
vec![Words, Attribute, Exactness, desc(), Typo, Proximity],
|
||||
vec![Words, Attribute, Exactness, Proximity, desc(), Typo],
|
||||
vec![Words, Attribute, Exactness, Proximity, Typo, desc()],
|
||||
vec![Words, Attribute, Exactness, Typo, desc(), Proximity],
|
||||
vec![Words, Attribute, Exactness, Typo, Proximity, desc()],
|
||||
vec![Words, Attribute, Proximity, desc(), Exactness, Typo],
|
||||
vec![Words, Attribute, Proximity, desc(), Typo, Exactness],
|
||||
vec![Words, Attribute, Proximity, Exactness, desc(), Typo],
|
||||
vec![Words, Attribute, Proximity, Exactness, Typo, desc()],
|
||||
vec![Words, Attribute, Proximity, Typo, desc(), Exactness],
|
||||
vec![Words, Attribute, Proximity, Typo, Exactness, desc()],
|
||||
vec![Words, Attribute, Typo, desc(), Exactness, Proximity],
|
||||
vec![Words, Attribute, Typo, desc(), Proximity, Exactness],
|
||||
vec![Words, Attribute, Typo, Exactness, desc(), Proximity],
|
||||
vec![Words, Attribute, Typo, Exactness, Proximity, desc()],
|
||||
vec![Words, Attribute, Typo, Proximity, desc(), Exactness],
|
||||
vec![Words, Attribute, Typo, Proximity, Exactness, desc()],
|
||||
vec![Words, desc(), Attribute, Exactness, Proximity, Typo],
|
||||
vec![Words, desc(), Attribute, Exactness, Typo, Proximity],
|
||||
vec![Words, desc(), Attribute, Proximity, Exactness, Typo],
|
||||
vec![Words, desc(), Attribute, Proximity, Typo, Exactness],
|
||||
vec![Words, desc(), Attribute, Typo, Exactness, Proximity],
|
||||
vec![Words, desc(), Attribute, Typo, Proximity, Exactness],
|
||||
vec![Words, desc(), Exactness, Attribute, Proximity, Typo],
|
||||
vec![Words, desc(), Exactness, Attribute, Typo, Proximity],
|
||||
vec![Words, desc(), Exactness, Proximity, Attribute, Typo],
|
||||
vec![Words, desc(), Exactness, Proximity, Typo, Attribute],
|
||||
vec![Words, desc(), Exactness, Typo, Attribute, Proximity],
|
||||
vec![Words, desc(), Exactness, Typo, Proximity, Attribute],
|
||||
vec![Words, desc(), Proximity, Attribute, Exactness, Typo],
|
||||
vec![Words, desc(), Proximity, Attribute, Typo, Exactness],
|
||||
vec![Words, desc(), Proximity, Exactness, Attribute, Typo],
|
||||
vec![Words, desc(), Proximity, Exactness, Typo, Attribute],
|
||||
vec![Words, desc(), Proximity, Typo, Attribute, Exactness],
|
||||
vec![Words, desc(), Proximity, Typo, Exactness, Attribute],
|
||||
vec![Words, desc(), Typo, Attribute, Exactness, Proximity],
|
||||
vec![Words, desc(), Typo, Attribute, Proximity, Exactness],
|
||||
vec![Words, desc(), Typo, Exactness, Attribute, Proximity],
|
||||
vec![Words, desc(), Typo, Exactness, Proximity, Attribute],
|
||||
vec![Words, desc(), Typo, Proximity, Attribute, Exactness],
|
||||
vec![Words, desc(), Typo, Proximity, Exactness, Attribute],
|
||||
vec![Words, Exactness, Attribute, desc(), Proximity, Typo],
|
||||
vec![Words, Exactness, Attribute, desc(), Typo, Proximity],
|
||||
vec![Words, Exactness, Attribute, Proximity, desc(), Typo],
|
||||
vec![Words, Exactness, Attribute, Proximity, Typo, desc()],
|
||||
vec![Words, Exactness, Attribute, Typo, desc(), Proximity],
|
||||
vec![Words, Exactness, Attribute, Typo, Proximity, desc()],
|
||||
vec![Words, Exactness, desc(), Attribute, Proximity, Typo],
|
||||
vec![Words, Exactness, desc(), Attribute, Typo, Proximity],
|
||||
vec![Words, Exactness, desc(), Proximity, Attribute, Typo],
|
||||
vec![Words, Exactness, desc(), Proximity, Typo, Attribute],
|
||||
vec![Words, Exactness, desc(), Typo, Attribute, Proximity],
|
||||
vec![Words, Exactness, desc(), Typo, Proximity, Attribute],
|
||||
vec![Words, Exactness, Proximity, Attribute, desc(), Typo],
|
||||
vec![Words, Exactness, Proximity, Attribute, Typo, desc()],
|
||||
vec![Words, Exactness, Proximity, desc(), Attribute, Typo],
|
||||
vec![Words, Exactness, Proximity, desc(), Typo, Attribute],
|
||||
vec![Words, Exactness, Proximity, Typo, Attribute, desc()],
|
||||
vec![Words, Exactness, Proximity, Typo, desc(), Attribute],
|
||||
vec![Words, Exactness, Typo, Attribute, desc(), Proximity],
|
||||
vec![Words, Exactness, Typo, Attribute, Proximity, desc()],
|
||||
vec![Words, Exactness, Typo, desc(), Attribute, Proximity],
|
||||
vec![Words, Exactness, Typo, desc(), Proximity, Attribute],
|
||||
vec![Words, Exactness, Typo, Proximity, Attribute, desc()],
|
||||
vec![Words, Exactness, Typo, Proximity, desc(), Attribute],
|
||||
vec![Words, Proximity, Attribute, desc(), Exactness, Typo],
|
||||
vec![Words, Proximity, Attribute, desc(), Typo, Exactness],
|
||||
vec![Words, Proximity, Attribute, Exactness, desc(), Typo],
|
||||
vec![Words, Proximity, Attribute, Exactness, Typo, desc()],
|
||||
vec![Words, Proximity, Attribute, Typo, desc(), Exactness],
|
||||
vec![Words, Proximity, Attribute, Typo, Exactness, desc()],
|
||||
vec![Words, Proximity, desc(), Attribute, Exactness, Typo],
|
||||
vec![Words, Proximity, desc(), Attribute, Typo, Exactness],
|
||||
vec![Words, Proximity, desc(), Exactness, Attribute, Typo],
|
||||
vec![Words, Proximity, desc(), Exactness, Typo, Attribute],
|
||||
vec![Words, Proximity, desc(), Typo, Attribute, Exactness],
|
||||
vec![Words, Proximity, desc(), Typo, Exactness, Attribute],
|
||||
vec![Words, Proximity, Exactness, Attribute, desc(), Typo],
|
||||
vec![Words, Proximity, Exactness, Attribute, Typo, desc()],
|
||||
vec![Words, Proximity, Exactness, desc(), Attribute, Typo],
|
||||
vec![Words, Proximity, Exactness, desc(), Typo, Attribute],
|
||||
vec![Words, Proximity, Exactness, Typo, Attribute, desc()],
|
||||
vec![Words, Proximity, Exactness, Typo, desc(), Attribute],
|
||||
vec![Words, Proximity, Typo, Attribute, desc(), Exactness],
|
||||
vec![Words, Proximity, Typo, Attribute, Exactness, desc()],
|
||||
vec![Words, Proximity, Typo, desc(), Attribute, Exactness],
|
||||
vec![Words, Proximity, Typo, desc(), Exactness, Attribute],
|
||||
vec![Words, Proximity, Typo, Exactness, Attribute, desc()],
|
||||
vec![Words, Proximity, Typo, Exactness, desc(), Attribute],
|
||||
vec![Words, Typo, Attribute, desc(), Exactness, Proximity],
|
||||
vec![Words, Typo, Attribute, desc(), Proximity, Exactness],
|
||||
vec![Words, Typo, Attribute, Exactness, desc(), Proximity],
|
||||
vec![Words, Typo, Attribute, Exactness, Proximity, desc()],
|
||||
vec![Words, Typo, Attribute, Proximity, desc(), Exactness],
|
||||
vec![Words, Typo, Attribute, Proximity, Exactness, desc()],
|
||||
vec![Words, Typo, desc(), Attribute, Proximity, Exactness],
|
||||
vec![Words, Typo, desc(), Exactness, Attribute, Proximity],
|
||||
vec![Words, Typo, desc(), Exactness, Attribute, Proximity],
|
||||
vec![Words, Typo, desc(), Exactness, Proximity, Attribute],
|
||||
vec![Words, Typo, desc(), Proximity, Attribute, Exactness],
|
||||
vec![Words, Typo, desc(), Proximity, Exactness, Attribute],
|
||||
vec![Words, Typo, Exactness, Attribute, desc(), Proximity],
|
||||
vec![Words, Typo, Exactness, Attribute, Proximity, desc()],
|
||||
vec![Words, Typo, Exactness, desc(), Attribute, Proximity],
|
||||
vec![Words, Typo, Exactness, desc(), Proximity, Attribute],
|
||||
vec![Words, Typo, Exactness, Proximity, Attribute, desc()],
|
||||
vec![Words, Typo, Exactness, Proximity, desc(), Attribute],
|
||||
vec![Words, Typo, Proximity, Attribute, desc(), Exactness],
|
||||
vec![Words, Typo, Proximity, Attribute, Exactness, desc()],
|
||||
vec![Words, Typo, Proximity, desc(), Attribute, Exactness],
|
||||
vec![Words, Typo, Proximity, desc(), Exactness, Attribute],
|
||||
vec![Words, Typo, Proximity, Exactness, Attribute, desc()],
|
||||
vec![Words, Typo, Proximity, Exactness, desc(), Attribute],
|
||||
]
|
||||
};
|
||||
|
||||
for criteria in criteria_mix {
|
||||
eprintln!("Testing with criteria order: {:?}", &criteria);
|
||||
//update criteria
|
||||
let mut wtxn = index.write_txn().unwrap();
|
||||
index.put_criteria(&mut wtxn, &criteria).unwrap();
|
||||
wtxn.commit().unwrap();
|
||||
|
||||
let mut rtxn = index.read_txn().unwrap();
|
||||
|
||||
let mut search = Search::new(&mut rtxn, &index);
|
||||
search.query(search::TEST_QUERY);
|
||||
search.limit(EXTERNAL_DOCUMENTS_IDS.len());
|
||||
search.optional_words(ALLOW_OPTIONAL_WORDS);
|
||||
search.authorize_typos(ALLOW_TYPOS);
|
||||
|
||||
let SearchResult { documents_ids, .. } = search.execute().unwrap();
|
||||
|
||||
let expected_external_ids: Vec<_> = search::expected_order(&criteria, ALLOW_OPTIONAL_WORDS, ALLOW_TYPOS)
|
||||
.into_iter()
|
||||
.map(|d| d.id)
|
||||
.collect();
|
||||
let documents_ids = search::internal_to_external_ids(&index, &documents_ids);
|
||||
|
||||
assert_eq!(documents_ids, expected_external_ids);
|
||||
}
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user