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typesense/test/collection_test.cpp

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#include <gtest/gtest.h>
#include <string>
#include <vector>
#include <fstream>
#include <algorithm>
#include <collection_manager.h>
#include "collection.h"
class CollectionTest : public ::testing::Test {
protected:
Collection *collection;
std::vector<std::string> query_fields;
Store *store;
CollectionManager & collectionManager = CollectionManager::get_instance();
std::vector<sort_by> sort_fields;
// used for generating random text
std::vector<std::string> words;
void setupCollection() {
std::string state_dir_path = "/tmp/typesense_test/collection";
LOG(INFO) << "Truncating and creating: " << state_dir_path;
system(("rm -rf "+state_dir_path+" && mkdir -p "+state_dir_path).c_str());
store = new Store(state_dir_path);
collectionManager.init(store, 1.0, "auth_key");
collectionManager.load(8, 1000);
std::ifstream infile(std::string(ROOT_DIR)+"test/documents.jsonl");
std::vector<field> search_fields = {
field("title", field_types::STRING, false),
field("points", field_types::INT32, false)
};
query_fields = {"title"};
sort_fields = { sort_by(sort_field_const::text_match, "DESC"), sort_by("points", "DESC") };
collection = collectionManager.get_collection("collection").get();
if(collection == nullptr) {
collection = collectionManager.create_collection("collection", 4, search_fields, "points").get();
}
std::string json_line;
// dummy record for record id 0: to make the test record IDs to match with line numbers
json_line = "{\"points\":10,\"title\":\"z\"}";
collection->add(json_line);
while (std::getline(infile, json_line)) {
collection->add(json_line);
}
infile.close();
std::ifstream words_file(std::string(ROOT_DIR)+"test/resources/common100_english.txt");
std::stringstream strstream;
strstream << words_file.rdbuf();
words_file.close();
StringUtils::split(strstream.str(), words, "\n");
}
virtual void SetUp() {
setupCollection();
}
virtual void TearDown() {
collectionManager.drop_collection("collection");
collectionManager.dispose();
delete store;
}
std::string get_text(size_t num_words) {
time_t t;
srand((unsigned) time(&t));
std::vector<std::string> strs;
for(size_t i = 0 ; i < num_words ; i++ ) {
int word_index = rand() % 100;
strs.push_back(words[word_index]);
}
return StringUtils::join(strs, " ");
}
};
TEST_F(CollectionTest, VerifyCountOfDocuments) {
// we have 1 dummy record to match the line numbers on the fixtures file with sequence numbers
ASSERT_EQ(24+1, collection->get_num_documents());
// check default no specific dirty values option is sent for a collection that has explicit schema
std::string empty_dirty_values;
ASSERT_EQ(DIRTY_VALUES::REJECT, collection->parse_dirty_values_option(empty_dirty_values));
}
TEST_F(CollectionTest, RetrieveADocumentById) {
Option<nlohmann::json> doc_option = collection->get("1");
ASSERT_TRUE(doc_option.ok());
nlohmann::json doc = doc_option.get();
std::string id = doc["id"];
doc_option = collection->get("foo");
ASSERT_TRUE(doc_option.ok());
doc = doc_option.get();
id = doc["id"];
ASSERT_STREQ("foo", id.c_str());
doc_option = collection->get("baz");
ASSERT_FALSE(doc_option.ok());
}
TEST_F(CollectionTest, ExactSearchShouldBeStable) {
std::vector<std::string> facets;
nlohmann::json results = collection->search("the", query_fields, "", facets, sort_fields, {0}, 10).get();
ASSERT_EQ(7, results["hits"].size());
ASSERT_EQ(7, results["found"].get<int>());
ASSERT_STREQ("collection", results["request_params"]["collection_name"].get<std::string>().c_str());
ASSERT_STREQ("the", results["request_params"]["q"].get<std::string>().c_str());
ASSERT_EQ(10, results["request_params"]["per_page"].get<size_t>());
// For two documents of the same score, the larger doc_id appears first
std::vector<std::string> ids = {"1", "6", "foo", "13", "10", "8", "16"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string id = ids.at(i);
std::string result_id = result["document"]["id"];
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// check ASC sorting
std::vector<sort_by> sort_fields_asc = { sort_by("points", "ASC") };
results = collection->search("the", query_fields, "", facets, sort_fields_asc, {0}, 10).get();
ASSERT_EQ(7, results["hits"].size());
ASSERT_EQ(7, results["found"].get<int>());
ids = {"16", "13", "10", "8", "6", "foo", "1"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string id = ids.at(i);
std::string result_id = result["document"]["id"];
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// when a query does not return results, hits and found fields should still exist in response
results = collection->search("zxsadqewsad", query_fields, "", facets, sort_fields_asc, {0}, 10).get();
ASSERT_EQ(0, results["hits"].size());
ASSERT_EQ(0, results["found"].get<int>());
}
TEST_F(CollectionTest, PhraseSearch) {
std::vector<std::string> facets;
nlohmann::json results = collection->search("rocket launch", query_fields, "", facets, sort_fields, {0}, 10).get();
ASSERT_EQ(5, results["hits"].size());
ASSERT_EQ(5, results["found"].get<uint32_t>());
/*
Sort by (match, diff, score)
8: score: 12, diff: 0
1: score: 15, diff: 4
17: score: 8, diff: 4
16: score: 10, diff: 5
13: score: 12, (single word match)
*/
std::vector<std::string> ids = {"8", "1", "17", "16", "13"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string id = ids.at(i);
std::string result_id = result["document"]["id"];
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
ASSERT_EQ(results["hits"][0]["highlights"].size(), (unsigned long) 1);
ASSERT_STREQ(results["hits"][0]["highlights"][0]["field"].get<std::string>().c_str(), "title");
ASSERT_STREQ(results["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str(),
"What is the power, requirement of a <mark>rocket</mark> <mark>launch</mark> these days?");
// Check ASC sort order
std::vector<sort_by> sort_fields_asc = { sort_by(sort_field_const::text_match, "DESC"), sort_by("points", "ASC") };
results = collection->search("rocket launch", query_fields, "", facets, sort_fields_asc, {0}, 10).get();
ASSERT_EQ(5, results["hits"].size());
ASSERT_EQ(5, results["found"].get<uint32_t>());
ids = {"8", "17", "1", "16", "13"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string id = ids.at(i);
std::string result_id = result["document"]["id"];
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// Check pagination
results = collection->search("rocket launch", query_fields, "", facets, sort_fields, {0}, 3).get();
ASSERT_EQ(3, results["hits"].size());
ASSERT_EQ(5, results["found"].get<uint32_t>());
ASSERT_EQ(3, results["request_params"]["per_page"].get<size_t>());
ids = {"8", "1", "17"};
for(size_t i = 0; i < 3; i++) {
nlohmann::json result = results["hits"].at(i);
std::string id = ids.at(i);
std::string result_id = result["document"]["id"];
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
}
TEST_F(CollectionTest, SearchWithExcludedTokens) {
std::vector<std::string> facets;
nlohmann::json results = collection->search("how -propellants -are", query_fields, "", facets, sort_fields, {0}, 10).get();
ASSERT_EQ(2, results["hits"].size());
ASSERT_EQ(2, results["found"].get<uint32_t>());
std::vector<std::string> ids = {"9", "17"};
for (size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string id = ids.at(i);
std::string result_id = result["document"]["id"];
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results = collection->search("-rocket", query_fields, "", facets, sort_fields, {0}, 50).get();
ASSERT_EQ(21, results["found"].get<uint32_t>());
ASSERT_EQ(21, results["hits"].size());
results = collection->search("-rocket -cryovolcanism", query_fields, "", facets, sort_fields, {0}, 50).get();
ASSERT_EQ(20, results["found"].get<uint32_t>());
}
TEST_F(CollectionTest, SkipUnindexedTokensDuringPhraseSearch) {
// Tokens that are not found in the index should be skipped
std::vector<std::string> facets;
nlohmann::json results = collection->search("DoesNotExist from", query_fields, "", facets, sort_fields, {0}, 10).get();
ASSERT_EQ(2, results["hits"].size());
std::vector<std::string> ids = {"2", "17"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string id = ids.at(i);
std::string result_id = result["document"]["id"];
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// with non-zero cost
results = collection->search("DoesNotExist from", query_fields, "", facets, sort_fields, {1}, 10).get();
ASSERT_EQ(2, results["hits"].size());
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string id = ids.at(i);
std::string result_id = result["document"]["id"];
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// with 2 indexed words
results = collection->search("from DoesNotExist insTruments", query_fields, "", facets, sort_fields, {1}, 10).get();
ASSERT_EQ(2, results["hits"].size());
ids = {"2", "17"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string id = ids.at(i);
std::string result_id = result["document"]["id"];
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// should not try to drop tokens to expand query
results.clear();
results = collection->search("the a", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}, 10).get();
ASSERT_EQ(9, results["hits"].size());
results.clear();
results = collection->search("the a", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}, 0).get();
ASSERT_EQ(3, results["hits"].size());
ids = {"8", "16", "10"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string id = ids.at(i);
std::string result_id = result["document"]["id"];
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results.clear();
results = collection->search("the a insurance", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}, 0).get();
ASSERT_EQ(0, results["hits"].size());
// with no indexed word
results.clear();
results = collection->search("DoesNotExist1 DoesNotExist2", query_fields, "", facets, sort_fields, {0}, 10).get();
ASSERT_EQ(0, results["hits"].size());
results.clear();
results = collection->search("DoesNotExist1 DoesNotExist2", query_fields, "", facets, sort_fields, {2}, 10).get();
ASSERT_EQ(0, results["hits"].size());
}
TEST_F(CollectionTest, PartialPhraseSearch) {
std::vector<std::string> facets;
nlohmann::json results = collection->search("rocket research", query_fields, "", facets, sort_fields, {0}, 10).get();
ASSERT_EQ(6, results["hits"].size());
std::vector<std::string> ids = {"19", "1", "10", "8", "16", "17"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
}
TEST_F(CollectionTest, QueryWithTypo) {
std::vector<std::string> facets;
nlohmann::json results = collection->search("kind biologcal", query_fields, "", facets, sort_fields, {2}, 3).get();
ASSERT_EQ(3, results["hits"].size());
std::vector<std::string> ids = {"19", "3", "20"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results.clear();
results = collection->search("fer thx", query_fields, "", facets, sort_fields, {1}, 3).get();
ids = {"1", "10", "13"};
ASSERT_EQ(3, results["hits"].size());
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
}
TEST_F(CollectionTest, TypoTokenRankedByScoreAndFrequency) {
std::vector<std::string> facets;
nlohmann::json results = collection->search("loox", query_fields, "", facets, sort_fields, {1}, 2, 1, MAX_SCORE, {false}).get();
ASSERT_EQ(2, results["hits"].size());
std::vector<std::string> ids = {"22", "3"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results = collection->search("loox", query_fields, "", facets, sort_fields, {1}, 3, 1, FREQUENCY, {false}).get();
ASSERT_EQ(3, results["hits"].size());
ids = {"22", "3", "12"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// Check pagination
results = collection->search("loox", query_fields, "", facets, sort_fields, {1}, 1, 1, FREQUENCY, {false}).get();
ASSERT_EQ(5, results["found"].get<int>());
ASSERT_EQ(1, results["hits"].size());
std::string solo_id = results["hits"].at(0)["document"]["id"];
ASSERT_STREQ("22", solo_id.c_str());
results = collection->search("loox", query_fields, "", facets, sort_fields, {1}, 2, 1, FREQUENCY, {false}).get();
ASSERT_EQ(5, results["found"].get<int>());
ASSERT_EQ(2, results["hits"].size());
// Check total ordering
results = collection->search("loox", query_fields, "", facets, sort_fields, {1}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(5, results["hits"].size());
ids = {"22", "3", "12", "23", "24"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results = collection->search("loox", query_fields, "", facets, sort_fields, {1}, 10, 1, MAX_SCORE, {false}).get();
ASSERT_EQ(5, results["hits"].size());
ids = {"22", "3", "12", "23", "24"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
}
TEST_F(CollectionTest, TextContainingAnActualTypo) {
// A line contains "ISX" but not "what" - need to ensure that correction to "ISS what" happens
std::vector<std::string> facets;
nlohmann::json results = collection->search("ISX what", query_fields, "", facets, sort_fields, {1}, 4, 1, FREQUENCY, {false}).get();
ASSERT_EQ(4, results["hits"].size());
ASSERT_EQ(13, results["found"].get<uint32_t>());
std::vector<std::string> ids = {"8", "19", "6", "21"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// Record containing exact token match should appear first
results = collection->search("ISX", query_fields, "", facets, sort_fields, {1}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(8, results["hits"].size());
ASSERT_EQ(8, results["found"].get<uint32_t>());
ids = {"20", "19", "6", "4", "3", "10", "8", "21"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
}
TEST_F(CollectionTest, Pagination) {
nlohmann::json results = collection->search("the", query_fields, "", {}, sort_fields, {0}, 3, 1, FREQUENCY, {false}).get();
ASSERT_EQ(3, results["hits"].size());
ASSERT_EQ(7, results["found"].get<uint32_t>());
std::vector<std::string> ids = {"1", "6", "foo"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results = collection->search("the", query_fields, "", {}, sort_fields, {0}, 3, 2, FREQUENCY, {false}).get();
ASSERT_EQ(3, results["hits"].size());
ASSERT_EQ(7, results["found"].get<uint32_t>());
ids = {"13", "10", "8"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results = collection->search("the", query_fields, "", {}, sort_fields, {0}, 3, 3, FREQUENCY, {false}).get();
ASSERT_EQ(1, results["hits"].size());
ASSERT_EQ(7, results["found"].get<uint32_t>());
ids = {"16"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
}
TEST_F(CollectionTest, WildcardQuery) {
nlohmann::json results = collection->search("*", query_fields, "points:>0", {}, sort_fields, {0}, 3, 1, FREQUENCY,
{false}).get();
ASSERT_EQ(3, results["hits"].size());
ASSERT_EQ(25, results["found"].get<uint32_t>());
// when no filter is specified, fall back on default sorting field based catch-all filter
Option<nlohmann::json> results_op = collection->search("*", query_fields, "", {}, sort_fields, {0}, 3, 1, FREQUENCY,
{false});
ASSERT_TRUE(results_op.ok());
ASSERT_EQ(3, results["hits"].size());
ASSERT_EQ(25, results["found"].get<uint32_t>());
// wildcard query with no filters and ASC sort
std::vector<sort_by> sort_fields = { sort_by("points", "ASC") };
results = collection->search("*", query_fields, "", {}, sort_fields, {0}, 3, 1, FREQUENCY, {false}).get();
ASSERT_EQ(3, results["hits"].size());
ASSERT_EQ(25, results["found"].get<uint32_t>());
std::vector<std::string> ids = {"21", "24", "17"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// wildcard query should not require a search field
results_op = collection->search("*", {}, "", {}, sort_fields, {0}, 3, 1, FREQUENCY, {false});
ASSERT_TRUE(results_op.ok());
results = results_op.get();
ASSERT_EQ(3, results["hits"].size());
ASSERT_EQ(25, results["found"].get<uint32_t>());
// non-wildcard query should require a search field
results_op = collection->search("the", {}, "", {}, sort_fields, {0}, 3, 1, FREQUENCY, {false});
ASSERT_FALSE(results_op.ok());
ASSERT_STREQ("No search fields specified for the query.", results_op.error().c_str());
}
TEST_F(CollectionTest, PrefixSearching) {
std::vector<std::string> facets;
nlohmann::json results = collection->search("ex", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {true}).get();
ASSERT_EQ(2, results["hits"].size());
std::vector<std::string> ids = {"6", "12"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results = collection->search("ex", query_fields, "", facets, sort_fields, {0}, 10, 1, MAX_SCORE, {true}).get();
ASSERT_EQ(2, results["hits"].size());
ids = {"6", "12"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results = collection->search("what ex", query_fields, "", facets, sort_fields, {0}, 10, 1, MAX_SCORE, {true}).get();
ASSERT_EQ(9, results["hits"].size());
ids = {"6", "12", "19", "22", "13", "8", "15", "24", "21"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// restrict to only 2 results and differentiate between MAX_SCORE and FREQUENCY
results = collection->search("t", query_fields, "", facets, sort_fields, {0}, 2, 1, MAX_SCORE, {true}).get();
ASSERT_EQ(2, results["hits"].size());
ids = {"19", "22"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results = collection->search("t", query_fields, "", facets, sort_fields, {0}, 2, 1, FREQUENCY, {true}).get();
ASSERT_EQ(2, results["hits"].size());
ids = {"19", "22"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// only the last token in the query should be used for prefix search - so, "math" should not match "mathematics"
results = collection->search("math fx", query_fields, "", facets, sort_fields, {0}, 1, 1, FREQUENCY, {true}).get();
ASSERT_EQ(0, results["hits"].size());
// single and double char prefixes should set a ceiling on the num_typos possible
results = collection->search("x", query_fields, "", facets, sort_fields, {2}, 2, 1, FREQUENCY, {true}).get();
ASSERT_EQ(0, results["hits"].size());
// prefix with a typo
results = collection->search("late propx", query_fields, "", facets, sort_fields, {2}, 1, 1, FREQUENCY, {true}).get();
ASSERT_EQ(1, results["hits"].size());
ASSERT_EQ("16", results["hits"].at(0)["document"]["id"]);
}
TEST_F(CollectionTest, TypoTokensThreshold) {
// Query expansion should happen only based on the `typo_tokens_threshold` value
auto results = collection->search("launch", {"title"}, "", {}, sort_fields, {2}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "", 0).get();
ASSERT_EQ(5, results["hits"].size());
ASSERT_EQ(5, results["found"].get<size_t>());
results = collection->search("launch", {"title"}, "", {}, sort_fields, {2}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "", 10).get();
ASSERT_EQ(7, results["hits"].size());
ASSERT_EQ(7, results["found"].get<size_t>());
}
TEST_F(CollectionTest, MultiOccurrenceString) {
Collection *coll_multi_string;
std::vector<field> fields = {
field("title", field_types::STRING, false),
field("points", field_types::INT32, false)
};
coll_multi_string = collectionManager.get_collection("coll_multi_string").get();
if (coll_multi_string == nullptr) {
coll_multi_string = collectionManager.create_collection("coll_multi_string", 4, fields, "points").get();
}
nlohmann::json document;
document["title"] = "The brown fox was the tallest of the lot and the quickest of the trot.";
document["points"] = 100;
coll_multi_string->add(document.dump()).get();
query_fields = {"title"};
nlohmann::json results = coll_multi_string->search("the", query_fields, "", {}, sort_fields, {0}, 10, 1,
FREQUENCY, {false}, 0).get();
ASSERT_EQ(1, results["hits"].size());
collectionManager.drop_collection("coll_multi_string");
}
TEST_F(CollectionTest, ArrayStringFieldHighlight) {
Collection *coll_array_text;
std::ifstream infile(std::string(ROOT_DIR) + "test/array_text_documents.jsonl");
std::vector<field> fields = {
field("title", field_types::STRING, false),
field("tags", field_types::STRING_ARRAY, false),
field("points", field_types::INT32, false)
};
coll_array_text = collectionManager.get_collection("coll_array_text").get();
if (coll_array_text == nullptr) {
coll_array_text = collectionManager.create_collection("coll_array_text", 4, fields, "points").get();
}
std::string json_line;
while (std::getline(infile, json_line)) {
coll_array_text->add(json_line);
}
infile.close();
query_fields = {"tags"};
std::vector<std::string> facets;
nlohmann::json results = coll_array_text->search("truth about", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY,
{false}, 0).get();
ASSERT_EQ(1, results["hits"].size());
std::vector<std::string> ids = {"0"};
for (size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
ASSERT_EQ(results["hits"][0]["highlights"].size(), 1);
ASSERT_STREQ(results["hits"][0]["highlights"][0]["field"].get<std::string>().c_str(), "tags");
// an array's snippets must be sorted on match score, if match score is same, priority to be given to lower indices
ASSERT_EQ(3, results["hits"][0]["highlights"][0]["snippets"].size());
ASSERT_STREQ("<mark>truth</mark> <mark>about</mark>", results["hits"][0]["highlights"][0]["snippets"][0].get<std::string>().c_str());
ASSERT_STREQ("the <mark>truth</mark>", results["hits"][0]["highlights"][0]["snippets"][1].get<std::string>().c_str());
ASSERT_STREQ("<mark>about</mark> forever", results["hits"][0]["highlights"][0]["snippets"][2].get<std::string>().c_str());
ASSERT_EQ(3, results["hits"][0]["highlights"][0]["indices"].size());
ASSERT_EQ(2, results["hits"][0]["highlights"][0]["indices"][0]);
ASSERT_EQ(0, results["hits"][0]["highlights"][0]["indices"][1]);
ASSERT_EQ(1, results["hits"][0]["highlights"][0]["indices"][2]);
results = coll_array_text->search("forever truth", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY,
{false}, 0).get();
ASSERT_EQ(1, results["hits"].size());
ids = {"0"};
for (size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
ASSERT_STREQ(results["hits"][0]["highlights"][0]["field"].get<std::string>().c_str(), "tags");
ASSERT_EQ(3, results["hits"][0]["highlights"][0]["snippets"].size());
ASSERT_STREQ("the <mark>truth</mark>", results["hits"][0]["highlights"][0]["snippets"][0].get<std::string>().c_str());
ASSERT_STREQ("about <mark>forever</mark>", results["hits"][0]["highlights"][0]["snippets"][1].get<std::string>().c_str());
ASSERT_STREQ("<mark>truth</mark> about", results["hits"][0]["highlights"][0]["snippets"][2].get<std::string>().c_str());
ASSERT_EQ(3, results["hits"][0]["highlights"][0]["indices"].size());
ASSERT_EQ(0, results["hits"][0]["highlights"][0]["indices"][0]);
ASSERT_EQ(1, results["hits"][0]["highlights"][0]["indices"][1]);
ASSERT_EQ(2, results["hits"][0]["highlights"][0]["indices"][2]);
results = coll_array_text->search("truth", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY,
{false}, 0).get();
ASSERT_EQ(2, results["hits"].size());
ids = {"1", "0"};
for (size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
results = coll_array_text->search("asdadasd", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY,
{false}, 0).get();
ASSERT_EQ(0, results["hits"].size());
query_fields = {"title", "tags"};
results = coll_array_text->search("truth", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY,
{false}, 0).get();
ASSERT_EQ(2, results["hits"].size());
ASSERT_EQ(2, results["hits"][0]["highlights"].size());
ids = {"1", "0"};
for (size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
ASSERT_EQ(4, results["hits"][0]["highlights"][0].size());
ASSERT_STREQ(results["hits"][0]["highlights"][0]["field"].get<std::string>().c_str(), "tags");
ASSERT_EQ(2, results["hits"][0]["highlights"][0]["snippets"].size());
ASSERT_STREQ("<mark>truth</mark>", results["hits"][0]["highlights"][0]["snippets"][0].get<std::string>().c_str());
ASSERT_STREQ("plain <mark>truth</mark>", results["hits"][0]["highlights"][0]["snippets"][1].get<std::string>().c_str());
ASSERT_EQ(2, results["hits"][0]["highlights"][0]["matched_tokens"].size());
ASSERT_STREQ("truth", results["hits"][0]["highlights"][0]["matched_tokens"][0][0].get<std::string>().c_str());
ASSERT_STREQ("truth", results["hits"][0]["highlights"][0]["matched_tokens"][1][0].get<std::string>().c_str());
ASSERT_EQ(2, results["hits"][0]["highlights"][0]["indices"].size());
ASSERT_EQ(1, results["hits"][0]["highlights"][0]["indices"][0]);
ASSERT_EQ(2, results["hits"][0]["highlights"][0]["indices"][1]);
ASSERT_EQ(3, results["hits"][0]["highlights"][1].size());
ASSERT_STREQ("title", results["hits"][0]["highlights"][1]["field"].get<std::string>().c_str());
ASSERT_STREQ("Plain <mark>Truth</mark>", results["hits"][0]["highlights"][1]["snippet"].get<std::string>().c_str());
ASSERT_EQ(1, results["hits"][0]["highlights"][1]["matched_tokens"].size());
ASSERT_STREQ("Truth", results["hits"][0]["highlights"][1]["matched_tokens"][0].get<std::string>().c_str());
ASSERT_EQ(3, results["hits"][1]["highlights"][0].size());
ASSERT_STREQ("title", results["hits"][1]["highlights"][0]["field"].get<std::string>().c_str());
ASSERT_STREQ("The <mark>Truth</mark> About Forever", results["hits"][1]["highlights"][0]["snippet"].get<std::string>().c_str());
ASSERT_EQ(1, results["hits"][1]["highlights"][0]["matched_tokens"].size());
ASSERT_STREQ("Truth", results["hits"][1]["highlights"][0]["matched_tokens"][0].get<std::string>().c_str());
ASSERT_EQ(4, results["hits"][1]["highlights"][1].size());
ASSERT_STREQ(results["hits"][1]["highlights"][1]["field"].get<std::string>().c_str(), "tags");
ASSERT_EQ(2, results["hits"][1]["highlights"][1]["snippets"].size());
ASSERT_STREQ("the <mark>truth</mark>", results["hits"][1]["highlights"][1]["snippets"][0].get<std::string>().c_str());
ASSERT_STREQ("<mark>truth</mark> about", results["hits"][1]["highlights"][1]["snippets"][1].get<std::string>().c_str());
ASSERT_EQ(2, results["hits"][1]["highlights"][1]["matched_tokens"].size());
ASSERT_STREQ("truth", results["hits"][1]["highlights"][1]["matched_tokens"][0][0].get<std::string>().c_str());
ASSERT_STREQ("truth", results["hits"][1]["highlights"][1]["matched_tokens"][1][0].get<std::string>().c_str());
ASSERT_EQ(2, results["hits"][1]["highlights"][1]["indices"].size());
ASSERT_EQ(0, results["hits"][1]["highlights"][1]["indices"][0]);
ASSERT_EQ(2, results["hits"][1]["highlights"][1]["indices"][1]);
// highlight fields must be ordered based on match score
results = coll_array_text->search("amazing movie", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY,
{false}, 0).get();
ASSERT_EQ(1, results["hits"].size());
ASSERT_EQ(2, results["hits"][0]["highlights"].size());
ASSERT_EQ(4, results["hits"][0]["highlights"][0].size());
ASSERT_STREQ("tags", results["hits"][0]["highlights"][0]["field"].get<std::string>().c_str());
ASSERT_STREQ("<mark>amazing</mark> <mark>movie</mark>", results["hits"][0]["highlights"][0]["snippets"][0].get<std::string>().c_str());
ASSERT_EQ(1, results["hits"][0]["highlights"][0]["indices"].size());
ASSERT_EQ(0, results["hits"][0]["highlights"][0]["indices"][0]);
ASSERT_EQ(1, results["hits"][0]["highlights"][0]["matched_tokens"].size());
ASSERT_STREQ("amazing", results["hits"][0]["highlights"][0]["matched_tokens"][0][0].get<std::string>().c_str());
ASSERT_EQ(3, results["hits"][0]["highlights"][1].size());
ASSERT_STREQ(results["hits"][0]["highlights"][1]["field"].get<std::string>().c_str(), "title");
ASSERT_STREQ(results["hits"][0]["highlights"][1]["snippet"].get<std::string>().c_str(),
"<mark>Amazing</mark> Spiderman is <mark>amazing</mark>"); // should highlight duplicating tokens
ASSERT_EQ(2, results["hits"][0]["highlights"][1]["matched_tokens"].size());
ASSERT_STREQ("Amazing", results["hits"][0]["highlights"][1]["matched_tokens"][0].get<std::string>().c_str());
ASSERT_STREQ("amazing", results["hits"][0]["highlights"][1]["matched_tokens"][1].get<std::string>().c_str());
// when query tokens are not found in an array field they should be ignored
results = coll_array_text->search("winds", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY,
{false}, 0).get();
ASSERT_EQ(1, results["hits"].size());
ASSERT_EQ(1, results["hits"][0]["highlights"].size());
collectionManager.drop_collection("coll_array_text");
}
TEST_F(CollectionTest, MultipleFields) {
Collection *coll_mul_fields;
std::ifstream infile(std::string(ROOT_DIR)+"test/multi_field_documents.jsonl");
std::vector<field> fields = {
field("title", field_types::STRING, false),
field("starring", field_types::STRING, false),
field("starring_facet", field_types::STRING, true),
field("cast", field_types::STRING_ARRAY, false),
field("points", field_types::INT32, false)
};
coll_mul_fields = collectionManager.get_collection("coll_mul_fields").get();
if(coll_mul_fields == nullptr) {
coll_mul_fields = collectionManager.create_collection("coll_mul_fields", 4, fields, "points").get();
}
std::string json_line;
while (std::getline(infile, json_line)) {
coll_mul_fields->add(json_line);
}
infile.close();
query_fields = {"title", "starring"};
std::vector<std::string> facets;
nlohmann::json results = coll_mul_fields->search("Will", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(4, results["hits"].size());
std::vector<std::string> ids = {"3", "2", "1", "0"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// when "starring" takes higher priority than "title"
query_fields = {"starring", "title"};
results = coll_mul_fields->search("thomas", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(4, results["hits"].size());
ids = {"15", "12", "13", "14"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
query_fields = {"starring", "title", "cast"};
results = coll_mul_fields->search("ben affleck", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(1, results["hits"].size());
query_fields = {"cast"};
results = coll_mul_fields->search("chris", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(3, results["hits"].size());
ids = {"6", "1", "7"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
query_fields = {"cast"};
results = coll_mul_fields->search("chris pine", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(3, results["hits"].size());
ids = {"7", "6", "1"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// filtering on unfaceted multi-valued string field
query_fields = {"title"};
results = coll_mul_fields->search("captain", query_fields, "cast: chris", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(1, results["hits"].size());
ids = {"6"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// when a token exists in multiple fields of the same document, document and facet should be returned only once
query_fields = {"starring", "title", "cast"};
facets = {"starring_facet"};
results = coll_mul_fields->search("myers", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(1, results["hits"].size());
ids = {"17"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
ASSERT_EQ(1, results["facet_counts"].size());
ASSERT_STREQ("starring_facet", results["facet_counts"][0]["field_name"].get<std::string>().c_str());
size_t facet_count = results["facet_counts"][0]["counts"][0]["count"];
ASSERT_EQ(1, facet_count);
collectionManager.drop_collection("coll_mul_fields");
}
TEST_F(CollectionTest, KeywordQueryReturnsResultsBasedOnPerPageParam) {
Collection *coll_mul_fields;
std::ifstream infile(std::string(ROOT_DIR)+"test/multi_field_documents.jsonl");
std::vector<field> fields = {
field("title", field_types::STRING, false),
field("starring", field_types::STRING, false),
field("starring_facet", field_types::STRING, true),
field("cast", field_types::STRING_ARRAY, false),
field("points", field_types::INT32, false)
};
coll_mul_fields = collectionManager.get_collection("coll_mul_fields").get();
if(coll_mul_fields == nullptr) {
coll_mul_fields = collectionManager.create_collection("coll_mul_fields", 4, fields, "points").get();
}
std::string json_line;
while (std::getline(infile, json_line)) {
coll_mul_fields->add(json_line);
}
infile.close();
query_fields = {"title", "starring"};
std::vector<std::string> facets;
spp::sparse_hash_set<std::string> empty;
nlohmann::json results = coll_mul_fields->search("w", query_fields, "", facets, sort_fields, {0}, 3, 1,
FREQUENCY, {true}, 1000, empty, empty, 10).get();
ASSERT_EQ(3, results["hits"].size());
ASSERT_EQ(7, results["found"].get<int>());
// cannot fetch more than in-built limit of 250
auto res_op = coll_mul_fields->search("w", query_fields, "", facets, sort_fields, {0}, 251, 1,
FREQUENCY, {true}, 1000, empty, empty, 10);
ASSERT_FALSE(res_op.ok());
ASSERT_EQ(422, res_op.code());
ASSERT_STREQ("Only upto 250 hits can be fetched per page.", res_op.error().c_str());
// when page number is not valid
res_op = coll_mul_fields->search("w", query_fields, "", facets, sort_fields, {0}, 10, 0,
FREQUENCY, {true}, 1000, empty, empty, 10);
ASSERT_FALSE(res_op.ok());
ASSERT_EQ(422, res_op.code());
ASSERT_STREQ("Page must be an integer of value greater than 0.", res_op.error().c_str());
// do pagination
results = coll_mul_fields->search("w", query_fields, "", facets, sort_fields, {0}, 3, 1,
FREQUENCY, {true}, 1000, empty, empty, 10).get();
ASSERT_EQ(3, results["hits"].size());
ASSERT_EQ(7, results["found"].get<int>());
results = coll_mul_fields->search("w", query_fields, "", facets, sort_fields, {0}, 3, 2,
FREQUENCY, {true}, 1000, empty, empty, 10).get();
ASSERT_EQ(3, results["hits"].size());
ASSERT_EQ(7, results["found"].get<int>());
results = coll_mul_fields->search("w", query_fields, "", facets, sort_fields, {0}, 3, 3,
FREQUENCY, {true}, 1000, empty, empty, 10).get();
ASSERT_EQ(1, results["hits"].size());
ASSERT_EQ(7, results["found"].get<int>());
collectionManager.drop_collection("coll_mul_fields");
}
std::vector<nlohmann::json> import_res_to_json(const std::vector<std::string>& imported_results) {
std::vector<nlohmann::json> out;
for(const auto& imported_result: imported_results) {
out.emplace_back(nlohmann::json::parse(imported_result));
}
return out;
}
TEST_F(CollectionTest, ImportDocumentsUpsert) {
Collection *coll_mul_fields;
std::ifstream infile(std::string(ROOT_DIR)+"test/multi_field_documents.jsonl");
std::stringstream strstream;
strstream << infile.rdbuf();
infile.close();
std::vector<std::string> import_records;
StringUtils::split(strstream.str(), import_records, "\n");
std::vector<field> fields = {
field("title", field_types::STRING, false),
field("starring", field_types::STRING, true),
field("cast", field_types::STRING_ARRAY, false),
field("points", field_types::INT32, false)
};
coll_mul_fields = collectionManager.get_collection("coll_mul_fields").get();
if(coll_mul_fields == nullptr) {
coll_mul_fields = collectionManager.create_collection("coll_mul_fields", 1, fields, "points").get();
}
// try importing records
nlohmann::json document;
nlohmann::json import_response = coll_mul_fields->add_many(import_records, document);
ASSERT_TRUE(import_response["success"].get<bool>());
ASSERT_EQ(18, import_response["num_imported"].get<int>());
// try searching with filter
auto results = coll_mul_fields->search("*", query_fields, "starring:= [Will Ferrell]", {"starring"}, sort_fields, {0}, 30, 1, FREQUENCY, {false}).get();
ASSERT_EQ(2, results["hits"].size());
// update existing record verbatim
std::vector<std::string> existing_records = {R"({"id": "0", "title": "Wake Up, Ron Burgundy: The Lost Movie"})"};
import_response = coll_mul_fields->add_many(existing_records, document, UPDATE);
ASSERT_TRUE(import_response["success"].get<bool>());
ASSERT_EQ(1, import_response["num_imported"].get<int>());
// update + upsert records
std::vector<std::string> more_records = {R"({"id": "0", "title": "The Fifth Harry", "starring": "Will Ferrell", "points":62, "cast":["Adam McKay","Steve Carell","Paul Rudd"]})",
R"({"id": "2", "cast": ["Chris Fisher", "Rand Alan"], "points":81, "starring":"Daniel Day-Lewis","title":"There Will Be Blood"})",
R"({"id": "18", "title": "Back Again Forest", "points": 45, "starring": "Ronald Wells", "cast": ["Dant Saren"]})",
R"({"id": "6", "points": 77, "cast":["Chris Evans","Scarlett Johansson"], "starring":"Samuel L. Jackson","title":"Captain America: The Winter Soldier"})"};
import_response = coll_mul_fields->add_many(more_records, document, UPSERT);
ASSERT_TRUE(import_response["success"].get<bool>());
ASSERT_EQ(4, import_response["num_imported"].get<int>());
std::vector<nlohmann::json> import_results = import_res_to_json(more_records);
ASSERT_EQ(4, import_results.size());
for(size_t i=0; i<4; i++) {
ASSERT_TRUE(import_results[i]["success"].get<bool>());
ASSERT_EQ(1, import_results[i].size());
}
// try with filters again
results = coll_mul_fields->search("*", query_fields, "starring:= [Will Ferrell]", {"starring"}, sort_fields, {0}, 30, 1, FREQUENCY, {false}).get();
ASSERT_EQ(2, results["hits"].size());
results = coll_mul_fields->search("*", query_fields, "", {"starring"}, sort_fields, {0}, 30, 1, FREQUENCY, {false}).get();
ASSERT_EQ(19, results["hits"].size());
ASSERT_EQ(19, coll_mul_fields->get_num_documents());
results = coll_mul_fields->search("back again forest", query_fields, "", {"starring"}, sort_fields, {0}, 30, 1, FREQUENCY, {false}).get();
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("Back Again Forest", coll_mul_fields->get("18").get()["title"].get<std::string>().c_str());
results = coll_mul_fields->search("fifth", query_fields, "", {"starring"}, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("The <mark>Fifth</mark> Harry", results["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
ASSERT_STREQ("The Woman in the <mark>Fifth</mark> from Kristin", results["hits"][1]["highlights"][0]["snippet"].get<std::string>().c_str());
results = coll_mul_fields->search("burgundy", query_fields, "", {}, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(0, results["hits"].size());
results = coll_mul_fields->search("harry", query_fields, "", {}, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(1, results["hits"].size());
results = coll_mul_fields->search("captain america", query_fields, "", {}, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(1, results["hits"].size());
ASSERT_EQ(77, results["hits"][0]["document"]["points"].get<size_t>());
// upserting with some bad docs
more_records = {R"({"id": "1", "title": "Wake up, Harry", "cast":["Josh Lawson","Chris Parnell"],"points":63,"starring":"Will Ferrell"})",
R"({"id": "90", "cast": ["Kim Werrel", "Random Wake"]})", // missing fields
R"({"id": "5", "points": 60, "cast":["Logan Lerman","Alexandra Daddario"],"starring":"Ron Perlman","starring_facet":"Ron Perlman","title":"Percy Jackson: Sea of Monsters"})",
R"({"id": "24", "starring": "John", "cast": ["John Kim"], "points": 11})"}; // missing fields
import_response = coll_mul_fields->add_many(more_records, document, UPSERT);
ASSERT_FALSE(import_response["success"].get<bool>());
ASSERT_EQ(2, import_response["num_imported"].get<int>());
import_results = import_res_to_json(more_records);
ASSERT_FALSE(import_results[1]["success"].get<bool>());
ASSERT_FALSE(import_results[3]["success"].get<bool>());
ASSERT_STREQ("Field `points` has been declared as a default sorting field, but is not found in the document.", import_results[1]["error"].get<std::string>().c_str());
ASSERT_STREQ("Field `title` has been declared in the schema, but is not found in the document.", import_results[3]["error"].get<std::string>().c_str());
// try to duplicate records without upsert option
more_records = {R"({"id": "1", "title": "Wake up, Harry"})",
R"({"id": "5", "points": 60})"};
import_response = coll_mul_fields->add_many(more_records, document, CREATE);
ASSERT_FALSE(import_response["success"].get<bool>());
ASSERT_EQ(0, import_response["num_imported"].get<int>());
import_results = import_res_to_json(more_records);
ASSERT_FALSE(import_results[0]["success"].get<bool>());
ASSERT_FALSE(import_results[1]["success"].get<bool>());
ASSERT_STREQ("A document with id 1 already exists.", import_results[0]["error"].get<std::string>().c_str());
ASSERT_STREQ("A document with id 5 already exists.", import_results[1]["error"].get<std::string>().c_str());
// update document with verbatim fields, except for points
more_records = {R"({"id": "3", "cast":["Matt Damon","Ben Affleck","Minnie Driver"],
"points":70,"starring":"Robin Williams","starring_facet":"Robin Williams",
"title":"Good Will Hunting"})"};
import_response = coll_mul_fields->add_many(more_records, document, UPDATE);
ASSERT_TRUE(import_response["success"].get<bool>());
ASSERT_EQ(1, import_response["num_imported"].get<int>());
results = coll_mul_fields->search("Good Will Hunting", query_fields, "", {"starring"}, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(70, results["hits"][0]["document"]["points"].get<uint32_t>());
// updating a document that does not exist should fail, others should succeed
more_records = {R"({"id": "20", "points": 51})",
R"({"id": "1", "points": 64})"};
import_response = coll_mul_fields->add_many(more_records, document, UPDATE);
ASSERT_FALSE(import_response["success"].get<bool>());
ASSERT_EQ(1, import_response["num_imported"].get<int>());
import_results = import_res_to_json(more_records);
ASSERT_FALSE(import_results[0]["success"].get<bool>());
ASSERT_TRUE(import_results[1]["success"].get<bool>());
ASSERT_STREQ("Could not find a document with id: 20", import_results[0]["error"].get<std::string>().c_str());
ASSERT_EQ(404, import_results[0]["code"].get<size_t>());
results = coll_mul_fields->search("wake up harry", query_fields, "", {"starring"}, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(64, results["hits"][0]["document"]["points"].get<uint32_t>());
// trying to create documents with existing IDs should fail
more_records = {R"({"id": "2", "points": 51})",
R"({"id": "1", "points": 64})"};
import_response = coll_mul_fields->add_many(more_records, document, CREATE);
ASSERT_FALSE(import_response["success"].get<bool>());
ASSERT_EQ(0, import_response["num_imported"].get<int>());
import_results = import_res_to_json(more_records);
ASSERT_FALSE(import_results[0]["success"].get<bool>());
ASSERT_FALSE(import_results[1]["success"].get<bool>());
ASSERT_STREQ("A document with id 2 already exists.", import_results[0]["error"].get<std::string>().c_str());
ASSERT_STREQ("A document with id 1 already exists.", import_results[1]["error"].get<std::string>().c_str());
ASSERT_EQ(409, import_results[0]["code"].get<size_t>());
ASSERT_EQ(409, import_results[1]["code"].get<size_t>());
}
TEST_F(CollectionTest, ImportDocumentsUpsertOptional) {
Collection *coll1;
std::vector<field> fields = {
field("title", field_types::STRING_ARRAY, false, true),
field("points", field_types::INT32, false)
};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
std::vector<std::string> records;
size_t NUM_RECORDS = 1000;
for(size_t i=0; i<NUM_RECORDS; i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["points"] = i;
records.push_back(doc.dump());
}
// import records without title
nlohmann::json document;
nlohmann::json import_response = coll1->add_many(records, document, CREATE);
ASSERT_TRUE(import_response["success"].get<bool>());
ASSERT_EQ(1000, import_response["num_imported"].get<int>());
// upsert documents with title
records.clear();
for(size_t i=0; i<NUM_RECORDS; i++) {
nlohmann::json updoc;
updoc["id"] = std::to_string(i);
updoc["points"] = i;
updoc["title"] = {
get_text(10),
get_text(10),
get_text(10),
get_text(10),
};
records.push_back(updoc.dump());
}
auto begin = std::chrono::high_resolution_clock::now();
import_response = coll1->add_many(records, document, UPSERT);
auto time_micros = std::chrono::duration_cast<std::chrono::microseconds>(
std::chrono::high_resolution_clock::now() - begin).count();
//LOG(INFO) << "Time taken for first upsert: " << time_micros;
ASSERT_TRUE(import_response["success"].get<bool>());
ASSERT_EQ(1000, import_response["num_imported"].get<int>());
// run upsert again with title override
records.clear();
for(size_t i=0; i<NUM_RECORDS; i++) {
nlohmann::json updoc;
updoc["id"] = std::to_string(i);
updoc["points"] = i;
updoc["title"] = {
get_text(10),
get_text(10),
get_text(10),
get_text(10),
};
records.push_back(updoc.dump());
}
begin = std::chrono::high_resolution_clock::now();
import_response = coll1->add_many(records, document, UPSERT);
time_micros = std::chrono::duration_cast<std::chrono::microseconds>(
std::chrono::high_resolution_clock::now() - begin).count();
//LOG(INFO) << "Time taken for second upsert: " << time_micros;
ASSERT_TRUE(import_response["success"].get<bool>());
ASSERT_EQ(1000, import_response["num_imported"].get<int>());
// update records (can contain partial fields)
records.clear();
for(size_t i=0; i<NUM_RECORDS; i++) {
nlohmann::json updoc;
updoc["id"] = std::to_string(i);
// no points field
updoc["title"] = {
get_text(10),
get_text(10),
get_text(10),
get_text(10),
};
records.push_back(updoc.dump());
}
import_response = coll1->add_many(records, document, UPDATE);
ASSERT_TRUE(import_response["success"].get<bool>());
ASSERT_EQ(1000, import_response["num_imported"].get<int>());
}
TEST_F(CollectionTest, ImportDocuments) {
Collection *coll_mul_fields;
std::ifstream infile(std::string(ROOT_DIR)+"test/multi_field_documents.jsonl");
std::stringstream strstream;
strstream << infile.rdbuf();
infile.close();
std::vector<std::string> import_records;
StringUtils::split(strstream.str(), import_records, "\n");
std::vector<field> fields = {
field("title", field_types::STRING, false),
field("starring", field_types::STRING, false),
field("cast", field_types::STRING_ARRAY, false),
field("points", field_types::INT32, false)
};
coll_mul_fields = collectionManager.get_collection("coll_mul_fields").get();
if(coll_mul_fields == nullptr) {
coll_mul_fields = collectionManager.create_collection("coll_mul_fields", 4, fields, "points").get();
}
// try importing records
nlohmann::json document;
nlohmann::json import_response = coll_mul_fields->add_many(import_records, document);
ASSERT_TRUE(import_response["success"].get<bool>());
ASSERT_EQ(18, import_response["num_imported"].get<int>());
// now try searching for records
query_fields = {"title", "starring"};
std::vector<std::string> facets;
auto x = coll_mul_fields->search("Will", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false});
nlohmann::json results = coll_mul_fields->search("Will", query_fields, "", facets, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(4, results["hits"].size());
std::vector<std::string> ids = {"3", "2", "1", "0"};
for(size_t i = 0; i < results["hits"].size(); i++) {
nlohmann::json result = results["hits"].at(i);
std::string result_id = result["document"]["id"];
std::string id = ids.at(i);
ASSERT_STREQ(id.c_str(), result_id.c_str());
}
// verify that empty import is handled gracefully
std::vector<std::string> empty_records;
import_response = coll_mul_fields->add_many(empty_records, document);
ASSERT_TRUE(import_response["success"].get<bool>());
ASSERT_EQ(0, import_response["num_imported"].get<int>());
// verify that only bad records are rejected, rest must be imported (records 2 and 4 are bad)
std::vector<std::string> more_records = {"{\"id\": \"id1\", \"title\": \"Test1\", \"starring\": \"Rand Fish\", \"points\": 12, "
"\"cast\": [\"Tom Skerritt\"] }",
"{\"title\": 123, \"starring\": \"Jazz Gosh\", \"points\": 23, "
"\"cast\": [\"Tom Skerritt\"] }",
"{\"title\": \"Test3\", \"starring\": \"Brad Fin\", \"points\": 11, "
"\"cast\": [\"Tom Skerritt\"] }",
"{\"title\": \"Test4\", \"points\": 55, "
"\"cast\": [\"Tom Skerritt\"] }"};
import_response = coll_mul_fields->add_many(more_records, document, CREATE, "", DIRTY_VALUES::REJECT);
ASSERT_FALSE(import_response["success"].get<bool>());
ASSERT_EQ(2, import_response["num_imported"].get<int>());
std::vector<nlohmann::json> import_results = import_res_to_json(more_records);
ASSERT_EQ(4, import_results.size());
ASSERT_TRUE(import_results[0]["success"].get<bool>());
ASSERT_FALSE(import_results[1]["success"].get<bool>());
ASSERT_TRUE(import_results[2]["success"].get<bool>());
ASSERT_FALSE(import_results[3]["success"].get<bool>());
ASSERT_STREQ("Field `title` must be a string.", import_results[1]["error"].get<std::string>().c_str());
ASSERT_STREQ("Field `starring` has been declared in the schema, but is not found in the document.",
import_results[3]["error"].get<std::string>().c_str());
ASSERT_STREQ("{\"title\": 123, \"starring\": \"Jazz Gosh\", \"points\": 23, \"cast\": [\"Tom Skerritt\"] }",
import_results[1]["document"].get<std::string>().c_str());
// record with duplicate IDs
more_records = {"{\"id\": \"id2\", \"title\": \"Test1\", \"starring\": \"Rand Fish\", \"points\": 12, "
"\"cast\": [\"Tom Skerritt\"] }",
"{\"id\": \"id1\", \"title\": \"Test1\", \"starring\": \"Rand Fish\", \"points\": 12, "
"\"cast\": [\"Tom Skerritt\"] }"};
import_response = coll_mul_fields->add_many(more_records, document);
ASSERT_FALSE(import_response["success"].get<bool>());
ASSERT_EQ(1, import_response["num_imported"].get<int>());
import_results = import_res_to_json(more_records);
ASSERT_EQ(2, import_results.size());
ASSERT_TRUE(import_results[0]["success"].get<bool>());
ASSERT_FALSE(import_results[1]["success"].get<bool>());
ASSERT_STREQ("A document with id id1 already exists.", import_results[1]["error"].get<std::string>().c_str());
ASSERT_STREQ("{\"id\": \"id1\", \"title\": \"Test1\", \"starring\": \"Rand Fish\", \"points\": 12, "
"\"cast\": [\"Tom Skerritt\"] }",import_results[1]["document"].get<std::string>().c_str());
// handle bad import json
// valid JSON but not a document
more_records = {"[]"};
import_response = coll_mul_fields->add_many(more_records, document);
ASSERT_FALSE(import_response["success"].get<bool>());
ASSERT_EQ(0, import_response["num_imported"].get<int>());
import_results = import_res_to_json(more_records);
ASSERT_EQ(1, import_results.size());
ASSERT_EQ(false, import_results[0]["success"].get<bool>());
ASSERT_STREQ("Bad JSON: not a properly formed document.", import_results[0]["error"].get<std::string>().c_str());
ASSERT_STREQ("[]", import_results[0]["document"].get<std::string>().c_str());
// invalid JSON
more_records = {"{"};
import_response = coll_mul_fields->add_many(more_records, document);
ASSERT_FALSE(import_response["success"].get<bool>());
ASSERT_EQ(0, import_response["num_imported"].get<int>());
import_results = import_res_to_json(more_records);
ASSERT_EQ(1, import_results.size());
ASSERT_EQ(false, import_results[0]["success"].get<bool>());
ASSERT_STREQ("Bad JSON: [json.exception.parse_error.101] parse error at line 1, column 2: syntax error "
"while parsing object key - unexpected end of input; expected string literal",
import_results[0]["error"].get<std::string>().c_str());
ASSERT_STREQ("{", import_results[0]["document"].get<std::string>().c_str());
collectionManager.drop_collection("coll_mul_fields");
}
TEST_F(CollectionTest, SearchingWithMissingFields) {
// return error without crashing when searching for fields that do not conform to the schema
Collection *coll_array_fields;
std::ifstream infile(std::string(ROOT_DIR)+"test/numeric_array_documents.jsonl");
std::vector<field> fields = {field("name", field_types::STRING, false),
field("age", field_types::INT32, false),
field("years", field_types::INT32_ARRAY, false),
field("timestamps", field_types::INT64_ARRAY, false),
field("tags", field_types::STRING_ARRAY, true)};
std::vector<sort_by> sort_fields = { sort_by("age", "DESC") };
coll_array_fields = collectionManager.get_collection("coll_array_fields").get();
if(coll_array_fields == nullptr) {
coll_array_fields = collectionManager.create_collection("coll_array_fields", 4, fields, "age").get();
}
std::string json_line;
while (std::getline(infile, json_line)) {
coll_array_fields->add(json_line);
}
infile.close();
// when a query field mentioned in schema does not exist
std::vector<std::string> facets;
std::vector<std::string> query_fields_not_found = {"titlez"};
Option<nlohmann::json> res_op = coll_array_fields->search("the", query_fields_not_found, "", facets, sort_fields, {0}, 10);
ASSERT_FALSE(res_op.ok());
ASSERT_EQ(404, res_op.code());
ASSERT_STREQ("Could not find a field named `titlez` in the schema.", res_op.error().c_str());
// when a query field is an integer field
res_op = coll_array_fields->search("the", {"age"}, "", facets, sort_fields, {0}, 10);
ASSERT_EQ(400, res_op.code());
ASSERT_STREQ("Field `age` should be a string or a string array.", res_op.error().c_str());
// when a facet field is not defined in the schema
res_op = coll_array_fields->search("the", {"name"}, "", {"timestamps"}, sort_fields, {0}, 10);
ASSERT_EQ(404, res_op.code());
ASSERT_STREQ("Could not find a facet field named `timestamps` in the schema.", res_op.error().c_str());
// when a rank field is not defined in the schema
res_op = coll_array_fields->search("the", {"name"}, "", {}, { sort_by("timestamps", "ASC") }, {0}, 10);
ASSERT_EQ(404, res_op.code());
ASSERT_STREQ("Could not find a field named `timestamps` in the schema for sorting.", res_op.error().c_str());
res_op = coll_array_fields->search("the", {"name"}, "", {}, { sort_by("_rank", "ASC") }, {0}, 10);
ASSERT_EQ(404, res_op.code());
ASSERT_STREQ("Could not find a field named `_rank` in the schema for sorting.", res_op.error().c_str());
collectionManager.drop_collection("coll_array_fields");
}
TEST_F(CollectionTest, IndexingWithBadData) {
// should not crash when document to-be-indexed doesn't match schema
Collection *sample_collection;
std::vector<field> fields = {field("name", field_types::STRING, false),
field("tags", field_types::STRING_ARRAY, true),
field("age", field_types::INT32, false),
field("average", field_types::INT32, false) };
std::vector<sort_by> sort_fields = { sort_by("age", "DESC"), sort_by("average", "DESC") };
sample_collection = collectionManager.get_collection("sample_collection").get();
if(sample_collection == nullptr) {
sample_collection = collectionManager.create_collection("sample_collection", 4, fields, "age").get();
}
const Option<nlohmann::json> & search_fields_missing_op1 = sample_collection->add("{\"name\": \"foo\", \"age\": 29, \"average\": 78}");
ASSERT_FALSE(search_fields_missing_op1.ok());
ASSERT_STREQ("Field `tags` has been declared in the schema, but is not found in the document.",
search_fields_missing_op1.error().c_str());
const Option<nlohmann::json> & search_fields_missing_op2 = sample_collection->add("{\"namez\": \"foo\", \"tags\": [], \"age\": 34, \"average\": 78}");
ASSERT_FALSE(search_fields_missing_op2.ok());
ASSERT_STREQ("Field `name` has been declared in the schema, but is not found in the document.",
search_fields_missing_op2.error().c_str());
const Option<nlohmann::json> & facet_fields_missing_op1 = sample_collection->add("{\"name\": \"foo\", \"age\": 34, \"average\": 78}");
ASSERT_FALSE(facet_fields_missing_op1.ok());
ASSERT_STREQ("Field `tags` has been declared in the schema, but is not found in the document.",
facet_fields_missing_op1.error().c_str());
const char *doc_str = "{\"name\": \"foo\", \"age\": 34, \"avg\": 78, \"tags\": [\"red\", \"blue\"]}";
const Option<nlohmann::json> & sort_fields_missing_op1 = sample_collection->add(doc_str);
ASSERT_FALSE(sort_fields_missing_op1.ok());
ASSERT_STREQ("Field `average` has been declared in the schema, but is not found in the document.",
sort_fields_missing_op1.error().c_str());
// Handle type errors
doc_str = "{\"name\": \"foo\", \"age\": 34, \"tags\": 22, \"average\": 78}";
const Option<nlohmann::json> & bad_facet_field_op = sample_collection->add(doc_str);
ASSERT_FALSE(bad_facet_field_op.ok());
ASSERT_STREQ("Field `tags` must be an array.", bad_facet_field_op.error().c_str());
doc_str = "{\"name\": \"foo\", \"age\": 34, \"tags\": [\"red\", 22], \"average\": 78}";
const Option<nlohmann::json> & bad_array_field_op = sample_collection->add(doc_str, CREATE, "",
DIRTY_VALUES::REJECT);
ASSERT_FALSE(bad_array_field_op.ok());
ASSERT_STREQ("Field `tags` must be an array of string.", bad_array_field_op.error().c_str());
// with coercion should work
doc_str = "{\"name\": \"foo\", \"age\": 34, \"tags\": [\"red\", 22], \"average\": 78}";
const Option<nlohmann::json> &bad_array_field_coercion_op = sample_collection->add(doc_str, CREATE, "",
DIRTY_VALUES::COERCE_OR_REJECT);
ASSERT_TRUE(bad_array_field_coercion_op.ok());
doc_str = "{\"name\": \"foo\", \"age\": 34, \"tags\": [], \"average\": 34}";
const Option<nlohmann::json> & empty_facet_field_op = sample_collection->add(doc_str);
ASSERT_TRUE(empty_facet_field_op.ok());
doc_str = "{\"name\": \"foo\", \"age\": [\"34\"], \"tags\": [], \"average\": 34 }";
const Option<nlohmann::json> & bad_default_sorting_field_op1 = sample_collection->add(doc_str);
ASSERT_FALSE(bad_default_sorting_field_op1.ok());
ASSERT_STREQ("Field `age` must be an int32.", bad_default_sorting_field_op1.error().c_str());
doc_str = "{\"name\": \"foo\", \"tags\": [], \"average\": 34 }";
const Option<nlohmann::json> & bad_default_sorting_field_op3 = sample_collection->add(doc_str);
ASSERT_FALSE(bad_default_sorting_field_op3.ok());
ASSERT_STREQ("Field `age` has been declared as a default sorting field, but is not found in the document.",
bad_default_sorting_field_op3.error().c_str());
doc_str = "{\"name\": \"foo\", \"age\": 34, \"tags\": [], \"average\": \"34\"}";
const Option<nlohmann::json> & bad_rank_field_op = sample_collection->add(doc_str, CREATE, "", DIRTY_VALUES::REJECT);
ASSERT_FALSE(bad_rank_field_op.ok());
ASSERT_STREQ("Field `average` must be an int32.", bad_rank_field_op.error().c_str());
doc_str = "{\"name\": \"foo\", \"age\": asdadasd, \"tags\": [], \"average\": 34 }";
const Option<nlohmann::json> & bad_default_sorting_field_op4 = sample_collection->add(doc_str);
ASSERT_FALSE(bad_default_sorting_field_op4.ok());
ASSERT_STREQ("Bad JSON: [json.exception.parse_error.101] parse error at line 1, column 24: syntax error "
"while parsing value - invalid literal; last read: '\"age\": a'",
bad_default_sorting_field_op4.error().c_str());
// should return an error when a document with pre-existing id is being added
std::string doc = "{\"id\": \"100\", \"name\": \"foo\", \"age\": 29, \"tags\": [], \"average\": 78}";
Option<nlohmann::json> add_op = sample_collection->add(doc);
ASSERT_TRUE(add_op.ok());
add_op = sample_collection->add(doc);
ASSERT_FALSE(add_op.ok());
ASSERT_EQ(409, add_op.code());
ASSERT_STREQ("A document with id 100 already exists.", add_op.error().c_str());
collectionManager.drop_collection("sample_collection");
}
TEST_F(CollectionTest, EmptyIndexShouldNotCrash) {
Collection *empty_coll;
std::vector<field> fields = {field("name", field_types::STRING, false),
field("tags", field_types::STRING_ARRAY, false),
field("age", field_types::INT32, false),
field("average", field_types::INT32, false)};
std::vector<sort_by> sort_fields = { sort_by("age", "DESC"), sort_by("average", "DESC") };
empty_coll = collectionManager.get_collection("empty_coll").get();
if(empty_coll == nullptr) {
empty_coll = collectionManager.create_collection("empty_coll", 4, fields, "age").get();
}
nlohmann::json results = empty_coll->search("a", {"name"}, "", {}, sort_fields, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(0, results["hits"].size());
collectionManager.drop_collection("empty_coll");
}
TEST_F(CollectionTest, IdFieldShouldBeAString) {
Collection *coll1;
std::vector<field> fields = {field("name", field_types::STRING, false),
field("tags", field_types::STRING_ARRAY, false),
field("age", field_types::INT32, false),
field("average", field_types::INT32, false)};
std::vector<sort_by> sort_fields = { sort_by("age", "DESC"), sort_by("average", "DESC") };
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "age").get();
}
nlohmann::json doc;
doc["id"] = 101010;
doc["name"] = "Jane";
doc["age"] = 25;
doc["average"] = 98;
doc["tags"] = nlohmann::json::array();
doc["tags"].push_back("tag1");
Option<nlohmann::json> inserted_id_op = coll1->add(doc.dump());
ASSERT_FALSE(inserted_id_op.ok());
ASSERT_STREQ("Document's `id` field should be a string.", inserted_id_op.error().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, AnIntegerCanBePassedToAFloatField) {
Collection *coll1;
std::vector<field> fields = {field("name", field_types::STRING, false),
field("average", field_types::FLOAT, false)};
std::vector<sort_by> sort_fields = { sort_by("average", "DESC") };
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "average").get();
}
nlohmann::json doc;
doc["id"] = "101010";
doc["name"] = "Jane";
doc["average"] = 98;
Option<nlohmann::json> inserted_id_op = coll1->add(doc.dump());
EXPECT_TRUE(inserted_id_op.ok());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, DeletionOfADocument) {
collectionManager.drop_collection("collection");
std::ifstream infile(std::string(ROOT_DIR)+"test/documents.jsonl");
std::vector<field> search_fields = {field("title", field_types::STRING, false),
field("points", field_types::INT32, false)};
std::vector<std::string> query_fields = {"title"};
std::vector<sort_by> sort_fields = { sort_by("points", "DESC") };
Collection *collection_for_del;
collection_for_del = collectionManager.get_collection("collection_for_del").get();
if(collection_for_del == nullptr) {
collection_for_del = collectionManager.create_collection("collection_for_del", 4, search_fields, "points").get();
}
std::string json_line;
rocksdb::Iterator* it;
size_t num_keys = 0;
// dummy record for record id 0: to make the test record IDs to match with line numbers
json_line = "{\"points\":10,\"title\":\"z\"}";
collection_for_del->add(json_line);
while (std::getline(infile, json_line)) {
collection_for_del->add(json_line);
}
ASSERT_EQ(25, collection_for_del->get_num_documents());
infile.close();
nlohmann::json results;
// asserts before removing any record
results = collection_for_del->search("cryogenic", query_fields, "", {}, sort_fields, {0}, 5, 1, FREQUENCY, {false}).get();
ASSERT_EQ(1, results["hits"].size());
it = store->get_iterator();
num_keys = 0;
for (it->SeekToFirst(); it->Valid(); it->Next()) {
num_keys += 1;
}
ASSERT_EQ(25+25+3, num_keys); // 25 records, 25 id mapping, 3 meta keys
delete it;
// actually remove a record now
collection_for_del->remove("1");
results = collection_for_del->search("cryogenic", query_fields, "", {}, sort_fields, {0}, 5, 1, FREQUENCY, {false}).get();
ASSERT_EQ(0, results["hits"].size());
ASSERT_EQ(0, results["found"]);
results = collection_for_del->search("archives", query_fields, "", {}, sort_fields, {0}, 5, 1, FREQUENCY, {false}).get();
ASSERT_EQ(1, results["hits"].size());
ASSERT_EQ(1, results["found"]);
collection_for_del->remove("foo"); // custom id record
results = collection_for_del->search("martian", query_fields, "", {}, sort_fields, {0}, 5, 1, FREQUENCY, {false}).get();
ASSERT_EQ(0, results["hits"].size());
ASSERT_EQ(0, results["found"]);
// delete all records
for(int id = 0; id <= 25; id++) {
collection_for_del->remove(std::to_string(id));
}
ASSERT_EQ(0, collection_for_del->get_num_documents());
it = store->get_iterator();
num_keys = 0;
for (it->SeekToFirst(); it->Valid(); it->Next()) {
num_keys += 1;
}
delete it;
ASSERT_EQ(3, num_keys);
collectionManager.drop_collection("collection_for_del");
}
TEST_F(CollectionTest, DeletionOfDocumentSingularFields) {
Collection *coll1;
std::vector<field> fields = {field("str", field_types::STRING, false),
field("int32", field_types::INT32, false),
field("int64", field_types::INT64, false),
field("float", field_types::FLOAT, false),
field("bool", field_types::BOOL, false)};
std::vector<sort_by> sort_fields = { sort_by("int32", "DESC") };
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "int32").get();
}
nlohmann::json doc;
doc["id"] = "100";
doc["str"] = "[NEW] Cell Phone Cases, Holders & Clips!";
doc["int32"] = 100032;
doc["int64"] = 1582369739000;
doc["float"] = -293.24;
doc["bool"] = true;
Option<nlohmann::json> add_op = coll1->add(doc.dump());
ASSERT_TRUE(add_op.ok());
nlohmann::json res = coll1->search("phone", {"str"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10).get();
ASSERT_EQ(1, res["found"]);
Option<std::string> rem_op = coll1->remove("100");
ASSERT_TRUE(rem_op.ok());
res = coll1->search("phone", {"str"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10).get();
ASSERT_EQ(0, res["found"].get<int32_t>());
// also assert against the actual index
Index *index = coll1->_get_indexes()[0]; // seq id will always be zero for first document
auto search_index = index->_get_search_index();
auto numerical_index = index->_get_numerical_index();
auto str_tree = search_index["str"];
auto int32_tree = numerical_index["int32"];
auto int64_tree = numerical_index["int64"];
auto float_tree = numerical_index["float"];
auto bool_tree = numerical_index["bool"];
ASSERT_EQ(0, art_size(str_tree));
ASSERT_EQ(0, int32_tree->size());
ASSERT_EQ(0, int64_tree->size());
ASSERT_EQ(0, float_tree->size());
ASSERT_EQ(0, bool_tree->size());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, DeletionOfDocumentArrayFields) {
Collection *coll1;
std::vector<field> fields = {field("strarray", field_types::STRING_ARRAY, false),
field("int32array", field_types::INT32_ARRAY, false),
field("int64array", field_types::INT64_ARRAY, false),
field("floatarray", field_types::FLOAT_ARRAY, false),
field("boolarray", field_types::BOOL_ARRAY, false),
field("points", field_types::INT32, false)};
std::vector<sort_by> sort_fields = { sort_by("points", "DESC") };
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "100";
doc["strarray"] = {"Cell Phones", "Cell Phone Accessories", "Cell Phone Cases & Clips"};
doc["int32array"] = {100, 200, 300};
doc["int64array"] = {1582369739000, 1582369739000, 1582369739000};
doc["floatarray"] = {19.99, 400.999};
doc["boolarray"] = {true, false, true};
doc["points"] = 25;
Option<nlohmann::json> add_op = coll1->add(doc.dump());
ASSERT_TRUE(add_op.ok());
nlohmann::json res = coll1->search("phone", {"strarray"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10).get();
ASSERT_EQ(1, res["found"]);
Option<std::string> rem_op = coll1->remove("100");
ASSERT_TRUE(rem_op.ok());
res = coll1->search("phone", {"strarray"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10).get();
ASSERT_EQ(0, res["found"].get<int32_t>());
// also assert against the actual index
Index *index = coll1->_get_indexes()[0]; // seq id will always be zero for first document
auto search_index = index->_get_search_index();
auto numerical_index = index->_get_numerical_index();
auto strarray_tree = search_index["strarray"];
auto int32array_tree = numerical_index["int32array"];
auto int64array_tree = numerical_index["int64array"];
auto floatarray_tree = numerical_index["floatarray"];
auto boolarray_tree = numerical_index["boolarray"];
ASSERT_EQ(0, art_size(strarray_tree));
ASSERT_EQ(0, int32array_tree->size());
ASSERT_EQ(0, int64array_tree->size());
ASSERT_EQ(0, floatarray_tree->size());
ASSERT_EQ(0, boolarray_tree->size());
collectionManager.drop_collection("coll1");
}
nlohmann::json get_prune_doc() {
nlohmann::json document;
document["one"] = 1;
document["two"] = 2;
document["three"] = 3;
document["four"] = 4;
return document;
}
TEST_F(CollectionTest, SearchLargeTextField) {
Collection *coll_large_text;
std::vector<field> fields = {field("text", field_types::STRING, false),
field("age", field_types::INT32, false),
};
std::vector<sort_by> sort_fields = { sort_by(sort_field_const::text_match, "DESC"), sort_by("age", "DESC") };
coll_large_text = collectionManager.get_collection("coll_large_text").get();
if(coll_large_text == nullptr) {
coll_large_text = collectionManager.create_collection("coll_large_text", 4, fields, "age").get();
}
std::string json_line;
std::ifstream infile(std::string(ROOT_DIR)+"test/large_text_field.jsonl");
while (std::getline(infile, json_line)) {
coll_large_text->add(json_line);
}
infile.close();
Option<nlohmann::json> res_op = coll_large_text->search("eguilazer", {"text"}, "", {}, sort_fields, {0}, 10);
ASSERT_TRUE(res_op.ok());
nlohmann::json results = res_op.get();
ASSERT_EQ(1, results["hits"].size());
res_op = coll_large_text->search("tristique", {"text"}, "", {}, sort_fields, {0}, 10);
ASSERT_TRUE(res_op.ok());
results = res_op.get();
ASSERT_EQ(2, results["hits"].size());
// query whose length exceeds maximum highlight window (match score's WINDOW_SIZE)
res_op = coll_large_text->search(
"Phasellus non tristique elit Praesent non arcu id lectus accumsan venenatis at",
{"text"}, "", {}, sort_fields, {0}, 10
);
ASSERT_TRUE(res_op.ok());
results = res_op.get();
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("1", results["hits"][0]["document"]["id"].get<std::string>().c_str());
// only single matched token in match window
res_op = coll_large_text->search("molestie maecenas accumsan", {"text"}, "", {}, sort_fields, {0}, 10);
ASSERT_TRUE(res_op.ok());
results = res_op.get();
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("non arcu id lectus <mark>accumsan</mark> venenatis at at justo.",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
collectionManager.drop_collection("coll_large_text");
}
TEST_F(CollectionTest, PruneFieldsFromDocument) {
nlohmann::json document = get_prune_doc();
Collection::prune_document(document, {"one", "two"}, spp::sparse_hash_set<std::string>());
ASSERT_EQ(2, document.size());
ASSERT_EQ(1, document["one"]);
ASSERT_EQ(2, document["two"]);
// exclude takes precedence
document = get_prune_doc();
Collection::prune_document(document, {"one"}, {"one"});
ASSERT_EQ(0, document.size());
// when no inclusion is specified, should return all fields not mentioned by exclusion list
document = get_prune_doc();
Collection::prune_document(document, spp::sparse_hash_set<std::string>(), {"three"});
ASSERT_EQ(3, document.size());
ASSERT_EQ(1, document["one"]);
ASSERT_EQ(2, document["two"]);
ASSERT_EQ(4, document["four"]);
document = get_prune_doc();
Collection::prune_document(document, spp::sparse_hash_set<std::string>(), spp::sparse_hash_set<std::string>());
ASSERT_EQ(4, document.size());
// when included field does not exist
document = get_prune_doc();
Collection::prune_document(document, {"notfound"}, spp::sparse_hash_set<std::string>());
ASSERT_EQ(0, document.size());
// when excluded field does not exist
document = get_prune_doc();
Collection::prune_document(document, spp::sparse_hash_set<std::string>(), {"notfound"});
ASSERT_EQ(4, document.size());
}
TEST_F(CollectionTest, StringArrayFieldShouldNotAllowPlainString) {
Collection *coll1;
std::vector<field> fields = {field("categories", field_types::STRING_ARRAY, true),
field("points", field_types::INT32, false)};
std::vector<sort_by> sort_fields = {sort_by("points", "DESC")};
coll1 = collectionManager.get_collection("coll1").get();
if (coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "100";
doc["categories"] = "Should not be allowed!";
doc["points"] = 25;
auto add_op = coll1->add(doc.dump());
ASSERT_FALSE(add_op.ok());
ASSERT_STREQ("Field `categories` must be an array.", add_op.error().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, SearchHighlightShouldFollowThreshold) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, true),
field("points", field_types::INT32, false)};
std::vector<sort_by> sort_fields = {sort_by("points", "DESC")};
coll1 = collectionManager.get_collection("coll1").get();
if (coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "100";
doc["title"] = "The quick brown fox jumped over the lazy dog and ran straight to the forest to sleep.";
doc["points"] = 25;
auto add_op = coll1->add(doc.dump());
ASSERT_TRUE(add_op.ok());
// first with a large threshold
auto res = coll1->search("lazy", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "").get();
ASSERT_STREQ("The quick brown fox jumped over the <mark>lazy</mark> dog and ran straight to the forest to sleep.",
res["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
// now with with a small threshold (will show only 4 words either side of the matched token)
res = coll1->search("lazy", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5).get();
ASSERT_STREQ("fox jumped over the <mark>lazy</mark> dog and ran straight",
res["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
// specify the number of surrounding tokens to return
size_t highlight_affix_num_tokens = 2;
res = coll1->search("lazy", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, highlight_affix_num_tokens).get();
ASSERT_STREQ("over the <mark>lazy</mark> dog and",
res["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
highlight_affix_num_tokens = 0;
res = coll1->search("lazy", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, highlight_affix_num_tokens).get();
ASSERT_STREQ("<mark>lazy</mark>",
res["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, SearchHighlightShouldUseHighlightTags) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, true),
field("points", field_types::INT32, false)};
std::vector<sort_by> sort_fields = {sort_by("points", "DESC")};
coll1 = collectionManager.get_collection("coll1").get();
if (coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "100";
doc["title"] = "The quick brown fox jumped over the lazy fox. "; // adding some extra spaces
doc["points"] = 25;
auto add_op = coll1->add(doc.dump());
ASSERT_TRUE(add_op.ok());
// use non-default highlighting tags
auto res = coll1->search("lazy", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<em class=\"h\">", "</em>").get();
ASSERT_STREQ("The quick brown fox jumped over the <em class=\"h\">lazy</em> fox. ",
res["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, SearchHighlightWithNewLine) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, true),
field("points", field_types::INT32, false)};
std::vector<sort_by> sort_fields = {sort_by("points", "DESC")};
coll1 = collectionManager.get_collection("coll1").get();
if (coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "100";
doc["title"] = "Blah, blah\nStark Industries";
doc["points"] = 25;
auto add_op = coll1->add(doc.dump());
ASSERT_TRUE(add_op.ok());
auto res = coll1->search("stark", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0).get();
ASSERT_STREQ("Blah, blah\n<mark>Stark</mark> Industries",
res["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
ASSERT_STREQ("Stark", res["hits"][0]["highlights"][0]["matched_tokens"][0].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, UpdateDocument) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, true),
field("tags", field_types::STRING_ARRAY, true, true),
field("points", field_types::INT32, false)};
std::vector<sort_by> sort_fields = {sort_by("points", "DESC")};
coll1 = collectionManager.get_collection("coll1").get();
if (coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "100";
doc["title"] = "The quick brown fox jumped over the lazy dog and ran straight to the forest to sleep.";
doc["tags"] = {"NEWS", "LAZY"};
doc["points"] = 25;
auto add_op = coll1->add(doc.dump());
ASSERT_TRUE(add_op.ok());
auto res = coll1->search("lazy", {"title"}, "", {"tags"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"].size());
ASSERT_STREQ("The quick brown fox jumped over the lazy dog and ran straight to the forest to sleep.",
res["hits"][0]["document"]["title"].get<std::string>().c_str());
// reindex the document entirely again verbatim and try querying
add_op = coll1->add(doc.dump(), UPSERT);
ASSERT_TRUE(add_op.ok());
res = coll1->search("lazy", {"title"}, "", {"tags"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"].size());
ASSERT_EQ(1, res["facet_counts"].size());
ASSERT_STREQ("tags", res["facet_counts"][0]["field_name"].get<std::string>().c_str());
ASSERT_EQ(2, res["facet_counts"][0]["counts"].size());
ASSERT_STREQ("NEWS", res["facet_counts"][0]["counts"][0]["value"].get<std::string>().c_str());
ASSERT_EQ(1, (int) res["facet_counts"][0]["counts"][0]["count"]);
ASSERT_STREQ("LAZY", res["facet_counts"][0]["counts"][1]["value"].get<std::string>().c_str());
ASSERT_EQ(1, (int) res["facet_counts"][0]["counts"][1]["count"]);
// upsert only part of the document -- document should be REPLACED
nlohmann::json partial_doc = doc;
partial_doc.erase("tags");
add_op = coll1->add(partial_doc.dump(), UPSERT);
ASSERT_TRUE(add_op.ok());
res = coll1->search("lazy", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"].size());
ASSERT_FALSE(res["hits"][0].contains("tags"));
// upserting without a mandatory field should be an error
partial_doc = doc;
partial_doc.erase("title");
LOG(INFO) << partial_doc.dump();
add_op = coll1->add(partial_doc.dump(), UPSERT);
ASSERT_FALSE(add_op.ok());
ASSERT_EQ("Field `title` has been declared in the schema, but is not found in the document.", add_op.error());
// try changing the title and searching for an older token
doc["title"] = "The quick brown fox.";
add_op = coll1->add(doc.dump(), UPSERT);
ASSERT_TRUE(add_op.ok());
ASSERT_EQ(1, coll1->get_num_documents());
res = coll1->search("lazy", {"title"}, "", {"tags"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(0, res["hits"].size());
res = coll1->search("quick", {"title"}, "", {"title"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"].size());
ASSERT_STREQ("The quick brown fox.", res["hits"][0]["document"]["title"].get<std::string>().c_str());
// try to update document tags without `id`
nlohmann::json doc2;
doc2["tags"] = {"SENTENCE"};
add_op = coll1->add(doc2.dump(), UPDATE);
ASSERT_FALSE(add_op.ok());
ASSERT_STREQ("For update, the `id` key must be provided.", add_op.error().c_str());
// now change tags with id
doc2["id"] = "100";
add_op = coll1->add(doc2.dump(), UPDATE);
ASSERT_TRUE(add_op.ok());
// check for old tag
res = coll1->search("NEWS", {"tags"}, "", {"tags"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(0, res["hits"].size());
// now check for new tag and also try faceting on that field
res = coll1->search("SENTENCE", {"tags"}, "", {"tags"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"].size());
ASSERT_STREQ("SENTENCE", res["facet_counts"][0]["counts"][0]["value"].get<std::string>().c_str());
// try changing points
nlohmann::json doc3;
doc3["points"] = 99;
doc3["id"] = "100";
add_op = coll1->add(doc3.dump(), UPDATE);
ASSERT_TRUE(add_op.ok());
res = coll1->search("*", {"tags"}, "points: > 90", {"tags"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"].size());
ASSERT_EQ(99, res["hits"][0]["document"]["points"].get<size_t>());
// id can be passed by param
nlohmann::json doc4;
doc4["points"] = 105;
add_op = coll1->add(doc4.dump(), UPDATE, "100");
ASSERT_TRUE(add_op.ok());
res = coll1->search("*", {"tags"}, "points: > 101", {"tags"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"].size());
ASSERT_EQ(105, res["hits"][0]["document"]["points"].get<size_t>());
// try to change a field with bad value and verify that old document is put back
doc4["points"] = "abc";
add_op = coll1->add(doc4.dump(), UPDATE, "100");
ASSERT_FALSE(add_op.ok());
ASSERT_EQ("Field `points` must be an int32.", add_op.error());
res = coll1->search("*", {"tags"}, "points: > 101", {"tags"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"].size());
ASSERT_EQ(105, res["hits"][0]["document"]["points"].get<size_t>());
// when explicit path id does not match doc id, error should be returned
nlohmann::json doc5;
doc5["id"] = "800";
doc5["title"] = "The Secret Seven";
doc5["points"] = 250;
doc5["tags"] = {"BOOK", "ENID BLYTON"};
add_op = coll1->add(doc5.dump(), UPSERT, "799");
ASSERT_FALSE(add_op.ok());
ASSERT_EQ(400, add_op.code());
ASSERT_STREQ("The `id` of the resource does not match the `id` in the JSON body.", add_op.error().c_str());
// passing an empty id should not succeed
nlohmann::json doc6;
doc6["id"] = "";
doc6["title"] = "The Secret Seven";
doc6["points"] = 250;
doc6["tags"] = {"BOOK", "ENID BLYTON"};
add_op = coll1->add(doc6.dump(), UPDATE);
ASSERT_FALSE(add_op.ok());
ASSERT_EQ(400, add_op.code());
ASSERT_STREQ("The `id` should not be empty.", add_op.error().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, UpdateDocumentSorting) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, true),
field("tags", field_types::STRING_ARRAY, true),
field("points", field_types::INT32, false)};
std::vector<sort_by> sort_fields = {sort_by("points", "DESC")};
coll1 = collectionManager.get_collection("coll1").get();
if (coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
nlohmann::json doc1;
doc1["id"] = "100";
doc1["title"] = "The quick brown fox jumped over the lazy dog and ran straight to the forest to sleep.";
doc1["tags"] = {"NEWS", "LAZY"};
doc1["points"] = 100;
nlohmann::json doc2;
doc2["id"] = "101";
doc2["title"] = "The random sentence.";
doc2["tags"] = {"RANDOM"};
doc2["points"] = 101;
auto add_op = coll1->add(doc1.dump());
coll1->add(doc2.dump());
auto res = coll1->search("*", {"tags"}, "", {"tags"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(2, res["hits"].size());
ASSERT_EQ(101, res["hits"][0]["document"]["points"].get<size_t>());
ASSERT_STREQ("101", res["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_EQ(100, res["hits"][1]["document"]["points"].get<size_t>());
ASSERT_STREQ("100", res["hits"][1]["document"]["id"].get<std::string>().c_str());
// now update doc1 points from 100 -> 1000 and it should bubble up
doc1["points"] = 1000;
coll1->add(doc1.dump(), UPDATE);
res = coll1->search("*", {"tags"}, "", {"tags"}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(2, res["hits"].size());
ASSERT_EQ(1000, res["hits"][0]["document"]["points"].get<size_t>());
ASSERT_STREQ("100", res["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_EQ(101, res["hits"][1]["document"]["points"].get<size_t>());
ASSERT_STREQ("101", res["hits"][1]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, UpdateDocumentUnIndexedField) {
Collection* coll1;
std::vector<field> fields = {field("title", field_types::STRING, true),
field("points", field_types::INT32, false)};
std::vector<sort_by> sort_fields = {sort_by("points", "DESC")};
coll1 = collectionManager.get_collection("coll1").get();
if (coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "100";
doc["title"] = "The quick brown fox jumped over the lazy dog and ran straight to the forest to sleep.";
doc["foo"] = "foo1";
doc["points"] = 25;
auto add_op = coll1->add(doc.dump());
ASSERT_TRUE(add_op.ok());
auto res = coll1->search("lazy", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"].size());
ASSERT_STREQ("The quick brown fox jumped over the lazy dog and ran straight to the forest to sleep.",
res["hits"][0]["document"]["title"].get<std::string>().c_str());
// reindex the document again by changing only the unindexed field
doc["foo"] = "foo2";
add_op = coll1->add(doc.dump(), UPSERT);
ASSERT_TRUE(add_op.ok());
res = coll1->search("lazy", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"].size());
ASSERT_STREQ("foo2", res["hits"][0]["document"]["foo"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, SearchHighlightFieldFully) {
Collection *coll1;
std::vector<field> fields = { field("title", field_types::STRING, true),
field("tags", field_types::STRING_ARRAY, true),
field("points", field_types::INT32, false)};
std::vector<sort_by> sort_fields = {sort_by("points", "DESC")};
coll1 = collectionManager.get_collection("coll1").get();
if (coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "100";
doc["title"] = "The quick brown fox jumped over the lazy dog and ran straight to the forest to sleep.";
doc["tags"] = {"NEWS", "LAZY"};
doc["points"] = 25;
auto add_op = coll1->add(doc.dump());
ASSERT_TRUE(add_op.ok());
// look for fully highlighted value in response
auto res = coll1->search("lazy", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title").get();
ASSERT_EQ(1, res["hits"][0]["highlights"].size());
ASSERT_STREQ("The quick brown fox jumped over the <mark>lazy</mark> dog and ran straight to the forest to sleep.",
res["hits"][0]["highlights"][0]["value"].get<std::string>().c_str());
// should not return value key when highlight_full_fields is not specified
res = coll1->search("lazy", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "").get();
ASSERT_EQ(3, res["hits"][0]["highlights"][0].size());
// query multiple fields
res = coll1->search("lazy", {"title", "tags"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 5, 5, "title, tags").get();
ASSERT_EQ(2, res["hits"][0]["highlights"].size());
ASSERT_EQ("<mark>LAZY</mark>", res["hits"][0]["highlights"][0]["values"][0].get<std::string>());
ASSERT_EQ("The quick brown fox jumped over the <mark>lazy</mark> dog and ran straight to the forest to sleep.",
res["hits"][0]["highlights"][1]["value"].get<std::string>());
ASSERT_EQ(1, res["hits"][0]["highlights"][1]["matched_tokens"].size());
ASSERT_STREQ("lazy", res["hits"][0]["highlights"][1]["matched_tokens"][0].get<std::string>().c_str());
ASSERT_EQ(1, res["hits"][0]["highlights"][0]["values"][0].size());
ASSERT_STREQ("<mark>LAZY</mark>", res["hits"][0]["highlights"][0]["values"][0].get<std::string>().c_str());
// excluded fields should not be returned in highlights section
spp::sparse_hash_set<std::string> excluded_fields = {"tags"};
res = coll1->search("lazy", {"title", "tags"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
excluded_fields, 10, "", 5, 5, "title, tags").get();
ASSERT_EQ(1, res["hits"][0]["highlights"].size());
ASSERT_STREQ("The quick brown fox jumped over the <mark>lazy</mark> dog and ran straight to the forest to sleep.",
res["hits"][0]["highlights"][0]["value"].get<std::string>().c_str());
// when all fields are excluded
excluded_fields = {"tags", "title"};
res = coll1->search("lazy", {"title", "tags"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
excluded_fields, 10, "", 5, 5, "title, tags").get();
ASSERT_EQ(0, res["hits"][0]["highlights"].size());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, OptionalFields) {
Collection *coll1;
std::vector<field> fields = {
field("title", field_types::STRING, false),
field("description", field_types::STRING, true, true),
field("max", field_types::INT32, false),
field("scores", field_types::INT64_ARRAY, false, true),
field("average", field_types::FLOAT, false, true),
field("is_valid", field_types::BOOL, false, true),
};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "max").get();
}
std::ifstream infile(std::string(ROOT_DIR)+"test/optional_fields.jsonl");
std::string json_line;
while (std::getline(infile, json_line)) {
auto add_op = coll1->add(json_line);
if(!add_op.ok()) {
std::cout << add_op.error() << std::endl;
}
ASSERT_TRUE(add_op.ok());
}
infile.close();
// first must be able to fetch all records (i.e. all must have been indexed)
auto res = coll1->search("*", {"title"}, "", {}, {}, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(6, res["found"].get<size_t>());
// search on optional `description` field
res = coll1->search("book", {"description"}, "", {}, {}, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(5, res["found"].get<size_t>());
// filter on optional `average` field
res = coll1->search("the", {"title"}, "average: >0", {}, {}, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(5, res["found"].get<size_t>());
// facet on optional `description` field
res = coll1->search("the", {"title"}, "", {"description"}, {}, {0}, 10, 1, FREQUENCY, {false}).get();
ASSERT_EQ(6, res["found"].get<size_t>());
ASSERT_EQ(5, res["facet_counts"][0]["counts"][0]["count"].get<size_t>());
ASSERT_STREQ("description", res["facet_counts"][0]["field_name"].get<std::string>().c_str());
// sort_by optional `average` field should be allowed (default used for missing values)
std::vector<sort_by> sort_fields = { sort_by("average", "DESC") };
auto res_op = coll1->search("*", {"title"}, "", {}, sort_fields, {0}, 10, 1, FREQUENCY, {false});
ASSERT_TRUE(res_op.ok());
res = res_op.get();
ASSERT_EQ(6, res["found"].get<size_t>());
ASSERT_EQ(0, res["hits"][5]["document"].count("average")); // record with missing average is last
// try deleting a record having optional field
Option<std::string> remove_op = coll1->remove("1");
ASSERT_TRUE(remove_op.ok());
// try fetching the schema (should contain optional field)
nlohmann::json coll_summary = coll1->get_summary_json();
ASSERT_STREQ("title", coll_summary["fields"][0]["name"].get<std::string>().c_str());
ASSERT_STREQ("string", coll_summary["fields"][0]["type"].get<std::string>().c_str());
ASSERT_FALSE(coll_summary["fields"][0]["facet"].get<bool>());
ASSERT_FALSE(coll_summary["fields"][0]["optional"].get<bool>());
ASSERT_STREQ("description", coll_summary["fields"][1]["name"].get<std::string>().c_str());
ASSERT_STREQ("string", coll_summary["fields"][1]["type"].get<std::string>().c_str());
ASSERT_TRUE(coll_summary["fields"][1]["facet"].get<bool>());
ASSERT_TRUE(coll_summary["fields"][1]["optional"].get<bool>());
// default sorting field should not be declared optional
fields = {
field("title", field_types::STRING, false),
field("score", field_types::INT32, false, true),
};
auto create_op = collectionManager.create_collection("coll2", 4, fields, "score");
ASSERT_FALSE(create_op.ok());
ASSERT_STREQ("Default sorting field `score` cannot be an optional field.", create_op.error().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, OptionalFieldCanBeNull) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false, true),
field("genres", field_types::STRING_ARRAY, false, true),
field("launch_year", field_types::INT32, false, true),
field("updated_at", field_types::INT64, false, true),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "0";
doc["title"] = "Beat it";
doc["artist"] = nullptr;
doc["genres"] = nullptr;
doc["launch_year"] = nullptr;
doc["updated_at"] = nullptr;
doc["points"] = 100;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
ASSERT_EQ(2, coll1->_get_indexes()[0]->_get_search_index().at("title")->size);
ASSERT_EQ(0, coll1->_get_indexes()[0]->_get_search_index().at("artist")->size);
ASSERT_EQ(0, coll1->_get_indexes()[0]->_get_search_index().at("genres")->size);
auto results = coll1->search("beat",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, EmptyStringNotIndexed) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false, true),
field("genres", field_types::STRING_ARRAY, false, true),
field("launch_year", field_types::STRING, false, true),
field("labels", field_types::STRING_ARRAY, false, true),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "0";
doc["title"] = "Beat it";
doc["artist"] = "";
doc["launch_year"] = " ";
doc["genres"] = {""};
doc["labels"] = {"song", " ", ""};
doc["points"] = 100;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
auto results = coll1->search("beat",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
ASSERT_EQ(2, coll1->_get_indexes()[0]->_get_search_index().at("title")->size);
ASSERT_EQ(0, coll1->_get_indexes()[0]->_get_search_index().at("artist")->size);
ASSERT_EQ(0, coll1->_get_indexes()[0]->_get_search_index().at("launch_year")->size);
ASSERT_EQ(0, coll1->_get_indexes()[0]->_get_search_index().at("genres")->size);
ASSERT_EQ(1, coll1->_get_indexes()[0]->_get_search_index().at("labels")->size);
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, WildcardQueryReturnsResultsBasedOnPerPageParam) {
std::vector<std::string> facets;
spp::sparse_hash_set<std::string> empty;
nlohmann::json results = collection->search("*", query_fields, "", facets, sort_fields, {0}, 12, 1,
FREQUENCY, {false}, 1000, empty, empty, 10).get();
ASSERT_EQ(12, results["hits"].size());
ASSERT_EQ(25, results["found"].get<int>());
// should match collection size
results = collection->search("*", query_fields, "", facets, sort_fields, {0}, 100, 1,
FREQUENCY, {false}, 1000, empty, empty, 10).get();
ASSERT_EQ(25, results["hits"].size());
ASSERT_EQ(25, results["found"].get<int>());
// cannot fetch more than in-built limit of 250
auto res_op = collection->search("*", query_fields, "", facets, sort_fields, {0}, 251, 1,
FREQUENCY, {false}, 1000, empty, empty, 10);
ASSERT_FALSE(res_op.ok());
ASSERT_EQ(422, res_op.code());
ASSERT_STREQ("Only upto 250 hits can be fetched per page.", res_op.error().c_str());
// when page number is not valid
res_op = collection->search("*", query_fields, "", facets, sort_fields, {0}, 10, 0,
FREQUENCY, {false}, 1000, empty, empty, 10);
ASSERT_FALSE(res_op.ok());
ASSERT_EQ(422, res_op.code());
ASSERT_STREQ("Page must be an integer of value greater than 0.", res_op.error().c_str());
// do pagination
results = collection->search("*", query_fields, "", facets, sort_fields, {0}, 10, 1,
FREQUENCY, {false}, 1000, empty, empty, 10).get();
ASSERT_EQ(10, results["hits"].size());
ASSERT_EQ(25, results["found"].get<int>());
results = collection->search("*", query_fields, "", facets, sort_fields, {0}, 10, 2,
FREQUENCY, {false}, 1000, empty, empty, 10).get();
ASSERT_EQ(10, results["hits"].size());
ASSERT_EQ(25, results["found"].get<int>());
results = collection->search("*", query_fields, "", facets, sort_fields, {0}, 10, 3,
FREQUENCY, {false}, 1000, empty, empty, 10).get();
ASSERT_EQ(5, results["hits"].size());
ASSERT_EQ(25, results["found"].get<int>());
// enforce limit_hits
res_op = collection->search("*", query_fields, "", facets, sort_fields, {0}, 10, 3,
FREQUENCY, {false}, 1000,
spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1}, 20);
ASSERT_FALSE(res_op.ok());
ASSERT_STREQ(
"Only upto 20 hits can be fetched. Ensure that `page` and `per_page` parameters are within this range.",
res_op.error().c_str());
}
TEST_F(CollectionTest, RemoveIfFound) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, true),
field("points", field_types::INT32, false)};
std::vector<sort_by> sort_fields = {sort_by("points", "DESC")};
coll1 = collectionManager.get_collection("coll1").get();
if (coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
for(size_t i=0; i<10; i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = "Title " + std::to_string(i);
doc["points"] = i;
coll1->add(doc.dump());
}
auto res = coll1->search("*", {"title"}, "", {}, sort_fields, {0}, 10, 1,
token_ordering::FREQUENCY, {true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0).get();
ASSERT_EQ(10, res["found"].get<int>());
// removing found doc
Option<bool> found_op = coll1->remove_if_found(0);
ASSERT_TRUE(found_op.ok());
ASSERT_TRUE(found_op.get());
auto get_op = coll1->get("0");
ASSERT_FALSE(get_op.ok());
ASSERT_EQ(404, get_op.code());
// removing doc not found
found_op = coll1->remove_if_found(100);
ASSERT_TRUE(found_op.ok());
ASSERT_FALSE(found_op.get());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, CreateCollectionInvalidFieldType) {
std::vector<field> fields = {field("title", "blah", true),
field("points", "int", false)};
std::vector<sort_by> sort_fields = {sort_by("points", "DESC")};
collectionManager.drop_collection("coll1");
auto create_op = collectionManager.create_collection("coll1", 4, fields, "points");
ASSERT_FALSE(create_op.ok());
ASSERT_STREQ("Field `title` has an invalid data type `blah`, see docs for supported data types.",
create_op.error().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, MultiFieldRelevance) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Down There by the Train", "Dustin Kensrue"},
{"Down There by the Train", "Gord Downie"},
{"State Trooper", "Dustin Kensrue"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("Dustin Kensrue Down There by the Train",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY).get();
ASSERT_EQ(3, results["found"].get<size_t>());
ASSERT_EQ(3, results["hits"].size());
std::vector<size_t> expected_ids = {0, 1, 2};
for(size_t i=0; i<expected_ids.size(); i++) {
ASSERT_EQ(expected_ids[i], std::stoi(results["hits"][i]["document"]["id"].get<std::string>()));
}
ASSERT_STREQ("<mark>Down</mark> <mark>There</mark> <mark>by</mark> <mark>the</mark> <mark>Train</mark>",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
ASSERT_STREQ("<mark>Down</mark> <mark>There</mark> <mark>by</mark> <mark>the</mark> <mark>Train</mark>",
results["hits"][1]["highlights"][0]["snippet"].get<std::string>().c_str());
ASSERT_STREQ("<mark>Dustin</mark> <mark>Kensrue</mark>",
results["hits"][2]["highlights"][0]["snippet"].get<std::string>().c_str());
// remove documents, reindex in another order and search again
for(size_t i=0; i<expected_ids.size(); i++) {
coll1->remove_if_found(i, true);
}
records = {
{"State Trooper", "Dustin Kensrue"},
{"Down There by the Train", "Gord Downie"},
{"Down There by the Train", "Dustin Kensrue"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
results = coll1->search("Dustin Kensrue Down There by the Train",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY).get();
ASSERT_EQ(3, results["found"].get<size_t>());
ASSERT_EQ(3, results["hits"].size());
expected_ids = {2, 1, 0};
for(size_t i=0; i<expected_ids.size(); i++) {
ASSERT_EQ(expected_ids[i], std::stoi(results["hits"][i]["document"]["id"].get<std::string>()));
}
// with exclude token syntax
results = coll1->search("-downie dustin kensrue down there by the train",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
expected_ids = {2, 0};
for(size_t i=0; i<expected_ids.size(); i++) {
ASSERT_EQ(expected_ids[i], std::stoi(results["hits"][i]["document"]["id"].get<std::string>()));
}
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, MultiFieldRelevance2) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"A Daikon Freestyle", "Ghosts on a Trampoline"},
{"Leaving on a Jetplane", "Coby Grant"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("on a jetplane",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("1", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("0", results["hits"][1]["document"]["id"].get<std::string>().c_str());
// change weights to favor artist
results = coll1->search("on a jetplane",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 4}).get();
ASSERT_STREQ("1", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("0", results["hits"][1]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, FieldWeightsNotProper) {
// when weights are not given properly
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
auto results_op = coll1->search("on a jetplane",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1});
ASSERT_FALSE(results_op.ok());
ASSERT_STREQ("Number of weights in `query_by_weights` does not match number "
"of `query_by` fields.", results_op.error().c_str());
results_op = coll1->search("on a jetplane",
{"title"}, "", {}, {}, {0}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {2, 1});
ASSERT_FALSE(results_op.ok());
ASSERT_STREQ("Number of weights in `query_by_weights` does not match number "
"of `query_by` fields.", results_op.error().c_str());
// empty weights are fine (will be defaulted to)
results_op = coll1->search("on a jetplane",
{"title"}, "", {}, {}, {0}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {});
ASSERT_TRUE(results_op.ok());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, MultiFieldRelevance3) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Taylor Swift Karaoke: reputation", "Taylor Swift"},
{"Style", "Taylor Swift"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("style taylor swift",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("1", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("0", results["hits"][1]["document"]["id"].get<std::string>().c_str());
results = coll1->search("swift",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][1]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, MultiFieldRelevance4) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Madras Dreams", "Chennai King"},
{"Madurai Express", "Madura Maddy"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("madras",
{"title", "artist"}, "", {}, {}, {2}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][1]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, MultiFieldRelevance5) {
Collection *coll1;
std::vector<field> fields = {field("company_name", field_types::STRING, false),
field("country", field_types::STRING, false),
field("field_a", field_types::STRING, false),
field("num_employees", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "num_employees").get();
}
std::vector<std::vector<std::string>> records = {
{"Stark Industries ™", "Canada", "Canadia", "5215"},
{"Canaida Corp", "United States", "Canadoo", "200"},
{"Acme Corp", "Mexico", "Canadoo", "300"}
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["company_name"] = records[i][0];
doc["country"] = records[i][1];
doc["field_a"] = records[i][2];
doc["num_employees"] = std::stoi(records[i][3]);
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("Canada",
{"company_name","country","field_a"}, "", {}, {}, {2}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1, 1}).get();
ASSERT_EQ(3, results["found"].get<size_t>());
ASSERT_EQ(3, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][1]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("2", results["hits"][2]["document"]["id"].get<std::string>().c_str());
results = coll1->search("Canada",
{"company_name","field_a","country"}, "", {}, {}, {2}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1, 1}).get();
ASSERT_EQ(3, results["found"].get<size_t>());
ASSERT_EQ(3, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][1]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("2", results["hits"][2]["document"]["id"].get<std::string>().c_str());
ASSERT_EQ(1, results["hits"][0]["highlights"].size());
ASSERT_EQ("country", results["hits"][0]["highlights"][0]["field"].get<std::string>());
ASSERT_EQ("<mark>Canada</mark>", results["hits"][0]["highlights"][0]["snippet"].get<std::string>());
ASSERT_EQ(1, results["hits"][1]["highlights"].size());
ASSERT_EQ("company_name", results["hits"][1]["highlights"][0]["field"].get<std::string>());
ASSERT_EQ("<mark>Canaida</mark> Corp", results["hits"][1]["highlights"][0]["snippet"].get<std::string>());
ASSERT_EQ(1, results["hits"][2]["highlights"].size());
ASSERT_EQ("field_a", results["hits"][2]["highlights"][0]["field"].get<std::string>());
ASSERT_EQ("<mark>Canadoo</mark>", results["hits"][2]["highlights"][0]["snippet"].get<std::string>());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, MultiFieldRelevance6) {
// with exact match preference
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Taylor Swift", "Taylor Swift"},
{"Taylor Swift Song", "Taylor Swift"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("taylor swift",
{"title", "artist"}, "", {}, {}, {2}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][1]["document"]["id"].get<std::string>().c_str());
// when exact matches are disabled
results = coll1->search("taylor swift",
{"title", "artist"}, "", {}, {}, {2}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}, 100, false).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("1", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("0", results["hits"][1]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, ExactMatch) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Alpha", "DJ"},
{"Alpha Beta", "DJ"},
{"Alpha Beta Gamma", "DJ"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("alpha beta",
{"title"}, "", {}, {}, {2}, 10, 1, FREQUENCY,
{true}, 10).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("1", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("2", results["hits"][1]["document"]["id"].get<std::string>().c_str());
results = coll1->search("alpha", {"title"}, "", {}, {}, {2}, 10, 1, FREQUENCY, {true}, 10).get();
ASSERT_EQ(3, results["found"].get<size_t>());
ASSERT_EQ(3, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("2", results["hits"][1]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][2]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, MultiFieldHighlighting) {
Collection *coll1;
std::vector<field> fields = {field("name", field_types::STRING, false),
field("description", field_types::STRING, false),
field("categories", field_types::STRING_ARRAY, false),
field("points", field_types::INT32, false)};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Best Wireless Vehicle Charger",
"Easily replenish your cell phone with this wireless charger.",
"Cell Phones > Cell Phone Accessories > Car Chargers"},
{"Annie's Song",
"John Denver",
"Album > Compilation"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
std::vector<std::string> categories;
StringUtils::split(records[i][2], categories, ">");
doc["id"] = std::to_string(i);
doc["name"] = records[i][0];
doc["description"] = records[i][1];
doc["categories"] = categories;
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("charger",
{"name","description","categories"}, "", {}, {}, {2}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1, 1}).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_EQ(2, results["hits"][0]["highlights"].size());
ASSERT_EQ("name", results["hits"][0]["highlights"][0]["field"].get<std::string>());
ASSERT_EQ("Best Wireless Vehicle <mark>Charger</mark>",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>());
ASSERT_EQ("description", results["hits"][0]["highlights"][1]["field"].get<std::string>());
ASSERT_EQ("Easily replenish your cell phone with this wireless <mark>charger.</mark>",
results["hits"][0]["highlights"][1]["snippet"].get<std::string>());
results = coll1->search("John With Denver",
{"description"}, "", {}, {}, {0}, 10, 1, FREQUENCY,
{true}, 1, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1}).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("1", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_EQ(1, results["hits"][0]["highlights"].size());
ASSERT_EQ("description", results["hits"][0]["highlights"][0]["field"].get<std::string>());
ASSERT_EQ("<mark>John</mark> <mark>Denver</mark>",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>());
results = coll1->search("Annies song John Denver",
{"name","description"}, "", {}, {}, {0}, 10, 1, FREQUENCY,
{true}, 1, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("1", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_EQ(2, results["hits"][0]["highlights"].size());
ASSERT_EQ("name", results["hits"][0]["highlights"][0]["field"].get<std::string>());
ASSERT_EQ("<mark>Annie's</mark> <mark>Song</mark>",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>());
ASSERT_EQ("description", results["hits"][0]["highlights"][1]["field"].get<std::string>());
ASSERT_EQ("<mark>John</mark> <mark>Denver</mark>",
results["hits"][0]["highlights"][1]["snippet"].get<std::string>());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, MultiFieldMatchRanking) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Style", "Taylor Swift"},
{"Blank Space", "Taylor Swift"},
{"Balance Overkill", "Taylor Swift"},
{"Cardigan", "Taylor Swift"},
{"Invisible String", "Taylor Swift"},
{"The Last Great American Dynasty", "Taylor Swift"},
{"Mirrorball", "Taylor Swift"},
{"Peace", "Taylor Swift"},
{"Betty", "Taylor Swift"},
{"Mad Woman", "Taylor Swift"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("taylor swift style",
{"artist", "title"}, "", {}, {}, {0}, 3, 1, FREQUENCY, {true}, 5).get();
ASSERT_EQ(10, results["found"].get<size_t>());
ASSERT_EQ(3, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("9", results["hits"][1]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("8", results["hits"][2]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, MultiFieldMatchRankingOnArray) {
Collection *coll1;
std::vector<field> fields = {field("name", field_types::STRING, false),
field("strong_skills", field_types::STRING_ARRAY, false),
field("skills", field_types::STRING_ARRAY, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::vector<std::string>>> records = {
{{"John Snow"}, {"Golang", "Vue", "React"}, {"Docker", "Goa", "Elixir"}},
{{"Jack Dan"}, {"Golang", "Phoenix", "React"}, {"Docker", "Vue", "Kubernetes"}},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["name"] = records[i][0][0];
doc["strong_skills"] = records[i][1];
doc["skills"] = records[i][2];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("golang vue",
{"strong_skills", "skills"}, "", {}, {}, {0}, 3, 1, FREQUENCY, {true}, 5).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][1]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, MultiFieldMatchRankingOnFieldOrder) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Toxic", "Britney Spears"},
{"Bad", "Michael Jackson"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("michael jackson toxic",
{"title", "artist"}, "", {}, {}, {0}, 3, 1, FREQUENCY, {true}, 5).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("1", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("0", results["hits"][1]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, PrefixRankedAfterExactMatch) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Rotini Puttanesca"},
{"Poulet Roti Tout Simple"},
{"Chapatis (Roti)"},
{"School Days Rotini Pasta Salad"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("roti", {"title"}, "", {}, {}, {0}, 3, 1, FREQUENCY, {true}, 5).get();
ASSERT_EQ(4, results["found"].get<size_t>());
ASSERT_EQ(3, results["hits"].size());
ASSERT_STREQ("2", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][1]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("3", results["hits"][2]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, HighlightWithAccentedCharacters) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if (coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 4, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Mise T.J. à jour Timy depuis PC"},
{"Down There by the T.r.a.i.n"},
{"State Trooper"},
{"The Google Nexus Q Is Baffling"},
};
for (size_t i = 0; i < records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("à jour", {"title"}, "", {}, {}, {0}, 10, 1, FREQUENCY).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("Mise T.J. <mark>à</mark> <mark>jour</mark> Timy depuis PC",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
ASSERT_EQ(2, results["hits"][0]["highlights"][0]["matched_tokens"].size());
ASSERT_STREQ("à", results["hits"][0]["highlights"][0]["matched_tokens"][0].get<std::string>().c_str());
ASSERT_STREQ("jour", results["hits"][0]["highlights"][0]["matched_tokens"][1].get<std::string>().c_str());
results = coll1->search("by train", {"title"}, "", {}, {}, {0}, 10, 1, FREQUENCY).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("Down There <mark>by</mark> the <mark>T.r.a.i.n</mark>",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
results = coll1->search("state trooper", {"title"}, "", {}, {}, {0}, 10, 1, FREQUENCY).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("<mark>State</mark> <mark>Trooper</mark>",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
// test single character highlight
results = coll1->search("q", {"title"}, "", {}, {}, {0}, 10, 1, FREQUENCY).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_STREQ("The Google Nexus <mark>Q</mark> Is Baffling",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, DISABLED_SearchingForRecordsWithSpecialChars) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("url", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Amazon Home", "https://amazon.com/"},
{"Google Home", "https://google.com///"},
{"Github Issue", "https://github.com/typesense/typesense/issues/241"},
{"Amazon Search", "https://www.amazon.com/s?k=phone&ref=nb_sb_noss_2"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["url"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("google",
{"title", "url"}, "", {}, {}, {2}, 10, 1, FREQUENCY).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_STREQ("1", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_EQ(2, results["hits"][0]["highlights"].size());
ASSERT_EQ("<mark>Google</mark> Home", results["hits"][0]["highlights"][0]["snippet"].get<std::string>());
ASSERT_EQ("https://<mark>google</mark>.com///", results["hits"][0]["highlights"][1]["snippet"].get<std::string>());
results = coll1->search("amazon.com",
{"title", "url"}, "", {}, {}, {2}, 10, 1, FREQUENCY).get();
ASSERT_EQ(3, results["found"].get<size_t>());
ASSERT_STREQ("3", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("0", results["hits"][1]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][2]["document"]["id"].get<std::string>().c_str());
results = coll1->search("typesense",
{"title", "url"}, "", {}, {}, {2}, 10, 1, FREQUENCY).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_STREQ("2", results["hits"][0]["document"]["id"].get<std::string>().c_str());
results = coll1->search("nb_sb_noss_2",
{"title", "url"}, "", {}, {}, {2}, 10, 1, FREQUENCY).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_STREQ("3", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_EQ(1, results["hits"][0]["highlights"].size());
ASSERT_EQ("https://www.amazon.com/s?k=phone&ref=<mark>nb</mark>_<mark>sb</mark>_<mark>noss</mark>_<mark>2</mark>",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, FieldSpecificNumTypos) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Taylor Swift Karaoke: reputation", "Taylor Swift"},
{"Taylor & Friends", "Adam Smith"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("tayylor",
{"title", "artist"}, "", {}, {}, {1, 1}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][1]["document"]["id"].get<std::string>().c_str());
results = coll1->search("tayylor",
{"title", "artist"}, "", {}, {}, {0, 1}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
// must return error when num_typos does not match length of search fields queried
auto res_op = coll1->search("tayylor",
{"title"}, "", {}, {}, {0, 1}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1});
ASSERT_FALSE(res_op.ok());
ASSERT_EQ("Number of weights in `query_by_weights` does not match number of `query_by` fields.", res_op.error());
// can use a single typo param for multiple fields
results = coll1->search("tayylor",
{"title", "artist"}, "", {}, {}, {1}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
// wildcard search with typos
results = coll1->search("*",
{}, "", {}, {}, {1}, 10, 1, FREQUENCY,
{true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, BadHighlightingOnText) {
Collection *coll1;
std::vector<field> fields = {field("text", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
nlohmann::json doc;
doc["id"] = "0";
doc["text"] = "include destruction of natural marine and estuarine\\nhabitats, loss of productive agricultural "
"land,\\nand soil erosion. 90 When interviewed, multiple\\nexperts stated that inappropriate land use "
"and\\nmanagement is a central factor contributing to\\nenvironmental degradation in the "
"Castries-Gros\\nIslet Corridor. 91 The construction is placing greater\\nstress on natural resources "
"and biodiversity, and\\nthe capacity to produce food and retain freshwater\\nhas been diminished. "
"92 Moreover, increased\\nwater consumption by the tourism sector, when\\ncompounded by climate "
"change, is increasing food\\nand water insecurity throughout Saint Lucia, as well\\nas suppressing "
"long-term growth prospects. 93";
doc["points"] = 0;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
auto results = coll1->search("natural saint lucia", {"text"}, "", {}, {}, {1}, 10, 1, FREQUENCY,
{true}, 10).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("food\\nand water insecurity throughout <mark>Saint</mark> <mark>Lucia,</mark> as well\\nas suppressing long-term",
results["hits"][0]["highlights"][0]["snippet"].get<std::string>().c_str());
ASSERT_EQ(2, results["hits"][0]["highlights"][0]["matched_tokens"].size());
ASSERT_STREQ("Saint", results["hits"][0]["highlights"][0]["matched_tokens"][0].get<std::string>().c_str());
ASSERT_STREQ("Lucia,", results["hits"][0]["highlights"][0]["matched_tokens"][1].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
TEST_F(CollectionTest, FieldLevelPrefixConfiguration) {
Collection *coll1;
std::vector<field> fields = {field("title", field_types::STRING, false),
field("artist", field_types::STRING, false),
field("points", field_types::INT32, false),};
coll1 = collectionManager.get_collection("coll1").get();
if(coll1 == nullptr) {
coll1 = collectionManager.create_collection("coll1", 1, fields, "points").get();
}
std::vector<std::vector<std::string>> records = {
{"Taylor Swift Karaoke: reputation", "Taylor Swift"},
{"Style", "Taylor Swift"},
};
for(size_t i=0; i<records.size(); i++) {
nlohmann::json doc;
doc["id"] = std::to_string(i);
doc["title"] = records[i][0];
doc["artist"] = records[i][1];
doc["points"] = i;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
}
auto results = coll1->search("taylo",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY,
{true, false}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(1, results["found"].get<size_t>());
ASSERT_EQ(1, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
results = coll1->search("taylo",
{"title", "artist"}, "", {}, {}, {0}, 10, 1, FREQUENCY,
{true, true}, 10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 40, {}, {}, {}, 0,
"<mark>", "</mark>", {1, 1}).get();
ASSERT_EQ(2, results["found"].get<size_t>());
ASSERT_EQ(2, results["hits"].size());
ASSERT_STREQ("0", results["hits"][0]["document"]["id"].get<std::string>().c_str());
ASSERT_STREQ("1", results["hits"][1]["document"]["id"].get<std::string>().c_str());
collectionManager.drop_collection("coll1");
}
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