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Merge pull request #1468 from krunal1313/float_range_facet_value_index_fix

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fix float range facet with value index
This commit is contained in:
Kishore Nallan 2024-01-05 12:49:58 +05:30 committed by GitHub
commit 431abf2f66
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2 changed files with 149 additions and 3 deletions
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10
src/index.cpp
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@ -1378,9 +1378,15 @@ void Index::do_facets(std::vector<facet> & facets, facet_query_t & facet_query,
for(const auto& kv : facet_results) {
//range facet processing
if(a_facet.is_range_query) {
const auto doc_val = kv.first;
int64_t doc_val = std::stoll(kv.first);
std::pair<int64_t , std::string> range_pair {};
if(a_facet.get_range(std::stoll(doc_val), range_pair)) {
if(facet_field.is_float()) {
float val = std::stof(kv.first);
doc_val = Index::float_to_int64_t(val);
}
if(a_facet.get_range(doc_val, range_pair)) {
const auto& range_id = range_pair.first;
facet_count_t& facet_count = a_facet.result_map[range_id];
facet_count.count += kv.second.count;

142
test/collection_optimized_faceting_test.cpp
View File

@ -2694,4 +2694,144 @@ TEST_F(CollectionOptimizedFacetingTest, RangeFacetAlphanumericLabels) {
ASSERT_EQ("20thAD", results["facet_counts"][0]["counts"][1]["value"]);
ASSERT_EQ(1, results["facet_counts"][0]["counts"][2]["count"]);
ASSERT_EQ("10thAD", results["facet_counts"][0]["counts"][2]["value"]);
}
}
TEST_F(CollectionOptimizedFacetingTest, RangeFacetsFloatRange) {
std::vector<field> fields = {field("name", field_types::STRING, false),
field("inches", field_types::FLOAT, true),};
Collection* coll1 = collectionManager.create_collection(
"coll1", 1, fields, "", 0, "", {}, {}).get();
nlohmann::json doc;
doc["id"] = "0";
doc["name"] = "TV 1";
doc["inches"] = 32.4;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
doc["id"] = "1";
doc["name"] = "TV 2";
doc["inches"] = 55;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
doc["id"] = "2";
doc["name"] = "TV 3";
doc["inches"] = 55.6;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
auto results = coll1->search("*", {},
"", {"inches(small:[0, 55.5])"},
{}, {2}, 10,
1, FREQUENCY, {true},
10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 10, {}, {}, {}, 0,
"<mark>", "</mark>", {}, 1000,
true, false, true, "", true,
6000*1000, 4, 7, fallback, 4, {off}, INT16_MAX, INT16_MAX,
2, 2, false, "", true, 0, max_score, 100, 0, 0, VALUE).get();
ASSERT_EQ(1, results["facet_counts"][0]["counts"].size());
ASSERT_EQ(2, (int) results["facet_counts"][0]["counts"][0]["count"]);
ASSERT_EQ("small", results["facet_counts"][0]["counts"][0]["value"]);
}
TEST_F(CollectionOptimizedFacetingTest, RangeFacetsMinMaxRange) {
std::vector<field> fields = {field("name", field_types::STRING, false),
field("inches", field_types::FLOAT, true),};
Collection* coll1 = collectionManager.create_collection(
"coll1", 1, fields, "", 0, "", {}, {}).get();
nlohmann::json doc;
doc["id"] = "0";
doc["name"] = "TV 1";
doc["inches"] = 32.4;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
doc["id"] = "1";
doc["name"] = "TV 2";
doc["inches"] = 55;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
doc["id"] = "2";
doc["name"] = "TV 3";
doc["inches"] = 55.6;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
auto results = coll1->search("*", {},
"", {"inches(small:[0, 55], large:[55, ])"},
{}, {2}, 10,
1, FREQUENCY, {true},
10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 10, {}, {}, {}, 0,
"<mark>", "</mark>", {}, 1000,
true, false, true, "", true,
6000*1000, 4, 7, fallback, 4, {off}, INT16_MAX, INT16_MAX,
2, 2, false, "", true, 0, max_score, 100, 0, 0, VALUE).get();
ASSERT_EQ(2, results["facet_counts"][0]["counts"].size());
ASSERT_EQ(2, (int) results["facet_counts"][0]["counts"][0]["count"]);
ASSERT_EQ("small", results["facet_counts"][0]["counts"][0]["value"]);
ASSERT_EQ(1, (int) results["facet_counts"][0]["counts"][1]["count"]);
ASSERT_EQ("large", results["facet_counts"][0]["counts"][1]["value"]);
results = coll1->search("*", {},
"", {"inches(small:[,55])"},
{}, {2}, 10,
1, FREQUENCY, {true},
10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 10, {}, {}, {}, 0,
"<mark>", "</mark>", {}, 1000,
true, false, true, "", true,
6000*1000, 4, 7, fallback, 4, {off}, INT16_MAX, INT16_MAX,
2, 2, false, "", true, 0, max_score, 100, 0, 0, VALUE).get();
ASSERT_EQ(1, results["facet_counts"][0]["counts"].size());
ASSERT_EQ(2, (int) results["facet_counts"][0]["counts"][0]["count"]);
ASSERT_EQ("small", results["facet_counts"][0]["counts"][0]["value"]);
}
TEST_F(CollectionOptimizedFacetingTest, RangeFacetRangeLabelWithSpace) {
std::vector<field> fields = {field("name", field_types::STRING, false),
field("inches", field_types::FLOAT, true),};
Collection* coll1 = collectionManager.create_collection(
"coll1", 1, fields, "", 0, "", {}, {}).get();
nlohmann::json doc;
doc["id"] = "0";
doc["name"] = "TV 1";
doc["inches"] = 32.4;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
doc["id"] = "1";
doc["name"] = "TV 2";
doc["inches"] = 55;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
doc["id"] = "2";
doc["name"] = "TV 3";
doc["inches"] = 55.6;
ASSERT_TRUE(coll1->add(doc.dump()).ok());
auto results = coll1->search("*", {},
"", {"inches(small tvs with display size:[0,55])"},
{}, {2}, 10,
1, FREQUENCY, {true},
10, spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 4, "", 10, {}, {}, {}, 0,
"<mark>", "</mark>", {}, 1000,
true, false, true, "", true,
6000*1000, 4, 7, fallback, 4, {off}, INT16_MAX, INT16_MAX,
2, 2, false, "", true, 0, max_score, 100, 0, 0, VALUE).get();
ASSERT_EQ(1, results["facet_counts"][0]["counts"].size());
ASSERT_EQ(2, (int) results["facet_counts"][0]["counts"][0]["count"]);
ASSERT_EQ("small tvs with display size", results["facet_counts"][0]["counts"][0]["value"]);
}