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Bump usearch to 2.13.2
This commit is contained in:
parent
58d76fabf6
commit
6170a8663f
2
contrib/SimSIMD
vendored
2
contrib/SimSIMD
vendored
@ -1 +1 @@
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Subproject commit 18d17686124ddebd9fe55eee56b2e0273a613d4b
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Subproject commit 91a76d1ac519b3b9dc8957734a3dabd985f00c26
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2
contrib/usearch
vendored
2
contrib/usearch
vendored
@ -1 +1 @@
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Subproject commit e6c81f78c64c0d8119f854691a06e60660638a25
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Subproject commit e21a5778a0d4469ddaf38c94b7be0196bb701ee4
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@ -59,6 +59,8 @@ Parameters:
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- `ef_construction`: (optional, default: 128)
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- `ef_search`: (optional, default: 64)
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Value 0 for parameters `m`, `ef_construction`, and `ef_search` refers to the default value.
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Example:
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```sql
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@ -2,9 +2,6 @@
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#if USE_USEARCH
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#pragma clang diagnostic push
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#pragma clang diagnostic ignored "-Wpass-failed"
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#include <Columns/ColumnArray.h>
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#include <Common/BitHelpers.h>
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#include <Common/formatReadable.h>
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@ -46,15 +43,15 @@ namespace
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{
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/// The only indexing method currently supported by USearch
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std::set<String> methods = {"hnsw"};
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const std::set<String> methods = {"hnsw"};
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/// Maps from user-facing name to internal name
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std::unordered_map<String, unum::usearch::metric_kind_t> distanceFunctionToMetricKind = {
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const std::unordered_map<String, unum::usearch::metric_kind_t> distanceFunctionToMetricKind = {
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{"L2Distance", unum::usearch::metric_kind_t::l2sq_k},
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{"cosineDistance", unum::usearch::metric_kind_t::cos_k}};
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/// Maps from user-facing name to internal name
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std::unordered_map<String, unum::usearch::scalar_kind_t> quantizationToScalarKind = {
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const std::unordered_map<String, unum::usearch::scalar_kind_t> quantizationToScalarKind = {
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{"f32", unum::usearch::scalar_kind_t::f32_k},
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{"f16", unum::usearch::scalar_kind_t::f16_k},
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{"i8", unum::usearch::scalar_kind_t::i8_k}};
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@ -96,13 +93,18 @@ USearchIndexWithSerialization::USearchIndexWithSerialization(
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unum::usearch::scalar_kind_t scalar_kind,
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UsearchHnswParams usearch_hnsw_params)
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{
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unum::usearch::metric_punned_t metric(dimensions, metric_kind, scalar_kind);
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USearchIndex::metric_t metric(dimensions, metric_kind, scalar_kind);
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unum::usearch::index_dense_config_t config(usearch_hnsw_params.m, usearch_hnsw_params.ef_construction, usearch_hnsw_params.ef_search);
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config.enable_key_lookups = false; /// we don't do row-to-vector lookups
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USearchIndex usearch_index = USearchIndex::make(metric, config);
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swap(usearch_index);
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if (auto error = config.validate(); error) /// already called in vectorSimilarityIndexValidator, call again because usearch may change the config in-place
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throw Exception(ErrorCodes::INCORRECT_DATA, "Invalid parameters passed to vector similarity index. Error: {}", String(error.release()));
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if (auto result = USearchIndex::make(metric, config); !result)
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throw Exception(ErrorCodes::INCORRECT_DATA, "Could not create vector similarity index. Error: {}", String(result.error.release()));
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else
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swap(result.index);
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}
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void USearchIndexWithSerialization::serialize(WriteBuffer & ostr) const
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@ -113,9 +115,8 @@ void USearchIndexWithSerialization::serialize(WriteBuffer & ostr) const
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return true;
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};
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auto result = Base::save_to_stream(callback);
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if (result.error)
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throw Exception::createRuntime(ErrorCodes::INCORRECT_DATA, "Could not save vector similarity index, error: " + String(result.error.release()));
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if (auto result = Base::save_to_stream(callback); !result)
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throw Exception(ErrorCodes::INCORRECT_DATA, "Could not save vector similarity index. Error: {}", String(result.error.release()));
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}
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void USearchIndexWithSerialization::deserialize(ReadBuffer & istr)
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@ -126,26 +127,43 @@ void USearchIndexWithSerialization::deserialize(ReadBuffer & istr)
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return true;
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};
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auto result = Base::load_from_stream(callback);
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if (result.error)
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if (auto result = Base::load_from_stream(callback); !result)
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/// See the comment in MergeTreeIndexGranuleVectorSimilarity::deserializeBinary why we throw here
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throw Exception::createRuntime(ErrorCodes::INCORRECT_DATA, "Could not load vector similarity index, error: " + String(result.error.release()) + " Please drop the index and create it again.");
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throw Exception(ErrorCodes::INCORRECT_DATA, "Could not load vector similarity index. Please drop the index and create it again. Error: {}", String(result.error.release()));
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if (!try_reserve(limits()))
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throw Exception(ErrorCodes::CANNOT_ALLOCATE_MEMORY, "Could not reserve memory for usearch index");
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}
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USearchIndexWithSerialization::Statistics USearchIndexWithSerialization::getStatistics() const
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{
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USearchIndex::stats_t global_stats = Base::stats();
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Statistics statistics = {
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.max_level = max_level(),
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.connectivity = connectivity(),
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.size = size(), /// number of vectors
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.capacity = capacity(), /// number of vectors reserved
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.memory_usage = memory_usage(), /// in bytes, the value is not exact
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.size = size(),
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.capacity = capacity(),
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.memory_usage = memory_usage(),
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.bytes_per_vector = bytes_per_vector(),
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.scalar_words = scalar_words(),
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.statistics = stats()};
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.nodes = global_stats.nodes,
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.edges = global_stats.edges,
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.max_edges = global_stats.max_edges,
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.level_stats = {}};
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for (size_t i = 0; i < statistics.max_level; ++i)
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statistics.level_stats.push_back(Base::stats(i));
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return statistics;
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}
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String USearchIndexWithSerialization::Statistics::toString() const
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{
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return fmt::format("max_level = {}, connectivity = {}, size = {}, capacity = {}, memory_usage = {}, bytes_per_vector = {}, scalar_words = {}, nodes = {}, edges = {}, max_edges = {}",
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max_level, connectivity, size, capacity, ReadableSize(memory_usage), bytes_per_vector, scalar_words, nodes, edges, max_edges);
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}
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MergeTreeIndexGranuleVectorSimilarity::MergeTreeIndexGranuleVectorSimilarity(
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const String & index_name_,
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const Block & index_sample_block_,
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@ -186,8 +204,7 @@ void MergeTreeIndexGranuleVectorSimilarity::serializeBinary(WriteBuffer & ostr)
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index->serialize(ostr);
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auto statistics = index->getStatistics();
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LOG_TRACE(logger, "Wrote vector similarity index: max_level = {}, connectivity = {}, size = {}, capacity = {}, memory_usage = {}",
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statistics.max_level, statistics.connectivity, statistics.size, statistics.capacity, ReadableSize(statistics.memory_usage));
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LOG_TRACE(logger, "Wrote vector similarity index: {}", statistics.toString());
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}
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void MergeTreeIndexGranuleVectorSimilarity::deserializeBinary(ReadBuffer & istr, MergeTreeIndexVersion /*version*/)
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@ -209,8 +226,7 @@ void MergeTreeIndexGranuleVectorSimilarity::deserializeBinary(ReadBuffer & istr,
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index->deserialize(istr);
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auto statistics = index->getStatistics();
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LOG_TRACE(logger, "Loaded vector similarity index: max_level = {}, connectivity = {}, size = {}, capacity = {}, memory_usage = {}",
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statistics.max_level, statistics.connectivity, statistics.size, statistics.capacity, ReadableSize(statistics.memory_usage));
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LOG_TRACE(logger, "Loaded vector similarity index: {}", statistics.toString());
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}
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MergeTreeIndexAggregatorVectorSimilarity::MergeTreeIndexAggregatorVectorSimilarity(
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@ -290,19 +306,24 @@ void MergeTreeIndexAggregatorVectorSimilarity::update(const Block & block, size_
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if (!index)
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index = std::make_shared<USearchIndexWithSerialization>(dimensions, metric_kind, scalar_kind, usearch_hnsw_params);
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/// We use Usearch's index_dense_t as index type which supports only 4 bio entries according to https://github.com/unum-cloud/usearch/tree/main/cpp
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if (index->size() + num_rows > std::numeric_limits<UInt32>::max())
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throw Exception(ErrorCodes::INCORRECT_DATA, "Size of vector similarity index in column {} would exceed 4 billion entries", index_column_name);
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/// Reserving space is mandatory
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if (!index->reserve(roundUpToPowerOfTwoOrZero(index->size() + num_rows)))
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if (!index->try_reserve(roundUpToPowerOfTwoOrZero(index->size() + num_rows)))
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throw Exception(ErrorCodes::CANNOT_ALLOCATE_MEMORY, "Could not reserve memory for vector similarity index");
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for (size_t row = 0; row < num_rows; ++row)
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{
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auto rc = index->add(static_cast<UInt32>(index->size()), &column_array_data_float_data[column_array_offsets[row - 1]]);
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if (!rc)
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throw Exception::createRuntime(ErrorCodes::INCORRECT_DATA, "Could not add data to vector similarity index, error: " + String(rc.error.release()));
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if (auto result = index->add(static_cast<UInt32>(index->size()), &column_array_data_float_data[column_array_offsets[row - 1]]); !result)
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throw Exception(ErrorCodes::INCORRECT_DATA, "Could not add data to vector similarity index. Error: {}", String(result.error.release()));
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else
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{
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ProfileEvents::increment(ProfileEvents::USearchAddCount);
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ProfileEvents::increment(ProfileEvents::USearchAddVisitedMembers, rc.visited_members);
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ProfileEvents::increment(ProfileEvents::USearchAddComputedDistances, rc.computed_distances);
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ProfileEvents::increment(ProfileEvents::USearchAddVisitedMembers, result.visited_members);
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ProfileEvents::increment(ProfileEvents::USearchAddComputedDistances, result.computed_distances);
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}
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}
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}
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else
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@ -356,17 +377,16 @@ std::vector<size_t> MergeTreeIndexConditionVectorSimilarity::getUsefulRanges(Mer
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const std::vector<float> reference_vector = vector_similarity_condition.getReferenceVector();
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auto result = index->search(reference_vector.data(), limit);
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if (result.error)
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throw Exception::createRuntime(ErrorCodes::INCORRECT_DATA, "Could not search in vector similarity index, error: " + String(result.error.release()));
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auto search_result = index->search(reference_vector.data(), limit);
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if (!search_result)
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throw Exception(ErrorCodes::INCORRECT_DATA, "Could not search in vector similarity index. Error: {}", String(search_result.error.release()));
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ProfileEvents::increment(ProfileEvents::USearchSearchCount);
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ProfileEvents::increment(ProfileEvents::USearchSearchVisitedMembers, result.visited_members);
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ProfileEvents::increment(ProfileEvents::USearchSearchComputedDistances, result.computed_distances);
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ProfileEvents::increment(ProfileEvents::USearchSearchVisitedMembers, search_result.visited_members);
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ProfileEvents::increment(ProfileEvents::USearchSearchComputedDistances, search_result.computed_distances);
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std::vector<USearchIndex::vector_key_t> neighbors(result.size()); /// indexes of dots which were closest to the reference vector
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std::vector<USearchIndex::distance_t> distances(result.size());
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result.dump_to(neighbors.data(), distances.data());
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std::vector<USearchIndex::vector_key_t> neighbors(search_result.size()); /// indexes of vectors which were closest to the reference vector
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search_result.dump_to(neighbors.data());
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std::vector<size_t> granules;
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granules.reserve(neighbors.size());
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@ -414,14 +434,13 @@ MergeTreeIndexConditionPtr MergeTreeIndexVectorSimilarity::createIndexCondition(
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MergeTreeIndexPtr vectorSimilarityIndexCreator(const IndexDescription & index)
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{
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const bool has_six_args = (index.arguments.size() == 6);
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/// Default parameters:
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unum::usearch::metric_kind_t metric_kind = distanceFunctionToMetricKind.at(index.arguments[1].safeGet<String>());
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/// use defaults for the other parameters
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unum::usearch::scalar_kind_t scalar_kind = unum::usearch::scalar_kind_t::f32_k;
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UsearchHnswParams usearch_hnsw_params;
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/// Optional parameters:
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const bool has_six_args = (index.arguments.size() == 6);
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if (has_six_args)
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{
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scalar_kind = quantizationToScalarKind.at(index.arguments[2].safeGet<String>());
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@ -466,12 +485,16 @@ void vectorSimilarityIndexValidator(const IndexDescription & index, bool /* atta
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{
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if (!quantizationToScalarKind.contains(index.arguments[2].safeGet<String>()))
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throw Exception(ErrorCodes::INCORRECT_DATA, "Third argument (quantization) of vector similarity index is not supported. Supported quantizations are: {}", joinByComma(quantizationToScalarKind));
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if (index.arguments[3].safeGet<UInt64>() < 2)
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throw Exception(ErrorCodes::INCORRECT_DATA, "Fourth argument (M) of vector similarity index must be > 1");
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if (index.arguments[4].safeGet<UInt64>() < 1)
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throw Exception(ErrorCodes::INCORRECT_DATA, "Fifth argument (ef_construction) of vector similarity index must be > 0");
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if (index.arguments[5].safeGet<UInt64>() < 1)
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throw Exception(ErrorCodes::INCORRECT_DATA, "Sixth argument (ef_search) of vector similarity index must be > 0");
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/// Call Usearche's own parameter validation method for HNSW-specific parameters
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UInt64 m = index.arguments[3].safeGet<UInt64>();
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UInt64 ef_construction = index.arguments[4].safeGet<UInt64>();
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UInt64 ef_search = index.arguments[5].safeGet<UInt64>();
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unum::usearch::index_dense_config_t config(m, ef_construction, ef_search);
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if (auto error = config.validate(); error)
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throw Exception(ErrorCodes::INCORRECT_DATA, "Invalid parameters passed to vector similarity index. Error: {}", String(error.release()));
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}
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/// Check that the index is created on a single column
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@ -4,12 +4,9 @@
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#if USE_USEARCH
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#pragma clang diagnostic push
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#pragma clang diagnostic ignored "-Wpass-failed"
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# include <Storages/MergeTree/VectorSimilarityCondition.h>
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# include <Common/Logger.h>
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# include <usearch/index_dense.hpp>
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#pragma clang diagnostic pop
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#include <Storages/MergeTree/VectorSimilarityCondition.h>
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#include <Common/Logger.h>
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#include <usearch/index_dense.hpp>
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namespace DB
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{
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@ -21,7 +18,7 @@ struct UsearchHnswParams
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size_t ef_search = unum::usearch::default_expansion_search();
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};
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using USearchIndex = unum::usearch::index_dense_gt</*key_at*/ uint32_t, /*compressed_slot_at*/ uint32_t>;
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using USearchIndex = unum::usearch::index_dense_t;
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class USearchIndexWithSerialization : public USearchIndex
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{
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@ -41,13 +38,18 @@ public:
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{
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size_t max_level;
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size_t connectivity;
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size_t size;
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size_t capacity;
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size_t memory_usage;
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/// advanced stats:
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size_t size; /// number of indexed vectors
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size_t capacity; /// reserved number of indexed vectors
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size_t memory_usage; /// byte size (not exact)
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size_t bytes_per_vector;
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size_t scalar_words;
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Base::stats_t statistics;
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size_t nodes;
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size_t edges;
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size_t max_edges;
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std::vector<USearchIndex::stats_t> level_stats; /// for debugging, excluded from getStatistics()
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String toString() const;
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};
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Statistics getStatistics() const;
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@ -3,8 +3,6 @@ Two or six index arguments
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2nd argument (distance function) must be String and L2Distance or cosineDistance
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3nd argument (quantization), if given, must be String and f32, f16, ...
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4nd argument (M), if given, must be UInt64 and > 1
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5nd argument (ef_construction), if given, must be UInt64 and > 0
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6nd argument (ef_search), if given, must be UInt64 and > 0
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Must be created on single column
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Must be created on Array(Float32) columns
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Rejects INSERTs of Arrays with different sizes
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@ -27,12 +27,6 @@ CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similar
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SELECT '4nd argument (M), if given, must be UInt64 and > 1';
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CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f32', 'invalid', 1, 1)) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
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CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f32', 1, 1, 1)) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_DATA }
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SELECT '5nd argument (ef_construction), if given, must be UInt64 and > 0';
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CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f32', 2, 'invalid', 1)) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
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CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f32', 2, 0, 1)) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_DATA }
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SELECT '6nd argument (ef_search), if given, must be UInt64 and > 0';
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CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f32', 2, 1, 'invalid')) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
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CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f32', 2, 1, 0)) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_DATA }
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SELECT 'Must be created on single column';
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CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx (vec, id) TYPE vector_similarity('hnsw', 'L2Distance')) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_NUMBER_OF_COLUMNS }
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