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Merge pull request #68678 from rschu1ze/usearch-2.14

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Vector similarity index: make `bf16` the default quantization
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Robert Schulze 2024-08-28 08:45:02 +00:00 committed by GitHub
commit 9fb4c23c06
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5 changed files with 73 additions and 3 deletions
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2
contrib/usearch vendored

@ -1 +1 @@
Subproject commit e21a5778a0d4469ddaf38c94b7be0196bb701ee4
Subproject commit 7a8967cb442b08ca20c3dd781414378e65957d37

2
docs/en/engines/table-engines/mergetree-family/annindexes.md
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@ -54,7 +54,7 @@ Parameters:
- `distance_function`: either `L2Distance` (the [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance) - the length of a
line between two points in Euclidean space), or `cosineDistance` (the [cosine
distance](https://en.wikipedia.org/wiki/Cosine_similarity#Cosine_distance)- the angle between two non-zero vectors).
- `quantization`: either `f32`, `f16`, or `i8` for storing the vector with reduced precision (optional, default: `f32`)
- `quantization`: either `f64`, `f32`, `f16`, `bf16`, or `i8` for storing the vector with reduced precision (optional, default: `bf16`)
- `m`: the number of neighbors per graph node (optional, default: 16)
- `ef_construction`: (optional, default: 128)
- `ef_search`: (optional, default: 64)

4
src/Storages/MergeTree/MergeTreeIndexVectorSimilarity.cpp
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@ -52,8 +52,10 @@ const std::unordered_map<String, unum::usearch::metric_kind_t> distanceFunctionT
/// Maps from user-facing name to internal name
const std::unordered_map<String, unum::usearch::scalar_kind_t> quantizationToScalarKind = {
{"f64", unum::usearch::scalar_kind_t::f64_k},
{"f32", unum::usearch::scalar_kind_t::f32_k},
{"f16", unum::usearch::scalar_kind_t::f16_k},
{"bf16", unum::usearch::scalar_kind_t::bf16_k},
{"i8", unum::usearch::scalar_kind_t::i8_k}};
/// Usearch provides more quantizations but ^^ above ones seem the only ones comprehensively supported across all distance functions.
@ -461,7 +463,7 @@ MergeTreeIndexPtr vectorSimilarityIndexCreator(const IndexDescription & index)
{
/// Default parameters:
unum::usearch::metric_kind_t metric_kind = distanceFunctionToMetricKind.at(index.arguments[1].safeGet<String>());
unum::usearch::scalar_kind_t scalar_kind = unum::usearch::scalar_kind_t::f32_k;
unum::usearch::scalar_kind_t scalar_kind = unum::usearch::scalar_kind_t::bf16_k;
UsearchHnswParams usearch_hnsw_params;
/// Optional parameters:

36
tests/queries/0_stateless/02354_vector_search_queries.reference
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@ -56,6 +56,24 @@ Expression (Projection)
1 [2,3.2] 2.3323807824711897
2 [4.2,3.4] 4.427188573446585
0 [4.6,2.3] 4.609772130377966
Expression (Projection)
Limit (preliminary LIMIT (without OFFSET))
Sorting (Sorting for ORDER BY)
Expression (Before ORDER BY)
ReadFromMergeTree (default.tab_f64)
Indexes:
PrimaryKey
Condition: true
Parts: 1/1
Granules: 4/4
Skip
Name: idx
Description: vector_similarity GRANULARITY 2
Parts: 1/1
Granules: 2/4
1 [2,3.2] 2.3323807824711897
2 [4.2,3.4] 4.427188573446585
0 [4.6,2.3] 4.609772130377966
Expression (Projection)
Limit (preliminary LIMIT (without OFFSET))
Sorting (Sorting for ORDER BY)
@ -92,6 +110,24 @@ Expression (Projection)
1 [2,3.2] 2.3323807824711897
2 [4.2,3.4] 4.427188573446585
0 [4.6,2.3] 4.609772130377966
Expression (Projection)
Limit (preliminary LIMIT (without OFFSET))
Sorting (Sorting for ORDER BY)
Expression (Before ORDER BY)
ReadFromMergeTree (default.tab_bf16)
Indexes:
PrimaryKey
Condition: true
Parts: 1/1
Granules: 4/4
Skip
Name: idx
Description: vector_similarity GRANULARITY 2
Parts: 1/1
Granules: 2/4
1 [2,3.2] 2.3323807824711897
2 [4.2,3.4] 4.427188573446585
0 [4.6,2.3] 4.609772130377966
Expression (Projection)
Limit (preliminary LIMIT (without OFFSET))
Sorting (Sorting for ORDER BY)

32
tests/queries/0_stateless/02354_vector_search_queries.sql
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@ -75,13 +75,30 @@ SETTINGS max_limit_for_ann_queries = 2; -- LIMIT 3 > 2 --> don't use the ann ind
DROP TABLE tab;
SELECT '-- Non-default quantization';
CREATE TABLE tab_f64(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f64', 0, 0, 0) GRANULARITY 2) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 3;
CREATE TABLE tab_f32(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f32', 0, 0, 0) GRANULARITY 2) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 3;
CREATE TABLE tab_f16(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f16', 0, 0, 0) GRANULARITY 2) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 3;
CREATE TABLE tab_bf16(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'bf16', 0, 0, 0) GRANULARITY 2) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 3;
CREATE TABLE tab_i8(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'i8', 0, 0, 0) GRANULARITY 2) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 3;
INSERT INTO tab_f64 VALUES (0, [4.6, 2.3]), (1, [2.0, 3.2]), (2, [4.2, 3.4]), (3, [5.3, 2.9]), (4, [2.4, 5.2]), (5, [5.3, 2.3]), (6, [1.0, 9.3]), (7, [5.5, 4.7]), (8, [6.4, 3.5]), (9, [5.3, 2.5]), (10, [6.4, 3.4]), (11, [6.4, 3.2]);
INSERT INTO tab_f32 VALUES (0, [4.6, 2.3]), (1, [2.0, 3.2]), (2, [4.2, 3.4]), (3, [5.3, 2.9]), (4, [2.4, 5.2]), (5, [5.3, 2.3]), (6, [1.0, 9.3]), (7, [5.5, 4.7]), (8, [6.4, 3.5]), (9, [5.3, 2.5]), (10, [6.4, 3.4]), (11, [6.4, 3.2]);
INSERT INTO tab_f16 VALUES (0, [4.6, 2.3]), (1, [2.0, 3.2]), (2, [4.2, 3.4]), (3, [5.3, 2.9]), (4, [2.4, 5.2]), (5, [5.3, 2.3]), (6, [1.0, 9.3]), (7, [5.5, 4.7]), (8, [6.4, 3.5]), (9, [5.3, 2.5]), (10, [6.4, 3.4]), (11, [6.4, 3.2]);
INSERT INTO tab_bf16 VALUES (0, [4.6, 2.3]), (1, [2.0, 3.2]), (2, [4.2, 3.4]), (3, [5.3, 2.9]), (4, [2.4, 5.2]), (5, [5.3, 2.3]), (6, [1.0, 9.3]), (7, [5.5, 4.7]), (8, [6.4, 3.5]), (9, [5.3, 2.5]), (10, [6.4, 3.4]), (11, [6.4, 3.2]);
INSERT INTO tab_i8 VALUES (0, [4.6, 2.3]), (1, [2.0, 3.2]), (2, [4.2, 3.4]), (3, [5.3, 2.9]), (4, [2.4, 5.2]), (5, [5.3, 2.3]), (6, [1.0, 9.3]), (7, [5.5, 4.7]), (8, [6.4, 3.5]), (9, [5.3, 2.5]), (10, [6.4, 3.4]), (11, [6.4, 3.2]);
WITH [0.0, 2.0] AS reference_vec
SELECT id, vec, L2Distance(vec, reference_vec)
FROM tab_f64
ORDER BY L2Distance(vec, reference_vec)
LIMIT 3;
EXPLAIN indexes = 1
WITH [0.0, 2.0] AS reference_vec
SELECT id, vec, L2Distance(vec, reference_vec)
FROM tab_f64
ORDER BY L2Distance(vec, reference_vec)
LIMIT 3;
WITH [0.0, 2.0] AS reference_vec
SELECT id, vec, L2Distance(vec, reference_vec)
FROM tab_f32
@ -108,6 +125,19 @@ FROM tab_f16
ORDER BY L2Distance(vec, reference_vec)
LIMIT 3;
WITH [0.0, 2.0] AS reference_vec
SELECT id, vec, L2Distance(vec, reference_vec)
FROM tab_bf16
ORDER BY L2Distance(vec, reference_vec)
LIMIT 3;
EXPLAIN indexes = 1
WITH [0.0, 2.0] AS reference_vec
SELECT id, vec, L2Distance(vec, reference_vec)
FROM tab_bf16
ORDER BY L2Distance(vec, reference_vec)
LIMIT 3;
WITH [0.0, 2.0] AS reference_vec
SELECT id, vec, L2Distance(vec, reference_vec)
FROM tab_i8
@ -121,8 +151,10 @@ FROM tab_i8
ORDER BY L2Distance(vec, reference_vec)
LIMIT 3;
DROP TABLE tab_f64;
DROP TABLE tab_f32;
DROP TABLE tab_f16;
DROP TABLE tab_bf16;
DROP TABLE tab_i8;
SELECT '-- Index on Array(Float64) column';