Merge pull request #70616 from rschu1ze/query-time-ef-search

Vector search: allow to specify HNSW parameter `ef_search` at query time
2024-11-24 16:42:05 +00:00 · 2024-10-21 06:47:46 +00:00 · 2024-10-21 06:47:46 +00:00 · d02a31da44
commit d02a31da44
parent 4c9e4699df c69cd58ec8
24 changed files with 281 additions and 165 deletions
--- a/contrib/usearch
+++ b/contrib/usearch
@ -1 +1 @@
-Subproject commit d1d33eac94acd3b628e0b446c927ec3295ef63c7
+Subproject commit 1706420acafbd83d852c512dcf343af0a4059e48
--- a/docs/en/engines/table-engines/mergetree-family/annindexes.md
+++ b/docs/en/engines/table-engines/mergetree-family/annindexes.md
@ -43,7 +43,7 @@ CREATE TABLE table
 (
  id Int64,
  vectors Array(Float32),
-  INDEX index_name vectors TYPE vector_similarity(method, distance_function[, quantization, connectivity, expansion_add, expansion_search]) [GRANULARITY N]
+  INDEX index_name vectors TYPE vector_similarity(method, distance_function[, quantization, hnsw_max_connections_per_layer, hnsw_candidate_list_size_for_construction]) [GRANULARITY N]
 )
 ENGINE = MergeTree
 ORDER BY id;
@ -55,11 +55,13 @@ Parameters:
  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 `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)
+- `hnsw_max_connections_per_layer`: the number of neighbors per HNSW graph node, also known as `M` in the [HNSW
+  paper](https://doi.org/10.1109/TPAMI.2018.2889473) (optional, default: 16)
+- `hnsw_candidate_list_size_for_construction`: the size of the dynamic candidate list when constructing the HNSW graph, also known as
+  `ef_construction` in the original [HNSW paper](https://doi.org/10.1109/TPAMI.2018.2889473) (optional, default: 128)

-Value 0 for parameters `m`, `ef_construction`, and `ef_search` refers to the default value.
+Values 0 for parameters `hnsw_max_connections_per_layer` and `hnsw_candidate_list_size_for_construction` means using the default values of
+these parameters.

 Example:

@ -115,6 +117,11 @@ ANN indexes are built during column insertion and merge. As a result, `INSERT` a
 tables. ANNIndexes are ideally used only with immutable or rarely changed data, respectively when are far more read requests than write
 requests.

+:::tip
+To reduce the cost of building vector similarity indexes, consider setting `materialize_skip_indexes_on_insert` which disables the
+construction of skipping indexes on newly inserted parts. Search would fall back to exact search but as inserted parts are typically small
+compared to the total table size, the performance impact of that would be negligible.
+
 ANN indexes support this type of query:

 ``` sql
@ -124,6 +131,7 @@ FROM table
 WHERE ...                       -- WHERE clause is optional
 ORDER BY Distance(vectors, reference_vector)
 LIMIT N
+SETTINGS enable_analyzer = 0;   -- Temporary limitation, will be lifted
 ```

 :::tip
@ -135,6 +143,10 @@ clickhouse-client --param_vec='hello' --query="SELECT * FROM table WHERE L2Dista
 ```
 :::

+To search using a different value of HNSW parameter `hnsw_candidate_list_size_for_search` (default: 64), also known as `ef_search` in the
+original [HNSW paper](https://doi.org/10.1109/TPAMI.2018.2889473), run the `SELECT` query with `SETTINGS hnsw_candidate_list_size_for_search
+= <value>`.
+
 **Restrictions**: Approximate algorithms used to determine the nearest neighbors require a limit, hence queries without `LIMIT` clause
 cannot utilize ANN indexes. Also, ANN indexes are only used if the query has a `LIMIT` value smaller than setting
 `max_limit_for_ann_queries` (default: 1 million rows). This is a safeguard to prevent large memory allocations by external libraries for
--- a/docs/en/operations/settings/merge-tree-settings.md
+++ b/docs/en/operations/settings/merge-tree-settings.md
@ -49,7 +49,7 @@ Default value: 8192.

 Maximum size of data granules in bytes.

-Default value: 10Mb.
+Default value: 10485760 (ca. 10 MiB).

 To restrict the granule size only by number of rows, set to 0 (not recommended).

--- a/docs/en/sql-reference/functions/random-functions.md
+++ b/docs/en/sql-reference/functions/random-functions.md
@ -24,7 +24,7 @@ Returns a random UInt32 number with uniform distribution.

 Uses a linear congruential generator with an initial state obtained from the system, which means that while it appears random, it's not truly random and can be predictable if the initial state is known. For scenarios where true randomness is crucial, consider using alternative methods like system-level calls or integrating with external libraries.

-### Syntax
+**Syntax**

 ```sql
 rand()
@ -32,15 +32,15 @@ rand()

 Alias: `rand32`

-### Arguments
+**Arguments**

 None.

-### Returned value
+**Returned value**

 Returns a number of type UInt32.

-### Example
+**Example**

 ```sql
 SELECT rand();
@ -54,23 +54,23 @@ SELECT rand();

 Returns a random UInt64 integer (UInt64) number

-### Syntax
+**Syntax**

 ```sql
 rand64()
 ```

-### Arguments
+**Arguments**

 None.

-### Returned value
+**Arguments**

 Returns a number UInt64 number with uniform distribution.

 Uses a linear congruential generator with an initial state obtained from the system, which means that while it appears random, it's not truly random and can be predictable if the initial state is known. For scenarios where true randomness is crucial, consider using alternative methods like system-level calls or integrating with external libraries.

-### Example
+**Example**

 ```sql
 SELECT rand64();
@ -84,21 +84,21 @@ SELECT rand64();

 Returns a random Float64 number.

-### Syntax
+**Syntax**

 ```sql
 randCanonical()
 ```

-### Arguments
+**Arguments**

 None.

-### Returned value
+**Arguments**

 Returns a Float64 value between 0 (inclusive) and 1 (exclusive).

-### Example
+**Example**

 ```sql
 SELECT randCanonical();
@ -112,25 +112,25 @@ SELECT randCanonical();

 Generates a single constant column filled with a random value. Unlike `rand`, this function ensures the same random value appears in every row of the generated column, making it useful for scenarios requiring a consistent random seed across rows in a single query.

-### Syntax
+**Syntax**

 ```sql
 randConstant([x]);
 ```

-### Arguments
+**Arguments**

 - **[x] (Optional):** An optional expression that influences the generated random value. Even if provided, the resulting value will still be constant within the same query execution. Different queries using the same expression will likely generate different constant values.

-### Returned value
+**Arguments**

 Returns a column of type UInt32 containing the same random value in each row.

-### Implementation details
+**Implementation details**

 The actual output will be different for each query execution, even with the same optional expression. The optional parameter may not significantly change the generated value compared to using `randConstant` alone.

-### Examples
+**Example**

 ```sql
 SELECT randConstant() AS random_value;
@ -156,22 +156,22 @@ SELECT randConstant(10) AS random_value;

 Returns a random Float64 drawn uniformly from interval [`min`, `max`].

-### Syntax
+**Syntax**

 ```sql
 randUniform(min, max)
 ```

-### Arguments
+**Arguments**

 - `min` - `Float64` - left boundary of the range,
 - `max` - `Float64` - right boundary of the range.

-### Returned value
+**Arguments**

 A random number of type [Float64](../data-types/float.md).

-### Example
+**Example**

 ```sql
 SELECT randUniform(5.5, 10) FROM numbers(5)
--- a/docs/en/sql-reference/table-functions/generate.md
+++ b/docs/en/sql-reference/table-functions/generate.md
@ -18,9 +18,9 @@ generateRandom(['name TypeName[, name TypeName]...', [, 'random_seed'[, 'max_str

 - `name` — Name of corresponding column.
 - `TypeName` — Type of corresponding column.
- `max_array_length` — Maximum elements for all generated arrays or maps. Defaults to `10`.
- `max_string_length` — Maximum string length for all generated strings. Defaults to `10`.
 - `random_seed` — Specify random seed manually to produce stable results. If NULL — seed is randomly generated.
+- `max_string_length` — Maximum string length for all generated strings. Defaults to `10`.
+- `max_array_length` — Maximum elements for all generated arrays or maps. Defaults to `10`.

 **Returned Value**

--- a/docs/ru/sql-reference/table-functions/generate.md
+++ b/docs/ru/sql-reference/table-functions/generate.md
@ -18,9 +18,9 @@ generateRandom('name TypeName[, name TypeName]...', [, 'random_seed'[, 'max_stri

 - `name` — название соответствующего столбца.
 - `TypeName` — тип соответствующего столбца.
- `max_array_length` — максимальная длина массива для всех сгенерированных массивов. По умолчанию `10`.
- `max_string_length` — максимальная длина строки для всех генерируемых строк. По умолчанию `10`.
 - `random_seed` — укажите состояние генератора случайных чисел вручную, чтобы получить стабильные результаты. Если значение равно `NULL` - генератор инициализируется случайным состоянием.
+- `max_string_length` — максимальная длина строки для всех генерируемых строк. По умолчанию `10`.
+- `max_array_length` — максимальная длина массива для всех сгенерированных массивов. По умолчанию `10`.

 **Возвращаемое значение**

--- a/docs/zh/sql-reference/table-functions/generate.md
+++ b/docs/zh/sql-reference/table-functions/generate.md
@ -18,9 +18,9 @@ generateRandom('name TypeName[, name TypeName]...', [, 'random_seed'[, 'max_stri

 -   `name` — 对应列的名称。
 -   `TypeName` — 对应列的类型。
-   `max_array_length` — 生成数组的最大长度。 默认为10。
-   `max_string_length` — 生成字符串的最大长度。 默认为10。
 -   `random_seed` — 手动指定随机种子以产生稳定的结果。 如果为NULL-种子是随机生成的。
+-   `max_string_length` — 生成字符串的最大长度。 默认为10。
+-   `max_array_length` — 生成数组的最大长度。 默认为10。

 **返回值**

--- a/src/Core/Settings.cpp
+++ b/src/Core/Settings.cpp
@ -5556,7 +5556,10 @@ If it is set to true, allow to specify experimental compression codecs (but we d
 Only in ClickHouse Cloud. Allow to create ShareSet and SharedJoin
 )", 0) \
    M(UInt64, max_limit_for_ann_queries, 1'000'000, R"(
-SELECT queries with LIMIT bigger than this setting cannot use ANN indexes. Helps to prevent memory overflows in ANN search indexes.
+SELECT queries with LIMIT bigger than this setting cannot use vector similarity indexes. Helps to prevent memory overflows in vector similarity indexes.
+)", 0) \
+    M(UInt64, hnsw_candidate_list_size_for_search, 0, R"(
+The size of the dynamic candidate list when searching the vector similarity index, also known as 'ef_search'. 0 means USearch's default value (64).
 )", 0) \
    M(Bool, throw_on_unsupported_query_inside_transaction, true, R"(
 Throw exception if unsupported query is used inside transaction
--- a/src/Core/SettingsChangesHistory.cpp
+++ b/src/Core/SettingsChangesHistory.cpp
@ -103,6 +103,7 @@ static std::initializer_list<std::pair<ClickHouseVersion, SettingsChangesHistory
            {"input_format_orc_dictionary_as_low_cardinality", false, true, "Treat ORC dictionary encoded columns as LowCardinality columns while reading ORC files"},
            {"allow_experimental_refreshable_materialized_view", false, true, "Not experimental anymore"},
            {"max_parts_to_move", 1000, 1000, "New setting"},
+            {"hnsw_candidate_list_size_for_search", 0, 0, "New setting"},
            {"allow_reorder_prewhere_conditions", false, true, "New setting"},
            {"input_format_parquet_bloom_filter_push_down", false, true, "When reading Parquet files, skip whole row groups based on the WHERE/PREWHERE expressions and bloom filter in the Parquet metadata."},
            {"date_time_64_output_format_cut_trailing_zeros_align_to_groups_of_thousands", false, false, "Dynamically trim the trailing zeros of datetime64 values to adjust the output scale to (0, 3, 6), corresponding to 'seconds', 'milliseconds', and 'microseconds'."}
--- a/src/Functions/randCanonical.cpp
+++ b/src/Functions/randCanonical.cpp
--- a/src/Storages/IndicesDescription.cpp
+++ b/src/Storages/IndicesDescription.cpp
@ -159,6 +159,14 @@ bool IndicesDescription::has(const String & name) const
    return false;
 }

+bool IndicesDescription::hasType(const String & type) const
+{
+    for (const auto & index : *this)
+        if (index.type == type)
+            return true;
+    return false;
+}
+
 String IndicesDescription::toString() const
 {
    if (empty())
--- a/src/Storages/IndicesDescription.h
+++ b/src/Storages/IndicesDescription.h
@ -65,6 +65,8 @@ struct IndicesDescription : public std::vector<IndexDescription>, IHints<>
 {
    /// Index with name exists
    bool has(const String & name) const;
+    /// Index with type exists
+    bool hasType(const String & type) const;
    /// Convert description to string
    String toString() const;
    /// Parse description from string
--- a/src/Storages/MergeTree/MergeTreeData.cpp
+++ b/src/Storages/MergeTree/MergeTreeData.cpp
@ -261,6 +261,7 @@ namespace ErrorCodes
    extern const int SUPPORT_IS_DISABLED;
    extern const int TOO_MANY_SIMULTANEOUS_QUERIES;
    extern const int INCORRECT_QUERY;
+    extern const int INVALID_SETTING_VALUE;
    extern const int CANNOT_RESTORE_TABLE;
    extern const int ZERO_COPY_REPLICATION_ERROR;
    extern const int NOT_INITIALIZED;
@ -759,6 +760,16 @@ void MergeTreeData::checkProperties(
        }
    }

+    /// If adaptive index granularity is disabled, certain vector search queries with PREWHERE run into LOGICAL_ERRORs.
+    ///     SET allow_experimental_vector_similarity_index = 1;
+    ///     CREATE TABLE tab (`id` Int32, `vec` Array(Float32), INDEX idx vec TYPE  vector_similarity('hnsw', 'L2Distance') GRANULARITY 100000000) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity_bytes = 0;
+    ///     INSERT INTO tab SELECT number, [toFloat32(number), 0.] FROM numbers(10000);
+    ///     WITH [1., 0.] AS reference_vec SELECT id, L2Distance(vec, reference_vec) FROM tab PREWHERE toLowCardinality(10) ORDER BY L2Distance(vec, reference_vec) ASC LIMIT 100;
+    /// As a workaround, force enabled adaptive index granularity for now (it is the default anyways).
+    if (new_metadata.secondary_indices.hasType("vector_similarity") && (*getSettings())[MergeTreeSetting::index_granularity_bytes] == 0)
+        throw Exception(ErrorCodes::INVALID_SETTING_VALUE,
+            "Experimental vector similarity index can only be used with MergeTree setting 'index_granularity_bytes' != 0");
+
    if (!new_metadata.projections.empty())
    {
        std::unordered_set<String> projections_names;
@ -3310,6 +3321,16 @@ void MergeTreeData::checkAlterIsPossible(const AlterCommands & commands, Context
        throw Exception(ErrorCodes::SUPPORT_IS_DISABLED,
            "Experimental vector similarity index is disabled (turn on setting 'allow_experimental_vector_similarity_index')");

+    /// If adaptive index granularity is disabled, certain vector search queries with PREWHERE run into LOGICAL_ERRORs.
+    ///     SET allow_experimental_vector_similarity_index = 1;
+    ///     CREATE TABLE tab (`id` Int32, `vec` Array(Float32), INDEX idx vec TYPE  vector_similarity('hnsw', 'L2Distance') GRANULARITY 100000000) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity_bytes = 0;
+    ///     INSERT INTO tab SELECT number, [toFloat32(number), 0.] FROM numbers(10000);
+    ///     WITH [1., 0.] AS reference_vec SELECT id, L2Distance(vec, reference_vec) FROM tab PREWHERE toLowCardinality(10) ORDER BY L2Distance(vec, reference_vec) ASC LIMIT 100;
+    /// As a workaround, force enabled adaptive index granularity for now (it is the default anyways).
+    if (AlterCommands::hasVectorSimilarityIndex(new_metadata) && (*getSettings())[MergeTreeSetting::index_granularity_bytes] == 0)
+        throw Exception(ErrorCodes::INVALID_SETTING_VALUE,
+            "Experimental vector similarity index can only be used with MergeTree setting 'index_granularity_bytes' != 0");
+
    for (const auto & disk : getDisks())
        if (!disk->supportsHardLinks() && !commands.isSettingsAlter() && !commands.isCommentAlter())
            throw Exception(
--- a/src/Storages/MergeTree/MergeTreeIndexVectorSimilarity.cpp
+++ b/src/Storages/MergeTree/MergeTreeIndexVectorSimilarity.cpp
@ -10,6 +10,7 @@
 #include <Common/typeid_cast.h>
 #include <Core/Field.h>
 #include <Core/ServerSettings.h>
+#include <Core/Settings.h>
 #include <DataTypes/DataTypeArray.h>
 #include <IO/ReadHelpers.h>
 #include <IO/WriteHelpers.h>
@ -45,6 +46,11 @@ namespace ErrorCodes
    extern const int NOT_IMPLEMENTED;
 }

+namespace Setting
+{
+    extern const SettingsUInt64 hnsw_candidate_list_size_for_search;
+}
+
 namespace
 {

@ -104,7 +110,7 @@ USearchIndexWithSerialization::USearchIndexWithSerialization(
 {
    USearchIndex::metric_t metric(dimensions, metric_kind, scalar_kind);

-    unum::usearch::index_dense_config_t config(usearch_hnsw_params.m, usearch_hnsw_params.ef_construction, usearch_hnsw_params.ef_search);
+    unum::usearch::index_dense_config_t config(usearch_hnsw_params.connectivity, usearch_hnsw_params.expansion_add, unum::usearch::default_expansion_search());
    config.enable_key_lookups = false; /// we don't do row-to-vector lookups

    auto result = USearchIndex::make(metric, config);
@ -399,6 +405,7 @@ MergeTreeIndexConditionVectorSimilarity::MergeTreeIndexConditionVectorSimilarity
    ContextPtr context)
    : vector_similarity_condition(query, context)
    , metric_kind(metric_kind_)
+    , expansion_search(context->getSettingsRef()[Setting::hnsw_candidate_list_size_for_search])
 {
 }

@ -430,13 +437,17 @@ std::vector<UInt64> MergeTreeIndexConditionVectorSimilarity::calculateApproximat
    const USearchIndexWithSerializationPtr index = granule->index;

    if (vector_similarity_condition.getDimensions() != index->dimensions())
-        throw Exception(ErrorCodes::INCORRECT_QUERY, "The dimension of the space in the request ({}) "
-            "does not match the dimension in the index ({})",
+        throw Exception(ErrorCodes::INCORRECT_QUERY, "The dimension of the space in the request ({}) does not match the dimension in the index ({})",
            vector_similarity_condition.getDimensions(), index->dimensions());

    const std::vector<Float64> reference_vector = vector_similarity_condition.getReferenceVector();

-    auto search_result = index->search(reference_vector.data(), limit);
+    /// We want to run the search with the user-provided value for setting hnsw_candidate_list_size_for_search (aka. expansion_search).
+    /// The way to do this in USearch is to call index_dense_gt::change_expansion_search. Unfortunately, this introduces a need to
+    /// synchronize index access, see https://github.com/unum-cloud/usearch/issues/500. As a workaround, we extended USearch' search method
+    /// to accept a custom expansion_add setting. The config value is only used on the fly, i.e. not persisted in the index.
+
+    auto search_result = index->search(reference_vector.data(), limit, USearchIndex::any_thread(), false, (expansion_search == 0) ? unum::usearch::default_expansion_search() : expansion_search);
    if (!search_result)
        throw Exception(ErrorCodes::INCORRECT_DATA, "Could not search in vector similarity index. Error: {}", String(search_result.error.release()));

@ -501,13 +512,12 @@ MergeTreeIndexPtr vectorSimilarityIndexCreator(const IndexDescription & index)
    UsearchHnswParams usearch_hnsw_params;

    /// Optional parameters:
-    const bool has_six_args = (index.arguments.size() == 6);
-    if (has_six_args)
+    const bool has_five_args = (index.arguments.size() == 5);
+    if (has_five_args)
    {
        scalar_kind = quantizationToScalarKind.at(index.arguments[2].safeGet<String>());
-        usearch_hnsw_params = {.m               = index.arguments[3].safeGet<UInt64>(),
-                               .ef_construction = index.arguments[4].safeGet<UInt64>(),
-                               .ef_search       = index.arguments[5].safeGet<UInt64>()};
+        usearch_hnsw_params = {.connectivity  = index.arguments[3].safeGet<UInt64>(),
+                               .expansion_add = index.arguments[4].safeGet<UInt64>()};
    }

    return std::make_shared<MergeTreeIndexVectorSimilarity>(index, metric_kind, scalar_kind, usearch_hnsw_params);
@ -516,25 +526,23 @@ MergeTreeIndexPtr vectorSimilarityIndexCreator(const IndexDescription & index)
 void vectorSimilarityIndexValidator(const IndexDescription & index, bool /* attach */)
 {
    const bool has_two_args = (index.arguments.size() == 2);
-    const bool has_six_args = (index.arguments.size() == 6);
+    const bool has_five_args = (index.arguments.size() == 5);

    /// Check number and type of arguments
-    if (!has_two_args && !has_six_args)
-        throw Exception(ErrorCodes::INCORRECT_QUERY, "Vector similarity index must have two or six arguments");
+    if (!has_two_args && !has_five_args)
+        throw Exception(ErrorCodes::INCORRECT_QUERY, "Vector similarity index must have two or five arguments");
    if (index.arguments[0].getType() != Field::Types::String)
        throw Exception(ErrorCodes::INCORRECT_QUERY, "First argument of vector similarity index (method) must be of type String");
    if (index.arguments[1].getType() != Field::Types::String)
        throw Exception(ErrorCodes::INCORRECT_QUERY, "Second argument of vector similarity index (metric) must be of type String");
-    if (has_six_args)
+    if (has_five_args)
    {
        if (index.arguments[2].getType() != Field::Types::String)
            throw Exception(ErrorCodes::INCORRECT_QUERY, "Third argument of vector similarity index (quantization) must be of type String");
        if (index.arguments[3].getType() != Field::Types::UInt64)
-            throw Exception(ErrorCodes::INCORRECT_QUERY, "Fourth argument of vector similarity index (M) must be of type UInt64");
+            throw Exception(ErrorCodes::INCORRECT_QUERY, "Fourth argument of vector similarity index (hnsw_max_connections_per_layer) must be of type UInt64");
        if (index.arguments[4].getType() != Field::Types::UInt64)
-            throw Exception(ErrorCodes::INCORRECT_QUERY, "Fifth argument of vector similarity index (ef_construction) must be of type UInt64");
-        if (index.arguments[5].getType() != Field::Types::UInt64)
-            throw Exception(ErrorCodes::INCORRECT_QUERY, "Sixth argument of vector similarity index (ef_search) must be of type UInt64");
+            throw Exception(ErrorCodes::INCORRECT_QUERY, "Fifth argument of vector similarity index (hnsw_candidate_list_size_for_construction) must be of type UInt64");
    }

    /// Check that passed arguments are supported
@ -542,18 +550,17 @@ void vectorSimilarityIndexValidator(const IndexDescription & index, bool /* atta
        throw Exception(ErrorCodes::INCORRECT_DATA, "First argument (method) of vector similarity index is not supported. Supported methods are: {}", joinByComma(methods));
    if (!distanceFunctionToMetricKind.contains(index.arguments[1].safeGet<String>()))
        throw Exception(ErrorCodes::INCORRECT_DATA, "Second argument (distance function) of vector similarity index is not supported. Supported distance function are: {}", joinByComma(distanceFunctionToMetricKind));
-    if (has_six_args)
+    if (has_five_args)
    {
        if (!quantizationToScalarKind.contains(index.arguments[2].safeGet<String>()))
            throw Exception(ErrorCodes::INCORRECT_DATA, "Third argument (quantization) of vector similarity index is not supported. Supported quantizations are: {}", joinByComma(quantizationToScalarKind));

        /// Call Usearch's own parameter validation method for HNSW-specific parameters
-        UInt64 m = index.arguments[3].safeGet<UInt64>();
-        UInt64 ef_construction = index.arguments[4].safeGet<UInt64>();
-        UInt64 ef_search = index.arguments[5].safeGet<UInt64>();
-
-        unum::usearch::index_dense_config_t config(m, ef_construction, ef_search);
+        UInt64 connectivity = index.arguments[3].safeGet<UInt64>();
+        UInt64 expansion_add = index.arguments[4].safeGet<UInt64>();
+        UInt64 expansion_search = unum::usearch::default_expansion_search();

+        unum::usearch::index_dense_config_t config(connectivity, expansion_add, expansion_search);
        if (auto error = config.validate(); error)
            throw Exception(ErrorCodes::INCORRECT_DATA, "Invalid parameters passed to vector similarity index. Error: {}", String(error.release()));
    }
--- a/src/Storages/MergeTree/MergeTreeIndexVectorSimilarity.h
+++ b/src/Storages/MergeTree/MergeTreeIndexVectorSimilarity.h
@ -13,9 +13,8 @@ namespace DB

 struct UsearchHnswParams
 {
-    size_t m = unum::usearch::default_connectivity();
-    size_t ef_construction = unum::usearch::default_expansion_add();
-    size_t ef_search = unum::usearch::default_expansion_search();
+    size_t connectivity = unum::usearch::default_connectivity();
+    size_t expansion_add = unum::usearch::default_expansion_add();
 };

 using USearchIndex = unum::usearch::index_dense_t;
@ -142,6 +141,7 @@ public:
 private:
    const VectorSimilarityCondition vector_similarity_condition;
    const unum::usearch::metric_kind_t metric_kind;
+    const size_t expansion_search;
 };


--- a/tests/queries/0_stateless/02354_vector_search_bugs.reference
+++ b/tests/queries/0_stateless/02354_vector_search_bugs.reference
@ -40,3 +40,4 @@ Expression (Projection)
            Condition: true
            Parts: 1/1
            Granules: 4/4
+index_granularity_bytes = 0 is disallowed
--- a/tests/queries/0_stateless/02354_vector_search_bugs.sql
+++ b/tests/queries/0_stateless/02354_vector_search_bugs.sql
@ -37,7 +37,7 @@ DROP TABLE tab;

 SELECT 'Correctness of index with > 1 mark';

-CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance')) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity_bytes = 0, min_rows_for_wide_part = 0, min_bytes_for_wide_part = 0, index_granularity = 8192; -- disable adaptive granularity due to bug
+CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance')) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 8192;
 INSERT INTO tab SELECT number, [toFloat32(number), 0.0] from numbers(10000);

 WITH [1.0, 0.0] AS reference_vec
@ -56,7 +56,7 @@ DROP TABLE tab;

 SELECT 'Issue #69085: Reference vector computed by a subquery';

-CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'cosineDistance', 'f16', 0, 0, 0) GRANULARITY 2) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 3;
+CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'cosineDistance', 'f16', 0, 0) GRANULARITY 2) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 3;
 INSERT INTO tab 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]);

 -- works
@ -100,3 +100,20 @@ FROM tab
 ORDER BY distance
 LIMIT 1
 SETTINGS enable_analyzer = 0;
+
+DROP TABLE tab;
+
+SELECT 'index_granularity_bytes = 0 is disallowed';
+
+-- If adaptive index granularity is disabled, certain vector search queries with PREWHERE run into LOGICAL_ERRORs.
+--     SET allow_experimental_vector_similarity_index = 1;
+--     CREATE TABLE tab (`id` Int32, `vec` Array(Float32), INDEX idx vec TYPE  vector_similarity('hnsw', 'L2Distance') GRANULARITY 100000000) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity_bytes = 0;
+--     INSERT INTO tab SELECT number, [toFloat32(number), 0.] FROM numbers(10000);
+--     WITH [1., 0.] AS reference_vec SELECT id, L2Distance(vec, reference_vec) FROM tab PREWHERE toLowCardinality(10) ORDER BY L2Distance(vec, reference_vec) ASC LIMIT 100;
+-- As a workaround, force enabled adaptive index granularity for now (it is the default anyways).
+CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance')) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity_bytes = 0; -- { serverError INVALID_SETTING_VALUE }
+
+CREATE TABLE tab(id Int32, vec Array(Float32)) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity_bytes = 0;
+ALTER TABLE tab ADD INDEX vec_idx1(vec) TYPE vector_similarity('hnsw', 'cosineDistance'); -- { serverError INVALID_SETTING_VALUE }
+
+DROP TABLE tab;
--- a/tests/queries/0_stateless/02354_vector_search_expansion_search.reference
+++ b/tests/queries/0_stateless/02354_vector_search_expansion_search.reference
@ -0,0 +1 @@
+2
--- a/tests/queries/0_stateless/02354_vector_search_expansion_search.sql
+++ b/tests/queries/0_stateless/02354_vector_search_expansion_search.sql
@ -0,0 +1,41 @@
+-- Tags: no-fasttest, long, no-asan, no-asan, no-ubsan, no-debug
+-- ^^ Disable test for slow builds: generating data takes time but a sufficiently large data set
+-- is necessary for different hnsw_candidate_list_size_for_search settings to make a difference
+
+-- Tests vector search with setting 'hnsw_candidate_list_size_for_search'
+
+SET allow_experimental_vector_similarity_index = 1;
+SET enable_analyzer = 0;
+
+DROP TABLE IF EXISTS tab;
+
+CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance')) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 8192;
+
+-- Generate random values but with a fixed seed (conceptually), so that the data is deterministic.
+-- Unfortunately, no random functions in ClickHouse accepts a seed. Instead, abuse the numbers table + hash functions to provide
+-- deterministic randomness.
+INSERT INTO tab SELECT number, [sipHash64(number)/18446744073709551615, wyHash64(number)/18446744073709551615] FROM numbers(370000); -- 18446744073709551615 is the biggest UInt64
+
+DROP TABLE IF EXISTS results;
+CREATE TABLE results(id Int32) ENGINE = Memory;
+
+-- Standard vector search with default hnsw_candidate_list_size_for_search = 64
+INSERT INTO results
+    SELECT id
+    FROM tab
+    ORDER BY L2Distance(vec, [0.5, 0.5])
+    LIMIT 1;
+
+-- Vector search with custom hnsw_candidate_list_size_for_search
+INSERT INTO results
+    SELECT id
+    FROM tab
+    ORDER BY L2Distance(vec, [0.5, 0.5])
+    LIMIT 1
+    SETTINGS hnsw_candidate_list_size_for_search = 1;
+
+-- Expect that matches are different
+SELECT count(distinct *) FROM results;
+
+DROP TABLE results;
+DROP TABLE tab;
--- a/tests/queries/0_stateless/02354_vector_search_index_creation_negative.reference
+++ b/tests/queries/0_stateless/02354_vector_search_index_creation_negative.reference
@ -1,4 +1,4 @@
-Two or six index arguments
+Two or five index arguments
 1st argument (method) must be String and hnsw
 2nd argument (distance function) must be String and L2Distance or cosineDistance
 3nd argument (quantization), if given, must be String and f32, f16, ...
--- a/tests/queries/0_stateless/02354_vector_search_index_creation_negative.sql
+++ b/tests/queries/0_stateless/02354_vector_search_index_creation_negative.sql
@ -6,12 +6,12 @@ SET allow_experimental_vector_similarity_index = 1;

 DROP TABLE IF EXISTS tab;

-SELECT 'Two or six index arguments';
+SELECT 'Two or five index arguments';
 CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
 CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity()) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
 CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('cant_have_one_arg')) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
 CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('cant', 'have', 'three_args')) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
-CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('cant', 'have', 'more', 'than', 'six', 'args', '!')) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
+CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('cant', 'have', 'more', 'than', 'five', 'args', '!')) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }

 SELECT '1st argument (method) must be String and hnsw';
 CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity(3, 'L2Distance')) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
@ -22,11 +22,11 @@ CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similar
 CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'invalid_distance')) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_DATA }

 SELECT '3nd argument (quantization), if given, must be String and f32, f16, ...';
-CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 1, 1, 1, 1)) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
-CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'invalid', 2, 1, 1)) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_DATA }
+CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 1, 1, 1)) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_QUERY }
+CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'invalid', 2, 1)) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_DATA }
 SELECT '4nd argument (M), if given, must be UInt64 and > 1';
 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 }
-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 }
+CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f32', 1, 1)) ENGINE = MergeTree ORDER BY id; -- { serverError INCORRECT_DATA }

 SELECT 'Must be created on single column';
 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 }
--- a/tests/queries/0_stateless/02354_vector_search_queries.reference
+++ b/tests/queries/0_stateless/02354_vector_search_queries.reference
@ -37,7 +37,7 @@ Expression (Projection)
            Parts: 1/1
            Granules: 2/4
 Special cases
-- Non-default metric, M, ef_construction, ef_search
+-- Non-default metric, hnsw_max_connections_per_layer, hnsw_candidate_list_size_for_construction
 6	[1,9.3]	0.005731362878640178
 4	[2.4,5.2]	0.09204062768384846
 1	[2,3.2]	0.15200169244542905
--- a/tests/queries/0_stateless/02354_vector_search_queries.sql
+++ b/tests/queries/0_stateless/02354_vector_search_queries.sql
@ -53,8 +53,8 @@ DROP TABLE tab;

 SELECT 'Special cases'; -- Not a systematic test, just to check that no bad things happen.

-SELECT '-- Non-default metric, M, ef_construction, ef_search';
-CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'cosineDistance', 'f32', 42, 99, 66) GRANULARITY 2) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 3;
+SELECT '-- Non-default metric, hnsw_max_connections_per_layer, hnsw_candidate_list_size_for_construction';
+CREATE TABLE tab(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'cosineDistance', 'f32', 42, 99) GRANULARITY 2) ENGINE = MergeTree ORDER BY id SETTINGS index_granularity = 3;
 INSERT INTO tab 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
@ -82,11 +82,11 @@ 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;
+CREATE TABLE tab_f64(id Int32, vec Array(Float32), INDEX idx vec TYPE vector_similarity('hnsw', 'L2Distance', 'f64', 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) 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) 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) 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) 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]);
--- a/utils/check-style/aspell-ignore/en/aspell-dict.txt
+++ b/utils/check-style/aspell-ignore/en/aspell-dict.txt
@ -31,6 +31,7 @@ AnyEvent
 AppleClang
 Approximative
 ArrayJoin
+ArrowCompression
 ArrowStream
 AsyncInsertCacheSize
 AsynchronousHeavyMetricsCalculationTimeSpent
@ -123,6 +124,7 @@ CMPLNT
 CMake
 CMakeLists
 CODECS
+CORS
 COVID
 CPUFrequencyMHz
 CPUs
@ -138,11 +140,13 @@ CacheDictionaryThreadsActive
 CacheDictionaryUpdateQueueBatches
 CacheDictionaryUpdateQueueKeys
 CacheFileSegments
+CacheWarmer
 CamelCase
 Cap'n
 CapContains
 CapUnion
 CapnProto
+CapnProtoEnumComparingMode
 CatBoost
 CellAreaM
 CellAreaRads
@ -209,6 +213,7 @@ DDLWORKER
 DDLWorker
 DDLWorkerThreads
 DDLWorkerThreadsActive
+DDLs
 DECRYPT
 DELETEs
 DESC
@ -217,6 +222,7 @@ DOGEFI
 Damerau
 DataGrip
 DataLens
+DataPacket
 DataTime
 DataTypes
 DatabaseCatalog
@ -228,11 +234,15 @@ DatabaseOnDiskThreadsActive
 DatabaseOrdinaryThreads
 DatabaseOrdinaryThreadsActive
 DateTime
+DateTimeInputFormat
+DateTimeOutputFormat
+DateTimeOverflowBehavior
 DateTimes
 DbCL
 Decrypted
 Deduplicate
 Deduplication
+DefaultTableEngine
 DelayedInserts
 DeliveryTag
 DeltaLake
@ -248,7 +258,11 @@ DiskSpaceReservedForMerge
 DiskTotal
 DiskUnreserved
 DiskUsed
+DistributedCacheLogMode
+DistributedCachePoolBehaviourOnLimit
+DistributedDDLOutputMode
 DistributedFilesToInsert
+DistributedProductMode
 DistributedSend
 DockerHub
 DoubleDelta
@ -257,6 +271,7 @@ Dresseler
 Durre
 ECMA
 ETag
+EachRow
 Ecto
 EdgeAngle
 EdgeLengthKm
@ -269,6 +284,7 @@ Enum
 Enums
 Eoan
 EphemeralNode
+EscapingRule
 Ethereum
 ExactEdgeLengthKm
 ExactEdgeLengthM
@ -373,6 +389,7 @@ IMDS
 INFILE
 INSERTed
 INSERTs
+INVOKER
 IOPrefetchThreads
 IOPrefetchThreadsActive
 IOThreads
@ -384,7 +401,10 @@ IOWriterThreadsActive
 IPTrie
 IProcessor
 IPv
+ITION
 Identifiant
+IdentifierQuotingRule
+IdentifierQuotingStyle
 Incrementing
 IndexesAreNeighbors
 InfluxDB
@ -403,6 +423,7 @@ IntervalMilliseconds
 IntervalMinute
 IntervalMonth
 IntervalNanosecond
+IntervalOutputFormat
 IntervalQuarter
 IntervalSecond
 IntervalWeek
@ -464,6 +485,8 @@ Jepsen
 JetBrains
 Jitter
 Joda
+JoinAlgorithm
+JoinStrictness
 JumpConsistentHash
 Jupyter
 KDevelop
@ -512,10 +535,16 @@ LinfNorm
 LinfNormalize
 LinksDeployment
 Linq
+ListObject
+ListObjects
 LoadAverage
+LoadBalancing
+LocalFSReadMethod
 LocalThread
 LocalThreadActive
 LogQL
+LogQueriesType
+LogsLevel
 Logstash
 LookML
 LoongArch
@ -552,6 +581,7 @@ MaxDDLEntryID
 MaxMind
 MaxPartCountForPartition
 MaxPushedDDLEntryID
+MaxThreads
 Mbps
 McNeal
 Memcheck
@ -559,6 +589,7 @@ MemoryCode
 MemoryDataAndStack
 MemoryResident
 MemoryResidentMax
+MemorySample
 MemorySanitizer
 MemoryShared
 MemoryTracking
@ -594,6 +625,7 @@ Mongo
 Mongodb
 Monotonicity
 MsgPack
+MsgPackUUIDRepresentation
 MultiLineString
 MultiPolygon
 Multiline
@ -602,6 +634,7 @@ Multithreading
 Multiword
 MurmurHash
 MySQLConnection
+MySQLDataTypesSupport
 MySQLDump
 MySQLThreads
 NATS
@ -637,6 +670,7 @@ NetworkSendPackets
 Noaa
 NodeJs
 NonMonotonic
+NonZeroUInt
 NuRaft
 NumHexagons
 NumPy
@ -649,6 +683,7 @@ NumberOfTables
 OFNS
 OLAP
 OLTP
+ORCCompression
 OSContextSwitches
 OSGuestNiceTime
 OSGuestNiceTimeCPU
@ -715,6 +750,8 @@ OrDefault
 OrNull
 OrZero
 OvercommitTracker
+OverflowMode
+OverflowModeGroupBy
 PAAMAYIM
 PCRE
 PRCP
@ -728,8 +765,11 @@ ParallelFormattingOutputFormatThreadsActive
 ParallelParsingInputFormat
 ParallelParsingInputFormatThreads
 ParallelParsingInputFormatThreadsActive
+ParallelReplicasMode
 Parametrized
+ParquetCompression
 ParquetMetadata
+ParquetVersion
 Parsers
 PartMutation
 Partitioner
@ -746,6 +786,7 @@ PartsWide
 PeerDB
 PendingAsyncInsert
 Percona
+PerfEventInfo
 PhpStorm
 PlantUML
 Poess
@ -797,6 +838,8 @@ QueryCacheBytes
 QueryCacheEntries
 QueryCacheHits
 QueryCacheMisses
+QueryCacheNondeterministicFunctionHandling
+QueryCacheSystemTableHandling
 QueryPreempted
 QueryThread
 QuickAssist
@ -805,6 +848,7 @@ QuoteMeta
 RBAC
 RClickHouse
 RHEL
+RIPEMD
 ROLLUP
 RWLock
 RWLockActiveReaders
@ -857,7 +901,7 @@ RestartReplicaThreads
 RestartReplicaThreadsActive
 RestoreThreads
 RestoreThreadsActive
-RIPEMD
+RetryStrategy
 RoaringBitmap
 RocksDB
 Rollup
@ -881,6 +925,7 @@ SQLAlchemy
 SQLConsoleDetail
 SQLInsert
 SQLSTATE
+SQLSecurityType
 SSDCache
 SSDComplexKeyCache
 SSDs
@ -893,6 +938,7 @@ Sankey
 Scalable
 Scatterplot
 Schaefer
+SchemaInferenceMode
 Schemas
 Schwartzian
 SeasClick
@ -901,8 +947,12 @@ SelfManaged
 Sematext
 SendExternalTables
 SendScalars
+SetOperationMode
 ShareAlike
+ShareSet
+SharedJoin
 SharedMergeTree
+ShortCircuitFunctionEvaluation
 Shortkeys
 Signup
 SimHash
@ -953,6 +1003,7 @@ SystemReplicasThreadsActive
 TABLUM
 TAVG
 TCPConnection
+TCPHandler
 TCPThreads
 TDigest
 TINYINT
@ -1020,8 +1071,10 @@ TotalPrimaryKeyBytesInMemory
 TotalPrimaryKeyBytesInMemoryAllocated
 TotalRowsOfMergeTreeTables
 TotalTemporaryFiles
+TotalsMode
 Tradeoff
 Transactional
+TransactionsWaitCSNMode
 Tsai
 Tukey
 TwoColumnList
@ -1043,6 +1096,7 @@ URLHash
 URLHierarchy
 URLPathHierarchy
 USearch
+USearch
 UTCTimestamp
 UUIDNumToString
 UUIDStringToNum
@ -1146,6 +1200,7 @@ aggregatio
 aggretate
 aggthrow
 aiochclient
+alloc
 allocator
 alphaTokens
 amplab
@ -1428,6 +1483,7 @@ config
 configs
 conformant
 congruential
+conjuctive
 connectionId
 const
 contrib
@ -1437,9 +1493,11 @@ corrMatrix
 corrStable
 corrmatrix
 corrstable
+cors
 cosineDistance
 countDigits
 countEqual
+countIf
 countMatches
 countMatchesCaseInsensitive
 countSubstrings
@ -1561,7 +1619,9 @@ denormalizing
 denormals
 dequeued
 dequeues
+dereference
 deserialization
+deserialize
 deserialized
 deserializing
 dest
@ -1604,6 +1664,7 @@ domainWithoutWWW
 domainWithoutWWWRFC
 dont
 dotProduct
+dotall
 downsampling
 dplyr
 dragonbox
@ -1707,6 +1768,7 @@ formatReadableSize
 formatReadableTimeDelta
 formatRow
 formatRowNoNewline
+formatdatetime
 formatschema
 formatter
 formatters
@ -1850,6 +1912,7 @@ heredocs
 hilbertDecode
 hilbertEncode
 hiveHash
+hnsw
 holistics
 homebrew
 hopEnd
@ -1880,6 +1943,7 @@ ilike
 incrementing
 indexHint
 indexOf
+inequal
 infi
 inflight
 infty
@ -1956,6 +2020,7 @@ kRing
 kafka
 kafkaMurmurHash
 kafkacat
+keepalive
 keepermap
 kerberized
 kerberos
@ -2148,15 +2213,19 @@ multiSearchFirstPosition
 multiSearchFirstPositionCaseInsensitive
 multiSearchFirstPositionCaseInsensitiveUTF
 multiSearchFirstPositionUTF
+multibuffer
 multibyte
 multidirectory
+multiif
 multiline
 multilinestring
 multiplyDecimal
 multipolygon
+multiread
 multisearchany
 multisets
 multithread
+multithreading
 multiword
 munmap
 murmurHash
@ -2208,6 +2277,7 @@ ngrambf
 ngrams
 noaa
 nonNegativeDerivative
+nonconst
 noop
 normalizeQuery
 normalizeQueryKeepNames
@ -2229,6 +2299,7 @@ nullIf
 nullability
 nullable
 nullables
+nullptr
 num
 numerics
 nypd
@ -2258,6 +2329,7 @@ pageviews
 parallelization
 parallelize
 parallelized
+param
 params
 parseDateTime
 parseDateTimeBestEffort
@ -2276,13 +2348,16 @@ parseReadableSizeOrNull
 parseReadableSizeOrZero
 parseTimeDelta
 parseable
+parsedatetime
 parsers
 partitionID
 partitionId
 pathFull
 pclmulqdq
 pcre
+perf
 performant
+perkey
 perl
 persistency
 phpclickhouse
@ -2317,6 +2392,7 @@ positionUTF
 positiveModulo
 postfix
 postfixes
+postgres
 postgresql
 pre
 pread
@ -2326,7 +2402,11 @@ prebuilt
 preemptable
 preferServerCiphers
 prefetch
+prefetched
+prefetches
+prefetching
 prefetchsize
+preimage
 preloaded
 prem
 prepend
@ -2480,6 +2560,7 @@ reinterpretAsInt
 reinterpretAsString
 reinterpretAsUInt
 reinterpretAsUUID
+remerge
 remoteSecure
 repivot
 replaceAll
@ -2487,6 +2568,7 @@ replaceOne
 replaceRegexpAll
 replaceRegexpOne
 replacingmergetree
+replcase
 replicatable
 replicatedmergetree
 replxx
@ -2494,6 +2576,7 @@ repo
 representable
 requestor
 requireTLSv
+rerange
 resharding
 reshards
 resolvers
@ -2525,6 +2608,7 @@ rowbinary
 rowbinarywithdefaults
 rowbinarywithnames
 rowbinarywithnamesandtypes
+rowlist
 rsync
 rsyslog
 runnable
@ -2713,6 +2797,7 @@ subtrees
 subtype
 sudo
 sumCount
+sumIf
 sumKahan
 sumMap
 sumMapFiltered
@ -2758,6 +2843,7 @@ theilsu
 themself
 threadpool
 throwIf
+throwif
 timeDiff
 timeSeriesData
 timeSeriesMetrics
@ -2923,9 +3009,11 @@ typename
 ubuntu
 uint
 ulid
+unacked
 unary
 unbin
 uncomment
+undelete
 undrop
 unencoded
 unencrypted
@ -2954,6 +3042,7 @@ uniqthetasketch
 unix
 unixODBC
 unixodbc
+unmerged
 unoptimized
 unparsed
 unpooled
@ -3060,90 +3149,3 @@ znode
 znodes
 zookeeperSessionUptime
 zstd
-postgres
-ArrowCompression
-CapnProtoEnumComparingMode
-DateTimeInputFormat
-DateTimeOutputFormat
-DateTimeOverflowBehavior
-deserialize
-dotall
-EachRow
-EscapingRule
-IdentifierQuotingRule
-IdentifierQuotingStyle
-IntervalOutputFormat
-MsgPackUUIDRepresentation
-ORCCompression
-ParquetCompression
-ParquetVersion
-SchemaInferenceMode
-alloc
-CacheWarmer
-conjuctive
-cors
-CORS
-countIf
-DefaultTableEngine
-dereference
-DistributedDDLOutputMode
-DistributedProductMode
-formatdatetime
-inequal
-INVOKER
-ITION
-JoinAlgorithm
-JoinStrictness
-keepalive
-ListObject
-ListObjects
-LoadBalancing
-LocalFSReadMethod
-LogQueriesType
-LogsLevel
-MaxThreads
-MemorySample
-multibuffer
-multiif
-multiread
-multithreading
-MySQLDataTypesSupport
-nonconst
-NonZeroUInt
-nullptr
-OverflowMode
-OverflowModeGroupBy
-ParallelReplicasMode
-param
-parsedatetime
-perf
-PerfEventInfo
-perkey
-prefetched
-prefetches
-prefetching
-preimage
-QueryCacheNondeterministicFunctionHandling
-QueryCacheSystemTableHandling
-remerge
-replcase
-rerange
-RetryStrategy
-rowlist
-SetOperationMode
-ShortCircuitFunctionEvaluation
-SQLSecurityType
-sumIf
-TCPHandler
-throwif
-TotalsMode
-TransactionsWaitCSNMode
-undelete
-unmerged
-DataPacket
-DDLs
-DistributedCacheLogMode
-DistributedCachePoolBehaviourOnLimit
-SharedJoin
-ShareSet
-unacked