--- title: "索引混合搜索（SQL 接口） - OceanBase 数据库 V5.0.1 | OceanBase 文档中心" description: 索引混合搜索（SQL 接口） 本文档介绍 OceanBase 的混合搜索 SQL 接口。该接口通过 HYBRID_SEARCH 关键字直接在一条 SELECT 查询语句中组合全文、向量搜索与过滤条件，并返回按相关性融合后的结果。 混合搜索（Hybrid Search）结合了基于向量的语义搜索和基于全文索引的关键词搜索… --- 切换语言 - 中文站 - 简体中文 - International - English - 日本站 - 日本語 文档反馈![](https://mdn.alipayobjects.com/huamei_22khvb/afts/img/A*P8CuR4UJ_FkAAAAAAAAAAAAADiGDAQ/original) OceanBase 数据库分布式版 - V 5.0.1 # 索引混合搜索（SQL 接口） 更新时间：2026-07-29 10:39:50 [编辑](https://github.com/oceanbase/oceanbase-doc/edit/V5.0.1/zh-CN/640.ob-vector-search/350.ob-vector-hybrid-search/100.ob-vector-index-hybrid-search-sql.md) 本文档介绍 OceanBase 的混合搜索 SQL 接口。该接口通过 `HYBRID_SEARCH` 关键字直接在一条 `SELECT` 查询语句中组合全文、向量搜索与过滤条件，并返回按相关性融合后的结果。 混合搜索（Hybrid Search）结合了基于向量的语义搜索和基于全文索引的关键词搜索，通过综合排序提供更准确、全面的搜索结果。向量搜索擅长语义近似匹配，但对精确的关键字、数字和专有名词等匹配能力较弱，而全文搜索能有效弥补这一不足。因此，混合搜索已成为向量数据库的关键特性之一，广泛应用于各类产品中。 ## 功能限制 - 当前仅支持在**堆表**上使用 `HYBRID_SEARCH` SQL 子句。 - 向量搜索要求目标向量列已创建向量索引。多路向量搜索当前仅支持稠密向量列。 - 全文搜索要求目标文本列已创建全文索引。如果全文列上是多个列的联合索引，则对于混合搜索无效。 - 标量过滤、JSON/ARRAY 过滤在无索引时也可执行，但建议创建相应索引以获得更好性能。 - 当前版本向量索引类型仅支持 HNSW 系列。 - 仅支持行存表。 - 不支持在生成列上使用。 本节只列出功能限制，需结合文末相关文档 `HYBRID_SEARCH` 中的语法限制内容一并理解。 ## 语法 ```sql SELECT select_list FROM HYBRID_SEARCH(TABLE table_name, dsl_string); ``` 参数说明如下： - `table_name`：目标表名，仅支持堆表（`ORGANIZATION = HEAP`）；支持分区表和非分区表。 - `dsl_string`：JSON 字符串，用于描述全文、向量搜索、过滤、排序融合等查询语义。 完整语法、参数和限制说明请参见文末相关文档 `HYBRID_SEARCH`。 ## 创建示例表并插入数据 本文与 [索引混合搜索（PL 接口）](https://www.oceanbase.com/docs/common-oceanbase-database-cn-1000000006615304) 使用相同的示例表。 - **`doc_table`**：用于全文、向量、标量过滤混合搜索的示例表 ```sql CREATE TABLE doc_table( c1 INT, vector VECTOR(3), query VARCHAR(255), content VARCHAR(255), VECTOR INDEX idx_vec(vector) WITH (distance=l2, type=hnsw_sq, lib=vsag), FULLTEXT INDEX idx_query(query), FULLTEXT INDEX idx_content(content) ) ORGANIZATION HEAP; INSERT INTO doc_table VALUES (1, '[1,2,3]', 'hello world', 'oceanbase Elasticsearch database'), (2, '[1,2,1]', 'hello world, what is your name', 'oceanbase mysql database'), (3, '[1,1,1]', 'hello world, how are you', 'oceanbase oracle database'), (4, '[1,3,1]', 'real world, where are you from', 'postgres oracle database'), (5, '[1,3,2]', 'real world, how old are you', 'redis oracle database'), (6, '[2,1,1]', 'hello world, where are you from', 'starrocks oceanbase database'); ``` - **`products_multi_vector`**：用于多路向量搜索的示例表 ```sql CREATE TABLE products_multi_vector ( product_id VARCHAR(50), product_name VARCHAR(255), description TEXT, vec1 VECTOR(4), vec2 VECTOR(4), vec3 VECTOR(4), VECTOR INDEX idx_vec1(vec1) WITH (distance=l2, type=hnsw_sq, lib=vsag), VECTOR INDEX idx_vec2(vec2) WITH (distance=l2, type=hnsw_sq, lib=vsag), VECTOR INDEX idx_vec3(vec3) WITH (distance=l2, type=hnsw_sq, lib=vsag) ) ORGANIZATION HEAP; INSERT INTO products_multi_vector VALUES ('prod-001', 'Gamer-Pro Mechanical Keyboard', 'A responsive mechanical keyboard', '[0.5,0.1,0.6,0.9]', '[0.2,0.3,0.4,0.5]', '[0.1,0.2,0.3,0.4]'), ('prod-002', 'Gamer-Pro Headset', 'High-fidelity gaming headset', '[0.1,0.9,0.2,0]', '[0.3,0.4,0.5,0.6]', '[0.2,0.3,0.4,0.5]'), ('prod-003', 'Eco-Friendly Yoga Mat', 'A non-slip yoga mat', '[0.1,0.9,0.3,0]', '[0.4,0.5,0.6,0.7]', '[0.3,0.4,0.5,0.6]'); ``` - **`doc_json_array`**：用于带有 JSON、ARRAY 过滤的混合搜索的示例表 ```sql CREATE TABLE doc_json_array ( id INT, created_date date, title varchar(255), doc_json JSON, tags_array1 ARRAY(VARCHAR(255)), tags_array2 ARRAY(VARCHAR(255)), INDEX idx_multivalue_tags((CAST(doc_json->'$.tags' AS CHAR(255) ARRAY))), INDEX idx1(id), INDEX idx2(title), INDEX idx_created_date(created_date) ) ORGANIZATION HEAP; INSERT INTO doc_json_array VALUES (1, '2023-01-01', 'doc1', '{"name":"doc1","tags":["database","oceanbase"],"metadata":{"type":"test","score":40}}', ['database','oceanbase'], ['database','mysql']), (2, '2023-01-02', 'doc2', '{"name":"doc2","tags":["database","mysql"],"metadata":{"type":"production","score":57}}', ['database','mysql'], ['database','mysql']), (3, '2023-01-03', 'doc3', '{"name":"doc3","tags":["database","oracle"],"metadata":{"type":"test","score":19}}', ['database','oracle'], ['database','oracle']), (4, '2023-01-04', 'doc4', '{"name":"doc4","tags":["database","postgres"],"metadata":{"type":"production","score":14}}', ['database','postgres'], ['database','postgres']), (6, '2023-01-06', 'doc6', '{"name":"doc6","tags":["database","starrocks"],"metadata":{"type":"production","score":25}}', ['database','starrocks'], ['database','starrocks']), (10, '2023-01-10', 'doc10', '{"name":"doc10","tags":["mobile","ios"],"metadata":{"type":"app","score":90}}', ['mobile','ios'], ['mobile','ios']); -- 推荐插入数据后建搜索索引（Search Index），以获得最佳搜索性能 CREATE SEARCH INDEX idx_json ON doc_json_array(doc_json); CREATE SEARCH INDEX idx_tags_array1 ON doc_json_array(tags_array1); CREATE SEARCH INDEX idx_tags_array2 ON doc_json_array(tags_array2); ``` 以下给出不同使用场景的示例，包含快速入门、拓展示例： ## 快速入门示例 这部分提供 6 个简单的核心示例，覆盖混合搜索的常用场景，包含向量搜索、全文搜索、向量搜索 + 全文搜索（RRF 融合）、多路向量搜索、过滤条件合并、分数阈值过滤。 ### 向量搜索 本示例搜索 `doc_table` 表中与向量 `[1,2,3]` 最相似的 3 条记录，并返回 `c1` 列。 ```sql SELECT c1 FROM HYBRID_SEARCH( TABLE doc_table, '{ "knn": { "field": "vector", "k": 3, "query_vector": "[1,2,3]" } }' ); ``` 预期返回结果如下： ```sql +------+ | c1 | +------+ | 1 | | 5 | | 2 | +------+ 3 rows in set ``` ### 全文搜索 本示例搜索 `doc_table` 表中 `content` 列包含 `oceanbase mysql` 的 4 条记录，并返回所有列。 ```sql SELECT * FROM HYBRID_SEARCH( TABLE doc_table, '{ "query": { "match": {"content": "oceanbase mysql"} } }' ); ``` 预期返回结果如下： ```sql +------+---------+---------------------------------+----------------------------------+--------------------+ | c1 | vector | query | content | __score | +------+---------+---------------------------------+----------------------------------+--------------------+ | 2 | [1,2,1] | hello world, what is your name | oceanbase mysql database | 2.170969786679347 | | 1 | [1,2,3] | hello world | oceanbase Elasticsearch database | 0.3503184713375797 | | 3 | [1,1,1] | hello world, how are you | oceanbase oracle database | 0.3503184713375797 | | 6 | [2,1,1] | hello world, where are you from | starrocks oceanbase database | 0.3503184713375797 | +------+---------+---------------------------------+----------------------------------+--------------------+ 4 rows in set ``` ### 全文与向量 RRF 混合搜索 本示例语句同时执行全文搜索（匹配关键词 `"oceanbase mysql"`）和向量搜索（搜索与向量 `[1,2,3]` 最相似的 5 条记录），然后通过 RRF 融合算法将两路结果合并，默认返回与查询最相关的 10 条文档，最终符合条件的共 6 条。 ```sql SELECT * FROM HYBRID_SEARCH( TABLE doc_table, '{ "query": { "match": {"content": "oceanbase mysql"} }, "knn": { "field": "vector", "k": 5, "query_vector": "[1,2,3]" }, "rank": { "rrf": { "rank_constant": 60, "rank_window_size": 10 } } }' ); ``` 预期返回结果如下： ```sql +------+---------+---------------------------------+----------------------------------+----------------------+ | c1 | vector | query | content | __score | +------+---------+---------------------------------+----------------------------------+----------------------+ | 1 | [1,2,3] | hello world | oceanbase Elasticsearch database | 0.03252247488101534 | | 2 | [1,2,1] | hello world, what is your name | oceanbase mysql database | 0.032266458495966696 | | 3 | [1,1,1] | hello world, how are you | oceanbase oracle database | 0.031754032258064516 | | 5 | [1,3,2] | real world, how old are you | redis oracle database | 0.016129032258064516 | | 6 | [2,1,1] | hello world, where are you from | starrocks oceanbase database | 0.016129032258064516 | | 4 | [1,3,1] | real world, where are you from | postgres oracle database | 0.015625 | +------+---------+---------------------------------+----------------------------------+----------------------+ 6 rows in set ``` ### 多路向量搜索 本示例语句同时在三个向量字段（`vec1`、`vec2`、`vec3`）上进行独立的向量搜索，各返回 5 个最相似的结果，然后通过默认的加权融合算法合并，返回综合相关性最高的文档。 ```sql SELECT * FROM HYBRID_SEARCH( TABLE products_multi_vector, '{ "knn": [ {"field":"vec1","k":5,"query_vector":"[0.5,0.1,0.6,0.9]"}, {"field":"vec2","k":5,"query_vector":"[0.2,0.3,0.4,0.5]"}, {"field":"vec3","k":5,"query_vector":"[0.1,0.2,0.3,0.4]"} ] }' ); ``` 预期返回结果如下： ```sql +------------+-------------------------------+----------------------------------+-------------------+-------------------+-------------------+--------------------+ | product_id | product_name | description | vec1 | vec2 | vec3 | __score | +------------+-------------------------------+----------------------------------+-------------------+-------------------+-------------------+--------------------+ | prod-002 | Gamer-Pro Headset | High-fidelity gaming headset | [0.1,0.9,0.2,0] | [0.3,0.4,0.5,0.6] | [0.2,0.3,0.4,0.5] | 2.7134181710480463 | | prod-003 | Eco-Friendly Yoga Mat | A non-slip yoga mat | [0.1,0.9,0.3,0] | [0.4,0.5,0.6,0.7] | [0.3,0.4,0.5,0.6] | 2.6366155630441215 | | prod-001 | Gamer-Pro Mechanical Keyboard | A responsive mechanical keyboard | [0.5,0.1,0.6,0.9] | [0.2,0.3,0.4,0.5] | [0.1,0.2,0.3,0.4] | 2.6237901221768167 | +------------+-------------------------------+----------------------------------+-------------------+-------------------+-------------------+--------------------+ 3 rows in set ``` ### 过滤条件合并 对于同一列在同一个 `bool.must` 或 `bool.filter` 路径下的多个标量过滤条件，这些条件仍以 `AND` 逻辑取交集，筛选同时满足所有条件的记录。查询优化器会在逻辑计划阶段将这些条件合并，避免执行阶段重复迭代。下例设置 `c1 >= 3` 与 `c1 <= 5`（相当于 `c1 >= 3 AND c1 <= 5`），因此只返回 `c1` 为 3、4、5 的行。 ```sql SELECT c1 FROM HYBRID_SEARCH(TABLE doc_table, '{ "query": { "bool": { "filter": [ {"range": {"c1": {"gte" : 3}}}, {"range": {"c1": {"lte" : 5}}} ] }} }'); ``` 预期返回结果如下： ```sql +------+ | c1 | +------+ | 3 | | 4 | | 5 | +------+ 3 rows in set ``` ### 分数阈值过滤（`min_score`） #### 注意 仅 SQL 接口支持 `min_score` 参数，PL 接口不支持。 本示例搜索 `doc_table` 表中 `content` 列包含 `oceanbase mysql` 的 2 条记录，分数阈值为 0.5，并返回所有列。 ```sql SELECT * FROM HYBRID_SEARCH( TABLE doc_table, '{ "query": {"match": {"content":{"query": "oceanbase mysql", "boost": 0.3}}}, "knn": {"field":"vector","k":5,"query_vector":"[1,2,3]", "boost": 0.7}, "min_score": 0.5 }' ); ``` 预期返回结果如下： ```sql +------+---------+--------------------------------+----------------------------------+--------------------+ | c1 | vector | query | content | __score | +------+---------+--------------------------------+----------------------------------+--------------------+ | 1 | [1,2,3] | hello world | oceanbase Elasticsearch database | 0.8050955414012738 | | 2 | [1,2,1] | hello world, what is your name | oceanbase mysql database | 0.7912909360038041 | +------+---------+--------------------------------+----------------------------------+--------------------+ 2 rows in set ``` ## 拓展示例 这部分提供一些更复杂的拓展示例，涵盖混合搜索的复杂场景，包含复杂类型过滤（JSON/ARRAY 等）、向量和全文搜索的加权混合、WRRF 混合、归一化、混合搜索分数查询等。 ### 标量+JSON/ARRAY 过滤 这部分示例需结合搜索索引使用。对于混合搜索场景，全文分词及关键词检索由全文索引负责，搜索索引则用于复杂类型内部路径的结构化、半结构化或简单标量条件，二者适用列类型不同，可在同一表中同时存在，并与向量索引配合使用，以提升查询性能。 除此之外，在分析型宽表场景下，搜索索引还可以叠加优化器的多索引联合查询（Index Merge）能力，自动识别并组合可用的全文和标量索引，选择最优扫描路径，以进一步提升查询性能。更多关于搜索索引的用法、语法说明和完整示例，请参考[搜索索引（Search Index）](https://www.oceanbase.com/docs/common-oceanbase-database-cn-1000000006615299)。 #### JSON 示例 1. JSON_CONTAINS JSON_CONTAINS() 函数用于判断目标 JSON 文档中是否包含指定的 `candidate` 子文档，或在给定路径 `path`（可选）下是否存在该元素。 ```sql SELECT id, doc_json FROM HYBRID_SEARCH( TABLE doc_json_array, '{ "query": { "bool" : { "filter" : [{ "json_contains":{ "doc_json": { "candidate": "doc2", "path": "$.name" } } }] } } }'); ``` 预期返回结果如下： ```sql +------+--------------------------------------------------------------------------------------------------+ | id | doc_json | +------+--------------------------------------------------------------------------------------------------+ | 2 | {"name": "doc2", "tags": ["database", "mysql"], "metadata": {"type": "production", "score": 57}} | +------+--------------------------------------------------------------------------------------------------+ 1 row in set ``` 2. JSON_OVERLAPS JSON_OVERLAPS() 函数用于判断两个 JSON 文档是否存在共同的键值对（key-value）或数组元素，`path` 为可选参数。 ```sql SELECT id, doc_json FROM HYBRID_SEARCH( TABLE doc_json_array, '{ "query": { "bool" : { "filter" : [{ "json_overlaps":{ "doc_json": { "candidate": "[\\"database\\", \\"mysql\\"]", "path": "$.tags" } } }] } } }'); ``` 预期返回结果如下： ```sql +------+------------------------------------------------------------------------------------------------------+ | id | doc_json | +------+------------------------------------------------------------------------------------------------------+ | 1 | {"name": "doc1", "tags": ["database", "oceanbase"], "metadata": {"type": "test", "score": 40}} | | 2 | {"name": "doc2", "tags": ["database", "mysql"], "metadata": {"type": "production", "score": 57}} | | 3 | {"name": "doc3", "tags": ["database", "oracle"], "metadata": {"type": "test", "score": 19}} | | 4 | {"name": "doc4", "tags": ["database", "postgres"], "metadata": {"type": "production", "score": 14}} | | 6 | {"name": "doc6", "tags": ["database", "starrocks"], "metadata": {"type": "production", "score": 25}} | +------+------------------------------------------------------------------------------------------------------+ 5 rows in set ``` 3. JSON_MEMBER_OF JSON_MEMBER_OF() 函数用于判断被检索的元素是否和 JSON 数组中的任意一个元素相同，`path` 为可选参数。 ```sql SELECT id, doc_json FROM HYBRID_SEARCH( TABLE doc_json_array, '{ "query": { "bool" : { "filter" : [{ "json_member_of":{ "doc_json": { "candidate": "\\"database\\"" } } }] } } }'); ``` 预期返回空。 4. JSON_EXTRACT JSON_EXTRACT() 函数用于从 JSON 文档中指定的路径返回数据。 ```sql -- 提取 JSON 字段 doc_json 中 key 为 "name" 的节点，判断 value 是否等于 "doc2" SELECT id, doc_json FROM HYBRID_SEARCH( TABLE doc_json_array, '{ "query": { "bool" : { "filter" : [{ "term":{"doc_json.name": "doc2"} }] } } }'); ``` 预期返回结果如下： ``` #### ARRAY 示例 语法定义： ```sql -- ARRAY 表达式语法 { "array_func" : { "field_name" : "value" } } ``` 1. ARRAY_CONTAINS ARRAY_CONTAINS() 函数用于判断数组中是否含有某个元素。 ```sql SELECT id, tags_array1 FROM HYBRID_SEARCH( TABLE doc_json_array, '{ "query": { "bool" : { "filter" : [ { "array_contains": { "tags_array1" : "ios" }} ] } } }'); ``` 预期返回结果如下： ```sql +------+------------------+ | id | tags_array1 | +------+------------------+ | 10 | ["mobile","ios"] | +------+------------------+ 1 row in set ``` 2. ARRAY_CONTAINS_ALL ARRAY_CONTAINS_ALL() 函数用于判断一个数组是否包含另一个数组中的所有元素。 ```sql SELECT id, tags_array1 FROM HYBRID_SEARCH( TABLE doc_json_array, '{ "query": { "bool" : { "filter" : [ { "array_contains_all": { "tags_array1": ["database", "postgres"]} } ] } } }'); ``` 预期返回结果如下： ```sql +------+-------------------------+ | id | tags_array1 | +------+-------------------------+ | 4 | ["database","postgres"] | +------+-------------------------+ 1 row in set ``` 3. ARRAY_OVERLAPS ARRAY_OVERLAPS() 函数用于判断两个数组是否存在交集。 ```sql SELECT id, tags_array1 FROM HYBRID_SEARCH( TABLE doc_json_array, '{ "query": { "bool" : { "filter" : [ { "array_overlaps": { "tags_array1": ["database", "postgres", "oceanbase"]} } ] } } }'); ``` 预期返回结果如下： ```sql +------+--------------------------+ | id | tags_array1 | +------+--------------------------+ | 1 | ["database","oceanbase"] | | 2 | ["database","mysql"] | | 3 | ["database","oracle"] | | 4 | ["database","postgres"] | | 6 | ["database","starrocks"] | +------+--------------------------+ 5 rows in set ``` ### 其他混合搜索场景 #### 向量与全文搜索加权混合 加权混合是 OceanBase AI 默认的混合方式，其中全文搜索的权重为 `0.3`，向量搜索的权重为 `0.7`。 ```sql SELECT * FROM HYBRID_SEARCH( TABLE doc_table, '{ "query": { "match": {"content": {"query": "oceanbase mysql", "boost": 0.3}} }, "knn": { "field": "vector", "k": 5, "query_vector": "[1,2,3]", "boost": 0.7 } }' ); ``` 预期返回结果如下： ```sql +------+---------+---------------------------------+----------------------------------+---------------------+ | c1 | vector | query | content | __score | +------+---------+---------------------------------+----------------------------------+---------------------+ | 1 | [1,2,3] | hello world | oceanbase Elasticsearch database | 0.8050955414012738 | | 2 | [1,2,1] | hello world, what is your name | oceanbase mysql database | 0.7912909360038041 | | 5 | [1,3,2] | real world, how old are you | redis oracle database | 0.2333333333333333 | | 3 | [1,1,1] | hello world, how are you | oceanbase oracle database | 0.22176220806794056 | | 4 | [1,3,1] | real world, where are you from | postgres oracle database | 0.11666666666666665 | | 6 | [2,1,1] | hello world, where are you from | starrocks oceanbase database | 0.1050955414012739 | +------+---------+---------------------------------+----------------------------------+---------------------+ 6 rows in set ``` #### 向量与全文搜索 WRRF 混合 在 RRF 基础上支持设置 boost 权重，本示例查询 `query` 和 `knn` 中的 `boost` 就是 WRRF 融合的权重。 ```sql SELECT * FROM HYBRID_SEARCH( TABLE doc_table, '{ "query": { "match": {"content": {"query": "oceanbase mysql", "boost": 0.3}} }, "knn": { "field": "vector", "k": 5, "query_vector": "[1,2,3]", "boost": 0.7 }, "rank": { "rrf": { "rank_constant": 60, "rank_window_size": 10 } } }' ); ``` 预期返回结果如下： ``` #### 向量与全文搜索归一化 支持设置 `normalizer` 参数，用于对查询结果进行归一化处理，本示例设置 `normalizer` 为 `"minmax"`，表示使用 Min-Max 归一化。 ```sql SELECT * FROM HYBRID_SEARCH( TABLE doc_table, '{ "query": { "match": {"content": {"query": "oceanbase mysql", "boost": 0.3}} }, "knn": { "field": "vector", "k": 5, "query_vector": "[1,2,3]", "boost": 0.7 }, "rank": { "weighted_sum": { "normalizer": "minmax", "rank_window_size": 10 } } }' ); ``` 预期返回结果如下： ```sql +------+---------+---------------------------------+----------------------------------+---------------------+ | c1 | vector | query | content | __score | +------+---------+---------------------------------+----------------------------------+---------------------+ | 1 | [1,2,3] | hello world | oceanbase Elasticsearch database | 0.7 | | 2 | [1,2,1] | hello world, what is your name | oceanbase mysql database | 0.328 | | 5 | [1,3,2] | real world, how old are you | redis oracle database | 0.13999999999999999 | | 3 | [1,1,1] | hello world, how are you | oceanbase oracle database | 0 | | 4 | [1,3,1] | real world, where are you from | postgres oracle database | 0 | | 6 | [2,1,1] | hello world, where are you from | starrocks oceanbase database | 0 | +------+---------+---------------------------------+----------------------------------+---------------------+ 6 rows in set ``` ## 查看执行计划 可使用 `EXPLAIN` 查看混合搜索计划中各子查询节点、混合融合方式和是否使用索引： ```sql EXPLAIN SELECT c1 FROM HYBRID_SEARCH(table doc_table, '{"query": { "bool": { "must" : [{"match" : {"content": "oceanbase mysql"}}], "filter": [ {"range": {"c1": {"gte" : 3}}}, {"range": {"c1": {"lte" : 10}}} ] }}, "knn": { "field": "vector", "k": 10, "query_vector": "[1, 2, 3]" }}'); ``` 预期返回结果如下，结果中展示了混合搜索计划中各子查询节点、子查询混合方式为 WRRF 融合，且使用了索引 `idx_vector` 和全文索引 `idx_content`： ```shell +------------------------------------------------------------------------------+ | Query Plan | +------------------------------------------------------------------------------+ | ================================================================== | | |ID|OPERATOR |NAME |EST.ROWS|EST.TIME(us)| | | ------------------------------------------------------------------ | | |0 |INDEX MERGE SCAN|doc_table(idx_vector)|1 |3 | | | ================================================================== | | Outputs & filters: | | ------------------------------------- | | 0 - output([doc_table.c1]), filter(nil), rowset=16 | | access([doc_table.__pk_increment], [doc_table.c1]), partitions(p0) | | is_index_back=true, is_global_index=false, use_index_merge=true, | | fusion node: method=WEIGHT_SUM, limit(10), window_size(10) | | vector node: index name=idx_vector | | boolean node: | | must: | | match node: index name=idx_content | | filter: | | scalar node: filter([doc_table.c1 >= 3], [doc_table.c1 <= 10]) | +------------------------------------------------------------------------------+ 17 rows in set ``` ## 相关文档 - 语法、参数和限制说明请参见 [HYBRID_SEARCH](https://www.oceanbase.com/docs/common-oceanbase-database-cn-1000000006620720) - [搜索索引（Search Index）](https://www.oceanbase.com/docs/common-oceanbase-database-cn-1000000006615299) - [全文索引](https://www.oceanbase.com/docs/common-oceanbase-database-cn-1000000006619248) - [向量索引](https://www.oceanbase.com/docs/common-oceanbase-database-cn-1000000006615292) 上一篇 下一篇 ![有帮助](https://gw.alipayobjects.com/mdn/ob_asset/afts/img/A*y6ocSqN8cqsAAAAAAAAAAAAAARQnAQ)![无帮助](https://gw.alipayobjects.com/mdn/ob_asset/afts/img/A*BG9IQJyLHF8AAAAAAAAAAAAAARQnAQ)![反馈](https://gw.alipayobjects.com/mdn/ob_asset/afts/img/A*eTWdQKCRKHwAAAAAAAAAAAAAARQnAQ)[AI](https://www.oceanbase.com/obi) 咨询热线