【ElasticSearch】json查询语法和可用的客户端

【一】Elasticsearch查询语法详解

【1】基本查询结构

GET /index_name/_search
{"query": {// 查询条件},"aggs": {// 聚合条件},"sort": [// 排序条件],"from": 0,"size": 10,"highlight": {// 高亮设置}
}

【2】关键字

（1）一般查询（Query）

​匹配查询（Match Query）​​：用于全文搜索。
词条查询（Term Query）​​：用于精确值匹配。
​范围查询（Range Query）​​：用于范围过滤。
​布尔查询（Bool Query）​​：组合多个查询条件（must, should, must_not, filter）。
​多匹配查询（Multi Match Query）​​：在多个字段上执行匹配查询。
​前缀查询（Prefix Query）​​：匹配以指定前缀开头的词条。
​通配符查询（Wildcard Query）​​：使用通配符匹配。
​正则表达式查询（Regexp Query）​​：使用正则表达式匹配。
​模糊查询（Fuzzy Query）​​：匹配与指定词条相似的词条。
​嵌套查询（Nested Query）​​：查询嵌套对象。

（2）指标聚合（Metric Aggregations）​​

avg：平均值。
sum：求和。
min：最小值。
max：最大值。
count：计数。
stats：包含count, min, max, avg, sum。
extended_stats：扩展的统计信息，包括方差、标准差等。
cardinality：基数统计（类似distinct count）

（3）桶聚合（Bucket Aggregations）​​

terms：按词条分组。
range：按范围分组。
date_range：日期范围分组。
histogram：直方图（数值间隔分组）。
date_histogram：日期直方图。
nested：嵌套聚合。
reverse_nested：从嵌套聚合返回父级。
filter：按过滤条件分组。
filters：多个过滤条件分组。
missing：处理缺失字段。

（4）管道聚合（Pipeline Aggregations）​​

对其它聚合的结果进行再聚合。
avg_bucket：计算多个桶的平均值。
sum_bucket：计算多个桶的总和。
min_bucket：计算多个桶的最小值。
max_bucket：计算多个桶的最大值。

【3】常用查询类型

（1）匹配查询-match

基本匹配查询（查找所有华为手机）

GET /product_info/_search
{"query": {"match": {"product_name": "华为手机"}}
}

（2）多字段搜索-multi_match（在名称和描述中搜索）

GET /product_info/_search
{"query": {"multi_match": {"query": "防水 智能","fields": ["product_name", "description"],"type": "best_fields"}}
}

（3）精确过滤-must（查找中国产电子产品）

GET /product_info/_search
{"query": {"bool": {"must": [{"match": {"category": "电子产品"}}],"filter": [{"term": {"origin": "中国"}}]}}
}

（4）范围查询-range（价格在1000-5000之间的商品）

GET /product_info/_search
{"query": {"range": {"price": {"gte": 1000,"lte": 5000}}}
}

（5）组合查询（查找库存大于100的服装）

GET /product_info/_search
{"query": {"bool": {"must": [{"match": {"category": "服装"}}],"filter": [{"range": {"stock": {"gt": 100}}}]}}
}

（6）分页排序（按价格降序排列）

GET /product_info/_search
{"query": {"match_all": {}},"sort": [{"price": {"order": "desc"}}],"from": 0,"size": 10
}

（7）高亮显示（高亮搜索结果）

GET /product_info/_search
{"query": {"match": {"description": "防水"}},"highlight": {"fields": {"description": {}},"pre_tags": ["<strong>"],"post_tags": ["</strong>"]}
}

（8）布尔查询（Bool）

{"query": {"bool": {"must": [{ "match": { "field1": "value1" } }],"should": [{ "match": { "field2": "value2" } }],"must_not": [{ "term": { "field3": "value3" } }],"filter": [{ "range": { "price": { "gte": 100 } } }]}}
}

GET /product_info/_search
{"query": {"bool": {"must": [{ "match": { "product_name": "手机" } }],"filter": [{ "term": { "status": "active" } },{ "range": { "price": { "gte": 1000, "lte": 5000 } } }]}}
}

（9）地理位置搜索

GET /stores/_search
{"query": {"bool": {"must": [{ "match": { "name": "咖啡" } }],"filter": {"geo_distance": {"distance": "2km","location": {"lat": 31.2304,"lon": 121.4737}}}}},"sort": [{"_geo_distance": {"location": {"lat": 31.2304,"lon": 121.4737},"order": "asc","unit": "km"}}]
}

【4】聚合语法

（1）基本词项聚合-Terms（按商品分类分组）

GET /product_info/_search
{"size": 0,"aggs": {"by_category": {"terms": {"field": "category","size": 5}}}
}

GET /product_info/_search
{"query": {"bool": {"must": [{ "match": { "product_name": "智能手机" } }],"filter": [{ "term": { "status": "active" } },{ "range": { "price": { "gte": 1000, "lte": 5000 } } }]}},"sort": [{ "price": { "order": "asc" } }],"from": 0,"size": 10,"highlight": {"fields": {"product_name": {},"description": {}}}
}

（2）指标聚合-Metrics（计算平均价格）

GET /product_info/_search
{"size": 0,"aggs": {"avg_price": {"avg": {"field": "price"}}}
}

GET /product_info/_search
{"query": {"multi_match": {"query": "防水 智能","fields": ["product_name", "description"],"type": "best_fields"}},"aggs": {"by_category": {"terms": {"field": "category","size": 5},"aggs": {"avg_price": {"avg": { "field": "price" }}}},"price_stats": {"stats": { "field": "price" }}},"size": 0
}

（3）多级聚合-Metrics（按分类分组后计算平均价格）

GET /product_info/_search
{"size": 0,"aggs": {"by_category": {"terms": {"field": "category","size": 5},"aggs": {"avg_price": {"avg": {"field": "price"}}}}}
}

{"aggs": {"avg_price": {"avg": { "field": "price" }},"max_price": {"max": { "field": "price" }},"min_price": {"min": { "field": "price" }},"sum_price": {"sum": { "field": "price" }}}
}

（4）范围聚合-Range（按价格区间分组）

GET /product_info/_search
{"size": 0,"aggs": {"price_ranges": {"range": {"field": "price","ranges": [{"to": 1000},{"from": 1000, "to": 5000},{"from": 5000}]}}}
}

GET /product_info/_search
{"query": {"range": {"stock": {"gt": 0}}},"aggs": {"by_category_origin": {"terms": {"field": "category","size": 10},"aggs": {"by_origin": {"terms": {"field": "origin","size": 5,"order": { "avg_price": "asc" }},"aggs": {"avg_price": {"avg": { "field": "price" }},"price_ranges": {"range": {"field": "price","ranges": [{ "to": 1000 },{ "from": 1000, "to": 3000 },{ "from": 3000 }]}}}}}},"global_price_stats": {"extended_stats": { "field": "price" }}},"size": 0
}

（5）复杂多级聚合（按产地分组后按分类分组）

GET /product_info/_search
{"size": 0,"aggs": {"by_origin": {"terms": {"field": "origin","size": 5},"aggs": {"by_category": {"terms": {"field": "category","size": 3},"aggs": {"avg_price": {"avg": {"field": "price"}}}}}}}
}

（6）排序聚合-Order（按平均价格升序排列）

GET /product_info/_search
{"size": 0,"aggs": {"by_origin": {"terms": {"field": "origin","size": 5,"order": {"avg_price": "asc"}},"aggs": {"avg_price": {"avg": {"field": "price"}}}}}
}

（7）嵌套聚合-Nested

{"aggs": {"nested_agg": {"nested": {"path": "specifications"},"aggs": {"by_spec": {"terms": {"field": "specifications.name"}}}}}
}

（8）统计聚合-Stats

{"aggs": {"price_stats": {"stats": { "field": "price" }}}
}

（9）扩展统计聚合-Extended Stats

{"aggs": {"price_extended_stats": {"extended_stats": { "field": "price" }}}
}

【二】完整查询与聚合组合案例

【1】聚合案例

（1）案例1：带过滤条件的聚合分析

GET /product_info/_search
{"query": {"bool": {"filter": [{"term": {"status": "active"}},{"range": {"stock": {"gt": 0}}}]}},"size": 0,"aggs": {"by_category": {"terms": {"field": "category","size": 5},"aggs": {"by_origin": {"terms": {"field": "origin","size": 3,"order": {"avg_price": "asc"}},"aggs": {"avg_price": {"avg": {"field": "price"}},"min_price": {"min": {"field": "price"}},"max_price": {"max": {"field": "price"}}}}}},"global_stats": {"stats": {"field": "price"}}}
}

（2）案例2：高亮搜索与聚合结合

GET /product_info/_search
{"query": {"match": {"description": "智能"}},"highlight": {"fields": {"description": {}}},"aggs": {"price_stats": {"stats": {"field": "price"}}},"size": 5
}

（3）案例3：多条件过滤聚合（中国产电子产品价格分析）

GET /product_info/_search
{"query": {"bool": {"must": [{"match": {"category": "电子产品"}}],"filter": [{"term": {"origin": "中国"}},{"range": {"price": {"gte": 1000}}}]}},"size": 0,"aggs": {"by_brand": {"terms": {"field": "product_name.keyword","size": 5},"aggs": {"avg_price": {"avg": {"field": "price"}},"price_distribution": {"histogram": {"field": "price","interval": 1000}}}}}
}

（4）案例4：日期范围聚合（按创建月份分组）

GET /product_info/_search
{"size": 0,"aggs": {"by_month": {"date_histogram": {"field": "created_at","calendar_interval": "month","format": "yyyy-MM"},"aggs": {"total_sales": {"sum": {"field": "sales"}}}}}
}

（5）案例5：指标聚合（Metric Aggregations）​​

计算商品的平均价格、最高价格、最低价格：

GET /product_info/_search
{"size": 0,"aggs": {"avg_price": { "avg": { "field": "price" } },"max_price": { "max": { "field": "price" } },"min_price": { "min": { "field": "price" } }}
}

（6）案例6：桶聚合（Bucket Aggregations）​​

按商品类别分组，并计算每组的平均价格：

GET /product_info/_search
{"size": 0,"aggs": {"by_category": {"terms": { "field": "category" },"aggs": {"avg_price": { "avg": { "field": "price" } }}}}
}

（7）案例7：范围聚合（Range Aggregation）​​

按价格范围分组：

GET /product_info/_search
{"size": 0,"aggs": {"price_ranges": {"range": {"field": "price","ranges": [{ "to": 1000 },{ "from": 1000, "to": 5000 },{ "from": 5000 }]},"aggs": {"avg_rating": { "avg": { "field": "rating" } }}}}
}

（8）案例8：嵌套聚合（Nested Aggregation）​​

对嵌套的规格属性进行聚合，统计内存大小的分布：

GET /product_info/_search
{"size": 0,"aggs": {"specs": {"nested": { "path": "specifications" },"aggs": {"memory_sizes": {"filter": { "term": { "specifications.name": "内存" } },"aggs": {"sizes": { "terms": { "field": "specifications.value" } }}}}}}
}

（9）​案例9：管道聚合（Pipeline Aggregation）​​

按类别分组后，再计算每个类别的平均价格，然后按平均价格排序：

GET /product_info/_search
{"size": 0,"aggs": {"by_category": {"terms": {"field": "category","order": { "avg_price": "desc" }  // 按子聚合avg_price降序排序},"aggs": {"avg_price": { "avg": { "field": "price" } }}}}
}

（10）案例10：组合查询和聚合

查询价格在1000到5000之间的活跃商品，按类别分组，并计算每组的平均价格和商品数量，并按平均价格降序排序：

GET /product_info/_search
{"size": 0,"query": {"bool": {"filter": [{ "term": { "status": "active" } },{ "range": { "price": { "gte": 1000, "lte": 5000 } } }]}},"aggs": {"by_category": {"terms": {"field": "category","size": 10,"order": { "avg_price": "desc" }},"aggs": {"avg_price": { "avg": { "field": "price" } },"product_count": { "value_count": { "field": "id" } }}}}
}

【2】实践技巧

（1）性能优化

GET /product_info/_search
{"query": {"bool": {"filter": [{"term": {"category": "电子产品"}}]}},"size": 0,"aggs": {"by_origin": {"terms": {"field": "origin","execution_hint": "map",  -- 使用map执行模式"size": 5}}}
}

（2）复合聚合（处理大数据集）

GET /product_info/_search
{"size": 0,"aggs": {"by_category_origin": {"composite": {"sources": [{"category": {"terms": {"field": "category"}}},{"origin": {"terms": {"field": "origin"}}}],"size": 100},"aggs": {"avg_price": {"avg": {"field": "price"}}}}}
}

（3）使用搜索模板

POST /_scripts/product_search_template
{"script": {"lang": "mustache","source": {"query": {"bool": {"must": [{"match": {"category": "{{category}}"}}],"filter": [{"term": {"origin": "{{origin}}"}}]}},"aggs": {"price_stats": {"stats": {"field": "price"}}},"size": "{{size}}"}}
}-- 调用模板
GET /product_info/_search/template
{"id": "product_search_template","params": {"category": "电子产品","origin": "中国","size": 10}
}

（4）使用索引别名

-- 创建别名
POST /_aliases
{"actions": [{"add": {"index": "product_info","alias": "current_products","filter": {"term": {"status": "active"}}}}]
}-- 使用别名查询
GET /current_products/_search
{"query": {"match_all": {}}
}

【3】常见问题

（1）查询性能慢

​优化方案​：添加路由和过滤条件

GET /product_info/_search?routing=category
{"query": {"bool": {"filter": [{"term": {"category": "电子产品"}}]}}
}

（2）聚合桶数量不足

​解决方案​：增加size参数

GET /product_info/_search
{"size": 0,"aggs": {"by_category": {"terms": {"field": "category","size": 20  -- 默认是10}}}
}

（3）处理空值聚合

​解决方案​：使用missing参数

GET /product_info/_search
{"size": 0,"aggs": {"by_origin": {"terms": {"field": "origin","missing": "未知产地"}}}
}

【三】springboot整合es的工具

【1】可选工具和客户端

（1）ElasticsearchRepository​

这是Spring Data Elasticsearch提供的一个接口，类似于Spring Data JPA的Repository。它提供了基本的CRUD操作和简单的查询方法（通过方法名或注解定义查询）。适用于简单的CRUD操作和查询，能够快速开发。

（2）​ElasticsearchRestTemplate​（或旧版的ElasticsearchTemplate）：

（1）ElasticsearchTemplate是Spring Data Elasticsearch早期版本中的主要类，基于TransportClient（已弃用）。
（2）ElasticsearchRestTemplate是Spring Data Elasticsearch 3.2.x及以上版本推荐的类，基于High Level REST Client。它提供了更底层的操作，可以执行复杂的查询和聚合，适用于需要高度自定义查询的场景。

（3）High Level REST Client​

Elasticsearch官方提供的Java高级 REST 客户端，用于与Elasticsearch集群通信。它提供了所有Elasticsearch操作的方法，但使用起来相对繁琐，需要手动构建请求和解析响应。在Spring Data Elasticsearch中，通常不需要直接使用，因为ElasticsearchRestTemplate已经对其进行了封装。

（4）​Java API Client​

Elasticsearch 7.15及以上版本引入了新的Java API客户端，这是一个基于Jackson的强类型客户端，提供了更好的类型安全和性能。但是，Spring Data Elasticsearch目前（截至3.2.x）还没有完全整合这个新客户端。

【2】如何选择

（1）如果只需要基本的CRUD和简单查询，推荐使用ElasticsearchRepository，因为它使用简单，代码量少。
（2）如果需要执行复杂的查询、聚合、或者需要更灵活地控制查询过程，那么应该使用ElasticsearchRestTemplate。
（3）如果Spring Data Elasticsearch提供的功能无法满足需求（例如，使用一些非常新的Elasticsearch特性），可以考虑直接使用Elasticsearch的Java API Client，但这样会失去Spring Data的便利性。

【3】如何使用

（1）ElasticsearchRepository 使用

（1）创建Repository接口

public interface ProductRepository extends ElasticsearchRepository<Product, String> {// 自定义查询方法List<Product> findByName(String name);List<Product> findByPriceBetween(Double minPrice, Double maxPrice);Page<Product> findByCategory(String category, Pageable pageable);// 使用@Query注解自定义DSL@Query("{\"match\": {\"name\": \"?0\"}}")Page<Product> findByNameCustom(String name, Pageable pageable);
}

（2）使用示例

@Service
@RequiredArgsConstructor
public class ProductService {private final ProductRepository productRepository;public Page<Product> searchProducts(String keyword, int page, int size) {return productRepository.findByNameCustom(keyword, PageRequest.of(page, size, Sort.by("price").descending()));}public List<Product> findProductsByPriceRange(double min, double max) {return productRepository.findByPriceBetween(min, max);}
}

（2）ElasticsearchRestTemplate 使用

（1）配置类

@Configuration
public class ElasticsearchConfig {@Beanpublic ElasticsearchRestTemplate elasticsearchRestTemplate(ElasticsearchRestClient elasticsearchRestClient) {return new ElasticsearchRestTemplate(elasticsearchRestClient);}
}

（2）复杂查询实现

@Service
@RequiredArgsConstructor
public class ProductSearchService {private final ElasticsearchRestTemplate elasticsearchRestTemplate;public SearchPage<Product> complexSearch(String keyword, String category, Double minPrice, Double maxPrice, int page, int size) {// 构建布尔查询BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();if (StringUtils.hasText(keyword)) {boolQuery.must(QueryBuilders.matchQuery("name", keyword).boost(2.0f));}if (StringUtils.hasText(category)) {boolQuery.must(QueryBuilders.termQuery("category", category));}if (minPrice != null || maxPrice != null) {RangeQueryBuilder rangeQuery = QueryBuilders.rangeQuery("price");if (minPrice != null) rangeQuery.gte(minPrice);if (maxPrice != null) rangeQuery.lte(maxPrice);boolQuery.must(rangeQuery);}// 构建分页和排序NativeSearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(boolQuery).withPageable(PageRequest.of(page, size)).withSort(SortBuilders.fieldSort("price").order(SortOrder.DESC)).build();SearchHits<Product> searchHits = elasticsearchRestTemplate.search(searchQuery, Product.class);return SearchHitSupport.searchPageFor(searchHits, searchQuery.getPageable());}// 聚合查询示例public Map<String, Long> getCategoryStats() {TermsAggregationBuilder aggregation = AggregationBuilders.terms("category_agg").field("category").size(10);NativeSearchQuery searchQuery = new NativeSearchQueryBuilder().addAggregation(aggregation).build();SearchHits<Product> searchHits = elasticsearchRestTemplate.search(searchQuery, Product.class);Terms terms = searchHits.getAggregations().get("category_agg");return terms.getBuckets().stream().collect(Collectors.toMap(Terms.Bucket::getKeyAsString, Terms.Bucket::getDocCount));}
}

（3）新的Java API Client使用（Elasticsearch 7.17+）

（1）添加依赖

<dependency><groupId>org.springframework.data</groupId><artifactId>spring-data-elasticsearch</artifactId><version>5.1.0</version>
</dependency>
<dependency><groupId>co.elastic.clients</groupId><artifactId>elasticsearch-java</artifactId><version>8.11.4</version>
</dependency>

（2）配置客户端

@Configuration
public class ElasticsearchClientConfig {@Value("${spring.elasticsearch.uris}")private String[] elasticsearchUris;@Beanpublic ElasticsearchClient elasticsearchClient() {// 创建低级客户端RestClient restClient = RestClient.builder(HttpHost.create(elasticsearchUris[0])).build();// 创建传输层ElasticsearchTransport transport = new RestClientTransport(restClient, new JacksonJsonpMapper());// 创建API客户端return new ElasticsearchClient(transport);}
}

（3）使用Java API Client

@Service
@RequiredArgsConstructor
public class ProductJavaClientService {private final ElasticsearchClient elasticsearchClient;public void createProduct(Product product) throws IOException {elasticsearchClient.index(i -> i.index("products").id(product.getId()).document(product));}public List<Product> searchProducts(String keyword) throws IOException {SearchResponse<Product> response = elasticsearchClient.search(s -> s.index("products").query(q -> q.match(m -> m.field("name").query(keyword))),Product.class);return response.hits().hits().stream().map(Hit::source).collect(Collectors.toList());}
}