• SpringBoot整合RestHighLevelClient案例

    1、RestHighLevelClient介绍

    JavaREST客户端有两种模式：

    • Java Low Level REST Client：ES官方的低级客户端。低级别的客户端通过http与Elasticearch集群通信。
    • Java High Level REST Client：ES官方的高级客户端。基于上面的低级客户端，也是通过HTTP与ES集群进行通信。它提供了更多的接口。

    下面介绍下 SpringBoot 如何通过 elasticsearch-rest-high-level-client 工具操作ElasticSearch。当然也可以通过spring-data-elasticsearch来操作ElasticSearch，而本文仅是 elasticsearch-rest-high-level-client 的案例介绍，所以本文中我并未使用spring-data-elasticsearch，后期我会补上。

    注意事项：客户端(Client) Jar包的版本尽量不要大于Elasticsearch本体的版本，否则可能出现客户端中使用的某些API在Elasticsearch中不支持。

    这里需要说一下，能使用RestHighLevelClient尽量使用它，为什么不推荐使用 Spring 家族封装的 spring-data-elasticsearch。主要原因是灵活性和更新速度，Spring 将 ElasticSearch 过度封装，让开发者很难跟 ES 的 DSL 查询语句进行关联。再者就是更新速度，ES 的更新速度是非常快，但是 spring-data-elasticsearch 更新速度比较缓慢。并且spring-data-elasticsearch在Elasticsearch6.x和7.x版本上的Java API差距很大，如果升级版本需要花点时间来了解。

    TIPS：spring-data-elasticsearch的底层其实也是否则了elasticsearch-rest-high-level-client的api。

    2、引入依赖

    特别注意：引入的依赖最好与SpringBoot中的版本一样，免得出现版本冲突。

    <!--引入es-high-level-client的坐标-->
<dependency>
    <groupId>org.elasticsearch.client</groupId>
    <artifactId>elasticsearch-rest-high-level-client</artifactId>
    <version>7.6.2</version>
</dependency>
<dependency>
    <groupId>org.elasticsearch.client</groupId>
    <artifactId>elasticsearch-rest-client</artifactId>
    <version>7.6.2</version>
</dependency>
<dependency>
    <groupId>org.elasticsearch</groupId>
    <artifactId>elasticsearch</artifactId>
    <version>7.6.2</version>
</dependency>

<!--mybatis-->
<dependency>
    <groupId>org.mybatis.spring.boot</groupId>
    <artifactId>mybatis-spring-boot-starter</artifactId>
    <version>2.1.0</version>
</dependency>

<dependency>
    <groupId>mysql</groupId>
    <artifactId>mysql-connector-java</artifactId>
</dependency>

    完整的Maven依赖：

    <?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">

    <modelVersion>4.0.0</modelVersion>
    <groupId>com.thr.elasticsearch</groupId>
    <artifactId>elasticsearch-rest-high-level-client-demo</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <name>elasticsearch-rest-high-level-client-demo</name>
    <description>Demo project for Spring Boot</description>

    <properties>
        <java.version>1.8</java.version>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
        <spring-boot.version>2.3.7.RELEASE</spring-boot.version>
    </properties>

    <dependencies>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter</artifactId>
        </dependency>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
            <exclusions>
                <exclusion>
                    <groupId>org.junit.vintage</groupId>
                    <artifactId>junit-vintage-engine</artifactId>
                </exclusion>
            </exclusions>
        </dependency>

        <!--引入es-high-level-client的坐标-->
        <dependency>
            <groupId>org.elasticsearch.client</groupId>
            <artifactId>elasticsearch-rest-high-level-client</artifactId>
            <version>7.6.2</version>
        </dependency>
        <dependency>
            <groupId>org.elasticsearch.client</groupId>
            <artifactId>elasticsearch-rest-client</artifactId>
            <version>7.6.2</version>
        </dependency>
        <dependency>
            <groupId>org.elasticsearch</groupId>
            <artifactId>elasticsearch</artifactId>
            <version>7.6.2</version>
        </dependency>

        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.72</version>
        </dependency>

        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>

        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <scope>test</scope>
        </dependency>

        <!--mybatis-->
        <dependency>
            <groupId>org.mybatis.spring.boot</groupId>
            <artifactId>mybatis-spring-boot-starter</artifactId>
            <version>2.1.0</version>
        </dependency>

        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
        </dependency>
    </dependencies>

    <dependencyManagement>
        <dependencies>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-dependencies</artifactId>
                <version>${spring-boot.version}</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
        </dependencies>
    </dependencyManagement>

    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.8.1</version>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                    <encoding>UTF-8</encoding>
                </configuration>
            </plugin>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
                <version>2.3.7.RELEASE</version>
                <configuration>
                    <mainClass>com.thr.elasticsearch.ESRestHighLevelClientApplication</mainClass>
                </configuration>
                <executions>
                    <execution>
                        <id>repackage</id>
                        <goals>
                            <goal>repackage</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>

</project>

    3、ES的配置

    (1)、创建索引

    PUT /goods
{
  "mappings": {
    "properties": {
      "brandName": {
        "type": "keyword"
      },
      "categoryName": {
        "type": "keyword"
      },
      "createTime": {
        "type": "date",
        "format": "yyyy-MM-dd HH:mm:ss"
      },
      "id": {
        "type": "keyword"
      },
      "price": {
        "type": "double"
      },
      "saleNum": {
        "type": "integer"
      },
      "status": {
        "type": "integer"
      },
      "stock": {
        "type": "integer"
      },
      "title": {
        "type": "text",
        "analyzer": "ik_max_word",
        "search_analyzer": "ik_smart"
      }
    }
  }
}

    (2)、application.yml 配置文件

    elasticsearch:
  host: 116.205.230.143
  port: 9200
spring:
  # 应用名称
  application:
    name: elasticsearch-spring-data
  datasource:
    username: root
    password: 123456
    url: jdbc:mysql://116.205.230.143:3306/es?useSSL=false&serverTimezone=UTC&characterEncoding=utf8&allowMultiQueries=true
    driver-class-name: com.mysql.cj.jdbc.Driver
  elasticsearch:
    rest:
      # 定位ES的位置
      uris: http://116.205.230.143:9200
mybatis:
  type-aliases-package: com.thr.elastisearch.domain
  mapper-locations: classpath:mapper/*.xml

    (3)、java 连接配置类

    写一个 Java 配置类读取 application 中的配置信息：

    /**
 * ES的配置类
 * ElasticSearchConfig
 *
 * @author tanghaorong
 */
@Data
@Configuration
@ConfigurationProperties(prefix = "elasticsearch")
public class ElasticSearchConfig {

    private String host;
    private Integer port;

    /**
     * 如果@Bean没有指定bean的名称，那么这个bean的名称就是方法名
     */
    @Bean
    public RestHighLevelClient restHighLevelClient() {
        return new RestHighLevelClient(
                RestClient.builder(
                        new HttpHost(host, port, "http")
                )
        );
    }
}

    (4)、mybatis配置

    /**
 * Mapper接口
 *
 * @author tanghaorong
 */
@Repository
@Mapper
public interface GoodsMapper {
    /**
     * 查询所有
     */
    List<Goods> findAll();
}

    <?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd">

<mapper namespace="com.thr.elasticsearch.dao.GoodsMapper">
    <select id="findAll" resultType="com.thr.elasticsearch.domain.Goods">
        select `id`,
               `title`,
               `price`,
               `stock`,
               `saleNum`,
               `createTime`,
               `categoryName`,
               `brandName`,
               `status`
        from goods
    </select>
</mapper>

    (5)、实体对象

    @Data
@Accessors(chain = true)   // 链式赋值(连续set方法)
@AllArgsConstructor        // 全参构造
@NoArgsConstructor         // 无参构造
public class Goods {

    /**
     * 商品编号
     */
    private Long id;

    /**
     * 商品标题
     */
    private String title;

    /**
     * 商品价格
     */
    private BigDecimal price;

    /**
     * 商品库存
     */
    private Integer stock;

    /**
     * 商品销售数量
     */
    private Integer saleNum;

    /**
     * 商品分类
     */
    private String categoryName;

    /**
     * 商品品牌
     */
    private String brandName;

    /**
     * 上下架状态
     */
    private Integer status;

    /**
     * 商品创建时间
     */
    @JSONField(format = "yyyy-MM-dd HH:mm:ss")
    private Date createTime;
}

    (6)、测试类

    @SpringBootTest
@RunWith(SpringRunner.class)
@Slf4j
public class ESRestHighLevelClientApplicationTests {

    @Test
    public void test1() throws IOException {
 
    }
}

    需要注意的是，测试启动类要和项目的启动类位于同一个包中，否则启动可能会报错。


    (7)、项目整体结构

    image

    4、索引操作

        /**
     * 创建索引库和映射表结构
     * 注意：索引一般不会怎么创建
     */
    @Test
    public void indexCreate() throws Exception {
        IndicesClient indicesClient = restHighLevelClient.indices();
        // 创建索引
        CreateIndexRequest indexRequest = new CreateIndexRequest("goods111");
        // 创建表 结构
        String mapping = "{\n" +
                "    \"properties\": {\n" +
                "      \"brandName\": {\n" +
                "        \"type\": \"keyword\"\n" +
                "      },\n" +
                "      \"categoryName\": {\n" +
                "        \"type\": \"keyword\"\n" +
                "      },\n" +
                "      \"createTime\": {\n" +
                "        \"type\": \"date\",\n" +
                "        \"format\": \"yyyy-MM-dd HH:mm:ss\"\n" +
                "      },\n" +
                "      \"id\": {\n" +
                "        \"type\": \"keyword\"\n" +
                "      },\n" +
                "      \"price\": {\n" +
                "        \"type\": \"double\"\n" +
                "      },\n" +
                "      \"saleNum\": {\n" +
                "        \"type\": \"integer\"\n" +
                "      },\n" +
                "      \"status\": {\n" +
                "        \"type\": \"integer\"\n" +
                "      },\n" +
                "      \"stock\": {\n" +
                "        \"type\": \"integer\"\n" +
                "      },\n" +
                "      \"title\": {\n" +
                "        \"type\": \"text\",\n" +
                "        \"analyzer\": \"ik_max_word\",\n" +
                "        \"search_analyzer\": \"ik_smart\"\n" +
                "      }\n" +
                "    }\n" +
                "  }";
        // 把映射信息添加到request请求里面
        // 第一个参数：表示数据源
        // 第二个参数：表示请求的数据类型
        indexRequest.mapping(mapping, XContentType.JSON);
        // 请求服务器
        CreateIndexResponse response = indicesClient.create(indexRequest, RequestOptions.DEFAULT);
        System.out.println(response.isAcknowledged());
    }

    /**
     * 获取表结构
     * GET goods/_mapping
     */
    @Test
    public void getMapping() throws Exception {
        IndicesClient indicesClient = restHighLevelClient.indices();

        // 创建get请求
        GetIndexRequest request = new GetIndexRequest("goods");
        // 发送get请求
        GetIndexResponse response = indicesClient.get(request, RequestOptions.DEFAULT);
        // 获取表结构
        Map<String, MappingMetaData> mappings = response.getMappings();
        for (String key : mappings.keySet()) {
            System.out.println("key--" + mappings.get(key).getSourceAsMap());
        }
    }

    /**
     * 删除索引库
     */
    @Test
    public void indexDelete() throws Exception {
        IndicesClient indicesClient = restHighLevelClient.indices();
        // 创建delete请求方式
        DeleteIndexRequest deleteIndexRequest = new DeleteIndexRequest("goods");
        // 发送delete请求
        AcknowledgedResponse response = indicesClient.delete(deleteIndexRequest, RequestOptions.DEFAULT);
        System.out.println(response.isAcknowledged());
    }

    /**
     * 判断索引库是否存在
     */
    @Test
    public void indexExists() throws Exception {
        IndicesClient indicesClient = restHighLevelClient.indices();
        // 创建get请求
        GetIndexRequest request = new GetIndexRequest("goods");
        // 判断索引库是否存在
        boolean result = indicesClient.exists(request, RequestOptions.DEFAULT);
        System.out.println(result);
    }

    5、文档操作

        /**
     * 增加文档信息
     */
    @Test
    public void addDocument() throws IOException {

        // 创建商品信息
        Goods goods = new Goods();
        goods.setId(1L);
        goods.setTitle("Apple iPhone 13 Pro (A2639) 256GB 远峰蓝色 支持移动联通电信5G 双卡双待手机");
        goods.setPrice(new BigDecimal("8799.00"));
        goods.setStock(1000);
        goods.setSaleNum(599);
        goods.setCategoryName("手机");
        goods.setBrandName("Apple");
        goods.setStatus(0);
        goods.setCreateTime(new Date());

        // 将对象转为json
        String data = JSON.toJSONString(goods);
        // 创建索引请求对象
        IndexRequest indexRequest = new IndexRequest("goods").id(goods.getId() + "").source(data, XContentType.JSON);
        // 执行增加文档
        IndexResponse response = restHighLevelClient.index(indexRequest, RequestOptions.DEFAULT);
        log.info("创建状态：{}", response.status());
    }

    /**
     * 获取文档信息
     */
    @Test
    public void getDocument() throws IOException {
        // 创建获取请求对象
        GetRequest getRequest = new GetRequest("goods", "1");
        GetResponse response = restHighLevelClient.get(getRequest, RequestOptions.DEFAULT);
        System.out.println(response.getSourceAsString());
    }


    /**
     * 更新文档信息
     */
    @Test
    public void updateDocument() throws IOException {

        // 设置商品更新信息
        Goods goods = new Goods();
        goods.setTitle("Apple iPhone 13 Pro Max (A2644) 256GB 远峰蓝色 支持移动联通电信5G 双卡双待手机");
        goods.setPrice(new BigDecimal("9999"));

        // 将对象转为json
        String data = JSON.toJSONString(goods);
        // 创建索引请求对象
        UpdateRequest updateRequest = new UpdateRequest("goods", "1");
        // 设置更新文档内容
        updateRequest.doc(data, XContentType.JSON);
        // 执行更新文档
        UpdateResponse response = restHighLevelClient.update(updateRequest, RequestOptions.DEFAULT);
        log.info("创建状态：{}", response.status());
    }

    /**
     * 删除文档信息
     */
    @Test
    public void deleteDocument() throws IOException {

        // 创建删除请求对象
        DeleteRequest deleteRequest = new DeleteRequest("goods", "1");
        // 执行删除文档
        DeleteResponse response = restHighLevelClient.delete(deleteRequest, RequestOptions.DEFAULT);
        log.info("删除状态：{}", response.status());
    }

    6、导入测试数据

    下载测试数据

    下载链接：https://files.cnblogs.com/files/tanghaorong/goods.zip?t=1654416464

    下载后导入数据库中，大概有900多条。

    image


    导入测试数据至ES中：

    /**
 * 批量导入测试数据
 */
@Test
public void importData() throws IOException {
    //1.查询所有数据，mysql
    List<Goods> goodsList = goodsMapper.findAll();

    //2.bulk导入
    BulkRequest bulkRequest = new BulkRequest();

    //2.1 循环goodsList，创建IndexRequest添加数据
    for (Goods goods : goodsList) {

        //将goods对象转换为json字符串
        String data = JSON.toJSONString(goods);//map --> {}
        IndexRequest indexRequest = new IndexRequest("goods");
        indexRequest.id(goods.getId() + "").source(data, XContentType.JSON);
        bulkRequest.add(indexRequest);
    }

    BulkResponse response = restHighLevelClient.bulk(bulkRequest, RequestOptions.DEFAULT);
    System.out.println(response.status());
}

    导入成功。

    image

    7、DSL高级查询操作

    精确查询(term)

    term查询：不会分析查询条件，只有当词条和查询字符串完全匹配时才匹配，也就是精确查找，比如数字，日期，布尔值或 not_analyzed 的字符串(未经分析的文本数据类型)

    terms查询：terms 跟 term 有点类似，但 terms 允许指定多个匹配条件。 如果某个字段指定了多个值，那么文档需要一起去 做匹配：

    /**
 * 精确查询（termQuery）
 */
@Test
public void termQuery() {
    try {
        // 构建查询条件（注意：termQuery 支持多种格式查询，如 boolean、int、double、string 等，这里使用的是 string 的查询）
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.termQuery("title", "华为"));
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info("=======" + userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

/**
 * terms:多个查询内容在一个字段中进行查询
 */
@Test
public void termsQuery() {
    try {
        // 构建查询条件（注意：termsQuery 支持多种格式查询，如 boolean、int、double、string 等，这里使用的是 string 的查询）
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.termsQuery("title", "华为", "OPPO", "TCL"));
        // 展示100条,默认只展示10条记录
        searchSourceBuilder.size(100);
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    全文查询(match)

    全文查询会分析查询条件，先将查询条件进行分词，然后查询，求并集。

    term和match的区别是：match是经过analyer的，也就是说，文档首先被分析器给处理了。根据不同的分析器，分析的结果也稍显不同，然后再根据分词结果进行匹配。term则不经过分词，它是直接去倒排索引中查找了精确的值了。

    match 查询语法汇总：

    1. match_all：查询全部。
    2. match：返回所有匹配的分词。
    3. match_phrase：短语查询，在match的基础上进一步查询词组，可以指定slop分词间隔。
    4. match_phrase_prefix：前缀查询，根据短语中最后一个词组做前缀匹配，可以应用于搜索提示，但注意和max_expanions搭配。其实默认是50.......
    5. multi_match：多字段查询，使用相当的灵活，可以完成match_phrase和match_phrase_prefix的工作。
    /**
 * 匹配查询符合条件的所有数据，并设置分页
 */
@Test
public void matchAllQuery() {
    try {
        // 构建查询条件
        MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
        // 创建查询源构造器
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(matchAllQueryBuilder);
        // 设置分页
        searchSourceBuilder.from(0);
        searchSourceBuilder.size(3);
        // 设置排序
        searchSourceBuilder.sort("price", SortOrder.ASC);
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

/**
 * 匹配查询数据
 */
@Test
public void matchQuery() {
    try {
        // 构建查询条件
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.matchQuery("title", "华为"));
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

/**
 * 词语匹配查询
 */
@Test
public void matchPhraseQuery() {
    try {
        // 构建查询条件
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.matchPhraseQuery("title", "三星"));
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

/**
 * 内容在多字段中进行查询
 */
@Test
public void matchMultiQuery() {
    try {
        // 构建查询条件
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.multiMatchQuery("手机", "title", "categoryName"));
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    通配符查询(wildcard)

    wildcard查询：会对查询条件进行分词。还可以使用通配符 ?（任意单个字符） 和 * （0个或多个字符）

    /**
 * 查询所有以 “三” 结尾的商品信息
 * <p>
 * *：表示多个字符（0个或多个字符）
 * ?：表示单个字符
 */
@Test
public void wildcardQuery() {
    try {
        // 构建查询条件
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.wildcardQuery("title", "*三"));
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    模糊查询(fuzzy)

    /**
 * 模糊查询所有以 “三” 结尾的商品信息
 */
@Test
public void fuzzyQuery() {
    try {
        // 构建查询条件
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.fuzzyQuery("title", "三").fuzziness(Fuzziness.AUTO));
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    排序查询(sort)

    注意：需要分词的字段不可以直接排序，比如：text类型，如果想要对这类字段进行排序，需要特别设置：对字段索引两次，一次索引分词（用于搜索）一次索引不分词（用于排序），es默认生成的text类型字段就是通过这样的方法实现可排序的。

    /**
 * 排序查询(sort) 代码同matchAllQuery
 * 匹配查询符合条件的所有数据，并设置分页
 */
@Test
public void matchAllQuery() {
    try {
        // 构建查询条件
        MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
        // 创建查询源构造器
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(matchAllQueryBuilder);
        // 设置分页
        searchSourceBuilder.from(0);
        searchSourceBuilder.size(3);
        // 设置排序
        searchSourceBuilder.sort("price", SortOrder.ASC);
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    分页查询(page)

    Elasticsearchde 的分页查询和 SQL 使用 LIMIT 关键字返回只有一页的结果一样，Elasticsearch 接受 from 和 size 参数：

    • size: 结果数，默认10
    • from: 跳过开始的结果数，即从哪一行开始获取数据，默认0

    这种方式分页查询如果需要深度分页，那么这种方式性能不太好。

    /**
 * 分页查询(page) 代码同matchAllQuery
 * 匹配查询符合条件的所有数据，并设置分页
 */
@Test
public void matchAllQuery() {
    try {
        // 构建查询条件
        MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
        // 创建查询源构造器
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(matchAllQueryBuilder);
        // 设置分页
        searchSourceBuilder.from(0);
        searchSourceBuilder.size(3);
        // 设置排序
        searchSourceBuilder.sort("price", SortOrder.ASC);
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    滚动查询(scroll)

    滚动查询可以优化ES的深度分页，但是需要维护scrollId

    /**
 * 根据查询条件滚动查询
 * 可以用来解决深度分页查询问题
 */
@Test
public void scrollQuery() {

    // 假设用户想获取第70页数据，其中每页10条
    int pageNo = 70;
    int pageSize = 10;

    // 定义请求对象
    SearchRequest searchRequest = new SearchRequest("goods");

    // 构建查询条件
    SearchSourceBuilder builder = new SearchSourceBuilder();
    searchRequest.source(builder.query(QueryBuilders.matchAllQuery()).size(pageSize));
    String scrollId = null;
    // 3、发送请求到ES
    SearchResponse scrollResponse = null;
    // 设置游标id存活时间
    Scroll scroll = new Scroll(TimeValue.timeValueMinutes(2));
    // 记录所有游标id
    List<String> scrollIds = new ArrayList<>();
    for (int i = 0; i < pageNo; i++) {
        try {
            // 首次检索
            if (i == 0) {
                //记录游标id
                searchRequest.scroll(scroll);
                // 首次查询需要指定索引名称和查询条件
                SearchResponse response = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
                // 下一次搜索要用到该游标id
                scrollId = response.getScrollId();
                // 记录所有游标id
            }
            // 非首次检索
            else {
                // 不需要在使用其他条件，也不需要指定索引名称，只需要使用执行游标id存活时间和上次游标id即可，毕竟信息都在上次游标id里面呢
                SearchScrollRequest searchScrollRequest = new SearchScrollRequest(scrollId);
                searchScrollRequest.scroll(scroll);
                scrollResponse = restHighLevelClient.scroll(searchScrollRequest, RequestOptions.DEFAULT);
                // 下一次搜索要用到该游标id
                scrollId = scrollResponse.getScrollId();
                // 记录所有游标id
            }
            scrollIds.add(scrollId);
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
    //清除游标id
    ClearScrollRequest clearScrollRequest = new ClearScrollRequest();
    clearScrollRequest.scrollIds(scrollIds);
    try {
        restHighLevelClient.clearScroll(clearScrollRequest, RequestOptions.DEFAULT);
    } catch (IOException e) {
        System.out.println("清除滚动查询游标id失败");
        e.printStackTrace();
    }
    // 4、处理响应结果
    System.out.println("滚动查询返回数据：");
    assert scrollResponse != null;
    SearchHits hits = scrollResponse.getHits();
    for (SearchHit hit : hits) {
        // 将 JSON 转换成对象
        Goods goods = JSON.parseObject(hit.getSourceAsString(), Goods.class);
        // 输出查询信息
        log.info(goods.toString());
    }
}

    范围查询(range)

    /**
 * 查询价格大于等于10000的商品信息
 */
@Test
public void rangeQuery() {
    try {
        // 构建查询条件
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.rangeQuery("price").gte(10000));
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            log.info(hits.getTotalHits().value + "");
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

/**
 * 查询距离现在 10 年间的商品信息
 * [年(y)、月(M)、星期(w)、天(d)、小时(h)、分钟(m)、秒(s)]
 * 例如：
 * now-1h 查询一小时内范围
 * now-1d 查询一天内时间范围
 * now-1y 查询最近一年内的时间范围
 */
@Test
public void dateRangeQuery() {
    try {
        // 构建查询条件
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        // includeLower（是否包含下边界）、includeUpper（是否包含上边界）
        searchSourceBuilder.query(QueryBuilders.rangeQuery("createTime")
                .gte("now-10y").includeLower(true).includeUpper(true));
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods userInfo = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(userInfo.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    布尔查询(bool)

    bool 查询可以用来合并多个条件查询结果的布尔逻辑，它包含一下操作符：

    • must：多个查询条件必须完全匹配，相当于关系型数据库中的 and。
    • should：至少有一个查询条件匹配，相当于关系型数据库中的 or。
    • must_not： 多个查询条件的相反匹配，相当于关系型数据库中的 not。
    • filter：过滤满足条件的数据。
      • range：条件筛选范围。
        • gt：大于，相当于关系型数据库中的 >。
        • gte：大于等于，相当于关系型数据库中的 >=。
        • lt：小于，相当于关系型数据库中的 <。
        • lte：小于等于，相当于关系型数据库中的 <=。
    /**
 * boolQuery 查询
 * 案例：查询从2018-2022年间标题含 三星 的商品信息
 */
@Test
public void boolQuery() {
    try {
        // 创建 Bool 查询构建器
        BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
        // 构建查询条件
        boolQueryBuilder.must(QueryBuilders.matchQuery("title", "三星"))
                .filter().add(QueryBuilders.rangeQuery("createTime").format("yyyy").gte("2018").lte("2022"));
        // 构建查询源构建器
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(boolQueryBuilder);
        searchSourceBuilder.size(100);
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods goods = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(goods.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    queryString查询

    会对查询条件进行分词， 然后将分词后的查询条件和词条进行等值匹配，默认取并集（OR），可以指定单个字段也可多个查询字段

    /**
 * queryStringQuery查询
 * 案例：查询出必须包含 华为手机 词语的商品信息
 */
@Test
public void queryStringQuery() {
    try {
        // 创建 queryString 查询构建器
        QueryStringQueryBuilder queryStringQueryBuilder = QueryBuilders.queryStringQuery("华为手机").defaultOperator(Operator.AND);

        // 构建查询源构建器
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(queryStringQueryBuilder);
        searchSourceBuilder.size(100);
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods goods = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(goods.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    查询结果过滤

    我们在查询数据的时候，返回的结果中，所有字段都给我们返回了，但是有时候我们并不需要那么多，所以可以对结果进行过滤处理。

    /**
 * 过滤source获取部分字段内容
 * 案例：只获取 title、categoryName和price的数据
 */
@Test
public void sourceFilter() {
    try {
        //查询条件(词条查询：对应ES query里的match)
        BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery()
                .must(QueryBuilders.matchQuery("title", "金立"))
                .must(QueryBuilders.matchQuery("categoryName", "手机"))
                .filter(QueryBuilders.rangeQuery("price").gt(1000).lt(2000));

        // 构建查询源构建器
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(boolQueryBuilder);

        // 如果查询的属性很少，那就使用includes，而excludes设置为空数组
        // 如果排序的属性很少，那就使用excludes，而includes设置为空数组
        String[] includes = {"title", "categoryName", "price"};
        String[] excludes = {};
        searchSourceBuilder.fetchSource(includes, excludes);

        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods goods = JSON.parseObject(hit.getSourceAsString(), Goods.class);
                // 输出查询信息
                log.info(goods.toString());
            }
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    高亮查询

    /**
 * 高亮查询
 * 案例：把标题中为 三星手机 的词语高亮显示
 */
@Test
public void highlightBuilder() {
    try {
        //查询条件(词条查询：对应ES query里的match)
        MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("title", "三星手机");

        //设置高亮三要素                                     field: 你的高亮字段    // preTags ：前缀    // postTags：后缀
        HighlightBuilder highlightBuilder = new HighlightBuilder().field("title").preTags("<font color='red'>").postTags("</font>");

        // 构建查询源构建器
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(matchQueryBuilder);
        searchSourceBuilder.highlighter(highlightBuilder);
        searchSourceBuilder.size(100);
        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 根据状态和数据条数验证是否返回了数据
        if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().getTotalHits().value > 0) {
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                // 将 JSON 转换成对象
                Goods goods = JSON.parseObject(hit.getSourceAsString(), Goods.class);

                // 获取高亮的数据
                HighlightField highlightField = hit.getHighlightFields().get("title");
                System.out.println("高亮名称：" + highlightField.getFragments()[0].string());

                // 替换掉原来的数据
                Text[] fragments = highlightField.getFragments();
                if (fragments != null && fragments.length > 0) {
                    StringBuilder title = new StringBuilder();
                    for (Text fragment : fragments) {
                        //System.out.println(fragment);
                        title.append(fragment);
                    }
                    goods.setTitle(title.toString());
                }
                // 输出查询信息
                log.info(goods.toString());
            }

        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    聚合查询

    我们平时在使用Elasticsearch时，更多会用到聚合操作，它类似SQL中的group by操作。ES的聚合查询一定是先查出结果，然后对结果使用聚合函数做处理，常用的操作有：avg：求平均、max：最大值、min：最小值、sum：求和等。

    在ES中聚合分为指标聚合和分桶聚合：

    • Metric 指标聚合：指标聚合对一个数据集求最大、最小、和、平均值等
    • Bucket 分桶聚合：除了有上面的聚合函数外，还可以对查询出的数据进行分组group by，再在组上进行游标聚合。

    Metric 指标聚合分析

    /**
 * 聚合查询
 * Metric 指标聚合分析
 * 案例：分别获取最贵的商品和获取最便宜的商品
 */
@Test
public void metricQuery() {
    try {
        // 构建查询条件
        MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
        // 创建查询源构造器
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(matchAllQueryBuilder);

        // 获取最贵的商品
        AggregationBuilder maxPrice = AggregationBuilders.max("maxPrice").field("price");
        searchSourceBuilder.aggregation(maxPrice);
        // 获取最便宜的商品
        AggregationBuilder minPrice = AggregationBuilders.min("minPrice").field("price");
        searchSourceBuilder.aggregation(minPrice);

        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        Aggregations aggregations = searchResponse.getAggregations();
        ParsedMax max = aggregations.get("maxPrice");
        log.info("最贵的价格：" + max.getValue());
        ParsedMin min = aggregations.get("minPrice");
        log.info("最便宜的价格：" + min.getValue());
    } catch (IOException e) {
        log.error("", e);
    }
}

/**
 * 聚合查询
 * Bucket 分桶聚合分析
 * 案例：根据品牌进行聚合查询
 */
@Test
public void bucketQuery() {
    try {
        // 构建查询条件
        MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
        // 创建查询源构造器
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(matchAllQueryBuilder);

        // 根据商品分类进行分组查询
        TermsAggregationBuilder aggBrandName = AggregationBuilders.terms("brandNameName").field("brandName");
        searchSourceBuilder.aggregation(aggBrandName);

        // 创建查询请求对象，将查询对象配置到其中
        SearchRequest searchRequest = new SearchRequest("goods");
        searchRequest.source(searchSourceBuilder);
        // 执行查询，然后处理响应结果
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        Aggregations aggregations = searchResponse.getAggregations();
        ParsedStringTerms aggBrandName1 = aggregations.get("brandNameName");
        for (Terms.Bucket bucket : aggBrandName1.getBuckets()) {
            System.out.println(bucket.getKeyAsString() + "====" + bucket.getDocCount());
        }
    } catch (IOException e) {
        log.error("", e);
    }
}

    Bucket 分桶聚合分析

        /**
     * 聚合查询
     * Bucket 分桶聚合分析
     * 案例：根据品牌进行聚合查询
     */
    @Test
    public void bucketQuery() {
        try {
            // 构建查询条件
            MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
            // 创建查询源构造器
            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
            searchSourceBuilder.query(matchAllQueryBuilder);

            // 根据商品分类进行分组查询
            TermsAggregationBuilder aggBrandName = AggregationBuilders.terms("brandNameName").field("brandName");
            searchSourceBuilder.aggregation(aggBrandName);

            // 创建查询请求对象，将查询对象配置到其中
            SearchRequest searchRequest = new SearchRequest("goods");
            searchRequest.source(searchSourceBuilder);
            // 执行查询，然后处理响应结果
            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
            Aggregations aggregations = searchResponse.getAggregations();
            ParsedStringTerms aggBrandName1 = aggregations.get("brandNameName");
            for (Terms.Bucket bucket : aggBrandName1.getBuckets()) {
                System.out.println(bucket.getKeyAsString() + "====" + bucket.getDocCount());
            }
        } catch (IOException e) {
            log.error("", e);
        }
    }

    /**
     * 子聚合聚合查询
     * Bucket 分桶聚合分析
     * 案例：根据商品分类进行分组查询,并且获取分类商品中的平均价格
     */
    @Test
    public void subBucketQuery() {
        try {
            // 构建查询条件
            MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
            // 创建查询源构造器
            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
            searchSourceBuilder.query(matchAllQueryBuilder);

            // 根据商品分类进行分组查询,并且获取分类商品中的平均价格
            TermsAggregationBuilder subAggregation = AggregationBuilders.terms("brandNameName").field("brandName")
                    .subAggregation(AggregationBuilders.avg("avgPrice").field("price"));
            searchSourceBuilder.aggregation(subAggregation);

            // 创建查询请求对象，将查询对象配置到其中
            SearchRequest searchRequest = new SearchRequest("goods");
            searchRequest.source(searchSourceBuilder);
            // 执行查询，然后处理响应结果
            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
            Aggregations aggregations = searchResponse.getAggregations();
            ParsedStringTerms aggBrandName1 = aggregations.get("brandNameName");
            for (Terms.Bucket bucket : aggBrandName1.getBuckets()) {
                // 获取聚合后的品牌的平均价格,注意返回值不是Aggregation对象,而是指定的ParsedAvg对象
                ParsedAvg avgPrice = bucket.getAggregations().get("avgPrice");
                System.out.println(bucket.getKeyAsString() + "====" + avgPrice.getValueAsString());
            }
        } catch (IOException e) {
            log.error("", e);
        }
    }

    综合聚合查询

    /**
 * 综合聚合查询
 * 根据商品分类聚合，获取每个商品类的平均价格，并且在商品分类聚合之上子聚合每个品牌的平均价格
 */
@Test
public void subSubAgg() throws IOException {

    // 构建查询条件
    MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
    // 创建查询源构造器
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(matchAllQueryBuilder);

    // 注意这里聚合写的位置不要写错,很容易搞混,错一个括号就不对了
    TermsAggregationBuilder subAggregation = AggregationBuilders.terms("categoryNameAgg").field("categoryName")
            .subAggregation(AggregationBuilders.avg("categoryNameAvgPrice").field("price"))
            .subAggregation(AggregationBuilders.terms("brandNameAgg").field("brandName")
                    .subAggregation(AggregationBuilders.avg("brandNameAvgPrice").field("price")));
    searchSourceBuilder.aggregation(subAggregation);

    // 创建查询请求对象，将查询对象配置到其中
    SearchRequest searchRequest = new SearchRequest("goods");
    searchRequest.source(searchSourceBuilder);
    // 执行查询，然后处理响应结果
    SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
    //获取总记录数
    System.out.println("totalHits = " + searchResponse.getHits().getTotalHits().value);
    // 获取聚合信息
    Aggregations aggregations = searchResponse.getAggregations();
    ParsedStringTerms categoryNameAgg = aggregations.get("categoryNameAgg");
    //获取值返回
    for (Terms.Bucket bucket : categoryNameAgg.getBuckets()) {
        // 获取聚合后的分类名称
        String categoryName = bucket.getKeyAsString();
        // 获取聚合命中的文档数量
        long docCount = bucket.getDocCount();
        // 获取聚合后的分类的平均价格,注意返回值不是Aggregation对象,而是指定的ParsedAvg对象
        ParsedAvg avgPrice = bucket.getAggregations().get("categoryNameAvgPrice");

        System.out.println(categoryName + "======平均价:" + avgPrice.getValue() + "======数量:" + docCount);

        ParsedStringTerms brandNameAgg = bucket.getAggregations().get("brandNameAgg");
        for (Terms.Bucket brandeNameAggBucket : brandNameAgg.getBuckets()) {
            // 获取聚合后的品牌名称
            String brandName = brandeNameAggBucket.getKeyAsString();

            // 获取聚合后的品牌的平均价格,注意返回值不是Aggregation对象,而是指定的ParsedAvg对象
            ParsedAvg brandNameAvgPrice = brandeNameAggBucket.getAggregations().get("brandNameAvgPrice");

            System.out.println("     " + brandName + "======" + brandNameAvgPrice.getValue());
        }
    }
}

    image
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  • 原文地址：https://www.cnblogs.com/tanghaorong/p/16344391.html
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