五、ElasticSearch应用

1.ES 的Java API两种方式

  Elasticsearch 的API 分为 REST Client API（http请求形式）以及 transportClient
API两种。相比来说transportClient API效率更高，transportClient
是通过Elasticsearch内部RPC的形式进行请求的，连接可以是一个长连接，相当于是把客户端的请求当成

  Elasticsearch 集群的一个节点，当然 REST Client API 也支持http
keepAlive形式的长连接，只是非内部RPC形式。但是从Elasticsearch 7 后就会移除transportClient
。主要原因是transportClient 难以向下兼容版本。

1.1 9300[TCP]

  利用9300端口的是spring-data-elasticsearch:transport-api.jar,但是这种方式因为对应的SpringBoot版本不一致，造成对应的transport-api.jar也不同，不能适配es的版本，而且ElasticSearch7.x中已经不推荐使用了，ElasticSearch 8之后更是废弃了，所以我们不做过多的介绍

1.2 9200[HTTP]

  基于9200端口的方式也有多种

• JsetClient:非官方，更新缓慢
• RestTemplate:模拟发送Http请求，ES很多的操作需要我们自己来封装，效率低
• HttpClient：和上面的情况一样
• ElasticSearch-Rest-Client:官方的RestClient，封装了ES的操作，API层次分明，易于上手。
• JavaAPIClient 7.15版本后推荐

2.ElasticSearch-Rest-Client整合

2.1 创建检索的服务

  我们在商城服务中创建一个检索的SpringBoot服务

添加对应的依赖：官方地址：https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-high-getting-started-maven.html#java-rest-high-getting-started-maven-maven

公共依赖不要忘了，同时我们在公共依赖中依赖了MyBatisPlus所以我们需要在search服务中排除数据源，不然启动报错

然后我们需要把这个服务注册到Nacos注册中心中，这块操作了很多遍，不重复

添加对应的ElasticSearch的配置类

/**
 * ElasticSearch的配置类
 */
@Configuration
public class MallElasticSearchConfiguration {

    @Bean
    public RestHighLevelClient restHighLevelClient(){
        RestClientBuilder builder = RestClient.builder(new HttpHost("192.168.56.100", 9200, "http"));
        RestHighLevelClient client = new RestHighLevelClient(builder);
        return client;
    }
}

测试：

2.2 测试保存文档

设置RequestOptions

我们就在ElasticSearch的配置文件中设置

保存数据

然后就可以结合官方文档来实现文档数据的存储

package com.msb.mall.mallsearch;

import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.util.JSONPObject;
import com.msb.mall.mallsearch.config.MallElasticSearchConfiguration;
import lombok.Data;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.common.xcontent.XContentType;
import org.json.JSONObject;
import org.junit.jupiter.api.Test;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;

@SpringBootTest
class MallSearchApplicationTests {

    @Autowired
    private RestHighLevelClient client;

    @Test
    void contextLoads() {
        System.out.println("--->"+client);
    }

    /**
     * 测试保存文档
     */
    @Test
    void saveIndex() throws Exception {
        IndexRequest indexRequest = new IndexRequest("system");
        indexRequest.id("1");
        // indexRequest.source("name","bobokaoya","age",18,"gender","男");
        User user = new User();
        user.setName("bobo");
        user.setAge(22);
        user.setGender("男");
        // 用Jackson中的对象转json数据
        ObjectMapper objectMapper = new ObjectMapper();
        String json = objectMapper.writeValueAsString(user);
        indexRequest.source(json, XContentType.JSON);
        // 执行操作
        IndexResponse index = client.index(indexRequest, MallElasticSearchConfiguration.COMMON_OPTIONS);
        // 提取有用的返回信息
        System.out.println(index);
    }
    @Data
    class User{
        private String name;
        private Integer age;
        private String gender;
    }

}

之后成功

2.3 检索操作

参考官方文档可以获取到处理各种检索情况的API

案例1：检索出所有的bank索引的所有文档

    @Test
    void searchIndexAll() throws IOException {
        // 1.创建一个 SearchRequest 对象
        SearchRequest searchRequest = new SearchRequest();
        searchRequest.indices("bank"); // 设置我们要检索的数据对应的索引库
        SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
        /*sourceBuilder.query();
        sourceBuilder.from();
        sourceBuilder.size();
        sourceBuilder.aggregation();*/
        searchRequest.source(sourceBuilder);

        // 2.如何执行检索操作
        SearchResponse response = client.search(searchRequest, MallElasticSearchConfiguration.COMMON_OPTIONS);
        // 3.获取检索后的响应对象，我们需要解析出我们关心的数据
        System.out.println("ElasticSearch检索的信息："+response);
    }

案例2：根据address全文检索

    @Test
    void searchIndexByAddress() throws IOException {
        // 1.创建一个 SearchRequest 对象
        SearchRequest searchRequest = new SearchRequest();
        searchRequest.indices("bank"); // 设置我们要检索的数据对应的索引库
        SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
        // 查询出bank下 address 中包含 mill的记录
        sourceBuilder.query(QueryBuilders.matchQuery("address","mill"));
        searchRequest.source(sourceBuilder);
        // System.out.println(searchRequest);

        // 2.如何执行检索操作
        SearchResponse response = client.search(searchRequest, MallElasticSearchConfiguration.COMMON_OPTIONS);
        // 3.获取检索后的响应对象，我们需要解析出我们关心的数据
        System.out.println("ElasticSearch检索的信息："+response);
    }

案例3：嵌套的聚合操作：检索出bank下的年龄分布和每个年龄段的平均薪资

/**
     * 聚合：嵌套聚合
     * @throws IOException
     */
    @Test
    void searchIndexAggregation() throws IOException {
        // 1.创建一个 SearchRequest 对象
        SearchRequest searchRequest = new SearchRequest();
        searchRequest.indices("bank"); // 设置我们要检索的数据对应的索引库
        SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
        // 查询出bank下 所有的文档
        sourceBuilder.query(QueryBuilders.matchAllQuery());
        // 聚合 aggregation
        // 聚合bank下年龄的分布和每个年龄段的平均薪资
        AggregationBuilder aggregationBuiler = AggregationBuilders.terms("ageAgg")
                                                .field("age")
                                                .size(10);
        // 嵌套聚合
        aggregationBuiler.subAggregation(AggregationBuilders.avg("balanceAvg").field("balance"));

        sourceBuilder.aggregation(aggregationBuiler);
        sourceBuilder.size(0); // 聚合的时候就不用显示满足条件的文档内容了
        searchRequest.source(sourceBuilder);
        System.out.println(sourceBuilder);

        // 2.如何执行检索操作
        SearchResponse response = client.search(searchRequest, MallElasticSearchConfiguration.COMMON_OPTIONS);
        // 3.获取检索后的响应对象，我们需要解析出我们关心的数据
        System.out.println(response);
    }

案例4：并行的聚合操作：查询出bank下年龄段的分布和总的平均薪资

/**
     * 聚合
     * @throws IOException
     */
    @Test
    void searchIndexAggregation1() throws IOException {
        // 1.创建一个 SearchRequest 对象
        SearchRequest searchRequest = new SearchRequest();
        searchRequest.indices("bank"); // 设置我们要检索的数据对应的索引库
        SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
        // 查询出bank下 所有的文档
        sourceBuilder.query(QueryBuilders.matchAllQuery());
        // 聚合 aggregation
        // 聚合bank下年龄的分布和平均薪资
        AggregationBuilder aggregationBuiler = AggregationBuilders.terms("ageAgg")
                .field("age")
                .size(10);

        sourceBuilder.aggregation(aggregationBuiler);
        // 聚合平均年龄
        AvgAggregationBuilder balanceAggBuilder = AggregationBuilders.avg("balanceAgg").field("age");
        sourceBuilder.aggregation(balanceAggBuilder);

        sourceBuilder.size(0); // 聚合的时候就不用显示满足条件的文档内容了
        searchRequest.source(sourceBuilder);
        System.out.println(sourceBuilder);

        // 2.如何执行检索操作
        SearchResponse response = client.search(searchRequest, MallElasticSearchConfiguration.COMMON_OPTIONS);
        // 3.获取检索后的响应对象，我们需要解析出我们关心的数据
        System.out.println(response);
    }

案例5：处理检索后的结果

 @Test
    void searchIndexResponse() throws IOException {
        // 1.创建一个 SearchRequest 对象
        SearchRequest searchRequest = new SearchRequest();
        searchRequest.indices("bank"); // 设置我们要检索的数据对应的索引库
        SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
        // 查询出bank下 address 中包含 mill的记录
        sourceBuilder.query(QueryBuilders.matchQuery("address","mill"));
        searchRequest.source(sourceBuilder);
        // System.out.println(searchRequest);

        // 2.如何执行检索操作
        SearchResponse response = client.search(searchRequest, MallElasticSearchConfiguration.COMMON_OPTIONS);
        // 3.获取检索后的响应对象，我们需要解析出我们关心的数据
       // System.out.println("ElasticSearch检索的信息："+response);
        RestStatus status = response.status();
        TimeValue took = response.getTook();
        SearchHits hits = response.getHits();
        TotalHits totalHits = hits.getTotalHits();
        TotalHits.Relation relation = totalHits.relation;
        long value = totalHits.value;
        float maxScore = hits.getMaxScore(); // 相关性的最高分
        SearchHit[] hits1 = hits.getHits();
        for (SearchHit documentFields : hits1) {
            /*"_index" : "bank",
                    "_type" : "account",
                    "_id" : "970",
                    "_score" : 5.4032025*/
            //documentFields.getIndex(),documentFields.getType(),documentFields.getId(),documentFields.getScore();
            String json = documentFields.getSourceAsString();
            //System.out.println(json);
            // JSON字符串转换为 Object对象
            ObjectMapper mapper = new ObjectMapper();
            Account account = mapper.readValue(json, Account.class);
            System.out.println("account = " + account);
        }
        //System.out.println(relation.toString()+"--->" + value + "--->" + status);
    }

    @ToString
    @Data
    static class Account {

        private int account_number;
        private int balance;
        private String firstname;
        private String lastname;
        private int age;
        private String gender;
        private String address;
        private String employer;
        private String email;
        private String city;
        private String state;

    }

数据的结果：