【业务功能篇83】微服务SpringCloud-ElasticSearch-Kibanan-docker安装-应用层实战

叁歲伎倆 2024-03-24 21:33 3阅读 0赞

## 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

![image.png][]

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

![image.png][image.png 1]

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

![image.png][image.png 2]

![image.png][image.png 3]

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;
        }
    }

![image.png][image.png 4]

测试：

![image.png][image.png 5]

#### 2.2 测试保存文档 ####

##### 设置RequestOptions #####

![image.png][image.png 6]

我们就在ElasticSearch的配置文件中设置

![image.png][image.png 7]

##### 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

![image.png][image.png 8]

![image.png][image.png 9]

#### 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);
        }

![image.png][image.png 10]

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：

![image.png][image.png 11]

[image.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/e4f915ae975f4143916c2fa1bbb8d997.png
[image.png 1]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/b29d5f7d8190482b8461c778dbe23a75.png
[image.png 2]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/275c246dd037448398eecefe8f24690a.png
[image.png 3]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/59819f4c231b497cb9e5b731206c77d9.png
[image.png 4]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/6345ba7c84e746738d19aca68d8a6834.png
[image.png 5]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/abb43c609f544e41a803cfc5115d85b1.png
[image.png 6]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/ee6009eefd4945bf94cad210a184cb1c.png
[image.png 7]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/16d5cc2a2931463ebea3b2efad62a208.png
[image.png 8]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/ee214676450442e4a2bf6ab963ade416.png
[image.png 9]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/3ea876ec08cd409b9b4fd760daec2873.png
[image.png 10]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/5830c3c12d3640b19e06f79ec4c8f159.png
[image.png 11]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/13/3f697c44306f4e499849828c51e18dd6.png