Davids实操笔记：Spring Boot使用docker整合ElasticSearch ik分词搜索和拼音搜索

刺骨的言语ヽ痛彻心扉 2023-02-23 07:58 13阅读 0赞

### 文章目录 ###

*   *  Spring Boot使用docker整合ElasticSearch ik分词搜索和拼音搜索
     *   *  准备工作
         *   *  安装ik分词器
             *  安装pinyin插件
         *  Spring Boot进行分词和拼音查询
         *   *  创建setting和mapping文件
             *  将setting和mapping配置到UserEntity中
             *  编写测试类
         *  总结

## Spring Boot使用docker整合ElasticSearch ik分词搜索和拼音搜索 ##

前面的blog已经处理完[Spring Boot和docker安装配置ElasticSearch][Spring Boot_docker_ElasticSearch]，这篇blog主要讲一下使用docker安装ElasticSearch ik分词器和拼音搜索功能。

### 准备工作 ###

#### 安装ik分词器 ####

我们直接使用`elasticsearch-plugin`安装`ik分词器`

// 进入elasticsearch容器
    docker exec -it elasticsearch /bin/bash
    
    // 安装ik分词器7.8.0
     ./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.8.0/elasticsearch-analysis-ik-7.8.0.zip

安装过程如下：  
![安装ik分词器][ik]

#### 安装pinyin插件 ####

和ik分词器一样我们同样使用`elasticsearch-plugin`安装`pinyin插件`

// 安装ik分词器7.8.0
     ./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-pinyin/releases/download/v7.8.0/elasticsearch-analysis-pinyin-7.8.0.zip

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0Rhdmlkc18_size_16_color_FFFFFF_t_70]  
检查一下plugins目录查看是否安装成功，准备工作就完成了。  
![检查plugins目录][plugins]

### Spring Boot进行分词和拼音查询 ###

前面已经完成了一部分编码工作了，请查看[Spring Boot 使用docker整合ElasticSearch][Spring Boot_docker_ElasticSearch]，那么这次我们就继续在上次的基础上改造，使其支持拼音和分词搜索。

#### 创建setting和mapping文件 ####

文件存放在`resource`目录下，为了方便区分，所以我新建了一个elasticsearch目录。  
![文件目录][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0Rhdmlkc18_size_16_color_FFFFFF_t_70 1]  
`elasticsearch_mapping.json`文件内容

{
        
      "block": {
        
        "properties": {
        
          "userName": {
        
            "type": "text",
            "analyzer": "pinyin_analyzer",
            "search_analyzer": "pinyin_analyzer",
            "fields": {
        
              "pinyin": {
        
                "type": "string",
                "ignore_above": 256
              }
            }
          },
          "sex": {
        
            "type": "keyword",
            "fields": {
        
              "keyword": {
        
                "type": "keyword",
                "ignore_above": 256
              }
            }
          },
          "age": {
        
            "type": "keyword",
            "fields": {
        
              "keyword": {
        
                "type": "keyword",
                "ignore_above": 256
              }
            }
          }
        }
      }
    }

`elasticsearch_setting.json`文件内容

{
        
      "index": {
        
        "analysis": {
        
          "analyzer": {
        
            "pinyin_analyzer": {
        
              "tokenizer": "my_pinyin"
            }
          },
          "tokenizer": {
        
            "my_pinyin": {
        
              "type": "pinyin",
              "keep_first_letter": true,
              "keep_separate_first_letter": false,
              "keep_full_pinyin": true,
              "keep_original": true,
              "limit_first_letter_length": 16,
              "lowercase": true,
              "remove_duplicated_term": true
            }
          }
        }
      }
    }

#### 将setting和mapping配置到UserEntity中 ####

如果之前已经创建了索引了，则需要删除，或者重新创建新的所有才能创建分词和拼音相关索引，支持分词和拼音搜索

import org.springframework.data.annotation.Id;
    import org.springframework.data.elasticsearch.annotations.Document;
    import org.springframework.data.elasticsearch.annotations.Field;
    import org.springframework.data.elasticsearch.annotations.FieldType;
    import org.springframework.data.elasticsearch.annotations.Mapping;
    import org.springframework.data.elasticsearch.annotations.Setting;
    
    import lombok.AllArgsConstructor;
    import lombok.Builder;
    import lombok.Data;
    import lombok.NoArgsConstructor;
    
    @Data
    @NoArgsConstructor
    @AllArgsConstructor
    @Builder
    @Setting(settingPath = "classpath:elasticsearch/elasticsearch_setting.json")
    @Mapping(mappingPath = "classpath:elasticsearch/elasticsearch_mapping.json")
    @Document(indexName = "user")
    public class UserEntity {
        
    
        @Id
        private Long userId;
    
        @Field(type = FieldType.Text, analyzer = "pinyin", searchAnalyzer = "pinyin")
        private String userName;
    
        @Field(type = FieldType.Keyword)
        private Integer age;
    
        @Field(type = FieldType.Keyword)
        private Integer sex;
    
    }

#### 编写测试类 ####

依旧是在之前的测试类基础上进行编写，首先执行save方法批量插入一些数据方便测试，然后执行`searchByUserName`查看结果。

import com.example.elasticsearch.entity.UserEntity;
    import com.example.elasticsearch.service.ElasticSearchService;
    import com.example.elasticsearch.util.StringUtils;
    
    import org.junit.jupiter.api.Test;
    import org.springframework.boot.test.context.SpringBootTest;
    
    import java.util.ArrayList;
    import java.util.List;
    import java.util.concurrent.ThreadLocalRandom;
    
    import javax.annotation.Resource;
    
    @SpringBootTest
    class ElasticsearchApplicationTests {
        
    
        @Resource
        private ElasticSearchService elasticSearchService;
    
    	/**
         * @Author David
         * @Description 批量插入测试数据
         **/
        @Test
        void save() {
        
            List<String> randomName = StringUtils.getRandomName(100);
            List<UserEntity> list = new ArrayList<>(100);
            for (int i = 0; i < randomName.size(); i++) {
        
                UserEntity userEntity = UserEntity.builder()
                        .userId(i + 1L).userName(randomName.get(i)).age(ThreadLocalRandom.current().nextInt(50))
                        .sex(ThreadLocalRandom.current().nextInt(2))
                        .build();
                list.add(userEntity);
            }
            elasticSearchService.saveUser(list);
        }
    	
    	/**
         * @Author David
         * @Description 根据id搜索
         **/
        @Test
        void findById() {
        
            UserEntity byId = elasticSearchService.findById(1L);
            System.out.println(byId);
        }
    
    	/**
         * @Author David
         * @Description 搜索
         **/
        @Test
        void searchByUserName() {
        
            List<UserEntity> da = elasticSearchService.searchByUserName("wpt");
            System.out.println(da);
            List<UserEntity> da1 = elasticSearchService.searchByUserName("闻平涂");
            System.out.println(da1);
        }
    
    }
    // searchByUserName output
    [UserEntity(userId=7, userName=闻平涂, age=44, sex=1)]
    [UserEntity(userId=7, userName=闻平涂, age=44, sex=1)]

### 总结 ###

ElasticSearch使用非常广泛，支持的场景也非常多，除了分词和拼音之外，还有像繁体搜索，以及高亮显示都用的比较多，后面一一梳理，如果对你有帮助记得关注支持一下哦，这是我前进的最大动力！

[Spring Boot_docker_ElasticSearch]: https://blog.csdn.net/Davids_/article/details/107149096
[ik]: https://img-blog.csdnimg.cn/20200706181415105.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0Rhdmlkc18=,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0Rhdmlkc18_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/20200706181249359.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0Rhdmlkc18=,size_16,color_FFFFFF,t_70
[plugins]: https://img-blog.csdnimg.cn/20200706181513368.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0Rhdmlkc18_size_16_color_FFFFFF_t_70 1]: https://img-blog.csdnimg.cn/20200706182131277.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0Rhdmlkc18=,size_16,color_FFFFFF,t_70