springboot整合elasticsearch+ik分词器+kibana

Bertha 。 2022-11-26 06:50 625阅读 0赞

# SpringBoot整合Elasticsearch+IK+Kibana #

ElasticSearch是一个基于Lucene的搜索服务器。它提供了一个分布式多用户能力的全文搜索引擎，基于RESTful web接口。

Elasticsearch是用Java开发的，并作为Apache许可条款下的开放源码发布，是当前流行的企业级搜索引擎。设计用于云计算中，能够达到实时搜索，稳定，可靠，快速，安装使用方便。

**安装相关软件**

<table> 
 <thead> 
  <tr> 
   <th>软件名称</th> 
   <th>软件版本</th> 
   <th>下载地址</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>Elasticsearch</td> 
   <td>6.2.4</td> 
   <td><a href="https://www.elastic.co/cn/downloads/past-releases" rel="nofollow">elasticsearch官网下载</a></td> 
  </tr> 
  <tr> 
   <td>IK中文分词器</td> 
   <td>6.2.4</td> 
   <td><a href="https://github.com/medcl/elasticsearch-analysis-ik/releases" rel="nofollow">ik分词器官网下载</a></td> 
  </tr> 
  <tr> 
   <td>kibana</td> 
   <td>6.2.4</td> 
   <td><a href="https://www.elastic.co/cn/downloads/kibana" rel="nofollow">kibana官网下载</a></td> 
  </tr> 
 </tbody> 
</table>

## 1，安装Elasticsearch ##

![img][]

安装教程百度一搜一大把，这里就不作详细解释，只说明如下几点

*  修改jvm.options的内存分配参数，否则容易造成内存不足的启动失败问题
 *  修改elasticsearch.yml配置文件，修改地址，端口，节点名称等信息

注意：elasticsearch自带jdk，注意Linux环境中的jdk和自带的jdk冲突！

安装完成之后启动es，默认启动端口为9200

./bin/elasticsearch

./bin/elasticsearch -d  # 后台运行

浏览器访问： http://ip:9200/ 会得到相应的版本信息，如

{ 
    	"name": "Bb-td48",
    	"cluster_name": "elasticsearch",
    	"cluster_uuid": "_IM0iQAeToWALU0tq7rsZQ",
    	"version": { 
    	"number": "6.2.4",
    	"build_hash": "ccec39f",
    	"build_date": "2018-04-12T20:37:28.497551Z",
    	"build_snapshot": false,
    	"lucene_version": "7.2.1",
    	"minimum_wire_compatibility_version": "5.6.0",
    	"minimum_index_compatibility_version": "5.0.0"
    	},
    	"tagline": "You Know, for Search"
    }

## 2，ES安装IK分词器 ##

为什么要在elasticsearch中要使用ik这样的中文分词呢，那是因为es提供的分词是英文分词，对于中文的分词就做的非常不好了，因此我们需要一个中文分词器来用于搜索和使用。今天我们就尝试安装下IK分词。

1、去github 下载对应的分词插件，根据不同版本下载不同的分词插件

https://github.com/medcl/elasticsearch-analysis-ik/releases

2、到es的plugins 目录创建文件夹

cd your-es-root/plugins/ && mkdir ik

3、解压ik分词插件到ik文件夹

unzip elasticsearch-analysis-ik-6.4.3.zip

然后重新启动ES，就可以看到分词器已经自动被加载了  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80NDAwMTk2NQ_size_16_color_FFFFFF_t_70]

## 3，ES安装Kibana（可视化工具） ##

Kibana可以到官网去下载，不过网速都是特别感人，这里提供一个华为云镜像地址，下载速度嗖嗖的！

https://mirrors.huaweicloud.com/kibana/

里面有所有版本的Kibana提供下载！

解压

tar -zxvf kibana-6.3.2-linux-x86_64.tar.gz

修改配置文件

vim config/kibana.yml

# 放开注释,将默认配置改成如下：
    server.port: 5601
    server.host: "0.0.0.0"
    elasticsearch.url: "http://192.168.202.128:9200"
    kibana.index: ".kibana"

启动

bin/kibana

启动失败 报错如下

![在这里插入图片描述][20200810173017905.png]

这个很明显是没有权限,一次切换root用户 给es用户这个文件的权限

chown -R 用户名:用户名 /usr/local/elasticsearch/kibana/kibana-7.8.0/

但是下面的警告出事了，这里并不是找不到啥导致报错，而是服务器内存不足造成的，所以，我选择放弃！

相信不用kibana照样玩转elasticsearch！

## 4，springboot工程集成elasticsearch ##

### （1）整合maven依赖 ###

<dependency>
          <groupId>org.springframework.boot</groupId>
          <artifactId>spring-boot-starter-data-elasticsearch</artifactId>
    </dependency>
         还有lombok，自己加一下

上面的是整合依赖，由于测试等原因，加上其他的依赖

<dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-data-elasticsearch</artifactId>
            </dependency>
            <dependency>
                <groupId>org.projectlombok</groupId>
                <artifactId>lombok</artifactId>
            </dependency>
            <dependency>
                <groupId>junit</groupId>
                <artifactId>junit</artifactId>
            </dependency>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-test</artifactId>
            </dependency>
            
            <dependency>
                <groupId>commons-beanutils</groupId>
                <artifactId>commons-beanutils</artifactId>
                <version>1.9.3</version>
            </dependency>

### （2）application.yml ###

spring:
      data:
        elasticsearch:
          cluster-name: my-application
          cluster-nodes: 101.201.101.206:9300

### （3）实体类 ###

@Data
    @AllArgsConstructor
    @NoArgsConstructor
    @Document(indexName = "item", type = "docs", shards = 1, replicas = 0)
    public class Item { 
        @Id
        private Long id;
    
        @Field(type = FieldType.Text, analyzer = "ik_max_word")
        private String title; //标题
    
        @Field(type = FieldType.Keyword)
        private String category;// 分类
    
        @Field(type = FieldType.Keyword)
        private String brand; // 品牌
    
        @Field(type = FieldType.Double)
        private Double price; // 价格
    
        @Field(index = false, type = FieldType.Keyword)
        private String images; // 图片地址
    }

Spring Data通过注解来声明字段的映射属性，有下面的三个注解：

*  @Document
    
    作用在类，标记实体类为文档对象，一般有两个属性
    
     *  indexName：对应索引库名称
     *  type：对应在索引库中的类型
     *  shards：分片数量，默认5
     *  replicas：副本数量，默认1
 *  `@Id` 作用在成员变量，标记一个字段作为id主键
 *  @Field
    
    作用在成员变量，标记为文档的字段，并指定字段映射属性：
    
     *  type：字段类型，是是枚举：FieldType
     *  index：是否索引，布尔类型，默认是true
     *  store：是否存储，布尔类型，默认是false
     *  analyzer：分词器名称

### （4）repository ###

需要提供一个repository仓库

public interface ItemRepository extends ElasticsearchRepository<Item, Long> { 
    
        /** * 根据价格区间查询 * * @param price1 * @param price2 * @return */
        List<Item> findByPriceBetween(double price1, double price2);
    }

### （5）测试 ###

这里对elasticsearch做增删改查！

@RunWith(SpringRunner.class)
    @SpringBootTest
    public class SpringbootElasticsearchApplicationTests { 
    
        @Autowired
        private ElasticsearchTemplate elasticsearchTemplate;
    
        @Autowired
        private ItemRepository itemRepository;
    
        /** * 创建索引 */
        @Test
        public void createIndex() { 
            // 创建索引，会根据Item类的@Document注解信息来创建
            elasticsearchTemplate.createIndex(Item.class);
            // 配置映射，会根据Item类中的id、Field等字段来自动完成映射
            elasticsearchTemplate.putMapping(Item.class);
        }
    
        /** * 删除索引 */
        @Test
        public void deleteIndex() { 
            elasticsearchTemplate.deleteIndex("item");
        }
    
        /** * 新增 */
        @Test
        public void insert() { 
            Item item = new Item(1L, "小米手机7", "手机", "小米", 2999.00, "https://img12.360buyimg.com/n1/s450x450_jfs/t1/14081/40/4987/124705/5c371b20E53786645/c1f49cd69e6c7e6a.jpg");
            itemRepository.save(item);
        }
    
        /** * 批量新增 */
        @Test
        public void insertList() { 
            List<Item> list = new ArrayList<>();
            list.add(new Item(2L, "坚果手机R1", "手机", "锤子", 3999.00, "https://img12.360buyimg.com/n1/s450x450_jfs/t1/14081/40/4987/124705/5c371b20E53786645/c1f49cd69e6c7e6a.jpg"));
            list.add(new Item(3L, "华为META20", "手机", "华为", 4999.00, "https://img12.360buyimg.com/n1/s450x450_jfs/t1/14081/40/4987/124705/5c371b20E53786645/c1f49cd69e6c7e6a.jpg"));
            list.add(new Item(4L, "iPhone X", "手机", "iPhone", 5100.00, "https://img12.360buyimg.com/n1/s450x450_jfs/t1/14081/40/4987/124705/5c371b20E53786645/c1f49cd69e6c7e6a.jpg"));
            list.add(new Item(5L, "iPhone XS", "手机", "iPhone", 5999.00, "https://img12.360buyimg.com/n1/s450x450_jfs/t1/14081/40/4987/124705/5c371b20E53786645/c1f49cd69e6c7e6a.jpg"));
            // 接收对象集合，实现批量新增
            itemRepository.saveAll(list);
        }
    
        /** * 修改 * * ：修改和新增是同一个接口，区分的依据就是id，这一点跟我们在页面发起PUT请求是类似的。 */
    
        /** * 删除所有 */
        @Test
        public void delete() { 
            itemRepository.deleteAll();
        }
    
        /** * 基本查询 */
        @Test
        public void query() { 
            // 查询全部，并按照价格降序排序
            Iterable<Item> items = itemRepository.findAll(Sort.by("price").descending());
            items.forEach(item -> System.out.println("item = " + item));
        }
    
        /** * 自定义方法 */
        @Test
        public void queryByPriceBetween() { 
            // 根据价格区间查询
            List<Item> list = itemRepository.findByPriceBetween(5000.00, 6000.00);
            list.forEach(item -> System.out.println("item = " + item));
        }
    
        /** * 自定义查询 */
        @Test
        public void search() { 
            // 构建查询条件
            NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
            // 添加基本分词查询
            queryBuilder.withQuery(QueryBuilders.matchQuery("title", "小米手机"));
            // 搜索，获取结果
            Page<Item> items = itemRepository.search(queryBuilder.build());
            // 总条数
            long total = items.getTotalElements();
            System.out.println("total = " + total);
            items.forEach(item -> System.out.println("item = " + item));
        }
    
        /** * 分页查询 */
        @Test
        public void searchByPage() { 
            // 构建查询条件
            NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
            // 添加基本分词查询
            queryBuilder.withQuery(QueryBuilders.termQuery("category", "手机"));
            // 分页：
            int page = 0;
            int size = 2;
            queryBuilder.withPageable(PageRequest.of(page, size));
            // 搜索，获取结果
            Page<Item> items = itemRepository.search(queryBuilder.build());
            long total = items.getTotalElements();
            System.out.println("总条数 = " + total);
            System.out.println("总页数 = " + items.getTotalPages());
            System.out.println("当前页：" + items.getNumber());
            System.out.println("每页大小：" + items.getSize());
            items.forEach(item -> System.out.println("item = " + item));
        }
    
        /** * 排序 */
        @Test
        public void searchAndSort() { 
            // 构建查询条件
            NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
            // 添加基本分词查询
            queryBuilder.withQuery(QueryBuilders.termQuery("category", "手机"));
            // 排序
            queryBuilder.withSort(SortBuilders.fieldSort("price").order(SortOrder.ASC));
            // 搜索，获取结果
            Page<Item> items = this.itemRepository.search(queryBuilder.build());
            // 总条数
            long total = items.getTotalElements();
            System.out.println("总条数 = " + total);
            items.forEach(item -> System.out.println("item = " + item));
        }
    
        /** * 聚合为桶 */
        @Test
        public void testAgg() { 
            NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
            // 不查询任何结果
            queryBuilder.withSourceFilter(new FetchSourceFilter(new String[]{ ""}, null));
            // 1、添加一个新的聚合，聚合类型为terms，聚合名称为brands，聚合字段为brand
            queryBuilder.addAggregation(AggregationBuilders.terms("brands").field("brand"));
            // 2、查询,需要把结果强转为AggregatedPage类型
            AggregatedPage<Item> aggPage = (AggregatedPage<Item>) itemRepository.search(queryBuilder.build());
            // 3、解析
            // 3.1、从结果中取出名为brands的那个聚合，
            // 因为是利用String类型字段来进行的term聚合，所以结果要强转为StringTerm类型
            StringTerms agg = (StringTerms) aggPage.getAggregation("brands");
            // 3.2、获取桶
            List<StringTerms.Bucket> buckets = agg.getBuckets();
            // 3.3、遍历
            for (StringTerms.Bucket bucket : buckets) { 
                // 3.4、获取桶中的key，即品牌名称
                System.out.println(bucket.getKeyAsString());
                // 3.5、获取桶中的文档数量
                System.out.println(bucket.getDocCount());
            }
        }
    
        /** * 嵌套聚合，求平均值 */
        @Test
        public void testSubAgg() { 
            NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
            // 不查询任何结果
            queryBuilder.withSourceFilter(new FetchSourceFilter(new String[]{ ""}, null));
            // 1、添加一个新的聚合，聚合类型为terms，聚合名称为brands，聚合字段为brand
            queryBuilder.addAggregation(
                    AggregationBuilders.terms("brands").field("brand")
                            .subAggregation(AggregationBuilders.avg("priceAvg").field("price")) // 在品牌聚合桶内进行嵌套聚合，求平均值
            );
            // 2、查询,需要把结果强转为AggregatedPage类型
            AggregatedPage<Item> aggPage = (AggregatedPage<Item>) this.itemRepository.search(queryBuilder.build());
            // 3、解析
            // 3.1、从结果中取出名为brands的那个聚合，
            // 因为是利用String类型字段来进行的term聚合，所以结果要强转为StringTerm类型
            StringTerms agg = (StringTerms) aggPage.getAggregation("brands");
            // 3.2、获取桶
            List<StringTerms.Bucket> buckets = agg.getBuckets();
            // 3.3、遍历
            for (StringTerms.Bucket bucket : buckets) { 
                // 3.4、获取桶中的key，即品牌名称 3.5、获取桶中的文档数量
                System.out.println(bucket.getKeyAsString() + "，共" + bucket.getDocCount() + "台");
    
                // 3.6.获取子聚合结果：
                InternalAvg avg = (InternalAvg) bucket.getAggregations().asMap().get("priceAvg");
                System.out.println("平均售价：" + avg.getValue());
            }
        }
    }

### （6）搜索分词高亮显示 ###

下面是测试类中的一个查询方法，并进行高亮显示

@org.junit.Test
        public void search() { 
            // 构建查询条件
            NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
            // 添加基本分词查询
            queryBuilder.withQuery(QueryBuilders.matchQuery("title", "搜索引擎"));
    
            HighlightBuilder.Field hfield= new HighlightBuilder.Field("title")
                    .preTags("<em style='color:red'>")
                    .postTags("</em>")
                    .fragmentSize(100);
            queryBuilder.withHighlightFields(hfield);
    
            // 搜索，获取结果
            Page<Item> items = itemRepository.search(queryBuilder.build());
            // 总条数
            long total = items.getTotalElements();
            System.out.println("total = " + total);
            items.forEach(item -> System.out.println("item = " + item));
        }

但是没有效果，百度发现，这个版本的mapper实现类没有设置高亮显示的字段，改正后的结果

新建一个MyResultMapper ，继承AbstractResultMapper 并对其方法进行重写，结果如下

其中需要上面的BeanUtils的依赖！

package com.example.elasticsearch.springbootelasticsearch.repository;
     
    import com.fasterxml.jackson.core.JsonEncoding;
    import com.fasterxml.jackson.core.JsonFactory;
    import com.fasterxml.jackson.core.JsonGenerator;
    import org.apache.commons.beanutils.PropertyUtils;
    import org.elasticsearch.action.get.GetResponse;
    import org.elasticsearch.action.get.MultiGetItemResponse;
    import org.elasticsearch.action.get.MultiGetResponse;
    import org.elasticsearch.action.search.SearchResponse;
    import org.elasticsearch.common.document.DocumentField;
    import org.elasticsearch.common.text.Text;
    import org.elasticsearch.search.SearchHit;
    import org.elasticsearch.search.fetch.subphase.highlight.HighlightField;
    import org.springframework.data.domain.Pageable;
    import org.springframework.data.elasticsearch.ElasticsearchException;
    import org.springframework.data.elasticsearch.annotations.Document;
    import org.springframework.data.elasticsearch.annotations.ScriptedField;
    import org.springframework.data.elasticsearch.core.AbstractResultMapper;
    import org.springframework.data.elasticsearch.core.DefaultEntityMapper;
    import org.springframework.data.elasticsearch.core.EntityMapper;
    import org.springframework.data.elasticsearch.core.aggregation.AggregatedPage;
    import org.springframework.data.elasticsearch.core.aggregation.impl.AggregatedPageImpl;
    import org.springframework.data.elasticsearch.core.mapping.ElasticsearchPersistentEntity;
    import org.springframework.data.elasticsearch.core.mapping.ElasticsearchPersistentProperty;
    import org.springframework.data.elasticsearch.core.mapping.SimpleElasticsearchMappingContext;
    import org.springframework.data.mapping.context.MappingContext;
    import org.springframework.stereotype.Component;
    import org.springframework.util.Assert;
    import org.springframework.util.StringUtils;
     
    import java.io.ByteArrayOutputStream;
    import java.io.IOException;
    import java.lang.reflect.InvocationTargetException;
    import java.nio.charset.Charset;
    import java.util.*;
    
    @Component
    public class MyResultMapper extends AbstractResultMapper { 
     
    	private final MappingContext<? extends ElasticsearchPersistentEntity<?>, ElasticsearchPersistentProperty> mappingContext;
     
    	public MyResultMapper() { 
    		this(new SimpleElasticsearchMappingContext());
    	}
     
    	public MyResultMapper(MappingContext<? extends ElasticsearchPersistentEntity<?>, ElasticsearchPersistentProperty> mappingContext) { 
    		
    		super(new DefaultEntityMapper(mappingContext));
    		
    		Assert.notNull(mappingContext, "MappingContext must not be null!");
    		
    		this.mappingContext = mappingContext;
    	}
     
    	public MyResultMapper(EntityMapper entityMapper) { 
    		this(new SimpleElasticsearchMappingContext(), entityMapper);
    	}
     
    	public MyResultMapper(
    			MappingContext<? extends ElasticsearchPersistentEntity<?>, ElasticsearchPersistentProperty> mappingContext,
    			EntityMapper entityMapper) { 
    		
    		super(entityMapper);
    		
    		Assert.notNull(mappingContext, "MappingContext must not be null!");
    		
    		this.mappingContext = mappingContext;
    	}
     
    	@Override
    	public <T> AggregatedPage<T> mapResults(SearchResponse response, Class<T> clazz, Pageable pageable) { 
    		
    		long totalHits = response.getHits().getTotalHits();
    		float maxScore = response.getHits().getMaxScore();
     
    		List<T> results = new ArrayList<>();
    		for (SearchHit hit : response.getHits()) { 
    			if (hit != null) { 
    				T result = null;
    				if (!StringUtils.isEmpty(hit.getSourceAsString())) { 
    					result = mapEntity(hit.getSourceAsString(), clazz);
    				} else { 
    					result = mapEntity(hit.getFields().values(), clazz);
    				}
     
    				setPersistentEntityId(result, hit.getId(), clazz);
    				setPersistentEntityVersion(result, hit.getVersion(), clazz);
    				setPersistentEntityScore(result, hit.getScore(), clazz);
    				
    				populateScriptFields(result, hit);
     
                    results.add(result);
    			}
    		}
     
    		return new AggregatedPageImpl<T>(results, pageable, totalHits, response.getAggregations(), response.getScrollId(),
    				maxScore);
    	}
     
        private String concat(Text[] texts) { 
            StringBuilder sb = new StringBuilder();
            for (Text text : texts) { 
                sb.append(text.toString());
            }
            return sb.toString();
        }
     
     
    	private <T> void populateScriptFields(T result, SearchHit hit) { 
    		if (hit.getFields() != null && !hit.getFields().isEmpty() && result != null) { 
    			for (java.lang.reflect.Field field : result.getClass().getDeclaredFields()) { 
    				ScriptedField scriptedField = field.getAnnotation(ScriptedField.class);
    				if (scriptedField != null) { 
    					String name = scriptedField.name().isEmpty() ? field.getName() : scriptedField.name();
    					DocumentField searchHitField = hit.getFields().get(name);
    					if (searchHitField != null) { 
    						field.setAccessible(true);
    						try { 
    							field.set(result, searchHitField.getValue());
    						} catch (IllegalArgumentException e) { 
    							throw new ElasticsearchException(
    									"failed to set scripted field: " + name + " with value: " + searchHitField.getValue(), e);
    						} catch (IllegalAccessException e) { 
    							throw new ElasticsearchException("failed to access scripted field: " + name, e);
    						}
    					}
    				}
    			}
    		}
     
            for (HighlightField field : hit.getHighlightFields().values()) { 
                try { 
                    PropertyUtils.setProperty(result, field.getName(), concat(field.fragments()));
                } catch (InvocationTargetException | IllegalAccessException | NoSuchMethodException e) { 
                    throw new ElasticsearchException("failed to set highlighted value for field: " + field.getName()
                            + " with value: " + Arrays.toString(field.getFragments()), e);
                }
            }
    	}
     
    	private <T> T mapEntity(Collection<DocumentField> values, Class<T> clazz) { 
    		return mapEntity(buildJSONFromFields(values), clazz);
    	}
     
    	private String buildJSONFromFields(Collection<DocumentField> values) { 
    		JsonFactory nodeFactory = new JsonFactory();
    		try { 
    			ByteArrayOutputStream stream = new ByteArrayOutputStream();
    			JsonGenerator generator = nodeFactory.createGenerator(stream, JsonEncoding.UTF8);
    			generator.writeStartObject();
    			for (DocumentField value : values) { 
    				if (value.getValues().size() > 1) { 
    					generator.writeArrayFieldStart(value.getName());
    					for (Object val : value.getValues()) { 
    						generator.writeObject(val);
    					}
    					generator.writeEndArray();
    				} else { 
    					generator.writeObjectField(value.getName(), value.getValue());
    				}
    			}
    			generator.writeEndObject();
    			generator.flush();
    			return new String(stream.toByteArray(), Charset.forName("UTF-8"));
    		} catch (IOException e) { 
    			return null;
    		}
    	}
     
    	@Override
    	public <T> T mapResult(GetResponse response, Class<T> clazz) { 
    		T result = mapEntity(response.getSourceAsString(), clazz);
    		if (result != null) { 
    			setPersistentEntityId(result, response.getId(), clazz);
    			setPersistentEntityVersion(result, response.getVersion(), clazz);
    		}
    		return result;
    	}
     
    	@Override
    	public <T> LinkedList<T> mapResults(MultiGetResponse responses, Class<T> clazz) { 
    		LinkedList<T> list = new LinkedList<>();
    		for (MultiGetItemResponse response : responses.getResponses()) { 
    			if (!response.isFailed() && response.getResponse().isExists()) { 
    				T result = mapEntity(response.getResponse().getSourceAsString(), clazz);
    				setPersistentEntityId(result, response.getResponse().getId(), clazz);
    				setPersistentEntityVersion(result, response.getResponse().getVersion(), clazz);
    				list.add(result);
    			}
    		}
    		return list;
    	}
     
    	private <T> void setPersistentEntityId(T result, String id, Class<T> clazz) { 
    		
    		if (clazz.isAnnotationPresent(Document.class)) { 
    			
    			ElasticsearchPersistentEntity<?> persistentEntity = mappingContext.getRequiredPersistentEntity(clazz);
    			ElasticsearchPersistentProperty idProperty = persistentEntity.getIdProperty();
     
    			// Only deal with String because ES generated Ids are strings !
    			if (idProperty != null && idProperty.getType().isAssignableFrom(String.class)) { 
    				persistentEntity.getPropertyAccessor(result).setProperty(idProperty, id);
    			}
    		}
    	}
     
    	private <T> void setPersistentEntityVersion(T result, long version, Class<T> clazz) { 
    		
    		if (clazz.isAnnotationPresent(Document.class)) { 
    			
    			ElasticsearchPersistentEntity<?> persistentEntity = mappingContext.getPersistentEntity(clazz);
    			ElasticsearchPersistentProperty versionProperty = persistentEntity.getVersionProperty();
     
    			// Only deal with Long because ES versions are longs !
    			if (versionProperty != null && versionProperty.getType().isAssignableFrom(Long.class)) { 
    				// check that a version was actually returned in the response, -1 would indicate that
    				// a search didn't request the version ids in the response, which would be an issue
    				Assert.isTrue(version != -1, "Version in response is -1");
    				persistentEntity.getPropertyAccessor(result).setProperty(versionProperty, version);
    			}
    		}
    	}
     
    	private <T> void setPersistentEntityScore(T result, float score, Class<T> clazz) { 
     
    		if (clazz.isAnnotationPresent(Document.class)) { 
     
    			ElasticsearchPersistentEntity<?> entity = mappingContext.getRequiredPersistentEntity(clazz);
     
    			if (!entity.hasScoreProperty()) { 
    				return;
    			}
     
    			entity.getPropertyAccessor(result) //
    					.setProperty(entity.getScoreProperty(), score);
    		}
    	}
    }

然后再运行上面的自定义查询方法，控制台打印效果如下图  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80NDAwMTk2NQ_size_16_color_FFFFFF_t_70 1]

## 5，springboot+elasticsearch实战 ##

虎你呢，没了！再见！

上面的已经够用了，兄弟萌！

[img]: /images/20221124/9f27c8f8e2644243b6a835a6d3f9d103.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80NDAwMTk2NQ_size_16_color_FFFFFF_t_70]: /images/20221124/4747d9334d45463ca998e81f9adf3e8a.png
[20200810173017905.png]: /images/20221124/4f82ba281575439293c0eedf951ec41b.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80NDAwMTk2NQ_size_16_color_FFFFFF_t_70 1]: /images/20221124/6057d633aed24beb950285eecc52bc07.png