目录

一、初始MQ

同步调用

异步调用

什么是MQ

执行下面的命令来运行MQ容器：

如果冲突了，可以先查询

RabbitMQ概述 

常见消息模型

HelloWorld案例

二、SpringAMQP

引入依赖

Work Queue 

消费预取限制

​编辑 发布、订阅

发布订阅Fanout Exchange

发布DirectExchange

发布订阅TopicExchange 

消息转化器

MQ代码

三、什么是elasticsearch

 正向索引

倒排索引

文档

索引

概念对比

架构 

 ​编辑

部署单点es

1.2.加载镜像

1.3.运行

命令解释：

2.1.部署

 分词器

2.2.DevTools

kibana中提供了一个DevTools界面：

3.安装IK分词器

3.1.在线安装ik插件（较慢）

3.2.离线安装ik插件（推荐）

1）查看数据卷目录

2）解压缩分词器安装包

3）上传到es容器的插件数据卷中

4）重启容器

5）测试：

3.3 扩展词词典

四、索引库操作 

创建索引库

查看、删除索引库​编辑

修改索引库

 新增文档​编辑

 查看、删除文档​编辑

修改文档

RestClient操作索引库

索引库代码

RestClient操作文档

操作文档代码

DSL 查询文档

 DSL  Query的分类​编辑

DSL Query基本语法

 全文检索查询​编辑

 精确查询​编辑

 地理查询​编辑

相关性算分

 Function Score Query​编辑

复合查询 Boolean Query

 搜索结果处理​编辑

分页

深度分页问题

​编辑高亮 

RestClient查询文档

全文检索查询

精确查询 ​编辑

符合查询

排序和分页

 高亮​编辑

---

初始MQ

同步调用

异步调用

什么是MQ

执行下面的命令来运行MQ容器：

docker run \-e RABBITMQ_DEFAULT_USER=itcast \-e RABBITMQ_DEFAULT_PASS=123321 \--name mq \--hostname mq1 \-p 15672:15672 \-p 5672:5672 \-d \rabbitmq:3-management

如果冲突了，可以先查询

RabbitMQ概述 

常见消息模型

HelloWorld案例

 

SpringAMQP

 

引入依赖

 

Work Queue 

 

 

消费预取限制

 发布、订阅

发布订阅Fanout Exchange

发布DirectExchange

发布订阅TopicExchange 

 

 

消息转化器

MQ代码

@Component
public class SpringRabbitListener {//    @RabbitListener(queues = "simple.queue")
//    public void listenSimpleQueue(String msg){
//        System.out.println("消费者接收到simple.queue的消息:["+msg+"]");
//
//    }@RabbitListener(queues = "simple.queue")public void listenWorkQueue1(String msg) throws InterruptedException {System.out.println("消费者1接收到simple.queue的消息:["+msg+"]"+ LocalTime.now());Thread.sleep(20);}@RabbitListener(queues = "simple.queue")public void listenWorkQueue2(String msg) throws InterruptedException {System.err.println("消费者2接收到simple.queue的消息:["+msg+"]"+LocalTime.now());Thread.sleep(200);}@RabbitListener(queues = "fanout.queue1")public void listenFanoutQueue1(String msg){System.out.println("消费者接收到fanout.queue1的消息:["+msg+"]");}@RabbitListener(queues = "fanout.queue2")public void listenFanoutQueue2(String msg){System.out.println("消费者接收到fanout.queue2的消息:["+msg+"]");}@RabbitListener(bindings = @QueueBinding(value = @Queue(name = "direct.queue1"),exchange = @Exchange(name = "itcast.direct",type = ExchangeTypes.DIRECT),key = {"red","blue"}))public void listenDirectQueue1(String msg){System.out.println("消费者接收到direct.queue1的消息:["+msg+"]");}@RabbitListener(bindings = @QueueBinding(value = @Queue(name = "direct.queue2"),exchange = @Exchange(name = "itcast.direct",type = ExchangeTypes.DIRECT),key = {"red","yellow"}))public void listenDirectQueue2(String msg){System.out.println("消费者接收到direct.queue2的消息:["+msg+"]");}@RabbitListener(bindings = @QueueBinding(value = @Queue(name = "topic.queue1"),exchange = @Exchange(name = "itcast.topic",type = ExchangeTypes.TOPIC),key = "china.#"))public void listenTopicQueue1(String msg){System.out.println("消费者接收到topic.queue1的消息:["+msg+"]");}@RabbitListener(bindings = @QueueBinding(value = @Queue(name = "topic.queue2"),exchange = @Exchange(name = "itcast.topic",type = ExchangeTypes.TOPIC),key = "#.news"))public void listenTopicQueue2(String msg){System.out.println("消费者接收到topic.queue2的消息:["+msg+"]");}@RabbitListener(queues = "object.queue")public void listObjectQueue(Map<String,Object> msg){System.out.println("接收object.queue的消息："+msg);}
}

@Configuration
public class FanoutConfig {//声明FanoutExchange 交换机//itcast.fanout@Beanpublic FanoutExchange fanoutExchange(){return new FanoutExchange("itcast.fanout");}//声明一个队列fanout.queue1@Beanpublic Queue fanoutQueue1(){return new Queue("fanout.queue1");}//绑定队列1和交换机@Beanpublic Binding fanoutBinding1(Queue fanoutQueue1,FanoutExchange fanoutExchange){return BindingBuilder.bind(fanoutQueue1).to(fanoutExchange);}//fanout.queue2//声明一个队列fanout.queue1@Beanpublic Queue fanoutQueue2(){return new Queue("fanout.queue2");}//绑定队列1和交换机@Beanpublic Binding fanoutBinding2(Queue fanoutQueue2,FanoutExchange fanoutExchange){return BindingBuilder.bind(fanoutQueue2).to(fanoutExchange);}@Beanpublic Queue objectQueue(){return new Queue("object.queue");}}

@SpringBootApplication
public class ConsumerApplication {public static void main(String[] args) {SpringApplication.run(ConsumerApplication.class, args);}@Beanpublic MessageConverter messageConverter(){return new Jackson2JsonMessageConverter();}
}

public class PublisherTest {@Testpublic void testSendMessage() throws IOException, TimeoutException {// 1.建立连接ConnectionFactory factory = new ConnectionFactory();// 1.1.设置连接参数，分别是：主机名、端口号、vhost、用户名、密码factory.setHost("虚拟机地址");factory.setPort(5672);factory.setVirtualHost("/");factory.setUsername("itcast");factory.setPassword("123321");// 1.2.建立连接Connection connection = factory.newConnection();// 2.创建通道ChannelChannel channel = connection.createChannel();// 3.创建队列String queueName = "simple.queue";channel.queueDeclare(queueName, false, false, false, null);// 4.发送消息String message = "hello, rabbitmq!";channel.basicPublish("", queueName, null, message.getBytes());System.out.println("发送消息成功：【" + message + "】");// 5.关闭通道和连接channel.close();connection.close();}
}

@RunWith(SpringRunner.class)
@SpringBootTest
public class SpringAmqpTest {@Autowiredprivate RabbitTemplate rabbitTemplate;@Testpublic void testSendMessage2SimpleWueue(){String queueName = "simple.queue";String message = "hello,spring amqp!!!";rabbitTemplate.convertAndSend(queueName,message);}@Testpublic void testSendMessage2WorkQueue() throws InterruptedException {String queueName = "simple.queue";String message = "hello,message__";for ( int i = 1; i <= 50; i++ ) {rabbitTemplate.convertAndSend(queueName,message+i);Thread.sleep(20);}}@Testpublic void testSendFanoutExchange(){//交换机名称String exchangeName = "itcast.fanout";//消息String message = "hello,every one !";//发送消息rabbitTemplate.convertAndSend(exchangeName,"",message);}@Testpublic void testSendDirectExchange(){//交换机名称String exchangeName = "itcast.direct";//消息String message = "hello,blue !";//发送消息rabbitTemplate.convertAndSend(exchangeName,"red",message);}@Testpublic void testSendTopicExchange(){//交换机名称String exchangeName = "itcast.topic";//消息String message = "中国NO.1";//发送消息rabbitTemplate.convertAndSend(exchangeName,"chi.weather",message);}@Testpublic void testSendObjectExchange(){HashMap<String, Object> msg = new HashMap<>();msg.put("name","留言2");msg.put("age",21);//发送消息rabbitTemplate.convertAndSend("object.queue",msg);}}

什么是elasticsearch

 

 

 正向索引

倒排索引

 

文档

索引

概念对比

架构 

 

 

部署单点es

因为我们还需要部署kibana容器，因此需要让es和kibana容器互联。这里先创建一个网络：

docker network create es-net

1.2.加载镜像

这里我们采用elasticsearch的7.12.1版本的镜像，这个镜像体积非常大，接近1G。不建议大家自己pull。

课前资料提供了镜像的tar包：

 大家将其上传到虚拟机中，然后运行命令加载即可：

# 导入数据
docker load -i es.tar

同理还有kibana的tar包也需要这样做。

1.3.运行

运行docker命令，部署单点es：

docker run -d \--name es \-e "ES_JAVA_OPTS=-Xms512m -Xmx512m" \-e "discovery.type=single-node" \-v es-data:/usr/share/elasticsearch/data \-v es-plugins:/usr/share/elasticsearch/plugins \--privileged \--network es-net \-p 9200:9200 \-p 9300:9300 \
elasticsearch:7.12.1

命令解释：

• -e "cluster.name=es-docker-cluster"：设置集群名称

• -e "http.host=0.0.0.0"：监听的地址，可以外网访问

• -e "ES_JAVA_OPTS=-Xms512m -Xmx512m"：内存大小

• -e "discovery.type=single-node"：非集群模式

• -v es-data:/usr/share/elasticsearch/data：挂载逻辑卷，绑定es的数据目录

• -v es-logs:/usr/share/elasticsearch/logs：挂载逻辑卷，绑定es的日志目录

• -v es-plugins:/usr/share/elasticsearch/plugins：挂载逻辑卷，绑定es的插件目录

• --privileged：授予逻辑卷访问权

• --network es-net ：加入一个名为es-net的网络中

• -p 9200:9200：端口映射配置

在浏览器中输入：http://192.168.150.101:9200 即可看到elasticsearch的响应结果：

 kibana可以给我们提供一个elasticsearch的可视化界面，便于我们学习。

2.1.部署

运行docker命令，部署kibana(版本一定要一样）

docker run -d \
--name kibana \
-e ELASTICSEARCH_HOSTS=http://es:9200 \
--network=es-net \
-p 5601:5601  \
kibana:7.12.1

• --network es-net ：加入一个名为es-net的网络中，与elasticsearch在同一个网络中

• -e ELASTICSEARCH_HOSTS=http://es:9200"：设置elasticsearch的地址，因为kibana已经与elasticsearch在一个网络，因此可以用容器名直接访问elasticsearch

• -p 5601:5601：端口映射配置

kibana启动一般比较慢，需要多等待一会，可以通过命令：

docker logs -f kibana

查看运行日志，当查看到下面的日志，说明成功：

 分词器

2.2.DevTools

kibana中提供了一个DevTools界面：

 这个界面中可以编写DSL来操作elasticsearch。并且对DSL语句有自动补全功能。

3.安装IK分词器

3.1.在线安装ik插件（较慢）

# 进入容器内部
docker exec -it elasticsearch /bin/bash# 在线下载并安装
./bin/elasticsearch-plugin  install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.12.1/elasticsearch-analysis-ik-7.12.1.zip#退出
exit
#重启容器
docker restart elasticsearch

3.2.离线安装ik插件（推荐）

1）查看数据卷目录

安装插件需要知道elasticsearch的plugins目录位置，而我们用了数据卷挂载，因此需要查看elasticsearch的数据卷目录，通过下面命令查看:

docker volume inspect es-plugins

显示结果：

[{"CreatedAt": "2022-05-06T10:06:34+08:00","Driver": "local","Labels": null,"Mountpoint": "/var/lib/docker/volumes/es-plugins/_data","Name": "es-plugins","Options": null,"Scope": "local"}
]

说明plugins目录被挂载到了：/var/lib/docker/volumes/es-plugins/_data这个目录中。

2）解压缩分词器安装包

下面我们需要把课前资料中的ik分词器解压缩，重命名为ik

3）上传到es容器的插件数据卷中

4）重启容器

# 4、重启容器
docker restart es
# 查看es日志
docker logs -f es

5）测试：

IK分词器包含两种模式：

• ik_smart：最少切分

• ik_max_word：最细切分

GET /_analyze
{"analyzer": "ik_max_word","text": "我爱学习java太棒了"
}

结果：

{"tokens" : [{"token" : "我","start_offset" : 0,"end_offset" : 1,"type" : "CN_CHAR","position" : 0},{"token" : "爱学习","start_offset" : 1,"end_offset" : 4,"type" : "CN_WORD","position" : 1},{"token" : "学习","start_offset" : 2,"end_offset" : 4,"type" : "CN_WORD","position" : 2},{"token" : "java","start_offset" : 4,"end_offset" : 8,"type" : "ENGLISH","position" : 3},{"token" : "太棒了","start_offset" : 8,"end_offset" : 11,"type" : "CN_WORD","position" : 4},{"token" : "太棒","start_offset" : 8,"end_offset" : 10,"type" : "CN_WORD","position" : 5},{"token" : "了","start_offset" : 10,"end_offset" : 11,"type" : "CN_CHAR","position" : 6}]
}

3.3 扩展词词典

随着互联网的发展，“造词运动”也越发的频繁。出现了很多新的词语，在原有的词汇列表中并不存在。比如：“奥力给”，“传智播客” 等。

所以我们的词汇也需要不断的更新，IK分词器提供了扩展词汇的功能。

1）打开IK分词器config目录：

 2）在IKAnalyzer.cfg.xml配置文件内容添加：

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd">
<properties><comment>IK Analyzer 扩展配置</comment><!--用户可以在这里配置自己的扩展字典 *** 添加扩展词典--><entry key="ext_dict">ext.dic</entry>
</properties>

索引库操作 

创建索引库

#创建索引库
PUT /heihei
{"mappings": {"properties": {"info": {"type": "text","analyzer": "ik_smart"},"email": {"type": "keyword","index": false},"name": {"type": "object","properties": {"firstName": {"type": "keyword"},"lastName": {"type": "keyword"}}}}}
}

查看、删除索引库

 

修改索引库

 

 

 

 新增文档

 查看、删除文档

修改文档

 

RestClient操作索引库

 

 

#酒店的mapping
PUT /hotel
{"mappings": {"properties": {"id":{"type": "keyword"},"name":{"type": "text","analyzer": "ik_max_word"},"adress":{"type": "keyword","index": false},"price":{"type": "integer"},"score":{"type": "integer"},"brand":{"type": "keyword"},"city":{"type": "keyword"},"starName":{"type": "keyword"},"business":{"type": "keyword"},"location":{"type": "geo_point"},"pic":{"type": "keyword","index": false}}}
}

索引库代码

public class HotelIndexTest {private RestHighLevelClient client;@Testvoid testInit(){System.out.println(client);}@Testvoid createHotelIndex() throws IOException {//1.创建Request对象CreateIndexRequest request = new CreateIndexRequest("hotel");//2.准备请求的参数，DSL语句request.source(MAPPTING_TEMPLATE, XContentType.JSON);//3.发送请求client.indices().create(request, RequestOptions.DEFAULT);}@Testvoid deleteHotelIndex() throws IOException {//1.创建Request对象DeleteIndexRequest request = new DeleteIndexRequest("hotel");//3.发送请求client.indices().delete(request, RequestOptions.DEFAULT);}@Testvoid testExistHotelIndex() throws IOException {//1.创建Request对象GetIndexRequest request = new GetIndexRequest("hotel");boolean exists = client.indices().exists(request, RequestOptions.DEFAULT);//3.发送请求System.err.println(exists ? "索引库已经存在" : "索引库不存在！");}@BeforeEachvoid setUp(){this.client = new RestHighLevelClient(RestClient.builder(HttpHost.create("http://虚拟机地址:es端口号")));}@AfterEachvoid tearDown()throws IOException{this.client.close();}
}

RestClient操作文档

 

 

 

操作文档代码

@SpringBootTest
public class HotelDocumentTest {@Autowiredprivate IHotelService hotelService;private RestHighLevelClient client;@Testvoid testAddDcoument() throws IOException {//根据id查询酒店数据Hotel hotel = hotelService.getById(36934L);//转化为文档类型HotelDoc hotelDoc = new HotelDoc(hotel);//1.准备Request对象IndexRequest request = new IndexRequest("hotel").id(hotel.getId().toString());//2.准备Json文件request.source(JSON.toJSONString(hotelDoc),XContentType.JSON);client.index(request,RequestOptions.DEFAULT);//3.发送请求}@Testvoid testGetDocumentById() throws IOException {//1.准备RequestGetRequest request = new GetRequest("hotel", "36934");//2.发送请求，得到响应GetResponse response = client.get(request, RequestOptions.DEFAULT);//3.解析响应结果String json = response.getSourceAsString();HotelDoc hotelDoc = JSON.parseObject(json, HotelDoc.class);System.out.println(hotelDoc);}@Testvoid testRulkRequest() throws IOException {//批量查询酒店数据List<Hotel> hotels = hotelService.list();//1.创建RequestBulkRequest request = new BulkRequest();//2.准备参数，添加多个新增的Requestfor ( Hotel hotel : hotels ) {//转换为文档类型HotelDocHotelDoc hotelDoc = new HotelDoc(hotel);//2.准备参数，添加多个新增的Requestrequest.add(new IndexRequest("hotel").id(hotel.getId().toString()).source(JSON.toJSONString(hotelDoc),XContentType.JSON));}//3.发送请求client.bulk(request,RequestOptions.DEFAULT);}@Testvoid testUpdateDocumentById() throws IOException {//1.准备RequestUpdateRequest request = new UpdateRequest("hotel", "36934");//2.准备请求参数request.doc("price","952","starName","五钻");//2.发送请求，得到响应client.update(request, RequestOptions.DEFAULT);//3.解析响应结果}@Testvoid testDeleteDocumentById() throws IOException {List<Hotel> list = hotelService.list();//循环删除for ( Hotel hotel : list ) {//1.准备RequestDeleteRequest request = new DeleteRequest("hotel", hotel.getId().toString());//2.发送请求，得到响应client.delete(request, RequestOptions.DEFAULT);}//1.准备RequestDeleteRequest request = new DeleteRequest("hotel", "36934");//2.发送请求，得到响应client.delete(request, RequestOptions.DEFAULT);}@BeforeEachvoid setUp(){this.client = new RestHighLevelClient(RestClient.builder(HttpHost.create("http://虚机机地址:es端口")));}@AfterEachvoid tearDown()throws IOException{this.client.close();}
}

DSL 查询文档

 

 DSL  Query的分类

DSL Query基本语法

 全文检索查询

GET /hotel/_doc/36934#查询所有
GET /hotel/_search
{"query": {"match_all": {}}
}#math查询
GET /hotel/_search
{"query": {"match": {"all": "外滩如家"}}
}#multi_math查询
GET /hotel/_search
{"query": {"multi_match": {"query": "外滩如家","fields": ["brand","name","business"]}}
}

 精确查询

 

#term查询
GET /hotel/_search
{"query": {"term": {"city": {"value": "上海"}}}
}#range查询 几个e代表等于
GET /hotel/_search
{"query": {"range": {"price": {"gte": 1000,"lte": 3000}}}
}

 地理查询

 

 

#distance查询
GET /hotel/_search
{"query": {"geo_distance": {"distance":"3km","location":"31.219306, 121.445427"}}
}

相关性算分

 

 Function Score Query

#function score 查询
GET /hotel/_search
{"query": {"function_score": {"query": {"match": {"all": "外滩"}},"functions": [{"filter":{"term":{"brand":"7天酒店"}},"weight":10}],"boost_mode":"sum"}}}}
}

 

复合查询 Boolean Query

 

GET /hotel/_search
{"query": {"bool": {"must": [{"match": {"name": "如家"}}],"must_not": [{"range": {"price": {"gt": 400}}}],"filter": [{"geo_distance": {"distance": "10km","location": {"lat": 31.21,"lon": 121.5}}}]}}
}

 搜索结果处理

排序

#sort排序
GET /hotel/_search
{"query": {"match_all": {}},"sort": [{"score": "desc"},{"price": "asc" }]
}#找到121.6122，31.034周围的酒店，距离升序排序
GET /hotel/_search
{"query": {"match_all": {}},"sort": [{"_geo_distance": {"location": {"lat": 31.034,"lon": 121.6122},"order": "asc","unit": "km"}}]
}

分页

深度分页问题

 

高亮 

 

#分页查询
GET /hotel/_search
{"query": {"match_all": {}},"sort": [{"price": "asc" }],"from":10,"size":10
}#高亮显示 默认情况，ES搜索字段必须与高亮字段一致
GET /hotel/_search
{"query": {"match": {"all": "如家"}},"highlight": {"fields": {"name":{"require_field_match": "false"}}}
}

RestClient查询文档

 

 

 

 

全文检索查询

 

精确查询 

符合查询

排序和分页

 ​​​​​​​高亮

 ​​​​​​​

觉得好的小伙伴记得一键三连哦

public class HotelIsearchTest {private RestHighLevelClient client;@Testvoid testMatchAll() throws IOException {//1 准备RequestSearchRequest request = new SearchRequest("hotel");//2.准备DSLrequest.source().query(QueryBuilders.matchAllQuery());//3.发送请求SearchResponse response = client.search(request, RequestOptions.DEFAULT);//4解析响应handleRequest(response);}/*** 全文检索查询* @throws IOException*/@Testvoid testMatch() throws IOException {//1 准备RequestSearchRequest request = new SearchRequest("hotel");//2.准备DSLrequest.source().query(QueryBuilders.matchQuery("all","如家"));//3.发送请求SearchResponse response = client.search(request, RequestOptions.DEFAULT);handleRequest(response);}/*** 精确查询、复合查询* @throws IOException*/@Testvoid testBool() throws IOException {//1 准备RequestSearchRequest request = new SearchRequest("hotel");//2.准备DSL//2.1准备BooleanQueryBoolQueryBuilder boolQuery = QueryBuilders.boolQuery();//2.2添加termboolQuery.must(QueryBuilders.termQuery("city","上海"));//2.3添加rangeboolQuery.filter(QueryBuilders.rangeQuery("price").lte(250));request.source().query(boolQuery);//3.发送请求SearchResponse response = client.search(request, RequestOptions.DEFAULT);handleRequest(response);}/*** 排序和分页* @throws IOException*/@Testvoid testPageAndSort() throws IOException {//页码、每页大小int page = 2,size = 5;//1 准备RequestSearchRequest request = new SearchRequest("hotel");//2.准备DSL//2.1queryrequest.source().query(QueryBuilders.matchAllQuery());//2.2排序sortrequest.source().sort("price", SortOrder.ASC);//2.3分页from、sizerequest.source().from((page-1) * size).size(5);//3.发送请求SearchResponse response = client.search(request, RequestOptions.DEFAULT);handleRequest(response);}/*** 高亮* @throws IOException*/@Testvoid testHighlight() throws IOException {//1 准备RequestSearchRequest request = new SearchRequest("hotel");//2.准备DSL//2.1queryrequest.source().query(QueryBuilders.matchQuery("all","如家"));//2.2高亮request.source().highlighter(new HighlightBuilder().field("name").requireFieldMatch(false));//3.发送请求SearchResponse response = client.search(request, RequestOptions.DEFAULT);handleHighlight(response);}private void handleRequest(SearchResponse response) {//4解析响应SearchHits searchHits = response.getHits();//4.1 获取总条数long total = searchHits.getTotalHits().value;System.out.println("共搜索到" + total + "条数据");//4.2文档数组SearchHit[] hits = searchHits.getHits();//4.3遍历for ( SearchHit hit : hits ) {//获取文档sourceString json = hit.getSourceAsString();//反序列化HotelDoc hotelDoc = JSON.parseObject(json, HotelDoc.class);System.out.println("hotelDoc = " + hotelDoc);}System.out.println(response);}/*** 高亮结果分析* @param response*/private void handleHighlight(SearchResponse response) {//4解析响应SearchHits searchHits = response.getHits();//4.1 获取总条数long total = searchHits.getTotalHits().value;System.out.println("共搜索到" + total + "条数据");//4.2文档数组SearchHit[] hits = searchHits.getHits();//4.3遍历for ( SearchHit hit : hits ) {//获取文档sourceString json = hit.getSourceAsString();//反序列化HotelDoc hotelDoc = JSON.parseObject(json, HotelDoc.class);//获取高亮结果Map<String, HighlightField> highlightFields = hit.getHighlightFields();if ( !CollectionUtils.isEmpty(highlightFields) ) {//根据字段名获取如果HighlightField highlightField = highlightFields.get("name");if ( highlightField!=null ) {//获取高亮的值String name = highlightField.getFragments()[0].string();//覆盖非高亮结果hotelDoc.setName(name);}}System.out.println("hotelDoc = " + hotelDoc);}System.out.println(response);}/***  高亮结果解析*/@BeforeEachvoid setUp(){this.client = new RestHighLevelClient(RestClient.builder(HttpHost.create("http://虚拟机地址:es端口号")));}@AfterEachvoid tearDown()throws IOException{this.client.close();}
}