本篇内容介绍了“Java怎么调用ElasticSearch API”的有关知识，在实际案例的操作过程中，不少人都会遇到这样的困境，接下来就让小编带领大家学习一下如何处理这些情况吧！希望大家仔细阅读，能够学有所成！
java操作es有两种方式
通过操作es的9300端口，9300是tcp端口，集群节点之间通信也是通过9300端口，会通过9300和es建立一个长连接，下面的es的依赖可以直接操作
但是随着es的版本的提升spring-data需要封装不同版本的es的jar包，好像还没封装到这个版本（2019），另外官方也不推荐通过9300来操作es，而且这种方式在es8以后将被废弃
通过9200操作，发送http请求
JestClient，非官方，更新慢
RestTemplate（springboot），模拟发http请求，es很多操作需要自己封装，麻烦
HttpCLient，同上
Elasticsearch-Rest-Client，官方RestClient，封装了ES操作，API层次分明，上手简单
我们在浏览官方文档的时候发现，js可以直接操作es，那为什么我们不直接用js来操作es呢？
出于安全，因为es集群属于后端集群服务器，端口一般不对外暴露，如果对外暴露，会被别人恶意利用
js对es支持度有些低，我们如果用js操作的话，不需要通过官网提供的api，我们直接发送ajax请求，用原生es语句即可
其中，官网的java api是通过9300来操作的，java rest api是通过9200来操作的
官网中有Java Low Level REST Client和Java High Level REST Client，关系就和mybatis和jdbc一样
Elasticsearch-Rest-Client（官方，推荐）
maven
<?xml version="1.0" encoding="UTF-8"?><project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <parent> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-parent</artifactId> <version>2.5.5</version> <relativePath/> <!-- lookup parent from repository --> </parent> <groupId>com.atlinxi.gulimall</groupId> <artifactId>gulimall-search</artifactId> <version>0.0.1-SNAPSHOT</version> <name>gulimall-search</name> <description>elasticsearch检索服务</description> <properties> <java.version>1.8</java.version> <elasticsearch.version>7.4.2</elasticsearch.version> <spring-cloud.version>2020.0.4</spring-cloud.version> </properties> <dependencies> <dependency> <groupId>com.atlinxi.gulimall</groupId> <artifactId>gulimall-common</artifactId> <version>0.0.1-SNAPSHOT</version> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-web</artifactId> </dependency> <dependency> <groupId>org.elasticsearch.client</groupId> <artifactId>elasticsearch-rest-high-level-client</artifactId> <version>7.4.2</version> </dependency> <dependency> <groupId>com.alibaba</groupId> <artifactId>fastjson</artifactId> <version>1.2.47</version> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-test</artifactId> <scope>test</scope> </dependency> </dependencies> <dependencyManagement> <dependencies> <dependency> <groupId>org.springframework.cloud</groupId> <artifactId>spring-cloud-dependencies</artifactId> <version>${spring-cloud.version}</version> <type>pom</type> <scope>import</scope> </dependency> </dependencies> </dependencyManagement> <build> <plugins> <plugin> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-maven-plugin</artifactId> </plugin> </plugins> </build></project>配置文件
spring.cloud.nacos.discovery.server-addr=127.0.0.1:8848spring.application.name=gulimall-searches配置类
package com.atlinxi.gulimall.search.config;import org.apache.http.HttpHost;import org.elasticsearch.client.RequestOptions;import org.elasticsearch.client.RestClient;import org.elasticsearch.client.RestHighLevelClient;import org.springframework.context.annotation.Bean;import org.springframework.context.annotation.Configuration;@Configurationpublic class GulimallElasticSearchConfig { // 后端访问es的时候，出于安全考虑，可以携带一个请求头 // 现在暂时不用 public static final RequestOptions COMMON_OPTIONS; static { RequestOptions.Builder builder = RequestOptions.DEFAULT.toBuilder();// builder.addHeader("Authorization", "Bearer " + TOKEN);// builder.setHttpAsyncResponseConsumerFactory(// new HttpAsyncResponseConsumerFactory// .HeapBufferedResponseConsumerFactory(30 * 1024 * 1024 * 1024)); COMMON_OPTIONS = builder.build(); } @Bean public RestHighLevelClient esRestClient(){ RestHighLevelClient client = new RestHighLevelClient( RestClient.builder( new HttpHost("192.168.56.10", 9200, "http")// new HttpHost("localhost", 9201, "http") )); return client; }}导包
package com.atlinxi.gulimall.search;import com.alibaba.fastjson.JSON;import com.atlinxi.gulimall.search.config.GulimallElasticSearchConfig;import lombok.Data;import lombok.ToString;import org.elasticsearch.action.index.IndexRequest;import org.elasticsearch.action.index.IndexResponse;import org.elasticsearch.action.search.SearchRequest;import org.elasticsearch.action.search.SearchResponse;import org.elasticsearch.client.RestHighLevelClient;import org.elasticsearch.common.xcontent.XContentType;import org.elasticsearch.index.query.QueryBuilders;import org.elasticsearch.search.SearchHit;import org.elasticsearch.search.SearchHits;import org.elasticsearch.search.aggregations.AggregationBuilders;import org.elasticsearch.search.aggregations.Aggregations;import org.elasticsearch.search.aggregations.bucket.terms.Terms;import org.elasticsearch.search.aggregations.bucket.terms.TermsAggregationBuilder;import org.elasticsearch.search.aggregations.metrics.Avg;import org.elasticsearch.search.aggregations.metrics.AvgAggregationBuilder;import org.elasticsearch.search.builder.SearchSourceBuilder;import org.junit.jupiter.api.Test;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.boot.test.context.SpringBootTest;import java.io.IOException;@AutowiredRestHighLevelClient restHighLevelClient;查询
// 1. 创建检索请求SearchRequest searchRequest = new SearchRequest();// 2. 指定索引searchRequest.indices("bank");// 3. 指定DSL，检索条件SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();// 3.1 构造检索条件 // 所有的函数名都对应原生es DSL语句// searchSourceBuilder.query();// searchSourceBuilder.from();// searchSourceBuilder.size();// searchSourceBuilder.aggregation();BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();boolQuery.must(QueryBuilders.matchQuery("skuTitle", param.getKeyword()));boolQuery.filter(QueryBuilders.termQuery("catalogId", param.getCatalog3Id()));boolQuery.filter(QueryBuilders.termsQuery("brandId", param.getBrandId()));BoolQueryBuilder nestedBoolQuery = QueryBuilders.boolQuery();QueryBuilders.nestedQuery("attrs", nestedBoolQuery, ScoreMode.None);boolQuery.filter(nestedQuery);QueryBuilders.rangeQuery("skuPrice");boolQuery.filter(rangeQuery);searchSourceBuilder.query(QueryBuilders.matchQuery("address","mill"));searchSourceBuilder.query(boolQuery);searchSourceBuilder.sort(field, order);sourceBuilder.from(0);sourceBuilder.size(10);HighlightBuilder builder = new HighlightBuilder();builder.field("skuTitle");builder.preTags("<b style='color:red'>");builder.postTags("</b>");sourceBuilder.highlighter(builder);// 3.2 聚合// 按照年龄的值分布进行聚合TermsAggregationBuilder ageAgg = AggregationBuilders.terms("ageAgg").field("age").size(10);// 计算平均薪资AvgAggregationBuilder balanceAvg = AggregationBuilders.avg("balanceAvg").field("balance");AggregationBuilders.nested("attr_agg", "attrs"); searchSourceBuilder.aggregation(balanceAvg);searchSourceBuilder.aggregation(ageAgg);// 4. 执行检索请求searchRequest.source(searchSourceBuilder);SearchResponse searchResponse = restHighLevelClient.search(searchRequest, GulimallElasticSearchConfig.COMMON_OPTIONS);// 5.获取响应结果SearchHits hits = searchResponse.getHits();SearchHit[] searchHits = hits.getHits();searchHit.getSourceAsString();// 3.1 获取聚合结果Aggregations aggregations = searchResponse.getAggregations();Terms ageAgg1 = aggregations.get("ageAgg");// 返回值为List<? extends Terms.Bucket>ageAgg1.getBuckets()bucket.getKeyAsString();aggregations.get("balanceAvg");保存更新
// 添加数据有多种方式，例如hashmap、直接将json粘在这儿IndexRequest request = new IndexRequest("users");request.id("1");// request.source("userName","zhangsan","age",12,"gender","男");// String jsonString = "{" +// "\"user\":\"kimchy\"," +// "\"postDate\":\"2013-01-30\"," +// "\"message\":\"trying out Elasticsearch\"" +// "}";// request.source(jsonString, XContentType.JSON);User user = new User();user.setUserName("zs");user.setAge(12);user.setGender("man");String jsonString = JSON.toJSONString(user);request.source(jsonString, XContentType.JSON);// 执行保存/更新操作IndexResponse index = restHighLevelClient.index(request, GulimallElasticSearchConfig.COMMON_OPTIONS);// 批量保存// 1. 建立索引 product 建立好映射关系（kibana操作）// 2. 给es中保存这些数据BulkRequest bulkRequest = new BulkRequest();IndexRequest indexRequest = new IndexRequest(EsConstant.Product_INDEX);indexRequest.id(skuEsModel.getSkuId().toString());String s = JSON.toJSONString(skuEsModel);indexRequest.source(s, XContentType.JSON);bulkRequest.add(indexRequest);BulkResponse bulk = restHighLevelClient.bulk(bulkRequest, GulimallElasticSearchConfig.COMMON_OPTIONS);// todo 如果批量错误，处理错误boolean b = bulk.hasFailures();bulk.getItems()Spring Data ElasticSearch
Spring Data可以极大的简化JPA的写法，可以在几乎不用写实现的情况下，实现对数据的访问和操作。除了CRUD外，还包括如分页、排序等一些常用的功能。
配置文件
<?xml version="1.0" encoding="UTF-8"?><beans xmlns="http://www.springframework.org/schema/beans" xmlns:es="http://www.springframework.org/schema/data/elasticsearch" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation=" http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd http://www.springframework.org/schema/data/elasticsearch http://www.springframework.org/schema/data/elasticsearch/spring-elasticsearch.xsd"> <!-- 如果你希望 进一步了解 xsd相关的知识 请求百度去 百度不着了 http://www.jk1123.com/?p=124 --> <!-- 配置 client 连上 es 配置 dao层的扫描 配置其他 一个叫做 esTemplate 就是一个简单对应client封装 --> <es:transport-client id="client" cluster-nodes="127.0.0.1:9300" cluster-name="my-elasticsearch"/> <es:repositories base-package="com.itheima.dao"></es:repositories> <bean id="elasticsearchTemplate" class="org.springframework.data.elasticsearch.core.ElasticsearchTemplate"> <constructor-arg name="client" ref="client"></constructor-arg> </bean></beans>实体类
实体类的无参构造必须有，否则查询出来的对象无法映射到实体类
@Document(indexName=“blob3”,type=“article”)：
indexName：索引的名称（必填项）
type：索引的类型
@Id：主键的唯一标识
@Field(index=true,analyzer=“ik_smart”,store=true,searchAnalyzer=“ik_smart”,type = FieldType.text)
analyzer：存储时使用的分词器
searchAnalyze：搜索时使用的分词器
store：是否存储
type: 数据类型
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;//@Document 文档对象 （索引信息、文档类型 ）@Document(indexName="test03",type="book")public class Book { //@Id 文档主键 唯一标识 @Id //@Field 每个文档的字段配置（类型、是否分词、是否存储、分词器 ） @Field(store = true, index = false, type = FieldType.Integer) private Integer id; @Field(analyzer = "ik_max_word", store = true, type = FieldType.text) private String title; @Field(analyzer = "ik_max_word", store = true, type = FieldType.text) private String content; @Field(index = false, store = true, type = FieldType.Long) private Long sales;dao
import com.itheima.domain.Book;import org.springframework.data.domain.Page;import org.springframework.data.domain.Pageable;import org.springframework.data.elasticsearch.repository.ElasticsearchRepository;import org.springframework.stereotype.Repository;import java.util.List;@Repositorypublic interface BookDao extends ElasticsearchRepository<Book, Integer> {// 除了系统自带的方法，还可以自定义命名 List<Book> findByContent(String content); List<Book> findByContentAndTitle(String content, String title); Page<Book> findByContent(String content, Pageable pageable);}crud
import org.junit.Test;import org.junit.runner.RunWith;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.data.elasticsearch.core.ElasticsearchTemplate;import org.springframework.test.context.ContextConfiguration;import org.springframework.test.context.junit4.SpringJUnit4ClassRunner;import javax.annotation.Resource;@RunWith(SpringJUnit4ClassRunner.class)@ContextConfiguration(locations = "classpath:beans.xml")public class AppTest { @Resource private BookDao bookDao; @Autowired private ElasticsearchTemplate elasticsearchTemplate; // 创建索引库 @Test public void testCreatIndex(){ elasticsearchTemplate.createIndex(Book.class); elasticsearchTemplate.putMapping(Book.class); }// 新增或者更新 @Test public void save(){ Book book = new Book(20,"20","20",20L); bookDao.save(book); } // 删除 @Test public void testDelete(){ bookDao.deleteById(20); } @Test public void testFindById(){ Book book = bookDao.findById(20).get(); System.out.println(book); }@Test public void testFindByPageAndSort() throws IOException { // PageRequest.of() 构建的是一个Pageable对象，此对象是在spring-data-commons包下 // 所以凡是spring data 系列，都可以用该对象来进行分页 Page<Book> books = bookDao.findAll(PageRequest.of(0, 10,Sort.Direction.ASC,"sales")); // 总条数 long totalElements = books.getTotalElements(); // 总页数 int totalPages = books.getTotalPages(); System.out.println(totalElements); System.out.println(totalPages); books.forEach(book -> System.out.println(book)); }方法命名规则查询
import org.springframework.data.domain.Page;import org.springframework.data.domain.Pageable;import org.springframework.data.elasticsearch.repository.ElasticsearchRepository;import org.springframework.stereotype.Repository;import java.util.List;@Repositorypublic interface BookDao extends ElasticsearchRepository<Book, Integer> { List<Book> findByContent(String content); List<Book> findByContentAndTitle(String content, String title); Page<Book> findByContent(String content, Pageable pageable);}@Test public void testMethodName(){ List<Book> byContentAndTitle = bookDao.findByContentAndTitle("程序", "程序"); byContentAndTitle.forEach(book -> System.out.println(book)); }springdata对es没有封装的方法
例如term、query_string、高亮显示等，就用原生api
@Test public void findQueryString(){ //没有封装 的方法 SearchQuery searchQuery=new NativeSearchQueryBuilder() //依旧传递的查询方式 查询参数 .withQuery(QueryBuilders.queryStringQuery("我是程序员")) .build(); Page<Book> page = bookDao.search(searchQuery); long totalElements = page.getTotalElements(); System.out.println("总条数:"+totalElements); int totalPages = page.getTotalPages(); System.out.println("总页数:"+totalPages); List<Book> books = page.getContent(); books.forEach(b-> System.out.println(b)); } @Test public void findTerm2(){ //没有封装 的方法 SearchQuery searchQuery=new NativeSearchQueryBuilder() //依旧传递的查询方式 查询参数 .withQuery(QueryBuilders.termQuery("content","程序")) .build(); Page<Book> page = bookDao.search(searchQuery); long totalElements = page.getTotalElements(); System.out.println("总条数:"+totalElements); int totalPages = page.getTotalPages(); System.out.println("总页数:"+totalPages); List<Book> books = page.getContent(); books.forEach(b-> System.out.println(b)); }高亮显示
@Test public void testHighLight() { SearchQuery searchQuery = new NativeSearchQueryBuilder() //依旧传递的查询方式 查询参数 .withQuery(QueryBuilders.termQuery("content", "程序")) .withHighlightFields(new HighlightBuilder.Field("content").preTags("<xh style='color:red'>").postTags("</xh>")) .build(); AggregatedPage<Book> page = elasticsearchTemplate.queryForPage(searchQuery, Book.class, new SearchResultMapper() { //自定义结果映射器 核心 将高亮字段取出 设置对象 返回数据就有高亮显示 而spring-data-es 默认实现 //DefaultResultMapper 它 不会取出高亮字段 不用 @Override public <T> AggregatedPage<T> mapResults(SearchResponse searchResponse, Class<T> aClass, Pageable pageable) { List<Book> books = new ArrayList<>(); // 总条数 long totalHits = searchResponse.getHits().getTotalHits(); //System.out.println(totalHits); // 数据，包含高亮显示的字段 SearchHits hits = searchResponse.getHits(); Iterator<SearchHit> iterator = hits.iterator(); while (iterator.hasNext()) { SearchHit sh = iterator.next(); // 每一条数据{id=17, title=程序员的自我修养—链接、装载与库, content=俯瞰程序前世今生参透代码如何变成程序在系统中运行 透过系统软件底层形成机制走进程序世界探索深层次的自己, sales=6856} //高亮字段{content=[content], fragments[[俯瞰<xh style='color:red'>程序</xh>前世今生参透代码如何变成<xh style='color:red'>程序</xh>在系统中运行 透过系统软件底层形成机制走进<xh style='color:red'>程序</xh>世界探索深层次的自己]]} Map<String, Object> source = sh.getSource(); System.out.println("每一条数据" + source); Map<String, HighlightField> highlightFields = sh.getHighlightFields(); System.out.println("高亮字段" + highlightFields); //开始封装book对象 Book book = new Book(); Integer id = (Integer) source.get("id"); book.setId(id); String title = (String) source.get("title"); book.setTitle(title); HighlightField content = highlightFields.get("content"); book.setContent(content.getFragments()[0].toString()); Integer sales = (Integer) source.get("sales"); book.setSales(Long.valueOf(sales)); books.add(book); } return new AggregatedPageImpl(books, pageable, totalHits); } }); long totalElements = page.getTotalElements(); System.out.println("总条数:" + totalElements); int totalPages = page.getTotalPages(); System.out.println("总页数:" + totalPages); List<Book> books = page.getContent(); books.forEach(b -> System.out.println(b)); }elasticsearch transport 通过9300操作
maven
<dependencies> <dependency> <groupId>org.elasticsearch</groupId> <artifactId>elasticsearch</artifactId> <version>5.6.8</version> </dependency> <dependency> <groupId>org.elasticsearch.client</groupId> <artifactId>transport</artifactId> <version>5.6.8</version> </dependency> <dependency> <groupId>org.apache.logging.log4j</groupId> <artifactId>log4j-to-slf4j</artifactId> <version>2.9.1</version> </dependency> <dependency> <groupId>org.slf4j</groupId> <artifactId>slf4j-api</artifactId> <version>1.7.24</version> </dependency> <dependency> <groupId>org.slf4j</groupId> <artifactId>slf4j-simple</artifactId> <version>1.7.21</version> </dependency> <dependency> <groupId>log4j</groupId> <artifactId>log4j</artifactId> <version>1.2.12</version> </dependency> <dependency> <groupId>junit</groupId> <artifactId>junit</artifactId> <version>4.12</version> </dependency> <dependency> <groupId>com.fasterxml.jackson.core</groupId> <artifactId>jackson-core</artifactId> <version>2.8.1</version> </dependency> <dependency> <groupId>com.fasterxml.jackson.core</groupId> <artifactId>jackson-databind</artifactId> <version>2.8.1</version> </dependency> <dependency> <groupId>com.fasterxml.jackson.core</groupId> <artifactId>jackson-annotations</artifactId> <version>2.8.1</version> </dependency></dependencies>// 创建客户端对象private TransportClient client; // 创建客户端对象 @Before public void init() { try { //创建一个客户端对象 Settings settings = Settings.builder() .put("cluster.name", "my-elasticsearch") .build(); client = new PreBuiltTransportClient(settings) //少服务器的地址 .addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("127.0.0.1"), 9300));// .addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("127.0.0.1"),9301))// .addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("127.0.0.1"),9302)); } catch (UnknownHostException e) { e.printStackTrace(); } }// 创建type和mappingclient.admin().indices().preparePutMapping("test02") .setType("book") .setSource("{\n" + " \"book\": {\n" + " \"properties\": {\n" + " \"id\": {\n" + " \t\"type\": \"long\",\n" + " \"store\": true,\n" + " \"index\":\"not_analyzed\"\n" + " },\n" + " \"title\": {\n" + " \t\"type\": \"text\",\n" + " \"store\": true,\n" + " \"index\":\"analyzed\",\n" + " \"analyzer\":\"ik_max_word\"\n" + " },\n" + " \"content\": {\n" + " \t\"type\": \"text\",\n" + " \"store\": true,\n" + " \"index\":\"analyzed\",\n" + " \"analyzer\":\"ik_max_word\"\n" + " },\n" + " \"sales\":{\n" + " \"type\": \"long\",\n" + " \"store\": true,\n" + " \"index\":\"not_analyzed\"\n" + " }\n" + " }\n" + " }\n" + " }", XContentType.JSON) .get();// 文档的crud@Test public void testAdd(){ client.prepareIndex("test02", "book", "1") .setSource( "{\n" + "\t\"id\":1,\n" + "\t\"title\":\"测试添加\",\n" + "\t\"content\":\"测试添加数据\",\n" + "\t\"sales\":666\n" + "}",XContentType.JSON ) .get(); }// 实体类进行存储 @Test public void testAdd() throws JsonProcessingException { Book book = new Book(); book.setId(2L); book.setTitle("对象测试"); book.setContent("对象测试内容"); book.setSales(1000L); // 使用json转换工具 ObjectMapper mappers = new ObjectMapper(); String string = mappers.writeValueAsString(book); client.prepareIndex("test02", "book", "2") .setSource( string,XContentType.JSON ) .get(); }@Testpublic void deleteDocument(){ client.prepareDelete("test02", "book", "1").get();}// 批量导入 @Test public void bulkAdd() throws IOException { BulkRequestBuilder bulkRequest = client.prepareBulk(); // 数据在本地中，进行读取 File file = new File("F:\\darkHorse\\darkHorsePool\\springbootSeries\\dailyQuest\\day90_elasticSearch\\resource\\esData.txt"); BufferedReader bufferedReader = new BufferedReader(new FileReader(file)); String line = null; int i = 1000; while ((line = bufferedReader.readLine()) != null){ bulkRequest.add(client.prepareIndex("test02", "book",i++ + "") .setSource(line,XContentType.JSON) ); } BulkResponse bulkResponse = bulkRequest.get(); if (bulkResponse.hasFailures()) { // process failures by iterating through each bulk response item } } @Test public void testFindIds(){ SearchRequestBuilder searchRequestBuilder = client.prepareSearch("test02") .setTypes("book") //这个地方 告诉构建器 使用什么类型查询方式 //查询方式 使用 QueryBuilders.term...matchall....queryString .setQuery(QueryBuilders.idsQuery().addIds("1000","1002","1003")) .setFrom(0) .setSize(20); //返回了一个 SearchResponse 响应对象 SearchResponse searchResponse = searchRequestBuilder.get(); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("一共多少条记录:"+totalHits); Iterator<SearchHit> iterator = hits.iterator(); while (iterator.hasNext()){ SearchHit searchHit = iterator.next(); Map<String, Object> source = searchHit.getSource(); System.out.println(source); } }SearchRequestBuilder searchRequestBuilder = client.prepareSearch("test02") .setTypes("book") //这个地方 告诉构建器 使用什么类型查询方式 //查询方式 使用 QueryBuilders.term...matchall....queryString .setQuery(QueryBuilders.termQuery("content","程序")) .setFrom(0) .setSize(20);@Test public void highLight() { HighlightBuilder highlightBuilder = new HighlightBuilder() .preTags("<font style='color:red'>") .postTags("</font>") .field("content"); SearchRequestBuilder searchRequestBuilder = client.prepareSearch("test02") .setTypes("book") //这个地方 告诉构建器 使用什么类型查询方式 //查询方式 使用 QueryBuilders.term...matchall....queryString .setQuery(QueryBuilders.termQuery("content", "程序")) .setFrom(0) .setSize(20) .highlighter(highlightBuilder); //返回了一个 SearchResponse 响应对象 SearchResponse searchResponse = searchRequestBuilder.get(); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("一共多少条记录:" + totalHits); Iterator<SearchHit> iterator = hits.iterator(); while (iterator.hasNext()) { SearchHit searchHit = iterator.next(); Map<String, Object> source = searchHit.getSource(); System.out.println(source); //获取高亮显示的内容 这是一个map集合 Map<String, HighlightField> highlightFields = searchHit.getHighlightFields(); HighlightField content = highlightFields.get("content"); Text[] fragments = content.getFragments(); System.out.println(fragments[0].toString()); } }“Java怎么调用ElasticSearch API”的内容就介绍到这里了，感谢大家的阅读。如果想了解更多行业相关的知识可以关注编程网网站，小编将为大家输出更多高质量的实用文章！
