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）
这个不是专门看视频学习的，是谷粒商城的时候，跟着老师敲的，所以其实就是一个对谷粒商城涉及到这块儿的一个总结，版本什么的自然也就是用的它的。
这算是我总结的一个api，没有真实对照的使用过，只是为了理清思路。
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=127.0.0.1:8848
spring.application.name=gulimall-search
es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;
/**
* es配置类，给容器中注入一个RestHighLevelClient
*/
@Configuration
public 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;
@Autowired
RestHighLevelClient restHighLevelClient;
api
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;
@Repository
public 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;
@Repository
public 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mapping
client.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();
}
@Test
public 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());
}
}
