| title | tags | categories | keywords | description | cover | abbrlink | date | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
ElasticSearch-进阶篇 |
|
|
ElasticSearch,全文检索 |
ElasticSearch-进阶篇，ElasticSearch的一些实战用法，集成SpringBoot。 |
50e81c79 |
2020-02-08 10:06:23 -0800 |
ES提供多种不同的客户端：
1、TransportClient
ES提供的传统客户端，官方计划8.0版本删除此客户端。
2、RestClient
RestClient是官方推荐使用的，它包括两种：Java Low Level REST Client和 Java High Level REST Client。
ES在6.0之后提供 Java High Level REST Client， 两种客户端官方更推荐使用 Java High Level REST Client，不过当
前它还处于完善中，有些功能还没有。
我们采用SpringBoot2.x与ElasticSearch集成
部分依赖
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
<java.version>1.8</java.version>
<elasticsearch.version>6.3.2</elasticsearch.version>
</properties>
<!-- ES -->
<dependencies>
<dependency>
<groupId>org.elasticsearch.client</groupId>
<artifactId>transport</artifactId>
<version>${elasticsearch.version}</version>
</dependency>
<dependency>
<groupId>org.elasticsearch.client</groupId>
<artifactId>elasticsearch-rest-high-level-client</artifactId>
<version>${elasticsearch.version}</version>
</dependency>
<dependency>
<groupId>org.elasticsearch</groupId>
<artifactId>elasticsearch</artifactId>
<version>${elasticsearch.version}</version>
</dependency>
<dependencies>
#elasticsearch配置
anshe.elasticsearch.hostlist=${eshostlist:你的IP地址:9200}package com.anshe.common.config.es;
import com.anshe.web.service.ISearchService;
import org.apache.http.HttpHost;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.client.transport.TransportClient;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.transport.TransportAddress;
import org.elasticsearch.transport.client.PreBuiltTransportClient;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import java.net.InetAddress;
/**
* @author Administrator
* @version 1.0
**/
@Configuration
public class ElasticsearchConfig {
private static final Logger logger = LoggerFactory.getLogger(ISearchService.class);
@Value("${anshe.elasticsearch.hostlist}")
private String hostlist;
@Bean
public RestHighLevelClient restHighLevelClient(){
//解析hostlist配置信息
String[] split = hostlist.split(",");
//创建HttpHost数组，其中存放es主机和端口的配置信息
HttpHost[] httpHostArray = new HttpHost[split.length];
for(int i=0;i<split.length;i++){
String item = split[i];
httpHostArray[i] = new HttpHost(item.split(":")[0], Integer.parseInt(item.split(":")[1]), "http");
}
//创建RestHighLevelClient客户端
return new RestHighLevelClient(RestClient.builder(httpHostArray));
}
//项目主要使用RestHighLevelClient，对于低级的客户端暂时不用
@Bean
public RestClient restClient(){
//解析hostlist配置信息
String[] split = hostlist.split(",");
//创建HttpHost数组，其中存放es主机和端口的配置信息
HttpHost[] httpHostArray = new HttpHost[split.length];
for(int i=0;i<split.length;i++){
String item = split[i];
httpHostArray[i] = new HttpHost(item.split(":")[0], Integer.parseInt(item.split(":")[1]), "http");
}
return RestClient.builder(httpHostArray).build();
}
@Bean(name = "transportClient")
public TransportClient transportClient() {
logger.info("Elasticsearch初始化开始。。。。。");
TransportClient transportClient = null;
try {
// 配置信息
Settings esSetting = Settings.builder()
.put("cluster.name", "elasticsearch_anshe") //集群名字
.put("client.transport.sniff", true)//增加嗅探机制，找到ES集群
.build();
//配置信息Settings自定义
transportClient = new PreBuiltTransportClient(esSetting);
TransportAddress transportAddress = new TransportAddress(InetAddress.getByName("你的IP地址"), 9300);
transportClient.addTransportAddresses(transportAddress);
} catch (Exception e) {
logger.error("elasticsearch TransportClient create error!!", e);
}
return transportClient;
}
}
package com.anshe;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import tk.mybatis.spring.annotation.MapperScan;
@SpringBootApplication
@MapperScan(basePackages = "com.anshe.web.mapper")
public class AnsheApplication {
public static void main(String[] args) {
System.setProperty("es.set.netty.runtime.available.processors", "false");
SpringApplication.run(AnsheApplication.class, args);
}
}创建索引：
put http://localhost:9200/索引名称
{
"settings":{
"index":{
"number_of_shards":"1", # 分片数
"number_of_replicas":"0" # 副本数
}
}
}创建映射：
发送：put http://localhost:9200/索引库名称/类型名称/_mapping
创建类型为xc_course的映射，共包括三个字段：name、description、studymodel 等
http://localhost:9200/xc_course/doc/_mapping
{
"properties": {
"name": {
"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_smart"
},
"description": {
"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_smart"
},
"studymodel": {
"type": "keyword"
},
"price": {
"type": "float"
},
"timestamp": {
"type": "date",
"format": "yyyy‐MM‐dd HH:mm:ss||yyyy‐MM‐dd||epoch_millis"
}
}
}@Autowired
RestHighLevelClient client;
@Autowired
RestClient restClient;
//创建索引库
@Test
public void testCreateIndex() throws IOException {
//创建索引对象
CreateIndexRequest createIndexRequest = new CreateIndexRequest("xc_course");
//设置参数
createIndexRequest.settings(Settings.builder().put("number_of_shards","1").put("number_of_replicas","0"));
//指定映射
createIndexRequest.mapping("doc"," {\n" +
" \t\"properties\": {\n" +
" \"studymodel\":{\n" +
" \"type\":\"keyword\"\n" +
" },\n" +
" \"name\":{\n" +
" \"type\":\"keyword\"\n" +
" },\n" +
" \"description\": {\n" +
" \"type\": \"text\",\n" +
" \"analyzer\":\"ik_max_word\",\n" +
" \"search_analyzer\":\"ik_smart\"\n" +
" },\n" +
" \"pic\":{\n" +
" \"type\":\"text\",\n" +
" \"index\":false\n" +
" }\n" +
" \t}\n" +
"}", XContentType.JSON);
//操作索引的客户端
IndicesClient indices = client.indices();
//执行创建索引库
CreateIndexResponse createIndexResponse = indices.create(createIndexRequest);
//得到响应
boolean acknowledged = createIndexResponse.isAcknowledged();
System.out.println(acknowledged);
}DELETE http://['你自己的Ip加Port']/test
{
"acknowledged": true
}//删除索引库
@Test
public void testDeleteIndex() throws IOException {
//删除索引对象
DeleteIndexRequest deleteIndexRequest = new DeleteIndexRequest("xc_course");
//操作索引的客户端
IndicesClient indices = client.indices();
//执行删除索引
DeleteIndexResponse delete = indices.delete(deleteIndexRequest);
//得到响应
boolean acknowledged = delete.isAcknowledged();
System.out.println(acknowledged);
}格式如下： PUT /{index}/{type}/{id} { "fifield": "value", ... }
如果不指定id，ES会自动生成。
一个例子：
put http://localhost:9200/xc_course/doc/3
{
"name": "spring cloud实战",
"description": "本课程主要从四个章节进行讲解： 1.微服务架构入门 2.spring cloud 基础入门 3.实战Spring Boot 4.注册中心eureka。",
"studymodel": "201001",
"price": 5.6
}//添加文档
@Test
public void testAddDoc() throws IOException {
//文档内容
//准备json数据
Map<String, Object> jsonMap = new HashMap<>();
jsonMap.put("name", "spring cloud实战");
jsonMap.put("description", "本课程主要从四个章节进行讲解： 1.微服务架构入门 2.spring cloud 基础入门 3.实战Spring Boot 4.注册中心eureka。");
jsonMap.put("studymodel", "201001");
SimpleDateFormat dateFormat =new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
jsonMap.put("timestamp", dateFormat.format(new Date()));
jsonMap.put("price", 5.6f);
//创建索引创建对象
IndexRequest indexRequest = new IndexRequest("xc_course","doc");
//文档内容
indexRequest.source(jsonMap);
//通过client进行http的请求
IndexResponse indexResponse = client.index(indexRequest);
DocWriteResponse.Result result = indexResponse.getResult();
System.out.println(result);
}格式如下： GET /{index}/{type}/{id}
//查询文档
@Test
public void testGetDoc() throws IOException {
//查询请求对象
GetRequest getRequest = new GetRequest("xc_course","doc","0fOCF2sBEYTsNRZ43I8b");
GetResponse getResponse = client.get(getRequest);
//得到文档的内容
Map<String, Object> sourceAsMap = getResponse.getSourceAsMap();
System.out.println(sourceAsMap);
}ES更新文档的顺序是：先检索到文档、将原来的文档标记为删除、创建新文档、删除旧文档，创建新文档就会重建
索引。
通过请求Url有两种方法：
1、完全替换
Post：http://localhost:9200/xc_test/doc/3
{
"name": "spring cloud实战",
"description": "本课程主要从四个章节进行讲解： 1.微服务架构入门 2.spring cloud 基础入门 3.实战SpringBoot 4.注册中心eureka。",
"studymodel": "201001",
"price": 5.6
}2、局部更新
下边的例子是只更新price字段。
post: http://localhost:9200/xc_test/doc/3/_update
{
"doc": {
"price": 66.6
}
}使用 Client Api更新文档的方法同上边第二种局部更新方法。
可以指定文档的部分字段也可以指定完整的文档内容。
//更新文档
@Test public void updateDoc() throws IOException {
UpdateRequest updateRequest = new UpdateRequest("xc_course", "doc", "4028e581617f945f01617f9dabc40000");
Map<String, String> map = new HashMap<>();
map.put("name", "spring cloud实战");
updateRequest.doc(map);
UpdateResponse update = client.update(updateRequest);
RestStatus status = update.status();
System.out.println(status);
}
1、根据id删除，格式如下：
DELETE /{index}/{type}/{id}
2、搜索匹配删除，将搜索出来的记录删除，格式如下：
POST /{index}/{type}/_delete_by_query
下边是搜索条件例子：
{
"query": {
"term": {
"studymodel": "201001"
}
}
}上边例子的搜索匹配删除会将studymodel为201001的记录全部删除
//根据id删除文档
@Test
public void testDelDoc() throws IOException {
//删除文档id
String id = "eqP_amQBKsGOdwJ4fHiC";
//删除索引请求对象
DeleteRequest deleteRequest = new DeleteRequest("xc_course","doc",id);
//响应对象
DeleteResponse deleteResponse = client.delete(deleteRequest);
//获取响应结果
DocWriteResponse.Result result = deleteResponse.getResult();
System.out.println(result);
}搜索匹配删除还没有具体的api，可以采用先搜索出文档id，根据文档id删除。
创建xc_course索引库。
创建如下映射
post：http://localhost:9200/xc_course/doc/_mapping
{
"properties": {
"description": {
"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_smart"
},
"name": {
"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_smart"
},
"pic": {
"type": "text",
"index": false
},
"price": {
"type": "float"
},
"studymodel": {
"type": "keyword"
},
"timestamp": {
"type": "date",
"format": "yyyy‐MM‐dd HH:mm:ss||yyyy‐MM‐dd||epoch_millis"
}
}
}向xc_course/doc中插入以下数据：
http://localhost:9200/xc_course/doc/1
{
"name": "Bootstrap开发",
"description": "Bootstrap是由Twitter推出的一个前台页面开发框架，是一个非常流行的开发框架，此框架集成了 多种页面效果。此开发框架包含了大量的CSS、JS程序代码，可以帮助开发者（尤其是不擅长页面开发的程序人员）轻松 的实现一个不受浏览器限制的精美界面效果。",
"studymodel": "201002",
"price": 38.6,
"timestamp": "2018‐04‐25 19:11:35",
"pic": "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg"
}
http://localhost:9200/xc_course/doc/2
{
"name": "java编程基础",
"description": "java语言是世界第一编程语言，在软件开发领域使用人数最多。",
"studymodel": "201001",
"price": 68.6,
"timestamp": "2018‐03‐25 19:11:35",
"pic": "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg"
}
http://localhost:9200/xc_course/doc/3
{
"name": "spring开发基础",
"description": "spring 在java领域非常流行，java程序员都在用。",
"studymodel": "201001",
"price": 88.6,
"timestamp": "2018‐02‐24 19:11:35",
"pic": "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg"
}
DSL(Domain Specifific Language)是ES提出的基于json的搜索方式，在搜索时传入特定的json格式的数据来完成不 同的搜索需求。 DSL比URI搜索方式功能强大，在项目中建议使用DSL方式来完成搜索。
查询所有索引库的文档。
发送：post http://localhost:9200/_search
查询指定索引库指定类型下的文档。（通过使用此方法）
发送：post http://localhost:9200/xc_course/doc/_search
{
"query": {
"match_all": {}
},
"_source": [
"name",
"studymodel"
]
}_source：source源过虑设置，指定结果中所包括的字段有哪些。
结果说明：
took：本次操作花费的时间，单位为毫秒。
timed_out：请求是否超时
_shards：说明本次操作共搜索了哪些分片
hits：搜索命中的记录
hits.total ： 符合条件的文档总数 hits.hits ：匹配度较高的前N个文档
hits.max_score：文档匹配得分，这里为最高分
_score：每个文档都有一个匹配度得分，按照降序排列。
_source：显示了文档的原始内容。
@Autowired
RestHighLevelClient client;
@Autowired
RestClient restClient;
//搜索全部记录
@Test
public void testSearchAll() throws IOException, ParseException {
//搜索请求对象
SearchRequest searchRequest = new SearchRequest("xc_course");
//指定类型
searchRequest.types("doc");
//搜索源构建对象
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//搜索方式
//matchAllQuery搜索全部
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});
//向搜索请求对象中设置搜索源
searchRequest.source(searchSourceBuilder);
//执行搜索,向ES发起http请求
SearchResponse searchResponse = client.search(searchRequest);
//搜索结果
SearchHits hits = searchResponse.getHits();
//匹配到的总记录数
long totalHits = hits.getTotalHits();
//得到匹配度高的文档
SearchHit[] searchHits = hits.getHits();
//日期格式化对象
// SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss.SSS'Z'");
for(SearchHit hit:searchHits){
//文档的主键
String id = hit.getId();
//源文档内容
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
//由于前边设置了源文档字段过虑，这时description是取不到的
String description = (String) sourceAsMap.get("description");
//学习模式
String studymodel = (String) sourceAsMap.get("studymodel");
//价格
Double price = (Double) sourceAsMap.get("price");
//日期
Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
System.out.println(studymodel);
System.out.println(description);
}
}ES支持分页查询，传入两个参数：from和size。
form：表示起始文档的下标，从0开始。
size：查询的文档数量。
发送：post http://localhost:9200/xc_course/doc/_search
{
"from": 0,
"size": 1,
"query": {
"match_all": {}
},
"_source": [
"name",
"studymodel"
]
}//分页查询
@Test
public void testSearchPage() throws IOException, ParseException {
//搜索请求对象
SearchRequest searchRequest = new SearchRequest("xc_course");
//指定类型
searchRequest.types("doc");
//搜索源构建对象
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//设置分页参数
//页码
int page = 1;
//每页记录数
int size = 1;
//计算出记录起始下标
int from = (page-1)*size;
searchSourceBuilder.from(from);//起始记录下标，从0开始
searchSourceBuilder.size(size);//每页显示的记录数
//搜索方式
//matchAllQuery搜索全部
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});
//向搜索请求对象中设置搜索源
searchRequest.source(searchSourceBuilder);
//执行搜索,向ES发起http请求
SearchResponse searchResponse = client.search(searchRequest);
//搜索结果
SearchHits hits = searchResponse.getHits();
//匹配到的总记录数
long totalHits = hits.getTotalHits();
//得到匹配度高的文档
SearchHit[] searchHits = hits.getHits();
//日期格式化对象
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for(SearchHit hit:searchHits){
//文档的主键
String id = hit.getId();
//源文档内容
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
//由于前边设置了源文档字段过虑，这时description是取不到的
String description = (String) sourceAsMap.get("description");
//学习模式
String studymodel = (String) sourceAsMap.get("studymodel");
//价格
Double price = (Double) sourceAsMap.get("price");
//日期
Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
System.out.println(studymodel);
System.out.println(description);
}
}Term Query为精确查询，在搜索时会整体匹配关键字，不再将关键字分词。
发送：post http://localhost:9200/xc_course/doc/_search
{
"query": {
"term": {
"name": "spring"
}
},
"_source": [
"name",
"studymodel"
]
}上边的搜索会查询name包括“spring”这个词的文档。
//TermQuery
@Test
public void testTermQuery() throws IOException, ParseException {
//搜索请求对象
SearchRequest searchRequest = new SearchRequest("xc_course");
//指定类型
searchRequest.types("doc");
//搜索源构建对象
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//设置分页参数
//页码
int page = 1;
//每页记录数
int size = 1;
//计算出记录起始下标
int from = (page-1)*size;
searchSourceBuilder.from(from);//起始记录下标，从0开始
searchSourceBuilder.size(size);//每页显示的记录数
//搜索方式
//termQuery
searchSourceBuilder.query(QueryBuilders.termQuery("name","spring"));
//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});
//向搜索请求对象中设置搜索源
searchRequest.source(searchSourceBuilder);
//执行搜索,向ES发起http请求
SearchResponse searchResponse = client.search(searchRequest);
//搜索结果
SearchHits hits = searchResponse.getHits();
//匹配到的总记录数
long totalHits = hits.getTotalHits();
//得到匹配度高的文档
SearchHit[] searchHits = hits.getHits();
//日期格式化对象
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for(SearchHit hit:searchHits){
//文档的主键
String id = hit.getId();
//源文档内容
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
//由于前边设置了源文档字段过虑，这时description是取不到的
String description = (String) sourceAsMap.get("description");
//学习模式
String studymodel = (String) sourceAsMap.get("studymodel");
//价格
Double price = (Double) sourceAsMap.get("price");
//日期
Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
System.out.println(studymodel);
System.out.println(description);
}
}ES提供根据多个id值匹配的方法：
测试：
post： http://127.0.0.1:9200/xc_course/doc/_search
{
"query": {
"ids": {
"type": "doc",
"values": [
"3",
"4",
"100"
]
}
}
}//根据id查询
@Test
public void testTermQueryByIds() throws IOException, ParseException {
//搜索请求对象
SearchRequest searchRequest = new SearchRequest("xc_course");
//指定类型
searchRequest.types("doc");
//搜索源构建对象
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//搜索方式
//根据id查询
//定义id
String[] ids = new String[]{"1","2"};
searchSourceBuilder.query(QueryBuilders.termsQuery("_id",ids));
//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});
//向搜索请求对象中设置搜索源
searchRequest.source(searchSourceBuilder);
//执行搜索,向ES发起http请求
SearchResponse searchResponse = client.search(searchRequest);
//搜索结果
SearchHits hits = searchResponse.getHits();
//匹配到的总记录数
long totalHits = hits.getTotalHits();
//得到匹配度高的文档
SearchHit[] searchHits = hits.getHits();
//日期格式化对象
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for(SearchHit hit:searchHits){
//文档的主键
String id = hit.getId();
//源文档内容
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
//由于前边设置了源文档字段过虑，这时description是取不到的
String description = (String) sourceAsMap.get("description");
//学习模式
String studymodel = (String) sourceAsMap.get("studymodel");
//价格
Double price = (Double) sourceAsMap.get("price");
//日期
Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
System.out.println(studymodel);
System.out.println(description);
}
}match Query即全文检索，它的搜索方式是先将搜索字符串分词，再使用各各词条从索引中搜索。
match query与Term query区别是match query在搜索前先将搜索关键字分词，再拿各各词语去索引中搜索。
发送：post http://localhost:9200/xc_course/doc/_search
{
"query": {
"match": {
"description": {
"query": "spring开发",
"operator": "or"
}
}
}
}query：搜索的关键字，对于英文关键字如果有多个单词则中间要用半角逗号分隔，而对于中文关键字中间可以用
逗号分隔也可以不用。
operator：or 表示 只要有一个词在文档中出现则就符合条件，and表示每个词都在文档中出现则才符合条件。
上边的搜索的执行过程是：
1、将“spring开发”分词，分为spring、开发两个词
2、再使用spring和开发两个词去匹配索引中搜索。
3、由于设置了operator为or，只要有一个词匹配成功则就返回该文档。
//MatchQuery
@Test
public void testMatchQuery() throws IOException, ParseException {
//搜索请求对象
SearchRequest searchRequest = new SearchRequest("xc_course");
//指定类型
searchRequest.types("doc");
//搜索源构建对象
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//搜索方式
//MatchQuery
searchSourceBuilder.query(QueryBuilders.matchQuery("description","spring开发框架")
.minimumShouldMatch("80%"));
//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});
//向搜索请求对象中设置搜索源
searchRequest.source(searchSourceBuilder);
//执行搜索,向ES发起http请求
SearchResponse searchResponse = client.search(searchRequest);
//搜索结果
SearchHits hits = searchResponse.getHits();
//匹配到的总记录数
long totalHits = hits.getTotalHits();
//得到匹配度高的文档
SearchHit[] searchHits = hits.getHits();
//日期格式化对象
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for(SearchHit hit:searchHits){
//文档的主键
String id = hit.getId();
//源文档内容
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
//由于前边设置了源文档字段过虑，这时description是取不到的
String description = (String) sourceAsMap.get("description");
//学习模式
String studymodel = (String) sourceAsMap.get("studymodel");
//价格
Double price = (Double) sourceAsMap.get("price");
//日期
Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
System.out.println(studymodel);
System.out.println(description);
}
}1、基本使用
上边学习的termQuery和matchQuery一次只能匹配一个Field，本节学习multiQuery，一次可以匹配多个字段。
单项匹配是在一个fifield中去匹配，多项匹配是拿关键字去多个Field中匹配。
例子：
发送：post http://localhost:9200/xc_course/doc/_search
拿关键字 “spring css”去匹配name 和description字段。
{
"query": {
"multi_match": {
"query": "spring css",
"minimum_should_match": "50%",
"fields": [
"name",
"description"
]
}
}
}2、提升boost
匹配多个字段时可以提升字段的boost（权重）来提高得分
例子：
提升boost之前，执行下边的查询：
{
"query": {
"multi_match": {
"query": "spring框架",
"minimum_should_match": "50%",
"fields": [
"name",
"description"
]
}
}
}通过查询发现Bootstrap排在前边。
提升boost，通常关键字匹配上name的权重要比匹配上description的权重高，这里可以对name的权重提升
{
"query": {
"multi_match": {
"query": "spring框架",
"minimum_should_match": "50%",
"fields": [
"name^10",
"description"
]
}
}
}“name^10” 表示权重提升10倍，执行上边的查询，发现name中包括spring关键字的文档排在前边。
//MultiMatchQuery
@Test
public void testMultiMatchQuery() throws IOException, ParseException {
//搜索请求对象
SearchRequest searchRequest = new SearchRequest("xc_course");
//指定类型
searchRequest.types("doc");
//搜索源构建对象
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//搜索方式
//MultiMatchQuery
searchSourceBuilder.query(QueryBuilders.multiMatchQuery("spring css","name","description")
.minimumShouldMatch("50%")
.field("name",10));
//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});
//向搜索请求对象中设置搜索源
searchRequest.source(searchSourceBuilder);
//执行搜索,向ES发起http请求
SearchResponse searchResponse = client.search(searchRequest);
//搜索结果
SearchHits hits = searchResponse.getHits();
//匹配到的总记录数
long totalHits = hits.getTotalHits();
//得到匹配度高的文档
SearchHit[] searchHits = hits.getHits();
//日期格式化对象
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for(SearchHit hit:searchHits){
//文档的主键
String id = hit.getId();
//源文档内容
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
//由于前边设置了源文档字段过虑，这时description是取不到的
String description = (String) sourceAsMap.get("description");
//学习模式
String studymodel = (String) sourceAsMap.get("studymodel");
//价格
Double price = (Double) sourceAsMap.get("price");
//日期
Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
System.out.println(studymodel);
System.out.println(description);
}
}布尔查询对应于Lucene的BooleanQuery查询，实现将多个查询组合起来。
-
三个参数：
-
must：文档必须匹配must所包括的查询条件，相当于 “AND”
-
should：文档应该匹配should所包括的查询条件其中的一个或多个，相当于 "OR"
-
must_not：文档不能匹配must_not所包括的该查询条件，相当于“NOT”
-
分别使用must、should、must_not测试下边的查询：
发送：POST http://localhost:9200/xc_course/doc/_search
{
"_source": [
"name",
"studymodel",
"description"
],
"from": 0,
"size": 1,
"query": {
"bool": {
"must": [
{
"multi_match": {
"query": "spring框架",
"minimum_should_match": "50%",
"fields": [
"name^10",
"description"
]
}
},
{
"term": {
"studymodel": "201001"
}
}
]
}
}
}must：表示必须，多个查询条件必须都满足。（通常使用must）
should：表示或者，多个查询条件只要有一个满足即可。
must_not：表示非。
//BoolQuery其实是一个过滤搜索
@Test
public void testBoolQuery() throws IOException, ParseException {
//搜索请求对象
SearchRequest searchRequest = new SearchRequest("xc_course");
//指定类型
searchRequest.types("doc");
//搜索源构建对象
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//boolQuery搜索方式
//先定义一个MultiMatchQuery
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring css", "name", "description")
.minimumShouldMatch("50%")
.field("name", 10);
//再定义一个termQuery
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("studymodel", "201001");
//定义一个boolQuery
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
boolQueryBuilder.must(multiMatchQueryBuilder);
boolQueryBuilder.must(termQueryBuilder);
searchSourceBuilder.query(boolQueryBuilder);
//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});
//向搜索请求对象中设置搜索源
searchRequest.source(searchSourceBuilder);
//执行搜索,向ES发起http请求
SearchResponse searchResponse = client.search(searchRequest);
//搜索结果
SearchHits hits = searchResponse.getHits();
//匹配到的总记录数
long totalHits = hits.getTotalHits();
//得到匹配度高的文档
SearchHit[] searchHits = hits.getHits();
//日期格式化对象
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for(SearchHit hit:searchHits){
//文档的主键
String id = hit.getId();
//源文档内容
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
//由于前边设置了源文档字段过虑，这时description是取不到的
String description = (String) sourceAsMap.get("description");
//学习模式
String studymodel = (String) sourceAsMap.get("studymodel");
//价格
Double price = (Double) sourceAsMap.get("price");
//日期
Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
System.out.println(studymodel);
System.out.println(description);
}
} 过虑是针对搜索的结果进行过虑，过虑器主要判断的是文档是否匹配，不去计算和判断文档的匹配度得分，所以过 虑器性能比查询要高，且方便缓存，推荐尽量使用过虑器去实现查询或者过虑器和查询共同使用。 过虑器在布尔查询中使用，下边是在搜索结果的基础上进行过虑：
{
"_source": [
"name",
"studymodel",
"description",
"price"
],
"query": {
"bool": {
"must": [
{
"multi_match": {
"query": "spring框架",
"minimum_should_match": "50%",
"fields": [
"name^10",
"description"
]
}
}
],
"filter": [
{
"term": {
"studymodel": "201001"
}
},
{
"range": {
"price": {
"gte": 60,
"lte": 100
}
}
}
]
}
}
}range：范围过虑，保留大于等于60 并且小于等于100的记录。
term：项匹配过虑，保留studymodel等于"201001"的记录。
注意：range和term一次只能对一个Field设置范围过虑。
//filter
@Test
public void testFilter() throws IOException, ParseException {
//搜索请求对象
SearchRequest searchRequest = new SearchRequest("xc_course");
//指定类型
searchRequest.types("doc");
//搜索源构建对象
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//boolQuery搜索方式
//先定义一个MultiMatchQuery
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring css", "name", "description")
.minimumShouldMatch("50%")
.field("name", 10);
//定义一个boolQuery
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
boolQueryBuilder.must(multiMatchQueryBuilder);
//定义过虑器
boolQueryBuilder.filter(QueryBuilders.termQuery("studymodel","201001"));
boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(90).lte(100));
searchSourceBuilder.query(boolQueryBuilder);
//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});
//向搜索请求对象中设置搜索源
searchRequest.source(searchSourceBuilder);
//执行搜索,向ES发起http请求
SearchResponse searchResponse = client.search(searchRequest);
//搜索结果
SearchHits hits = searchResponse.getHits();
//匹配到的总记录数
long totalHits = hits.getTotalHits();
//得到匹配度高的文档
SearchHit[] searchHits = hits.getHits();
//日期格式化对象
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for(SearchHit hit:searchHits){
//文档的主键
String id = hit.getId();
//源文档内容
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
//由于前边设置了源文档字段过虑，这时description是取不到的
String description = (String) sourceAsMap.get("description");
//学习模式
String studymodel = (String) sourceAsMap.get("studymodel");
//价格
Double price = (Double) sourceAsMap.get("price");
//日期
Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
System.out.println(studymodel);
System.out.println(description);
}
}可以在字段上添加一个或多个排序，支持在keyword、date、flfloat等类型上添加，text类型的字段上不允许添加排
序。
发送 POST http://localhost:9200/xc_course/doc/_search
过虑0--10元价格范围的文档，并且对结果进行排序，先按studymodel降序，再按价格升序
{
"_source": [
"name",
"studymodel",
"description",
"price"
],
"query": {
"bool": {
"filter": [
{
"range": {
"price": {
"gte": 0,
"lte": 100
}
}
}
]
}
},
"sort": [
{
"studymodel": "desc"
},
{
"price": "asc"
}
]
}//Sort
@Test
public void testSort() throws IOException, ParseException {
//搜索请求对象
SearchRequest searchRequest = new SearchRequest("xc_course");
//指定类型
searchRequest.types("doc");
//搜索源构建对象
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//boolQuery搜索方式
//定义一个boolQuery
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
//定义过虑器
boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(0).lte(100));
searchSourceBuilder.query(boolQueryBuilder);
//添加排序
searchSourceBuilder.sort("studymodel", SortOrder.DESC);
searchSourceBuilder.sort("price", SortOrder.ASC);
//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});
//向搜索请求对象中设置搜索源
searchRequest.source(searchSourceBuilder);
//执行搜索,向ES发起http请求
SearchResponse searchResponse = client.search(searchRequest);
//搜索结果
SearchHits hits = searchResponse.getHits();
//匹配到的总记录数
long totalHits = hits.getTotalHits();
//得到匹配度高的文档
SearchHit[] searchHits = hits.getHits();
//日期格式化对象
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for(SearchHit hit:searchHits){
//文档的主键
String id = hit.getId();
//源文档内容
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
//由于前边设置了源文档字段过虑，这时description是取不到的
String description = (String) sourceAsMap.get("description");
//学习模式
String studymodel = (String) sourceAsMap.get("studymodel");
//价格
Double price = (Double) sourceAsMap.get("price");
//日期
Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
System.out.println(studymodel);
System.out.println(description);
}
}高亮显示可以将搜索结果一个或多个字突出显示，以便向用户展示匹配关键字的位置。
在搜索语句中添加highlight即可实现，如下：
Post： http://127.0.0.1:9200/xc_course/doc/_search
{
"_source": [
"name",
"studymodel",
"description",
"price"
],
"query": {
"bool": {
"must": [
{
"multi_match": {
"query": "开发框架",
"minimum_should_match": "50%",
"fields": [
"name^10",
"description"
],
"type": "best_fields"
}
}
],
"filter": [
{
"range": {
"price": {
"gte": 0,
"lte": 100
}
}
}
]
}
},
"sort": [
{
"price": "asc"
}
],
"highlight": {
"pre_tags": [
"<tag1>"
],
"post_tags": [
"</tag2>"
],
"fields": {
"name": {},
"description": {}
}
}
} //Highlight
@Test
public void testHighlight() throws IOException, ParseException {
//搜索请求对象
SearchRequest searchRequest = new SearchRequest("xc_course");
//指定类型
searchRequest.types("doc");
//搜索源构建对象
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//boolQuery搜索方式
//先定义一个MultiMatchQuery
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("开发框架", "name", "description")
.minimumShouldMatch("50%")
.field("name", 10);
//定义一个boolQuery
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
boolQueryBuilder.must(multiMatchQueryBuilder);
//定义过虑器
boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(0).lte(100));
searchSourceBuilder.query(boolQueryBuilder);
//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});
//设置高亮
HighlightBuilder highlightBuilder = new HighlightBuilder();
highlightBuilder.preTags("<tag>");
highlightBuilder.postTags("</tag>");
highlightBuilder.fields().add(new HighlightBuilder.Field("name"));
highlightBuilder.fields().add(new HighlightBuilder.Field("description"));
searchSourceBuilder.highlighter(highlightBuilder);
//向搜索请求对象中设置搜索源
searchRequest.source(searchSourceBuilder);
//执行搜索,向ES发起http请求
SearchResponse searchResponse = client.search(searchRequest);
//搜索结果
SearchHits hits = searchResponse.getHits();
//匹配到的总记录数
long totalHits = hits.getTotalHits();
//得到匹配度高的文档
SearchHit[] searchHits = hits.getHits();
//日期格式化对象
// SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss.SSS Z");
for(SearchHit hit:searchHits){
//文档的主键
String id = hit.getId();
//源文档内容
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
//源文档的name字段内容
String name = (String) sourceAsMap.get("name");
//取出高亮字段
Map<String, HighlightField> highlightFields = hit.getHighlightFields();
if(highlightFields!=null){
//取出name高亮字段
HighlightField nameHighlightField = highlightFields.get("name");
if(nameHighlightField!=null){
Text[] fragments = nameHighlightField.getFragments();
StringBuffer stringBuffer = new StringBuffer();
for(Text text:fragments){
stringBuffer.append(text);
}
name = stringBuffer.toString();
}
}
//由于前边设置了源文档字段过虑，这时description是取不到的
String description = (String) sourceAsMap.get("description");
//学习模式
String studymodel = (String) sourceAsMap.get("studymodel");
//价格
Double price = (Double) sourceAsMap.get("price");
//日期
Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
System.out.println(studymodel);
System.out.println(description);
}
}