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title

搭建工程

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

Maven依赖

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>

application.properties

#elasticsearch配置
anshe.elasticsearch.hostlist=${eshostlist:你的IP地址:9200}

配置类

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;
    }
}

主启动类

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);
    }

}

索引管理

创建索引库

API

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"
		}
	}
}

Java客户端

@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);

}

删除索引库

API

DELETE http://['你自己的Ip加Port']/test
{
    "acknowledged": true
}

Java客户端

//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);

}

添加文档

API

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
}

Java客户端

//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);

}

查询文档

API

格式如下： GET /{index}/{type}/{id}

Java客户端

//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);
}

更新文档

API

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Spring Boot 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
	}
}

Java客户端

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);
}

删除文档

API

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

Java客户端

//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。

-----下面是DSL搜索的内容-----

DSL搜索环境准备

创建映射

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"
		}
	}
}

插入原始数据

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。

查询所有文档

API

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。

Java客户端

	 @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);
        }

    }

分页查询

API

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"
	]
}

Java客户端

//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

API

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。

Java客户端

//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);
    }

}

根据id精确匹配

API

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"
			]
		}
	}
}

Java客户端

//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

API

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。

Java客户端

//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);
    }

}

multi Query

API

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。

Java客户端

//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

API

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。

Java客户端

//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);
    }

}

过虑器

API

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。

Java客户端

//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);
    }

}

排序

API

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"
		}
	]
}

Java客户端

//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

API

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": {}
		}
	}
}

Java客户端

  //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);
        }

    }

47 KiB Raw Blame History Unescape Escape

搭建工程

Maven依赖

application.properties

配置类

主启动类

索引管理

创建索引库

API

Java客户端

删除索引库

API

Java客户端

添加文档

API

Java客户端

查询文档

API

Java客户端

更新文档

API

Java客户端

删除文档

API

Java客户端

-----下面是DSL搜索的内容-----

DSL搜索环境准备

创建映射

插入原始数据

查询所有文档

API

Java客户端

分页查询

API

Java客户端

Term Query

API

Java客户端

根据id精确匹配

API

Java客户端

match Query

API

Java客户端

multi Query

API

Java客户端

布尔查询

API

Java客户端

过虑器

API

Java客户端

排序

API

Java客户端

高亮显示

API

Java客户端

47 KiB

Raw Blame History