实验环境
- ES版本:5.3.0
- spring bt版本:1.5.9
首先当然需要安装好elastic search环境,最好再安装上可视化插件 elasticsearch-head来便于我们直观地查看数据。
Spring工程创建
这部分没有特殊要交代的,但有几个注意点一定要当心
- 注意在新建项目时记得勾选web和NoSQL中的Elasticsearch依赖,来张图说明一下吧:
项目自动生成以后pom.xml中会自动添加spring-boot-starter-data-elasticsearch
的依赖:
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>1234
- 本项目中我们使用开源的基于restful的es java客户端
jest
,所以还需要在pom.xml中添加jest
依赖:
<dependency>
<groupId>io.searchbox</groupId>
<artifactId>jest</artifactId>
</dependency>1234
- 除此之外还必须添加
jna
的依赖:
<dependency>
<groupId>net.java.dev.jna</groupId>
<artifactId>jna</artifactId>
</dependency>1234
否则启动spring项目的时候会报JNA not found. native methods will be disabled.
的错误:
- 项目的配置文件application.yml中需要把es服务器地址配置对
server:
port: 6325
spring:
elasticsearch:
jest:
uris:
- http://113.209.119.170:9200 # ES服务器的地址!
read-timeout: 5000123456789
代码组织
我的项目代码组织如下:
各部分代码详解如下,注释都有:
- Entity.java
package com.hansonwang99.springboot_es_demo.entity;
import java.io.Serializable;
import org.springframework.data.elasticsearch.annotations.Document;
public class Entity implements Serializable{
private static final long serialVersionUID = -763638353551774166L;
public static final String INDEX_NAME = "index_entity";
public static final String TYPE = "tstype";
private Long id;
private String name;
public Entity() {
super();
}
public Entity(Long id, String name) {
this.id = id;
this.name = name;
}
public Long getId() {
return id;
}
public void setId(Long id) {
this.id = id;
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
}
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- TestService.java
package com.hansonwang99.springboot_es_demo.service;
import com.hansonwang99.springboot_es_demo.entity.Entity;
import java.util.List;
public interface TestService {
void saveEntity(Entity entity);
void saveEntity(List<Entity> entityList);
List<Entity> searchEntity(String searchContent);
}1234567891011121314
- TestServiceImpl.java
package com.hansonwang99.springboot_es_demo.service.impl;
import java.io.IOException;
import java.util.List;
import com.hansonwang99.springboot_es_demo.entity.Entity;
import com.hansonwang99.springboot_es_demo.service.TestService;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;
import io.searchbox.client.JestClient;
import io.searchbox.client.JestResult;
import io.searchbox.core.Bulk;
import io.searchbox.core.Index;
import io.searchbox.core.Search;
@Service
public class TestServiceImpl implements TestService {
private static final Logger LOGGER = LoggerFactory.getLogger(TestServiceImpl.class);
@Autowired
private JestClient jestClient;
@Override
public void saveEntity(Entity entity) {
Index index = new Index.Builder(entity).index(Entity.INDEX_NAME).type(Entity.TYPE).build();
try {
jestClient.execute(index);
LOGGER.info("ES 插入完成");
} catch (IOException e) {
e.printStackTrace();
LOGGER.error(e.getMessage());
}
}
/**
* 批量保存内容到ES
*/
@Override
public void saveEntity(List<Entity> entityList) {
Bulk.Builder bulk = new Bulk.Builder();
for(Entity entity : entityList) {
Index index = new Index.Builder(entity).index(Entity.INDEX_NAME).type(Entity.TYPE).build();
bulk.addAction(index);
}
try {
jestClient.execute(bulk.build());
LOGGER.info("ES 插入完成");
} catch (IOException e) {
e.printStackTrace();
LOGGER.error(e.getMessage());
}
}
/**
* 在ES中搜索内容
*/
@Override
public List<Entity> searchEntity(String searchContent){
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//searchSourceBuilder.query(QueryBuilders.queryStringQuery(searchContent));
//searchSourceBuilder.field("name");
searchSourceBuilder.query(QueryBuilders.matchQuery("name",searchContent));
Search search = new Search.Builder(searchSourceBuilder.toString())
.addIndex(Entity.INDEX_NAME).addType(Entity.TYPE).build();
try {
JestResult result = jestClient.execute(search);
return result.getSourceAsObjectList(Entity.class);
} catch (IOException e) {
LOGGER.error(e.getMessage());
e.printStackTrace();
}
return null;
}
}
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- EntityController.java
package com.hansonwang99.springboot_es_demo.controller;
import java.util.ArrayList;
import java.util.List;
import com.hansonwang99.springboot_es_demo.entity.Entity;
import com.hansonwang99.springboot_es_demo.service.TestService;
import org.apache.commons.lang.StringUtils;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestMethod;
import org.springframework.web.bind.annotation.RestController;
@RestController
@RequestMapping("/entityController")
public class EntityController {
@Autowired
TestService cityESService;
@RequestMapping(value="/save", method=RequestMethod.GET)
public String save(long id, String name) {
System.out.println("save 接口");
if(id>0 && StringUtils.isNotEmpty(name)) {
Entity newEntity = new Entity(id,name);
List<Entity> addList = new ArrayList<Entity>();
addList.add(newEntity);
cityESService.saveEntity(addList);
return "OK";
}else {
return "Bad input value";
}
}
@RequestMapping(value="/search", method=RequestMethod.GET)
public List<Entity> save(String name) {
List<Entity> entityList = null;
if(StringUtils.isNotEmpty(name)) {
entityList = cityESService.searchEntity(name);
}
return entityList;
}
}1234567891011121314151617181920212223242526272829303132333435363738394041424344
实际实验
增加几条数据,可以使用postman工具,也可以直接在浏览器中输入,如增加以下5条数据:
http://localhost:6325/entityController/save?id=1&name=南京中山陵
http://localhost:6325/entityController/save?id=2&name=中国南京师范大学
http://localhost:6325/entityController/save?id=3&name=南京夫子庙
http://localhost:6325/entityController/save?id=4&name=杭州也非常不错
http://localhost:6325/entityController/save?id=5&name=中国南边好像没有叫带京字的城市了12345
数据插入效果如下(使用可视化插件elasticsearch-head观看):
我们来做一下搜索的测试:例如我要搜索关键字“南京”
我们在浏览器中输入:
http://localhost:6325/entityController/search?name=南京1
搜索结果如下:
刚才插入的5条记录中包含关键字“南京”的四条记录均被搜索出来了!
当然这里用的是standard分词方式,将每个中文都作为了一个term,凡是包含“南”、“京”关键字的记录都被搜索了出来,只是评分不同而已,当然还有其他的一些分词方式,此时需要其他分词插件的支持,此处暂不涉及,后文中再做探索。