微服务框架
【SpringCloud+RabbitMQ+Docker+Redis+搜索+分布式，系统详解springcloud微服务技术栈课程|黑马程序员Java微服务】
SpringCloud微服务架构
文章目录
- 微服务框架
- SpringCloud微服务架构
- 27 自动补全
- 27.4 修改酒店索引库数据结构
- 27.4.1 案例
27 自动补全
27.4 修改酒店索引库数据结构
27.4.1 案例
案例：实现hotel索引库的自动补全、拼音搜索功能
实现思路如下：
- 修改hotel索引库结构，设置自定义拼音分词器
当前的hotel 数据结构
{
"hotel" : {
"mappings" : {
"properties" : {
"address" : {
"type" : "keyword",
"index" : false
},
"all" : {
"type" : "text",
"analyzer" : "ik_max_word"
},
"brand" : {
"type" : "keyword",
"copy_to" : [
"all"
]
},
"business" : {
"type" : "keyword",
"copy_to" : [
"all"
]
},
"city" : {
"type" : "keyword"
},
"id" : {
"type" : "keyword"
},
"isAD" : {
"type" : "boolean"
},
"location" : {
"type" : "geo_point"
},
"name" : {
"type" : "text",
"copy_to" : [
"all"
],
"analyzer" : "ik_max_word"
},
"pic" : {
"type" : "keyword",
"index" : false
},
"price" : {
"type" : "integer"
},
"score" : {
"type" : "integer"
},
"starName" : {
"type" : "keyword"
}
}
}
}
}
可以看到 all 和 name 是text的
而且分词器也是默认的ik_max_word
改成下面这样
// 酒店数据索引库
PUT /hotel
{
"settings": {
"analysis": {
"analyzer": {
"text_anlyzer": {
"tokenizer": "ik_max_word",
"filter": "py"
},
"completion_analyzer": {
"tokenizer": "keyword",
"filter": "py"
}
},
"filter": {
"py": {
"type": "pinyin",
"keep_full_pinyin": false,
"keep_joined_full_pinyin": true,
"keep_original": true,
"limit_first_letter_length": 16,
"remove_duplicated_term": true,
"none_chinese_pinyin_tokenize": false
}
}
}
},
"mappings": {
"properties": {
"id":{
"type": "keyword"
},
"name":{
"type": "text",
"analyzer": "text_anlyzer",
"search_analyzer": "ik_smart",
"copy_to": "all"
},
"address":{
"type": "keyword",
"index": false
},
"price":{
"type": "integer"
},
"score":{
"type": "integer"
},
"brand":{
"type": "keyword",
"copy_to": "all"
},
"city":{
"type": "keyword"
},
"starName":{
"type": "keyword"
},
"business":{
"type": "keyword",
"copy_to": "all"
},
"location":{
"type": "geo_point"
},
"pic":{
"type": "keyword",
"index": false
},
"all":{
"type": "text",
"analyzer": "text_anlyzer",
"search_analyzer": "ik_smart"
},
"suggestion":{
"type": "completion",
"analyzer": "completion_analyzer"
}
}
}
}
- settings：定义索引库的分词器
- mappings：定义字段
贴到kibana 中
先把之前的hotel 索引库删掉
然后直接运行创建
OK了
-
修改索引库的name、all字段，使用自定义分词器
-
索引库添加一个新字段suggestion，类型为completion类型，使用自定义的分词器
-
给HotelDoc类添加suggestion字段，内容包含brand、business
package cn.itcast.hotel.pojo;
import lombok.Data;
import lombok.NoArgsConstructor;
import java.util.Arrays;
import java.util.List;
/**
* ClassName: HotelDoc
* date: 2022/11/1 10:51
*
* @author DingJiaxiong
*/
@Data
@NoArgsConstructor
public class HotelDoc {
private Long id;
private String name;
private String address;
private Integer price;
private Integer score;
private String brand;
private String city;
private String starName;
private String business;
private String location;
private String pic;
private Object distance;
private Boolean isAD;
private List<String> suggestion;
public HotelDoc(Hotel hotel) {
this.id = hotel.getId();
this.name = hotel.getName();
this.address = hotel.getAddress();
this.price = hotel.getPrice();
this.score = hotel.getScore();
this.brand = hotel.getBrand();
this.city = hotel.getCity();
this.starName = hotel.getStarName();
this.business = hotel.getBusiness();
this.location = hotel.getLatitude() + ", " + hotel.getLongitude();
this.pic = hotel.getPic();
this.suggestion = Arrays.asList(this.brand , this.business);
}
}
- 重新导入数据到hotel库
//批量插入文档
@Test
void testBulkRequest() throws IOException {
//批量查询酒店数据
List<Hotel> hotels = hotelService.list();
//1. 创建Request
BulkRequest request = new BulkRequest();
//2. 准备参数，添加多个新增的Request
for (Hotel hotel : hotels) {
//转换为文档类型HotelDoc
HotelDoc hotelDoc = new HotelDoc(hotel);
//创建新增文档的Request 对象
request.add(new IndexRequest("hotel")
.id(hotelDoc.getId().toString())
.source(JSON.toJSONString(hotelDoc),XContentType.JSON));
}
//3. 发送请求
client.bulk(request , RequestOptions.DEFAULT);
}
运行结果
OK，数据库中201 条数据就全部插入成功了
注意：name、all是可分词的，自动补全的brand、business是不可分词的，要使用不同的分词器组合
打开kibana ，看看
OK，没问题
而且命中的结果中的suggestion 字段包含了品牌brand 和 商业圈两个信息
但是有些数据会有些问题
例如这个
其实它是有两个商圈，江湾或者五角场
这种数据将来进行提示的时候就只能根据 江来提示了，搞不到五
【所以需要解决一下】【这种应该拆分成两个词条】
老师的是用 / 划分的，但是笔者拿到的资料不一样
它有些是用的 / ，有些是 、【为了和老师的一致，笔者手动把这些、 改成了 /】
改一下Java 代码
package cn.itcast.hotel.pojo;
import lombok.Data;
import lombok.NoArgsConstructor;
import org.springframework.util.CollectionUtils;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
/**
* ClassName: HotelDoc
* date: 2022/11/1 10:51
*
* @author DingJiaxiong
*/
@Data
@NoArgsConstructor
public class HotelDoc {
private Long id;
private String name;
private String address;
private Integer price;
private Integer score;
private String brand;
private String city;
private String starName;
private String business;
private String location;
private String pic;
private Object distance;
private Boolean isAD;
private List<String> suggestion;
public HotelDoc(Hotel hotel) {
this.id = hotel.getId();
this.name = hotel.getName();
this.address = hotel.getAddress();
this.price = hotel.getPrice();
this.score = hotel.getScore();
this.brand = hotel.getBrand();
this.city = hotel.getCity();
this.starName = hotel.getStarName();
this.business = hotel.getBusiness();
this.location = hotel.getLatitude() + ", " + hotel.getLongitude();
this.pic = hotel.getPic();
if (this.business.contains("/")){
//business 有多个值，需要进行切割
String[] arr = this.business.split("/");
//添加元素
this.suggestion = new ArrayList<>();
this.suggestion.add(this.brand);
Collections.addAll(this.suggestion,arr);
}else {
this.suggestion = Arrays.asList(this.brand , this.business);
}
}
}
重新进行批量导入
OK，看看kibana
OK，这下就拆开了，直接测试自动补全查询
GET /hotel/_search
{
"suggest": {
"suggestions": {
"text": "h",
"completion": {
"field": "suggestion",
"skip_duplicates": true,
"size": 10
}
}
}
}
运行结果
OK， 没问题
换成s
换成sd
没问题【酒店数据的修改工作就完成了】
