电商项目高级篇

高级篇"/>

电商项目高级篇

电商项目高级篇-02 elasticsearch-下

• • 4.2、返回指定字段
  • 4.3、match查询
  • 4.4、短语匹配：match_phrase(用于短语匹配。包含匹配)
  • 4.5、多字段匹配：multi_match
  • 4.6、bool复合查询
  • 4.7、filter过滤查询（不贡献相关性得分）
  • 4.8、term（非文本检索）
  • 4.9、执行聚合
  • 4.10、映射
  • 4.11、ik分词器
  • 4.12、自定义分词
  • • 4.12.1、linux下安装nginx
• 5、java集成es
• • 5.1、模块搭建
  • 5.2、es index 保存数据

4.2、返回指定字段

返回单个字段

GET bank/_search
{"query": {"match_all": {}}, "sort": [{"balance": {"order": "desc"}}], "from": 5, "size": 5, "_source": "balance"
}

返回多个字段：

GET bank/_search
{"query": {"match_all": {}}, "sort": [{"balance": {"order": "desc"}}], "from": 5, "size": 5, "_source": ["balance","age"]
}

4.3、match查询

精确查询（对非字符串）

GET bank/_search
{"query": {"match": {"account_number": "20"}}
}

模糊查询（对字符串）全文检索

GET bank/_search
{"query": {"match": {"address": "kings"}}
}

###根据评分倒排索引

GET bank/_search
{
"query": {
"match": {
"address": "mill road"
}
}
}

得益于倒排索引机制。会分词匹配。查询出结果

4.4、短语匹配：match_phrase(用于短语匹配。包含匹配)

GET bank/_search
{
"query": {
"match_phrase": {
"address": "mill road"
}
}
}

###字段.keyword相当于精确匹配

GET bank/_search
{
"query": {
"match": {
"address.keyword": "mill road"
}
}
}

4.5、多字段匹配：multi_match

GET bank/_search
{
"query": {
"multi_match": {
"query": "mill",
"fields": ["state","address"]
}
}
}

state或者address中包含mill的

4.6、bool复合查询

GET bank/_search
{"query": {"bool": {"must": [{"match": {"address": "mill"}},{"match": {"gender": "M"}}],"should": [{"match": {"address": "lane"}}],"must_not": [{"match": {"email": "baluba"}}]}}
}

查询一定是地址包含mill和性别是M的，一定不是email包含baluba的，可以是address包含lane的结果集

4.7、filter过滤查询（不贡献相关性得分）

GET bank/_search
{"query": {"bool": {"filter": {"range": {"balance": {"gte": 10000,"lte": 20000}}}}}
}

GET bank/_search
{"query": {"bool": {"must": [{"match": {"address": "mill"}}],"filter": {"range": {"balance": {"gte": 10000,"lte": 20000}}}}}
}

4.8、term（非文本检索）

match 可适用于文本检索。term适用于非文本检索

GET bank/_search
{
"query": {
"bool": {
"must": [
{"term": {
"age": {
"value": "28"
}
}},
{"match": {
"address": "990 Mill Road"
}}
]
}
}
}

4.9、执行聚合

需求一：搜索 address 中包含 mill 的所有人 的年龄分布以及平均年龄，但不显示这些人的详情

GET bank/_search
{"query": {"match": {"address": "mill"}},"aggs": {"group_by_state": {"terms": {"field": "age"}},"avg_age": {"avg": {"field": "age"}}},"size": 0
}

aggs:聚合函数
terms：分布
avg：平均
size：0 不显示hits详情

需求二：按照年龄聚合，并且请求这些年龄段的这些人的平均薪资

会用到子聚合

GET bank/_search
{"query": {"match_all": {}},"aggs": {"age_avg": {"terms": {"field": "age","size": 1000}}}
}

子聚合：

GET bank/_search
{"query": {"match_all": {}},"aggs": {"age_avg": {"terms": {"field": "age","size": 1000},"aggs":{"balance_avg":{"avg": {"field": "balance"}}}}
}
}

需求三：查出所有年龄分布，并且这些年龄段中 M 的平均薪资和 F 的平均薪资以及这个年龄
段的总体平均薪资

多重子聚合

GET bank/_search
{"query": {"match_all": {}},"aggs": {"age_agg": {"terms": {"field": "age","size": 100},"aggs": {"gender_agg": {"terms": {"field": "gender.keyword","size": 100},"aggs": {"balance_avg": {"avg": {"field": "balance"}}}},"balance_avg": {"avg": {"field": "balance"}}}}}
}

4.10、映射

查询映射

GET /bank/_mapping

修改映射

PUT /my-index
{"mappings": {"properties": {"age": {"type": "integer"},"email": {"type": "keyword"},"name": {"type": "text"}}}
}

添加新的字段映射

PUT /my-index/_mapping
{"properties": {"employee-id": {"type": "keyword","index": false}}
}

更新映射
对于已经存在的映射字段，我们不能更新。更新必须创建新的索引进行数据迁移

##数据迁移

1、获取原来银行的映射关系

GET /bank/_mapping

{"bank" : {"mappings" : {"properties" : {"account_number" : {"type" : "long"},"address" : {"type" : "text","fields" : {"keyword" : {"type" : "keyword","ignore_above" : 256}}},"age" : {"type" : "long"},"balance" : {"type" : "long"},"city" : {"type" : "text","fields" : {"keyword" : {"type" : "keyword","ignore_above" : 256}}},"email" : {"type" : "text","fields" : {"keyword" : {"type" : "keyword","ignore_above" : 256}}},"employer" : {"type" : "text","fields" : {"keyword" : {"type" : "keyword","ignore_above" : 256}}},"firstname" : {"type" : "text","fields" : {"keyword" : {"type" : "keyword","ignore_above" : 256}}},"gender" : {"type" : "text","fields" : {"keyword" : {"type" : "keyword","ignore_above" : 256}}},"lastname" : {"type" : "text","fields" : {"keyword" : {"type" : "keyword","ignore_above" : 256}}},"state" : {"type" : "text","fields" : {"keyword" : {"type" : "keyword","ignore_above" : 256}}}}}}
}

2、创建出新银行映射规则

PUT /newbank
{"mappings": {"properties": {"account_number": {"type": "long"},"address": {"type": "text"},"age": {"type": "integer"},"balance": {"type": "long"},"city": {"type": "keyword"},"email": {"type": "keyword"},"employer": {"type": "keyword"},"gender": {"type": "keyword"},"lastname": {"type": "text","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"state": {"type": "keyword"}}}
}

3、查询新规则

GET /newbank/_mapping

4、数据迁移

POST _reindex
{"source": {"index": "bank"},"dest": {"index": "newbank"}
}

5、查询新索引

GET /newbank/_search

4.11、ik分词器

标准分词器不好用，是专门用来分割英文的。不太支持中文（它会分成一个一个字的）
比如：

POST /_analyze
{"analyzer": "standard","text":"今天的清蒸鲈鱼蒸得还行"
}

下载ik分词器
添加链接描述

复制到linux这个文件夹下

确认是否安装好分词器

进到容器内部，然后输入命令：

elasticsearch plugin list

出现ik说明安装成功。

然后重启容器

然后执行这段代码：

POST _analyze
{"analyzer": "ik_smart","text": "今天的清蒸鲈鱼蒸得还行"
}

目前还稍微比较智能化一些了

但是实际上不能满足网络上新的单词搜索

POST /_analyze
{"analyzer": "ik_max_word","text": "你在干嘛哎哟"
}

4.12、自定义分词

4.12.1、linux下安装nginx

1、暂时先启动一个nginx

docker run -p 80:80 --name nginx -d nginx:1.10

2、将容器内的配置文件拷贝到当前目录

docker container cp nginx:/etc/nginx .

3、修改文件名称

cd ../
mv nginx conf

4、把这个 conf 移动到/mydata/nginx 下

5、执行命令删除原容器：docker rm $ContainerId

6、创建新的 nginx

docker run -p 80:80 --name nginx \
-v /mydata/nginx/html:/usr/share/nginx/html \
-v /mydata/nginx/logs:/var/log/nginx \
-v /mydata/nginx/conf:/etc/nginx \
-d nginx:1.10

将index.html放到html文件里。就可以访问nginx首页了

##7、将所有es关于分词器的内容，nginx这边新建文件夹保管


8、访问该fcword.txt
可以访问

###9、ik分词器绑定fcword.txt

cd /mydata/elasticsearch/plugins/ik/config

vi IKAnalyzer.cfg.xml

开启远程配置

虚拟机地址/es/fcword.txt

分词前：

重启容器实例

分词后：

已达到分词效果

5、java集成es

5.1、模块搭建

新建module

创建一个springboot模块


pom.xml

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns=".0.0" xmlns:xsi=""xsi:schemaLocation=".0.0 .0.0.xsd"><modelVersion>4.0.0</modelVersion><parent><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-parent</artifactId><version>2.1.8.RELEASE</version><relativePath/> <!-- lookup parent from repository --></parent><groupId>com.ljs.gulimall</groupId><artifactId>gulimall-search</artifactId><version>0.0.1-SNAPSHOT</version><name>gulimall-search</name><description>检索服务</description><properties><java.version>1.8</java.version><elasticsearch.version>7.4.2</elasticsearch.version></properties><dependencies><!--导入common--><dependency><groupId>com.ljs.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><!--导入es的高阶api--><dependency><groupId>org.elasticsearch.client</groupId><artifactId>elasticsearch-rest-high-level-client</artifactId><version>${elasticsearch.version}</version></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-test</artifactId><scope>test</scope></dependency></dependencies><build><plugins><plugin><groupId>org.springframework.boot</groupId><artifactId>spring-boot-maven-plugin</artifactId></plugin></plugins></build></project>

application.properties

spring.cloud.nacos.discovery.server-addr=127.0.0.1:8848
spring.application.name=gulimall-search

GulimallSearchApplication

package com.ljs.gulimall.search;import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
import org.springframework.cloud.client.discovery.EnableDiscoveryClient;@EnableDiscoveryClient
@SpringBootApplication(exclude = DataSourceAutoConfiguration.class)
public class GulimallSearchApplication {public static void main(String[] args) {SpringApplication.run(GulimallSearchApplication.class, args);}}

GulimallElasticsearchConfig

package com.ljs.gulimall.search.config;import org.apache.http.HttpHost;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;@Configuration
public class GulimallElasticsearchConfig {@Beanpublic RestHighLevelClient getClient(){return new RestHighLevelClient(RestClient.builder(new HttpHost("虚拟机ip",9200,"http")));}}

测试类
GulimallSearchApplicationTests

package com.ljs.gulimall.search;import org.elasticsearch.client.RestHighLevelClient;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.test.context.junit4.SpringRunner;@RunWith(SpringRunner.class)
@SpringBootTest
public class GulimallSearchApplicationTests {@Autowiredprivate RestHighLevelClient client;@Testpublic void contextLoads() {System.out.println(client);}}

运行结果：
已经获取到bean容器的实例

5.2、es index 保存数据

GET /user/_search

没有user这个索引

GulimallElasticsearchConfig

public static final RequestOptions COMMON_OPTIONS;static {RequestOptions.Builder builder = RequestOptions.DEFAULT.toBuilder();COMMON_OPTIONS = builder.build();}

GulimallSearchApplicationTests

 @Testpublic void indexData() throws IOException {// 创建indexRequest对象user index索引IndexRequest indexRequest = new IndexRequest("user");// 设置索引idindexRequest.id("1");User user = new User();user.setAge(18);user.setGender("男");user.setName("帅淞");// 要保存的内容转成JSON StringString jsonString = JSON.toJSONString(user);// 将保存的内容放到indexRequest对象indexRequest.source(jsonString, XContentType.JSON);// 执行操作IndexResponse index = client.index(indexRequest, GulimallElasticsearchConfig.COMMON_OPTIONS);// 提取响应数据System.out.println(index);}@Dataclass User{private Integer age;private String name;private String gender;}

执行完毕说明保存成功。

再次查询。发现有值