谷粒商城--分布式高级篇P102~P128

由于学习的时间也比较少，只有周六周末才有时间出来学习总结，所以一篇一篇慢慢更新吧，本次总结内容为Elasticsearch（相关内容：kibana，es，nginx，ik分词器）

【谷粒商城--分布式基础篇P1~P27】: https://blog.csdn.net/Empire_ing/article/details/118860147

【谷粒商城--分布式基础篇P28~P101】https://mp.weixin.qq.com/s/5kvXjLNyVn-GBhNMWyJdpg

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目录

• 1.ElasticSearch与kibana
  • 1.1.基本概念
  • 1.2 安装es与kibana
  • 1.3 Nginx安装
  • 1.4 Ik中文分词器
• 2.SpringBoot整合Es
  • 2.1.环境配置
  • 2.2.搜索实现

1.ElasticSearch与kibana

​ 内容概况：es、kibana、ik相关软件于centos中docker的下载与配置使用。本次安装最大感悟就是docker太好用了，真的好强。

​ 之前也写过一篇关于es文章实例：

​ SpringBoot整合es实现高亮搜索：https://www.cnblogs.com/meditation5201314/p/14801585.html

1.1.基本概念

​ 索引index：类似于数据库

​ 类型type：类似于库中的表

​ 文档document：类似于表的每一行

​ 方法/属性：类似于每一行的字段

1.2 安装es与kibana

​ 1. ES访问地址：http://公网IP:9200/

# 1、下载包
docker pull elasticsearch:7.4.2

# 2、配置es文件映射
# 将docker里的目录挂载到linux的/mydata目录中
# 修改/mydata就可以改掉docker里的
mkdir -p /mydata/elasticsearch/config
mkdir -p /mydata/elasticsearch/data
# es可以被远程任何机器访问
echo "http.host: 0.0.0.0" >/mydata/elasticsearch/config/elasticsearch.yml
# 递归更改权限，es需要访问
chmod -R 777 /mydata/elasticsearch/

# 3、启动es
# 9200是用户交互端口 9300是集群心跳端口  -e指定是单阶段运行  -e指定占用的内存大小，生产时可以设置32G
docker run --name elasticsearch -p 9200:9200 -p 9300:9300 \
-e  "discovery.type=single-node" \
-e ES_JAVA_OPTS="-Xms64m -Xmx512m" \
-v /mydata/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml \
-v /mydata/elasticsearch/data:/usr/share/elasticsearch/data \
-v  /mydata/elasticsearch/plugins:/usr/share/elasticsearch/plugins \
-d elasticsearch:7.4.2 

# 4、设置开机启动elasticsearch
docker update elasticsearch --restart=always

1. kibana下载、配置、启动

Kibana访问地址：http://公网IP:5601/

# 1、下载包
docker pull kibana:7.4.2

# 2、启动es（这里填自己的IP地址）
docker run --name kibana -e ELASTICSEARCH_HOSTS=http://公网IP:9200 -p 5601:5601 -d kibana:7.4.2 

# 3、设置开机启动kibana
docker update kibana  --restart=always

​ 访问地址：

查看es的node节点：http://公网IP:9200/_cat/nodes

查看es的helth健康状态：http://公网IP:9200/_cat/health

查看es的master主节点：http://公网IP:9200/_cat/master

查看es的索引主节点：http://公网IP:9200/_cat/indices

1.3 Nginx安装

docker run -p80:80 --name nginx -d nginx:1.10   

mkdir -p /mydata/nginx/html
mkdir -p /mydata/nginx/logs
mkdir -p /mydata/nginx/conf
docker container cp nginx:/etc/nginx/*  /mydata/nginx/conf/
#由于拷贝完成后会在config中存在一个nginx文件夹，所以需要将它的内容移动到conf中
mv /mydata/nginx/conf/nginx/* /mydata/nginx/conf/
rm -rf /mydata/nginx/conf/nginx

docker stop nginx
docker rm 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
docker update nginx --restart=always

1.4 Ik中文分词器

​ 在elasticsearch/plugins目录下下载解压ik分词器后重启即可

#下载ik分词器
wget https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.4.2/elasticsearch-analysis-ik-7.4.2.zip
#解压并重命名ik
unzip elasticsearch-analysis-ik-7.4.2.zip -d ik

chmod -R 777 plugins/ik
rm -rf elasticsearch-analysis-ik-7.4.2.zip  #这里要保证plugins目录下纯净，否则启动会报错
docker restart elasticsearch

2.SpringBoot整合Es

2.1.环境配置

• ELK版本对应并去掉springboot中自带的es包

  org.elasticsearch.client elasticsearch-rest-high-level-client 7.4.2

  1.8 7.4.2

• Config配置

  package com.empirefree.gulimall.search.config;

  import org.apache.http.HttpHost;
  import org.elasticsearch.client.RequestOptions;
  import org.elasticsearch.client.RestClient;
  import org.elasticsearch.client.RestClientBuilder;
  import org.elasticsearch.client.RestHighLevelClient;
  import org.springframework.context.annotation.Bean;
  import org.springframework.context.annotation.Configuration;

  /**

  • @program: gulimall-search
  • @description:
  • @author: huyuqiao
  • @create: 2021/08/01 13:54
    */

  @Configuration
  public class GulimallElasticSearchConfig {
  public static final RequestOptions COMMON_OPTIONS;

  static {
      RequestOptions.Builder builder = RequestOptions.DEFAULT.toBuilder();

  // builder.addHeader("Authorization", "Bearer " + TOKEN);
  // builder.setHttpAsyncResponseConsumerFactory(
  // new HttpAsyncResponseConsumerFactory
  // .HeapBufferedResponseConsumerFactory(30 * 1024 * 1024 * 1024));
  COMMON_OPTIONS = builder.build();
  }

  @Bean
  public RestHighLevelClient restHighLevelClient(){
      RestClientBuilder restClientBuilder = null;
      restClientBuilder = RestClient.builder(new HttpHost("公网IP", 9200, "http"));
  RestHighLevelClient client = new RestHighLevelClient(restClientBuilder);
  return client;
  }

  }

2.2.搜索实现

​ 用过两款，一种是狂神的整合es高亮，一种是现在的，做的一些平均值，有点难理解，但是还是先贴出来

       @Test
    public void testEs() throws IOException {
        SearchRequest searchRequest = new SearchRequest();

        // 指定索引
        searchRequest.indices("newbank");

        // 1.指定检索条件 DSL
        SearchSourceBuilder builder = new SearchSourceBuilder();
        // 1.1 构造检索条件
        builder.query(QueryBuilders.matchQuery("address","mill"));

        // 1.2 按照年龄值聚合
        TermsAggregationBuilder ageAgg = AggregationBuilders.terms("ageAgg").field("age").size(10);
        builder.aggregation(ageAgg);
        // 1.3 计算平均薪资
        AvgAggregationBuilder balanceAvg = AggregationBuilders.avg("balanceAvg").field("balance");
        builder.aggregation(balanceAvg);

        System.out.println("检索条件：" + builder.toString());
        searchRequest.source(builder);

        // 2.执行检索
        SearchResponse search = restHighLevelClient.search(searchRequest, GulimallElasticSearchConfig.COMMON_OPTIONS);

        // 3.分析结果
//        Map map = JSON.parseObject(search.toString(), Map.class);
//        System.out.println(map);
        // 3.1 索取所有记录
        SearchHits hits = search.getHits();
        // 详细记录
        SearchHit[] searchHits = hits.getHits();
        for (SearchHit hit : searchHits) {
//            String index = hit.getIndex();
//            String id = hit.getId();
            String source = hit.getSourceAsString();
            Account account = JSON.parseObject(source, Account.class);
            System.out.println(account);
        }
        // 获取分析数据
        Aggregations aggregations = search.getAggregations();
//        List<Aggregation> list = aggregations.asList();
//        for (Aggregation aggregation : list) {
//            Terms agg = aggregations.get(aggregation.getName());
//            System.out.println(agg.getBuckets());
//        }
        Terms agg = aggregations.get("ageAgg");
        for (Terms.Bucket bucket : agg.getBuckets()) {
            System.out.println("年龄: " + bucket.getKeyAsString() + "-->" + bucket.getDocCount() + "人");
        }

        Avg avg = aggregations.get("balanceAvg");
        System.out.println("平均薪资： " + avg.getValue());
    }

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