docker虚拟化技术-elasticSearch与springBoot

版本信息：

docker for Windows : 18.03.1-ce-win65 (17513)
springBoot : 2.2.2.RELEASE
springDataElasticSearch : 3.2.3
elasticSearch Image : 6.8.5
elasticSearch-analysis-ik : 6.8.5
mySql : 5.6.40-log
JDK : 1.8
gradle : 6.0.1

项目介绍：

为何要学习elasticSearch？由于快，由于能提供良好的中文分词，由于分布式，由于springBoot已经集成了。其实由于最近项目中咱们对接了京东大约百万条商品数据，致使之前的一些查询出现十几秒加载的状况，让我从新进行了sql的优化（拆分join，设置联合索引，异步请求）使得我对索引进行了复习，而且想去了解搜索引擎与mysql全文索引的具体区别。这里我是用了docker + elasticSearch + springBoot来初步了解elasticsearch。

docker安装elasticsearch

由于在dockers pull elasticsearch 的时候提示没有latest版本因此从docker hub上找到6.8.5来测试，这个版本比较稳定也比较新。

• docker pull elasticsearch:6.8.5
• docker images

• docker run -p 9200:9200 -p 9300:9300 elasticsearch:6.8.5
• docker ps

• 浏览器访问：http://localhost:9200

• curl -i -XGET 'http://localhost:9200/_analyze?pretty' -H "Content-Type:application/json" -d '{"text":"我爱中国"}'

HTTP/1.1 200 OK
content-type: application/json; charset=UTF-8
content-length: 578

{
  "tokens" : [
    {
      "token" : "我",
      "start_offset" : 0,
      "end_offset" : 1,
      "type" : "<IDEOGRAPHIC>",
      "position" : 0
    },
    {
      "token" : "爱",
      "start_offset" : 1,
      "end_offset" : 2,
      "type" : "<IDEOGRAPHIC>",
      "position" : 1
    },
    {
      "token" : "中",
      "start_offset" : 2,
      "end_offset" : 3,
      "type" : "<IDEOGRAPHIC>",
      "position" : 2
    },
    {
      "token" : "国",
      "start_offset" : 3,
      "end_offset" : 4,
      "type" : "<IDEOGRAPHIC>",
      "position" : 3
    }
  ]
}

分词效果很差，和老外同样。

进入container安装IK分词器：

• docker exec -it 容器id /bin/bash

• 进入elasticsearch容器->plugins 目录下 : cd plugins/
• 下载资源 : wget https://github.com/medcl/elas...
• 解压 : unzip elasticsearch-analysis-ik-6.8.5.zip -d /ik
• 退出容器 : exit
• 重启容器： docker stop 容器Id , docker start 容器Id
• curl -i -XGET 'http://localhost:9200/_analyze?pretty' -H "Content-Type:application/json" -d '{"text":"我爱中国","analyzer":"ik_smart"}'

HTTP/1.1 200 OK
content-type: application/json; charset=UTF-8
content-length: 424

{
  "tokens" : [
    {
      "token" : "我",
      "start_offset" : 0,
      "end_offset" : 1,
      "type" : "CN_CHAR",
      "position" : 0
    },
    {
      "token" : "爱",
      "start_offset" : 1,
      "end_offset" : 2,
      "type" : "CN_CHAR",
      "position" : 1
    },
    {
      "token" : "中国",
      "start_offset" : 2,
      "end_offset" : 4,
      "type" : "CN_WORD",
      "position" : 2
    }
  ]
}

接入springboot

具体接入网上不少，只提一点，要使用IK分词器不能使用@Field这些注解，只能本身写JSON文件进行mapping:

@Getter  
@Mapping(mappingPath = "es_article_mapping.json")  
@Document(indexName = "article",type = "article")  
public class ArticleEsEntity {  
  
    @Id  
 private String id;   
 private String title;  
 private String content;  
 private long createTime;  
  
 public ArticleEsEntity(String title, String content) {  
        this.id = System.nanoTime() + "";  
        this.title = title;  
        this.content = content;  
        this.createTime = System.currentTimeMillis();  
  }
  }

{  
  "article":{  
    "properties":{  
      "id":{  
        "type":"text"  
  },  
  "create\_time":{  
        "type":"long"  
  },  
  "content":{  
        "type":"text",  
  "analyzer":"ik\_smart",  
  "search\_analyzer":"ik\_smart",  
  "fields":{  
          "keyword":{  
            "type":"keyword",  
  "ignore\_above":10000  
  }  
        }  
      },  
  "title":{  
        "type":"text",  
  "analyzer":"ik\_smart",  
  "search\_analyzer":"ik\_smart",  
  "fields":{  
          "keyword":{  
            "type":"keyword",  
  "ignore\_above":256  
  }  
        }  
      }  
    }  
  }  
}

最后测试一下：

总共12w+的记录，mysql与elasticsearch都是。

• SELECT* FROM article WHERE title LIKE '%spring%' OR content LIKE '%spring%' 12.81s --- 9810;
• SELECT * FROM article WHERE MATCH(title,content) AGAINST ('spring') 4.296s --- 9810 ;
• curl 'http://127.0.0.1:9200/article/article/_search' -H "Content-Type:application/json" -d {"query":{"bool":{"should":[{"match":{"title":"spring"}},{"match":{"content":"spring"}}]}}} 125ms --- 9810;

另外：mysql的fullIndex很差分词哦~~~