docker虛擬化技術-elasticSearch與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

項目介紹：

爲何要學習elasticSearch？由於快，由於能提供良好的中文分詞，由於分佈式，由於springBoot已經集成了。其實由於最近項目中咱們對接了京東大約百萬條商品數據，致使之前的一些查詢出現十幾秒加載的狀況，讓我從新進行了sql的優化（拆分join，設置聯合索引，異步請求）使得我對索引進行了複習，而且想去了解搜索引擎與mysql全文索引的具體區別。這裏我是用了docker + elasticSearch + springBoot來初步瞭解elasticsearch。

docker安裝elasticsearch

由於在dockers pull elasticsearch 的時候提示沒有latest版本因此從docker hub上找到6.8.5來測試，這個版本比較穩定也比較新。

• docker pull elasticsearch:6.8.5
• docker images

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

• 瀏覽器訪問：http://localhost:9200

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

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" : "愛",
      "start_offset" : 1,
      "end_offset" : 2,
      "type" : "<IDEOGRAPHIC>",
      "position" : 1
    },
    {
      "token" : "中",
      "start_offset" : 2,
      "end_offset" : 3,
      "type" : "<IDEOGRAPHIC>",
      "position" : 2
    },
    {
      "token" : "國",
      "start_offset" : 3,
      "end_offset" : 4,
      "type" : "<IDEOGRAPHIC>",
      "position" : 3
    }
  ]
}

分詞效果很差，和老外同樣。

進入container安裝IK分詞器：

• docker exec -it 容器id /bin/bash

• 進入elasticsearch容器->plugins 目錄下 : cd plugins/
• 下載資源 : wget https://github.com/medcl/elas...
• 解壓 : unzip elasticsearch-analysis-ik-6.8.5.zip -d /ik
• 退出容器 : exit
• 重啓容器： 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":"我愛中國","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" : "愛",
      "start_offset" : 1,
      "end_offset" : 2,
      "type" : "CN_CHAR",
      "position" : 1
    },
    {
      "token" : "中國",
      "start_offset" : 2,
      "end_offset" : 4,
      "type" : "CN_WORD",
      "position" : 2
    }
  ]
}

接入springboot

具體接入網上不少，只提一點，要使用IK分詞器不能使用@Field這些註解，只能本身寫JSON文件進行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  
  }  
        }  
      }  
    }  
  }  
}

最後測試一下：

總共12w+的記錄，mysql與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很差分詞哦~~~