白话Elasticsearch15-深度探秘搜索技术之使用copy_to定制组合field解决cross-fields搜索弊端

文章目录

概述

继续跟中华石杉老师学习ES，第15篇

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---

官网

https://www.elastic.co/guide/en/elasticsearch/reference/current/copy-to.html

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例子

新增字段，用作测试

PUT /forum/_mapping/article
{
  "properties": {
    "new_author_first_name": {
      "type": "text",
      "copy_to": "new_author_full_name"
    },
    "new_author_last_name": {
      "type": "text",
      "copy_to": "new_author_full_name"
    },
    "new_author_full_name": {
      "type": "text"
    }
  }
}

---

更新数据

POST /forum/article/_bulk
{ "update": { "_id": "1"} }
{ "doc" : {"new_author_first_name" : "Peter", "new_author_last_name" : "Smith"} }   
{ "update": { "_id": "2"} } 
{ "doc" : {"new_author_first_name" : "Smith", "new_author_last_name" : "Williams"} }    
{ "update": { "_id": "3"} }
{ "doc" : {"new_author_first_name" : "Jack", "new_author_last_name" : "Ma"} }     
{ "update": { "_id": "4"} }
{ "doc" : {"new_author_first_name" : "Robbin", "new_author_last_name" : "Li"} }     
{ "update": { "_id": "5"} }
{ "doc" : {"new_author_first_name" : "Tonny", "new_author_last_name" : "Peter Smith"} }

---

查询

GET /forum/article/_search
{
  "query": {
    "match": {
      "new_author_full_name":       "Peter Smith"
    }
  }
}

返回结果

{
  "took": 3,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 2,
    "max_score": 2.3258216,
    "hits": [
      {
        "_index": "forum",
        "_type": "article",
        "_id": "1",
        "_score": 2.3258216,
        "_source": {
          "articleID": "XHDK-A-1293-#fJ3",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-01",
          "tag": [
            "java",
            "hadoop"
          ],
          "tag_cnt": 2,
          "view_cnt": 30,
          "title": "this is java and elasticsearch blog",
          "content": "i like to write best elasticsearch article",
          "sub_title": "learning more courses",
          "author_first_name": "Peter",
          "author_last_name": "Smith",
          "new_author_last_name": "Smith",
          "new_author_first_name": "Peter"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "5",
        "_score": 1.7770995,
        "_source": {
          "articleID": "DHJK-B-1395-#Ky5",
          "userID": 3,
          "hidden": false,
          "postDate": "2019-05-01",
          "tag": [
            "elasticsearch"
          ],
          "tag_cnt": 1,
          "view_cnt": 10,
          "title": "this is spark blog",
          "content": "spark is best big data solution based on scala ,an programming language similar to java",
          "sub_title": "haha, hello world",
          "author_first_name": "Tonny",
          "author_last_name": "Peter Smith",
          "new_author_last_name": "Peter Smith",
          "new_author_first_name": "Tonny"
        }
      }
    ]
  }
}

---

总结

cross field的问题，是否解决了呢？

• 问题1：只是找到尽可能多的field匹配的doc，而不是某个field完全匹配的doc

  答: 解决，最匹配的document被最先返回

• 问题2：most_fields，没办法用minimum_should_match去掉长尾数据，就是匹配的特别少的结果

  答: 解决，可以使用minimum_should_match去掉长尾数据

• 问题3：TF/IDF算法，比如Peter Smith和Smith Williams，搜索Peter
  Smith的时候，由于first_name中很少有Smith的，所以query在所有document中的频率很低，得到的分数很高，可能Smith Williams反而会排在Peter Smith前面

  答: 解决，Smith和Peter在一个field了，所以在所有document中出现的次数是均匀的，不会有极端的偏差