文章目录

• 概述
• 官网
• 例子
• 总结

概述

继续跟中华石杉老师学习ES，第15篇

课程地址： https://www.roncoo.com/view/55

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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"} }

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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"}}]} }

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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

总结

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