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elasticSearch的has_child查询

发布时间：2021-09-07 17:36:56编辑：雪饮阅读（）

 ElasticSearch中has_child查询主要是以匹配子文档来返回响应其父文档。

那么既然是父子文档查询，所以我们先建立拥有父子关系的索引。
http://localhost:9200/tutorials put
请求体：
{
  "mappings": {
    "properties": {
      "my_join_field": { 
        "type": "join",
        "relations": {
          "parent_article": "article" 
        }
      }
    }
  }
}
响应体：
{
    "acknowledged": true,
    "shards_acknowledged": true,
    "index": "tutorials"
}
然后索引父文档
http://localhost:9200/tutorials/_doc/parent_article_1 post
请求体：
{
   "name":"Parent School1", "Text":"This is article 1 of chapter 1(parent)", "street":"Nagan",
   "city":"paprola", "state":"HP", "zip":"176115", "location":[31.8955385, 76.8380405],
   "fees":2200, "tags":["Senior Secondary", "beautiful campus"], "rating":"3.3",
   "my_join_field": { 
        "name":"parent_article"
      }
}
响应体：
{
    "_index": "tutorials",
    "_type": "_doc",
    "_id": "parent_article_1",
    "_version": 2,
    "result": "updated",
    "_shards": {
        "total": 2,
        "successful": 1,
        "failed": 0
    },
    "_seq_no": 1,
    "_primary_term": 1
}
然后索引子文档
http://localhost:9200/tutorials/_doc/article1?routing=parent_article_1 put
请求体：
{
  "name":"Parent School1", "Text":"This is article 1 of chapter 1(child)", "street":"Nagan",
   "city":"paprola", "state":"HP", "zip":"176115", "location":[31.8955385, 76.8380405],
   "fees":2200, "tags":["Senior Secondary", "beautiful campus"], "rating":"3.3",
  "my_join_field":{
    "name":"article",
    "parent":"parent_article_1"
  }
}
响应体：
{
    "_index": "tutorials",
    "_type": "_doc",
    "_id": "article1",
    "_version": 2,
    "result": "updated",
    "_shards": {
        "total": 2,
        "successful": 1,
        "failed": 0
    },
    "_seq_no": 3,
    "_primary_term": 1
}
然后我们就可以进行has_child查询了
http://localhost:9200/tutorials/_search post
请求体：
{
   "query":
   {
      "has_child" : {
         "type" : "article", 
         "query" : {
            "match" : {
               "Text" : "This is article 1 of chapter 1(child)"
            }
         }
      }
   }
}
响应体：
{
    "took": 65,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 1,
            "relation": "eq"
        },
        "max_score": 1.0,
        "hits": [
            {
                "_index": "tutorials",
                "_type": "_doc",
                "_id": "parent_article_1",
                "_score": 1.0,
                "_source": {
                    "name": "Parent School1",
                    "Text": "This is article 1 of chapter 1(parent)",
                    "street": "Nagan",
                    "city": "paprola",
                    "state": "HP",
                    "zip": "176115",
                    "location": [
                        31.8955385,
                        76.8380405
                    ],
                    "fees": 2200,
                    "tags": [
                        "Senior Secondary",
                        "beautiful campus"
                    ],
                    "rating": "3.3",
                    "my_join_field": {
                        "name": "parent_article"
                    }
                }
            }
        ]
    }
}
可以看到我has_child查询中type指定是子文档的相对于父子关系索引中的角色定位。
然后是match到Text字段以”This is article 1 of chapter 1(child)
”进行匹配，但是会发现最后响应结果中的文档的Text的值为”
This is article 1 of chapter 1(parent)
这样正好应了前面所说的has_child查询是查询匹配子文档，然后返回对应的父文档。