ElasticSearch34：初识搜索引擎_mapping复杂数据类型以及object类型数据底层结构揭秘
1.mapping复杂数据类型
1）multivalue field，字段可以接收多个值
{"tags":["tag1","tag2"]}
建立索引时与string是一样的，数据类型不能混。


2）empty field
null, [],  [null]


3）object field
如下，其中的author就是object field

{
    "title":"my first title",
    "author":{
        "author_id":"1",
        "gender":"male",
        "age":27,
        "names":{
            "full":"John_Jack",
            "first":"John",
            "last":"Jack"
        }
    }
}

例子：

PUT /company/employee/1
{
  "address":{
    "country":"China",
    "province":"Zhejiang",
    "city":"Hangzhou"
  },
  "name":"jack",
  "age":27,
  "join_date":"2018-01-04"
}

执行结果：
{
  "_index": "company",
  "_type": "employee",
  "_id": "1",
  "_version": 1,
  "result": "created",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "created": true
}

查看company/employee的mapping
GET /company/_mapping/employee
执行结果：es动态建立的mapping，可以看到address 的数据类型，里面包含了properties：city,country,province，这个address就是object类型

{
  "company": {
    "mappings": {
      "employee": {
        "properties": {
          "address": {
            "properties": {
              "city": {
                "type": "text",
                "fields": {
                  "keyword": {
                    "type": "keyword",
                    "ignore_above": 256
                  }
                }
              },
              "country": {
                "type": "text",
                "fields": {
                  "keyword": {
                    "type": "keyword",
                    "ignore_above": 256
                  }
                }
              },
              "province": {
                "type": "text",
                "fields": {
                  "keyword": {
                    "type": "keyword",
                    "ignore_above": 256
                  }
                }
              }
            }
          },
          "age": {
            "type": "long"
          },
          "join_date": {
            "type": "date"
          },
          "name": {
            "type": "text",
            "fields": {
              "keyword": {
                "type": "keyword",
                "ignore_above": 256
              }
            }
          }
        }
      }
    }
  }
}

而ES的底层存储格式其实是下面这样的，上面的数据对应的底层数据结构

{
    "name":[jack],
    "age":[27],
    "join_date":[2018-01-04],
    "address.province":[Zhejiang],
    "address.country":[China],
    "address.city":[Hangzhou]
}


而更复杂一点的数据类型，如
{
    "author":[
        {"name":"jack1 white","age":27},
        {"name":"jack2 blue","age":28},
        {"name":"jack3 yellow","age":29}
    ]
}

对应的底层数据结构
{
    "author.name":[jack1,white,jack2,blue,jack3,yellow],
    "author.age":[27,28,29]
}