37mapping字段数据类型以及object类型数据底层结构

1、字段类型概述 一级分类二级分类具体类型核心类型字符串类型string,text,keyword整数类型integer,long,short,byte浮点类型double,float,half_float,scaled_float逻辑类型boolean日期类型date范围类型range二进制类型binary复合类型数组类型array对象类型object嵌套类型nested地理类型地理坐标类型geo_point地理地图geo_shape特殊类型IP类型ip范围类型completion令牌计数类型token_count附件类型attachment抽取类型percolator 2、object 类型

JSON天生具有层级关系，文档会包含嵌套的对象：

1）创建index并动态创建mapping

PUT /company/employee/1
{
  "address": {
    "country": "china",
    "province": "guangdong",
    "city": "guangzhou"
  },
  "name": "zhangsan",
  "age": 18,
  "join_date": "2017-01-01"
}

响应结果

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

address：object类型

2）查看自动创建的mapping

GET /company/_mapping/employee

响应结果

{
  "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
              }
            }
          }
        }
      }
    }
  }
}

3address对象在es底层的结构

{
  "address": {
    "country": "china",
    "province": "guangdong",
    "city": "guangzhou"
  },
  "name": "zhangsan",
  "age": 18,
  "join_date": "2017-01-01"
}

在es底层的结构

{
    "name":            [zhangsan],
    "age":          [18],
    "join_date":      [2017-01-01],
    "address.country":         [china],
    "address.province":   [guangdong],
    "address.city":  [guangzhou]
}

4如果是数组类型

{
    "authors": [
        { "age": 26, "name": "Jack White"},
        { "age": 55, "name": "Tom Jones"},
        { "age": 39, "name": "Kitty Smith"}
    ]
}

在es底层的结构

{
    "authors.age":    [26, 55, 39],
    "authors.name":   [jack, white, tom, jones, kitty, smith]
}

对于其他字段类型就不一一提及了，可以参考

https://www.cnblogs.com/candlia/p/11920029.html