46、初识搜索引擎_mapping复杂数据类型以及object类型数据底层结构大揭秘

1、multivalue field， 多值字段

{ "tags": [ "tag1", "tag2" ]}

建立索引时与string是一样的，数据类型不能混

2、empty field，空值字段

null，[]，[null]

3、object field 可以理解为对象字段

PUT /company/_doc/1
{
  "address": {
    "country": "china",
    "province": "guangdong",
    "city": "guangzhou"
  },
  "name": "jack",
  "age": 27,
  "join_date": "2017-01-01"
}

address：上面的 document 就是 object类型
mapping 结构如下：

{
  "company": {
    "mappings": {
      "_doc": {
        "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
              }
            }
          }
        }
      }
    }
  }
}

案例一：document 如下：

{
  "address": {
    "country": "china",
    "province": "guangdong",
    "city": "guangzhou"
  },
  "name": "jack",
  "age": 27,
  "join_date": "2017-01-01"
}

底层数据结构如下：

{
    "name":            [jack],
    "age":             [27],
    "join_date":       [2017-01-01],
    "address.country":         [china],
    "address.province":   [guangdong],
    "address.city":       [guangzhou]
}

案例二：document 如下：

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

底层数据结构如下：

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