八、ElasticSearch之mapping API

（1）mapping 定义每个field的数据类型、索引行为、是否分词以及分词器等，就是index的type的元数据

string --> text/keyword

byte，short，integer，long --> 123 long

float，double --> 123.45 double

boolean --> true or false

date --> 2019-02-02

Text：会分词，然后进行索引，支持模糊、精确查询，不支持聚合

keyword：不进行分词，直接索引，支持模糊、精确查询，支持聚合

analyzed 分词建立索引
not_analyzed 不分词建立索引
no 不分词不建立索引

（2）建立mapping，结构化索引

PUT /person
{
    "settings": {
        "number_of_shards": 3,
        "number_of_replicas": 1
    },
    "mappings": {
        "person": {
            "properties": {
                "name": {
                    "type": "text"
                },
                "age": {
                    "type": "integer"
                },
                "birthday": {
                    "type": "date",
                    "format": "yyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
                },
                "country": {
                    "type": "keyword"
                },
                "tag": {
                     "type": "text",
                      "index": "not_analyzed"
                 }
            }
        }
    }
}

（3）查看mapping

GET /person/_mapping

（4）新增field

PUT /person
{
    "mappings": {
        "person": {
            "properties": {
                "name": {
                    "type": "keyword"
                }
            }
        }
    }
}

--> 报错，不能修改已经定义好的field


PUT /person/_mapping/person
{
    "properties": {
        "nickname": {
            "type": "keyword"
        }
    }
}
--> 成功

（5）测试分词

GET /person/_analyze
{
  "field": "name",
  "text": "kill tiger"
}
--> 结果分词 

GET /person/_analyze
{
  "field": "nickname",
  "text": "kill tiger"
}
--> 结果不分词 

（6）嵌套Object的mapping

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

GET company/_mapping

{
  "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
              }
            }
          }
        }
      }
    }
  }
}

实际上es内部会转成列式存储

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

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

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

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