1、multivalue field
{ "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
举例
有这样一条document数据,它在底层中的结构是怎样的呢?
PUT /company/employee/1
{
"address": {
"country": "china",
"province": "guangdong",
"city": "guangzhou"
},
"name": "jack",
"age": 27,
"join_date": "2017-01-01"
}
(1)查看mapping数据类型
GET /company/_mapping/employee
-------------------------------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
}
}
}
}
}
}
}
}
(2)数据底层结构解释
其中,field参数中address就是object类型。
这条document底层的结构
{
"address": {
"country": "china",
"province": "guangdong",
"city": "guangzhou"
},
"name": "jack",
"age": 27,
"join_date": "2017-01-01"
}
-------------------------底层的结构如下-------------------------
{
"name": [jack],
"age": [27],
"join_date": [2017-01-01],
"address.country": [china],
"address.province": [guangdong],
"address.city": [guangzhou]
}
(3)更复杂的object类型底层结构
如:
{
"authors": [
{ "age": 26, "name": "Jack White"},
{ "age": 55, "name": "Tom Jones"},
{ "age": 39, "name": "Kitty Smith"}
]
}
-------------------------底层的结构如下-------------------------
{
"authors.age": [26, 55, 39],
"authors.name": [jack, white, tom, jones, kitty, smith]
}
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