前面博客中创建的索引以及插入数据，都是由Elasticsearch进行自动判断类型，有些时候是需要进行明确字段类型的，否则，自动判断的类型和实际需求有时候是不相符的。
自动判断的规则如下：
| JSON type | Field type |
| Boolean: true or false | "boolean" |
| Whole number: 123 | "long" |
| Floating point: 123.45 | "double" |
| String, valid date: "2014-09-15" | "date" |
| String: "foo bar" | "string" |
Elasticsearch中支持的类型如下：
| 类型 | 表示的数据类型 |
| String | string , text , keyword |
| Whole number | byte , short , integer , long |
| Floating point | float , double |
| Boolean | boolean |
| Date | date |
注意：
- string类型在ElasticSearch 旧版本中使用较多，从ElasticSearch 5.x开始不再支持string，由text和 keyword类型替代。
- text 类型，当一个字段是要被全文搜索的，比如Email内容、产品描述，应该使用text类型。设置text类型以后，字段内容会被分析，在生成倒排索引以前，字符串会被分析器分成一个一个词项。text类型的字段不用于排序，很少用于聚合。
- keyword类型适用于索引结构化的字段，比如email地址、主机名、状态码和标签。如果字段需要进行过滤(比如查找已发布博客中status属性为published的文章)、排序、聚合。keyword类型的字段只能通过精确值搜索到。
创建明确类型的索引：
PUT /study
# 请求数据
{
"settings": {
"index": {
"number_of_shards": "2",
"number_of_replicas": "0"
}
},
"mappings": {
"properties": {
"name": {
"type": "text"
},
"age": {
"type": "integer"
},
"mail": {
"type": "keyword"
},
"hobby": {
"type": "text"
}
}
}
}
# 响应数据
{
"acknowledged": true,
"shards_acknowledged": true,
"index": "study"
}
这儿可能存在的错误，参考博文：ElasticSearch 7.x 报错：Root mapping definition has unsupported parameters_Sunny Feng的博客-CSDN博客
查看映射：
GET /study/_mapping
# 响应数据
{
"study": {
"mappings": {
"properties": {
"age": {
"type": "integer"
},
"hobby": {
"type": "text"
},
"mail": {
"type": "keyword"
},
"name": {
"type": "text"
}
}
}
}
}
插入数据：
POST /study/_bulk
# 请求数据
{"index":{"_index":"study"}}
{"name":"张三","age": 20,"mail": "111@qq.com","hobby":"羽毛球、乒乓球、足球"}
{"index":{"_index":"study"}}
{"name":"李四","age": 21,"mail": "222@qq.com","hobby":"羽毛球、乒乓球、足球、篮球"}
{"index":{"_index":"study"}}
{"name":"王五","age": 22,"mail": "333@qq.com","hobby":"羽毛球、篮球、游泳、听音乐"}
{"index":{"_index":"study"}}
{"name":"赵六","age": 23,"mail": "444@qq.com","hobby":"跑步、游泳"}
{"index":{"_index":"study"}}
{"name":"孙七","age": 24,"mail": "555@qq.com","hobby":"听音乐、看电影"}
# 响应结果
{
"took": 25,
"errors": false,
"items": [
{
"index": {
"_index": "study",
"_type": "_doc",
"_id": "SHjOVIIBpyNh4YQ4CVSN",
"_version": 1,
"result": "created",
"_shards": {
"total": 1,
"successful": 1,
"failed": 0
},
"_seq_no": 0,
"_primary_term": 1,
"status": 201
}
},
{
"index": {
"_index": "study",
"_type": "_doc",
"_id": "SXjOVIIBpyNh4YQ4CVSN",
"_version": 1,
"result": "created",
"_shards": {
"total": 1,
"successful": 1,
"failed": 0
},
"_seq_no": 0,
"_primary_term": 1,
"status": 201
}
},
{
"index": {
"_index": "study",
"_type": "_doc",
"_id": "SnjOVIIBpyNh4YQ4CVSN",
"_version": 1,
"result": "created",
"_shards": {
"total": 1,
"successful": 1,
"failed": 0
},
"_seq_no": 1,
"_primary_term": 1,
"status": 201
}
},
{
"index": {
"_index": "study",
"_type": "_doc",
"_id": "S3jOVIIBpyNh4YQ4CVSN",
"_version": 1,
"result": "created",
"_shards": {
"total": 1,
"successful": 1,
"failed": 0
},
"_seq_no": 1,
"_primary_term": 1,
"status": 201
}
},
{
"index": {
"_index": "study",
"_type": "_doc",
"_id": "THjOVIIBpyNh4YQ4CVSN",
"_version": 1,
"result": "created",
"_shards": {
"total": 1,
"successful": 1,
"failed": 0
},
"_seq_no": 2,
"_primary_term": 1,
"status": 201
}
}
]
}
注意：通过上面的数据库中数据可以看到，默认生成的是_doc类型的数据。
测试搜索：
POST /study/_search
# 请求数据
{
"query": {
"match": {
"hobby": "音乐"
}
}
}
# 响应数据
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 2,
"successful": 2,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 1.0470967,
"hits": [
{
"_index": "study",
"_type": "_doc",
"_id": "THjOVIIBpyNh4YQ4CVSN",
"_score": 1.0470967,
"_source": {
"name": "孙七",
"age": 24,
"mail": "555@qq.com",
"hobby": "听音乐、看电影"
}
},
{
"_index": "study",
"_type": "_doc",
"_id": "SnjOVIIBpyNh4YQ4CVSN",
"_score": 0.8527901,
"_source": {
"name": "王五",
"age": 22,
"mail": "333@qq.com",
"hobby": "羽毛球、篮球、游泳、听音乐"
}
}
]
}
}
