映射关系（`mapping`）

类比关系型数据库，我们在插入数据之前我们需要首先去创建表结构，而我们以上对文档的操作却一路没有进行结构的创建，其实在ES中确实可以不创建类似于表结构的东西，但是他也是可以创建表结构的。
在ES中这个表结构叫着映射。它主要的作用就是用于定义字段是否被分词和被检索。

测试准备工作

为了更好的实现我们首先创建一个新的索引student.
创建新索引

创建映射关系

创建新索引之后我们再新索引上建立映射关系。建立映射关系同样要使用PUT请求，请求的URL地址:http://127.0.0.1:9200/student/_mapping

创建映射关系

插入测试数据

为了测试插入三条数据，
数据1

{
    "name": "张三",
    "sex": "男的",
    "tel": "18180486815"
}

数据2

{
    "name": "张三丰",
    "sex": "男学生",
    "tel": "18180486814"
}

数据3

{
    "name": "张无极",
    "sex": "男",
    "tel": "18180486823"
}

查询一下保存的结果：
查询结果
从结果上看已经将测试数据插入成功了。

测试

根据`name`查询

根据name查询,验证检索结果。

name检索
响应结果：

{
    "took": 1,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 3,
            "relation": "eq"
        },
        "max_score": 0.14874382,
        "hits": [
            {
                "_index": "student",
                "_type": "_doc",
                "_id": "1001",
                "_score": 0.14874382,
                "_source": {
                    "name": "张三",
                    "sex": "男的",
                    "tel": "18180486815"
                }
            },
            {
                "_index": "student",
                "_type": "_doc",
                "_id": "1002",
                "_score": 0.12703526,
                "_source": {
                    "name": "张三丰",
                    "sex": "男学生",
                    "tel": "18180486814"
                }
            },
            {
                "_index": "student",
                "_type": "_doc",
                "_id": "1003",
                "_score": 0.12703526,
                "_source": {
                    "name": "张无极",
                    "sex": "男",
                    "tel": "18180486823"
                }
            }
        ]
    }
}

如果使用name为张极进行查询：

{
    "query": {
        "match": {
            "name":"张极"
        }
    }
}

响应的结果仍然包含了三条数据，只是因为命中得分顺序发生了改变：

{
    "took": 1,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 3,
            "relation": "eq"
        },
        "max_score": 1.0601485,
        "hits": [
            {
                "_index": "student",
                "_type": "_doc",
                "_id": "1003",
                "_score": 1.0601485,
                "_source": {
                    "name": "张无极",
                    "sex": "男",
                    "tel": "18180486823"
                }
            },
            {
                "_index": "student",
                "_type": "_doc",
                "_id": "1001",
                "_score": 0.14874382,
                "_source": {
                    "name": "张三",
                    "sex": "男的",
                    "tel": "18180486815"
                }
            },
            {
                "_index": "student",
                "_type": "_doc",
                "_id": "1002",
                "_score": 0.12703526,
                "_source": {
                    "name": "张三丰",
                    "sex": "男学生",
                    "tel": "18180486814"
                }
            }
        ]
    }
}

根据查询的返回结果可以看出，根据张可以查询出所有的name字段带张的文档。也就是说name字段支持全量查询，即验证了text类型是支持全量查询的。

根据`keyword`类型的`sex`进行检索

首先将sex查询的内容设置为男。检索的内容体为：

{
    "query": {
        "match": {
            "sex":"男"
        }
    }
}

执行查询
sex字段检索
响应结果为：

{
    "took": 1,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 1,
            "relation": "eq"
        },
        "max_score": 0.9808291,
        "hits": [
            {
                "_index": "student",
                "_type": "_doc",
                "_id": "1003",
                "_score": 0.9808291,
                "_source": {
                    "name": "张无极",
                    "sex": "男",
                    "tel": "18180486823"
                }
            }
        ]
    }
}

从结果上可以看出，该字段精准的匹配了为男的性别，而没匹配上另外两条数据。也就是说，keyword类型的字段是不会进行分词存储的。

测试`index=false`的映射

我们在创建映射关系时，tel字段设置的index为false。我们再来测试通过tel字段检索。
body:

{
    "query": {
        "match": {
            "tel":"18180486814"
        }
    }
}

操作
tel检索
通过查询可以知道，明显查询结果是失败了。并且后台爆出了查询错误提示.

{
    "error": {
        "root_cause": [
            {
                "type": "query_shard_exception",
                "reason": "failed to create query: Cannot search on field [tel] since it is not indexed.",
                "index_uuid": "kdZOZTxDR_Go1Nr3B9vQKA",
                "index": "student"
            }
        ],
        "type": "search_phase_execution_exception",
        "reason": "all shards failed",
        "phase": "query",
        "grouped": true,
        "failed_shards": [
            {
                "shard": 0,
                "index": "student",
                "node": "6eel-aElR5uwyZ7-TkBmsg",
                "reason": {
                    "type": "query_shard_exception",
                    "reason": "failed to create query: Cannot search on field [tel] since it is not indexed.",
                    "index_uuid": "kdZOZTxDR_Go1Nr3B9vQKA",
                    "index": "student",
                    "caused_by": {
                        "type": "illegal_argument_exception",
                        "reason": "Cannot search on field [tel] since it is not indexed."
                    }
                }
            }
        ]
    },
    "status": 400
}