json文件可以直接导入数据库吗

直接读写文件，再把读出来的文件内容格式化成json，再用JDBC、Mybatis或者其他框架将json数据存入数据库。

假设实体类是这样的：

public class ElectSet {

public String xueqi

public String xuenian

public String startTime

public String endTime

public int menshu

public String isReadDB

//{"xueqi":,"xuenian":,"startTime":,"endTime":,"renshu":,"isReadDB":}

public String getXueqi() {

return xueqi

}

public void setXueqi(String xueqi) {

this.xueqi = xueqi

}

public String getXuenian() {

return xuenian

}

public void setXuenian(String xuenian) {

this.xuenian = xuenian

}

public String getStartTime() {

return startTime

}

public void setStartTime(String startTime) {

this.startTime = startTime

}

public String getEndTime() {

return endTime

}

public void setEndTime(String endTime) {

this.endTime = endTime

}

public int getMenshu() {

return menshu

}

public void setMenshu(int menshu) {

this.menshu = menshu

}

public String getIsReadDB() {

return isReadDB

}

public void setIsReadDB(String isReadDB) {

this.isReadDB = isReadDB

}

}

有一个json格式的文件，存的信息如下：

Sets.json:

{"xuenian":"2007-2008","xueqi":"1","startTime":"2009-07-19 08:30","endTime":"2009-07-22 18:00","menshu":"10","isReadDB":"Y"}

具体 *** 作：

/*

* 取出文件内容，填充对象

*/

public ElectSet findElectSet(String path){

ElectSet electset=new ElectSet()

String sets=ReadFile(path)//获得json文件的内容

JSONObject jo=JSONObject.fromObject(sets)//格式化成json对象

//System.out.println("------------" jo)

//String name = jo.getString("xuenian")

//System.out.println(name)

electset.setXueqi(jo.getString("xueqi"))

electset.setXuenian(jo.getString("xuenian"))

electset.setStartTime(jo.getString("startTime"))

electset.setEndTime(jo.getString("endTime"))

electset.setMenshu(jo.getInt("menshu"))

electset.setIsReadDB(jo.getString("isReadDB"))

return electset

}

//设置属性，并保存

public boolean setElect(String path,String sets){

try {

writeFile(path,sets)

return true

} catch (IOException e) {

// TODO Auto-generated catch block

e.printStackTrace()

return false

}

}

//读文件，返回字符串

public String ReadFile(String path){

File file = new File(path)

BufferedReader reader = null

String laststr = ""

try {

//System.out.println("以行为单位读取文件内容，一次读一整行：")

reader = new BufferedReader(new FileReader(file))

String tempString = null

int line = 1

//一次读入一行，直到读入null为文件结束

while ((tempString = reader.readLine()) != null) {

//显示行号

System.out.println("line " line ": " tempString)

laststr = laststr tempString

line

}

reader.close()

} catch (IOException e) {

e.printStackTrace()

} finally {

if (reader != null) {

try {

reader.close()

} catch (IOException e1) {

}

}

}

return laststr

}

将获取到的字符串，入库即可。

我们知道，JSON是一种轻量级的数据交互的格式，大部分NO SQL数据库的存储都用JSON。MySQL从5.7开始支持JSON格式的数据存储，并且新增了很多JSON相关函数。MySQL 8.0 又带来了一个新的把JSON转换为TABLE的函数JSON_TABLE，实现了JSON到表的转换。

举例一

我们看下简单的例子：

简单定义一个两级JSON 对象

mysql>set @ytt='{"name":[{"a":"ytt","b":"action"},  {"a":"dble","b":"shard"},{"a":"mysql","b":"oracle"}]}'Query OK, 0 rows affected (0.00 sec)

第一级：

mysql>select json_keys(@ytt)+-----------------+| json_keys(@ytt) |+-----------------+| ["name"]        |+-----------------+1 row in set (0.00 sec)

第二级：

mysql>select json_keys(@ytt,'$.name[0]')+-----------------------------+| json_keys(@ytt,'$.name[0]') |+-----------------------------+| ["a", "b"]                  |+-----------------------------+1 row in set (0.00 sec)

我们使用MySQL 8.0 的JSON_TABLE 来转换 @ytt。

mysql>select * from json_table(@ytt,'$.name[*]' columns (f1 varchar(10) path '$.a', f2 varchar(10) path '$.b')) as tt

+-------+--------+

| f1    | f2     |

+-------+--------+

| ytt   | action |

| dble  | shard  |

| mysql | oracle |

+-------+--------+

3 rows in set (0.00 sec)

举例二

再来一个复杂点的例子，用的是EXPLAIN 的JSON结果集。

JSON 串 @json_str1。

set @json_str1 = ' {  "query_block": {    "select_id": 1,    "cost_info": {      "query_cost": "1.00"    },    "table": {      "table_name": "bigtable",      "access_type": "const",      "possible_keys": [        "id"      ],      "key": "id",      "used_key_parts": [        "id"      ],      "key_length": "8",      "ref": [        "const"      ],      "rows_examined_per_scan": 1,      "rows_produced_per_join": 1,      "filtered": "100.00",      "cost_info": {        "read_cost": "0.00",        "eval_cost": "0.20",        "prefix_cost": "0.00",        "data_read_per_join": "176"      },      "used_columns": [        "id",        "log_time",        "str1",        "str2"      ]    }  }}'

第一级：

mysql>select json_keys(@json_str1) as 'first_object'+-----------------+| first_object    |+-----------------+| ["query_block"] |+-----------------+1 row in set (0.00 sec)

第二级：

mysql>select json_keys(@json_str1,'$.query_block') as 'second_object'+-------------------------------------+| second_object                       |+-------------------------------------+| ["table", "cost_info", "select_id"] |+-------------------------------------+1 row in set (0.00 sec)

第三级：

mysql> select json_keys(@json_str1,'$.query_block.table') as 'third_object'\G*************************** 1. row ***************************third_object: ["key","ref","filtered","cost_info","key_length","table_name","access_type","used_columns","possible_keys","used_key_parts","rows_examined_per_scan","rows_produced_per_join"]1 row in set (0.01 sec)

第四级：

mysql>select json_extract(@json_str1,'$.query_block.table.cost_info') as 'forth_object'\G*************************** 1. row ***************************forth_object: {"eval_cost":"0.20","read_cost":"0.00","prefix_cost":"0.00","data_read_per_join":"176"}1 row in set (0.00 sec)

那我们把这个JSON 串转换为表。

SELECT * FROM JSON_TABLE(@json_str1,

"$.query_block"

COLUMNS(

rowid FOR ORDINALITY,

NESTED PATH '$.table'

COLUMNS (

a1_1 varchar(100) PATH '$.key',

a1_2 varchar(100) PATH '$.ref[0]',

a1_3 varchar(100) PATH '$.filtered',

nested path '$.cost_info'

columns (

a2_1 varchar(100) PATH '$.eval_cost' ,

a2_2 varchar(100) PATH '$.read_cost',

a2_3 varchar(100) PATH '$.prefix_cost',

a2_4 varchar(100) PATH '$.data_read_per_join'

),

a3 varchar(100) PATH '$.key_length',

a4 varchar(100) PATH '$.table_name',

a5 varchar(100) PATH '$.access_type',

a6 varchar(100) PATH '$.used_key_parts[0]',

a7 varchar(100) PATH '$.rows_examined_per_scan',

a8 varchar(100) PATH '$.rows_produced_per_join',

a9 varchar(100) PATH '$.key'

),

NESTED PATH '$.cost_info'

columns (

b1_1 varchar(100) path '$.query_cost'

),

c INT path "$.select_id"

)

) AS tt

+-------+------+-------+--------+------+------+------+------+------+----------+-------+------+------+------+------+------+------+

| rowid | a1_1 | a1_2  | a1_3   | a2_1 | a2_2 | a2_3 | a2_4 | a3   | a4       | a5    | a6   | a7   | a8   | a9   | b1_1 | c    |

+-------+------+-------+--------+------+------+------+------+------+----------+-------+------+------+------+------+------+------+

|     1 | id   | const | 100.00 | 0.20 | 0.00 | 0.00 | 176  | 8    | bigtable | const | id   | 1    | 1    | id   | NULL |    1 |

|     1 | NULL | NULL  | NULL   | NULL | NULL | NULL | NULL | NULL | NULL     | NULL  | NULL | NULL | NULL | NULL | 1.00 |    1 |

+-------+------+-------+--------+------+------+------+------+------+----------+-------+------+------+------+------+------+------+

2 rows in set (0.00 sec)

当然，JSON_table 函数还有其他的用法，我这里不一一列举了，详细的参考手册。

请点击输入图片描述

直接读写文件，再把读出来的文件内容格式化成json，再用JDBC、Mybatis或者其他框架将json数据存入数据库。 假设实体类是这样的： public class ElectSet {public String xueqipublic String xuenianpublic String startTimepublic

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