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 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。
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