mysql json被转义 mysql json转表

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。