mysql使用什么类型存json数据

mysql使用什么类型存json数据？

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。

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。