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*fromjson_table(@ytt,'$.name[*]'columns(f1 varchar(10)path'$.a',f2 varchar(10)path'$.b'))astt;

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

|f1|f2|

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

|ytt|action|

|dble|shard|

|mysql|oracle|

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

3rowsinset(0.00sec)

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|

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

2rowsinset(0.00sec)

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