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mysql怎么存json mysql jsonb( 二 )

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怎么在mysql中放入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：
mysqlselect 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'

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