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57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 80 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 (000 sec)
第一级:
mysql> select json_keys(@ytt);+-----------------+| json_keys(@ytt) |+-----------------+| ["name"] |+-----------------+1 row in set (000 sec)
第二级:
mysql> select json_keys(@ytt,'$name[0]');+-----------------------------+| json_keys(@ytt,'$name[0]') |+-----------------------------+| ["a", "b"] |+-----------------------------+1 row in set (000 sec)
我们使用MySQL 80 的JSON_TABLE 来转换 @ytt。
mysql> select from json_table(@ytt,'$name[]' columns (f1 varchar(10) path '$a', f2 varchar(10) path '$b')) as tt;
+-------+--------+
| f1 | f2 |
+-------+--------+
| ytt | action |
| dble | shard |
| mysql | oracle |
+-------+--------+
3 rows in set (000 sec)
举例二
再来一个复杂点的例子,用的是EXPLAIN 的JSON结果集。
JSON 串 @json_str1。
set @json_str1 = ' { "query_block": { "select_id": 1, "cost_info": { "query_cost": "100" }, "table": { "table_name": "bigtable", "access_type": "const", "possible_keys": [ "id" ], "key": "id", "used_key_parts": [ "id" ], "key_length": "8", "ref": [ "const" ], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "10000", "cost_info": { "read_cost": "000", "eval_cost": "020", "prefix_cost": "000", "data_read_per_join": "176" }, "used_columns": [ "id", "log_time", "str1", "str2" ] } }}';
第一级:
mysql> select json_keys(@json_str1) as 'first_object';+-----------------+| first_object |+-----------------+| ["query_block"] |+-----------------+1 row in set (000 sec)
第二级:
mysql> select json_keys(@json_str1,'$query_block') as 'second_object';+-------------------------------------+| second_object |+-------------------------------------+| ["table", "cost_info", "select_id"] |+-------------------------------------+1 row in set (000 sec)
第三级:
mysql> select json_keys(@json_str1,'$query_blocktable') as 'third_object'\G 1 row third_object: ["key","ref","filtered","cost_info","key_length","table_name","access_type","used_columns","possible_keys","used_key_parts","rows_examined_per_scan","rows_produced_per_join"]1 row in set (001 sec)
第四级:
mysql> select json_extract(@json_str1,'$query_blocktablecost_info') as 'forth_object'\G 1 row forth_object: {"eval_cost":"020","read_cost":"000","prefix_cost":"000","data_read_per_join":"176"}1 row in set (000 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 | 10000 | 020 | 000 | 000 | 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 | 100 | 1 |
+-------+------+-------+--------+------+------+------+------+------+----------+-------+------+------+------+------+------+------+
2 rows in set (000 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。
将json对象的 键值对,转化为 ContentValues 对象中的键值对(键 为表中的字段名),然后插入数据库就可以了。dbManagerinsert(TABLENAME, null, values);
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