0. 准备相关表来进行接下来的测试
相关建表语句请看:https://github.com/YangBaohust/my_sql
user1表,取经组 +----+-----------+-----------------+---------------------------------+ | id | user_name | comment | mobile | +----+-----------+-----------------+---------------------------------+ | 1 | 唐僧 | 旃檀功德佛 | 138245623,021-382349 | | 2 | 孙悟空 | 斗战胜佛 | 159384292,022-483432,+86-392432 | | 3 | 猪八戒 | 净坛使者 | 183208243,055-8234234 | | 4 | 沙僧 | 金身罗汉 | 293842295,098-2383429 | | 5 | NULL | 白龙马 | 993267899 | +----+-----------+-----------------+---------------------------------+ user2表,悟空的朋友圈 +----+--------------+-----------+ | id | user_name | comment | +----+--------------+-----------+ | 1 | 孙悟空 | 美猴王 | | 2 | 牛魔王 | 牛哥 | | 3 | 铁扇公主 | 牛夫人 | | 4 | 菩提老祖 | 葡萄 | | 5 | NULL | 晶晶 | +----+--------------+-----------+ user1_kills表,取经路上杀的妖怪数量 +----+-----------+---------------------+-------+ | id | user_name | timestr | kills | +----+-----------+---------------------+-------+ | 1 | 孙悟空 | 2013-01-10 00:00:00 | 10 | | 2 | 孙悟空 | 2013-02-01 00:00:00 | 2 | | 3 | 孙悟空 | 2013-02-05 00:00:00 | 12 | | 4 | 孙悟空 | 2013-02-12 00:00:00 | 22 | | 5 | 猪八戒 | 2013-01-11 00:00:00 | 20 | | 6 | 猪八戒 | 2013-02-07 00:00:00 | 17 | | 7 | 猪八戒 | 2013-02-08 00:00:00 | 35 | | 8 | 沙僧 | 2013-01-10 00:00:00 | 3 | | 9 | 沙僧 | 2013-01-22 00:00:00 | 9 | | 10 | 沙僧 | 2013-02-11 00:00:00 | 5 | +----+-----------+---------------------+-------+ user1_equipment表,取经组装备 +----+-----------+--------------+-----------------+-----------------+ | id | user_name | arms | clothing | shoe | +----+-----------+--------------+-----------------+-----------------+ | 1 | 唐僧 | 九环锡杖 | 锦斓袈裟 | 僧鞋 | | 2 | 孙悟空 | 金箍棒 | 梭子黄金甲 | 藕丝步云履 | | 3 | 猪八戒 | 九齿钉耙 | 僧衣 | 僧鞋 | | 4 | 沙僧 | 降妖宝杖 | 僧衣 | 僧鞋 | +----+-----------+--------------+-----------------+-----------------+
1. 使用left join优化not in子句
例子:找出取经组中不属于悟空朋友圈的人
+----+-----------+-----------------+-----------------------+ | id | user_name | comment | mobile | +----+-----------+-----------------+-----------------------+ | 1 | 唐僧 | 旃檀功德佛 | 138245623,021-382349 | | 3 | 猪八戒 | 净坛使者 | 183208243,055-8234234 | | 4 | 沙僧 | 金身罗汉 | 293842295,098-2383429 | +----+-----------+-----------------+-----------------------+
not in写法:
select * from user1 a where a.user_name not in (select user_name from user2 where user_name is not null);
left join写法:
首先看通过user_name进行连接的外连接数据集
select a.*, b.* from user1 a left join user2 b on (a.user_name = b.user_name);
+----+-----------+-----------------+---------------------------------+------+-----------+-----------+ | id | user_name | comment | mobile | id | user_name | comment | +----+-----------+-----------------+---------------------------------+------+-----------+-----------+ | 2 | 孙悟空 | 斗战胜佛 | 159384292,022-483432,+86-392432 | 1 | 孙悟空 | 美猴王 | | 1 | 唐僧 | 旃檀功德佛 | 138245623,021-382349 | NULL | NULL | NULL | | 3 | 猪八戒 | 净坛使者 | 183208243,055-8234234 | NULL | NULL | NULL | | 4 | 沙僧 | 金身罗汉 | 293842295,098-2383429 | NULL | NULL | NULL | | 5 | NULL | 白龙马 | 993267899 | NULL | NULL | NULL | +----+-----------+-----------------+---------------------------------+------+-----------+-----------+
可以看到a表中的所有数据都有显示,b表中的数据只有b.user_name与a.user_name相等才显示,其余都以null值填充,要想找出取经组中不属于悟空朋友圈的人,只需要在b.user_name中加一个过滤条件b.user_name is null即可。
select a.* from user1 a left join user2 b on (a.user_name = b.user_name) where b.user_name is null;
+----+-----------+-----------------+-----------------------+ | id | user_name | comment | mobile | +----+-----------+-----------------+-----------------------+ | 1 | 唐僧 | 旃檀功德佛 | 138245623,021-382349 | | 3 | 猪八戒 | 净坛使者 | 183208243,055-8234234 | | 4 | 沙僧 | 金身罗汉 | 293842295,098-2383429 | | 5 | NULL | 白龙马 | 993267899 | +----+-----------+-----------------+-----------------------+
看到这里发现结果集中还多了一个白龙马,继续添加过滤条件a.user_name is not null即可。
select a.* from user1 a left join user2 b on (a.user_name = b.user_name) where b.user_name is null and a.user_name is not null;
2. 使用left join优化标量子查询
例子:查看取经组中的人在悟空朋友圈的昵称
+-----------+-----------------+-----------+ | user_name | comment | comment2 | +-----------+-----------------+-----------+ | 唐僧 | 旃檀功德佛 | NULL | | 孙悟空 | 斗战胜佛 | 美猴王 | | 猪八戒 | 净坛使者 | NULL | | 沙僧 | 金身罗汉 | NULL | | NULL | 白龙马 | NULL | +-----------+-----------------+-----------+
子查询写法:
select a.user_name, a.comment, (select comment from user2 b where b.user_name = a.user_name) comment2 from user1 a;
left join写法:
select a.user_name, a.comment, b.comment comment2 from user1 a left join user2 b on (a.user_name = b.user_name);
3. 使用join优化聚合子查询
例子:查询出取经组中每人打怪最多的日期
+----+-----------+---------------------+-------+ | id | user_name | timestr | kills | +----+-----------+---------------------+-------+ | 4 | 孙悟空 | 2013-02-12 00:00:00 | 22 | | 7 | 猪八戒 | 2013-02-08 00:00:00 | 35 | | 9 | 沙僧 | 2013-01-22 00:00:00 | 9 | +----+-----------+---------------------+-------+
聚合子查询写法:
select * from user1_kills a where a.kills = (select max(b.kills) from user1_kills b where b.user_name = a.user_name);
join写法:
首先看两表自关联的结果集,为节省篇幅,只取猪八戒的打怪数据来看
select a.*, b.* from user1_kills a join user1_kills b on (a.user_name = b.user_name) order by 1;
+----+-----------+---------------------+-------+----+-----------+---------------------+-------+ | id | user_name | timestr | kills | id | user_name | timestr | kills | +----+-----------+---------------------+-------+----+-----------+---------------------+-------+ | 5 | 猪八戒 | 2013-01-11 00:00:00 | 20 | 5 | 猪八戒 | 2013-01-11 00:00:00 | 20 | | 5 | 猪八戒 | 2013-01-11 00:00:00 | 20 | 6 | 猪八戒 | 2013-02-07 00:00:00 | 17 | | 5 | 猪八戒 | 2013-01-11 00:00:00 | 20 | 7 | 猪八戒 | 2013-02-08 00:00:00 | 35 | | 6 | 猪八戒 | 2013-02-07 00:00:00 | 17 | 7 | 猪八戒 | 2013-02-08 00:00:00 | 35 | | 6 | 猪八戒 | 2013-02-07 00:00:00 | 17 | 5 | 猪八戒 | 2013-01-11 00:00:00 | 20 | | 6 | 猪八戒 | 2013-02-07 00:00:00 | 17 | 6 | 猪八戒 | 2013-02-07 00:00:00 | 17 | | 7 | 猪八戒 | 2013-02-08 00:00:00 | 35 | 5 | 猪八戒 | 2013-01-11 00:00:00 | 20 | | 7 | 猪八戒 | 2013-02-08 00:00:00 | 35 | 6 | 猪八戒 | 2013-02-07 00:00:00 | 17 | | 7 | 猪八戒 | 2013-02-08 00:00:00 | 35 | 7 | 猪八戒 | 2013-02-08 00:00:00 | 35 | +----+-----------+---------------------+-------+----+-----------+---------------------+-------+
可以看到当两表通过user_name进行自关联,只需要对a表的所有字段进行一个group by,取b表中的max(kills),只要a.kills=max(b.kills)就满足要求了。sql如下
select a.* from user1_kills a join user1_kills b on (a.user_name = b.user_name) group by a.id, a.user_name, a.timestr, a.kills having a.kills = max(b.kills);
4. 使用join进行分组选择
例子:对第3个例子进行升级,查询出取经组中每人打怪最多的前两个日期
+----+-----------+---------------------+-------+ | id | user_name | timestr | kills | +----+-----------+---------------------+-------+ | 3 | 孙悟空 | 2013-02-05 00:00:00 | 12 | | 4 | 孙悟空 | 2013-02-12 00:00:00 | 22 | | 5 | 猪八戒 | 2013-01-11 00:00:00 | 20 | | 7 | 猪八戒 | 2013-02-08 00:00:00 | 35 | | 9 | 沙僧 | 2013-01-22 00:00:00 | 9 | | 10 | 沙僧 | 2013-02-11 00:00:00 | 5 | +----+-----------+---------------------+-------+
在oracle中,可以通过分析函数来实现
select b.* from (select a.*, row_number() over(partition by user_name order by kills desc) cnt from user1_kills a) b where b.cnt <= 2;
很遗憾,上面sql在mysql中报错ERROR 1064 (42000): You have an error in your SQL syntax; 因为mysql并不支持分析函数。不过可以通过下面的方式去实现。
首先对两表进行自关联,为了节约篇幅,只取出孙悟空的数据
select a.*, b.* from user1_kills a join user1_kills b on (a.user_name=b.user_name and a.kills<=b.kills) order by a.user_name, a.kills desc;
+----+-----------+---------------------+-------+----+-----------+---------------------+-------+ | id | user_name | timestr | kills | id | user_name | timestr | kills | +----+-----------+---------------------+-------+----+-----------+---------------------+-------+ | 4 | 孙悟空 | 2013-02-12 00:00:00 | 22 | 4 | 孙悟空 | 2013-02-12 00:00:00 | 22 | | 3 | 孙悟空 | 2013-02-05 00:00:00 | 12 | 3 | 孙悟空 | 2013-02-05 00:00:00 | 12 | | 3 | 孙悟空 | 2013-02-05 00:00:00 | 12 | 4 | 孙悟空 | 2013-02-12 00:00:00 | 22 | | 1 | 孙悟空 | 2013-01-10 00:00:00 | 10 | 1 | 孙悟空 | 2013-01-10 00:00:00 | 10 | | 1 | 孙悟空 | 2013-01-10 00:00:00 | 10 | 3 | 孙悟空 | 2013-02-05 00:00:00 | 12 | | 1 | 孙悟空 | 2013-01-10 00:00:00 | 10 | 4 | 孙悟空 | 2013-02-12 00:00:00 | 22 | | 2 | 孙悟空 | 2013-02-01 00:00:00 | 2 | 1 | 孙悟空 | 2013-01-10 00:00:00 | 10 | | 2 | 孙悟空 | 2013-02-01 00:00:00 | 2 | 3 | 孙悟空 | 2013-02-05 00:00:00 | 12 | | 2 | 孙悟空 | 2013-02-01 00:00:00 | 2 | 4 | 孙悟空 | 2013-02-12 00:00:00 | 22 | | 2 | 孙悟空 | 2013-02-01 00:00:00 | 2 | 2 | 孙悟空 | 2013-02-01 00:00:00 | 2 | +----+-----------+---------------------+-------+----+-----------+---------------------+-------+
从上面的表中我们知道孙悟空打怪前两名的数量是22和12,那么只需要对a表的所有字段进行一个group by,对b表的id做个count,count值小于等于2就满足要求,sql改写如下:
select a.* from user1_kills a join user1_kills b on (a.user_name=b.user_name and a.kills<=b.kills) group by a.id, a.user_name, a.timestr, a.kills having count(b.id) <= 2;
5. 使用笛卡尔积关联实现一列转多行
例子:将取经组中每个电话号码变成一行
原始数据:
+-----------+---------------------------------+ | user_name | mobile | +-----------+---------------------------------+ | 唐僧 | 138245623,021-382349 | | 孙悟空 | 159384292,022-483432,+86-392432 | | 猪八戒 | 183208243,055-8234234 | | 沙僧 | 293842295,098-2383429 | | NULL | 993267899 | +-----------+---------------------------------+
想要得到的数据:
+-----------+-------------+ | user_name | mobile | +-----------+-------------+ | 唐僧 | 138245623 | | 唐僧 | 021-382349 | | 孙悟空 | 159384292 | | 孙悟空 | 022-483432 | | 孙悟空 | +86-392432 | | 猪八戒 | 183208243 | | 猪八戒 | 055-8234234 | | 沙僧 | 293842295 | | 沙僧 | 098-2383429 | | NULL | 993267899 | +-----------+-------------+
可以看到唐僧有两个电话,因此他就需要两行。我们可以先求出每人的电话号码数量,然后与一张序列表进行笛卡儿积关联,为了节约篇幅,只取出唐僧的数据
select a.id, b.* from tb_sequence a cross join (select user_name, mobile, length(mobile)-length(replace(mobile, ',', ''))+1 size from user1) b order by 2,1;
+----+-----------+---------------------------------+------+ | id | user_name | mobile | size | +----+-----------+---------------------------------+------+ | 1 | 唐僧 | 138245623,021-382349 | 2 | | 2 | 唐僧 | 138245623,021-382349 | 2 | | 3 | 唐僧 | 138245623,021-382349 | 2 | | 4 | 唐僧 | 138245623,021-382349 | 2 | | 5 | 唐僧 | 138245623,021-382349 | 2 | | 6 | 唐僧 | 138245623,021-382349 | 2 | | 7 | 唐僧 | 138245623,021-382349 | 2 | | 8 | 唐僧 | 138245623,021-382349 | 2 | | 9 | 唐僧 | 138245623,021-382349 | 2 | | 10 | 唐僧 | 138245623,021-382349 | 2 | +----+-----------+---------------------------------+------+
a.id对应的就是第几个电话号码,size就是总的电话号码数量,因此可以加上关联条件(a.id <= b.size),将上面的sql继续调整
select b.user_name, replace(substring(substring_index(b.mobile, ',', a.id), char_length(substring_index(mobile, ',', a.id-1)) + 1), ',', '') as mobile from tb_sequence a cross join (select user_name, concat(mobile, ',') as mobile, length(mobile)-length(replace(mobile, ',', ''))+1 size from user1) b on (a.id <= b.size);
6. 使用笛卡尔积关联实现多列转多行
例子:将取经组中每件装备变成一行
原始数据:
+----+-----------+--------------+-----------------+-----------------+ | id | user_name | arms | clothing | shoe | +----+-----------+--------------+-----------------+-----------------+ | 1 | 唐僧 | 九环锡杖 | 锦斓袈裟 | 僧鞋 | | 2 | 孙悟空 | 金箍棒 | 梭子黄金甲 | 藕丝步云履 | | 3 | 猪八戒 | 九齿钉耙 | 僧衣 | 僧鞋 | | 4 | 沙僧 | 降妖宝杖 | 僧衣 | 僧鞋 | +----+-----------+--------------+-----------------+-----------------+
想要得到的数据:
+-----------+-----------+-----------------+ | user_name | equipment | equip_mame | +-----------+-----------+-----------------+ | 唐僧 | arms | 九环锡杖 | | 唐僧 | clothing | 锦斓袈裟 | | 唐僧 | shoe | 僧鞋 | | 孙悟空 | arms | 金箍棒 | | 孙悟空 | clothing | 梭子黄金甲 | | 孙悟空 | shoe | 藕丝步云履 | | 沙僧 | arms | 降妖宝杖 | | 沙僧 | clothing | 僧衣 | | 沙僧 | shoe | 僧鞋 | | 猪八戒 | arms | 九齿钉耙 | | 猪八戒 | clothing | 僧衣 | | 猪八戒 | shoe | 僧鞋 | +-----------+-----------+-----------------+
union的写法:
select user_name, 'arms' as equipment, arms equip_mame from user1_equipment union all select user_name, 'clothing' as equipment, clothing equip_mame from user1_equipment union all select user_name, 'shoe' as equipment, shoe equip_mame from user1_equipment order by 1, 2;
join的写法:
首先看笛卡尔数据集的效果,以唐僧为例
select a.*, b.* from user1_equipment a cross join tb_sequence b where b.id <= 3;
+----+-----------+--------------+-----------------+-----------------+----+ | id | user_name | arms | clothing | shoe | id | +----+-----------+--------------+-----------------+-----------------+----+ | 1 | 唐僧 | 九环锡杖 | 锦斓袈裟 | 僧鞋 | 1 | | 1 | 唐僧 | 九环锡杖 | 锦斓袈裟 | 僧鞋 | 2 | | 1 | 唐僧 | 九环锡杖 | 锦斓袈裟 | 僧鞋 | 3 | +----+-----------+--------------+-----------------+-----------------+----+
使用case对上面的结果进行处理
select user_name, case when b.id = 1 then 'arms' when b.id = 2 then 'clothing' when b.id = 3 then 'shoe' end as equipment, case when b.id = 1 then arms end arms, case when b.id = 2 then clothing end clothing, case when b.id = 3 then shoe end shoe from user1_equipment a cross join tb_sequence b where b.id <=3;
+-----------+-----------+--------------+-----------------+-----------------+ | user_name | equipment | arms | clothing | shoe | +-----------+-----------+--------------+-----------------+-----------------+ | 唐僧 | arms | 九环锡杖 | NULL | NULL | | 唐僧 | clothing | NULL | 锦斓袈裟 | NULL | | 唐僧 | shoe | NULL | NULL | 僧鞋 | +-----------+-----------+--------------+-----------------+-----------------+
使用coalesce函数将多列数据进行合并
select user_name, case when b.id = 1 then 'arms' when b.id = 2 then 'clothing' when b.id = 3 then 'shoe' end as equipment, coalesce(case when b.id = 1 then arms end, case when b.id = 2 then clothing end, case when b.id = 3 then shoe end) equip_mame from user1_equipment a cross join tb_sequence b where b.id <=3 order by 1, 2;
7. 使用join更新过滤条件中包含自身的表
例子:把同时存在于取经组和悟空朋友圈中的人,在取经组中把comment字段更新为"此人在悟空的朋友圈"
我们很自然地想到先查出user1和user2中user_name都存在的人,然后更新user1表,sql如下
update user1 set comment = '此人在悟空的朋友圈' where user_name in (select a.user_name from user1 a join user2 b on (a.user_name = b.user_name));
很遗憾,上面sql在mysql中报错:ERROR 1093 (HY000): You can't specify target table 'user1' for update in FROM clause,提示不能更新目标表在from子句的表。
那有没有其它办法呢?我们可以将in的写法转换成join的方式
select c.*, d.* from user1 c join (select a.user_name from user1 a join user2 b on (a.user_name = b.user_name)) d on (c.user_name = d.user_name);
+----+-----------+--------------+---------------------------------+-----------+ | id | user_name | comment | mobile | user_name | +----+-----------+--------------+---------------------------------+-----------+ | 2 | 孙悟空 | 斗战胜佛 | 159384292,022-483432,+86-392432 | 孙悟空 | +----+-----------+--------------+---------------------------------+-----------+
然后对join之后的视图进行更新即可
update user1 c join (select a.user_name from user1 a join user2 b on (a.user_name = b.user_name)) d on (c.user_name = d.user_name) set c.comment = '此人在悟空的朋友圈';
再查看user1,可以看到user1已修改成功
select * from user1;
+----+-----------+-----------------------------+---------------------------------+ | id | user_name | comment | mobile | +----+-----------+-----------------------------+---------------------------------+ | 1 | 唐僧 | 旃檀功德佛 | 138245623,021-382349 | | 2 | 孙悟空 | 此人在悟空的朋友圈 | 159384292,022-483432,+86-392432 | | 3 | 猪八戒 | 净坛使者 | 183208243,055-8234234 | | 4 | 沙僧 | 金身罗汉 | 293842295,098-2383429 | | 5 | NULL | 白龙马 | 993267899 | +----+-----------+-----------------------------+---------------------------------+
8. 使用join删除重复数据
首先向user2表中插入两条数据
insert into user2(user_name, comment) values ('孙悟空', '美猴王'); insert into user2(user_name, comment) values ('牛魔王', '牛哥');
例子:将user2表中的重复数据删除,只保留id号大的
+----+--------------+-----------+ | id | user_name | comment | +----+--------------+-----------+ | 1 | 孙悟空 | 美猴王 | | 2 | 牛魔王 | 牛哥 | | 3 | 铁扇公主 | 牛夫人 | | 4 | 菩提老祖 | 葡萄 | | 5 | NULL | 晶晶 | | 6 | 孙悟空 | 美猴王 | | 7 | 牛魔王 | 牛哥 | +----+--------------+-----------+
首先查看重复记录
select a.*, b.* from user2 a join (select user_name, comment, max(id) id from user2 group by user_name, comment having count(*) > 1) b on (a.user_name=b.user_name and a.comment=b.comment) order by 2;
+----+-----------+-----------+-----------+-----------+------+ | id | user_name | comment | user_name | comment | id | +----+-----------+-----------+-----------+-----------+------+ | 1 | 孙悟空 | 美猴王 | 孙悟空 | 美猴王 | 6 | | 6 | 孙悟空 | 美猴王 | 孙悟空 | 美猴王 | 6 | | 2 | 牛魔王 | 牛哥 | 牛魔王 | 牛哥 | 7 | | 7 | 牛魔王 | 牛哥 | 牛魔王 | 牛哥 | 7 | +----+-----------+-----------+-----------+-----------+------+
接着只需要删除(a.id < b.id)的数据即可
delete a from user2 a join (select user_name, comment, max(id) id from user2 group by user_name, comment having count(*) > 1) b on (a.user_name=b.user_name and a.comment=b.comment) where a.id < b.id;
查看user2,可以看到重复数据已经被删掉了
select * from user2;
+----+--------------+-----------+ | id | user_name | comment | +----+--------------+-----------+ | 3 | 铁扇公主 | 牛夫人 | | 4 | 菩提老祖 | 葡萄 | | 5 | NULL | 晶晶 | | 6 | 孙悟空 | 美猴王 | | 7 | 牛魔王 | 牛哥 | +----+--------------+-----------+
总结:
给大家就介绍到这里,大家有兴趣可以多造点数据,然后比较不同的sql写法在执行时间上的区别。本文例子取自于慕课网《sql开发技巧》。
好了,以上就是这篇文章的全部内容了,希望本文的内容对大家的学习或者工作具有一定的参考学习价值,谢谢大家对的支持。
免责声明:本站资源来自互联网收集,仅供用于学习和交流,请遵循相关法律法规,本站一切资源不代表本站立场,如有侵权、后门、不妥请联系本站删除!
稳了!魔兽国服回归的3条重磅消息!官宣时间再确认!
昨天有一位朋友在大神群里分享,自己亚服账号被封号之后居然弹出了国服的封号信息对话框。
这里面让他访问的是一个国服的战网网址,com.cn和后面的zh都非常明白地表明这就是国服战网。
而他在复制这个网址并且进行登录之后,确实是网易的网址,也就是我们熟悉的停服之后国服发布的暴雪游戏产品运营到期开放退款的说明。这是一件比较奇怪的事情,因为以前都没有出现这样的情况,现在突然提示跳转到国服战网的网址,是不是说明了简体中文客户端已经开始进行更新了呢?
更新日志
- 小骆驼-《草原狼2(蓝光CD)》[原抓WAV+CUE]
- 群星《欢迎来到我身边 电影原声专辑》[320K/MP3][105.02MB]
- 群星《欢迎来到我身边 电影原声专辑》[FLAC/分轨][480.9MB]
- 雷婷《梦里蓝天HQⅡ》 2023头版限量编号低速原抓[WAV+CUE][463M]
- 群星《2024好听新歌42》AI调整音效【WAV分轨】
- 王思雨-《思念陪着鸿雁飞》WAV
- 王思雨《喜马拉雅HQ》头版限量编号[WAV+CUE]
- 李健《无时无刻》[WAV+CUE][590M]
- 陈奕迅《酝酿》[WAV分轨][502M]
- 卓依婷《化蝶》2CD[WAV+CUE][1.1G]
- 群星《吉他王(黑胶CD)》[WAV+CUE]
- 齐秦《穿乐(穿越)》[WAV+CUE]
- 发烧珍品《数位CD音响测试-动向效果(九)》【WAV+CUE】
- 邝美云《邝美云精装歌集》[DSF][1.6G]
- 吕方《爱一回伤一回》[WAV+CUE][454M]