我有一个具有这种结构的表
Name Type Collation Attributes Null Default Extra Action
1 user_id int(11) No None Change Change Drop Drop Browse distinct values Browse distinct values Primary Primary Unique Unique Show more actions More
2 amount decimal(16,8) No None Change Change Drop Drop Browse distinct values Browse distinct values Primary Primary Unique Unique Show more actions More
3 aff int(11) No 0 Change Change Drop Drop Browse distinct values Browse distinct values Primary Primary Unique Unique Show more actions More
4 jackpot int(11) No 0 Change Change Drop Drop Browse distinct values Browse distinct values Primary Primary Unique Unique Show more actions More
5 paidout int(11) No 0 Change Change Drop Drop Browse distinct values Browse distinct values Primary Primary Unique Unique Show more actions More
6 type int(11) No 0 Change Change Drop Drop Browse distinct values Browse distinct values Primary Primary Unique Unique Show more actions More
7 created timestamp No CURRENT_TIMESTAMP Change Change Drop Drop Browse distinct values Browse distinct values Primary Primary Unique Unique Show more actions More
我在同一个查询中尝试了这两行而没有成功:
UPDATE `trans` where paidout=1 GROUP BY user_id
UPDATE `trans`where paidout=0 GROUP BY user_id
也只是为了查看不更新会很好
像这样SELECT * FROM `trans` where paidout=1 GROUP BY user_id
SELECT * FROM `trans` where paidout=0 GROUP BY user_id
我需要在同一个查询上运行这两行
我需要按user_id对表行进行分组,但是相同的user_id在某些行中的paidout = 1,而在其他一些行中的paidout = 0
所以我想按user_id进行分组,其中paidout = 1,GROUP BY user_id,其中paidout = 0
所以我会为每个user_id获得2行
答案 0 :(得分:0)
从你给我们的小东西狂野猜测你想要的东西:
SELECT user_id,paidout,count(*),sum(amount) FROM trans GROUP BY user_id,paidout
答案 1 :(得分:0)
如果您只想查看Paidout = 0和Paidout = 1的所有记录,您需要执行以下操作:
SELECT * from `trans` WHERE paidout = 1
或
SELECT * from `trans` WHERE paidout = 0
或(如果你想要两者)
SELECT * from `trans` WHERE paidout = 1 OR paidout = 0
只有在想要使用聚合函数(Sum,Average,Max,Min等)时才需要Group By
子句。
如果您想要运行聚合函数(例如,如果您想要paidout
= 1和0的记录数),那么您将执行以下操作:
SELECT paidout, count(paidout) FROM `trans` GROUP BY paidout
我希望这已经解决了您的问题,如果没有,请回复更多详情,我会更新此答案!
注意:这些只是运行这些查询的最基本方法,您可以根据自己的需要进一步调整和优化它们,但这超出了这个答案的范围!