我在使用联接时努力从qty列获取正确的总和。当我尝试从timestamp表中获取paymentType并将rowid加入orders和paymentType表，然后将timestamp分组时，会出现此问题{1}}
我希望使用(day(from_unixtime(paymentType.timestamp)))表格中的qty按小时计算timestamp的总和，唯一的链接是paymentType（这是codeigniter＆＃39; s购物车模块的rowid）。逻辑问题（至少对我而言）是rowid表中存在的行数（因为这是每个产品）比orders表中存在的更多行（这只是为了跟踪借方还是现金）用过）。当我将这些表连接在一起时，每小时的总和乘以paymentType中的每次匹配。
如果解释不好，我很抱歉，但我希望我能够理解这件事可以得到帮助。
我至少有10次查询，但似乎都没有按照我想要的方式运作。
以下是我的orders.rowid <--> paymentType.rowid表格
orders这是+---------+----+-------+-----+----------+------------------+----------------------------------+
| orderID | id | price | qty | subtotal | name | rowid |
+---------+----+-------+-----+----------+------------------+----------------------------------+
| 3 | 49 | 35 | 1 | 35 | Red Bull Stor | f457c545a9ded88f18ecee47145a72c0 |
| 4 | 24 | 35 | 1 | 35 | Monster Energy | 1ff1de774005f8da13f42943881c655f |
| 5 | 49 | 35 | 1 | 35 | Red Bull Stor | f457c545a9ded88f18ecee47145a72c0 |
| 6 | 19 | 20 | 1 | 20 | Sprite 0.5L | 1f0e3dad99908345f7439f8ffabdffc4 |
| 7 | 1 | 25 | 1 | 25 | Pringles | c4ca4238a0b923820dcc509a6f75849b |
| 8 | 43 | 20 | 1 | 20 | Lån av stekovn | 17e62166fc8586dfa4d1bc0e1742c08b |
| 9 | 46 | 35 | 1 | 35 | Burn | d9d4f495e875a2e075a1a4a6e1b9770f |
| 10 | 49 | 35 | 3 | 105 | Red Bull Stor | f457c545a9ded88f18ecee47145a72c0 |
| 11 | 49 | 35 | 1 | 35 | Red Bull Stor | f457c545a9ded88f18ecee47145a72c0 |
| 12 | 29 | 25 | 1 | 25 | Potetskruer | 6ea9ab1baa0efb9e19094440c317e21b |
| 13 | 16 | 20 | 1 | 20 | Coca-Cola 0.5L | c74d97b01eae257e44aa9d5bade97baf |
| 14 | 46 | 35 | 1 | 35 | Burn | d9d4f495e875a2e075a1a4a6e1b9770f |
| 15 | 1 | 25 | 1 | 25 | Pringles | c4ca4238a0b923820dcc509a6f75849b |
| 16 | 18 | 20 | 1 | 20 | Eventyrbrus 0.5L | 6f4922f45568161a8cdf4ad2299f6d23 |
| 17 | 16 | 20 | 1 | 20 | Coca-Cola 0.5L | c74d97b01eae257e44aa9d5bade97baf |
| 18 | 15 | 30 | 1 | 30 | Coca-Cola 1.5L | 9bf31c7ff062936a96d3c8bd1f8f2ff3 |
| 19 | 19 | 20 | 1 | 20 | Sprite 0.5L | 1f0e3dad99908345f7439f8ffabdffc4 |
| 20 | 50 | 20 | 1 | 20 | Stratos bar | c0c7c76d30bd3dcaefc96f40275bdc0a |
+---------+----+-------+-----+----------+------------------+----------------------------------+
表
paymentType修改 SQL查询我到目前为止已经尝试过，存在更多，但这些是最新的。我认为这些是最正确的＃34;。
+-----------+-------------+------------+----------------------------------+
| paymentID | paymentType | timestamp | rowid |
+-----------+-------------+------------+----------------------------------+
| 3 | Kort | 1424447799 | f457c545a9ded88f18ecee47145a72c0 |
| 4 | Kort | 1424448791 | 1ff1de774005f8da13f42943881c655f |
| 5 | Kort | 1424452822 | f457c545a9ded88f18ecee47145a72c0 |
| 6 | Kort | 1424454483 | c4ca4238a0b923820dcc509a6f75849b |
| 7 | Kort | 1424454665 | d9d4f495e875a2e075a1a4a6e1b9770f |
| 8 | Kontant | 1424454799 | f457c545a9ded88f18ecee47145a72c0 |
| 9 | Kontant | 1424454825 | f457c545a9ded88f18ecee47145a72c0 |
| 10 | Kort | 1424454870 | 6ea9ab1baa0efb9e19094440c317e21b |
| 11 | Kontant | 1424455510 | d9d4f495e875a2e075a1a4a6e1b9770f |
| 12 | Kort | 1424455847 | c4ca4238a0b923820dcc509a6f75849b |
| 13 | Kontant | 1424456025 | 6f4922f45568161a8cdf4ad2299f6d23 |
| 14 | Kontant | 1424456099 | c74d97b01eae257e44aa9d5bade97baf |
| 15 | Kontant | 1424456148 | 9bf31c7ff062936a96d3c8bd1f8f2ff3 |
| 16 | Kontant | 1424456242 | c0c7c76d30bd3dcaefc96f40275bdc0a |
| 17 | Kort | 1424456266 | c74d97b01eae257e44aa9d5bade97baf |
| 18 | Kort | 1424456445 | c0c7c76d30bd3dcaefc96f40275bdc0a |
| 19 | Kort | 1424456964 | 70efdf2ec9b086079795c442636b55fb |
| 20 | Kort | 1424457701 | 1ff1de774005f8da13f42943881c655f |
+-----------+-------------+------------+----------------------------------+
预期的结果是将红牛Stor＆＃39;的数量列相加。 （即。）按小时分组的每一天。
答案 0 :(得分：0)
您可以尝试这样的事情：
select o.name
, pt.rowid
, sum(o.qty)
, hour(from_unixtime(pt.timestamp))
, day(from_unixtime(pt.timestamp))
from orders o
join paymentType pt using(rowid)
where o.name = 'Red Bull Stor'
group by o.name
, o.rowid
, hour(from_unixtime(pt.timestamp))
, day(from_unixtime(pt.timestamp));