Question

我正在搜索一个简单的查询，可以将较低时间范围内的库存数据更改为更高的时间范围。考虑下表

                          Open    High    Low    Close   Volume
    Date                                                       
    1999-01-04 10:22:00  1.1801  1.1819  1.1801  1.1817       4
    1999-01-04 10:23:00  1.1817  1.1818  1.1804  1.1814      18
    1999-01-04 10:24:00  1.1817  1.1817  1.1802  1.1806      12
    1999-01-04 10:25:00  1.1807  1.1815  1.1795  1.1808      26
    1999-01-04 10:26:00  1.1803  1.1806  1.1790  1.1806       4
    1999-01-04 10:27:00  1.1801  1.1801  1.1779  1.1786      23
    1999-01-04 10:28:00  1.1795  1.1801  1.1776  1.1788      28
    1999-01-04 10:29:00  1.1793  1.1795  1.1782  1.1789      10
    1999-01-04 10:31:00  1.1780  1.1792  1.1776  1.1792      12
    1999-01-04 10:32:00  1.1788  1.1792  1.1788  1.1791       4

每1分钟更新一次。如何通过查询将其更改为2分钟数据？

Answer 1

你想要分组：

select floor(time/2) as time,
       sum(volume) as volume,
       max(case when time = 2*floor(time/2) then open end) as open,
       max(high) as high,
       max(low) as low),
       max(case when time = 2*floor(time/2)+1 then close end) as close
from t
group by floor(time/2)

使用row_number()可以使打开和关闭的公式更简单，更通用，但您需要指定数据库。

Answer 2

答案在SQL Server。因此，您可能希望更改某些语法以适应。就partition check this out.而言。

同时假设您的资产非常有流动性且不会错过一分钟......;）此查询可以进一步改进。请试一试。

SQLFIDDLE DEMO

查询：[编辑以排除任何来自null的ohlcv值。]

select z.dt, a.opens as o, z.h, 
z.l, b.closes as c, z.v
from (
select Dateadd(minute, 1, x.dates) as dt,
max(y.high) as h, min(y.low) as l,
sum(y.volume) as v
from ohlcv x
left join ohlcv y
on y.dates
between x.dates and 
Dateadd(minute, 1, x.dates)
where (DATEPART(MINUTE, x.Dates) % 2) = 0
group by Dateadd(minute, 1, x.dates)) z
left join 
ohlcv a
on a.dates = Dateadd(minute, -1, z.dt)
left join ohlcv b
on b.dates = z.dt
where not (a.opens is null or z.h is null 
or z.l is null or b.closes is null
or z.v is null)
;

结果：

| DT                             |O       |H       |L       |C       | V  |
---------------------------------------------------------------------------
| January, 04 1999 10:23:00+0000 | 1.1801 | 1.1819 | 1.1801 | 1.1814 | 22 |
| January, 04 1999 10:25:00+0000 | 1.1817 | 1.1817 | 1.1795 | 1.1808 | 38 |
| January, 04 1999 10:27:00+0000 | 1.1803 | 1.1806 | 1.1779 | 1.1786 | 27 |
| January, 04 1999 10:29:00+0000 | 1.1795 | 1.1801 | 1.1776 | 1.1789 | 38 |
| January, 04 1999 10:31:00+0000 | 1.1781 | 1.1793 | 1.1776 | 1.1792 | 17 |

查询库存数据时间范围的变化

2 个答案:

SQLFIDDLE DEMO