我有以下T-SQL表,数据和查询.
create table sampledata
(
name nvarchar(50),
sampletime datetime,
samplevalue decimal
);
insert into sampledata (name, sampletime, samplevalue) values
('ABC1235', cast('2016/01/01 10:00:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 10:05:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 10:10:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 10:15:00 AM' as datetime), null),
('ABC1235', cast('2016/01/01 10:20:00 AM' as datetime), null),
('ABC1235', cast('2016/01/01 10:25:00 AM' as datetime), null),
('ABC1235', cast('2016/01/01 10:30:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 10:35:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 10:40:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 10:45:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 10:50:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 10:55:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 11:00:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 11:05:00 AM' as datetime), null),
('ABC1235', cast('2016/01/01 11:10:00 AM' as datetime), null),
('ABC1235', cast('2016/01/01 11:15:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 11:20:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 11:25:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 11:30:00 AM' as datetime), null),
('ABC1235', cast('2016/01/01 11:35:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 11:40:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 11:45:00 AM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 11:50:00 AM' as datetime), null),
('ABC1235', cast('2016/01/01 11:55:00 AM' as datetime), null),
('ABC1235', cast('2016/01/01 12:00:00 PM' as datetime), 50.00),
('ABC1235', cast('2016/01/01 12:05:00 PM' as datetime), null),
('ABC1235', cast('2016/01/01 12:10:00 PM' as datetime), null),
('ABC1235', cast('2016/01/01 12:15:00 PM' as datetime), null),
('ABC1235', cast('2016/01/01 12:20:00 PM' as datetime), null),
('ABC1235', cast('2016/01/01 12:25:00 PM' as datetime), null),
('ABC1235', cast('2016/01/01 12:30:00 PM' as datetime), null)
('ZYA4567', cast('2016/01/01 10:00:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 10:05:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 10:10:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 10:15:00 AM' as datetime), null),
('ZYA4567', cast('2016/01/01 10:20:00 AM' as datetime), null),
('ZYA4567', cast('2016/01/01 10:25:00 AM' as datetime), null),
('ZYA4567', cast('2016/01/01 10:30:00 AM' as datetime), null),
('ZYA4567', cast('2016/01/01 10:35:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 10:40:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 10:45:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 10:50:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 10:55:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 11:00:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 11:05:00 AM' as datetime), null),
('ZYA4567', cast('2016/01/01 11:10:00 AM' as datetime), null),
('ZYA4567', cast('2016/01/01 11:15:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 11:20:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 11:25:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 11:30:00 AM' as datetime), null),
('ZYA4567', cast('2016/01/01 11:35:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 11:40:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 11:45:00 AM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 11:50:00 AM' as datetime), null),
('ZYA4567', cast('2016/01/01 11:55:00 AM' as datetime), null),
('ZYA4567', cast('2016/01/01 12:00:00 PM' as datetime), 50.00),
('ZYA4567', cast('2016/01/01 12:05:00 PM' as datetime), null),
('ZYA4567', cast('2016/01/01 12:10:00 PM' as datetime), null),
('ZYA4567', cast('2016/01/01 12:15:00 PM' as datetime), null),
('ZYA4567', cast('2016/01/01 12:20:00 PM' as datetime), null),
('ZYA4567', cast('2016/01/01 12:25:00 PM' as datetime), 40.00),
('ZYA4567', cast('2016/01/01 12:30:00 PM' as datetime), 50.00)
查询:
select
name,
sampletime,
samplevalue,
sum(case when samplevalue is null then 0 else 1 end)
over(partition by name order by sampletime)
* case when samplevalue is null then 1 else 0 end as block
from sampledata
我需要将其转换为LINQ.
我想我会把它分成两个步骤(我的实际查询更多涉及包含连接和where子句比这个例子)
var list = (from s in db.sampledata).ToList();
现在我不知道该怎么办
sum(case when samplevalue is null then 0 else 1 end)
over(partition by name order by sampletime)
* case when samplevalue is null then 1 else 0 end as block
最佳答案 你不能使用LinQToSQL来做到这一点,因为在Linq的分区构建中没有直接转换为SQL.
但你可以在客户端做到这一点,我建议你这样:
int i = 0; //we need this for closure
var list = db.sampledata
.OrderBy(x => x.name)
.ThenBy(x => x.sampletime) //order your data like partition function do
.ToList() //get all from DB to server memory
.Select(x =>
{
int block = 0; //logic of your block calculation
if (x.samplevalue.HasValue)
i++;
else
block = i;
//return your full collection
return new {
name = x.name,
sampletime = x.sampletime,
samplevalue = x.samplevalue,
block = block
};
});
正如您所看到的,排序和选择逻辑将在DB端,但计算的字段块将在LinQ端.
另一种可能让您感兴趣的方法是使用存储过程或存储函数包装T-SQL查询,并将其映射到LinQToSQL DataContext,以便您可以调用它.