SQL获取行之间经过的天数，并进行分组_Sql_Sql Server_Azure Sql Database

SQL获取行之间经过的天数，并进行分组

sql sql-server azure-sql-database

SQL获取行之间经过的天数，并进行分组,sql,sql-server,azure-sql-database,Sql,Sql Server,Azure Sql Database,环境：SQLAzure-因此一些外来函数有些有限我有一个记录资产物流事件的表，我想从该表中计算资产在设施中的天数。见下表示例： AssetID LocationID SublocationID MoveDate CAR1 LOC1 SUB1 1/1/2015 01:01:01 CAR1 LOC1 SUB2 1/3/2015 03:03:03 CAR1 LOC1 SUB1 1/4/2015

环境：SQLAzure-因此一些外来函数有些有限

我有一个记录资产物流事件的表，我想从该表中计算资产在设施中的天数。见下表示例：

AssetID LocationID SublocationID MoveDate
CAR1    LOC1       SUB1          1/1/2015 01:01:01
CAR1    LOC1       SUB2          1/3/2015 03:03:03
CAR1    LOC1       SUB1          1/4/2015 04:04:04
CAR1    LOC99      SUB99         1/5/2015 05:05:05
CAR1    LOC1       SUB1          1/9/2015 09:09:09

此表记录从一个位置/子位置移动到另一个位置。我不在乎次定位。我只需要报告资产在每个位置的天数。起初我走的是这条路：

SELECT  AssetID,
        LocationID,
        DATEDIFF(DAY, MIN(MoveDate), MAX(MoveDate))
FROM    TABLE
GROUP BY AssetID, LocationID

然而，这很快揭示了一个陷阱，在数据中，您可以看到资产从LOC1移动到LOC2，然后再返回LOC1。我的查询将计算2015年1月1日至2015年1月9日期间LOC1的所有天数，而实际上它在LOC99处花费了1/5至1/9之间的时间

有没有一种纯SQL的方法来实现这一点

使用

快进

光标，按日期顺序在表上迭代，并在临时表中构建结果集

这可以通过

LEAD

或

LAG

来完成，但Azure中没有。毫无疑问，某种非游标T-SQL解决方案是可能的，但我怀疑它的性能会比游标更好。具有“快进”功能的光标通常比包含相关子查询的查询性能更好。

它应该如下所示：

SELECT  [details].[AssetId],
        [details].[LocationId],
        DATEDIFF(DAY, MIN([details].[MovedInDate]), [details].[MoveOutDate]) AS DaysIn
FROM (
    SELECT DISTINCT movedInRow.[AssetId], [movedInRow].[LocationId], [movedInRow].[MoveDate] AS MovedInDate, ISNULL(nm.[MoveDate], GETDATE()) AS MoveOutDate
    FROM [dbo].[t1] movedInRow
        OUTER APPLY (
            SELECT TOP 1 [MoveDate]
            FROM [dbo].[t1]
            WHERE 
                [AssetId] = movedInRow.[AssetId]
                AND [LocationId] != movedInRow.[LocationId]
                AND [MoveDate] >= [movedInRow].[MoveDate]
                ORDER BY [MoveDate] DESC
        ) nm
) AS details
GROUP BY
    [details].[AssetId],
    [details].[LocationId],
    [details].[MoveOutDate];

无论出于何种原因，两个位置的MoveDate可能是相同的，本例不检查这种可能性

AssetId LocationId DaysIn
CAR1    LOC1       4
CAR1    LOC1       13
CAR1    LOC99      4

不使用窗口函数（如LEAD或LAG）和任何t-sql编码，您可以使用递归CTE使其工作：

/*Create table and sample data*/

create table #mov (
  AssetID varchar(10),
  LocationID varchar(10),
  SublocationID varchar(10),
  MoveDate datetime
)

insert into #mov
select 'CAR1',    'LOC1',       'SUB1',          '1/1/2015 01:01:01' union all
select 'CAR1',    'LOC1',       'SUB2',          '1/3/2015 03:03:03' union all
select 'CAR1',    'LOC1',       'SUB1',          '1/4/2015 04:04:04' union all
select 'CAR1',    'LOC99',      'SUB99',         '1/5/2015 05:05:05' union all
select 'CAR1',    'LOC1',       'SUB1' ,         '1/9/2015 09:09:09' union all
select 'CAR2',    'LOC1',       'SUB1',          '1/1/2015 01:01:01' union all
select 'CAR2',    'LOC1',       'SUB2',          '1/3/2015 03:03:03' union all
select 'CAR2',    'LOC1',       'SUB1',          '1/4/2015 04:04:04' union all
select 'CAR2',    'LOC99',      'SUB99',         '1/5/2015 05:05:05' union all
select 'CAR2',    'LOC1',       'SUB1' ,         '1/9/2015 09:09:09'

/*Create CTEs*/
/*1. cteMov - adds the row number to the dataset*/
;with cteMov as (
    select AssetID, LocationID, MoveDate, row_number() over(partition by AssetID order by MoveDate) as rn
    from #mov
),
/*recursive CTE to get records groups*/
rec as (
  select AssetID, LocationID, MoveDate, rn, 1 as rnk
  from cteMov
  where rn = 1
  union all
  select c.AssetID, c.LocationID, c.MoveDate, c.rn, case when c.LocationID = rec.LocationID then rec.rnk else rec.rnk + 1 end as rnk
  from cteMov as c
  join rec on c.AssetID = rec.AssetID and c.rn = rec.rn + 1
)
/*3. Final query*/
select
  rec1.AssetID, rec1.LocationID,
  datediff(dd, min(rec1.MoveDate), isnull(max(rec2.MoveDate), getdate())) as DaysSpent, 
  rec1.rnk
from rec as rec1
left join rec as rec2 on rec1.rnk = rec2.rnk - 1
group by rec1.AssetID, rec1.LocationID, rec1.rnk
order by rec1.AssetID, rec1.rnk
option(MAXRECURSION  0)

/*drop temp table */
drop table #mov

结果是：

AssetID    LocationID DaysSpent   rnk
---------- ---------- ----------- -----------
CAR1       LOC1       4           1
CAR1       LOC99      4           2
CAR1       LOC1       13          3
CAR2       LOC1       4           1
CAR2       LOC99      4           2
CAR2       LOC1       13          3

使用先前响应中的样本数据：

create table t1 (
  AssetID varchar(10),
  LocationID varchar(10),
  SublocationID varchar(10),
  MoveDate datetime
);


insert into t1
select 'CAR1',    'LOC1',       'SUB1',          '1/1/2015 01:01:01' union all
select 'CAR1',    'LOC1',       'SUB2',          '1/3/2015 03:03:03' union all
select 'CAR1',    'LOC1',       'SUB1',          '1/4/2015 04:04:04' union all
select 'CAR1',    'LOC99',      'SUB99',         '1/5/2015 05:05:05' union all
select 'CAR1',    'LOC1',       'SUB1' ,         '1/9/2015 09:09:09' union all
select 'CAR2',    'LOC1',       'SUB1',          '1/1/2015 01:01:01' union all
select 'CAR2',    'LOC1',       'SUB2',          '1/3/2015 03:03:03' union all
select 'CAR2',    'LOC1',       'SUB1',          '1/4/2015 04:04:04' union all
select 'CAR2',    'LOC99',      'SUB99',         '1/5/2015 05:05:05' union all
select 'CAR2',    'LOC1',       'SUB1' ,         '1/9/2015 09:09:09';

select * from t1;

╔═════════╦════════════╦═══════════════╦════════════════════════════════╗
║ ASSETID ║ LOCATIONID ║ SUBLOCATIONID ║            MOVEDATE            ║
╠═════════╬════════════╬═══════════════╬════════════════════════════════╣
║ CAR1    ║ LOC1       ║ SUB1          ║ January, 01 2015 01:01:01+0000 ║
║ CAR2    ║ LOC1       ║ SUB1          ║ January, 01 2015 01:01:01+0000 ║
║ CAR2    ║ LOC1       ║ SUB2          ║ January, 03 2015 03:03:03+0000 ║
║ CAR1    ║ LOC1       ║ SUB2          ║ January, 03 2015 03:03:03+0000 ║
║ CAR1    ║ LOC1       ║ SUB1          ║ January, 04 2015 04:04:04+0000 ║
║ CAR2    ║ LOC1       ║ SUB1          ║ January, 04 2015 04:04:04+0000 ║
║ CAR2    ║ LOC99      ║ SUB99         ║ January, 05 2015 05:05:05+0000 ║
║ CAR1    ║ LOC99      ║ SUB99         ║ January, 05 2015 05:05:05+0000 ║
║ CAR1    ║ LOC1       ║ SUB1          ║ January, 09 2015 09:09:09+0000 ║
║ CAR2    ║ LOC1       ║ SUB1          ║ January, 09 2015 09:09:09+0000 ║
╚═════════╩════════════╩═══════════════╩════════════════════════════════╝

如果支持lead（）分析函数，则更好的解决方案（简单性和性能方面）是：

select AssetID, LocationID, 
       sum(datediff(dd,MoveDate,isnull(nextMoveDate,getDate()))) daysAtLoc
from (
    select AssetID, LocationID, MoveDate, 
           lead(MoveDate) over (partition by AssetID
                               order by MoveDate) nextMoveDate
    from t1
    ) t2
group by AssetID, LocationID
order by AssetID, LocationID;

╔═════════╦════════════╦═══════════╗
║ ASSETID ║ LOCATIONID ║ DAYSATLOC ║
╠═════════╬════════════╬═══════════╣
║ CAR1    ║ LOC1       ║        18 ║
║ CAR1    ║ LOC99      ║         4 ║
║ CAR2    ║ LOC1       ║        18 ║
║ CAR2    ║ LOC99      ║         4 ║
╚═════════╩════════════╩═══════════╝

纯SQL解决方案：无分析、无递归CTE、无外部应用/相关子查询；只是简单的连接。我从未使用过Azure SQL，但如果它不支持这一点（仍然称自己为SQL），我会非常惊讶

当然，您不需要使用dtu范围的表格，我这样做只是为了同时测试各种条件。我确实更喜欢使用[currentstart，nextstart]的日期范围，因为编写SQL变得更容易，而不会重叠，例如月报

create table dt_range 
    (thisStartDate date, 
     nextStartDate date, 
     primary key (thisStartDate,nextStartDate));

insert into dt_range 
select '01-dec-2014','01-jan-2015' union
select '01-jan-2015','01-feb-2015' union
select '02-jan-2015','09-jan-2015' union
select '01-feb-2015','01-mar-2015' ;

╔═══════════════╦═══════════════╗
║ THISSTARTDATE ║ NEXTSTARTDATE ║
╠═══════════════╬═══════════════╣
║ 2014-12-01    ║ 2015-01-01    ║
║ 2015-01-01    ║ 2015-02-01    ║
║ 2015-01-02    ║ 2015-01-09    ║
║ 2015-02-01    ║ 2015-03-01    ║
╚═══════════════╩═══════════════╝

以及查询：

select  thisStartDate, nextStartDate, t.AssetID, ArrivalLocation, 
        round(sum(datediff(ss,ArrivalTime, DepartureTime))/(24.0*60*60),1) DaysAtLoc
from (        
select  thisStartDate, nextStartDate, t.AssetID, ArrivalLocation, ArrivalTime, 
        coalesce(min(MoveDate),nextStartDate) DepartureTime
from (
select  assetsInRange.thisStartDate, assetsInRange.nextStartDate, assetsInRange.assetID, 
        coalesce(ArrivalLocation,InitialLocation) ArrivalLocation, 
        coalesce(ArrivalTime,assetsInRange.thisStartDate) ArrivalTime
from 
      (
        select  thisStartDate, nextStartDate, assetID
        from    dt_range
                join t1 on MoveDate < nextStartDate
        group by thisStartDate, nextStartDate, assetID        
      ) assetsInRange
    left outer join
      (
        select  thisStartDate, nextStartDate, assetID, 
                max(MoveDate) precedingDtRangeMoveDt 
        from    dt_range 
                join t1 
                    on MoveDate < thisStartDate
        group by thisStartDate, nextStartDate, assetID
      ) 
      precedingMoveDt
        on (assetsInRange.assetID = precedingMoveDt.assetID)
    left outer join
      (
        select AssetID, MoveDate precedingDtRangeMoveDt, LocationID initialLocation
        from   t1
      ) 
        precedingMoveLoc
        on (precedingMoveDt.assetID = precedingMoveLoc.AssetID
            and precedingMoveDt.precedingDtRangeMoveDt = precedingMoveLoc.precedingDtRangeMoveDt)
    left outer join 
      (
        select AssetId, LocationId ArrivalLocation, MoveDate ArrivalTime
        from t1
      ) 
        arrivals 
        on assetsInRange.AssetID = arrivals.AssetId
                and ArrivalTime >= assetsInRange.thisStartDate
                and ArrivalTime < assetsInRange.nextStartDate
    group by assetsInRange.thisStartDate, assetsInRange.nextStartDate, assetsInRange.AssetId, 
            coalesce(ArrivalLocation,InitialLocation) , 
            coalesce(ArrivalTime,assetsInRange.thisStartDate) 
) t
left join t1 on t.assetID = t1.assetID
            and t1.MoveDate > ArrivalTime
            and t1.MoveDate < nextStartDate
group by thisStartDate, nextStartDate, t.AssetID, ArrivalLocation, ArrivalTime
) t
group by thisStartDate, nextStartDate, t.AssetID, ArrivalLocation
order by 1, 3;

注意-我假设资产的第一条记录表明它以前在任何位置都不存在……因此2014年12月-2015年1月的测试月不会显示在结果中，因为没有具有2014年移动日期的资产。

您可以使用滞后窗口功能来执行此操作，但我不知道Azure数据库是否支持它。否则，您可能不得不这样做使用CTE或进行一些子查询，非常感谢您的帮助！不幸的是，SQL Azure没有超前或滞后功能。简单的连接就可以了！！！我的下一个挑战是如何添加日期范围回答以下问题：对于2015年6月1日至2015年8月1日的日期范围，资产在每个位置停留了多少天。我可以必须跳转到存储过程才能找到答案。是的。假设MoveDate列包含项目移入的日期，那么它第一次在LOC1位置停留了4天，然后在LOC 99停留了4天，直到今天（2015年1月22日）它仍然停留在LOC1位置这是13天。我喜欢纯SQL解决方案。非常感谢！有没有办法修改它以拥有一个日期范围？因此，在两个日期之间，资产驻留在哪里，即使在该范围内没有移动事件…我想我将不得不为此执行存储过程…再次感谢！是的-我将附加到主答案以便于格式化。

create table dt_range 
    (thisStartDate date, 
     nextStartDate date, 
     primary key (thisStartDate,nextStartDate));

insert into dt_range 
select '01-dec-2014','01-jan-2015' union
select '01-jan-2015','01-feb-2015' union
select '02-jan-2015','09-jan-2015' union
select '01-feb-2015','01-mar-2015' ;

╔═══════════════╦═══════════════╗
║ THISSTARTDATE ║ NEXTSTARTDATE ║
╠═══════════════╬═══════════════╣
║ 2014-12-01    ║ 2015-01-01    ║
║ 2015-01-01    ║ 2015-02-01    ║
║ 2015-01-02    ║ 2015-01-09    ║
║ 2015-02-01    ║ 2015-03-01    ║
╚═══════════════╩═══════════════╝

select  thisStartDate, nextStartDate, t.AssetID, ArrivalLocation, 
        round(sum(datediff(ss,ArrivalTime, DepartureTime))/(24.0*60*60),1) DaysAtLoc
from (        
select  thisStartDate, nextStartDate, t.AssetID, ArrivalLocation, ArrivalTime, 
        coalesce(min(MoveDate),nextStartDate) DepartureTime
from (
select  assetsInRange.thisStartDate, assetsInRange.nextStartDate, assetsInRange.assetID, 
        coalesce(ArrivalLocation,InitialLocation) ArrivalLocation, 
        coalesce(ArrivalTime,assetsInRange.thisStartDate) ArrivalTime
from 
      (
        select  thisStartDate, nextStartDate, assetID
        from    dt_range
                join t1 on MoveDate < nextStartDate
        group by thisStartDate, nextStartDate, assetID        
      ) assetsInRange
    left outer join
      (
        select  thisStartDate, nextStartDate, assetID, 
                max(MoveDate) precedingDtRangeMoveDt 
        from    dt_range 
                join t1 
                    on MoveDate < thisStartDate
        group by thisStartDate, nextStartDate, assetID
      ) 
      precedingMoveDt
        on (assetsInRange.assetID = precedingMoveDt.assetID)
    left outer join
      (
        select AssetID, MoveDate precedingDtRangeMoveDt, LocationID initialLocation
        from   t1
      ) 
        precedingMoveLoc
        on (precedingMoveDt.assetID = precedingMoveLoc.AssetID
            and precedingMoveDt.precedingDtRangeMoveDt = precedingMoveLoc.precedingDtRangeMoveDt)
    left outer join 
      (
        select AssetId, LocationId ArrivalLocation, MoveDate ArrivalTime
        from t1
      ) 
        arrivals 
        on assetsInRange.AssetID = arrivals.AssetId
                and ArrivalTime >= assetsInRange.thisStartDate
                and ArrivalTime < assetsInRange.nextStartDate
    group by assetsInRange.thisStartDate, assetsInRange.nextStartDate, assetsInRange.AssetId, 
            coalesce(ArrivalLocation,InitialLocation) , 
            coalesce(ArrivalTime,assetsInRange.thisStartDate) 
) t
left join t1 on t.assetID = t1.assetID
            and t1.MoveDate > ArrivalTime
            and t1.MoveDate < nextStartDate
group by thisStartDate, nextStartDate, t.AssetID, ArrivalLocation, ArrivalTime
) t
group by thisStartDate, nextStartDate, t.AssetID, ArrivalLocation
order by 1, 3;

╔═══════════════╦═══════════════╦═════════╦═════════════════╦═══════════╗
║ THISSTARTDATE ║ NEXTSTARTDATE ║ ASSETID ║ ARRIVALLOCATION ║ DAYSATLOC ║
╠═══════════════╬═══════════════╬═════════╬═════════════════╬═══════════╣
║ 2015-01-01    ║ 2015-02-01    ║ CAR1    ║ LOC1            ║ 26.8      ║
║ 2015-01-01    ║ 2015-02-01    ║ CAR1    ║ LOC99           ║ 4.2       ║
║ 2015-01-01    ║ 2015-02-01    ║ CAR2    ║ LOC1            ║ 24.7      ║
║ 2015-01-01    ║ 2015-02-01    ║ CAR2    ║ LOC99           ║ 4.2       ║
║ 2015-01-01    ║ 2015-02-01    ║ CAR3    ║ LOC2            ║ 16.4      ║
║ 2015-01-02    ║ 2015-01-09    ║ CAR1    ║ LOC1            ║ 2.1       ║
║ 2015-01-02    ║ 2015-01-09    ║ CAR1    ║ LOC99           ║ 3.8       ║
║ 2015-01-02    ║ 2015-01-09    ║ CAR2    ║ LOC1            ║ 2.1       ║
║ 2015-01-02    ║ 2015-01-09    ║ CAR2    ║ LOC99           ║ 3.8       ║
║ 2015-02-01    ║ 2015-03-01    ║ CAR1    ║ LOC1            ║ 28        ║
║ 2015-02-01    ║ 2015-03-01    ║ CAR2    ║ LOC1            ║ 28        ║
║ 2015-02-01    ║ 2015-03-01    ║ CAR3    ║ LOC2            ║ 28        ║
╚═══════════════╩═══════════════╩═════════╩═════════════════╩═══════════╝