我如何替换 T-SQL 游标？
How could I replace a T-SQL cursor?
我想问你如何替换插入到我的存储过程中的游标。
实际上，我们发现游标是管理我的场景的唯一出路，但据我所知，这不是最佳做法。
这是我的 scenario:I 必须逐行递归计算库存并根据前几行中计算的内容设置季节。
我可以设置转会类型为"purchase"的赛季。其他转会应通过 T-SQL 查询设置正确的季节。
我应该计算季节的table有以下模板和假数据，但它们反映了真实情况：
Transfer Table Example
"FlgSeason"为null的行，按如下方式计算：按升序，游标从第3行开始往回走前几行，计算每个季节的存货量然后用库存的最小季节更新列季节。
这是我使用的代码：
CREATE TABLE [dbo].[transfers]
(
[rowId] [int] NULL,
[area] [int] NULL,
[store] [int] NULL,
[item] [int] NULL,
[date] [date] NULL,
[type] [nvarchar](50) NULL,
[qty] [int] NULL,
[season] [nvarchar](50) NULL,
[FlagSeason] [int] NULL
) ON [PRIMARY]
INSERT INTO [dbo].[transfers]
([rowId]
,[area]
,[store]
,[item]
,[date]
,[type]
,[qty]
,[season]
,[FlagSeason])
VALUES (1,1,20,300,'2015-01-01','Purchase',3,'2015-FallWinter',1)
, (2,1,20,300,'2015-01-01','Purchase',4,'2016-SpringSummer',1)
, (3,1,20,300,'2015-01-01','Sales',-1,null,null)
, (4,1,20,300,'2015-01-01','Sales',-2,null,null)
, (5,1,20,300,'2015-01-01','Sales',-1,null,null)
, (6,1,20,300,'2015-01-01','Sales',-1,null,null)
, (7,1,20,300,'2015-01-01','Purchase',4,'2016-FallWinter',1)
, (8,1,20,300,'2015-01-01','Sales',-1,null,null)
DECLARE @RowId as int
DECLARE db_cursor CURSOR FOR
Select RowID
from Transfers
where [FlagSeason] is null
order by RowID
OPEN db_cursor
FETCH NEXT FROM db_cursor INTO @RowId
WHILE @@FETCH_STATUS = 0
BEGIN
Update Transfers
set Season = (Select min (Season) as Season
from (
Select
Season
, SUM(QTY) as Qty
from Transfers
where RowID < @RowId
and [FlagSeason] = 1
group by Season
having Sum(QTY) > 0
)S
where s.QTY >= 0
)
, [FlagSeason] = 1
where rowId = @RowId
FETCH NEXT FROM db_cursor INTO @RowId
end
在这种情况下，查询将提取：
- 2015 秋冬 3 件数量
- 4 代表 2016 春夏。
比更新声明将设置 2015-fw（两个赛季的最小数量）。
然后 courson 前进到第 4 行，并再次运行查询以提取考虑到第 3 行的计算而更新的股票。所以结果应该是
- 数量 2 2015 FW
- 2016 春夏数量 4
然后更新将设置 2015 FW。
等等。
最终输出应该是这样的：
Output
实际上，唯一的出路是实现游标，现在扫描和更新大约 250 万行需要 30/40 分钟以上。有没有人知道不重复游标的解决方案？
提前致谢！
2008 年更新为 运行
IF OBJECT_ID('tempdb..#transfer') IS NOT NULL
DROP TABLE #transfer;
GO
CREATE TABLE #transfer (
RowID INT IDENTITY(1, 1) PRIMARY KEY NOT NULL,
Area INT,
Store INT,
Item INT,
Date DATE,
Type VARCHAR(50),
Qty INT,
Season VARCHAR(50),
FlagSeason INT
);
INSERT INTO #transfer ( Area,
Store,
Item,
Date,
Type,
Qty,
Season,
FlagSeason
)
VALUES (1, 20, 300, '20150101', 'Purchase', 3, '2015-SpringSummer', 1),
(1, 20, 300, '20150601', 'Purchase', 4, '2016-SpringSummer', 1),
(1, 20, 300, '20150701', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20150721', 'Sales', -2, NULL, NULL),
(1, 20, 300, '20150901', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20160101', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170101', 'Purchase', 4, '2017-SpringSummer', 1),
(1, 20, 300, '20170125', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170201', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170225', 'Sales', -1, NULL, NULL),
(1, 21, 301, '20150801', 'Purchase', 4, '2017-SpringSummer', 1),
(1, 21, 301, '20150901', 'Sales', -1, NULL, NULL),
(1, 21, 301, '20151221', 'Sales', -2, NULL, NULL),
(1, 21, 302, '20150801', 'Purchase', 1, '2016-SpringSummer', 1),
(1, 21, 302, '20150901', 'Purchase', 1, '2017-SpringSummer', 1),
(1, 21, 302, '20151101', 'Sales', -1, NULL, NULL),
(1, 21, 302, '20151221', 'Sales', -1, NULL, NULL),
(1, 20, 302, '20150801', 'Purchase', 1, '2016-SpringSummer', 1),
(1, 20, 302, '20150901', 'Purchase', 1, '2017-SpringSummer', 1),
(1, 20, 302, '20151101', 'Sales', -1, NULL, NULL),
(1, 20, 302, '20151221', 'Sales', -1, NULL, NULL);
WITH Purchases
AS (SELECT t1.RowID,
t1.Area,
t1.Store,
t1.Item,
t1.Date,
t1.Type,
t1.Qty,
t1.Season,
RunningInventory = ( SELECT SUM(t2.Qty)
FROM #transfer AS t2
WHERE t1.Type = t2.Type
AND t1.Area = t2.Area
AND t1.Store = t2.Store
AND t1.Item = t2.Item
AND t2.Date <= t1.Date
)
FROM #transfer AS t1
WHERE t1.Type = 'Purchase'
),
Sales
AS (SELECT t1.RowID,
t1.Area,
t1.Store,
t1.Item,
t1.Date,
t1.Type,
t1.Qty,
t1.Season,
RunningSales = ( SELECT SUM(ABS(t2.Qty))
FROM #transfer AS t2
WHERE t1.Type = t2.Type
AND t1.Area = t2.Area
AND t1.Store = t2.Store
AND t1.Item = t2.Item
AND t2.Date <= t1.Date
)
FROM #transfer AS t1
WHERE t1.Type = 'Sales'
)
SELECT Sales.RowID,
Sales.Area,
Sales.Store,
Sales.Item,
Sales.Date,
Sales.Type,
Sales.Qty,
Season = ( SELECT TOP 1
Purchases.Season
FROM Purchases
WHERE Purchases.Area = Sales.Area
AND Purchases.Store = Sales.Store
AND Purchases.Item = Sales.Item
AND Purchases.RunningInventory >= Sales.RunningSales
ORDER BY Purchases.Date, Purchases.Season
)
FROM Sales
UNION ALL
SELECT Purchases.RowID ,
Purchases.Area ,
Purchases.Store ,
Purchases.Item ,
Purchases.Date ,
Purchases.Type ,
Purchases.Qty ,
Purchases.Season
FROM Purchases
ORDER BY Sales.Area, Sales.Store, item, Sales.Date
*下面是原始答案**
我不明白 flagseason 专栏的目的，所以我没有包含它。从本质上讲，这会计算采购和销售的 运行 总和，然后找到每个销售交易的 purchase_to_date 库存至少 sales_to_date 流出量的季节。
IF OBJECT_ID('tempdb..#transfer') IS NOT NULL
DROP TABLE #transfer;
GO
CREATE TABLE #transfer (
RowID INT IDENTITY(1, 1) PRIMARY KEY NOT NULL,
Area INT,
Store INT,
Item INT,
Date DATE,
Type VARCHAR(50),
Qty INT,
Season VARCHAR(50),
FlagSeason INT
);
INSERT INTO #transfer ( Area,
Store,
Item,
Date,
Type,
Qty,
Season,
FlagSeason
)
VALUES (1, 20, 300, '20150101', 'Purchase', 3, '2015-FallWinter', 1),
(1, 20, 300, '20150601', 'Purchase', 4, '2016-SpringSummer', 1),
(1, 20, 300, '20150701', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20150721', 'Sales', -2, NULL, NULL),
(1, 20, 300, '20150901', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20160101', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170101', 'Purchase', 4, '2016-FallWinter', 1),
(1, 20, 300, '20170201', 'Sales', -1, NULL, NULL);
WITH Inventory
AS (SELECT *,
PurchaseToDate = SUM(CASE WHEN Type = 'Purchase' THEN Qty ELSE 0 END) OVER (ORDER BY Date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW),
SalesToDate = ABS(SUM(CASE WHEN Type = 'Sales' THEN Qty ELSE 0 END) OVER (ORDER BY Date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW))
FROM #transfer
)
SELECT Inventory.RowID,
Inventory.Area,
Inventory.Store,
Inventory.Item,
Inventory.Date,
Inventory.Type,
Inventory.Qty,
Season = CASE
WHEN Inventory.Season IS NULL
THEN ( SELECT TOP 1
PurchaseToSales.Season
FROM Inventory AS PurchaseToSales
WHERE PurchaseToSales.PurchaseToDate >= Inventory.SalesToDate
ORDER BY Inventory.Date
)
ELSE
Inventory.Season
END,
Inventory.PurchaseToDate,
Inventory.SalesToDate
FROM Inventory;
*更新*******************************
您需要一个数据索引来帮助排序才能执行此操作。
可能：
CREATE NONCLUSTERED INDEX IX_Transfer ON #transfer(Store, Item, Date) INCLUDE(Area,Qty,Season,Type)
您应该会看到对指定索引的索引扫描。它不会是一个搜索，因为示例查询不过滤任何数据并且包含所有数据。
此外，您需要从 SalesToDate 的 Partition By 子句中删除 Season。重置每个季节的销售额会使您的比较失败，因为滚动销售额需要与滚动库存进行比较，以便您确定销售库存的来源。
分区子句的其他两个提示：
不要重复分区依据和排序依据之间的字段。分区字段的顺序无关紧要，因为每个分区都会重置聚合。最好的情况是，有序的分区字段将被忽略，最坏的情况是它可能导致优化器以特定顺序聚合字段。这对结果没有任何影响，但会增加不必要的开销。
确保您的索引与分区 by/order 的定义匹配。
索引应该是[分区字段，顺序无所谓] + [排序字段，顺序需要匹配order by clause]。
在您的场景中，索引列应该在商店、项目和日期上。如果日期在商店或项目之前，则不会使用索引，因为优化器需要先按商店和项目处理分区，然后再按日期排序。
如果您的数据中可能有多个区域，则索引和分区子句需要
索引：地区、店铺、项目、日期
分区依据：区域、商店、项目按日期排序
参考Wes的回答，提出的解决方案已经差不多了。它运作良好，但我注意到季节分配无法正常工作，因为在我的场景中，库存应该由商店和商品本身计算和更新。我更新了脚本，添加了一些调整。此外，我添加了一些新的 "Fake" 数据以更好地理解我的场景及其工作原理。
IF OBJECT_ID('tempdb..#transfer') IS NOT NULL
DROP TABLE #transfer;
GO
CREATE TABLE #transfer (
RowID INT IDENTITY(1, 1) PRIMARY KEY NOT NULL,
Area INT,
Store INT,
Item INT,
Date DATE,
Type VARCHAR(50),
Qty INT,
Season VARCHAR(50),
FlagSeason INT
);
INSERT INTO #transfer ( Area,
Store,
Item,
Date,
Type,
Qty,
Season,
FlagSeason
)
VALUES (1, 20, 300, '20150101', 'Purchase', 3, '2015-SpringSummer', 1),
(1, 20, 300, '20150601', 'Purchase', 4, '2016-SpringSummer', 1),
(1, 20, 300, '20150701', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20150721', 'Sales', -2, NULL, NULL),
(1, 20, 300, '20150901', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20160101', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170101', 'Purchase', 4, '2017-SpringSummer', 1),
(1, 20, 300, '20170125', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170201', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170225', 'Sales', -1, NULL, NULL),
(1, 21, 301, '20150801', 'Purchase', 4, '2017-SpringSummer', 1),
(1, 21, 301, '20150901', 'Sales', -1, NULL, NULL),
(1, 21, 301, '20151221', 'Sales', -2, NULL, NULL),
(1, 21, 302, '20150801', 'Purchase', 1, '2016-SpringSummer', 1),
(1, 21, 302, '20150901', 'Purchase', 1, '2017-SpringSummer', 1),
(1, 21, 302, '20151101', 'Sales', -1, NULL, NULL),
(1, 21, 302, '20151221', 'Sales', -1, NULL, NULL),
(1, 20, 302, '20150801', 'Purchase', 1, '2016-SpringSummer', 1),
(1, 20, 302, '20150901', 'Purchase', 1, '2017-SpringSummer', 1),
(1, 20, 302, '20151101', 'Sales', -1, NULL, NULL),
(1, 20, 302, '20151221', 'Sales', -1, NULL, NULL)
;
WITH Inventory
AS (SELECT *,
PurchaseToDate = SUM(CASE WHEN Type = 'Purchase' THEN Qty ELSE 0 END) OVER (partition by store, item ORDER BY store, item,Date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW),
SalesToDate = ABS(SUM(CASE WHEN Type = 'Sales' THEN Qty ELSE 0 END) OVER (partition by store, item,season ORDER BY store, item, Date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW))
FROM #transfer
)
SELECT Inventory.RowID,
Inventory.Area,
Inventory.Store,
Inventory.Item,
Inventory.Date,
Inventory.Type,
Inventory.Qty,
Season = CASE
WHEN Inventory.Season IS NULL
THEN ( SELECT TOP 1
PurchaseToSales.Season
FROM Inventory AS PurchaseToSales
WHERE PurchaseToSales.PurchaseToDate >= Inventory.SalesToDate
and PurchaseToSales.Item = inventory.item --//Added
and PurchaseToSales.store = inventory.store --//Added
and PurchaseToSales.Area = Inventory.area --//Added
ORDER BY Inventory.Date
)
ELSE
Inventory.Season
END,
Inventory.PurchaseToDate,
Inventory.SalesToDate
FROM Inventory
此处输出：
enter image description here
经过这些调整后，它工作正常，但如果我将假数据与 600 万行数据中的真实数据切换 table，查询变得非常慢（每次提取约 400 行分钟）因为在子查询的 where 子句中插入了这些检查：
WHERE PurchaseToSales.PurchaseToDate >= Inventory.SalesToDate
and PurchaseToSales.Item = inventory.item --//Added
and PurchaseToSales.store = inventory.store --//Added
and PurchaseToSales.Area = Inventory.area --//Added
我尝试用 "Cross Apply" 函数替换子查询，但没有任何改变。我错过了什么吗？
提前致谢
我想问你如何替换插入到我的存储过程中的游标。
实际上，我们发现游标是管理我的场景的唯一出路，但据我所知，这不是最佳做法。
这是我的 scenario:I 必须逐行递归计算库存并根据前几行中计算的内容设置季节。
我可以设置转会类型为"purchase"的赛季。其他转会应通过 T-SQL 查询设置正确的季节。
我应该计算季节的table有以下模板和假数据，但它们反映了真实情况：
Transfer Table Example
"FlgSeason"为null的行，按如下方式计算：按升序，游标从第3行开始往回走前几行，计算每个季节的存货量然后用库存的最小季节更新列季节。
这是我使用的代码：
CREATE TABLE [dbo].[transfers]
(
[rowId] [int] NULL,
[area] [int] NULL,
[store] [int] NULL,
[item] [int] NULL,
[date] [date] NULL,
[type] [nvarchar](50) NULL,
[qty] [int] NULL,
[season] [nvarchar](50) NULL,
[FlagSeason] [int] NULL
) ON [PRIMARY]
INSERT INTO [dbo].[transfers]
([rowId]
,[area]
,[store]
,[item]
,[date]
,[type]
,[qty]
,[season]
,[FlagSeason])
VALUES (1,1,20,300,'2015-01-01','Purchase',3,'2015-FallWinter',1)
, (2,1,20,300,'2015-01-01','Purchase',4,'2016-SpringSummer',1)
, (3,1,20,300,'2015-01-01','Sales',-1,null,null)
, (4,1,20,300,'2015-01-01','Sales',-2,null,null)
, (5,1,20,300,'2015-01-01','Sales',-1,null,null)
, (6,1,20,300,'2015-01-01','Sales',-1,null,null)
, (7,1,20,300,'2015-01-01','Purchase',4,'2016-FallWinter',1)
, (8,1,20,300,'2015-01-01','Sales',-1,null,null)
DECLARE @RowId as int
DECLARE db_cursor CURSOR FOR
Select RowID
from Transfers
where [FlagSeason] is null
order by RowID
OPEN db_cursor
FETCH NEXT FROM db_cursor INTO @RowId
WHILE @@FETCH_STATUS = 0
BEGIN
Update Transfers
set Season = (Select min (Season) as Season
from (
Select
Season
, SUM(QTY) as Qty
from Transfers
where RowID < @RowId
and [FlagSeason] = 1
group by Season
having Sum(QTY) > 0
)S
where s.QTY >= 0
)
, [FlagSeason] = 1
where rowId = @RowId
FETCH NEXT FROM db_cursor INTO @RowId
end
在这种情况下，查询将提取：
- 2015 秋冬 3 件数量
- 4 代表 2016 春夏。
比更新声明将设置 2015-fw（两个赛季的最小数量）。
然后 courson 前进到第 4 行，并再次运行查询以提取考虑到第 3 行的计算而更新的股票。所以结果应该是
- 数量 2 2015 FW
- 2016 春夏数量 4
然后更新将设置 2015 FW。 等等。
最终输出应该是这样的：
Output
实际上，唯一的出路是实现游标，现在扫描和更新大约 250 万行需要 30/40 分钟以上。有没有人知道不重复游标的解决方案？
提前致谢！
2008 年更新为 运行
IF OBJECT_ID('tempdb..#transfer') IS NOT NULL
DROP TABLE #transfer;
GO
CREATE TABLE #transfer (
RowID INT IDENTITY(1, 1) PRIMARY KEY NOT NULL,
Area INT,
Store INT,
Item INT,
Date DATE,
Type VARCHAR(50),
Qty INT,
Season VARCHAR(50),
FlagSeason INT
);
INSERT INTO #transfer ( Area,
Store,
Item,
Date,
Type,
Qty,
Season,
FlagSeason
)
VALUES (1, 20, 300, '20150101', 'Purchase', 3, '2015-SpringSummer', 1),
(1, 20, 300, '20150601', 'Purchase', 4, '2016-SpringSummer', 1),
(1, 20, 300, '20150701', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20150721', 'Sales', -2, NULL, NULL),
(1, 20, 300, '20150901', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20160101', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170101', 'Purchase', 4, '2017-SpringSummer', 1),
(1, 20, 300, '20170125', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170201', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170225', 'Sales', -1, NULL, NULL),
(1, 21, 301, '20150801', 'Purchase', 4, '2017-SpringSummer', 1),
(1, 21, 301, '20150901', 'Sales', -1, NULL, NULL),
(1, 21, 301, '20151221', 'Sales', -2, NULL, NULL),
(1, 21, 302, '20150801', 'Purchase', 1, '2016-SpringSummer', 1),
(1, 21, 302, '20150901', 'Purchase', 1, '2017-SpringSummer', 1),
(1, 21, 302, '20151101', 'Sales', -1, NULL, NULL),
(1, 21, 302, '20151221', 'Sales', -1, NULL, NULL),
(1, 20, 302, '20150801', 'Purchase', 1, '2016-SpringSummer', 1),
(1, 20, 302, '20150901', 'Purchase', 1, '2017-SpringSummer', 1),
(1, 20, 302, '20151101', 'Sales', -1, NULL, NULL),
(1, 20, 302, '20151221', 'Sales', -1, NULL, NULL);
WITH Purchases
AS (SELECT t1.RowID,
t1.Area,
t1.Store,
t1.Item,
t1.Date,
t1.Type,
t1.Qty,
t1.Season,
RunningInventory = ( SELECT SUM(t2.Qty)
FROM #transfer AS t2
WHERE t1.Type = t2.Type
AND t1.Area = t2.Area
AND t1.Store = t2.Store
AND t1.Item = t2.Item
AND t2.Date <= t1.Date
)
FROM #transfer AS t1
WHERE t1.Type = 'Purchase'
),
Sales
AS (SELECT t1.RowID,
t1.Area,
t1.Store,
t1.Item,
t1.Date,
t1.Type,
t1.Qty,
t1.Season,
RunningSales = ( SELECT SUM(ABS(t2.Qty))
FROM #transfer AS t2
WHERE t1.Type = t2.Type
AND t1.Area = t2.Area
AND t1.Store = t2.Store
AND t1.Item = t2.Item
AND t2.Date <= t1.Date
)
FROM #transfer AS t1
WHERE t1.Type = 'Sales'
)
SELECT Sales.RowID,
Sales.Area,
Sales.Store,
Sales.Item,
Sales.Date,
Sales.Type,
Sales.Qty,
Season = ( SELECT TOP 1
Purchases.Season
FROM Purchases
WHERE Purchases.Area = Sales.Area
AND Purchases.Store = Sales.Store
AND Purchases.Item = Sales.Item
AND Purchases.RunningInventory >= Sales.RunningSales
ORDER BY Purchases.Date, Purchases.Season
)
FROM Sales
UNION ALL
SELECT Purchases.RowID ,
Purchases.Area ,
Purchases.Store ,
Purchases.Item ,
Purchases.Date ,
Purchases.Type ,
Purchases.Qty ,
Purchases.Season
FROM Purchases
ORDER BY Sales.Area, Sales.Store, item, Sales.Date
*下面是原始答案**
我不明白 flagseason 专栏的目的，所以我没有包含它。从本质上讲，这会计算采购和销售的 运行 总和，然后找到每个销售交易的 purchase_to_date 库存至少 sales_to_date 流出量的季节。
IF OBJECT_ID('tempdb..#transfer') IS NOT NULL
DROP TABLE #transfer;
GO
CREATE TABLE #transfer (
RowID INT IDENTITY(1, 1) PRIMARY KEY NOT NULL,
Area INT,
Store INT,
Item INT,
Date DATE,
Type VARCHAR(50),
Qty INT,
Season VARCHAR(50),
FlagSeason INT
);
INSERT INTO #transfer ( Area,
Store,
Item,
Date,
Type,
Qty,
Season,
FlagSeason
)
VALUES (1, 20, 300, '20150101', 'Purchase', 3, '2015-FallWinter', 1),
(1, 20, 300, '20150601', 'Purchase', 4, '2016-SpringSummer', 1),
(1, 20, 300, '20150701', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20150721', 'Sales', -2, NULL, NULL),
(1, 20, 300, '20150901', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20160101', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170101', 'Purchase', 4, '2016-FallWinter', 1),
(1, 20, 300, '20170201', 'Sales', -1, NULL, NULL);
WITH Inventory
AS (SELECT *,
PurchaseToDate = SUM(CASE WHEN Type = 'Purchase' THEN Qty ELSE 0 END) OVER (ORDER BY Date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW),
SalesToDate = ABS(SUM(CASE WHEN Type = 'Sales' THEN Qty ELSE 0 END) OVER (ORDER BY Date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW))
FROM #transfer
)
SELECT Inventory.RowID,
Inventory.Area,
Inventory.Store,
Inventory.Item,
Inventory.Date,
Inventory.Type,
Inventory.Qty,
Season = CASE
WHEN Inventory.Season IS NULL
THEN ( SELECT TOP 1
PurchaseToSales.Season
FROM Inventory AS PurchaseToSales
WHERE PurchaseToSales.PurchaseToDate >= Inventory.SalesToDate
ORDER BY Inventory.Date
)
ELSE
Inventory.Season
END,
Inventory.PurchaseToDate,
Inventory.SalesToDate
FROM Inventory;
*更新*******************************
您需要一个数据索引来帮助排序才能执行此操作。
可能：
CREATE NONCLUSTERED INDEX IX_Transfer ON #transfer(Store, Item, Date) INCLUDE(Area,Qty,Season,Type)
您应该会看到对指定索引的索引扫描。它不会是一个搜索，因为示例查询不过滤任何数据并且包含所有数据。
此外，您需要从 SalesToDate 的 Partition By 子句中删除 Season。重置每个季节的销售额会使您的比较失败，因为滚动销售额需要与滚动库存进行比较，以便您确定销售库存的来源。
分区子句的其他两个提示：
不要重复分区依据和排序依据之间的字段。分区字段的顺序无关紧要，因为每个分区都会重置聚合。最好的情况是，有序的分区字段将被忽略，最坏的情况是它可能导致优化器以特定顺序聚合字段。这对结果没有任何影响，但会增加不必要的开销。
确保您的索引与分区 by/order 的定义匹配。
索引应该是[分区字段，顺序无所谓] + [排序字段，顺序需要匹配order by clause]。 在您的场景中，索引列应该在商店、项目和日期上。如果日期在商店或项目之前，则不会使用索引，因为优化器需要先按商店和项目处理分区，然后再按日期排序。
如果您的数据中可能有多个区域，则索引和分区子句需要
索引：地区、店铺、项目、日期
分区依据：区域、商店、项目按日期排序
参考Wes的回答，提出的解决方案已经差不多了。它运作良好，但我注意到季节分配无法正常工作，因为在我的场景中，库存应该由商店和商品本身计算和更新。我更新了脚本，添加了一些调整。此外，我添加了一些新的 "Fake" 数据以更好地理解我的场景及其工作原理。
IF OBJECT_ID('tempdb..#transfer') IS NOT NULL
DROP TABLE #transfer;
GO
CREATE TABLE #transfer (
RowID INT IDENTITY(1, 1) PRIMARY KEY NOT NULL,
Area INT,
Store INT,
Item INT,
Date DATE,
Type VARCHAR(50),
Qty INT,
Season VARCHAR(50),
FlagSeason INT
);
INSERT INTO #transfer ( Area,
Store,
Item,
Date,
Type,
Qty,
Season,
FlagSeason
)
VALUES (1, 20, 300, '20150101', 'Purchase', 3, '2015-SpringSummer', 1),
(1, 20, 300, '20150601', 'Purchase', 4, '2016-SpringSummer', 1),
(1, 20, 300, '20150701', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20150721', 'Sales', -2, NULL, NULL),
(1, 20, 300, '20150901', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20160101', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170101', 'Purchase', 4, '2017-SpringSummer', 1),
(1, 20, 300, '20170125', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170201', 'Sales', -1, NULL, NULL),
(1, 20, 300, '20170225', 'Sales', -1, NULL, NULL),
(1, 21, 301, '20150801', 'Purchase', 4, '2017-SpringSummer', 1),
(1, 21, 301, '20150901', 'Sales', -1, NULL, NULL),
(1, 21, 301, '20151221', 'Sales', -2, NULL, NULL),
(1, 21, 302, '20150801', 'Purchase', 1, '2016-SpringSummer', 1),
(1, 21, 302, '20150901', 'Purchase', 1, '2017-SpringSummer', 1),
(1, 21, 302, '20151101', 'Sales', -1, NULL, NULL),
(1, 21, 302, '20151221', 'Sales', -1, NULL, NULL),
(1, 20, 302, '20150801', 'Purchase', 1, '2016-SpringSummer', 1),
(1, 20, 302, '20150901', 'Purchase', 1, '2017-SpringSummer', 1),
(1, 20, 302, '20151101', 'Sales', -1, NULL, NULL),
(1, 20, 302, '20151221', 'Sales', -1, NULL, NULL)
;
WITH Inventory
AS (SELECT *,
PurchaseToDate = SUM(CASE WHEN Type = 'Purchase' THEN Qty ELSE 0 END) OVER (partition by store, item ORDER BY store, item,Date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW),
SalesToDate = ABS(SUM(CASE WHEN Type = 'Sales' THEN Qty ELSE 0 END) OVER (partition by store, item,season ORDER BY store, item, Date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW))
FROM #transfer
)
SELECT Inventory.RowID,
Inventory.Area,
Inventory.Store,
Inventory.Item,
Inventory.Date,
Inventory.Type,
Inventory.Qty,
Season = CASE
WHEN Inventory.Season IS NULL
THEN ( SELECT TOP 1
PurchaseToSales.Season
FROM Inventory AS PurchaseToSales
WHERE PurchaseToSales.PurchaseToDate >= Inventory.SalesToDate
and PurchaseToSales.Item = inventory.item --//Added
and PurchaseToSales.store = inventory.store --//Added
and PurchaseToSales.Area = Inventory.area --//Added
ORDER BY Inventory.Date
)
ELSE
Inventory.Season
END,
Inventory.PurchaseToDate,
Inventory.SalesToDate
FROM Inventory
此处输出：
enter image description here
经过这些调整后，它工作正常，但如果我将假数据与 600 万行数据中的真实数据切换 table，查询变得非常慢（每次提取约 400 行分钟）因为在子查询的 where 子句中插入了这些检查：
WHERE PurchaseToSales.PurchaseToDate >= Inventory.SalesToDate
and PurchaseToSales.Item = inventory.item --//Added
and PurchaseToSales.store = inventory.store --//Added
and PurchaseToSales.Area = Inventory.area --//Added
我尝试用 "Cross Apply" 函数替换子查询，但没有任何改变。我错过了什么吗？
提前致谢