SQL Reloaded: The WINDOW Clause in SQL Server 2022 (Part I: Simple Aggregations)

Between the many new features introduced in SQL Server 2022, Microsoft brings the WINDOW clause for defining the partitioning and ordering of a dataset which uses window functions. But before unveiling the change, let's take a walk down the memory lane.

In the early ages of SQL Server, many of descriptive statistics techniques were resuming in using the averages over a dataset that contained more or less complex logic. For example, to get the total and average of sales per Month, the query based on AdventureWorks database would look something like:

-- aggregated sales orders - detailed (SQL Server 2000+)
SELECT SOL.ProductId
, Year(SOH.OrderDate) [Year]
, Month(SOH.OrderDate) [Month]
, SUM(SOL.OrderQty) TotalQty
, AVG(SOL.OrderQty) AverageQty
FROM Sales.SalesOrderDetail SOL
     JOIN Sales.SalesOrderHeader SOH
	   ON SOL.SalesOrderId = SOH.SalesOrderId
WHERE SOL.ProductId IN (745)
  AND Year(SOH.OrderDate) = 2012
  AND Month(SOH.OrderDate) BETWEEN 1 AND 3
GROUP BY SOL.ProductId
, Year(SOH.OrderDate) 
, Month(SOH.OrderDate)

When possible, the base logic was encapsulated within a view, hiding query's complexity from the users, allowing also reuse and better maintenance, just to mention a few of the benefits of this approach:

-- encapsulating the logic into a view (SQL Server 2000+)
CREATE OR ALTER VIEW Sales.vSalesOrders
AS
-- sales orders details
SELECT SOL.SalesOrderId 
, SOL.ProductId
, Cast(SOH.OrderDate as Date) OrderDate
, Year(SOH.OrderDate) [Year]
, Month(SOH.OrderDate) [Month]
, Cast(SOL.OrderQty as decimal(18,2)) OrderQty
-- many more columns 
FROM Sales.SalesOrderDetail SOL
     JOIN Sales.SalesOrderHeader SOH
	   ON SOL.SalesOrderId = SOH.SalesOrderId
/* -- some constraints can be brought directly into the view
WHERE SOL.ProductId IN (745)
  AND Year(SOH.OrderDate) = 2012
  AND Month(SOH.OrderDate) BETWEEN 1 AND 3
*/

The above query now becomes:

 

-- aggregated sales orders - simplified (SQL Server 2000+)
SELECT SOL.ProductId
, SOL.[Year]
, SOl.[Month]
, SUM(SOL.OrderQty) TotalQty
, AVG(SOL.OrderQty) AverageQty
FROM Sales.vSalesOrders SOL
WHERE SOL.ProductId IN (745)
  AND SOL.[Year] = 2012
  AND SOL.[Month] BETWEEN 1 AND 3
GROUP BY SOL.ProductId
, SOL.[Year]
, SOl.[Month]

In many cases, performing this kind of aggregations was all the users wanted. However, quite often it's useful to look and the individual sales and consider them as part of the broader picture. For example, it would be interesting to know, what's the percentage of an individual value from the total (see OrderQtyPct) or any similar aggregate information. In SQL Server 2000 addressing such requirements would involve a join between the same view - one query with the detailed records, while the other contains the aggregated data:

-- sales orders from the totals (SQL Server 2000+)
SELECT SOL.*
, ASO.TotalQty
, Cast(CASE WHEN ASO.TotalQty <> 0 THEN 100*SOL.OrderQty/ASO.TotalQty ELSE 0 END as decimal(18,2)) OrderQtyPct
, ASO.AverageQty
FROM Sales.vSalesOrders SOL
     JOIN ( -- aggregated sales orders
		SELECT SOL.ProductId
		, SOL.[Year]
		, SOl.[Month]
		, SUM(SOL.OrderQty) TotalQty
		, AVG(SOL.OrderQty) AverageQty
		FROM Sales.vSalesOrders SOL
		WHERE SOL.ProductId IN (745)
		  AND SOL.[Year] = 2012
		  AND SOL.[Month] BETWEEN 1 AND 3
		GROUP BY SOL.ProductId
		, SOL.[Year]
		, SOl.[Month]
	) ASO
	ON SOL.ProductId = ASO.ProductId 
   AND SOL.[Year] = ASO.[Year]
   AND SOL.[Month] = ASO.[Month]
ORDER BY SOL.ProductId
, SOL.OrderDate

Now, just imagine that you can't create a view and having to duplicate the logic each time the view is used! Aggregating the data at different levels would require similar joins to the same view or piece of logic. 

Fortunately, SQL Server 2005 came with two long-awaited features, common table expressions (CTEs) and window functions, which made a big difference. First, CTEs allowed defining inline views that can be referenced multiple times. Secondly, the window functions allowed aggregations within a partition.

 

-- sales orders with CTE SQL Server 2005+ query 
WITH CTE
AS (--sales orders in scope
SELECT SOL.SalesOrderId 
, SOL.ProductId
, Cast(SOH.OrderDate as Date) OrderDate
, Year(SOH.OrderDate) [Year]
, Month(SOH.OrderDate) [Month]
, SOL.OrderQty
FROM Sales.SalesOrderDetail SOL
     JOIN Sales.SalesOrderHeader SOH
	   ON SOL.SalesOrderId = SOH.SalesOrderId
WHERE SOL.ProductId IN (745)
  AND Year(SOH.OrderDate) = 2012
  AND Month(SOH.OrderDate) BETWEEN 1 AND 3
)
SELECT SOL.SalesOrderId 
, SOL.ProductId
, SOL. OrderDate
, SOL.[Year]
, SOL.[Month]
, SOL.OrderQty
, SUM(SOL.OrderQty) OVER(PARTITION BY SOL.[Year], SOL.[Month]) TotalQty
, AVG(SOL.OrderQty)  OVER(PARTITION BY SOL.[Year], SOL.[Month]) AverageQty
FROM CTE SOL
WHERE SOL.ProductId IN (745)
  AND SOL.[Year] = 2012
  AND SOL.[Month] BETWEEN 1 AND 3

This kind of structuring the queries allows to separate the base logic for better maintainability, readability and fast prototyping. Once the logic from CTE becomes stable, it can be moved within a view, following to replace the CTE reference with view's name in the final query. On the other side, the window functions allow writing more flexible and complex code, even if the statements can become occasionally complex (see OrderQtyPct):

 

-- aggregated sales orders (SQL Server 2005+)
SELECT SOL.SalesOrderId 
, SOL.ProductId
, SOL. OrderDate
, SOL.[Year]
, SOL.[Month]
, SOL.OrderQty
, SUM(SOL.OrderQty) OVER(PARTITION BY SOL.[Year], SOL.[Month]) TotalQty
, AVG(SOL.OrderQty)  OVER(PARTITION BY SOL.[Year], SOL.[Month]) AverageQty
, Cast(CASE WHEN SUM(SOL.OrderQty) OVER(PARTITION BY SOL.[Year], SOL.[Month]) <> 0 THEN 100*SOL.OrderQty/SUM(SOL.OrderQty) OVER(PARTITION BY SOL.[Year], SOL.[Month]) ELSE 0 END as decimal(18,2)) OrderQtyPct
FROM Sales.vSalesOrders SOL
WHERE SOL.ProductId IN (745)
  AND SOL.[Year] = 2012
  AND SOL.[Month] BETWEEN 1 AND 3

Now, SQL Server 2022 allows to further simplify the logic by allowing to define with a name the window at the end of the statement and reference the name in several window functions (see last line of the query):

-- Aggregations per month (SQL Server 2022+)
SELECT SOL.SalesOrderId 
, SOL.ProductId
, SOL. OrderDate
, SOL.[Year]
, SOL.[Month]
, SOL.OrderQty
, SUM(SOL.OrderQty) OVER SalesByMonth AS TotalQty
, AVG(SOL.OrderQty) OVER SalesByMonth AS AverageQty
, Cast(CASE WHEN SUM(SOL.OrderQty) OVER SalesByMonth <> 0 THEN 100*SOL.OrderQty/SUM(SOL.OrderQty) OVER SalesByMonth ELSE 0 END as decimal(18,2)) OrderQtyPct
FROM Sales.vSalesOrders SOL
WHERE SOL.ProductId IN (745)
  AND SOL.[Year] = 2012
  AND SOL.[Month] BETWEEN 1 AND 3
WINDOW SalesByMonth AS (PARTITION BY SOL.[Year], SOL.[Month])

Moreover, several windows can be defined. For example, aggregating the data also per year:

-- Aggregations per month and year (SQL Server 2022+) 
SELECT SOL.SalesOrderId 
, SOL.ProductId
, SOL. OrderDate
, SOL.[Year]
, SOL.[Month]
, SOL.OrderQty
, SUM(SOL.OrderQty) OVER SalesByMonth AS TotalQtyByMonth
, AVG(SOL.OrderQty) OVER SalesByMonth AS AverageQtyByMonth
, Cast(CASE WHEN SUM(SOL.OrderQty) OVER SalesByMonth <> 0 THEN 100*SOL.OrderQty/SUM(SOL.OrderQty) OVER SalesByMonth ELSE 0 END as decimal(18,2)) OrderQtyPctByMonth
, SUM(SOL.OrderQty) OVER SalesByYear AS TotalQtyByYear
, AVG(SOL.OrderQty) OVER SalesByYear AS AverageQtyByYear
, Cast(CASE WHEN SUM(SOL.OrderQty) OVER SalesByYear <> 0 THEN 100*SOL.OrderQty/SUM(SOL.OrderQty) OVER SalesByYear ELSE 0 END as decimal(18,2)) OrderQtyPctByYear
FROM Sales.vSalesOrders SOL
WHERE SOL.ProductId IN (745)
  AND SOL.[Year] = 2012
  AND SOL.[Month] BETWEEN 1 AND 3
WINDOW SalesByMonth AS (PARTITION BY SOL.[Year], SOL.[Month])
, SalesByYear AS  (PARTITION BY SOL.[Year])

Isn't that cool? It will take probably some time to get used in writing and reading this kind of queries, though using descriptive names for the windows should facilitate the process! 

As a side note, even if there's no product function like in Excel, there's a mathematical trick to transform a product into a sum of elements by applying the Exp (exponential) and Log (logarithm) functions (see example).

Happy coding!