SQL Query的性能问题

Question

I am pulling data from two tables-Forecast and Orders to compute sales forecast accuracy.

Steps I am taking:

1. Identifying all exhaustive combinations of product-region-demand month b/w both data sets...let's call this (1)

2. Identifying different forecast snapshots in forecast data... let's call this (2)

3. Performing a cross-join of (1) and (2)...let's call this (3)

4. Performing the "SUMIF()" equivalent on the lines from (3) for both orders and forecast. For example, if I am comparing forecast to actual orders for February,

Jan "INDPOR" Forecast---> For some Product/Region-Feb Delivery Combination: February Forecast (generated in January) vs. Orders booked after Jan 1st with a delivery schedule in Feb

Feb "INDPOR" Forecast---> For the same Product/Region-Feb Delivery Date Combination: February Forecast (generated in February) vs. Orders booked after Jan 27th* with a delivery schedule in Feb

Note 1: Generating multiple forecasts for the same month

Note 2: Fiscal calendar definitions used; that is why Feb starts on Jan 27th

Output is generating correctly. But, it is painfully slow (1 hour +). Please help me fine-tune this and make it faster as I will need to use this for larger data sets too.

Other Details:

1. I am running this on SQL Server 2014 locally from my desktop.Uploading this using the SQL data import wizard into SQL from an Excel file currently
2. Input Forecast data: ForecastAggTable
3. Input Orders data: OrderAggTable

Input and Output Files

Code:

Select * 
from
    (

            Select *,

            (Select isnull(sum([Forecast Qty]),0) from ForecastAggTable t2 where t2.LOB=D.LOB and
                    t2.[Demand Month]=D.[Demand Month] and t2.Class=D.Class 
                    and t2.[Item Type]=D.[Item Type] and t2.[LoB Region]=D.[LoB Region] and
                    t2.[Key Account]=D.[Key Account] and t2.Country=D.Country 
                    and t2.[Master Customer]=D.[Master Customer] and t2.[INDPOR Version]=D.[INDPOR Version])[Forecast Qty],

            (
                    Select isnull(sum([Order Qty]),0) from OrderAggTable t1 where t1.LOB=D.LOB and
                    t1.[SAD Month]=D.[Demand Month] and t1.Class=D.Class 
                    and t1.[Item Type]=D.[Item Type] and t1.[LoB Region]=D.[LoB Region] and
                    t1.[Key Account]=D.[Key Account] and t1.Country=D.Country 
                    and t1.[Master Customer]=D.[Master Customer] and t1.[Book Date]>=D.[INDPOR Timestamp]
            )[SAD-OrderQty],

            (
                    Select isnull(sum([Order Revenue]),0) from OrderAggTable t1 where t1.LOB=D.LOB and
                    t1.[SAD Month]=D.[Demand Month] and t1.Class=D.Class 
                    and t1.[Item Type]=D.[Item Type] and t1.[LoB Region]=D.[LoB Region] and
                    t1.[Key Account]=D.[Key Account] and t1.Country=D.Country 
                    and t1.[Master Customer]=D.[Master Customer] and t1.[Book Date]>=D.[INDPOR Timestamp]
            )[SAD-OrderRevenue],


            (
                    Select isnull(sum([Order Qty]),0) from OrderAggTable t1 where t1.LOB=D.LOB and
                    t1.[RDD Month]=D.[Demand Month] and t1.Class=D.Class 
                    and t1.[Item Type]=D.[Item Type] and t1.[LoB Region]=D.[LoB Region] and
                    t1.[Key Account]=D.[Key Account] and t1.Country=D.Country 
                    and t1.[Master Customer]=D.[Master Customer] and t1.[Book Date]>=D.[INDPOR Timestamp]
            )[RDD-OrderQty],

            (
                    Select isnull(sum([Order Revenue]),0) from OrderAggTable t1 where t1.LOB=D.LOB and
                    t1.[RDD Month]=D.[Demand Month] and t1.Class=D.Class 
                    and t1.[Item Type]=D.[Item Type] and t1.[LoB Region]=D.[LoB Region] and
                    t1.[Key Account]=D.[Key Account] and t1.Country=D.Country 
                    and t1.[Master Customer]=D.[Master Customer] and t1.[Book Date]>=D.[INDPOR Timestamp]
            )[RDD-OrderRevenue]


            from
            (
            Select distinct LOB,[INDPOR Version],[INDPOR Timestamp],[Demand Month],
            [Demand Quarter],[Min Date],Class,[Item Type],[Offer PF],
            [LoB Region],[Key Account],Country,[Master Customer]

            from

            (

                            Select V.LOB,V.[SAD Month][Demand Month],V.[SAD Quarter][Demand Quarter],V.[SAD Min Date][Min Date],V.Class,
                            [Item Type],[Offer PF],[LoB Region],[Key Account],Country,[Master Customer]
                            from OrderAggTable V

                            union

                            (
                            Select Z.LOB,Z.[RDD Month][Demand Month],Z.[RDD Quarter][Demand Quarter],Z.[RDD Min Date][Min Date],Z.Class,
                            [Item Type],[Offer PF],[LoB Region],[Key Account],Country,[Master Customer]
                            from OrderAggTable Z
                            )

                            union

                            (
                            Select LOB,[Demand Month],[Demand Quarter],[Min Date],Class[Class],[Item Type],[Offer PF],[LoB Region],
                            [Key Account],Country,[Master Customer] from ForecastAggTable
                            )
            )A

            cross join

            (
            select distinct [INDPOR Version],[INDPOR Timestamp] 
            from ForecastAggTable
            )B
            )D
            where [Min Date]>=[INDPOR Timestamp]
            )E
            where ([SAD-OrderQty] +  [RDD-OrderQty] + [Forecast Qty]<>0)

Answer 1

How about simplifying, and doing less passes of your tables.

In this example I do two scans of the forecast table, one for the distinct, and one for the union, and one scan of the orders table.

with cte as
(
 select distinct [INDPOR Version],[INDPOR Timestamp] 
            from ForecastAggTable
)
,cte2 as
(
Select 
    V.LOB
    ,iif(DUP=0,V.[SAD Month]    ,V.[RDD Month]      )   [Demand Month]
    ,iif(DUP=0,V.[SAD Quarter]  ,V.[RDD Quarter]    )   [Demand Quarter]
    ,iif(DUP=0,V.[SAD Min Date] ,V.[RDD Min Date]   )   [Min Date]
    ,V.[Book Date]
    ,V.Class
    ,V.[Item Type]
    ,V.[Offer PF]
    ,V.[LoB Region]
    ,V.[Key Account]
    ,V.Country
    ,V.[Master Customer]
    ,null [INDPOR Version]
    ,null [Forecast Qty]
    ,iif(DUP=0,v.[Order Qty]    ,null   )       [SAD-OrderQty]
    ,iif(DUP=0,V.[Order Revenue]    ,null   )   [SAD-OrderRevenue]
    ,iif(DUP=1,V.[Order Qty]    ,null   )       [RDD-OrderQty]
    ,iif(DUP=1,V.[Order Revenue]    ,null   )   [RDD-OrderRevenue]
from OrderAggTable V
cross join (select dup from (values (0),(1))a(dup)) a
union all
Select 
    LOB
    ,[Demand Month]
    ,[Demand Quarter]
    ,[Min Date]
    ,[Min Date]
    ,Class
    ,[Item Type]
    ,[Offer PF]
    ,[LoB Region]
    ,[Key Account]
    ,Country
    ,[Master Customer] 
    ,[INDPOR Version]
    ,[Forecast Qty] 
    ,null[SAD-OrderQty]
    ,null[SAD-OrderRevenue]
    ,null[RDD-OrderQty]
    ,null[RDD-OrderRevenue]
    from ForecastAggTable
)
select
    cte2.LOB
    ,cte.[INDPOR Version]
    ,cte.[INDPOR Timestamp]
    ,cte2.[Demand Month]
    ,cte2.[Demand Quarter]
    ,cte2.[Min Date]
    ,cte2.Class
    ,cte2.[Item Type]
    ,cte2.[Offer PF]
    ,cte2.[LoB Region]
    ,cte2.[Key Account]
    ,cte2.Country
    ,cte2.[Master Customer]
    ,isnull(sum(cte2.[Forecast Qty]    ),0) [Forecast Qty]     
    ,isnull(sum(cte2.[SAD-OrderQty]    ),0) [SAD-OrderQty]
    ,isnull(sum(cte2.[SAD-OrderRevenue])    ,0) [SAD-OrderRevenue]
    ,isnull(sum(cte2.[RDD-OrderQty]    ),0) [RDD-OrderQty]     
    ,isnull(sum(cte2.[RDD-OrderRevenue])    ,0) [RDD-OrderRevenue]
from cte2
inner join cte
on cte2.[Book Date]>=cte.[INDPOR Timestamp]
where isnull(cte2.[INDPOR Version],cte.[INDPOR Version])=cte.[INDPOR Version]
group by    
     cte2.LOB
    ,cte2.[Demand Month]
    ,cte2.[Demand Quarter]
    ,cte2.[Min Date]
    ,cte2.Class
    ,cte2.[Item Type]
    ,cte2.[Offer PF]
    ,cte2.[LoB Region]
    ,cte2.[Key Account]
    ,cte2.Country
    ,cte2.[Master Customer]
    ,cte.[INDPOR Version]
    ,cte.[INDPOR Timestamp]
having 
    isnull(sum(cte2.[Forecast Qty]     ),0) + 
    isnull(sum(cte2.[SAD-OrderQty]     ),0) +
    isnull(sum(cte2.[RDD-OrderQty]     ),0) 
    !=0