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Into the Future
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How does the quantity sold in a fiscal year differ from that in a subsequent year This is also a ParallelPeriod query
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-- into the future with member [Measures][Quantity Sold] as iif(isempty([Measures][Reseller Order Quantity]),0, [Measures][Reseller Order Quantity]),format_string="#,#" member [Measures][Change from Next Year] as ([Measures][Reseller Order Quantity]) - (ParallelPeriod([Date][Fiscal] [Fiscal Year], 1,[Date][Fiscal]),[Measures][Reseller Order Quantity]), format_string="#,#" select [Date][Fiscal][Fiscal Year] on columns, {[Measures][Quantity Sold],[Measures][Change from Next Year]} on rows from [Adventure Works]
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8: Clockwork: Calculations Using Dates and Times
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To move into the future, all you have to do is use a negative number (here, it s 1) as the second numeric parameter for the ParallelPeriod function
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This shows yet another syntactical variation Here we convert the nulls into zeros again, but this time we adopt a two-step approach
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Syntax
-- gets rid of the nulls in cellset with member [Measures][Quantity Sold] as iif(isempty([Measures][Reseller Order Quantity]),0, [Measures][Reseller Order Quantity]),format_string="#,#" member [Measures][Change from Next Year] as ([Measures][Reseller Order Quantity]) (ParallelPeriod([Date][Fiscal][Fiscal Year], 1, [Date][Fiscal]),[Measures][Reseller Order Quantity]) member [Measures][Change] as iif(isempty([Measures][Change from Next Year]),0, [Measures][Change from Next Year]),format_string="#,#" select [Date][Fiscal][Fiscal Year] on columns, {[Measures][Quantity Sold],[Measures][Change]} on rows from [Adventure Works]
Result
Analysis
The second row is the Change measure This is, of course, a calculated measure You have already tried a few of these Only this one is different The Change measure is based on the Change from Next Year measure That, in turn, is also a calculated
Practical MDX Queries for Microsoft SQL Ser ver Analysis Ser vices 2008
measure The Change from Next Year is an intermediate measure You are free to use a calculated measure in another calculated measure This may simplify the logic and complexity of your code It s an incremental approach that many MDX people adopt
Introduction to Sum
So far, we have been examining differences across the time dimension It s often a requirement to look at totals (for example, a summation) across the time dimension This query is a starting point for a few examples of what is called aggregation
Syntax
-- SUM select {[Date][Calendar][Calendar Year][CY 2001], [Date][Calendar][Calendar Year][CY 2002]} on columns from [Adventure Works] where [Measures][Internet Order Quantity]
Result
Analysis
The result is the Internet Order Quantity measure for two calendar years on the Columns axis
Applying Sum 1/2
This is an interesting query in that, though syntactically valid, the result looks strange because it is wrong!
Syntax
-- incorrect cells with member [Date][Calendar][Two Years] as sum({[Date][Calendar][Calendar Year][CY 2001], [Date][Calendar][Calendar Year][CY 2002]},
8: Clockwork: Calculations Using Dates and Times
[Measures][Internet Order Quantity]) select {[Date][Calendar][Calendar Year][CY 2001], [Date][Calendar][Calendar Year][CY 2002],[Two Years]} on columns from [Adventure Works]
Result
Analysis
The Sum function has a set as the first parameter and a measure to aggregate as the second parameter The Sum function here adds the Internet Order Quantity for CY 2001 and CY 2002 The answer 3,690 is the correct answer But I forgot to have a Where slicer CY 2001 and CY 2002 are therefore using the default measure, Reseller Sales Amount In order to achieve sensible results with aggregation functions such as Sum, it s vital that the query is consistent in its use of measures Interestingly, the calculated member [Date][Calendar][Two Years] has a triple-part name and not a double name, such as [Measures][Two Years] It s a calculated member, sure, but not the special case of a calculated measure (more on this in the next query)
Applying Sum 2/2
Hopefully, this is better Note the inclusion of a Where clause that slices the cube on the Internet Order Quantity measure
Syntax
--where [Measures][Internet Order Quantity] with member [Date][Calendar][Two Years] as sum({[Date][Calendar][Calendar Year][CY 2001], [Date][Calendar][Calendar Year][CY 2002]}, [Measures][Internet Order Quantity]) select {[Date][Calendar][Calendar Year][CY 2001], [Date][Calendar][Calendar Year][CY 2002],[Two Years]} on columns from [Adventure Works] where [Measures][Internet Order Quantity]
Practical MDX Queries for Microsoft SQL Ser ver Analysis Ser vices 2008
Result
Analysis
This query returns the correct result It introduces a couple of new concepts First, it performs an aggregation with the Sum function Second, it shows the aggregation alongside two members of the Calendar hierarchy on the Columns axis Members on the same axis have to have the same dimensionality and hierarchality (unless you perform a Crossjoin) The member Two Years is therefore defined as [Date][Calendar] [Two Years] Calculated members that are members of the Measures dimension are defined as [Measures][membername] and are a subset of calculated members, called calculated measures Calculated members that are not part of the Measures dimension are simply called calculated members and they must be prefaced by both the dimension name and the dimension hierarchy name here, it s [Date][Calendar]
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