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-- missing member due to a non-typo on two axes select {[Customer][Customer Geography][Country][United Kingdom]} on columns, {[Customer][State-Province][Quebec],[Customer][State-Province] [England]} on rows from [Adventure Works] where [Measures][Internet Sales Amount]
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Quebec is back This result is quite strange it would seem to show that Quebec is in the United Kingdom, only sales were not very good there Not sure what s happening here To those of you who like looking at maps, after I wrote this query I discovered
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Practical MDX Queries for Microsoft SQL Ser ver Analysis Ser vices 2008
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a tiny village called Quebec in the United Kingdom! By Quebec, I mean the Quebec that is a province of Canada and is at the State-Province level
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Hiding Non-Typo Missing Members 1/2
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This is a preferable result Note the inclusion of the Exists function
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-- missing member suppressed by exists select {[Customer][Customer Geography][Country][United Kingdom]} on columns, exists({[Customer][State-Province][Quebec], [Customer][State-Province][England]}, {[Customer][Customer Geography][Country][United Kingdom]} ) on rows from [Adventure Works] where [Measures][Internet Sales Amount]
Result
Analysis
The Exists function is checking to see if Quebec and England are children of the United Kingdom It only returns the ones (in this case, only England) that evaluate to true If we had had Scotland in the dimension, that would have appeared even if it had null sales
Hiding Non-Typo Missing Members 2/2
An alternative approach is simply to have a Where clause in the MDX
Syntax
-- missing member suppressed by where clause select
C h a p te r 9 : Ve n n D i a g ra m s : V i s u a l i z i n g a n d M a n i p u l a t i n g S e t s
{[Customer][State-Province][Quebec],[Customer][State-Province] [England]} on columns from [Adventure Works] where ([Measures][Internet Sales Amount], [Customer][Customer Geography][Country][United Kingdom])
Result
Analysis
This works fine, too Perhaps the Exists version is a little more elegant, and it allows us to see United Kingdom in the grid
More on Exists 1/3
This is a really careless query easily done when you don t know the data well Because cubes can contain millions of members, it s not difficult to build meaningless sets as is done here
Syntax
-- Mountain-100 Black, 44 is not in Components select [Product][Category][Components] on columns, {[Product][Product][Product][ML Fork], [Product][Product][Product][Chain], [Product][Product][Mountain-100 Black, 44]} on rows from [Adventure Works]
Result
Practical MDX Queries for Microsoft SQL Ser ver Analysis Ser vices 2008
Analysis
Chain is in Components ML Fork is in Components with null sales Mountain-100 Black, 44 is in Bikes not Components Our results are wrong!
More on Exists 2/3
Let s try and get rid of Mountain-100 Black, 44 with a clever Non Empty
Syntax
-- but ML Fork is! select [Product][Category][Components] on columns, non empty {[Product][Product][Product][ML Fork], [Product][Product][Product][Chain], [Product][Product][Mountain-100 Black, 44]} on rows from [Adventure Works]
Result
Analysis
That s cool Mountain-100 Black, 44 has gone Chain is indeed a child of Components, but it s still not right ML Fork, which is in Components, has gone, too The next query fixes this
More on Exists 3/3
Here s one final attempt at solving the riddle of missing members Non Empty has been replaced by the Exists function
Syntax
-- ML Fork select [Product][Category][Components] on columns, exists({[Product][Product][Product][ML Fork], [Product][Product][Product][Chain],
C h a p te r 9 : Ve n n D i a g ra m s : V i s u a l i z i n g a n d M a n i p u l a t i n g S e t s
[Product][Product][Mountain-100 Black, 44]}, [Product][Category][Components]) on rows from [Adventure Works]
Result
Analysis
We got there at last ML Fork is a child of Components (even if sales were pretty bad) The purpose of this query (using Exists) and the previous query (using Non Empty) is to illustrate the subtle but vital difference between Non Empty and Exists When you suspect missing members are not caused by typos, then Exists is a safe bet
Counting Members in a Set
Here s quite a common request: How many customers do we have We need to establish the number of members in a set There are two ways of counting Two queries to run separately
Syntax
-- how many customers 1/2 with member [Measures][Customers] as count([Customer][Customer][Customer]) select [Measures][Customers] on columns from [Adventure Works] -- how many customers 2/2 with member [Measures][Customers] as [Customer][Customer][Customer]count select [Measures][Customers] on columns from [Adventure Works]
Practical MDX Queries for Microsoft SQL Ser ver Analysis Ser vices 2008
Result
Analysis
Same result from both queries: There are 18,484 customers First, we used the Count method function Second, we used the count property function
10
Views on Cubes: Working with Subcubes
Practical MDX Queries for Microsoft SQL Ser ver Analysis Ser vices 2008
f you are familiar with SQL, you may use views One use of a view on a relational table is to present only a part of the table Often, you will want to work on only a part of a cube The SSAS versions of SQL views are called perspectives, subselects, and subcubes In this chapter we get to exploit those perspectives, subselects, and subcubes Key concepts Views on cubes, visual totals Keywords Select, Non Visual, defaultmember, Create Subcube
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