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5: Slice, Dice, and Filter : Using Where and Filter
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-- toppercent, 99 returns about half select [Measures][Internet Sales Amount] on columns, toppercent([Product][Product Categories][Subcategory],99, [Measures][Internet Sales Amount]) on rows from [Adventure Works]
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You are looking at the full cellset No, it has not returned the top 99 percent of the subcategories It has resulted in those subcategories whose total Internet sales include 99 percent of the total Internet sales of all the subcategories It has returned eight subcategories Shorts is the seventh and Bottles and Cages the eighth Without Bottles and Cages but with Shorts, the total is less than 99 percent of all sales Therefore, Bottles and Cages is appended after Shorts, even though we might have over 99 percent of total sales Toppercent does not add any more rows after the 99 percent is reached or surpassed
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As you have already guessed, there is also a Bottompercent function
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-- bottompercent, 1 returns about half select [Measures][Internet Sales Amount]
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Practical MDX Queries for Microsoft SQL Ser ver Analysis Ser vices 2008
on columns, non empty bottompercent([Product][Product Categories] [Subcategory],1,[Measures][Internet Sales Amount]) on rows from [Adventure Works]
Result
Analysis
The total sales of these subcategories represent just 1 percent (or possibly just over) of the total sales for all subcategories All the null values have been suppressed
Topsum
Here s a variation on a powerful theme, Topsum
Syntax
-- topsum all 3 add up to 26000000 select [Measures][Internet Sales Amount] on columns, topsum([Product][Product Categories][Subcategory],25000000, [Measures][Internet Sales Amount]) on rows from [Adventure Works]
5: Slice, Dice, and Filter : Using Where and Filter
Result
Analysis
The second parameter is $25,000,000 The sum of Road Bikes and Mountain Bikes is less than that If you add on Touring Bikes, the sum is more than that Therefore, we get our three best-selling subcategories for Internet sales, and together they contribute $25,000,000 (or just over) to our total Internet sales for all subcategories
Bottomsum
This is the very last query in this chapter Last but not least, as they say, even if the function name might suggest otherwise Here s Bottomsum
Syntax
-- bottomsum select [Measures][Internet Sales Amount] on columns, non empty bottomsum([Product][Product Categories] [Subcategory],100000,[Measures][Internet Sales Amount]) on rows from [Adventure Works]
Result
Analysis
Excluding nulls, these five subcategories are our worst five, with total sales of only $100,000 (or just over)
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6
Using the Abacus: Introduction to Calculations
Practical MDX Queries for Microsoft SQL Ser ver Analysis Ser vices 2008
n general, the measures in your cube are based directly or indirectly on the columns in your fact table in your star schema However, it s likely your reports will need further metrics These are often based on the existing measures in some way One way to devise these new measures is to use MDX query calculations In this chapter, we explore just how to do this In addition, we take a look at creating non-measure members and creating our own sets of data Key concepts Aliases, calculated measures, named sets, formatting, scopes
Keywords With Member, format_string, With Set, Create Member, currentmember, level, ordinal
With Clause
So far, to a large extent, we have been using the cube, dimension, hierarchy, and attribute designs that are defined in BIDS Maybe you design the cubes, or perhaps you inherit and work with cubes designed by others If you are unable or don t want to alter a design, MDX allows you to extend the cube functionality temporarily by using a With clause before the Select statement The following few queries give you an introduction to the With clause A similar clause, Create, will be covered later The With clause is also useful when you want an ad-hoc, one-off extension to the cube design and it s simply too much to go back and alter the cube in BIDS and then reprocess Be sure to try this query twice First, run the whole query including the With clause and the complete Select statement Then highlight all of the Select statement (and not the With clause) before executing the query again
Syntax
-- hello world calculated member/calculated measure with member [Measures][My Measure] as "Hello world" select [Measures][My Measure] on columns, [Date][Calendar][Calendar Year] on rows from [Adventure Works]
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