Let’s finalize our efforts by placing the logic within a Named
Set. Creating the Named Set within Analysis Services will
allow for easy reuse of a predefined sibling Sales Employees group in Reporting
Services, as well as other client applications, where we might, for
example, define a row in a report through the use of a single object.
22.
Replace the
top line of the query (commented out) with the following:
-- MDX051-002-3 Reusable Named Set using Filter() / IsSibling() Combination
23.
Select File
-> Save MDX051-002-2.mdx As ..., name the file MDX051-002-3,
and place it with the queries saved earlier.
24.
Place the
cursor to the immediate right of the statement inserted above (in the top row).
25.
Press the ENTER
key four times to “push down” the rest of the line, and to add space
between the comment line and the SELECT keyword.
26.
Insert the
following into the space between the comment line and the SELECT
keyword:
WITH
SET
[SALES OPERATIVES]
AS
'FILTER(
[Employee].[Employee Department].MEMBERS,
ISSIBLING([Employee].[Employee Department].CURRENTMEMBER,
[Employee].[Employee Department].[Sales Representative].[Jae B. Pak]))'
Here
we have simply defined a Named Set containing the logic that we used
within our row axis definition in the previous example.
27.
Replace the
following four lines within the Select statement (currently lines 13, 14,
15, and 16):
FILTER(
[Employee].[Employee Department].MEMBERS,
ISSIBLING([Employee].[Employee Department].CURRENTMEMBER,
[Employee].[Employee Department].[Sales Representative].[Jae B. Pak]))
with the following:
[SALES OPERATIVES]
The complete query is as
follows, if cutting and pasting is the preference:
-- MDX051-002-3 Reusable Named Set using Filter() / IsSibling() Combination
WITH
SET
[SALES OPERATIVES]
AS
'FILTER(
[Employee].[Employee Department].MEMBERS,
ISSIBLING([Employee].[Employee Department].CURRENTMEMBER,
[Employee].[Employee Department].[Sales Representative].[Jae B. Pak]))'
SELECT
{[Measures].[Reseller Sales Amount]} ON AXIS(0),
NONEMPTY( {
[SALES OPERATIVES]
})ON AXIS(1)
FROM
[Adventure Works]
WHERE
[Date].[Calendar].[Calendar Year].[CY 2004]
The Query pane appears,
with our input, as depicted in Illustration 12.
Illustration 12: Our Modified Query in the Query Pane ...
28.
Execute the
query by clicking the Execute button in the toolbar.
The Results pane is populated by Analysis
Services. This time, the dataset shown in Illustration 13 appears.
Illustration 13: Results Dataset Sibling Employee Members
via Named Set
In the returned dataset, we see the same filtered list of
employees. This serves to illustrate how we might meet the business need with
a Named Set, which, once created within the cube involved, would support
easy, consistent reporting via a single object for row / column definitions,
and the like.
29.
Select File
-> Save MDX049-002-3 to save the file.
The
client representatives confirm that their immediate goals have been met, and
that the illustrations we have provided can be easily extended to local
business scenarios where filtering for sibling members is useful in
meeting reporting and analysis requirements.
30.
Select File
-> Exit to leave the SQL Server Management Studio, when ready.
Summary ...
In
this article, we extended our examination of the IsSibling() function,
exploring its use, once again, as a conditional logic modifier - but this time
within the context of a filter, through its combination with the MDX Filter()
function. We stated that, along with the IIF() function, this is
another commonly employed approach for using IsSibling() within the
business environment.
We
next reviewed the general syntax involved in using IsSibling(). Finally,
we undertook illustrative examples whereby we put the IsSibling() function
to work, in combination with the Filter() function, initially within a
simple illustration to illustrate its general operation. We followed our
initial practice example with another, where we began by employing the IsSibling()
/ Filter() combination within a direct row-axis definition, before placing
the combination within a Named Set, to meet a hypothetical business need.
Throughout our practice session, we briefly discussed the results datasets
we obtained from each of the queries we constructed.
»
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