# Set Functions: The StripCalculatedMembers() Function

Monday Apr 7th 2008 by William Pearson

Business Intelligence Architect Bill Pearson continues his examination of MDX functions, this time introducing StripCalculatedMembers(). In this article, we expose the function, and then lead a hands-on practice session with examples that reinforce the concepts.

This article is a member of the series, MDX Essentials. The series is designed to provide hands-on application of the fundamentals of the Multidimensional Expressions (MDX) language, with each tutorial progressively adding features designed to meet specific real-world needs.

For more information about the series in general, as well as the software and systems requirements for getting the most out of the lessons included, please see my first article, MDX at First Glance: Introduction to MDX Essentials.

Note: Current updates are assumed for MSSQL Server, MSSQL Server Analysis Services, and the related Books Online and Samples.

### Overview

In this lesson, we will introduce StripCalculatedMembers(), a basic set function which is often “just what the doctor ordered” in the context of the specific need. The general purpose of StripCalculatedMembers() is to retrieve the members of a specified set, after removing any calculated members.

StripCalculatedMembers() can be leveraged in a wide range of activities, from the support of simple list generation, to the support of sophisticated conditional and other calculations and presentations. We will introduce the function, commenting upon its operation and touching upon creative effects that we can employ it to deliver. As a part of our discussion, we will:

• Examine the syntax surrounding the function;
• Undertake illustrative examples of the uses of the function in practice exercises;
• Briefly discuss the results datasets we obtain in the practice examples.

### The StripCalculatedMembers() Function

#### Introduction

According to the Analysis Services Books Online, the StripCalculatedMembers() function “returns a set generated by removing calculated members from a specified set.” StripCalculatedMembers() has numerous applications. For example, the function can be leveraged within queries to create datasets, in reporting applications such as MSSQL Server Reporting Services, for the support of picklists within the reports, for the support of axes within various end presentations, and so forth. The StripCalculatedMembers() function provides an intuitive option anytime we need to present, in a returned dataset, all members –minus calculated members – that belong to a specified set.

As we have noted to have been the case with many individual MDX functions we have examined within this series, combining StripCalculatedMembers() with other functions allows us to further extend its power. We will get a taste of this synergy in the practice exercises that follow.

We will examine the syntax for the StripCalculatedMembers() function after a brief discussion in the next section. We will then explore, from the straightforward context of MDX queries, and within practice examples constructed to support hypothetical business needs, some of the capabilities it offers the knowledgeable user. This will allow us to activate what we explore in the Discussion and Syntax sections, and afford us some hands-on exposure in creating expressions that employ the StripCalculatedMembers() function.

#### Discussion

To restate our initial explanation of its operation, the StripCalculatedMembers() function examines a set expression that we specify and returns the members that remain after it removes all calculated members. StripCalculatedMembers() can be used for a great deal more than simple list retrieval, as we have intimated. When coupled with other functions or used within MDX scripts, among other applications, we can leverage StripCalculatedMembers() to support a wide range of analysis and reporting utility.

Let’s discuss syntax to further clarify the operation of StripCalculatedMembers().

#### Syntax

Syntactically, in using the StripCalculatedMembers() function to return a set of members (minus calculated members), the set expression upon which we seek to apply the function is specified within the parentheses to the right of the StripCalculatedMembers keyword. The function removes calculated members from the set expression (a valid MDX expression that returns a set) enclosed within the parentheses, and returns a set representing only the base members contained within the scope of the set expression. As we shall see, StripCalculatedMembers() removes all calculated members from a set, including those added within the query itself (via the WITH MEMBER keywords). StripCalculatedMembers() also removes all calculated members added to a specified set using either of the AddCalculatedMembers() or .AllMembers functions, both of which return calculated members defined on the Analysis Server.

NOTE: For more detail surrounding the AddCalculatedMembers() function, see Set Functions: The AddCalculatedMembers() Function, and for information about the .AllMembers function, see Set Functions: The .AllMembers Function. Both articles are members of my MDX Essentials series at Database Journal.

For a general introduction to calculated members, together with a discussion of further considerations and perspectives involved in working with calculated members, see Calculated Members: Introduction and Calculated Members: Further Considerations and Perspectives, respectively, both of which are members of my MDX in Analysis Services series at Database Journal.

The general syntax for the application of StripCalculatedMembers() appears in the following string:

`  StripCalculatedMembers( <<Set_Expression>> )`

Putting StripCalculatedMembers() to work is straightforward. When using the function to return the members, minus any calculated members, contained within a set expression, we simply supply the required set expression within the parentheses to the right of the StripCalculatedMembers keyword.

As an example, say we specify, within a query executed against the sample Adventure Works cube, a column axis containing all members of the Product Categories level of the Product dimension (specified as {[Product].[Product Categories].[Category].MEMBERS}), with a row axis such as the following:

`  STRIPCALCULATEDMEMBERS( {[Measures].ALLMEMBERS} )`

Moreover, say that we add a WHERE clause to filter the retrieved data set to Calendar Year 2004. Depending upon the calculated members we have defined within our cube (we might have added calculated members beyond those that appear in the pristine sample cube), we would expect to retrieve results similar to those depicted in Illustration 1.

Illustration 1: Example Returned Data: StripCalculatedMembers() Function Employed in Query

We can see, within the dataset returned above, that only base members / measures appear. (If we remove the StripCalculatedMembers() from around the rest of the row axis specification, we will see that a greater number of measures (both base and calculated) now appear, and that the column axis increases dramatically (from 30 measures, in my local cube, to 50-plus measures).

Because of the relative ease with which we can employ StripCalculatedMembers(), and because of the flexibility with which we can exploit it to meet various business needs (particularly those meeting metadata requirements), the function can become a popular member of our analysis and reporting toolsets. It is easy, for example, when considering the above scenario, to see that we might simply parameterize “on / off” behavior for the StripCalculatedMembers() function within a client application, such as Reporting Services, to allow information consumers to choose either “include” or “exclude” behavior with regard to calculated members within axes or picklists at report run time.

We will get some hands-on exposure to the StripCalculatedMembers() function in the section that follows.

#### Practice

Preparation: Access SQL Server Management Studio

To reinforce our understanding of the basics we have covered, we will use the StripCalculatedMembers() function within queries that illustrate its operation. The intention, of course, is to demonstrate the use of StripCalculatedMembers() in a straightforward, memorable manner.

We will turn to the SQL Server Management Studio as a platform from which to construct and execute the MDX we examine, and to view the results datasets we obtain. If you do not know how to access the SQL Server Management Studio in preparation for using it to query an Analysis Services cube (we will be using the sample Adventure Works cube in the Adventure Works DW Analysis Services database), please perform the steps of the following procedure, located in the References section of my articles index:

This procedure will take us through opening a new Query pane, upon which we can create our first query within the section that follows.

Procedure: Satisfy Business Requirements with MDX

As a basis for our practice example, we will assume that we have received a request for assistance from representatives of our client, the Adventure Works organization. As we have noted in other articles of the series, the Reporting department, a group of client-facing authors and developers, often requests assistance with designing queries to support organizational analysis and reporting efforts. As a part of our relationship with Adventure Works, as well as with other clients, we provide on-site staff augmentation for business requirements gathering and training, as well as for combined development workshops and “train the trainer” events.

In a brief discussion with members of the Reporting department, we learn that a need has arisen to craft MDX queries for some new analysis and reporting requirements. First, several requirements have been identified to generate datasets, from the Adventure Works cube, to support OLAP reports that management has requested. The client has implemented the integrated Microsoft BI solution, and, in addition to using Analysis Services as an OLAP data source, they use Reporting Services as an enterprise reporting solution. The MDX we explore together, we are told, will thus be adapted and extended for ultimate use within Reporting Services, in multiple parameterized reports.

The requests relayed by the client representatives evidence a need to present multidimensional data in a manner that we think might best be served with the StripCalculatedMembers() function. Once our colleagues provide an overview of the business requirements, and we conclude that StripCalculatedMembers() is likely to be a key component of the option we offer, we provide the details about the function and its use, much as we have done in the earlier sections of this article. We convince the authors that they might best become familiar with the StripCalculatedMembers() function by examining an introductory example, where we employ the function to generate a straightforward group of the members, excluding calculated members, that are contained within the scope of a specified set expression, based upon an example we provided in an earlier session where we demonstrated a means of generating a simple set of base and calculated members in results dataset.

Procedure: Use the StripCalculatedMembers() Function to Generate a Simple Set of Members (Calculated Members Excluded) in a Results Dataset

Let’s construct a simple query to provide a conceptual “starting point” for illustrating the use of the StripCalculatedMembers() function. We will leverage an example we encountered in Set Functions: The AddCalculatedMembers() Function, using it first to generate a basic data set that displays a single base member that we request, along with all calculated members that share the same parent, [Measures]. Once we established a dataset containing both base and calculated members, we will demonstrate how we might use StripCalculatedMembers() to remove calculated members from that set.

To reiterate the initial scenario, the client representatives have told us that they would like to see the base member / measure Internet Sales Amount, alongside all calculated members whose parent is [Measures] (in effect, practically all calculated members within their cube). Within the scope of our current visit, they add another requirement: once we have a working query that retrieves the desired base measure, together with all calculated members that exist as siblings to the desired measure, our colleagues wish to see how we might modify the query to once again remove the calculated members, leaving only the base measure – preferably in a way that requires minimal syntax modification, so as to easily support parameterization of an “include” or “exclude” state within a targeted client application, Reporting Services.

Our client colleagues present the following specifics for this initial illustration: they wish to design and build a query that presents Internet Sales Amount, alongside all calculated measures, for each of the Customer Countries purchasing Adventure Works products in operating Calendar Years 2003 and 2004. They tell us that they want Internet Sales Amount and the calculated members to appear as columns and the Customer Countries to appear as rows. Moreover, they wish to break out the values for each of the two Calendar Years, affording consumers the capability to easily compare, one above the other, a given Customer’s values for each year. In effect, they wish to see Internet Sales Amount and all calculated members presented by Customer Country and subanalyzed by Calendar Year (for each of 2003 and 2004).

The new twist in the original requirement, as our colleagues have told us, is that, in addition to being able to generate a dataset containing all calculated members, as noted on our previous visit, they then need to be able to strip the calculated members out - in a manner that will lend itself to “on – off” parameterization. The initial dataset we generate will contain the desired base member, along with all calculated members that share the same parent, [Measures]. With this as a starting point, we will be able to show the concepts behind using the StripCalculatedMembers() function. Once we have accomplished our immediate goal in this section, we will further evolve these concepts in meeting another business requirement in the procedure that follows it.

1.  Type (or cut and paste) the following query into the Query pane:

```
-- MDX065-1: Basic Use of ADDCALCULATEDMEMBERS() Function  (from MDX064-1)
SELECT
ON AXIS (0),
NON EMPTY
CROSSJOIN(
{[Customer].[Customer Geography].[Country].MEMBERS},
{[Date].[Calendar Year].[CY 2003]:[Date].[Calendar Year].[CY 2004]}
)
ON AXIS (1)
FROM
```

The Query pane appears, with our input, as shown in Illustration 2.

Illustration 2: Our Initial Query in the Query Pane ...

The above query sets the stage for our practice with the use of StripCalculatedMembers(), and certainly accomplishes the basic objective of illustrating, in the simplest manner, how it works. The idea is to generate a dataset to activate the concepts in the minds of our client colleagues.

2.  Execute the query by clicking the Execute button in the toolbar, as depicted in Illustration 3.

Illustration 3: Click Execute to Run the Query...

The Results pane is populated by Analysis Services, and a dataset similar to that partially shown in Illustration 4, appears.

Illustration 4: Results Dataset – Single Member with Sibling Calculated Members Scenario (Partial View)

In the returned dataset, we see all members of the Country level of the Customer dimension (Customer Geography hierarchy). We have juxtaposed the crossjoin of each Country with each of Calendar Years 2003 and 2004 (generating them with the Range (“:”) operator) with the associated Internet Sales Amount base member, and all sibling calculated member, values.

NOTE: For more detail surrounding the CrossJoin() function, see Basic Set Functions: The CrossJoin() Function. For an introduction to the .Members function, see my article MDX Members: Introducing Members and Member. Finally, for a discussion of the Range operator, see my article MDX Operators: The Basics. All articles are members of my MDX Essentials series at Database Journal.

3.  Select File -> Save MDXQuery1.mdx As ..., name the file MDX065-001, and place it in a meaningful location.

Per the client request, our next step is to generate, from the current data, a dataset containing only the single base member of interest, Internet Sales Amount. For this we will employ the StripCalculatedMembers() function.

4.  Replace the commented line atop the query with the following text:

`          -- MDX065-2: Basic Use of STRIPCALCULATEDMEMBERS() Function`

5.  Place the cursor within the query one line above the AddCalculatedMembers keyword.

6.  Press the ENTER key twice create an additional couple of empty lines above the AddCalculatedMembers keyword.

7.  Type the following into the space a line above the AddCalculatedMembers keyword:

`          STRIPCALCULATEDMEMBERS(`

8.  Type an additional right parenthesis ( “)” ) to the immediate right of the line containing the AddCalculatedMembers function.

The Query pane appears, with our changes circled, as depicted in Illustration 5 (relevant portions of the query only).

Illustration 5: Relevant Portions of the Query in the Query Pane (Modifications Circled) ...

The above query sets the stage for our practice with the use of StripCalculatedMembers(), and certainly accomplishes the basic objective of illustrating, in the simplest manner, how it works. The idea, again, is to generate a dataset to activate the concepts in the minds of our client colleagues.

9.  Execute the query by clicking the Execute button in the toolbar, as we did earlier.

The Results pane is populated by Analysis Services, and a dataset similar to that shown in Illustration 6, appears.

Illustration 6: Results Dataset – StripCalculatedMembers() in Action ...

In the returned dataset, we see the same axes as before, with the obvious difference lying in the measure column. All that appears now is the Internet Sales Amount base member; all sibling calculated members have disappeared. The resulting dataset provides an excellent demonstration of the action of the StripCalculatedMembers() function, which we have used to enclose an AddCalculatedMembers() component whose output we have verified independently in the steps preceding the addition of StripCalculatedMembers(). Having demonstrated the workings of the two functions in this fashion helps us to show our client colleagues that we have, within the current dataset query, the mechanics for parameterization with respect to the StripCalculatedMembers() function – we can make it possible to provide a parameter that enables / disables the function at runtime, perhaps with a parameter picklist of, say, “include” or “exclude” options for calculated members.

10.  Select File -> Save MDX065-001 As ..., name the file MDX065-002, and place it in a meaningful location.

Our developer / author colleagues express satisfaction with the contextual backdrop we have established for introducing the StripCalculatedMembers() function. We will employ the function again in our next steps, this time generating our “all members” dataset with another previously presented example, before once again eliminating calculated members from the set via the StripCalculatedMembers() function.

Procedure: Use the StripCalculatedMembers() Function to Generate Another Set of Members (Calculated Members Excluded) in a Filtered Results Dataset

In Set Functions: The .AllMembers Function, we examined a function in the MDX toolset whose purpose is to return a set composed of all members within a specified dimensional level or hierarchy. The set returned includes all calculated members contained within the specified level or hierarchy, so, depending upon the set specified in the function, the data retrieved is similar to that retrieved through the simple employment (such as that we saw in our first practice example above) of the AddCalculatedMembers() function.

In one of the practice examples we undertook, we described a client requirement to construct a query that presents all measures (including calculated members / measures) for each of the Product Categories offered by the organization for their current and prior year (2004 and 2003, respectively), presented by Product Category, and subanalyzed by Customer Country. Our colleagues explain that management is attempting to perform analysis upon the Categories, specifically within the context of the “contribution” of each Customer Country toward the totals for each Category value. .

Because the initial business requirement entailed working with all measures (“all members of the Measure dimension,” as it were), we explained that .AllMembers promised to be useful in generating the desired presentation. We confirmed our understanding of the stated needs, and then set out to craft a query that relied upon .AllMembers, in conjunction with a couple of other MDX functions, to meet the business need. We repeat these steps in this section, from which we will derive a set comprising all members within the Measures dimension, including calculated members.

1.  Select File --> New from the main menu, once again.

2.  Select Query with Current Connection from the cascading menu that appears next, as depicted in Illustration 7.

Illustration 7: Create a New Query with the Current Connection ...

A new tab, with a connection to the Adventure Works cube (we can see it listed in the selector of the Metadata pane, as expected) appears in the Query pane.

3.  Type (or cut and paste) the following query into the Query pane:

3. Type (or cut and paste) the following query into the Query pane:
```
-- MDX065-3: Basic Use of .ALLMEMBERS Function;  Measure Dimension
-- ( from MDX061-2)
SELECT
CROSSJOIN(
{[Measures].ALLMEMBERS},
{[Date].[Calendar Year].[CY 2004]:[Date].[Calendar Year].[CY 2003]})
ON AXIS (0),
CROSSJOIN(
{[Product].[Product Categories].CHILDREN},
[Customer].[Country].[Country].MEMBERS)
ON AXIS (1)
FROM
```

The Query pane appears, with our input, as shown in Illustration 8.

Illustration 8: Our Second Query in the Query Pane ...

4.  Execute the query by clicking the Execute button in the toolbar.

The Results pane is, once again, populated by Analysis Services. This time, the dataset partially depicted in Illustration 9 appears.

Illustration 9: Results Dataset – .AllMembers Applied to Deliver All Measures (Partial View)

In the returned dataset, we see the juxtaposed Years (2003 and 2004), which we generate via the MDX Range operator (“:”) and all measures within the cube – including calculated members / measures, which we deliver via the .AllMembers function. Moreover, we leverage the .Children and .Members functions to specify a row axis containing Product Categories, which we further subanalyze by Customer Country. We perform the desired juxtapositions within the query via the CrossJoin() function.

Of primary focus within this practice example is our use of the .AllMembers function, in conjunction with these other functions, to return all measures – in effect, “all members of the Measures dimension.” (We can easily verify operation by observing that all measures within the cube appear within the dataset – we can scroll over to see that all measures are present.) In this example, we can also see another characteristic of the behavior of .AllMembers in cases where a dimension contains only a single visible hierarchy: in such cases, the hierarchy can be referenced by the hierarchy name or the dimension name, because the dimension name in such a scenario is resolved to its only visible hierarchy. In our immediate example, Measures.AllMembers is a valid MDX expression because it resolves to the only hierarchy in the Measures dimension.

5.  Select File -> Save MDXQuery2.mdx As ..., name the file MDX065-003.mdx, and place it in the same location used to store the earlier query.

Per the client request, our next step is to generate a dataset containing only the base members of the Measures dimension. For this we will employ the StripCalculatedMembers() function.

6.  Replace the commented line atop the query with the following text:

`          -- MDX065-4: Another Basic Use of STRIPCALCULATEDMEMBERS() Function`

7.  Place the cursor within the query one line above {[Measures].ALLMEMBERS} (currently the fourth line from the top in the query), underneath the line containing the first CROSSJOIN keyword).

8.  Press the ENTER key twice create an additional couple of empty lines between the lines containing CROSSJOIN( and {[Measures].ALLMEMBERS}.

9.  Type the following into the space a line above {[Measures].ALLMEMBERS}.

`    STRIPCALCULATEDMEMBERS(`

10.  Type an additional right parenthesis ( “)” )to the immediate right of {[Measures].ALLMEMBERS} (between {[Measures].ALLMEMBERS} and the comma ( “ , “ ) that appears to its right).

The relevant portion of the Query pane appears, with our changes circled, as shown in Illustration 10.

Illustration 10: Relevant Portions of the Query in the Query Pane (Modifications Circled) ...

The above modifications set the stage for our practice with the use of StripCalculatedMembers(), this time within the context of calculated members being exposed via the .AllMembers function.

11.  Execute the query by clicking the Execute button in the toolbar, as we did earlier.

The Results pane is populated by Analysis Services, and a dataset similar to that partially depicted in Illustration 11, appears.

Illustration 11: Results Dataset – StripCalculatedMembers() in Action ... (Partial Dataset View)

In the returned dataset, we see the same axes as before, with the obvious difference lying in the measure columns. All that appears now are the base members of the Measures dimension; all calculated members have disappeared. The resulting dataset provides another demonstration of the action of the StripCalculatedMembers() function, which we have used to enclose an .AllMembers component whose output we have verified independently in the steps preceding the addition of StripCalculatedMembers().

Having demonstrated the workings of the two functions in this fashion once again helps us to show our client colleagues that we have, within the current dataset query, established the mechanics for parameterization with respect to the StripCalculatedMembers() function. As we noted in our first practice example above (where we based our stripping action upon a set of all Measure members which we had derived via the AddCalculatedMembers() function), we can make it possible to provide a parameter that enables / disables the function at runtime, again perhaps with a parameter picklist of, say, “include” or “exclude” options for calculated members.

12.  Select File -> Save MDX065-003.mdx As ..., name the file MDX065-004, and place it in a meaningful location.

Our client colleagues express satisfaction with the results, and confirm their understanding of the operation of the StripCalculatedMembers() function within the context we have presented in both practice exercises. We suggest to the team that, in addition to parameterization of a “show / don’t show calculated members” option and other possibilities, the Years (“beginning” and “ending,” for that matter) might be parameterized, that we might build in the capability to swap crossjoined members, and that we might add other capabilities within the ultimate reporting dataset query. Suffice it to say that, assuming a thorough knowledge of the various layers of the Microsoft integrated BI solution, one can obtain many powerful capabilities and features, and knowing “where to put the intelligence” within the sometimes multiple choices can mean highly tuned performance and effective solutions for consumers throughout our organizations. For more of my observations on this subject see Multi-Layered Business Solutions ... Require Multi-Layered Architects.

13.  Select File -> Exit to leave the SQL Server Management Studio, when ready.

### Summary ...

In this article, we explored the MDX StripCalculatedMembers() function, whose general purpose is to retrieve the members of a specified set, after removing any calculated members.

We examined the syntax involved with StripCalculatedMembers(), and then undertook a couple of illustrative practice examples of uses for the function, generating queries that capitalized upon its capabilities. Throughout our practice session, we briefly discussed the results datasets we obtained from each of the queries we constructed, as well as extending our discussion to other possible options and uses for the concepts we exposed.

Discuss this article in the MSSQL Server 2000 Analysis Services and MDX Topics Forum.

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