MDX statements

Introduction

MDX statements are what SQL queries are to relational databases, but instead acting on OLAP (multidimensional) databases. In the case of TM1, we will use these expressions to query a dimension (hierarchy) and its members, cubes and their data points, etc. You will find out that a lot is possible if you get the syntax right.

Topics

Sources
Credits
use-cases
Referencing elements
Using an existing subset in an expression
Elements at different levels
Sorting
Descendants and Ascendants
More on hierarchical structures
Planning Analytics hierarchies
Union and Intersect
Cube values
Filtering on attributes
Double lookups
Filtering over dimensions
Filtering with wildcards
More on sorting
Generate
Subsets based on other objects
Distinct elements
Orphans and top consolidations
TM1 users and groups
Application and control objects
Temporary subsets
TM1ELLIST
IS
Count
Escape character
Caveats
Excel
MDX views

Sources

Writing MDX statements will not be that easy, certainly not in the beginning. Where can you find help ?

  1. This very page you are looking at ! In all honesty and humbleness, it contains very good material.
  2. This very nice overview with other practical examples by George Tonkin.
  3. This high-quality overview for more details, written by Phillip Bichard and Martin Findon.
  4. MDX for views written by George Tonkin (see all parts of the series).
  5. Microsoft documentation on the topic. Also, see member properties and several related pages.
  6. Functions in IBM DB2. Mind you, not all these functions are supported in Planning Analytics, however it may add some more information you may find useful.
  7. TM1 has a 'Record expression' functionality:


  8. Record the relevant steps, much like the Macro recorder in MS Office applications - Visual Basic for Applications or VBA for short.
  9. PAW has equivalent functionality, where you could insert elements and make manipulations, then get the see/change/commit the generated MDX behind. Due to autocomplete of functions you can also see what is supported and learn from that.
  10. Working with Time Related MDX Functions by George Tonkin (you need an IBM ID to access).

Credits

I already dropped the name, George Tonkin. A great number of discoveries were done by him and he shared them to me and the TM1 community via this page but also through the TM1 forum. He does a lot of effort to advance the collective knowledge on things like MDX and REST API in the TM1 community. This page would not nearly be the same without his contributions. Send him a big thank you and please make sure to share your own findings with George and myself. Countless hours (or weeks) went into collecting and testing the information below and I (we) appreciate any comment / remark / addition / error correction.

MDX use-cases

As a TM1 developer, we mainly use MDX statements in the following cases:

  • to make dynamic subsets rather than static subsets. For example, a cubeview showing the sales of the customers who bought last month as well (and only those customers);
  • to create custom views in a Turbo Integrator (TI) process. We will often zero out (part of) a cube, this is clearing cells at the lowest level elements in certain dimensions. This list of elements can be generated with no need to loop through the dimension ourselves.
  • Active forms in Excel have dynamic row subsets, you can expand and contract consolidations. The list of elements in the rows can again be an MDX statement, even quite complex statements.

Mind the syntax, it is crucial to get that straight. If not, TM1 won‘t like it… Some of the statements can be generated in the Subset Editor: turn on the Properties Window (menu View), then choose Tools > Record Expression. Record the expression while you do the steps manually. Stop recording when you are finished.

General tips

the following high-level tips should be taken into account:

  • As MDX statements lead to dynamic selections of elements, it is important to keep performance in mind. Usually it's all really quick but pay attention to large dimensions with deeply nested consolidation structures. One would argue that at least elements that are not needed in the dimension, and do not contain historical data, should be removed from the dimension.
  • Try to keep the definition of MDX subsets rather condensed instead of having MDX expressions with thousands of characters. For instance, if you re-use the same code within 1 or more dynamic subsets, consider adopting a more modular approach. Create a different (public) subset with that piece of logic and use the resulting subset in other MDX statements. Refer to TM1SubsetToSet below in the text. It will certainly lead to more maintainable subsets and MDX expressions.
  • Turbo Integrator could be used to set up bunches of MDX-driven subsets, if you like. No need to create/update them all manually. TI could also easily convert dynamic subsets into static subsets.

Often used MDX statements

Below, I will present you the MDX statements I need most of the time. This page will therefore serve as a kind of code library: we can copy/paste and adjust only names of cubes/dimensions/elements. You will notice [] around dimension names and element names. They could be left out, unless (for instance) the name contains a space. Then we must enclose the name with []. The expressions are most of the time case-insensitive. Except for function names, the expressions are also space-insensitive.

Referencing elements

  • 1 hard-coded element (dimension name and element name follow):
    {[Project_type].[All types]}
    or:
    {[FIN_Year].[2023]}

  • In a Turbo Integrator process, we often use a parameter for the year or scenario:
    SubsetCreatebyMDX('Subset_Years', '{[FIN_Year].[2023]}');
    becomes:
    SubsetCreatebyMDX('Subset_Years', '{[FIN_Year].['|pYear|']}');

    The function EXPAND in TI can be used to substitute variable names to their values at run-time: SubsetCreatebyMDX('Subset_Years', EXPAND('{[FIN_Year].[%pYear%]}'));

  • 2 hard-coded elements:
    {[FIN_Year].[2023], [FIN_Year].[2023]}

  • Another example of EXPAND:
    SubsetCreateByMDX( vSubset, 'Descendants( TM1FilterByPattern( TM1SubsetAll([ ' | Dim1 | ']), ' | vConso | ' ))' );
    compared to:
    SubsetCreateByMDX( vSubset, Expand( 'Descendants( TM1FilterByPattern( TM1SubsetAll([%Dim1%]), %vConso% ))' ));

  • If you want to use MDX statements in Excel or TM1 Web, you can use cell references in the following way:
    ="{[FIN_Year].[" & E15 & "],[FIN_Year].[" & E16 & "]}"

    This allows you to customize your reports to a great extent. For example, the user can sort the rows ascending or descending, where these 2 options are a selection in a cell. The choice of the user is then picked up in the MDX expression at hand.

  • Getting the element on a certain index position in the dimension / hierarchy:
    {[Account].Members.Item(5)}


    This gives us the 6th account, index-wise, since we start counting at 0.
  • Using an existing subset in an expression

  • The function TM1SubsetToSet can be really useful (information). It allows us to use a different subset (name-based) into another expression. No need to duplicate the same logic twice or even more. Also, the referenced subset could be maintained by users and can change over time - even static subsets. The referenced subset can be public or private, if unspecified through the argument then a private subset will win over the public subset with the same name.
    {TM1SubsetToSet([Period].[Period], "Current Period", "public")}


    This expression uses the contents of the "Current period" subset within the Period hierarchy of the Period dimension.

    The public/private character of the referenced subset was submitted by George Tonkin.

  • Before TM1 version 12, the result of using TM1SubsetToSet could also be obtained with a different syntax: [dimension name].[hierarchy name].[subset name]. In TM1 version 12 and later, this square brackets notation will not be allowed anymore. TM1SubsetToSet will be used instead. You might need to make changes when upgrading. Refer to: this discussion.

  • The first element of an existing subset called by name:
    {TM1SubsetToSet([Period].[Period], "Current Period", "public").Item(0)}

    Don't forget the curly braces. Or:

    Head( {TM1SubsetToSet([Period].[Period], "Current Period", "public")}, 1 )

    The value of 1 can be left out if you want, Head will return the first element if that argument is not provided.

  • Item returns a tuple, for the first item in the collection (Set):
    {Filter( TM1SubsetAll( [Dates] ), [Dates].CurrentMember.Properties("Serial date") < 20635)}.Item(0)

    When you add the curly braces, the tuple becomes a set:

    {{Filter( TM1SubsetAll( [Dates] ), [Dates].CurrentMember.Properties("Serial date") < 20635)}.Item(0)}

  • What is mentioned inside Properties() can be retrieved from a cube as well:
    {Filter( {TM1SubsetAll( [Scenario] )}, Val([Scenario].CurrentMember.Properties([cube].([dim1].[member], [dim2].[member]))) = 1)}

    This expression will look for a Scenario where the Flag attribute is 1, knowing that the cube stores Flag as a string value.

  • A nice asset in the TM1 developer's toolkit is the following. Selections in dimensions that are positioned in rows and columns of a view or report, can reflect the selections made in a dimension positioned in the titles. Here's a practical example. Suppose we have 5 measures in a measures dimension. They are positioned in the titles. Each of the 5 measures can lead to a different subset in a certain row dimension. Measure 1 can be shown with high-level selections in that row dimension, while measure 2 would be "connected" with level 0 members in that row dimension. What we can easily do, is create 5 subsets in that row dimension. It should be possible to derive their names based on the selection of the element in the particular titles dimension. Let's say the subset names are equal to the measures names. Then 1 subset suffices and you have to create it with Turbo Integrator (not manually in the interface, the subset needs a context):
    {TM1FilterByLevel( TM1SubsetAll( [Project_type] ), 0)}
    SubsetCreatebyMDX( 'Subset by measure', '{TM1SubsetToSet([Account], [Measure].CurrentMember.Name, "public")}', 'Account' );
    
    Attach the subset called 'Subset by measure' to the view for that row dimension. Make sure the measures are positioned in the titles section of the view. When you now switch from 1 measure to another, the rows will update on the fly ! Great trick to make your reports truly dynamic. It avoids either creating 5 reports, or asking the user to selecting 1 of 5 subsets in the rows - you don't want to ask that from your user base.

    Of course, the 5 subsets in the row dimension should exist (as public subsets but you are free to add whatever custom logic you need for the MDX definition of the subsets. Very useful !

  • Elements at different levels

  • All lowest level elements in a dimension:
    {TM1FilterByLevel( TM1SubsetAll( [Project_type] ), 0)}

  • A bit more verbose but applicable outside of TM1 as well:
    {Filter( [Project_type].Members, [Project_type].CurrentMember.Properties("ELEMENT_LEVEL")="0")}

  • All elements at certain levels:
    {TM1FilterByLevel( TM1SubsetAll( [Project_type] ), 1,2,3 )}

    Alternatively: {Filter( TM1SubsetAll( [Project_type] ), StrToValue([Project_type].CurrentMember.Properties("ELEMENT_LEVEL")) >= 1 AND StrToValue([Project_type].CurrentMember.Properties("ELEMENT_LEVEL")) <= 3 )}

    StrToValue can be swapped for Val as well.

    This version avoids having to specify the levels in between. Granted, it's a longer syntax but probably better than listing for example 1,2,3 and even more (1,2,3,4,5,6,7,8, ...). Or you could use the Intersect of 2 sets: 1 set for at least level 1 and 1 set for at most level 3. The advantage with listing the desired levels, is that you can add other levels too and the order does not need to be respected: {TM1FilterByLevel( TM1SubsetAll( [Project_type] ), 3,6,1 )} is the same as: {TM1FilterByLevel( TM1SubsetAll( [Project_type] ), 1,3,6 )}

  • Elements without parents and between certain levels in the dimension in a TI process:
    pDim = 'Customer';
    LEVEL_MIN = 1;
    LEVEL_MAX = 6;
    
    vMDX = 'Filter( TM1SubsetAll( [%pDim%] ), StrToValue([%pDim%].CurrentMember.Properties("ELEMENT_LEVEL")) >= %LEVEL_MIN%';
    vMDX = vMDX | ' AND StrToValue([%pDim%].CurrentMember.Properties("ELEMENT_LEVEL")) <= %LEVEL_MAX% )';
    vMDX = Expand( 'Filter( ' | vMDX | ', [%pDim%].CurrentMember.Parent.Name = "" )' );
    
    AsciiOutput( 'test.txt', vMDX );
    


  • Very interesting is also the function Val to convert strings to numbers:
    Filter( TM1SubsetAll( [Period] ), Val( Left( [Period].CurrentMember.Name, 4 )) = 2023 )

    Thanks (again) George Tonkin, and he continued to add the following. What seems to be very useful is you can use Val against a numeric attribute e.g.:
    Filter( TM1SubsetAll( [Scenario] ), Val( [Scenario].CurrentMember.Properties("Flag")) = 1 )

    For C levels and other N levels where flag was never specified and shows a 0, these do not result in an error like StrToValue and the need to use Iif to trap for a null and set it to 0 before converting. Changing the above MDX to filter on a value of 0 returns those members either set to 0 or never set to begin with.

  • All consolidated elements in a dimension:
    { Except( TM1SubsetAll( [Project_type] ), { TM1FilterByLevel( TM1SubsetAll( [Project_type] ), 0) } )}

  • Sorting all elements (descending) based on the element level:
    Order( TM1SubsetAll( [Product]), Val([Product].CurrentMember.Properties("ELEMENT_LEVEL")), Bdesc)

    This could help you for instance in case of duplicate alias values. You could add a numeric suffix to elements with the same alias value, whereby the elements appear in the Data tab of the process based on their level in the dimension. Then, incrementing numbers for the suffix will go along with the levels as they decrease.

  • So the Except function expects 2 sets as the arguments. Elements of the second set that are found in the first set, are removed from the first set. However, in case the first set contains duplicates, there is a way to still keep the duplicates. The 3rd argument 'ALL' should be specified in that case.

    {Except( Descendants( [Client].[Running projects] ), Descendants( [Client].[Paid projects] ), ALL )}

  • All consolidated elements in a dimension - hierarchical representation:
    { Except( Hierarchize( TM1SubsetAll( [Project_type] )), { TM1FilterByLevel( TM1SubsetAll( [Project_type] ), 0) } )}

  • Instead of TM1SubsetAll, you can also use Members:
    {[Project_type].Members}

    HOWEVER, TM1SubsetAll and Members do not necessarily lead to the same output ! Members can have more elements in the resulting subset, since it counts unique paths towards an element whereas TM1SubsetAll only takes unique elements. So: if you use certain elements multiple times in the dimension, it can lead to different results.

  • AllMembers is similar to Members:
    { [Account].AllMembers }

  • All lowest level elements in a dimension, except one element:
    { Except( TM1FilterByLevel( TM1SubsetAll( [Work_Customers] ), 0), {[Work_Customers].[Office]} ) }

    Please refer to below for a discussion of the Subset function that can also exclude for example the first element of a set.

  • We can use the concept of levels as follows. Given a simple dimension called Period_MDX like this, the following statements all work - depending on the entries in the }HierarchyProperties cube where we can give meaningful names to levels:


    Filter( Descendants( [Period_MDX].[All months]), [Period_MDX].CurrentMember.Level.Ordinal < 2 )
    Intersect( Descendants( [Period_MDX].[All months]), [Period_MDX].[Year].Members )
    Filter( Descendants( [Period_MDX].[All months]), [Period_MDX].CurrentMember.Level.Name = "Year" ), OR:
    Filter( Descendants( [Period_MDX].[All months]), [Period_MDX].CurrentMember.Level.Name = "level001" )

    Filter( Descendants( [Period_MDX].[All months]), [Period_MDX].CurrentMember.Level.Ordinal = [Period_MDX].[Year].Ordinal ), OR:
    Filter( Descendants( [Period_MDX].[All months]), [Period_MDX].CurrentMember.Level.Ordinal = [Period_MDX].[level001].Ordinal )


    For this to work, you should refer to the picture below for the level names:





    Run the little TI process to update the hierarchies in the different dimensions (every time you are done making changes to that particular cube) !

    Note also this possibility:
    Filter( TM1DrillDownMember( TM1SubsetAll([Period_MDX]), ALL, Recursive), StrToValue([Period_MDX].CurrentMember.Properties("LEVEL_NUMBER")) = 1)
    It starts at the top of the hierarchy and goes down a level with every number increased. Level 0 equals root members, level 1 the children of the root members, etc.
  • Sorting

  • All lowest level elements in a dimension, sorted alphabetically:
    {TM1Sort( TM1FilterByLevel( TM1SubsetAll( [Project_type] ), 0), Asc)}

    Next to Sort, Order is also supported.

  • If you would like to Order elements based on an alias or other attribute:
    Order( {[Month].Members}, [Month].CurrentMember.Properties("Short monthnr"), Asc)

    Short monthnr is an alias in this case.

  • Sorting the elements on an attribute:
    {Order( TM1SubsetAll( [Month] ), [Month].CurrentMember.Properties("Long name"), Asc)}

  • Drive the sorting on a report or input form using an attribute, where the users can set the ordering themselves:
    {Order( TM1SubsetAll( [Product_Group] ), Val([Product_Group].CurrentMember.Properties("Sort order")), Asc )}

  • Intermezzo: here we see that we must use Properties syntax to refer to an attribute. The square brackets notation of [dimension name].[hierarchy name].[attribute name] still works but not anymore in TM1 version 12 and later. You might need to make changes when upgrading. Refer to: this discussion.

    For instance, to filter out elements based on an attribute value: Filter( TM1SubsetAll( [Company].[Company]), [Company].[Company].CurrentMember.Properties("Size") = "Large" )

    rather than:

    Filter( TM1SubsetAll( [Company].[Company]), [Company].[Company].[Size] = "Large" )

    IMPORTANT note on using numeric attributes in MDX !
    Refer to the same discussion and a peek into future TM1 versions/changes. A.o., the idea is to use the optional TYPED parameter in the Properties function. Like that, the Properties function will not automatically convert to a text value (with side effects as a result of that). For this to work, IBM are working on this.

    In TM1 V11 (11.8.019 and later) using TYPED in TM1 works. It also works in V12. In earlier V11 version it throws a syntax error.

    Filter( TM1SubsetAll( [Company].[Company]), [Company].[Company].CurrentMember.Properties("Number of employees", TYPED) > 100 )

    Like this, the attribute "Number of employees" is allowed to be a string attribute and calculations are still possible. This is great as it gives us a solution to also properly resolving numeric attribute values without a CAST function. If you still want a safe solution for all V11 and V12 installs, the only way which works in all versions is a cell value query to the attribute cube itself.

  • To filter on numeric attributes, the best option is to query the underlying control cube:
    Filter( TM1SubsetAll( [Company].[Company]), [}ElementAttributes_Company].([}ElementAttributes_Company].[Number of employees]) > 100 )

  • Alternatively, filtering on the string representation can work too but is much less favorable:
    Filter( TM1SubsetAll( [Customer]), [Customer].CurrentMember.Properties("Segment") = "4.000000" )

    Using older ambiguous notation (you should avoid potential conflicts between elements / subsets / attributes):
    Filter( TM1SubsetAll( [Customer]), [Customer].[Segment] = 4 )


  • Another example for customers:
    {Order( Descendants( [Client].[Paid projects] ), [Client].CurrentMember.Properties("Description"), Asc)}

  • Sorting customers based on Sales value in a cube, leaving out sales values that are almost 0:
    {[Customer].[Total Customer]} + {Order( Filter( TM1FilterByLevel( Descendants( [Customer].[Total Customer]), 0), [Sales].([Product].[Total Product], [Year].[Total Year], [Period].[Total Period], [Currency].[EUR], [Sales_Msr].[Sales]) < -0.01 OR [Sales].([Product].[Total Product], [Year].[Total Year], [Period].[Total Period], [Currency].[EUR], [Sales_Msr].[Sales]) > 0.01 ), [Sales].([Product].[Total Product], [Year].[Total Year], [Period].[Total Period], [Currency].[EUR], [Sales_Msr].[Sales]), Desc) }

    Note how we have 3 times the same information in the expression regarding element selections. For some dimensions, it would be better to leave them out and use the DefaultMember property in the }HierarchyProperties control cube.

  • To filter out cube values irrespective of the sign, we would automatically think about a function like Absolute value, Abs(). In fact, it does not exist. The workaround would be an Iif and negating the negative values:
    {Filter( TM1FilterByLevel( TM1SubsetAll( [Customer] ), 0), IIF( [SalesCube].([Product].[Total Product], [Year].[Total Year], [Sales_Msr].[Sales USD]) < 0, -1*[SalesCube].([Product].[Total Product], [Year].[Total Year], [Sales_Msr].[Sales USD]), [SalesCube].([Product].[Total Product], [Year].[Total Year], [Sales_Msr].[Sales USD])) > 10000 )}

    Declan Rodger posted an alternative with an MDX view query in this discussion topic. Also, Hubert Heijkers commented there about other functions that are supported in other IBM tools and that could one day be supported in TM1/Planning Analytics.

  • An alternative to Iif is a Case structure. Consider switching measures for reporting in a sales cube based on a selection in a parameter cube - where we set K for 1,000 or M for 1,000,000 or nothing for no specific selection:
    {StrToMember( "[Sales_Msr].[" +
    Case [Sys_Param].([Sys_Param].[Sales amounts abbreviation], [Sys_Param_Msr].[String])
       When 'K' Then 'Value (K)'
       When 'M' Then 'Value (M)'
    Else
       'Value'
    End
    + "]" )}


  • Another example on IIF:
    {StrToMember ( "[Dim_Measure].[" + IIF ( [Scenario].CurrentMember.Name = "Elem1", "MeasureA", "MeasureB" ) + "]")}

  • A Case structure could be:
    {StrToMember ( "[Dim_Measure].[" + CASE [Scenario].CurrentMember.Name WHEN "Elem1" then "MeasureA" WHEN "....." then "Measure..." ELSE "MeasureB" END ) + "]")}

    Link

  • To decide on which element to use based on the non-emptyness of a certain set through an expression:
    {{TM1SubsetAll( [Version] )}.Item(Iif(TM1TupleSize({Filter( {TM1SubsetAll( [Weekly Performance] )}, [Weekly Performance].[enddate] < 20635)}.Item(0)) = 0, 2, 3))}

    Thank you Trevor MacPherson

    Note that relying on indexes is not always the best idea as they can change.

  • Order can be nested, so if you want to sort on 3 measures, in order (no pun intended), you can put Order inside a second Order inside a third Order:
    Order( Order( Order( {[Employee].Members}, [Employee].CurrentMember.Properties("Department"), Asc), [Employee].CurrentMember.Properties("Age"), Asc), [Employee].CurrentMember.Properties("Salary"), Asc)

    This expression sorts employees first on their Salary, then on their Age, finally on their Department. Thank you Keith Would for sending an email on this expression. Note that using BAsc and BDesc is probably preferred over Asc and Desc, respectively. When using Order, Asc/Desc and BAsc/BDesc are for different cases. BAsc/BDesc breaks down any hierarchies before sorting, Asc/Desc sorts within hierarchies.

    Keith also pointed out that you can sort on the concatenated attribute values by using, for example:

    Order( Order( {[Employee].Members}, [Employee].CurrentMember.Properties("Department")+[Employee].CurrentMember.Properties("Age"), Asc), [Employee].CurrentMember.Properties("Salary"), Asc)

  • To Order by numbers in an attribute (attributes are always seen as strings):
    Order( TM1FilterByLevel( TM1SubsetAll( [Month].[Month] ), 0), Val( Iif([Month].[Month].CurrentMember.Properties("Seq No") = "", "9999" /* Default Value */, [Month].[Month].CurrentMember.Properties("Seq No")))), BAsc)

    But probably best to use the attributes cube:
    Order( TM1FilterByLevel( TM1SubsetAll( [Month] ), 0), [}ElementAttributes_Month].( [}ElementAttributes_Month].[Seq No] ), BAsc )

  • Descendants and Ascendants

  • An element and its descendants all the way down the hierarchy:
    {Descendants([FIN_Account].[EBIT]) }

  • All Descendants of an element, without that element:
    {Except( Descendants([FIN_Account].[EBIT]), {[FIN_Account].[EBIT]} )}

  • The Descendants function has 3 arguments, that can provide a specified distance and a flag:
    {Descendants([FIN_Account].[EBIT], 0, AFTER )}

    gives us the same result, and thereby providing the names of dimension and element only once. AFTER omits the parent element. Other flags exist, such as: SELF, AFTER, BEFORE, BEFORE_AND_AFTER, SELF_AND_AFTER, SELF_AND_BEFORE, SELF_BEFORE_AFTER, LEAVES.
    For more information, refer to: Microsoft documentation

  • This leaves (pun intended) us with the following statement to select all level 0 descendants of a given selection:
    {Descendants([FIN_Account].[EBIT], 99, LEAVES )} PAW generates this kind of expression, at least in version 2.0.82, as reported by George Tonkin end of 2023. Whether the arbitrary distance value of 99 is sufficient/necessary/efficient, is up to your judgment.

    At any rate, the expression will include consolidated elements without children, should they exist in the hierarchy.

  • As an illustration to select the elements as descendants of a certain parent element, at a distance of 2 levels:
    Descendants([FIN_Account].[FIN_Account].[EBIT], 2)

    It follows that Descendants with a distance of 1 just returns the element and its immediate children: Descendants([FIN_Account].[FIN_Account].[EBIT], 1)

    Adding the flag to only return the level 0 elements becomes easy and at the same time very useful: Descendants([FIN_Account].[FIN_Account].[EBIT], 2, LEAVES)

  • What we often need, is a consolidated element, expanded for instance 2 times such that we see 3 levels:
    Descendants([FIN_Account].[FIN_Account].[EBIT], 3, BEFORE)

  • The current period and its 2 periods before (year crossings are respected) whereby the current month is stored in a central configuration cube:
    {LastPeriods( 3, StrToMember( "[Cm_YearMonth].[" + [Sys_CFG].([Sys_CFG_Environment].[Current], [Sys_CFG_Input].[Value], [Sys_CFG_Msr].[Reporting Year Month]) + "]"))}

  • Note that the MDX above will contain the part surrounded with + characters. If you were to say, create the subset sourcing from a cube, but that value can remain fixed, you don't need StrToMember:
    sYearMonth = CellGetS( 'Sys_CFG', 'Current', 'Value', 'Reporting Year Month' );
    SubsetCreateByMDX( vSubset, '{LastPeriods( 3, {[Cm_YearMonth].[' | sYearMonth | ']} )}' );

  • The current month followed by the 12 months of the year:
    {StrToMember( "[Cm_YearMonth].[" + [Sys_CFG].([Sys_CFG_Environment].[Current], [Sys_CFG_Input].[Value], [Sys_CFG_Msr].[Reporting Year Month]) + "]"), Descendants( StrToMember( "[Cm_YearMonth].[" + [Sys_CFG].([Sys_CFG_Environment].[Current], [Sys_CFG_Input].[Value], [Sys_CFG_Msr].[Reporting Year]) + "]"), 1 )}

    Here, "Reporting Year" and "Reporting Year Month" are populated in a general configuration cube. They could be data input, populated with a TI process, or rules-calculated with whatever logic you see fit. For now, it would be 2023-10 and 2023, for instance.

    Additionally, you could sort the children alphabetically based on an attribute.

    More information on how to filter dimension members using cube values will follow below.

    The dimension Cm_YearMonth (here) contains totals for the years (yyyy) and descendants for the periods (yyyy-mm). By taking out the parameter 1 at the end of the MDX, you will have the current month, followed by the year total, followed by the 12 months of the year. Hence, if you link that value of 1 to a selection for the user, the user can easily toggle between data including or excluding the sum total of the year.

    If you include quarters and/or half years in the same rollup, that distance parameter of 1 should be set accordingly to exclude these intermediate levels. Or, leave them in for more detailed analyses over the time periods.

    Instead of the comma to separate the 2 sets in the MDX above, the most likely alternative is the Union function with the ALL argument.

    Union operates on only 2 sets, contrary to the original Microsoft implementation.

  • Leaf-level Descendants of a given element:
    {TM1FilterByLevel( Descendants([FIN_Account].[EBIT]), 0)}
    or:
    {TM1FilterByLevel( TM1DrilldownMember( [FIN_Account].[EBIT], ALL, Recursive), 0)}

    You can easily sort the returned elements (here, ascending):
    {TM1Sort( TM1FilterByLevel( Descendants([FIN_Account].[EBIT]), 0), Asc)}

    Leaving out the filter by level will return the consolidated element(s) as well. So, Descendants and TM1DrilldownMember both include the parent element that was drilled upon.

  • A typical month selection where the user could choose a consolidated element - parameter pMonth:
    SubsetCreateByMDX( vSubset, '{TM1FilterByLevel( Descendants( [Month].[' | pMonth | ']), 0)}', 'Month' );
    
  • All lowest level elements in a dimension except those elements below a certain consolidation:
    { Except( TM1FilterByLevel( TM1SubsetAll( [Fct_Product] ), 0), Descendants( [Fct_Product].[My consolidated product] ) )}

  • An element and its descendants all the way down the hierarchy, but omitting level 0:
    {Except( Descendants([Customer].[Total Customer]), {TM1FilterByLevel( Descendants([Customer].[Total Customer]), 0 )} )}

  • Leaf-level descendants of 2 consolidated elements:
    {TM1FilterByLevel( Union( Descendants( [FIN_Account].[EBIT] ), Descendants( [FIN_Account].[Taxes] )), 0)}

  • Leaf-level descendants of a given consolidated element, that consolidation included:
    {Union( {FIN_Account.[EBIT]}, TM1FilterByLevel( Descendants(FIN_Account.[EBIT]), 0) )}
    or:
    {FIN_Account.[EBIT], TM1FilterByLevel( Descendants(FIN_Account.[EBIT]), 0) }
    Note: The Union function can be shortened to the + operator (an element is listed only once):
    {FIN_Account.[EBIT]} + {TM1FilterByLevel( Descendants(FIN_Account.[EBIT]), 0)}
    or, now EBIT is at the bottom of the list, the Order of the elements in the expression is retained left to right:
    {{TM1FilterByLevel( Descendants(FIN_Account.[EBIT]), 0)}, FIN_Account.[EBIT] }

    Next to Union, Intersect is also supported. Sidenote: if you want to avoid the removal of duplicate elements, use a comma instead of a plus sign. Example: [Fct_Product].[A], [Fct_Product].[B], [Fct_Product].[C], TM1FilterByLevel( Descendants([Fct_Product].[C]), 0)}

  • The planning scenario followed by all other scenarios (elements listed once):
    {StrToMember( "[Cm_Scenario].[" + [Fn_Rp_General_Config].( [Cm_Scenario].[Actual], [Fn_Rp_General_Config].[Planning Scenario], [Fn_Rp_General_Config_Msr].[Value] ) + "]")} + {TM1Sort( TM1FilterByLevel( TM1SubsetAll( [Cm_Scenario] ), 0 ), Asc )}

  • Filtering out Profit and Loss (P&L) and Balance Sheet accounts:
    TM1Sort( Union( TM1FilterByPattern( TM1FilterByLevel( TM1SubsetAll( [St_Account] ), 0), "6*"), TM1FilterByPattern( TM1FilterByLevel( TM1SubsetAll( [St_Account] ), 0), "7*") ), Asc )

  • Filtering out Balance Sheet accounts as the result of what remains when P&L accounts are removed:
    Except( TM1FilterByLevel( TM1SubsetAll( [St_Account] ), 0), TM1SubsetToSet( [PL_Account], "P&L Accounts" ))

    Notice that the subset "P&L accounts" should exist too: we filter out elements that appear in a certain subset.

  • The parent elements of an element including the element itself, can be retrieved with Ascendants:
    {Ascendants([Fct_Customer].[111522])}

    Note that only the parents in the first rollup in the hierarchy are retrieved, which can often be a limitation.

  • The parent elements of an element without the element itself, but only in the first rollup in the hierarchy:
    Hierarchize( [Fct_Customer].[111522].Ancestors )

  • The parent elements of an element including the element itself, but only in the first rollup in the hierarchy:
    Hierarchize( Ascendants( [Fct_Customer].[111522] ))

  • When an element occurs multiple times in a hierarchy, it is imperative to understand that you only receive the parents of one of them. You will need to use the Member Unique Name (MUN) to better identify the element in which you are interested. However, as often is the case: you select an element like "Marketing" as a cost center in the cost center hierarchy. You simply want all of its parents and elements in which "Marketing" rolls up. This can be done as follows:
    {Hierarchize( Generate( Filter( Distinct({[Cost Center].[Cost Center].Members, {[Cost Center].[Cost Center].[Total Cost Center^Cost Centers]}}), [Cost Center].[Cost Center].CurrentMember.Name = "Marketing"), Ascendants([Cost Center].[Cost Center].CurrentMember)))}

    Now that's a mouthful ! First, we take all members of the dimension and out of all those members, we take the set of Distinct members. Next, we filter that resulting list on the elements whose name is Marketing - it could well be multiple elements. For instance, Marketing could be used 4 times in the hierarchy, with different parent sets. Generate is then used to "generate" all ascendants elements of each of the 4 element instances. To format the result a bit, we throw an Hierarchize against it and we nicely see the rollup structures from 4 elements all the way to their top parents.

  • Much better would be to list all parent elements of an element in the entire dimension. The element drilled upon in the example below is 'INPUT Sales third parties' in the dimension 'Rp_Cost_Element'.
    Filter( Except( TM1SubsetAll( [Rp_Cost_Element] ), TM1FilterByLevel( TM1SubsetAll( [Rp_Cost_Element] ), 0 )), TM1TupleSize( Intersect({[Rp_Cost_Element].[INPUT Sales third parties]}, Descendants([Rp_Cost_Element].CurrentMember)).Item(0)) > 0)


    Item(0) gives us the first element in the result set.
    Thank you Ty Cardin

    Put differently, to collect all ascendants of an N-Element right to the root of the dimension tree: Filter( TM1SubsetAll( [Dimension] ), TM1TupleSize( Intersect( {[Dimension].[N-Element]}, Descendants( [Dimension].CurrentMember )).Item(0)) > 0 )

  • The top parent of an element would then be:
    {Tail( {Ascendants([Fct_Customer].[111522])}, 1 )}

    In TM1 an element may have multiple parents within a hierarchy so if there are multiple parent branches you may need the intersect between the ancestors and all top node elements in the dimension:
    {Intersect( {Ascendants([Fct_Customer].[111522])}, {Filter( {TM1SubsetAll( [Fct_Customer] )}, [Fct_Customer].CurrentMember.Parent.Name = "")})}

    I would understand it if you prefer levels (0 is the highest level in a dimension/hierarchy): {Intersect( {Ascendants([Fct_Customer].[111522])}, [Fct_Customer].Levels(0).Members )}

  • An interesting function is ToggleDrillState. It allows us to expand or collapse consolidations, toggled/inverted with respect to the drill state it was (drilled into or not)
    {ToggleDrillState( {[Account].[6].Children}, {[Account].[63]} )}

    The consolidated element '6' in the Account dimension is drilled into and gives consolidated elements ( not expanded) of '60', '61', '62', ... What ToggleDrillState does is still drill into an element, in this case the '63' consolidation.

    This leaves the possibility to expand on the second set - it could be a filter in itself:
    {{ToggleDrillState( {[Account].[6].Children}, {Filter( {[Account].[6].Children}, [Account].CurrentMember.Name < "63" ) } )}

    The above works as long as all such children can be compared in an alphanumeric way. Should we want to compare in a numeric way, we need to convert strings to numbers:
    {ToggleDrillState( {[Account].[6].Children}, {Filter( {[Account].[6].Children}, StrToValue( "0" + [Account].CurrentMember.Name ) <= 21 ) } )}

    Note that I applied an interesting trick: I use a prefix of '0' for those element names that are not really numbers !
  • TM1ToggleDrillStateis similar:
    {TM1ToggleDrillState( {[Account].[6].Children}, {[Account].[63]}, EXPAND_BELOW, RECURSIVE )}
  • When hierarchies can be out of sync, that is difficult to spot check. Another helper MDX can be as follows, to identify parent segments that contain wrong descendant elements (any level deep):
    Filter( Filter( TM1SubsetAll( [Customer] ), [Customer].CurrentMember.Parent.Name = "" ), Count( Filter( Descendants([Customer].CurrentMember), Instr( [Customer].CurrentMember.Name, [Customer].CurrentMember.Parent.Name ) = 0 )) > 0 )

    The interesting part to notice as well is that [Customer].CurrentMember can be different following the context where it is evaluated.



  • More on hierarchical structures

  • The immediate children (leaf level or consolidated) of a given element:
    {[Project_type].[All Types].Children}

  • Retrieving only 1 of the immediate children is similar:
    {[Project_type].[All Types].Children(0)}

    Here we ask for the first child, as the index is zero-based. The 5th child is done with Children(4) It is a shorthand notation for the Item function.

  • An element together with its immediate children (leaf level or consolidated):
    DrillDownLevel( {[Project_type].[All Types]} )

  • Alternatively:
    TM1DrillDownMember( {[Project_type].[All Types]}, ALL )

  • As a consolidated element, expanded twice such that we see 3 levels:
    Descendants([Project_type].[Project_type].[All Types], 3, BEFORE)

  • Sometimes we require a consolidated element with all of its descendants, coupled with a different consolidation with that one's immediate children:
    { Descendants([Fct_Assumption].[Total Assumption]) } + { DrillDownLevel( [Fct_Assumption].[Subtotals]) }



  • Similar to DrillDownLevel, but you limit the list to the first x elements:
    DrilldownLevelTOP( {[Project_type].[All Types]}, 3 )
    Here we grab the parent element (All Types) and its first 3 immediate children.

    DrilldownLevelBOTTOM will be easy to understand now.

  • DrillUpLevel will have its use-cases as well. It allows to "condense" elements in a set up until a specified level in the dimension. And if you don't specify that level TM1 will use the level just above the lowest level present in the set.
    DrillUpLevel( Descendants( [Cm_Date].[YTD] ), [Cm_Date].Levels(2) )
    An entire structure of consolidated elements starting with YTD can be expanded, but only up to the desired level. Not all the way down the hierarchy. An example of not specifying the level, whereby TM1 will stop above the lowest level present in this set:

    DrillUpLevel( Descendants( [Cm_Date].[YTD] ))

  • There is also DrillDownMember which operates on 2 sets (or a tuple and a set). It comes down to drilling down on elements of a first set but only for those elements that are part of a second set.
    DrillDownMember( {[Month].[Q2]}, {[Month].[Total Year].Children} )
    will leave us with the element Q2 as well as its 3 children (Apr, May, Jun), provided the element "Total Year" contains Q2 as an immediate child.

    Moreover, if "Total Year" contains 4 elements for the quarters, then this MDX:
    DrillDownMember( {[Month].[Q2], [Month].[Total Year]}, {[Month].[Total Year].Children} )


    Will return Q2, Apr, May, Jun and the "Total Year". The latter is just returned, not drilled on, because it is not part of the second set.

    A 3rd argument called RECURSIVE allows to do the drill more than once, actually until no more drilling is possible or none of the resulting elements is part of the second set.
    DrillDownMember( {[Month].[Q2]}, {[Month].[Total Year].Children}, RECURSIVE )

    In this case, it won't change the result.

  • An example on the tuple variant for DrillDownMember will be useful. Below we drill down on "AW", where the selection is "910-20" in the other dimension, together with "AT9210" with "910-30":
    SELECT {[Nummer].[3]} ON 0, DrilldownMember( {([Postcode].[AW],[VerkoopOrganisatie].[910-20]), ([Postcode].[AT9210],[VerkoopOrganisatie].[910-30])}, { [Postcode].[AW] }) ON 1 FROM [test]

    This is an example of an (asymmetric) MDX view. The possibilities are endless !


  • DrillDownMemberTop and DrillDownMemberBottom are there to limit the resulting set of elements, should you need to.


  • In a similar spirit, DrillUpMember exists too and takes you in the opposite direction.


  • FIRSTCHILD gives us the first child of the element:
    {[Month].[Q2].FirstChild}

    … will return Apr. LASTCHILD gives us Jun.

  • FIRSTSIBLING gives us the first child of the shared parent:
    {[Month].[Q2].FirstSibling}

    … will return Q1. LASTSIBLING gives us Q4.

  • SIBLINGS, not surprisingly, gives us all the siblings of the given selection:
    {[Month].[Q1].Siblings}

    … will return the 4 quarters.

  • If you want to write it with a filter and a different function, IsSibling, here you go:
    {Filter( TM1SubsetAll( [Month] ), IsSibling( [Month].CurrentMember, [Month].[Q1] ) )}

    … will return the same 4 quarters, but in larger dimensions, loops over elements for filtering can degrade the performance.

  • HEAD gives us the first element of a set:
    {Head( {[Month].[Q1].Children}

    … will return Jan.

  • If we can ask for the first x and last y number of elements of a subset, then logically we can also expect an MDX function that starts somewhere in the middle and allows a parameter for how many elements you want to retrieve, from that start onwards. That is exactly what the SUBSET function does:
    {Subset( TM1SubsetAll( [Month] ), 2, 3 )}

    … will return 01, 02, 03 in my case since the Month dimension has elements (based on their index) of Total, Q1, 01, 02, 03, Q2, 04, …

    We take 3 elements (the last argument) as of spot 3 since the argument of 2 is a 0-based index. Should we omit the value of 3 then we get all elements starting at the 3rd element until the last element.

  • An interesting by-product of the Subset function is this way to easily exclude the first element of a set. I apply it to retrieve the children of the first element of a certain set:
    Subset( DrillDownLevel( Head( TM1SubsetToSet([Month], "Current YTD", "public" ))), 1 )

    The catch is near the end of the expression. 1 means that we start returning elements as of the 2nd element (it's 0-based). Then we omit the 3rd argument such that TM1 will happily give us all following elements. The end result is that, while DrillDownLevel gives us the consolidation and its immediate children, we can exclude the consolidation without any difficulty.

  • TAIL gives us the last element of a set:
    {Tail( {[Month].[Q1].Children}

    … will return Mar.

  • LAG returns the element that is a specified number of positions along the element’s level:
    {[Month].[Q3].Lag(2)}

    … will return Q1.

  • A dynamic expression to give us all periods from history until the current period or the prior period:
    [Fiscal Period].[2023.01]:StrToMember("[Fiscal Period].[" + [Sys_CFG].([Sys_CFG_Input].[Value], [Sys_CFG_Msr].[Current Period]) + "]").Lag(1)

    January 2023 is hard-coded but you could make this dynamic. We need a cube called Sys_CFG, as well as the few other components that you can see in the MDX.

    You can get more alternative expressions and food for thought here.

  • LEAD is the inverse of the function LAG:
    {[Month].[Q3].Lead(1)}

    … will return Q4.

    Lag(1) is equivalent to LEAD(-1), since the functions are inverse. Both functions can take on positive, negative or 0 values.
  • PREVMEMBER is equal to LAG(1) and NEXTMEMBER is LEAD(1):
    {[Month].[Q3].PrevMember}

    … will return Q2.

  • PREVMEMBER and NEXTMEMBER can be very useful (but read the next paragraph with even more attention). Just think about averages of the last 3 years including this year. To avoid hardcoding the current year too often, let's use Generate and work off that returned selection:
    Generate({[Cm_YearMonth].[Cm_YearMonth].[2023]}, {[Cm_YearMonth].[Cm_YearMonth].CurrentMember,[Cm_YearMonth].[Cm_YearMonth].CurrentMember.PrevMember,[Cm_YearMonth].[Cm_YearMonth].CurrentMember.PrevMember.PrevMember})

    This statement will return 2023, 2021, 2020, as for instance the 3 most recent years. 2023 could be sourced from a parameter cube.
    Obviously, you could also store the previous years in the parameter cube (manual entry, rules-calculated, TI, whatever) but this example takes away the need to do so. Or the members could be obtained from attribute values.

    Very important ! We are taking the previous or next members in a hierarchy. TM1 respects the levels in the hierarchy. So, even if the hierarchy as in my case, contains rollups for years with 12 month children underneath each year: the previous element at the year level goes to last year, not last month. But the previous element at the month level goes to the last month. No additional coding should be done in case of year crossings or just make sure that the previous element of 2023-01 is not 2023 (index-wise, it is, though).
  • BUT WAIT ! LastPeriods is a much easier approach and superior to the above attempts:
    {TM1Sort( LastPeriods( 3, [Cm_YearMonth].[2023]), Desc )}

    This statement will also return 2023, 2021, 2020 (respecting the levels in the hierarchy) when 2023 is the base year.

    The current year and the 2 next years will then be:
    {LastPeriods( -3, [Cm_YearMonth].[2023])}

    This statement will return 2023, 2023, 2024 when 2023 is the base year.

    The function name is a bit misleading and not indicative of the fact that it works in any hierarchy - not just hierarchies with periods. The next team member name in a hierarchy, the previous 10 cost centers or revenue accounts, the following 30 product names, whatever.
  • COUSIN is used to retrieve an element (period probably) in a parent, relative to an element (and its parent). An example will clarify:
    {Cousin( [Month].[10], [Month].[Q3] )}

    … will return 07. Assumed is a structure of 4 quarters, with children 01-02-03, 04-05-06, 07-08-09, 10-11-12. Month 10 is similar to month 07 if you apply the parent element of Q3. TM1 recognizes Q4 as the parent of month 10 and then jumps back to Q3 (what we asked for) and singles out its second child. Both months are the second month within the respective quarter. It's probably not a bad idea to qualify month 10 more as: [Month].[Q4^10] in case month 10 is used multiple times in the same dimension.

  • OPENINGPERIOD is, again, not restricted to time periods like months or days. You need a level (defined in the cube }HierarchyProperties) and a consolidated element. The MDX then gives back the first element below the consolidation that intersects the specified level. It does not have to be an immediate child of the consolidation.
    {OpeningPeriod([Month].[Month].[Level 0],[Month].[Month].[2023])}

    … will return 202301 (in my example dimension of concatenated years and months). 202301 is the first child (descendant) below 2023, which cuts the level of "Level 0" that I used as the name.

    This function (like a number of others) was brought to my attention by George Tonkin, many thanks for that.
  • CLOSINGPERIOD is similar, obviously. As a different illustration, let's take a Day dimension where I need a subset with the last day of 2023:
    {ClosingPeriod([Day].[Day].[Level 0],[Day].[Day].[2023])}

    … will return 2023-12-31 (in my example dimension of all days > years > quarters > months > days). Note that there are 2 intermediate levels in the dimension (quarter and month) that are not important here and will be skipped). Level 0 descendants of 2023 will be used, then the last element is used. Alternatively, we could look at Descendants and Tail but it's good to see other ways of achieving the same result. Even more, Descendants will not always lead to the same result as a level.

    The last day in the dimension will then be: {ClosingPeriod([Day].[Day].[Level 0],[Day].[Day].[All dates])} or {Tail( TM1FilterByLevel( Descendants( [Day].[Day].[All dates]), 0))}

  • I can see benefits too in a budget input situation for accounts. If in every bucket of accounts the first account can serve as input, this will retrieve it for 1 such bucket:
    {OpeningPeriod([Account].[Account].[Level 0],[Account].[Account].[Personnel costs])} or {Head( TM1FilterByLevel( Descendants( [Account].[Account].[Personnel costs]), 0))}
    If you stick it in the Generate function, nice results will come out :-) A simple list of input accounts based on your high-level buckets.

  • What should we do if we want to retrieve the next or previous member (index-wise) in any dimension ? The added challenge is that the current element is stored in a subset, rather than entered in a cube or as an attribute. For the solution, please refer to my posts here where I demonstrate Named levels in TM1.
    { ParallelPeriod( [Week].[Week_L0], -1, TM1Member( [Week].[Current week].Item(0), 0) )}

    ParallelPeriod is actually to be understood as a lag. With a positive value, you go backwards in the dimension, index-wise. Please check out the function LastPeriods as well, elsewhere on this page.

    Note that I also use the Week_L0 'level' element in the }HierarchyProperties cube. Pay attention to use e.g. 'Week_L0' if you fill out the cube cell, however, if you did not specify anything you should use level002 (within the given dimension/hierarchy). You need to refresh when edits are made to this cube, but other than that, it's a good way to make your TM1 models more dynamic and 'readable' by humans. Refreshing can be done using the TI function RefreshMDXHierarchy( '' ); for all dimensions / hierarchies, or RefreshMDXHierarchy( 'dimension or hierarchy' ); for a given dimension/hierarchy.



    I used the dimension for 'Week' as an example but the above function also works on dimensions that do not have a time concept, like companies.

    Notice the defaultMember element too, we will discuss it later on in the document.

    For more information on Named levels, refer to: IBM documentation. The idea is also that statements like [Customer].[Country].Members or [Customer].[Country].Members work, certainly in for dimensions/hierarchies that are not ragged - here, we have a Customer dimension where a rollup exists for customers into countries (the result is the list of distinct countries).

  • This would work too and is probably easier:
    { TM1Member( [Week].[Current week].Item(0), 0).NextMember }

    Please note that TM1Member is probably not your safest bet. In Planning Analytics there have been cases where it can lead to issues, depending on the usage and situation at hand of course. Use with caution. The bottom line is that it seems that this function, when used in other MDX, is stripped and Planning Analytics reverts to the definition/logic contained in it.

  • We also have functions to roll up from elements to their parent(s), for example Parent, Ancestors or TM1Rollup:
    {TM1Rollup( {[Month].[Jan]}, {[Month].[Jan]} )}

    returns the parents of the month of January in the Month dimension. This expression mimicks the rollup button in the Subset Editor, by the way. It can be similar to a loop over Elpar from 1 to ElparN.

    You can use Except( TM1Rollup( {[Month].[Jan]}, {[Month].[Jan]} ), {[Month].[Jan]} ) to leave out the level 0 element from the result set.

  • Ancestor can be useful to ask for the parents of an element, going from parent to grandparent to grand-grandparent, etc:
    {Ancestor([Rp_Account].[600000], 0)},
    {Ancestor([Rp_Account].[600000], 1)},
    {Ancestor([Rp_Account].[600000], 2)},
    {Ancestor([Rp_Account].[600000], 3)}, …

    will return the element itself (0), then the parent (1), grandparent (2), parent of the grandparent (3).


    In case an element has multiple parents, for instance immediate parents, then you will only receive one of the parents. It is not necessarily giving you the parent with the smallest index in the hierarchy. It's probably the parent that is part of the first rollup of the hierarchy.

    Also consider the use of the function Ascendants elsewhere in this document, for similar use-cases.

  • Ancestor's second argument can not only a measure of distance, it can also refer to a level in the hierarchy:
    {Ancestor([Rp_Account].[600000], [Rp_Account].[Level000])} such that you can ask for an element higher up in the dimension that is cut by some level.

  • The Ancestors function can be worthwile too:
    {Ancestors([Rp_Account].[600000], 1)}, {Ancestors([Rp_Account].[600000], 2)}, {Ancestors([Rp_Account].[600000], 3)}, …

    The same comments as to Ancestor apply here.

  • The IsAncestor function yields similar results:
    {Filter( TM1SubsetAll( [Rp_Account] ), IsAncestor( [Rp_Account].CurrentMember, [Rp_Account].[600000] ))}

    Note that performance can be degraded with the Filter function, as it needs to loop over items. In addition, the function will not yield all hierarchy elements that have the said element as an ancestor.

  • LASTPERIODS returns the n elements preceding and including the selected element along the element’s level
    {LastPeriods( 3, [Month].[Q3])}

    … will return Q1, Q2, Q3.

    Please note that LastPeriods is not restricted to time dimensions. It can be utilized in a similar fashion on any dimension irrespective to what element names are used.

  • LEVEL returns the elements at the same level as the chosen element:
    {[Month].[Q3].Level.Members}

    … will return Q1, Q2, Q3, Q4.

  • PERIODSTODATE is an interesting one. It returns the set of sibling elements (so at the same level) starting with the first element, up until the chosen/last element. Ty Cardin gave a nice example where cube data is filtered from beginning of the year until a certain period:
    PeriodsToDate( [Manad].[Level000], TM1Member( Tail( Filter( [Manad].[Total Year].children, [cubename].([z.TestRowEntryList].[R01]) > 0), 1).Item(0), 0))

    This solution works if the Level000 name is adequate (it can be swapped for something meaningful). It stands for the parent level of the elements to be selected. Look at the }HierarchyProperties cube and a TI process with the command RefreshMDXHierarchy.

  • The functions WTD, MTD, QTD and YTD can be equivalent to PeriodsToDate but needs more intelligence.

  • Should you prefer to work with the name of the consolidated element, rather than the level name, then use the Level function:
    PeriodsToDate( [Manad].[Total Year].Level, TM1Member( Tail( Filter( [Manad].[Total Year].children, [cubename].([z.TestRowEntryList].[R01]) > 0), 1).Item(0), 0))

    The PeriodsToDate formula can also be used in dimensions (hierarchies) that are not dealing with Time or Periods. So Accounts, Cost Centers, Companies, ... though of course it still has to make sense.

  • The : operator allows us to select a range of contiguous elements (following dimension indexes) from the same level specifying the first and last element of the set:
    {[Month].[Month].[Jan]:[Month].[Month].[Oct]}

    … will return Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct.

      Please note the following requirements (if not satisfied, an empty set is returned and/or an error):
    • Both elements should exist in the hierarchy and be at the same level in the hierarchy
    • Index-wise, no dimension elements at a different level, can be between the 2 listed elements


    Using a filter could be an option too, for instance in a dimension with countinuous dates:

    Filter( TM1FilterByLevel( TM1SubsetAll( [Time_Day] ), 0 ), [Time_Day].CurrentMember.Properties("Name") ≥ "20230801" AND [Time_Day].CurrentMember.Properties("Name") < "20230831" )
  • A more advanced example of this range operator:
    TM1SortByIndex( TM1Member( TM1SubsetToSet([Months].[Months], "subset1", "public").Item(0), 0):TM1Member( TM1SubsetToSet([Months].[Months], "subset1", "public").Item(0), 0).Lead(5), Asc)

    Here we retrieve a number of months, based on the contents of a public subset called subset1 (its first element). That element and the next 5 elements are taken, 6 months in total. Note that this technique is very powerful in continuous time dimensions, crossing years. Your 12 month moving windows becomes child's play !

    Also note that the previous expression can be greatly simplified to:
    TM1SortByIndex( LastPeriods( -6, TM1Member( TM1SubsetToSet( [Months], "subset1", "public").Item(0), 0 )), Asc)

    Finally on this topic, consider "jumping" to a different month by advancing 5 months:

    {TM1Member( TM1SubsetToSet( [Months], "subset1", "public").Item(0), 0).Lead(5)}
  • Planning Analytics hierarchies

    Since some time now we can use hierarchies in IBM Planning Analytics. Any dimension can become a container of 1 or more so called hierarchies. These hierarchies can be used in cube views and reports in an orthogonal fashion, such that one can analyze the data in a much richer way than before. The so-called Leaves hierarchy is automatically maintained by the software, containing a copy of all level 0 elements in the entire dimension (over hierarchies). Here is a dynamic subset on the }Dimensions dimension to identify all dimensions that contain hierarchies: Filter( TM1SubsetAll( [}Dimensions] ), Instr( [}Dimensions].CurrentMember.Lead(1).Name, [}Dimensions].CurrentMember.Name + ":" ) = 1 )

  • Occasionally, though, there could be a disconnect between elements in the Main hierarchy of a dimension, and the Leaves hierarchy of the same dimension. This MDX allows you to filter them out from the Leaves hierarchy:
    Except( TM1FilterByLevel( TM1SubsetAll( [Customer].[Leaves]), 0 ), Generate( TM1FilterByLevel( TM1SubsetAll( [Customer].[Customer]), 0 ), Filter( TM1FilterByLevel(TM1SubsetAll([Customer].[Leaves]) , 0), [Customer].[Leaves].CurrentMember.Name = [Customer].[Customer].CurrentMember.Name )))

    Submitted by George Tonkin, thanks for this.

  • Union and Intersect

  • Union can be interesting if you have a subset that should "expand above" but there are other elements that should be shown at the top:
    {Union( {[Account].[Earnings Before Taxes] }, {[Account].[Subset Exp Above] })}

    Here the subset 'Subset Exp Above' is a second (public) subset on the same dimension: { Except( {TM1DrillDownMember( {[Account].[Earnings Before Taxes] }, ALL, RECURSIVE )}, { [Account].[Earnings Before Taxes] })}
    Thanks to Paul Simon for posting.

    Update by Lotsaram (October 2021) in the same topic, with a simpeler syntax: {TM1ToggleExpandMode( {[Account].[Earnings Before Taxes]} + {[Account].[Subset Exp Above]}, EXPAND_ABOVE)}

  • TM1ToggleExpandMode does what you can expect from it - expand e.g. elements above instead of the usual expand below:
    {TM1ToggleExpandMode( {[Account].[Earnings Before Taxes]}, EXPAND_ABOVE)}

  • Union will, by default, show elements only once even if they occur in both sets. You can override this behavior by adding the parameter ALL:
    Union( TM1FilterByPattern( TM1FilterByLevel( Descendants( [St_CostCenter].[FP] ), 0 ), "613194?00*" ), TM1FilterByPattern( TM1FilterByLevel( Descendants( [St_CostCenter].[Plant Manager] ), 0 ), "613194?00*" ), ALL )

  • Intersect is useful to evaluate two sets of elements:
    {Intersect( Filter( TM1SubsetAll( [Month] ), [Filter].([Filter].[FilterOrder]) <> 0), Descendants(Month.[Q1]) )}

  • To spot potential double counting problems, we could create an MDX query with Intersect to show us all elements in a rollup that appear multiple times:
    Filter( Descendants( [CostCenter].[CostCenter].[Total Cost Center By Location] ), Count( Intersect( Descendants( [CostCenter].[CostCenter].[Total Cost Center By Location]), {[CostCenter].[CostCenter].CurrentMember}, All )) > 1 )

    Notice the use of the argument All. If we were to leave it out, like we do in other examples on Intersect, then the MDX engine will first remove duplicate elements. Of course this is not what we want in this case. If All is specified, the Intersect function intersects nonduplicated elements as usual, and also intersects each duplicate in the first set that has a matching duplicate in the second set.

  • What we can use to spot potential double counting problems, is:
    Filter( TM1FilterByLevel( Descendants( [CostCenter].[CostCenter].[Total Cost Center By Location] ), 0 ), TM1TupleSize( Intersect( Descendants( [CostCenter].[CostCenter].[Total Cost Center By Location] ), {[CostCenter].CurrentMember}, All ).Item(1)) = 1 )

    This expression finds the leaf elements that have multiple parents in a given rollup (see the example given for cost centers).

    The result is for instance 1 element name (like Cost Center ABC) but it appears twice in the subset. This is because the Distinct function looks at the Member Unique Name (MUN). Those 2 results could then be expanded to for instance their parent elements (ancestors) to quickly analyze where the double counting affects the totals and/or to understand where it went wrong.

    Alternatively, you remove the duplicates in Excel and work from that list of really unique elements. Why did I write Excel instead of PAW ? PAW has a button to remove duplicate elements in the Set editor. However, that button works on the MUNs and effectively adds the Distinct function that we added ourselves too. Hence, this will not be the solution to your problem. To still have a solution in PAW using MDX, read the following paragraph.
  • Following up on the challenge in the previous paragraph, here is a trick of mine to convert a set of duplicate element names, but unique MUNs, to what folks commonly understand when they talk about unique elements:
    Generate( Filter( TM1FilterByLevel( Descendants( [CostCenter].[CostCenter].[Total Cost Center By Location] ), 0 ), TM1TupleSize( Intersect( Descendants( [CostCenter].[CostCenter].[Total Cost Center By Location] ), {[CostCenter].CurrentMember}, All ).Item(1)) = 1 ), { StrToMember( "[CostCenter].[CostCenter].[" + [CostCenter].[CostCenter].CurrentMember.Name + "]" ) })

    See: this page

  • Another example on Intersect:
    {Intersect( TM1SubsetToSet( [Account], "Cost accounts" ), TM1SubsetToSet( [Account], "Filter by level 0" ) )}

    The above expression would be more efficient with TM1FilterByLevel, however, but this is just an illustration.

  • We can automate the previous subset creation in Turbo Integrator as follows:
    vDim = 'Account';
    
    vSubset1 = 'Cost accounts';
    vSubset2 = 'Filter by level 0';
    vSubset3 = 'Input cost accounts';
    
    # Create MDX
    vMdx = '{Intersect( TM1SubsetToSet( [' | vDim | '], "' | vSubset1 | '" ), TM1SubsetToSet( [' | vDim | '], "' | vSubset2 | '" ) )}';
    
    # Or, in a more readable format:
    vMdx = Expand( '{Intersect( TM1SubsetToSet( [%vDim%], "%vSubset1%" ), TM1SubsetToSet( [%vDim%], "%vSubset2%" ) )}' );
    
    SubsetCreateByMDX( vSubset3, vMDX, vDim );
    
  • As well-known the Hierarchize function is, it is remarkably not known at all that it can allow us to show the "dimension structures upside down", much like the "Expand above" option in any subset:
    Hierarchize( TM1SubsetAll( [Project] ), POST )

    However, it is not really an Expand above. Even though the children are shown below the parents, when you expand a parent, it will expand downwards ! (hence, in the usual fashion of expanding totals). This means that you will first see the children, then the total and when expanding the totals, again the children. I don't have an immediate use-case for it but let's keep in mind for when it's needed.

  • Cube values

  • Selecting elements based on values in a cube (we do not have to specify every dimension in the cube):
    {Filter( TM1FilterByLevel( TM1SubsetAll( [BS_Account] ), 0), [BalanceSheet].([FIN_Year].[2023],[FIN_Period].[P07],[FIN_Scenario].[Actual],[BS_Measures].[Amount]) <> 0)}

    If we do not specify an element in a dimension of the cube, TM1 will use the element with the lowest index of all elements at the highest level in the dimension, unless we specify a defaultMember in the }HierarchyProperties control cube. So watch out and make sure this is what you need. Note that we also have a DEFAULT_HIERARCHY property in the }DimensionProperties cube.
    Note that the user must have (READ) access to the cube that is used in the lookup, just as to the elements.
    The defaultMember property of a dimension/hierarchy can be retrieved with:
    { [SalesPerson].DefaultMember }
    The }HierarchyProperties control cube is useful to turn your TM1 models into more dynamic models which are 'readable' by developers that come after you !
    Topcount, bottomcount, topsum, bottomsum, toppercent and bottompercent could be done in a similar fashion:
    {TopCount( TM1FilterByLevel( TM1SubsetAll( [SalesPerson] ), 0), 5, [Sales].([Sales_Measures].[Amount]))}

    A practical use-case for Order and TopCount:
    {Order( TopCount( TM1FilterByLevel( TM1SubsetAll( [SalesPerson] ), 0), 10, [Sales].([Sales_Measures].[Amount])), [Sales].([Sales_Measures].[Amount]), BDesc)} Statements like TopCount or TopSum can be recorded with the interface, as well as sorting elements alphabetically:


    In the above expression please take out the dreaded TM1SubsetBasis (cf. supra). By the way, I discovered a nice trick to quickly see in which cubes a dimension is used: Go to the dimension's Subset Editor, then Tools > Filter... and the dropdown will show you the cubes containing the dimension.

    In Excel reports, the TM1RPTFILTER function can be used as well, to drive TopCount, BottomSum and similar results.



  • As we noticed earlier, the HEAD function can be used to limit a subset to, say, its first 5 elements.

  • Which months in the current year have an actuals exchange rate of USD to EUR not exceeding 0.9 ?
    {Filter( TM1FilterByLevel( TM1SubsetAll( [Month] ), 0), [Currency Rate].([Currency].[USD], TM1Member([Year].[Current Year].Item(0),0), [Scenario].[Actual], [Measure Currency].[Average rate] ) < 0.9 )}

    Here, "Current Year" is a public subset in the Year dimension. Its first and only element is used to filter out the average rate in the cube.

  • Selecting customers that have an outstanding balance in the current month:
    Filter( {TM1FilterByLevel( {TM1SubsetAll( [Customer] )}, 0)}, [Invoice].(TM1Member([Time].[Invoice Month].Item(0),0),[Invoice_measures].[Outstanding balance]) > 0 )

  • A side note: should the cube reference consist of only 1 element, then the brackets ( ) can be left out:
    Filter({TM1FilterByLevel( {TM1SubsetAll( [Customer] )}, 0)}, [Invoice].([Invoice_measures].[Outstanding balance]) > 0 )
    is equal to:
    Filter({TM1FilterByLevel( {TM1SubsetAll( [Customer] )}, 0)}, [Invoice].[Invoice_measures].[Outstanding balance] > 0 )

  • A practical example is an MDX statement to replace the spacer trick. This method allows you to show the next 5 open entries ('rows') for the user. Think about vacancies to budget new hires, or entering CAPEX details.



    {Head( Filter( [Data Entry Row].[All Rows].Children, [Entry Cube].([Version].[Forecast], [Entry Cube Measure].[Entry]) = "" ), 5 )}

    Important notes:
    • This method requires a refresh of the sheet/dashboard to get the extra rows to appear (but not after every row that was input).
    • For the HEAD function to work properly the element ordering and leveling in the dimension is important !
    • If your Entry measure is of type Numeric, replace the double quotes with a 0 in the expression.
    • You could still add [Data Entry Row].CurrentMember, in the Filter expression but you don't have to


    Thank you Lotsaram

  • To convert text in a cube to valid elements, we typically use: TM1FilterByPattern, StrToMember or LookUpCube. We will show examples of the syntax below.

  • The user can choose how many lines to have on screen for input, but with a hardcoded minimum number of 10 lines:
    Head( TM1SortByIndex( TM1FilterByLevel( TM1SubsetAll( [LineNr] ), 0), Asc), Iif( [Activity_Input].([YearMonth].CurrentMember, [Consultant].CurrentMember, [LineNr].[1], [Msr].[Nr of lines] ) < 10, 10, [Activity_Input].([YearMonth].CurrentMember, [Consultant].CurrentMember, [LineNr].[1], [Msr].[Nr of lines] ))))

    Should you want to bring over the value of 10 to a parameter cube:
    Head( TM1SortByIndex( TM1FilterByLevel( TM1SubsetAll( [LineNr] ), 0), Asc), Iif( [Activity_Input].([YearMonth].CurrentMember, [Consultant].CurrentMember, [LineNr].[1], [Msr].[Nr of lines] ) < [z_PARAM].([z_PARAM].[Minimum number of lines], [VAR_TXT].[NUM_VAR1]), [z_PARAM].([z_PARAM].[Minimum number of lines], [VAR_TXT].[NUM_VAR1]), [Activity_Input].([YearMonth].CurrentMember, [Consultant].CurrentMember, [LineNr].[1], [Msr].[Nr of lines] ))))

  • TM1FilterByPattern:
    {TM1FilterByPattern( TM1SubsetAll([Account_PL]), [Prm_Account].([Prm_Account_dim1].[Pattern], [Prm_Account_Msr].[Text]))}

  • LookUpCube is more advanced but it also allows us to filter on elements following information in a cube:
    {TM1FilterByPattern( TM1SubsetAll([Account_PL]), LookUpCube ( "Prm_Account", "([Prm_Account_dim1].[Pattern], [Prm_Account_Msr].[Text])" ) )}

    … will filter all elements in the Account_PL dimension following the pattern mentioned in the lookup cube Prm_Account.


    Furthermore, LookUpCube could also retrieve longer (or entire) MDX expression from a cube cell, next to element names or certain selections. For example:
    {StrToMember( LookUpCube( "Sys_CFG", "[Sys_CFG].[MDX current month], [Sys_CFG_Msr].[Text]" ))}

    whereby the target string cell in the system configuration cube holds: [Period].[June]
    Or:
    {StrToSet( LookUpCube( "Sys_CFG", "[Sys_CFG].[MDX for active users], [Sys_CFG_Msr].[Text]" ))}

    whereby the target string cell in the system configuration cube holds: TM1Sort( Filter( TM1SubsetAll( [}Clients] ), [}ClientProperties].([}ClientProperties].[STATUS]) = "ACTIVE" ), Asc )
    Imagine the possibilities when rules are going to dynamically piece together MDX statements for a given context and that MDX is picked up in a dynamic way in a subset ? Highly dynamic and customized picklists, anyone ? :-)

  • A more useful business example would be to return in a subset the month name that is entered in a lookup cube. For instance, which month and year are subject to being closed financially ?
    {TM1FilterByPattern( TM1SubsetAll([Month]), [Prm_Finance].([Prm_Fin_Param].[Month of close], [Prm_Finance_Msr].[Text]))}

  • But now it gets interesting ! To the best of my knowledge, there aren't many ways to have a dynamic subset on a Months dimension return for example both a month and its year to date (YTD) counterpart. Like, "Nov" and "YTD_Nov" where "Nov" is input in a lookup cube.



    This can be done, however, with similar syntax:
    {Union( TM1FilterByPattern( TM1SubsetAll([Month]), [Prm_Finance].([Prm_Fin_Param].[Month of close], [Prm_Finance_Msr].[Text])), TM1FilterByPattern( TM1SubsetAll([Month]), "YTD_" + [Prm_Finance].([Prm_Fin_Param].[Month of close], [Prm_Finance_Msr].[Text])))}

    Alternatively you can again use the LookUpCube function:
    {Union( TM1FilterByPattern( TM1SubsetAll([Month]), LookUpCube( "Prm_Finance", "([Prm_Fin_Param].[Month of close], [Prm_Finance_Msr].[Text])" )), TM1FilterByPattern( TM1SubsetAll([Month]), "YTD_" + LookUpCube( "Prm_Finance", "([Prm_Fin_Param].[Month of close], [Prm_Finance_Msr].[Text])" )))}

    Syntax 1 definitely has my vote, since it is somewhat shorter, but most of all because we avoid the double quote character ".

    You can of course use Turbo Integrator to create/maintain subsets but honestly, this MDX-based dynamic solution certainly has merits, and is something I would add to TM1 models to increase the usefulness to the TM1 user community.

    You could use a wildcard to cut down on the length of the expression, but beware that this could lead to additional elements in the subset which might not be wanted:
    {TM1FilterByPattern( TM1SubsetAll([Month]), "*" + [Prm_Finance].([Prm_Fin_Param].[Month of close], [Prm_Finance_Msr].[Text]))}

    Finally, and apologies for the spoiler to the Generate function which is discussed below:
    Generate( Filter( TM1FilterByLevel( TM1SubsetAll( [Period] ), 0), [Period].CurrentMember.Properties("YTD") <> ""), {StrToMember("[Period].[" + [Period].CurrentMember.Properties("YTD") + "]")})

    Here we filter out all lowest-level Period elements that have an attribute value (textual) for their YTD name. Then the MDX returns those YTD elements instead of the level 0 elements. Think of Generate as swapping elements for the result of a subquery that uses each element (in turn). More on this below !



  • I already showed, it let's now spend some more time on the StrToMember function, for instance to get the reporting year for Actuals from a parameter cube:
    {StrToMember("[Rp_Year].[" + [Rp_Irp_Parameter].([Rp_Scenario].[Actual], [Rp_Irp_Parameter].[Reporting Year], [Rp_Irp_Parameter_Msr].[Value]) + "]") }

  • An easier example to get introduced to the function:
    {StrToMember("[Period].[" + [Period].[Jul 2023].Properties("Prior Period") + "]")}

    July 2023 is hard-coded but you could make this dynamic.

  • The same result but using the Properties of an element:
    {Filter( TM1FilterByLevel( TM1SubsetAll([Rp_Year]), 0 ), [Rp_Year].CurrentMember.Name = [Rp_Irp_Parameter].([Rp_Scenario].[Actual], [Rp_Irp_Parameter].[Reporting Year], [Rp_Irp_Parameter_Msr].[Value]))}

  • The same result but using the LookUpCube function to get the cube value:
    {StrToMember("[Rp_Year].[" + LookUpCube( "Rp_Irp_Parameter", "[Rp_Scenario].[Actual],[Rp_Irp_Parameter].[Reporting Year],[Rp_Irp_Parameter_Msr].[Value]" ) + "]") }

  • As a short side step, NameToSet exists too:
    {NameToSet("[Rp_Year].[2023]")}

    To point to the element 2023 within the "All years" hierarchy (not PA-hierarchy but traditional hierarchies): {NameToSet("[Rp_Year].[All years^2023]")}

  • This means that we can filter years based on the input of a given year in a system cube:
    {LastPeriods( 4, StrToMember("[Year].[" + [System].([System_Prm].[Year],[System_Msr].[Text]) + "]") )}

    Here we want to retrieve the year from the system cube along with its 3 previous years. Make sure the Year dimension indexes are correct.

  • Going further, a way to filter elements in a dimension based on cube data, where the definition of the cube cells is stored in a parameter cube:
    {Filter( TM1FilterByLevel( TM1SubsetAll( [Period] ), 0), [Periods 2D].( StrToMember("[Year].[" + [System].([System_Prm].[Year], [System_Msr].[Text]) + "]")) > 0 )}

    Hereby, we filter elements in the dimension 'Period' based on data in the cube 'Periods 2D'. In that cube, we select cells based on a year that is stored in the cube 'System'.

  • A real-world example, taken from the TM1 forum. We want to dynamically filter projects for the logged on user, whereby a cube stores the access of users to sites. Site is an attribute of Project:
    {Filter( {Filter({TM1SubsetAll([Project])}, [Project].[Primary Site] <> "" )}, [z_Security_Site].( StrToMember( "[}Clients].[" + USERNAME + "]"), StrToMember("[Site].[" + [Project].[Primary Site] + "]"), [z_Security_Control_Measure].[Write_Flag]) > 0 )}

  • StrToMember and MemberToStr are each other's inverse:
    {StrToMember( MemberToStr( [Project].[001] ) )}

    gives us the element 001. MemberToStr gives us here the string: "[Project].[001]".

  • StrToMember is capable of interpreting functions as well:
    StrToMember("[Period].[2023-05].NextMember")

    can return the next member in the dimension, 2023-06 in this case. An alternative expression could be:

    {StrToMember("[Period].[2023-05]").NextMember}

    or simply:

    [Period].[2023-05].NextMember

  • Likewise, StrToMember can understand FirstChild or Cousin or many others:
    {StrToMember( "[Day].[2023-06].FirstChild.Lag(1)")}

    to get the last day of the month of May 2023 (admittedly, LastChild of 2023-05 is far easier but it's just for illustration purposes).

    It reminds me of the Excel function: =Date(2023, 6, 0 ). "Day 0" of any month gives you the last day of the previous month (even going back to December of last year if needed) !

  • We can apply functions to StrToMember:
    {StrToMember("[Product].[ABC]").FirstChild}

  • Next to StrToMember, functions like StrToSet also exist. The idea is, like with converting a string to a valid dimension member, converting a string to a valid set of elements:
    StrToSet( "{Filter( {[Year].Members}, " + Iif( Count( {Filter( {[Year].Members}, [YM].([Year].CurrentMember, [Maand].[tekst]) = "test" )} ) > 0, "[YM].([Year].CurrentMember, [Maand].[tekst]) = """ + "test" + """", "[Year].CurrentMember.Name = """ + "total" + """" ) + ")}" )

    If certain elements satisfy the condition of having a certain input text in a 2D cube, then take that list. If not, take a dummy element. Code adapted from Declan Rodger's posting here. Added benefit: this example teaches you the functions IIF and COUNT (see below).

  • Another example with IIF and COUNT:
    StrToSet( "{Filter(Descendants([z_test].[Total)," + Iif( Count( {Filter(Descendants([z_test].[Total), [z_test].[Type] = 'A')}) > 0, "[z_test].[Type] = 'A'", Iif( Count( {Filter(Descendants([z_test].[Total]), [z_test].[Type] = 'B')}) > 0, "[z_test].[Type] = 'B'", "[z_test].[Type] = 'C'" )) + ")}" )


  • StrToSet and SetToStr are each other's inverse:
    {StrToSet( SetToStr( [Project].[All projects].Children ) )}

    gives us the children of "All projects" in the Project dimension. SetToStr gives us here the string: "{[Project].[001], [Project].[002], [Project].[003]}" if we limit ourselves to 3 projects.

    Note that even if the set only returns 1 element, the name of the element will still be wrapped in curly braces {}:
    {[Project].[001]}

  • Intermezzo; rather than testing if a cell / input is not empty by using <> "", you can use IsEmpty:
    {Filter( {Filter({TM1SubsetAll([Project])}, Not( IsEmpty( [Project].[Primary Site] )) )}, [z_Security_Site].( StrToMember( "[}Clients].[" + USERNAME + "]"), StrToMember("[Site].[" + [Project].[Primary Site] + "]"), [z_Security_Control_Measure].[Write_Flag]) > 0 )}

    The function IsNull, a valid function in MDX-land, does not seem to be implemented in TM1.

  • Filtering those elements whose cells in a cube contain a certain text:
    Filter( TM1FilterByLevel( TM1SubsetAll( [CostCenter] ), 0), Instr([Prm_CostCenter].([CostType].[No type], [Prm_CostCenter_Msr].[Manager Name]), 'jones' ) > 0)


  • Filtering those elements whose values in a cube are lower than the average over all elements. For instance, the customers who bought more than the average of all customers:
    {Filter( TM1FilterByLevel( TM1SubsetAll( [Customer] ), 0), [Sales].([Sales_Msr].[Amount]) > Avg( TM1FilterByLevel( TM1SubsetAll( [Customer] ), 0), [Sales].([Sales_Msr].[Amount] )))}

    Just like Avg, you can also use (among others): Sum, Min, Max, Median, Aggregate, Var.

    Filter( TM1FilterByLevel(TM1SubsetAll([Time]), 0), [Balance].([Funds].[KDB]) > Avg( TM1FilterByLevel(TM1SubsetAll([Time]), 0), [Balance].([Funds].[KDB])))

    Aggregate( TM1SubsetToSet( [Product], 'Best products' ))
  • Selecting elements based on values in a cube and sort on the cube values:
    {[Customers].[All customers]} + {Order( Filter( TM1FilterByLevel( TM1SubsetAll( [Customers] ), 0), [Sales].([Sales_Measures].[Amount]) <> 0 ), [Sales].([Sales_Measures].[Amount],[Sales_Year].[2023]), Asc) }

  • Filtering elements in rows or columns can also be done on selections in other dimensions, provided that the latter are part of the title section of a view or report. For example, let's filter out models based on the region:


    Suppose that each region/country holds the name of the (consolidated) model that can be sold in the region/country:




    Then we can get the relevant consolidated model element based on the region selection in the titles section:







    1. The MDX is like this:
    {StrToMember( "[model].[" + [region].CurrentMember.Properties("Model selection") + "]")}

    2. Alternatively: We can also use the Filter function as with Declan Rodger here
    Filter( TM1SubsetAll( [model] ), [model].CurrentMember.Name = [region].[Model selection])

    3. This is somewhat longer, in case the attribute name could/would coincide with an element name in the dimension:
    Filter( TM1SubsetAll( [model] ), [model].CurrentMember.Name = [region].CurrentMember.Properties("Model selection"))

    If we want to have the consolidated element and all its lowest-level descendants (for data entry for example):
    {StrToMember( "[model].[" + [region].CurrentMember.Properties("Model selection") + "]")} + TM1Sort( TM1FilterByLevel( Hierarchize( Descendants( {StrToMember( "[model].[" + [region].CurrentMember.Properties("Model selection") + "]")} )), 0 ), Asc )





  • We can also apply it to a more interesting case like the following. Suppose that we have companies and each company sells within a main product category.
    For budget entry we can then have a template with companies as a title selection and in the rows we have the main product category for that company, as well as the level 0 descendants:
    {StrToMember( "[Rp_ProductGroup].[" + [Rp_Company].CurrentMember.Properties("Product Group parent member") + "]")} + TM1Sort( TM1FilterByLevel( Hierarchize( Descendants( {StrToMember( "[Rp_ProductGroup].[" + [Rp_Company].CurrentMember.Properties("Product Group parent member") + "]")} )), 0 ), Asc )



  • Ty Cardin posted on an MDX query where a filter to cube values uses an element that does not exist in a dimension. You can read a short discussion here.

  • Quite often we need to generate subsets that are to be used by input or reporting areas of the TM1 model. It's convenient to generate these subsets as MDX-based dynamic subsets, but obviously you can also turn them into the static variants. Following is a concrete example of a company dimension that holds an attribute of the product group sold. The idea is to create 1 dynamic subset for each company, containing the lowest-level products within the given product group. An example for 1 company:
    TM1Sort( TM1FilterByLevel( Descendants( {StrToMember("[Rp_ProductGroup].[" + [Rp_Company].[C90290].Properties("Product Group parent member") + "]") }] ), 0 ), Asc )

    How do we generate the subsets in 1 TI process ? There are a lot of interesting learning tips in this code so please be sure to look in detail, if needed. A double Expand function is just 1 area of interest.
    # Process to (re)generate subsets on the product dimension, where every company has its own (dynamic) subset of products sold
    sDim_Comp = 'Rp_Company';
    sDim_Prod = 'Rp_ProductGroup';
    sAttr_For_Prod = 'Product Group parent member';
    
    
    # MDX query to get the products linked to a company
    sMDX = 'TM1Sort( TM1FilterByLevel( Descendants( {StrToMember("[%sDim_Prod%].[" + [%sDim_Comp%].[%sElem_Code%].Properties("%sAttr_For_Prod%") + "]") }] ), 0 ), Asc )';
    
    # loop over companies and (re)generate the dynamic subsets
    c = 1;
    While( c <= Dimsiz( sDim_Comp ) );
    
       sElem_Name = Dimnm( sDim_Comp, c );
       sElem_Code = Attrs( sDim_Comp, sElem_Name, 'Code' );
    
       If( sElem_Code @<> '' );
       If( Ellev( sDim_Comp, sElem_Name ) = 0 );
       If( Elisanc( sDim_Comp, 'Total Company', sElem_Name ) = 1 );
    
          vSubset = '}Products_' | sElem_Code;
          If( SubsetExists( sDim_Prod, vSubset ) = 0 );
              SubsetCreate( sDim_Prod, vSubset );
          EndIf;
          SubsetMDXSet( sDim_Prod, vSubset, Expand( sMDX ));
          SubsetAliasSet( sDim_Prod, vSubset, 'Description' );
    
       EndIf;
       EndIf;
       EndIf;
    
       c = c + 1;
    End;
    


  • A consolidated element has multiple (consolidated) children. We want the total and any of the non-zero consolidated children. For any of the children, we want to expand to their children too. This means that for example zero suppression could be turned off and still have a limited number of cube cells. For instance, data input could then be done in an easy way.
    {DrillDownLevel( {[Account].[Net result]} + {Filter( {[Account].[Net result].Children}, [PnL].([Scenario].[Actual], [Period].[2023], [Currency].[Local Currency], [Company].[3200], [PnL_Msr].[Amount] ) <> 0 )} )}

  • When retrieving cube values as strings, they could be empty for whatever reason. Maybe the user missed to do some input. In that case we can use the IIF function:
    StrToMember("[Period].[" + IIF( [User-Navigation].( StrToMember("[}Clients].[" + UserName + "]"), [User-Navigation Measures].[Period]) <> "", [User-Navigation].(StrToMember("[}Clients].[" + UserName + "]"), [User-Navigation Measures].[Period]), "<default>") + "]")

    However, George Tonkin (again him!) found a much neater and shorter solution with a different function, CoalesceEmpty:
    StrToMember("[Period].[" + CoalesceEmpty( [User-Navigation].(StrToMember("[}Clients].[" + UserName + "]"), [User-Navigation Measures].[Period]), "<default>" ) + "]")

  • Filtering on attributes

  • Filtering elements on a String attribute (alias or text attribute) could be achieved with a Property:
    {Filter( TM1SubsetAll( [FIN_Account] ), [FIN_Account].CurrentMember.Properties("Type") = "PL")}

  • The same result can be obtained as follows, in a shorter way:
    {Filter( TM1SubsetAll( [FIN_Account] ), [FIN_Account].[Type] = "PL")}

    The drawback is that this syntax could be ambiguous, if 'Type' is an element or subset or attribute of the dimension/hierarchy. The previous syntax is more robust and therefore better.

  • Another variation, here to retrieve versions that were created by a certain user:
    {Filter( {[version].members}, [version].[created by user] = StrToMember( "[}Clients].[" + UserName + "]").Properties('}TM1_DefaultDisplayValue'))}
    Double quotes around }TM1_DefaultDisplayValue are allowed too.

  • The Caption is a specific attribute and also leads to a specific element property, that can be used for filter purposes. We can filter out elements that match a certain Caption attribute value:
    Filter( TM1SubsetAll( [FIN_Account] ), [FIN_Account].CurrentMember.Properties("MEMBER_CAPTION")="Hotel costs")
    The Caption attribute can be an alias or a regular text attribute. When it is an alias, at most 1 element will be returned. When it is a text attribute, more than 1 element can be returned.

  • Filtering elements on a Numeric attribute is best done through the control cube for element attributes:
    TM1SortByIndex( Filter( TM1FilterByLevel( TM1SubsetAll( [Article] ), 0 ), [}ElementAttributes_Article].([}ElementAttributes_Article].[Quantity]) = 0 ), Asc)
    Here we filter out articles that have a Quantity equal to 0 and sort the resulting articles (if any).

  • Combining (string) information from a lookup cube with a numeric comparison (of dates) involving an attribute - the goal is to filter out periods based on dates:
    Filter( TM1FilterByLevel( TM1SubsetAll([Periods-Months]), 0), [Periods-Months].[TM1 Last Day Serial Date] >= StrToValue( StrToMember( "[Periods-Months].[" + [Prm_Finance].( [Prm_Fin_Param].[Value], [Prm_Finance_Msr].[Text] ) + "]" ).Properties("TM1 Last Day Serial Date")))
    See here.

  • The lookup value for the attribute can also be stored in a cube:
    {Filter( TM1SubsetAll( [FIN_Account] ), [FIN_Account].[Type] = [Prm_Account].([Prm_Account].[Parameter_Value],[Prm_Account_Measures].[Account type]))}

  • Filtering elements on a Numeric attribute:
    {Filter( TM1SubsetAll( [FIN_Account] ), [FIN_Account].[Conversion] = 1)}

  • Filtering those elements at any level that contain an alias:
    {Filter( TM1SubsetAll( [FIN_Account] ), [FIN_Account].[Description] <> "" )}

  • Filtering those elements where an attribute contains a certain text:
    {Filter( TM1SubsetAll( [FIN_Account] ), Instr( [FIN_Account].[Description], "Amortization" ) > 0 )}

    Note that the MDX function Instr is case-sensitive in this form but it can be made case-insensitive too with an additional optional argument of value 1: {Filter( TM1SubsetAll( [FIN_Account] ), Instr( [FIN_Account].[Description], "Amortization", 1 ) > 0 )} In that case, TM1 will convert both earlier arguments to lowercase and then perform the comparison. This means that adding 1 is a more elegant solution then us having to add the LCase or UCase function to both arguments. More information can be obtained here and also here

  • Filtering the currency dimension when the user has a currency attribute filled in:
    { Filter( {TM1SubsetAll([Dim_Currency])}, [}ClientProperties].( StrToMember("[}Clients].[" + USERNAME + "]"), [}ClientProperties].[currency]) = [Dim_Currency].CurrentMember.Name )}
    • Dim_Currency is the dimension of currencies, it could be anywhere in the view, active form, ...
    • currency is an attribute added to the }ClientProperties cube, it should match the currencies in the dimension Dim_Currency

  • Filtering the organisation to which the currently logged in client belongs:
    {Filter({[Organisation].Members}, [Organisation].CurrentMember.Name = StrToMember ( "[}Clients].[" + UserName + "]" ).Properties("Department"))}
  • Filtering the level 0 descendants of elements marked with a certain attribute:
    {TM1FilterByLevel( Descendants( Filter( TM1SubsetAll( [CostCenter] ), [CostCenter].[Overhead CC] = "Y" ) ), 0)}

  • Filtering with the negation of NOT can be useful too:
    {Filter( TM1SubsetAll( [CostCenter] ), NOT Iisleaf( [CostCenter].CurrentMember ))}

  • Filter out elements (consolidations) with exactly 3 children (any level allowed):
    {Filter( TM1SubsetAll( [CostCenter] ), [CostCenter].CurrentMember.Properties("CHILDREN_CARDINALITY") = "3" )}

  • Filter out elements (consolidations) without children:
    {Filter( Filter( TM1SubsetAll( [CostCenter] ), [CostCenter].CurrentMember.Properties("ELEMENT_TYPE") = "3" ), [CostCenter].CurrentMember.Properties("CHILDREN_CARDINALITY") = "0" ) }

  • Filtering out products by inspecting attribute values, taking into account the attribute of a bucket of similar products:
    TM1Sort( Generate( Filter( TM1FilterByLevel(TM1SubsetAll([Product]), 0), [Product].CurrentMember.Properties("Profit Center") <> "" ), { StrToMember("[Product].[" + Iif( StrToMember("[Product].[" + [Product].CurrentMember.Properties("Profit Center") + "]").FirstChild.Properties("Local / Global") <> [Product].CurrentMember.Properties("Local / Global"), [Product].CurrentMember.Name, "# Product" ) + "]" )} ), Asc )

    Well done, George Tonkin !

  • Double lookups

  • We have discussed that attribute values can be retrieved. They can be converted into element names. Let's go a step further and do 2 such lookups. Based on the current month, we ask the "Prior Period", of which we again ask the Period Period:
    { StrToMember("[Period].[" + StrToMember("[Period].[" + [Period].[Jul 2023].Properties("Prior Period") + "]").Properties("Prior Period") + "]") }

    I am not saying that is the best method or even the only one. You could store the attribute values differently and do 1 lookup instead of 2. Of you could use the Lag function.



  • A second illustration goes as follows. A system cube holds the choice of a year. This is converted into a valid element in the Year dimension. That dimension has a text attribute called "Best month", filled in with 01, 02, ..., 12. Lastly the dimension Period has the MDX expression which gives us 1 element as the final result: 03
    {StrToMember("[Period].[" + StrToMember("[Year].[" + [Sys_CFG].([Sys_CFG_Environment].[Current_Env], [Sys_CFG_Input].[Value], [Sys_CFG_Msr].[Selected year]) + "]").Properties("Best month") + "]")}



  • Filtering over dimensions

  • A very useful trick involving Instr is the following. You can apply it to views in the Cube viewer, Planning Analytics, Active forms, and so on. Well, you can filter (e.g.) accounts in the rows of a view in the cube viewer, when the account prefix equals the company name. Company is another dimension in the cube:
    {Filter( TM1SubsetAll( [St_Account] ), Instr( [St_Account].CurrentMember.Name, [Mp_Std_Company].([Mp_Std_Company_Msr].[Company]) ) = 1 )}
    • St_Account is the dimension of accounts in the rows.
    • Mp_Std_Company is the cube where the companies are mapped (a 2D cube with companies and a measure called "Company"). Below, China Guangzhou is mapped in the lookup cube to "C010", which filters the prefix in the accounts.
    It appears that in this setup the element selection for the dimension in the titles must be "retrieved" via a cube, such as Mp_Std_Company. A good alternative can be to use the }ElementAttributes control cube for said dimension.



    This is based on the information in this topic.

  • Above we see a typical mapping cube. In practice we need to find the source elements that are mapped to a certain target:
    {TM1Sort( Filter( TM1FilterByLevel( TM1SubsetAll( [St_Account] ), 0), Instr([Mp_Std_Account].([Mp_Std_Account_Msr].[Reporting Account]), "710000" ) = 1 ), Asc )}

    Here we generate a list of source accounts that are mapped to account 710000. Combine it with the OR function for greater flexibility.

  • Filtering with wildcards

  • Filtering using wildcards:
    {TM1FilterByPattern( TM1FilterByLevel( TM1SubsetAll( [FIN_Account] ), 0), "613?2*")}

  • Filtering using AND and OR:
    { Filter( TM1SubsetAll( [FIN_Account] ), ( ([FIN_Account].[Type] = "PL" AND [FIN_Account].[Conversion] = 1) OR ([FIN_Account].[Description] <> "" ) ) ) }

  • Taking these filters next level:
    TM1Sort(Except({ Filter(TM1FilterByLevel(TM1SubsetAll([_S-Product]), 0), ( [_S-Product].CurrentMember.Properties("AAA") = "" OR [_S-Product].CurrentMember.Properties("BBB") = "" OR [_S-Product].CurrentMember.Properties("CCC") = "" OR ( [_S-Product].CurrentMember.Properties("FFF") = "XYZ" AND [_S-Product].CurrentMember.Properties("GGG") = "")) AND Instr(1, [_S-Product].CurrentMember.Properties("Status"), "DO NOT DELETE", 1) = 0 )}, {[_S-Product].[#Product],[_S-Product].[No Product]}), Asc)



  • You can also interrogate values of a chosen attribute for the pattern - not just aliases are supported:
    {TM1FilterByPattern( TM1FilterByLevel( TM1SubsetAll( [FIN_Account] ), 0), "*Maintenance*", "Description")}

    Simply add the attribute name as an extra argument to the function. Note that the lookup is a case-insensitive one, so Maintenance yields the same hits as mAinTeNANcE. This is probably what most users require such that they do not have to remember or guess the exact spelling. For a case-sensitive search, consider Instr. Note that Filter and Instr can be much slower than. TM1FilterByPattern. Certainly as of April 2023, when it was reported that IBM apparently improved the function.

  • The Is keyword can be used to execute logical tests too:
    {Filter( {TM1SubsetAll( [Fct_Country] )}, [Fct_Country].CurrentMember Is [Fct_Country].[BE] )}

    Here I filter out the element that is logically equal to the BE element in the dimension Fct_Country. Of course, the expression above is not very optimized. We should not 'loop' over all elements to identify a certain element, since we can pick the said element in a direct way (see other syntax examples), like: {[Fct_Country].[BE] )}. However more advanced examples could be thought of.

  • More on sorting

  • Sorting the hierarchy following its consolidation structures:
    { Hierarchize( TM1SubsetAll( [CostCenter] ))}

  • Sorting the elements by index (all elements have a unique index number):
    {TM1SortByIndex( TM1SubsetAll( [PL_Account] ), Asc)}

    Alternatively:
    {Order( TM1SubsetAll( [PL_Account] ), [PL_Account].CurrentMember.Properties("Index"), Asc)}
    Or:
    {Order( TM1SubsetAll( [PL_Account] ), [PL_Account].CurrentMember.Properties("MEMBER_ORDINAL"), Asc)}
    Both submitted by George Tonkin, thanks.

  • Sorting the elements the principal name:
    Order( TM1SubsetAll( [PL_Account] ), [PL_Account].CurrentMember.Properties("MEMBER_CAPTION"), Asc)

  • A TI process approach to sort elements on their principal name, leading to a static subset. Here, vDim is the name of the dimension of the subset, vSubset is the name of the subset to sort.
  • vDim = 'PL_Account';
    vSubset = 'tmp';
    vSubset_tmp = vSubset | '_xyz';
    
    SubsetCreate( vDim, vSubset_tmp, 1 );
    vMDX = '{TM1SubsetToSet([' | vDim | '].[' | vDim | '], "' | vSubset | '", "public")}';
    SubsetMDXSet( vDim, vSubset_tmp, vMDX );
    vMDX = 'Order( {TM1SubsetToSet([' | vDim | '].[' | vDim | '], "' | vSubset_tmp | '", "public")}, [' | vDim | '].[' | vDim | '].CurrentMember.Properties("MEMBER_CAPTION"), Asc )';
    
    SubsetMDXSet( vDim, vSubset, vMDX );
    SubsetMDXSet( vDim, vSubset, '' );
    SubsetDestroy( vDim, vSubset_tmp );
                            
  • Months 'smaller' (earlier) than a threshold (variable) month (for example, copy Actuals to Budget scenario) (element names like 202009):
    {TM1Sort( Filter( TM1FilterByLevel( TM1SubsetAll( [Time] ), 0), [Time].CurrentMember.Name <= "' | pLastMonthOfActuals | '" ), Asc)}
    or (Code is an alias on the Time dimension):
    {TM1Sort( Filter( TM1FilterByLevel( TM1SubsetAll( [Time] ), 0), [Time].[Code] <= "' | pLastMonthOfActuals | '" ), Asc)}
    or (selecting a range of months, possibly spanning multiple years):
    {TM1Sort( TM1FilterByLevel( [Time].[202001]:[Time].[202009], 0), Asc)}

  • Selecting Products that have revenue but where an attribute is missing (entered by users or loaded from a source system):
    {TM1Sort( Filter( Filter( TM1FilterByLevel( TM1SubsetAll( [Product] ), 0), [Rpt_Sales].([Year_Month].[Total 2023], [Region].[Total Region], [Sales_Msr].[Revenue]) <> 0), [Product].[Sales_Rep] = "" ), Asc )}

    Note that this kind of dynamic subset is an ideal candidate to present in a view to users - one can see immediately for which products the attribute should be completed.

  • Generate

  • Generate can be tricky but very useful. It allows to apply an operation on every element in a first selection/Set. Like in: select all level 1 customers (consolidated customers) and for each of them, find the customer with the highest revenue:
    {Generate( {TM1FilterByLevel( {TM1SubsetAll( [Customers] )}, 1)}, TopCount( Descendants([Customers].CurrentMember, 1), 1, Act_Sales.([Act_Sales_Msr].[Revenue])))}

    Please note that with Generate, the second clause is the operative dimension in which you create the subset.

  • A second example is provided below. You have a typical month structure but the fiscal year starts in April while the calendar year starts in January (obviously there are multiple ways to tackle this and this is not necessarily the best method):
    Generate( Order([Month_YTD_FY_Offset].[Total Year].Children, [Month_YTD_FY_Offset].CurrentMember.Properties("FY order"), Asc), Descendants( {StrToMember("[Month_YTD_FY_Offset].[" + [Month_YTD_FY_Offset].CurrentMember.Name + "]")}))

    A numeric attribute is used to capture the order of the months in the fiscal year. The output is summarized for clarity, not all days are shown.



    gives:



  • A third example if you like. List all managers of employees in a subset. Manager names are part of the same dimension and they are entered against the employee name in a 3D-cube called "Employee Planning":
    {Generate( Filter( TM1SubsetAll( [Employee] ), [Employee Planning].([Scenario].[RP 2023], [Employee Planning Measures].[Manager ID]) <> ""), {StrToMember("[" + [Employee Planning].([Scenario].[RP 2023], [Employee].CurrentMember, [Employee Planning Measures].[Manager ID]) + "]")})}

  • A fourth example looking at cost accounts in the Profit and Loss statement. What about, by 2-digit cost bucket (60, 61, 62, 63, 64, ... ) listing the value of that bucket, including the 3 accounts with the highest values:
    {Generate( TM1FilterByLevel( Descendants( {[Account].[6]} ), 1 ), Union( [Account].CurrentMember, TopCount( Descendants([Account].CurrentMember, 1), 3, [Rpt_PL].([Company].CurrentMember, [Scenario].CurrentMember, [Year].CurrentMember, [Period].CurrentMember, [Currency].[Group Currency], [Rpt_PL_Msr].[Value] ))))}

    I will let you digest that one for a minute, although we have discussed all functions used.

  • To return all elements in a dimension (dim_1) that also exist in a second dimension (dim_2):
    Generate( TM1SubsetAll([Dim_1]), Filter( TM1SubsetAll([Dim_2]), [Dim_2].CurrentMember.Name = [Dim_1].CurrentMember.Name))

    In this example, the subset will be created in the dimension Dim_2. Adapted from here.

  • We can use this function to compare elements in dimensions. For clean up purposes, we would like to identify all elements that are not part of a second dimension. Real use-case: a dimension containing balance sheet accounts got polluted and needs to be validated against a dimension containing all accounts (all correct accounts).
    Except( TM1FilterByLevel( TM1SubsetAll([Balance Sheet Account]), 0), Generate( TM1FilterByLevel( TM1SubsetAll([_S-General Ledger Account]), 0), Filter( TM1FilterByLevel( TM1SubsetAll([Balance Sheet Account]), 0), [Balance Sheet Account].CurrentMember.Name = [_S-General Ledger Account].CurrentMember.Name)))

    Yes, that's correct, it's lengthy. And an ElementIndex (Dimix) function in a TI process could do the same. But still useful as MDX serves different purposes. Submitted by George Tonkin, thanks for that.

  • Let's compare the lowest level elements in 2 entire hierarchies:
    { Except( { TM1FilterByLevel( Descendants( {[Customer].[Total Customer by country]} ), 0 )}, { TM1FilterByLevel( Descendants( {[Customer].[Total Customer by manager]} ), 0 )} )}

    What remains is the elements of the first hierarchy that are not part of the second. Note: to compare elements in different hierarchies in Planning Analytics-speak ('Hierarchies' or Alternative Hierarchies), you need code that is more involved. Tweaking the above with different hierarchy names will not work.

    To put you on the right track with dimensions (introduce hierarchies yourself):
    Except( TM1FilterByLevel( TM1SubsetAll([ Dimension 1 ]), 0), Generate( TM1FilterByLevel( TM1SubsetAll([Dimension 2]), 0), Filter( TM1FilterByLevel( TM1SubsetAll( [Dimension 1]), 0), [Dimension 1].CurrentMember.Name = [Dimension 2].CurrentMember.Name)))

    Unfortunately, alias values will not be picked up. A Dimix or ElementIndex nowadays, is more powerful.

  • Return all elements in a dimension that are a child of a certain element in a different dimension:
    Generate( [dim_B].[700000].Children, Filter( TM1FilterByLevel( TM1SubsetAll([dim_A]), 0), [dim_A].CurrentMember.Name = [dim_B].CurrentMember.Name))

  • Another stab on comparing the lowest level elements in 2 entire parts of the dimension/hierarchies:
    Except( TM1FilterByLevel( Descendants( [Trading Partner].[All by Geography] ), 0 ), {Intersect( TM1FilterByLevel( Descendants( [Trading Partner].[All by Geography] ), 0 ), TM1FilterByLevel( Descendants( [Trading Partner].[IC] ), 0 ))})

  • Final example: you have a dimension ('A') with elements. These elements can occur as an alias (called Alt_Name) in a second dimension ('B'). You would like to create a subset containing all dimension A elements that occur in dimension B:
    Generate( Filter( TM1SubsetAll( [B] ), Len([B].[Alt_Name]) > 0), {StrToMember("[A].[" + [B].[Alt_Name] + "]")})

    Caveat: if the Alt_Name alias is filled in in dimension B, that name has to exist as an element in dimension A ! If it does not, TM1 will throw up an error in the best case, some TM1 versions will even experience a crash ! Thank you Ty Cardin



  • To get the first full admin user:
    Head( Filter( TM1SubsetAll( [}Clients] ), [}ClientGroups].([}Groups].[ADMIN]) = "ADMIN" ), 1 )

  • To list all security groups that 1 or more users are part of:
    Hierarchize( Generate( TM1SubsetToSet([}Clients], "users" ), Filter( TM1SubsetAll([}Groups]), [}ClientGroups].([}Clients].CurrentMember) <> "" )))

    "users" is a (public) subset containing the users you would like to evaluate. Most probably this subset will only contain 1 element but you are free to have multiple users. The result of the MDX expression, group names, can be copy/pasted elsewhere - for example in other security cubes.
    You can also have other logic instead of SubsetToSet, adjust that part of the expression to suit.

    With a Turbo Integrator process to automate the task:
    m = 'Test users';
    n = Expand( 'Groups linked to subset %m%' );
    
    If( SubsetExists( '}Clients', m ) = 0 );
       SubsetCreate(  '}Clients', m );
    EndIf;
    If( SubsetExists( '}Groups', n ) = 0 );
       SubsetCreateByMDX( n, Expand( 'Hierarchize( Generate( TM1SubsetToSet([}Clients], "%m%" ), Filter( TM1SubsetAll([}Groups]), [}ClientGroups].([}Clients].CurrentMember) <> "" )))'), '}Groups' );
    EndIf;
    

    Below you will find similar code.

  • To list all security clients that are part of a number of security groups:
    Generate( TM1SubsetToSet([}Groups], "Groups subset" ), Filter( TM1SubsetAll([}Clients]), [}ClientGroups].([}Groups].CurrentMember) <> "" ))

    "Groups subset" is a (public) subset containing the groups you would like to evaluate. Most probably this subset will only contain 1 element but you are free to have multiple groups. The result of the MDX expression, client names, can be used elsewhere.
  • The Len function gives you the length of a string.


  • Subsets based on other objects

  • To quickly populate a subset in TI with elements from another subset, use TM1SubsetToSet:
    SubsetCreateByMDX( 'Target subset', 'TM1SubsetToSet( [Account], "Source subset" )' );
    


    The source subset will probably be dynamic but that's not a requirement. After the previous line to create the subset, you can still add or remove elements in the target subset such that, as an added benefit, the target subset becomes static.

    [Continue reading on this in the next paragraph.]


    Or retrieve all elements of that dimension:
    SubsetCreateByMDX( 'Target subset', 'TM1SubsetAll( [Account] )' );
    

    Or all elements in a dimension Account2 that also exist in the dimension Account:
    SubsetCreateByMDX( 'Target subset', 'Generate( TM1SubsetAll([Account]), Filter( TM1SubsetAll([Account2]), [Account].CurrentMember.Name = [Account2].CurrentMember.Name))' );
    

    Finally, all elements in a dimension Account2 that also exist in the subset 'Filter by level 0' in the dimension Account:
    SubsetCreateByMDX( 'Target subset', 'Generate( TM1SubsetToSet([Account], "Filter by level 0"), Filter( TM1SubsetAll([Account2]), [Account].CurrentMember.Name = [Account2].CurrentMember.Name))' );
    

    The latter expression is a winner, it saves you from writing a loop over subset elements.
  • If an MDX expression returns no results, use a different subset:
    StrToSet( Iif( Count( Filter( TM1SubsetAll([Company]), [Company].CurrentMember.Properties("Active") = "Y" )) > 0, "Filter( TM1SubsetAll( [Company]), [Company].CurrentMember.Properties(""Active"") = ""Y"" )", "TM1SubsetAll([Company])" ))

    If there are Active companies, filter those out. If there are No Active companies, return all companies.
    The function StrToSet is not my favorite to be honest. Working with text to generate an MDX query is second best in my opinion.

    Does anyone know a better way to achieve the same result ?

  • Distinct elements

  • Generating a list of distinct element names:
    { Distinct( TM1SubsetAll( [PL_Account] ))}


    or based on an existing subset:
    { Distinct( TM1SubsetToSet( [PL_Account], "YOUR_SUBSET_NAME" ))}
  • To end up with only the distinct (unique) elements in a set in PAW, you can simply put a Distinct( {Rest of the existing MDX code} ) around it which removes any duplicates from the given set while retaining the first instance of each element from that original set. For instance, copy/paste a set of elements in the Set editor, then go to the MDX definition and surround it with that function.

    Keep in mind though that Distinct({MDX Statement}) is not the same as starting with TM1SubsetAll. Distinct is looking for unique MUNs (Member Unique Name), dimension paths towards an element or elements.
    [Product].[Product].[New Products^A] is a different member than [Product].[Product].[Products On Sale^A]

    Refer to this topic on removing duplicate elements.
  • Weird at first sight... I compared 2 sets of elements:
    TM1FilterByLevel( TM1SubsetAll( [Customer] ), 2 )
    TM1FilterByLevel( Descendants( {[Customer].[Selections]} ), 2 )


    Set 2 contained more elements than set 1. The right comparison is to filter in case 1 on all MUNs:
    TM1FilterByLevel( Distinct( [Customer].Members ), 2)

    This dimension happened to have a lot of cases where the same-named element appears in many parts of the dimension.

  • We can generate a list of Distinct elements with MDX applied in a TI process. Consider the solutions in this topic:
    dDimName = 'Versions';
    
    # the operator +
    SubsetCreateByMDX( '1', Expand( '{{[%dDimName%].[Planning]} + {[%dDimName%].[Budget]} + 
    {[%dDimName%].[%PriorMonthForecast%]} + {[%dDimName%].[Jan Forecast]} + {[%dDimName%].[Mar Forecast]} + 
    {[%dDimName%].[%PriorMonthSnapshot_1%]} + {[%dDimName%].[%PriorMonthSnapshot_2%]}}' ));
    
    # the function Union, which only works on pairs
    SubsetCreateByMDX( '2', Expand( 'Union( {[%dDimName%].[Planning]}, { {[%dDimName%].[Budget]}, 
    {[%dDimName%].[%PriorMonthForecast%]}, {[%dDimName%].[Jan Forecast]}, {[%dDimName%].[Mar Forecast]}, 
    {[%dDimName%].[%PriorMonthSnapshot_1%]}, {[%dDimName%].[%PriorMonthSnapshot_2%]} } )' ));
    
    # function Distinct
    SubsetCreateByMDX( '3', Expand( 'Distinct( { {[%dDimName%].[Planning]}, {[%dDimName%].[Budget]}, 
    {[%dDimName%].[%PriorMonthForecast%]}, {[%dDimName%].[Jan Forecast]}, {[%dDimName%].[Mar Forecast]}, 
    {[%dDimName%].[%PriorMonthSnapshot_1%]}, {[%dDimName%].[%PriorMonthSnapshot_2%]} } )' ));
    
    # Distinct with condensed coding (double Expand function is needed)
    d = '[%dDimName%].';
    SubsetCreateByMDX( '4', Expand( Expand( 'Distinct( { %d%[Planning], %d%[Budget], %d%[%PriorMonthForecast%], 
    %d%[Jan Forecast], %d%[Mar Forecast], %d%[%PriorMonthSnapshot_1%], %d%[%PriorMonthSnapshot_2%] } )' )));
    


  • Orphans and top consolidations

  • Orphans in the dimension (definition: level 0 elements without parent consolidation), but ONLY elements of type N or S:
    {Filter( TM1FilterByLevel( TM1SubsetAll([Accounts]), 0), [Accounts].CurrentMember.Parent.Name = "" )}

    Or:
    {Filter( TM1FilterByLevel( TM1SubsetAll([Accounts]), 0), Count([Accounts].CurrentMember.Ancestors) = 0)}

    Or:
    {Filter( Filter( TM1SubsetAll([Accounts]), [Accounts].CurrentMember.Parent.Name = ""), Isleaf( [Accounts].CurrentMember ))}

  • Orphans in the dimension (definition: elements without parent consolidation), all element types (N, C, S)):
    {Filter( TM1SubsetAll([Accounts]), [Accounts].CurrentMember.Parent.Name = "" )}

  • Orphans in the dimension (definition: elements without parent consolidation), all element types (N, C, S)):
    {Filter( TM1SubsetAll([Accounts]), [Accounts].CurrentMember.Parent.Name = "" )}

  • Elsewhere in this document we show how to filter on element types:
    [dimension].[hierarchy].CurrentMember.Properties("ELEMENT_TYPE") = "1" or "2" of "3"

  • Top level consolidations or the root elements
    In Turbo Integrator, have a look at the DimensionTopElementName function too. {Except( Filter( TM1SubsetAll( [Accounts] ), [Accounts].CurrentMember.Parent.Name = "" ), {TM1FilterByLevel( TM1SubsetAll( [Accounts] ), 0 )} )}
    Wrapping this statement in the TM1SortByIndex function can be useful.

    Alternative shorter expression:
    [Accounts].Levels(0).Members

    Here I used the levels of a dimension/hierarchy, as discussed above.
    This works too:
    [Accounts].[level000].Members or even [Accounts].[Top accounts].Members if you gave that specific level000 a clear name (which is good practice in TM1 by the way !). Please refer to the IBM site

    Should a subset exist with the same name as a named level, then here the named level takes precedence.

  • Top level consolidations containing a certain element (account 600000):
    Filter( Filter( TM1SubsetAll([Accounts]), [Accounts].CurrentMember.Parent.Name = ''), TM1TupleSize(Intersect({[Accounts].[600000]}, Descendants({[Accounts].CurrentMember})).Item(0)) > 0 )

    This expression features the function TM1TupleSize to return the number of members in a tuple.

  • Consolidations without children:
    {Filter( TM1FilterByLevel( TM1SubsetAll([Accounts]), 1), Isleaf( [Accounts].CurrentMember ))}

    Alternatively:
    {Filter( TM1FilterByLevel( TM1SubsetAll([Accounts]), 1), [Accounts].CurrentMember.FirstChild.Name = "")}

    Alternatively:
    {Filter( TM1FilterByLevel( TM1SubsetAll([Accounts]), 1), Count([Accounts].CurrentMember.Children) = 0)}

    Alternatively:
    {Filter( TM1FilterByLevel( TM1SubsetAll([Accounts]), 1), TM1TupleSize( ([Accounts].CurrentMember.Children).Item(0)) = 0)}

    With the TM1 REST API:
    /api/v1/Dimensions('Accounts')/Hierarchies('Accounts')/Members?$select=Name&$expand=Element($select=Type),Children/$count&$filter=Element/Type eq 3 and Children/$count eq 0
    Source

  • Distinguishing the element type (N, C or S), much like ElementType and DType elsewhere in TM1:
    Filter( TM1SubsetAll( [Revenue_Msr] ), [Revenue_Msr].CurrentMember.Properties("ELEMENT_TYPE") = "1" )
    "1" = type N (Numeric, level 0), "2" = type S (String, text), "3" = type C (Consolidated, level > 0 )
    Thanks to George Tonkin.

  • In a similar spirit of having an MDX equivalent for existing TM1 functions like ElementWeight and ElWeight:
    {Filter( Filter( TM1SubsetAll([Revenue_Msr]), Count([Revenue_Msr].CurrentMember.Ancestors) > 0), [Revenue_Msr].CurrentMember.Properties("MEMBER_WEIGHT") <> "1.000000")}

    Better would be to convert textual values to a number with StrToValue:
    {Filter( Filter( TM1SubsetAll([Revenue_Msr]), Count([Revenue_Msr].CurrentMember.Ancestors) > 0), StrToValue([Revenue_Msr].CurrentMember.Properties("MEMBER_WEIGHT")) <> 1)}

  • To check with a TI statement whether an hierarchy contains orphans, consider:
    If( HierarchyHasOrphanedLeaves( 'Dimension name', 'Hierarchy name' ) = 1 );
       # The hierarchy contains orphaned leaves, take action if needed
    EndIf;
    


  • TM1 users and groups

  • The current TM1 username in the }Clients dimension (call this subset whoami):
    {StrToMember("[}Clients].[" + USERNAME + "]")}

    Alternatively:
    {TM1FilterByPattern( TM1SubsetAll( [}Clients] ), USERNAME )}

  • Using this notion of a username we can also use for the user (given a subset whoami as defined above):
    {[}Clients].[whoami].Item(0)}

    Or:
    TM1SubsetToSet([}Clients], "whoami")

    Or:
    {TM1Member([}Clients].[whoami].Item(0),[}Clients])}

  • The list of security groups to which a client (vUser) has been assigned:
    Filter( [}Groups].Members, [}ClientGroups].( [}Clients].[' | vUser | '] ) <> "" )
    Note that the resulting subset could be empty.

  • The list of security groups to which the logged in user has been assigned:
    Filter( [}Groups].Members, [}ClientGroups].( StrToMember("[}Clients].[" + USERNAME + "]")) <> "" )
    Note that the resulting subset could be empty.

  • Let me take this (a whole lot) further with a TI process to create a custom view with dynamic subsets in the }ClientGroups cube:
    # Make sure the }ClientPropertiesSyncInterval=5 is present in the TM1s.cfg file
    
    c0 = 'Active clients security';
    vCube = '}ClientGroups';
    vDim_1 = '}Clients';
    vDim_2 = '}Groups';
    
    ## start from scratch
    If( ViewExists( vCube, c0 ) > 0 );
       ViewDestroy( vCube, c0 );
       SubsetDestroy( vDim_1, c0 );
       SubsetDestroy( vDim_2, c0 );
    EndIf;
    
    # create subsets in the relevant dimensions
    SubsetCreateByMDX( c0, Expand( 'TM1Sort( Filter( TM1SubsetAll( [%vDim_1%] ), [}ClientProperties].([}ClientProperties].[STATUS]) = "ACTIVE" ), Asc )' ), vDim_1 );
    SubsetCreateByMDX( c0, Expand( 'TM1Sort( Hierarchize( Generate( Filter( TM1SubsetAll( [%vDim_1%] ), [}ClientProperties].([}ClientProperties].[STATUS]) = "ACTIVE" ), Filter( TM1SubsetAll( [%vDim_2%] ), [%vCube%].([%vDim_1%].CurrentMember) <> "" ))), Asc )' ), vDim_2 );
    
    # apply an Alias
    If( Dtype( '}ElementAttributes_}Clients', '}TM1_DefaultDisplayValue' ) @= 'AA' );
       SubsetAliasSet( vDim_1, c0, '}TM1_DefaultDisplayValue' );
    EndIf;
    If( Dtype( '}ElementAttributes_}Groups', '}TM1_DefaultDisplayValue' ) @= 'AA' );
       SubsetAliasSet( vDim_2, c0, '}TM1_DefaultDisplayValue' );
    EndIf;
    
    # create a view
    ViewCreate( vCube, c0 );
    
    # add subsets to the view
    ViewSubsetAssign( vCube, c0, vDim_1, c0 );
    ViewSubsetAssign( vCube, c0, vDim_2, c0 );
    
    # the view layout
    ViewRowDimensionSet(  vCube, c0, vDim_1, 1 );
    ViewRowDimensionSet(  vCube, c0, vDim_2, 2 );
    ViewSuppressZeroesSet( vCube, c0, 1 );
    
  • The list of users that are ACTIVE (logged on, at least) in TM1:
    TM1Sort( Filter( TM1SubsetAll( [}Clients] ), [}ClientProperties].([}ClientProperties].[STATUS]) = 'ACTIVE' ), Asc )

    Precondition is that in the TM1s.cfg file, we add a property: ClientPropertiesSyncInterval=5 (a dynamic property, no need to restart TM1)
    TM1 stores the output in the }ClientProperties cube in a measure called "STATUS"
    5 is the number of seconds at which the list of active users is refreshed.
    To disable it, use 0 or leave out the property.

  • Combine the previous MDX to end up with a view in the }ClientGroups cube containing the groups of the active users:
    Filter( [}Groups].Members, [}ClientGroups].( StrToMember("[}Clients].[" + USERNAME + "]")) <> "" )
    Note that the resulting subset could be empty.

  • Application and control objects

  • All application cubes in the TM1 model:
    TM1Sort( Except( TM1SubsetAll( [}Cubes] ), TM1FilterByPattern( TM1SubsetAll( [}Cubes] ), "}*" )), Asc)
    Likewise for processes, dimensions, … TM1Sort( Except( TM1SubsetAll( [}Cubes] ), TM1FilterByPattern( TM1SubsetAll( [}Dimensions] ), "}*" ) ), Asc)

  • All control cubes in the TM1 model:
    TM1Sort( {TM1FilterByPattern( TM1SubsetAll( [}Cubes] ), "}*" ), Asc)

    Likewise for processes, dimensions, …

  • When you look at the Microsoft links I mentioned above, you will find a lot more functions. Including functions for information on the dimension structure: FirstSibling, Parent, Children, FirstChild / LastChild, Ancestors, and so on. Many other options for creating dynamic subsets are explained on that webpage. It is a must read!

    Temporary subsets

    Needless to say, but these subset definitions using MDX syntax can be used in the function SubsetCreatebyMDX. That function can also create temporary subsets as of TM1 10.2.2 FP4 (see here).

    TM1ELLIST

    The function TM1ELLIST in a Planning Analytics For Excel spreadsheet can return an array of elements from a hierarchy. Interesting twist is that the list can be driven by an MDX. This opens many doors that were previously hard to open. The workaround of having a dynamic report (active form) was not elegant. Nor the workaround of having to array-enter the SUBNM formula in "enough" cells, knowing that it would need the MDX dynamic subset be part of the hierarchy. A fully dynamic MDX in a spreadsheet to drive a selection… nada ! Now we can.

    You can just enter in a cell like A1:
    =TM1ELLIST("CXMD:}Clients",,,,,"Head( TM1SubsetAll( [}Clients] ), 10 )")
    and the result will spill down in the cell and 9 cells below - unless you have less than 10 users in the model. No need for array-entering the formula with Ctrl-Shift-Enter to receive the curly braces left and right of the formula. You now enter the world of dynamic arrays in Excel.

    For those using VBA to generate the formula, consider:

    Sub create_ellist()
    
        Dim vMDX As String
    
        vMDX = "TM1FilterByLevel( TM1SubsetAll( [Year] ), 0 )"
    
        'creating a TM1ELLIST function as a dynamic array
        Range("A1").Formula2 = "=TM1ELLIST(""servername:Year"",,,,,""" & vMDX & """)"
        Range("B1").Formula2 = "=""Y"" & A1#"
    
    End Sub
    

    The result are Year elements in column A, and the same elements prefixed with a "Y" in the corresponding cells in column B.

    Lists in Planning Analytics For Excel provide similar functionality. They could provide a good alternative for dynamic reports in case you just want to return hierarchy members with some attributes or security information.

    IS

    The IS keyword can be used as well. If you remember the dynamic subsets we created to filter elements by levels, named appropriately in the }HierarchyProperties control cube, this can be written with IS as well:
    Filter( TM1SubsetAll( [Period_MDX] ), [Period_MDX].CurrentMember.Level IS Semester )

    In case the name of the level is a reserved keyword or there happens to be a dimension with the same name, you should fully qualify the name:
    Filter( TM1SubsetAll( [Period_MDX] ), [Period_MDX].CurrentMember.Level IS [Period_MDX].[Year] )

    Another secret found by George Tonkin.

    Count

    We have used the function Count before, but it's a good idea to list some of the many use cases (input by Philip Bichard):

    • how many bad debtors do we have ?
    • how many cost centres are late with their budget submission
    • how many customers did not buy from us in the last 12 months
    • etc.

    Escape character

  • When you are searching for text and the text contains a double quote ("), you should escape it with another double quote (here we look for elements with my "quoted text" as cell contents):
    Filter( TM1SubsetAll([Line]), [inputcube].([measure].[Text]) = "my ""quoted text""" )

    When you are filtering out elements that should match a pattern with a double quote, use the same trick (here we look for the element "quoted text" surrounded by quotes):
    TM1FilterByPattern( TM1SubsetAll([Line]), """qu*ed text""")

    Lastly, it is identical for the Instr function (here we look for elements containing "quoted):
    Filter( TM1SubsetAll( [Line] ), Instr( [Line].CurrentMember.Name, """quoted" ) > 0 )

  • Caveats

    A few caveats apply. If you create a dynamic subset in TI (the function is called SubsetCreatebyMDX('NAME OF THE SUBSET', 'MDX EXPRESSION'), make sure you always have at least 1 element that matches. If not, the process errors out. Unless you use TM1 10.1 or later, where an undocumented 3rd parameter to the function equal to the dimension name, will avoid the error in case no elements satisfy the expression. As an alternative, in that case you should loop over the dimension elements and insert the matching elements in a static subset SubsetCreate('DIMENSION NAME', 'SUBSET NAME') and SubsetElementInsert('DIMENSION NAME', 'SUBSET NAME', 'ELEMENT NAME', POSITION). The latter technique will always work (unless you are stuck in an endless loop like me on some Monday mornings), whichever you will use depends on your liking and coding skills.

    Please do NOT use the function TM1SubsetBasis() (unless you know what you are doing). Even though the MDX expression recorder generates such code, it is in fact not to be used. It refers to a relative selection of elements ('at the time of using the function') rather than an absolute selection of elements ('it will always be the same selection/result, all else being equal').

    Excel

    In Excel spreadsheets, we can work with MDX queries to return a subset: for example in active forms. There, you could store the MDX query in a (hidden) cell. The query expression could be chopped up to include cell references. For instance, the user can choose a Product family in cell H10, and the active form returns the data on the lowest-level children of that Product family. Mind that there could be a 256 characters limit for the MDX expression for older versions of TM1. You COULD leave out the dimension names BUT then the element names must be unique throughout the ENTIRE TM1 model (over all dimensions).

    MDX Views

    Now that you are a full-blown expert on MDX in Planning Analytics, the party's only started. You can have cube views based on MDX expressions too. Since this is a broad topic on its own, here is an example of what an MDX view might look like:

  • A Profit and Loss cube, with level 0 company elements in the columns. In the titles we have element references for: Actual scenario, year 2023, September year-to-date, currency EUR. Lastly, in the rows we have an asymmetric selection of elements within the Accounts and CostCenter dimensions. First we have the tuple EBITDA with Total Cost Center and its immediate children. Then we have all level 0 accounts combined with all level 0 cost centers.
    SELECT NON EMPTY {TM1FilterByLevel( TM1SubsetAll( [Company].[Company] ), 0)} ON 0, NON EMPTY { {[Account].[Account].[EBITDA]}*{DrillDownLevel( {[CostCenter].[CostCenter].[Total Cost Center]} )}, {TM1FilterByLevel( TM1SubsetAll( [Account] ), 0)}*{TM1FilterByLevel( TM1SubsetAll( [CostCenter].[CostCenter] ), 0)}} ON 1 FROM [Rpt_ProfitLoss] WHERE ([Scenario].[Scenario].[Actual], [Year].[Year].[2023], [Period].[Period].[9 YTD], [Currency].[Currency].[EUR])

    Likewise for processes, dimensions, …

    ON 0 can be substituted for ON COLUMNS. ON 1 can be substituted for ON ROW. You may swap rows and columns in the MDX view definition if you find it easier to understand.

    Views like this were not possible in Architect/Perspectives. Views like this can be the data source to a TI process. They are stored with extension xbv in the data directory. xbv stands for "Expression-Based View".

    You can go definitely crazy here since you would apply any MDX syntax you already learnt on this page ! :-)

  • Thank you

    One of the many nice emails I received over the years !






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    Wim Gielis is a Business Intelligence consultant and Excel expert

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