As I understand Microsoft's explanation setting the AggregateFunction of a measure to "None" should null out the value unless you are viewing the data at the lowest possible level. (i.e. the data element is a copy of the value in one exact cell in the cube).
I've created a fact table at the grain product id and sales date, and have set AggregateFunction property of a few measures (they are percentages of some sort) to "None", and I nulls at every level in the cube, even the product/sales date level (I am using Excel to connect to the cube and drilling through a pivot table).
I'm sure that there is something simple that I am missing, but I don't quite see what.
When Aggregate Function of a Measure is set to 'None', SSAS does not calculate the measure for the 'All' member in any dimension. Put in other words, we will have only leaf-level values for measures and that too only for dimensions that are directly linked to that fact.
You can find more elaborate explanation in this post.
Related
I am trying to write a calculated member which acts differently depending on whether the user is filtering by that member or has it dragged down as rows or columns on their pivot table (using Excel).
The rules are:
1. If the user is using the date dimensin as a Report Filter in Excel, then the calculated member should get the maximum date out of all dates that they are filtered by.
2. If they have the date dimension as rows on the pivot table, then I need to apply ClosingPeriod and some other logic.
Please try this. The idea came from here.
Basically the dynamic named set represents what's in the report filters. And the EXISTING keyword trims the list of days down to the filter context of the current cell letting you detect say if one month is on rows. Compare counts and you can detect what the user did.
CREATE HIDDEN DYNAMIC SET CURRENTCUBE.SelectedDays as
[Date].[Date].[Date].Members;
CREATE MEMBER CURRENTCUBE.[Measures].[My Calc] as
CASE
WHEN SelectedDays.Count > {existing [Date].[Date].[Date].Members}.Count
THEN Tail({existing [Date].[Date].[Date].Members},1).Item(0).Item(0).Name
WHEN SelectedDays.Count < [Date].[Date].[Date].Members.Count
THEN Tail(SelectedDays,1).Item(0).Item(0).Name
END
Performance is going to not be good. And I suspect users will be confused with the results of your calc. If you want to describe the business scenario more I can maybe recommend a better approach.
We are using a SASS SSAS driven pilot table where we would like to add a calculated measure using the sum of a column.
We don't know in advance which filters the users will be using, the measure is valid for any of them, so we just tried adding a calc measure on the excel file such as
[Measures].[Sales]/sum(axis(1),[Measures].[Sales])
But it doesn't seem to work. So just to test we started with a plain
sum(axis(1),[Measures].[Sales])
which gives some astonishing result.
We cannot figure out what the result is adding up! Applying some filters and a detailed row, we get exactly twice the expected value (!!??).
Applying exactly the same filters and filtering also the rows, we get a value that we are not able to guess where it comes from.
Any idea about what MDX should we use?
Edited to clarify: We want to add the calculated measure on an Excel pivot table, not on the SSAS olap cube definition.
I obviously was having a bad day. One cannot think excel-like to solve an mdx issue.
A simple
([MyDim].[MyHierarchy].currentmember.parent,[Measures].[Sales])
is the right syntax to use in our calculus as the "parent total".
Thks
Due to performance issues I need to remove a few distinct counts on my DAX. However, I have a particular scenario and I can't figure out how to do it.
As example, let's say one or more restaurants can be hired at one or more feasts and prepare one or more menus (see data below).
I want a PowerPivot table that shows in how many feasts each restaurant was present (see table below). I achieved this by using distinctcount.
Why not precalculating this on Power Query? The real data I have is a bit more complex (more ID columns) and in order to be able to pivot the data I would have to calculate thousands of possible combinations.
I tried adding to my model a Feast dimensional table (on the example this would only be 1 column of 2 rows). I was hoping to use that relationship to be able to make a straight count, but I haven't been able to come up with the right DAX to do so.
You could use COUNTROWS() combined with VALUES().
Specifically, COUNTROWS() will give you the count of rows in a table. That means COUNTROWS is expecting a table is input. Here's the magic part: VALUES() will return a table as results, and the table it returns are the distinct values in the table/column that you provide as the argument for VALUES().
I'm not sure if I'm explaining it well, so for the sample data you provided, the measure would look like this (assuming the table is named Table1):
Unique Feasts:=COUNTROWS(VALUES('Table1'[Feast Id]))
You can then create a pivot table from Powerpivot, and drag Restaurant Id into Rows, and drag the measure above into Values. Same result as DISTINCTCOUNT, but with less performance overhead (I think).
I have 2 tables.
First table: dimensional table to show available units of cars at start of selling cycle and for how long these units will be available.
Second table: to show how many cars were sold on a given month within their "available cycle".
I'd like to compare the "selling behaviour" within each cycle. Thus, I want to display the total initial units available next to the units sold at each stage within the cycle. The second dimension works fine, but not the first one.
This is what I get:
And this the desired output (note rows 4 and 5 for available_units)
I tried the below DAX code without success:
SumAvailableUnits:=CALCULATE(SUM([available_units]),FILTER(ALL(Table1[month_within_cycle]),[month_within_cycle]>=MAX([months_available])))
First, DAX Formatter is your friend. You may like writing unreadable single line measures, but no one else likes reading them.
I've also taken the liberty of cleaning up your table names and adding fully qualified column references. (Ignoring that your dimension isn't a pure dimension, as it holds numeric values that you aggregate in a measure)
SumAvailableUnits :=
CALCULATE (
SUM ( DimCar[available_units] ),
FILTER (
ALL ( FactSale[month_within_cycle] ),
FactSale[month_within_cycle] >= MAX ( DimCar[months_available] )
)
)
And immediately we see a problem. With the fully qualified column references, it is clear that you're trying to filter the lookup table (the one side) by the base table (the many side). In Power Pivot for Excel, we do not have bi-directional relationships (though they're available in Power BI and coming for Excel 2016). Our relationships' filter context only flows from the lookup table to the base table, typically from the dimension to the fact.
Additionally, your DimCar, by holding [available_units] and [months_available] encodes an implicit assumption that a specific [car_id] can only ever refer to a single, unchanging lot. You will never see another row with [car_id] = 1. This strikes me as highly unlikely. Even if it is the case the better solution is a model change.
In general, anything that goes onto a row or column label should come from a dimension, not a fact. Similarly, anything you're aggregating in a measure should live in a fact table. The usual exception is dimension counts - either bare, or as a denominator in a measure. Following these will get you 80% of the way in terms of dimensional modeling. You can see the tables and model diagram I've ended up with in the image below.
Here are the measure definitions
SumAvailableUnits:=SUM( FactAvailability[available_units] )
SumSold:=SUM( FactSale[cars_sold] )
Here are my source tables, my model diagram with relationships, and a pivot table built from these pieces and the measures above. Note the source of [month_within_cycle] in the pivot.
Finally, you might notice that my grand total behaves in a different way than in your original. Since the values are repeated monthly, we get a much larger grand total. If you need to instead end with the sum from the latest month (which it looks like you have in your sample), you can use an alternate measure, provided below. I don't understand why this would be your desired grand total, but you can achieve it fairly easily. Personally, I'd probably blank the measure at the grand total level.
SumAvailableUnits - GrandTotal:=
SUMX(
TOPN(
1
,FactAvailability
,FactAvailability[month_within_cycle]
,0
)
,FactAvailability[available_units]
)
This uses SUMX() to step through the table provided, defined by TOPN(). TOPN() returns the first row (in this case) in FactAvailability, including ties, after sorting by [month_within_cycle], out of all rows available in the filter context. In the context of a specific month, you get all the rows associated with that month - identical to the simple sum. In the grand total context, you get the rows associated with the last month.
SUMX() iterates over that table and accumulates the values of [available_units] in a sum.
I have run into performance problems with MDX measure calculations for a summary report, using SQL Server 2008 R2.
I have a Person dimension, and a related fact table containing multiple records per person. (Qualifications)
Eg [Measures].[Other Qual Count] would give me the number of qualifications of a certain type.
Each person could have multiple, so [Measures].[Other Qual Count] > 1 for one person.
However on my summary report I would like to indicate this as 1 per person only. (To indicate the number of persons with Other qualifications.)
The summary report rolls up the values against some other dimensions including an unknown Region hierarchy (it can be one of 3 hierarchies).
I have done this as follows:
MEMBER [Measures].[Other Count2]
AS
SUM(
EXISTING [Person].[Staff Code].[Staff Code].Members,
IIF([Measures].[Other Count] > 0, 1, NULL)
)
However, I have to create several more derived measures - deriving from each other, and all at Person level to avoid unwanted multiple counts. The query slows down from <1 second to 1min+ (my goal is <3s).
The reason for all the derivations is a lot of logic to determine within which one of 6 mutually exclusive column a person will be reported in.
I have also tried to create a Cube Calculation, but this gives me the same value as [Other Count].
SCOPE (({[Person].[Staff Code].[Staff Code].MEMBERS}, [Measures].[Has Other Qual]));
THIS = ([Person].[Staff Code].[Staff Code], [Measures].[Has Other Qual]).Count;
END SCOPE;
Is there a better MDX/Cube calculation that can be used, or any suggestions on improving performance?
This is unfortunately my first time working with MDX and ran into this problem close to a deadline, so I am trying to make this work if possible without changes to the cube.
I have resolved the issue by changing the cube, which was simpler than expected.
On the Data Source View, I created a named query which summarizes the existing fact table at Person level. I also derive all the columns which I will need on my reports.
Treating this named query as a separate fact table, I added a measure group for it and that resolved all my problems.