I have a calculated member that looks like this:
Asian Weighted = ([Measures].[Asian] * [Measures].[Population])
My MDX query looks like this:
WITH
MEMBER [Measures].[AsianPop] AS
(([Measures].[Asian Weighted], [Jurisdiction.BTA].[BTA].&[51]) / ([Jurisdiction.BTA].[BTA].&[51], [Measures].[Population]))
SELECT
{[Measures].[AsianPop]} ON 0
FROM
[Selection Statistics]
The problem is in the numerator. Asian and Population are both SUMMED before they are multiplied together. Is there a straightforward way to do a weighted average in MDX?
The solution that you described in your comment - pre-caclulating the measure to sum - is the best approach. In theory, you could implement the correct calculation purely in MDX, but this is complex and in many cases - at least in Analysis Services, I have no experience with Mondrian - really slow. You would have to instruct the MDX engine explicitly to do the multiplication on leaf level, and then aggregate. You could use functions like Leaves or Descendants to go to leaf level. You would have to think about the attributes for which you need to go down to leaf level, and for which attributes this may not be necessary. My assumption - as far as Analysis Services is concerned - is that as this uses a custom aggregation, all the built in aggregations which make the cube fast are not used.
Related
I have a problem which looked like a simple requirement ... it turned out it wasn't ... at least for me.
At the moment I feel like I've read half of the MDX internet ...
I'm using latest Saiku CE (Mondrian 4), and my simplified cube looks like this:
Dimensions:
Machine.Manufacturer
Measures:
Measure.[Msg count]
Measure.[Distinct machines]
Measure.[Distinct days]
Calculated measures:
Measure.[Msg xMxD] which is basically: (Measure.[Msg count] / Measure.[Distinct machines] / Measure.[Distinct days]).
Measure.[Msg xMxd %] which is: (Measure.[Msg xMxD] / SUM(Measure.[Msg xMxD], Machine.[Manufacturer].[All Manufacturers]))
What I want to accomplish is this table:
But as you've probably guessed, I have a problem with the Measure.[Msg xMxd %] measure ...
Because it is calculated on base of another calculated measure, the % calculation is done after the summing for a particular Manufacturer and I don't know how to overcome this.
The closest answer I found was this one: https://forums.pentaho.com/threads/160265-Calculate-members-in-mdx/
... but this concerns only one generated member as a sum of all manufacturers.
I've found also some resolutions based on Axis(...) functions but those are unavailable in Mondrian.
Do you have any ideas ? Is there a possibility to generate a set of calculated members ? this would (at least theoretically) give me a possible to set solve order for all child members of [Machine].[Manufacturer]
Any help is much appreciated.
Scenario
Designing a Star Diagram for an OLAP environment for the process Incident Management. Management requests to be able to both filter on SLA status (breached, achieved or in progress) and being able to calculate the percentage of sla achieved vs breached. Reporting will be done through in Excel/SSRS through SSAS (tabular).
Question
I’m reasonable inexperienced in designing for an OLAP environment. I know my idea will work but I’m concerned this is not the best approach.
My idea:
SLA needs to be both a measure and a dimension.
DimSLA
…
(Nullable bool) Sla Achieved -> Yes=True, No=False, and InProgress=NULL
…
FactIncident
…
(Nullable Integer) Sla Achieved Yes=1,No=0 and In Progress=NULL
…
Then in SSAS, publish a calculated percentage field which averages FactIncident-SlaAchieved.
Is this the right/advisable way to do it?
As you describe it, "SLA achieved" should be an attribute, as you want to classify by it, not sum it. The only thing you want to sum or aggregate would be other measures (maybe an incident count) under the condition that the "SLA achieved" attribute has certain values like "achieved" or "not achieved". This is the main rule in dimensional design: Things you use for classifying or break down are attributes, and things that you calculate are measures. There are a few cases where you need a column for both, but not many.
Do not just use a boolean value. Use a string value easily understand by users like the texts "SLA achieved", "SLA not achieved", "in progress". This makes it much more easy for non technical users to use the cube. In case you use this in a dimension table , there would be just three records with the strings, and the fact table would reference them with maybe a byte foreign key, hence more meaningful texts do not use up millions of bytes.
How do I create custom rollup types in icCube?
Say, I need WAvg (which is already implemplemented there) instead of plain Avg function. But I it is not on the dropdown list in measure creation form. What should I do now?
Alexander, I assume you're talking about the cube builder.
The weighted-average is not available in the list of available aggregation types because there's no straitforward way to implement it at cube level. Aggregation types available for standard measures are simple calculations. Those calculation are meant to be very fast for millions of rows. You've two kinds of average available for standard measures : 'average on leafs(rows)' and 'average on children', which might be near what you're looking for.
In the case of a weighted average you have to create a calculated measure: you need to defined the values to "weight" your underlying measure against. The documentation weighted-average is giving several examples.
I have a SSAS cube in which there is a measure that needs to be allocated via a percentage located in another measure. I have all this set up as a Measure Expression in my "Equity Amount" measure and it works great.
My problem is that this "Equity Amount" measure is actually a snapshot so I would need it to aggregate using the LastChild function. It turns out that you cannot have a measure expression in a semi additive measure so i'm trying to fake the LastChild function in MDX.
I've seen a lot of examples everywhere on the web and all but none of them talk about having multiple hierarchies in the date dimension. I have both "calendar Year" and "Fiscal Year" hierarchies.
My MDX works for one hierarchy but as soon as I scope for the second hierarchy, the first one gets overwritten. I'm guessing I need to treat both hierarchies in a single statement but am having a real tough time getting it to work.
Here is my MDX for one hierarchy. Can anyone help modify it for multiple hierarchies or is there any other way to solve my problem ?
Scope([Measures].[Equity Value]);
This = iif(isleaf([Calendar].[By Calendar Year].CurrentMember),
[Measures].[Equity Value],
([Calendar].[By Calendar Year].CurrentMember.LastChild,[Measures].[Equity Value]));
End Scope;
David,
1) You're using scope as a calculated member. You can get rid of your iif by declaring the scope working only in a sub-cube :
scope ([Measures].[Equity Value],[Calendar].[By Calendar Year].levels(0).... )
This = (the expression)
2) Not sure to understand your problem but a tuple with two members of two hierarchies of the same dimension can be null by construction: As an example your first day of the calendar (1/1/2010) and the first day of your fiscal calendar (e.g. 1/6/2020) are not the same day so actually null. Two hierarchies of a same dimension are only ways of representing the same coordindates (here days), you're doing an intersection by declaring a tuple.
Not sure I'm helping you...
Thanks for trying! I understand what you mean (I think). MDX is one tough language!
I ended up doing the allocation via the view that is the source for my measure and keeping the LastChild aggregation function for the measure. In the end, it is much easier and also is better for query performance.
Thanks anyway :)
I know MDX is used for much more sophisticated math, so please forgive the simplistic scenario, but this is one of my first Calculated members.
When I multiply Price x Quantity, the AS cube's data browser has the correct information in the leaf elements, but not in any of the parents. The reason seems to be that I want something like (1 * 2) + (2 * 3) + (4 * 5) and not (7 * 10) which think I am getting as a result of how the Sum is done on columns.
Is the IsLeaf expression intended to be used in these circumstances? Or is there another way? If so, are there any examples as simple as this I can see?
This Calculated member that I tried to create is just this:
[Measures].[Price]*[Measures].[Quantity]
The result for a particular line item (the leaf) is correct. But the results for, say, all of april, is an incredibly high number.
Edit:
I am now considering that this might be an issue regarding bad data. It would be helpful though if someone could just confirm that the above calculated member should be work under normal circumstances.
Here it is a blog post dealing with this particular problem: Aggregating the Result of an MDX Calculation Using Scoped Assignments.
For leaf level computations resulting in something that can then be summed, MDX is rather complex and slow.
The simplest way to do what you want to achieve would be to make this a normal measure, based on the Price x Quantity calculation defined in the data source view.