I struggling with conditional grouping of some members within query.
In my simplified example I have two dimensions and one measure. The first dimension contains some categories and the second dimension some units. In all but one category, all categories have a single unit (category A and B in the example). However, one category has multiple units. If I put both dimensions on rows I get multiple results for category C (as in the following example). What I really need is to get one line per category, with the Amount appropriately aggregated but also with the displayed units (in case of category C, they should be replaced either by single "none" or concatenated together if this is not possible ("km, kg" in the example)).
The following example should illustrate what I am trying to achieve.
With the following query:
SELECT
NON EMPTY { [Measures].[Amount] } ON COLUMNS,
NON EMPTY { ([Grouping A].[Category].[Category].ALLMEMBERS *
[Grouping B].[Unit].[Unit].ALLMEMBERS ) } ON ROWS
FROM [ExampleCube]
I get data like this:
Category Unit Amount
A km 10
B km 5
C km 5
C kg 2
C km 5
But what I really need to achieve is to group the dimension Category and treat the dimension Unit and measure Amount appropriately as follows:
Category Unit Amount
A km 10
B km 5
C none 12
Maybe this is really simple but I have been trying to solve this for a while with no results.
Any ideas would be appreciated.
Thanks.
It's not simple. OLAP hasn't been designed for this kind of things.
Nonetheless, you can solve it in the following way:
With
[Measures].[Unit] as
IIF(
NonEmpty(
[Grouping B].[Unit].[Unit].Members,
[Measures].[Amount]
).Count > 1,
"None",
NonEmpty(
[Grouping B].[Unit].[Unit].Members,
[Measures].[Amount]
).Item(0).Name
)
Select
Non Empty { [Measures].[Unit],[Measures].[Amount] } on 0,
Non Empty { [Grouping A].[Category].[Category].Members } on 1
From [ExampleCube]
Related
I'm attempting to create a new Calculated Measure that is based on 2 different attributes. I can query the data directly to see that the values are there, but when I create the Calculated Member, it always returns null.
Here is what I have so far:
CREATE MEMBER CURRENTCUBE.[Measures].[Absorption]
AS sum
(
Filter([Expense].MEMBERS, [Expense].[Amount Category] = "OS"
AND ([Expense].[Account Number] >= 51000
AND [Expense].[Account Number] < 52000))
,
[Measures].[Amount - Expense]
),
VISIBLE = 1 , ASSOCIATED_MEASURE_GROUP = 'Expense';
Ultimately, I need to repeat this same pattern many times. A particular accounting "type" (Absorption, Selling & Marketing, Adminstrative, R&D, etc.) is based on a combination of the Category and a range of Account Numbers.
I've tried several combinations of Sum, Aggregate, Filter, IIF, etc. with no luck, the value is always null.
However, if I don't use Filter and just create a Tuple with 2 values, it does give me the data I'd expect, like this:
CREATE MEMBER CURRENTCUBE.[Measures].[Absorption]
AS sum
(
{( [Expense].[Amount Category].&[OS], [Expense].[Account Number].&[51400] )}
,
[Measures].[Amount - Expense]
),
VISIBLE = 1 , ASSOCIATED_MEASURE_GROUP = 'Expense';
But, I need to specify multiple account numbers, not just one.
In general, you should only use the FILTER function when you need to filter your fact table based on the value of some measure (for instance, all Sales Orders where Sales Amount > 10.000). It is not intended to filter members based on dimension properties (although it could probably work, but the performance would likely suffer).
If you want to filter by members of one or more dimension attributes, use tuples and sets to express the filtering:
CREATE MEMBER CURRENTCUBE.[Measures].[Absorption]
AS
Sum(
{[Expense].[Account Number].&[51000]:[Expense].[Account Number].&[52000].lag(1)} *
[Expense].[Amount Category].&[OS],
[Measures].[Amount - Expense]
),
VISIBLE = 1 , ASSOCIATED_MEASURE_GROUP = 'Expense';
Here, I've used the range operator : to construct a set consisting of all [Account Number] members greater than or equal to 51000 and less than 52000. I then cross-join * this set with the relevant [Amount Category] attribute, to get the relevant set of members that I want to sum my measure over.
Note that this only works if you actually have a member with the account number 51000 and 52000 in your Expense dimension (see comments).
An entirely different approach, would be to perform this logic in your ETL process. For example you could have a table of account-number ranges that map to a particular accounting type (Absorption, Selling & Marketing, etc.). You could then add a new attribute to your Expense-dimension, holding the accounting type for each account, and populate it using dynamic SQL and the aforementioned mapping table.
I don't go near cube scripts but do you not need to create some context via the currentmember function and also return some values for correct evaluation against the inequality operators (e.g.>) via the use of say the membervalue function ?
CREATE MEMBER CURRENTCUBE.[Measures].[Absorption]
AS sum
(
[Expense].[Amount Category].&[OS]
*
Filter(
[Expense].[Account Number].MEMBERS,
[Expense].[Account Number].currentmember.membervalue >= 51000
AND
[Expense].[Account Number].currentmember.membervalue < 52000
)
,
[Measures].[Amount - Expense]
),
VISIBLE = 1 , ASSOCIATED_MEASURE_GROUP = 'Expense';
EDIT
Dan has used the range operator :. Please make sure your hierarchy is ordered correctly and that the members you use with this operator actually exist. If they do not exist then they will be evaluated as null:
Against the AdvWks cube:
SELECT
{} ON 0
,{
[Date].[Calendar].[Month].&[2008]&[4]
:
[Date].[Calendar].[Month].&[2009]&[2]
} ON 1
FROM [Adventure Works];
Returns the following:
If the left hand member does not exist in the cube then it is evaluated as null and therefore open ended on that side:
SELECT
{} ON 0
,{
[Date].[Calendar].[Month].&[2008]&[4]
:
[Date].[Calendar].[Month].&[1066]&[2] //<<year 1066 obviously not in our cube
} ON 1
FROM [Adventure Works];
Returns:
i have a huge table of cashflows that means there are +int values for income and -int values for outcome.
I have MeasureGroup for Sum the amount of money.
I now want to display not only the sum of money per month but also the sum of all the past time until the current month so like that:
Month MoneyAmount Total
1 20 20
2 -10 10
3 5 15
4 -10 5
So i know for the first part its just like
select [Measures].[Money] on 0,
[Date].[Month].Members on 1
From MyCube
but how can i add the sum column?
i thought about something like SUM( { NULL : [Date].[Month].CurrentMember } , [Measures].[Money] ) but that didnt work as well :(
In MDX, the total is already there. You do not have to do complex calculations to get it.
But it depends on your exact hierarchy structure how the All member is called. If you have a date user hierarchy named [Date].[Date], and it has a month level named [Date].[Date].[Month], then the all member of the hierarchy would probably be called something like [Date].[Date].[All]. If [Month] is an attribute hierarchy of the Date dimension, then the "all member" would probably be called [Date].[Month].[All]. In the latter case, the all member would already be the first member of the set [Date].[Month].Members. As you are asking the question, I am assuming this is not the case, and you are using a user hierarchy. Then you could change your MDX query to
select [Measures].[Money] on 0,
Union([Date].[Month].Members, { [Date].[Date].[All] }) on 1
From MyCube
Please note that you can change the name of the All member in the property settings of a dimension when designing an Analysis Services dimension, hence I cannot know the definitive name without knowing the details of this setting in your cube. So you might have to adapt the name of the all member.
You can find this name out in SQL Server Management Studio in an MDX window as follows: open the hierarchy that you are using, and then open the "Members" node, below which you should find the "All Member". You can drag this into your MDX statement, and the proper name will appear there.
As in a running sum?
You need a calculated measure, like this:
With Member [Measures].[Running Sum] as Sum( ( [Date].[Months].Members.Item(0) : [Date].[Months].CurrentMember ), [Measures].[Money])
Select [Date].[Months].Members on Rows,
{[Measures].[Money], [Measures].[Running Sum] } on Columns
From [MyCube]
I am trying to calculate percentile (for example 90th percentile point of my measure) in a cube and I think I am almost there. The problem I am facing is, I am able to return the row number of the 90th percentile, but do not know how to get my measure.
With
Member [Measures].[cnt] as
Count(NonEmpty(
-- dimensions to find percentile on (the same should be repeated again
[Calendar].[Hierarchy].members *
[Region Dim].[Region].members *
[Product Dim].[Product].members
,
-- add the measure to group
[Measures].[Profit]))
-- define percentile
Member [Measures].[Percentile] as 90
Member [Measures].[PercentileInt] as Int((([Measures].[cnt]) * [Measures].[Percentile]) / 100)
**-- this part finds the tuple from the set based on the index of the percentile point and I am using the item(index) to get the necessary info from tuple and I am unable to get the measure part
Member [Measures].[PercentileLo] as
(
Order(
NonEmpty(
[Calendar].[Hierarchy].members *
[Region Dim].[Region].members *
[Product Dim].[Product].members,
[Measures].[Profit]),
[Measures].[Profit].Value, BDESC)).Item([Measures].[PercentileInt]).Item(3)**
select
{
[Measures].[cnt],
[Measures].[Percentile],[Measures].[PercentileInt],
[Measures].[PercentileLo],
[Measures].[Profit]
}
on 0
from
[TestData]
I think there must a way to get measure of a tuple found through index of a set. Please help, let me know if you need any more information. Thanks!
You should extract the tuple at position [Measures].[PercentileInt] from your set and add the measure to it to build a tuple of four elements. Then you want to return its value as the measure PercentileLo, i. e. define
Member [Measures].[PercentileLo] as
(
[Measures].[Profit],
Order(
NonEmpty(
[Calendar].[Hierarchy].members *
[Region Dim].[Region].members *
[Product Dim].[Product].members,
[Measures].[Profit]),
[Measures].[Profit], BDESC)).Item([Measures].[PercentileInt])
)
The way you implemented it, you tried to extract the fourth (as Item() starts counting from zero) item from a tuple containing only three elements. Your ordered set only has three hierarchies.
Just another unrelated remark: I think you should avoid using complete hierarchies for [Calendar].[Hierarchy].members, [Region Dim].[Region].members, and [Product Dim].[Product].members. Your code looks like you are including all levels (including the all member) in the calculation. But I do not know the structure and names of your cube, hence I may be wrong with this.
An alternate method could be to find the median of the last 20% of the records in the table. I've used this combination of functions to find the 75th percentile. By dividing the record count by 5, you can use the TopCount function to return a set of tuples that make up 20% of the whole table sorted in descending order by your target measure. The median function should then land you at the correct 90th percentile value without having to find the record's coordinates. In my own use, I use the same measure for the last parameter in both the Median and TopCount functions.
Here's my code:
WITH MEMBER Measures.[90th Percentile] AS MEDIAN(
TOPCOUNT(
[set definition]
,Measures.[Fact Table Record Count] / 5
,Measures.[Value by which to sort the set so the first 20% of records are chosen]
)
,Measures.[Value from which the median should be determined]
)
Based on what you've supplied in your problem definition, I would expect your code to look something like this:
WITH MEMBER Measures.[90th Percentile] AS MEDIAN(
TOPCOUNT(
{
[Calendar].[Hierarchy].members *
[Region Dim].[Region].members *
[Product Dim].[Product].members
}
,Measures.[Fact Table Record Count] / 5
,[Measures].[Profit]
)
,[Measures].[Profit]
)
I have two measures:
[Measure].[ChildCount] and [Measure].[Buyings]
and two dimensions:
[Buyers] and [Sellers].
[Measure].[ChildCount] uses [Buyers] dimension to count child organization for each of the buyer.
[Measure].[Buyings] uses [Buyers] and [Sellers] to count buying from [Seller] to [Buyer].
What I want to achieve is select all buyings for Buyers with ChildCount < 1 and Buyers with ChildCount > 0.
Currently these queries are working fine:
First one that count buying for each sender/buyer:
SELECT [Measure].[Buyings] on COLUMNS,
[Sellers].[Code].[Code] *
[Buyers].[Code].[Code] ON ROWS
FROM MyCube
And second that calculates buyings for buyers with and without childs:
WITH MEMBER [Measure].[BuyingsWithChilds]
as SUM
(
FILTER([Buyers].[Code].[Code],[Measure].[ChildCount]>0),
[Measure].[Buyings]
)
MEMBER [Measure].[BuyingsWithoutChilds]
as SUM
(
FILTER([Buyers].[Code].[Code],[Measure].[ChildCount]<1),
[Measure].[Buyings]
)
SELECT
{
[Measure].[BuyingsWithChilds],
[Measure].[BuyingsWithoutChilds]
} ON COLUMNS,
[Buyers].[Code].[Code] ON ROWS
FROM MyCube
But if I trying to combine these queries into desired one:
WITH MEMBER [Measure].[BuyingsWithChilds]
as SUM
(
FILTER([Buyers].[Code].[Code],[Measure].[ChildCount]>0),
[Measure].[Buyings]
)
MEMBER [Measure].[BuyingsWithoutChilds]
as SUM
(
FILTER([Buyers].[Code].[Code],[Measure].[ChildCount]<1),
[Measure].[Buyings]
)
SELECT
{
[Measure].[BuyingsWithChilds],
[Measure].[BuyingsWithoutChilds]
} ON COLUMNS,
[Sellers].[Code].[Code] ON ROWS
FROM MyCube
This query's execution takes forever.
Is it possible to fix or optimize this?
If you convert [Measure].[ChildCount]>0 and [Measure].[ChildCount]<1 to an attribute like "HasChildren", then you can avoid the Filter function which is normally slow, and which you use two times.
Then your WITH clause would be simplified to
WITH MEMBER [Measure].[BuyingsWithChilds]
as ([Buyers].[HasChildren].[Yes], [Measure].[Buyings])
MEMBER [Measure].[BuyingsWithoutChilds]
as ([Buyers].[HasChildren].[No], [Measure].[Buyings])
which should be much faster, as it uses the standard aggregation of [Measure].[Buyings].
I’m pretty new to the many-to-many dimensions but I have a scenario to solve, which raised a couple of questions that I can’t solve myself… So your help would be highly appreciated!
The scenario is:
There is a parent-child Categories dimension which has a recursive Categories hierarchy with NonLeafDataVisible set
There is a regular Products dimension, that slices the fact table
There is a bridge many-to-many ProductCategory table which defines the relation between the two. Important to note is that a product can belong to any level of the categories hierarchy – i.e. a particular category can have both – directly assigned products and sub-categories.
There is a fact Transactions table that holds a FK to the Product that has been sold, as well as a FK to its category. The FK is needed, because
I have all this modeled in BIDS, the dimension usage is set between each of the dimensions and the facts, the many-to-many relation between the Categories and the Transactions table is in place is in place. In other words everything seems kind of OK..
I now need to write an MDX which I would use to create a report that shows something like that:
Lev1 Lev2 Lev3 Prod Count
-A
-AA 6
-AA 2
P6 1
P5 1
-AAA 2
P1 1
P2 1
-AAB 2
P3 1
P4 1
+BB
The following MDX almost returns what I need:
SELECT
[Measures].[SALES Count] ON COLUMNS,
NONEMPTYCROSSJOIN(
DESCENDANTS([Category].[PARENTCATEGORY].[Level 01].MEMBERS),
[Product].[Prod KEY].[Prod KEY].MEMBERS,
[Measures].[Measures].[Bridge Distinct Count],
[Measures].[SALES Count],
2) ON ROWS
FROM [Sales]
The problem that I have is that for each of the non-leaf categories, the cross join returns a valid intersection with each of the products that’s been sold for it + all subcategories. Hence the result set contains way too much redundant data and besides I can’t find a way to filter out the redundancies in the SSRS report itself.
Any idea on how to rewrite the MDX so that it only returns the result set above?
Another problem is that if I create a role-playing Category dimension which I set to slice directly the transactions data, then the numbers that I get when browsing the cube are completely off… It seems as SSAS is doing something during processing (but it’s not the SQL statements it shoots to the OLTP, as those remain exactly the same) that causes the problem, but I’ve no idea what. Any ideas?
Cheers,
Alex
I think I found a solution to the problem, using the following query:
WITH
MEMBER [Measures].[Visible] AS
IsLeaf([DIM Eco Res Category].[PARENTCATEGORY].CurrentMember)
MEMBER [Measures].[CurrentProd] AS
IIF
(
[Measures].[Visible]
,[DIM Eco Res Product].[Prod KEY].CurrentMember.Name
,""
)
SELECT
{
[Measures].[Visible]
,[Measures].[CurrentProd]
,[Measures].[FACT PRODSALES Count]
} ON COLUMNS
,NonEmptyCrossJoin
(
Descendants
(
[DIM Eco Res Product].[Prod KEY].[(All)],
,Leaves
)
,Descendants([DIM Eco Res Category].[PARENTCATEGORY].[(All)])
,[Measures].[FACT PRODSALES Count]
,2
)
DIMENSION PROPERTIES
MEMBER_CAPTION
,MEMBER_UNIQUE_NAME
,PARENT_UNIQUE_NAME
,LEVEL_NUMBER
ON ROWS
FROM [Sales];
In the report then I use the [Measures].[CurrentProd] as a source for the product column and that seems to work fine so far.