I have a named set like this :
(
[DimDate].[Hierarchy].currentmember.lag(1)
,
[Measures].[Fact Transaction Count]
)
This code give me count of transaction of yesterday current member. now I want to use it to calculate daily growth. some thing like this :
(
([Measures].[Fact Transaction Count] - GetPreviousTransactionValueDate.Item(0).Item(0)) / GetPreviousTransactionValueDate.Item(0).Item(0)
) * 100
when use it in SSMS I can get output but when I send it to SSDT I get a Null value for all hierarchy.
this code give me output :
with member measures.GetPreviousTransactionValueDate as
(
[DimDate].[Hierarchy].currentmember.lag(1)
,
[Measures].[Fact Transaction Count]
)
member measures.Roshd as
(
([Measures].[Fact Transaction Count] - measures.GetPreviousTransactionValueDate) / measures.GetPreviousTransactionValueDate) * 100
)
select non empty( measures.Roshd) on columns,
non empty([DimDate].[Hierarchy].[Month]) on rows
from [Cube]
I want to only use named Set not another calculated member for this topic. any help?
Finally I found that my way is wrong. because sets works on dimensions not use for creating a calculated member.
Related
I have a fact table say WhsFactJob where we have CreatedTimeKey and InProgressTimeKey and I have a measure where Job Count.
I am trying to create a Calculated measure which will fetch me the job count whose CreatedTimeKey falls between 1(1:00 AM) and 2(2:00 AM) and InProgressTimeKey also falls with the same 1(1:00 AM) and 2(2:00 AM).
I tried to use SUM and Except, But it errors out saying Except has to use the same hierarchy.( CreatedTimeKey and InprogressTime Key are two seperate dimensions.
Any suggestions would help.
Here is the MDX example I am trying out.
WITH
MEMBER [Measures].[Sum] AS
SUM(
EXCEPT(
{[Created Time].[Hour].&[0]:[Created Time].[Hour].&[14]},
{[In Progress Time].[Hour].&[0]:[In Progress Time].[Hour].&[14]}
)
,[Measures].[Job Count]
)
SELECT
[Measures].[Sum] ON 0
FROM [Cube]
I'm not clear why you're using EXCEPT. How about this:
SUM
(
CROSSJOIN(
{[Created Time].[Hour].&[0]:[Created Time].[Hour].&[14]},
{[In Progress Time].[Hour].&[0]:[In Progress Time].[Hour].&[14]}
)
,[Measures].[Job Count]
)
I think you can get rid of the exception by cross-joining each set to members from the other set: not sure if the result of the query will be useful though - currently I'm unable to test the following:
The dimensionality of the two sets of tuples within the EXCEPT function should now be the same:
WITH
MEMBER [Measures].[Sum] AS
SUM(
EXCEPT(
{[Created Time].[Hour].&[0]:[Created Time].[Hour].&[14]}
*[In Progress Time].[Hour].[Hour].MEMBERS
, [Created Time].[Hour].[Hour].MEMBERS
*{[In Progress Time].[Hour].&[0]:[In Progress Time].[Hour].&[14]}
)
,[Measures].[Job Count]
)
SELECT
[Measures].[Sum] ON 0
FROM [Cube];
I am working with a system were items are created (postDate dimension) and closed (endDate dimension). The endDate column is always populated with the last time the item was seen. An item is considered closed in a certain time if its last seen date is before the date you are querying. Each row in the fact table has the item, postDate, endDate, locationID, and some other dimensions used for aggregations. What I am trying to accomplish is getting all items still active for a given time frame. For example I want to know all items posted in November 2008 or before November 2008 that has not yet closed. In SQL it would look something like:
SELECT C.geoCountyArea,TM.CalendarYear,COUNT(DISTINCT a.itemid)
FROM [dbo].[factTable] a
JOIN dbo.dimDate AS TM
ON TM.DateKey BETWEEN postDate AND endDate
JOIN [dbo].[dim_geography] C
ON A.geographyID=C.geographyID
WHERE C.geoCountyArea = '1204000057'
AND TM.CalendarYear = 2008 AND TM.MonthNumberOfYear = 11
GROUP BY C.geoCountyArea,TM.CalendarYear
ORDER BY C.geoCountyArea,TM.CalendarYear
This returns 27,715 which is expected. Now, in MDX this looks like:
WITH MEMBER Measures.[itemCount] AS
AGGREGATE(
{NULL:[PostDate].[Month Name].&[2008]&[11]} * {[EndDate].[Month Name].&[2008]&[11]:NULL},
[Measures].[Fact_itemCount]
)
SELECT NON EMPTY (
Measures.[itemCount]
) ON 0,
NON EMPTY (
{[PostDate].[Month Name].&[2008]&[11]},
{[Geography].[Geo County Area].&[1204000057]}
)ON 1
FROM [Cube];
This returns 27,717 - which is 2 more than the SQL version that could be due to items with no end Date posted. Now, the complication comes when I want to get more than one explicit time - for example item count for all months in 2008 or item count for all years. I looked up methods to link a given param to another one via roll playing dimensions and came across this link. I altered my script so it looks like:
WITH MEMBER Measures.[itemCount] AS
AGGREGATE(
{NULL:LINKMEMBER([DATE].[Calendar].CURRENTMEMBER
,[PostDate].[Calendar])}
* {LINKMEMBER([DATE].[Calendar].CURRENTMEMBER
, [EndDate].[Calendar]):NULL}
, [Measures].[Fact_itemCount]
)
SELECT {Measures.[jobCount]} ON 0,
NON EMPTY (
{[DATE].[Month Name].&[2008]&[11]},
{[Geography].[Geo County Area].&[1204000057]}
)ON 1
FROM [Cube];
This, however, returns only the items created in November 2008 - value of 14,884. If I add in other months I do get individual counts for each month but, again, these are just the items created in those months.
How do I get the "active" item count for a given month/year/quarter without having do explicitly declare the time values in the AGGREGATE?
Can you use NonEmpty?
WITH MEMBER Measures.[itemCount] AS
AGGREGATE(
{NULL:
NONEMPTY(
[PostDate].[Month Name].MEMBERS //<<AMEND TO EXACT STRUCTURE USED IN YOUR CUBE
,[DATE].[Calendar].CURRENTMEMBER
).ITEM(0).ITEM(0)}
* {NONEMPTY(
[EndDate].[Month Name].MEMBERS //<<AMEND TO EXACT STRUCTURE USED IN YOUR CUBE
,[DATE].[Calendar].CURRENTMEMBER
).ITEM(0).ITEM(0): NULL}
, [Measures].[Fact_itemCount]
)
...
This ended up being the solution that provided valid results (tested against SQL calls against the warehouse tables):
WITH MEMBER Measures.[itemCount] AS
AGGREGATE(
{NULL:LINKMEMBER([Post Date].[Calendar],
[Post Date].[Calendar])}
* {LINKMEMBER([Post Date].[Calendar],
[End Date].[Calendar]):NULL},
[Measures].[Fact_itemCount]
)
SELECT {Measures.[itemCount]} ON 0,
NON EMPTY (
{[Post Date].[Month Name].Children},
{[Geography].[Geo County Area].&[1204000057]}
)
FROM [Cube]
Not that I am doing LINKMEMBER against the post and end dates - not against the global Date measure.
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 am developing a query builder application that generates MDX and trying to get customer counts from a cube using the following, which works just fine:
WITH MEMBER MEASURES.X AS (
{ [Customer].[Gender].[Female]},
[Customer].[Customer].Children
).Count
SELECT Measures.X ON 0 FROM [Adventure Works]
However, if the user drags in a dimension that is not related to the customer like:
WITH MEMBER MEASURES.X AS (
{ [Customer].[Gender].[Female]},
{ [Employee].[Status].[Active], [Employee].[Status].[Inactive]},
[Customer].[Customer].Children
).Count
SELECT Measures.X ON 0 FROM [Adventure Works]
the count result obviously becomes incorrect.
Is there a way to determine whether a dimension is related to the customer so that I can exclude it from the generated MDX query?
This information can be retrieved from the cube through AMO. The Cube class contains all the cube metadata you'll need.
Solved the problem by using the Exists( Set_Expression1 , Set_Expression2 [, MeasureGroupName] ) function. No need to manually determine which dimensions are related. The Exists function filters out the unrelated tuples, leaving only the
{ [Customer].[Customer].Children, [Customer].[Gender].[Female]} set to do the count over.
Here is the MDX:
WITH MEMBER MEASURES.X AS Exists(
[Customer].[Customer].Children,
{[Customer].[Gender].[Female]}
*
{[Employee].[Status].[Active], [Employee].[Status].[Inactive]}
).Count
SELECT Measures.X ON 0 FROM [Adventure Works]
with member [Measures].[BoughtDispenser] as
Sum(Descendants([Customer].[Customer].CurrentMember, [Customer].[Customer]),
Iif(
(IsEmpty(([Item].[ItemNumber].&[011074], [Measures].[Sale Amount]))
And IsEmpty(([Item].[ItemNumber].&[011069], [Measures].[Sale Amount]))
)
Or IsEmpty([Measures].[Sale Amount]),
0 , 1
)
)
select
{[Measures].[Sale Amount]} on columns,
non empty filter([Customer].[Customer].children, [Measures].[BoughtDispenser])
* {[Item].[ItemNumber].members}
on rows
from [Sales]
where [EnteredDate].[Quarter].&[2010-01-01T00:00:00]
;
The object is to show all the items purchased by customers who also bought either of the two dispensers (011069 and 011074).
I based the calculated member on a query I found to do basket analysis. I feel like there should be a way to write it with the set {[Item].[ItemNumber].&[011074], [Item].[ItemNumber].&[011069]} instead of the two IsEmpty tests. Everything I've tried ended up having every Customer in the result.
My environment is SQL Server Analysis Services 2005.
Yes I can! It just required a slightly different approach to the calculated member:
with member [Measures].[BoughtDispenser] as
Sum(Descendants([Customer].[Customer].CurrentMember, [Customer].[Customer])
* {[Item].[ItemNumber].&[011069], [Item].[ItemNumber].&[011074]},
[Measures].[Quantity Shipped]
)
select
{[Measures].[Sale Amount]} on columns,
non empty filter([Customer].[Customer].children, [Measures].[BoughtDispenser])
* {[Item].[ItemNumber].members}
on rows
from [Sales]
where [EnteredDate].[Quarter].&[2010-01-01T00:00:00]
;