I am using Performance Point Dashboard Designer 2013 and SharePoint Server 2013 for building dashboards. I am using SSAS2012 for Cube.
I have a scenario similar to the one illustrated by figure below. I am required to find Previous Non-Empty value for purpose of finding Trends.
Measure: [Quota]
Dimension: [Date].[Calendar Date].[Date]
The script ([Measures].[Quota], [Date].[Calendar Date].PrevMember) gives you a previous date. Lets say for date 27-Jan-13 whose Quota value is 87, it returns 26-Jan-13 which has null value. I want it to return 21-Jan-13 that has some Quota value. And for date 21-Jan-13, I want to return 15-Jan-13.
I wonder if this is possible.
Thanks,
Merin
After long searches and hits & trials and so on, I think I invented a solution of my own for myself.
Following is the script for my Calculated Member.
(
[Quota],
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
).Item(0)
)
Explanation
The number 15 means it will look for non-empty measures up to 15 siblings.
Now we know up to how many siblings to traverse back, in this case 15.
Lets find 15 previous siblings (both empty and non-empty) excluding current member.
(LastPeriods(15, [Date].[Calendar Date].PrevMember)
Since it will yield both empty and non-empty members, lets filter out empty members in terms of measure [Quota]. If we don't specify measure here, it will use default measure whatever it is and we may not get desired result.
Nonempty(LastPeriods(15, [Date].[Calendar Date].PrevMember),[Quota])
We may have several members in the output. And we will choose the last one.
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
)
So far, the script above gives previous non-empty member. Now we want to implement this member for our measure [Quota].
Hence we get the script below ready to create a Calculated Member.
(
[Quota],
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
).Item(0)
)
You can use recursion to define this.
The following query delivers something similar for the Adventure Works cube:
WITH member [Measures].[Prev non empty] AS
IIf(IsEmpty(([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Internet Sales Amount])),
([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Prev non empty]),
([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Internet Sales Amount])
), format_String = '$#,##0.00'
SELECT {[Measures].[Internet Sales Amount], [Measures].[Prev non empty]}
ON COLUMNS,
non empty
Descendants([Date].[Calendar].[Month].&[2007]&[12], [Date].[Calendar].[Date])
ON ROWS
FROM [Adventure Works]
WHERE [Customer].[Customer].&[12650]
You would have to replace the name of the date hierarchy, as well as the measure name from Internet Sales Amount to Quota in the recursive definition of the measure Prev non empty.
Related
Here are two simple queries which shows data on month level filtered by dates.
In the first query I am using Month level of "Date.Calendar" user hierarchy.
SELECT
NON EMPTY { [Measures].[Internet Sales Amount] } ON 0,
NON EMPTY { [Date].[Calendar].[Month].&[2013]&[1] } ON 1
FROM [Adventure Works]
WHERE {[Date].[Date].&[20130105]:[Date].[Date].&[20130106]}
And recieved - January 2013 -> $857,689.91
Results
In the second query I am using "Date.Month of Year" attribute hierarchy.
SELECT
NON EMPTY { [Measures].[Internet Sales Amount]} ON 0,
NON EMPTY { [Date].[Month of Year].&[1] } ON 1
FROM [Adventure Works]
WHERE { [Date].[Date].&[20130105] : [Date].[Date].&[20130106] }
And received - January -> $54,468.46
Results
I can not figure out why these two queries show different results. If the same dimension is used and data are filtered/sliced on the lovest possible level.
Here are values for each of these dates.
SELECT
NON EMPTY { [Measures].[Internet Sales Amount]} ON 0,
NON EMPTY { [Date].[Calendar].[Date] } ON 1
FROM [Adventure Works]
WHERE { [Date].[Date].&[20130105] : [Date].[Date].&[20130106] }
January 5, 2013 $32,681.44
January 6, 2013 $21,787.02
Result
Total value for these two dates is equal with the second querie's result - $54,468.46
I understand that in the first query it is user hierarchy and the second query it is attribute hierarchy from the Date dimension but I can not figure out which rule(s) tells to calculate these values differently.
If someone could explain this logic behind - it would be very helpful. Any link to some resource which explains this logic also could help.
BTW: I have created simple cube with simple Date dimension which consists just of attribute hierrarchies (date, month, year) and it still works like in the first query so it is not clear why it behaves like that.
I explored the reason for this behavior, and I think I have figured out the reason. The explanation below is based on the book SQL SERVER 2008 MDX Step by Step pages 51-58(especially Avoiding Reference Conflicts).
Your problem is a typical Reference Conflict problem.In MDX a hierarchy cannot be used more than once in a given tuple, but if you are using a USER Hierarchy and its under lying Attribute Hierarchy, you essentially by-pass this check. This is what happened in your query
In your first query you are using the User Hierarchy
[Date].[Calendar].[Month].&[2013]&1
In MDX a User Hierarchy is translated to Attribute Hierarchies. In your first query
SELECT
NON EMPTY { [Measures].[Internet Sales Amount] } ON 0,
NON EMPTY { [Date].[Calendar].[Month].&[2013]&1 } ON 1
FROM [Adventure Works] WHERE
{[Date].[Date].&[20130105]:[Date].[Date].&[20130106]}
you are using a User Hierarchy "[Date].[Calendar].[Month].&[2013]&1", which in its last level has "[Date].[Date]". Then in the where clause you use the same "[Date].[Date]" Attribute Hierarchy to filter. Since in the USER Hierarchy you have not used the leaf level, hence you have made a partial address, therefore the members and its ancestors are resolved. All the descendants are ignored in translation. Take a look at the below query(This is based on your first query,I have purposely removed your where clause).
with member [Measures].[CalendarYear] as [Date].[Calendar Year].currentmember.name
member [Measures].[CalendarSemester] as [Date].[Calendar Semester of Year].currentmember.name
member [Measures].[CalendarQuater] as [Date].[Calendar Quarter of Year].currentmember.name
member [Measures].[CalendarMonth] as [Date].[Month of Year].currentmember.name
member [Measures].[CalendarDate] as [Date].[Date].currentmember.name
SELECT
NON EMPTY { [Measures].[Internet Sales Amount] ,[Measures].[CalendarYear],[Measures].[CalendarSemester],[Measures].[CalendarQuater],[Measures].[CalendarMonth],[Measures].[CalendarDate]} ON 0,
NON EMPTY { [Date].[Calendar].[Month].&[2013]&[1] } ON 1
FROM [Adventure Works]
Result.
Notice that Calendar year, Semester and quarter all are showing non-default values. But we never used them. This shows that translation of User Hierarchy is done into underlying Attribute Hierarchies. Now take a look at Calendar, it is still showing "All Period". Since it was ignored.
Now if you add your where clause back, the Date still shows "All Period", there are two reasons
1) Because it was ignored in User Hierarchy translation ,
2)You used a range in where. If you replace your row axis tuple with your where tuple it will still show "All Period" as a range is based. However while resolving it will take just two dates.
Based on this while resolving your query, it had two translation for Date attribute hierarchy, one said to ignore it based on User Hierarchy, the other provided a range. This is where due to conflict the result is in-correct.
Now lets consider the query you gave me in your comment earlier
with member [Measures].[CalendarYear] as [Date].[Calendar Year].currentmember.name
member [Measures].[CalendarSemester] as [Date].[Calendar Semester of Year].currentmember.name
member [Measures].[CalendarQuater] as [Date].[Calendar Quarter of Year].currentmember.name
member [Measures].[CalendarMonth] as [Date].[Month of Year].currentmember.name
member [Measures].[CalendarDate] as [Date].[Date].currentmember.name
SELECT
NON EMPTY { [Measures].[Internet Sales Amount] ,[Measures].[CalendarYear],[Measures].[CalendarSemester],[Measures].[CalendarQuater],[Measures].[CalendarMonth],[Measures].[CalendarDate]} ON 0,
NON EMPTY { [Date].[Calendar].[Month].&[2013]&[1] } ON 1
FROM [Adventure Works]
WHERE {[Date].[Date].&[20130105]}
Result:
Notice that this time the resolution of a single member, was used instead of the User hierarchy resolution. Now this behavior might be due to the fact that one translation is giving "All Period" and the next is giving a member, hence the member won.
To further confirm this, I made a change to my AdventureWorks sample. The Date attribute hierarchy is based on "Simple Date" column. I exposed "Simple Date" as a separate attribute and processed my cube.
Take a look at the "Simple Date" query and results.
with member [Measures].[CalendarYear] as [Date].[Calendar Year].currentmember.name
member [Measures].[CalendarSemester] as [Date].[Calendar Semester of Year].currentmember.name
member [Measures].[CalendarQuater] as [Date].[Calendar Quarter of Year].currentmember.name
member [Measures].[CalendarMonth] as [Date].[Month of Year].currentmember.name
member [Measures].[CalendarDate] as [Date].[Date].currentmember.name
SELECT
NON EMPTY { [Measures].[Internet Sales Amount] ,[Measures].[CalendarYear],[Measures].[CalendarSemester],[Measures].[CalendarQuater],[Measures].[CalendarMonth],[Measures].[CalendarDate]} ON 0,
NON EMPTY { [Date].[Calendar].[Month].&[2013]&[1] } ON 1
FROM [Adventure Works]
WHERE
--{[Date].[Date].&[20130105]}
{[Date].[Simple Date].&[20130105]:[Date].[Simple Date].&[20130106]}
Results:
I am trying to learn MDX. I am an experienced SQL Developer.
I am trying to find an example of an MDX query that has more than two dimensions. Every single webpage that talks about MDX provides simple two dimensional examples link this:
select
{[Measures].[Sales Amount]} on columns,
Customer.fullname.members on rows
from [Adventure Works DW2012]
I am looking for examples that use the following aliases: PAGES (third dimension?), section (forth dimension?) and Chapter (fifth dimension?). I have tried this but I do not think it is correct:
select
{[Measures].[Sales Amount]} on columns,
Customer.fullname.members on rows,
customer.Location.[Customer Geography] as pages
from [Adventure Works DW2012]
I am trying to get this output using an MDX query (this is from AdventureWorks DW2012):
That's not a 3-dimensional resultset in your screenshot, unless there's something cropped from it.
Something like
SELECT [Geography].[Country].Members ON 0,
[Customer].[CustomerName].Members ON 1
FROM [whatever the cube is called]
WHERE [Measures].[Sales Amount]
(dimension/hierarchy/level names may not be exactly right)
would give a resultset like the one in your message.
The beyond 2nd-dimension dimensions and dimension names are not used in any client tool that I know. (Others may know different). They seem to be there in MDX so that MDX can hand >2-dimensional resultsets to clients that can handle them (e.g. an MDX subquery handing its results to the main query).
An often-used trick in MDX is to get the members of two dimensions onto one axis by cross-joining:
SELECT
{[Date].[Calendar Date].[Calendar Year].Members * [Geography].[Country].Members} ON 0,
[something else] ON 1
FROM [Cube]
How about the following - it does not send more than two dimensions back to a flat screen but it uses quite a few dimensions explicitly:
SELECT
[Measures].[Sales Amount] ON O,
[Customer].[fullname].MEMBERS ON 1
FROM
(
SELECT
[Date].[Calendar Month].[Calendar Month].&[February-2012] ON 0,
[Geography].[Country].[Country].&[Canada] ON 1,
[Product].[Product].&[Red Bike] ON 2,
[Customer].[Customer].&[foo bar] ON 3
FROM [Adventure Works DW2012]
)
I've made up the dimension | hierarchy | member combinations as I do not have access to the cube.
Also if we consider implicit dimensions then take the following:
SELECT
[Customer].[Location].[Customer Geography] ON 0,
[Customer].[fullname].[fullname].&[Aaron Flores] ON 1
FROM [Adventure Works DW2012]
WHERE
(
[Measures].[Sales Amount]
);
On the slicer I've used braces (..) which indicate a tuple, but this is actually shorthand for the following:
SELECT
[Customer].[Location].[Customer Geography] ON 0,
[Customer].[fullname].[fullname].&[Aaron Flores] ON 1
FROM [Adventure Works DW2012]
WHERE
(
[Measures].[Sales Amount]
,[Date].[Calendar Month].[Calendar Month].[All],
,[Geography].[Country].[Country].[All],
,[Product].[Product].[All]
,...
,...
....
);
The All member from every dimension in the cube could be included in this slicer without affecting the result.
So the whole nature of mdx is multi-dimensional - yes you do not get more than a 2 dimensional table returned to your screen but the way you get to that cellset could well involve many dimensions.
The following script gives exactly the result I want.
It feels like a hack as I've added the custom members VALUE and VALUE_MTD onto the hierarchy [Customer].[Country]. I've chosen this hierarchy arbitrarily - just not used [Measures] or [Date].[Calendar] as they are already in use.
Is there a more standard approach to returning exactly the same set of cells?
WITH
MEMBER [Customer].[Country].[VALUE] AS
Aggregate([Customer].[Country].[(All)].MEMBERS)
MEMBER [Customer].[Country].[VALUE_MTD] AS
Aggregate
(
PeriodsToDate
(
[Date].[Calendar].[Month]
,[Date].[Calendar].CurrentMember
)
,[Customer].[Country].[VALUE]
)
SELECT
{
[Customer].[Country].[VALUE]
,[Customer].[Country].[VALUE_MTD]
} ON 0
,NON EMPTY
{
[Measures].[Internet Sales Amount]
,[Measures].[Internet Order Quantity]
}
*
Descendants
(
{
[Date].[Calendar].[Month].&[2007]&[12]
:
[Date].[Calendar].[Month].&[2008]&[01]
}
,[Date].[Calendar].[Date]
) ON 1
FROM [Adventure Works];
The standard approach is called utility dimension. If you Google this term, you will find several descriptions of this approach. A "utility dimension" is one which does not reference any data, but is just added to the cube for the purpose of being able to cross join them with all other dimensions for calculations. You can have one or more of them.
Thus, in most cases, physically there is nothing in the dimension. It is just used for calculated members. (Depending on the implementation, you may have the attribute members defined physically, if you want to have some properties for them. But then, only the default member is referenced in the star schema from the fact tables. The attribute member values are then overwritten in the calculation script.)
Typical applications for this are time calculations like YTD, MTD, MAT (Moving Annual Total, i. e. a full year of data ending in the selected date), or comparisons like growth vs. a previous period.
The custom measure in the following is taken from the book MDX Cookbook (Tomislav Piasevoli):
WITH
MEMBER [Internet Sales PP] AS
Sum
(
Generate
(
{
[Date].[Calendar].[Date].&[20080105]
:
[Date].[Calendar].[Date].&[20080125]
}
,{
ParallelPeriod
(
[Date].[Calendar].[Calendar Year]
,1
,[Date].[Calendar].CurrentMember.Item(0)
)
}
)
,[Measures].[Internet Sales Amount]
)
SELECT
{
[Measures].[Internet Sales Amount]
,[Internet Sales PP]
} ON 0
,[Product].[Color].MEMBERS ON 1
FROM [Adventure Works];
What purpose does the item(0) serve?
My understanding, which is probably wrong is
<set>.item(0) gives us first tuple in set
<tuple>.item(0) gives us first member in tuple
So what is the point of <member>.item(0)?
Refer this excellent article on the topic.
To sum it up, when we are doing a .ITEM(0) on a member, that member is implicitly converted to a tuple. So, .ITEM(0) does not really serve any purpose other than returning the member itself.
I would assume this is a typo or a copy paste error. At least in the official Microsoft MDX reference, there are only the two Item() versions that you mention.
And this does not cause an error, as there are some implicit type conversions:
If you have a member and need a tuple for the current expression, AS implicitly builds a one-member tuple from the member. Which is what takes place here presumably, when applying Item(0) to a member.
If you have a one member tuple and need a member for the current expression, AS implicitly applies Item(0).
There are similar implicit conversions from tuple and level to set, from tuple to scalar value, from dimension to hierarchy, and from hierarchy to member.
I'm trying to write a query to give me the total number of users for each customer per day.
Here is what I have so far, which for each customer/day combination is giving the total number of user dimension entries without splitting them up by customer/day.
WITH MEMBER [Measures].[MyUserCount]
AS COUNT(Descendants([User].CurrentMember, [User].[User Name]), INCLUDEEMPTY)
SELECT
NON EMPTY CrossJoin([Date].[Date].Members, [Customer].[Customer Name].Members) ON ROWS,
{[Measures].[MyUserCount]} on COLUMNS
FROM
[Users]
The problem with your calculated member is that [User].CurrentMember is set to the All member for every row tuple, and thus the count is the total. What you need is a way for the [Customer].CurrentMember and [Date].CurrentMember to effectively filter the [User] dimension.
You need to use a measure that makes sense, i.e. that will have a non-empty value for meaningful joins of the dimension members that you're interested in.
To find this out, you could start by running a query like this:
SELECT
NON EMPTY CrossJoin(
[User].[User Name].Members,
[Measures].[Some measuse]
) ON COLUMNS,
NON EMPTY CrossJoin(
[Date].[Date].Members,
[Customer].[Customer Name].Members
) ON ROWS
FROM [Project]
You would have selected Some measure adequately. The results of that query will be a lot of empty cells, but in a given row, the columns that do have a value correspond to the Users that are related to a given Customer x Date tuple (on the row). You want to count those columns for every row. COUNT and FILTER are what you need, then the query with the calculated member will be
WITH MEMBER [Measures].[User count] AS
COUNT(
FILTER(
[User].[User Name].Members,
NOT ISEMPTY([Measures].[Some measure])
)
)
SELECT
NON EMPTY {[Measures].[User count]} ON COLUMNS,
NON EMPTY CrossJoin(
[Date].[Date].Members,
[Customer].[Customer Name].Members
) ON ROWS
FROM [Users]
I am assuming a fair bit here, but with some experimentation you should be able to work it out.