I have
Geography Dimension
-> Admin Hierarchy
-> Province level
-> District level
-> Facility level.
Now I want to find the geography data when province = 'BeiJing' and facility = 'test'. How should I do ?
I write MDX code like this:
SELECT
{} ON 0,
{[Geography.Admin].[BeiJing].[All Geography.Admin].[test]} ON 1
FROM [EIDCube]
but It doesn't work. How can I get all province/district/facility data as table when I set special province and facility ?
In AdvWrks the following throws an error
Query (4, 5) The Customer Geography hierarchy is used more than once
in the Crossjoin function.
This is thrown when I try to run the following:
SELECT
[Measures].[Internet Sales Amount] ON 0
,
[Customer].[Customer Geography].[Country]
*
[Customer].[Customer Geography].[State-Province] ON 1
FROM [Adventure Works];
The way around this is to use the attribute hierarchies which the levels of the [Customer Geography] user hierarchy is made up of, like this:
SELECT
[Measures].[Internet Sales Amount] ON 0
,
[Country].[Country]
*
[State-Province].[State-Province] ON 1
FROM [Adventure Works];
Now if I want Australia and Queensland I can cross-join a couple of single member sets:
SELECT
[Measures].[Internet Sales Amount] ON 0
,
{[Country].[Country].[Australia]}
*
{[State-Province].[State-Province].[Queensland]} ON 1
FROM [Adventure Works];
Results in this:
Edit
Applying the above to your structure you should be able to do something like this:
SELECT
{[Measures].[someMeasureInCube]} ON 0
,
{[Province].[Province].[BeiJing]}
* {[Facility].[Facility].[test]} ON 1
FROM [EIDCube];
Assuming your hierarchichal structure to be
Geography-->Geography.Admin-->Province-->District-->Facility
(dimension) (hierarchy) (level 1) (level 2) (level 3)
Here is the MDX to do it the long way(short way being directly feeding the values in query, which surprisingly didn't work)
select [Geography].[Geography.Admin].CHILDREN
having
[Geography].[Geography.Admin].currentmember.member_caption = "test" and
ancestors([Geography].[Geography.Admin].currentmember, 3).item(0).member_caption = "BeiJing"
on 1,
{} on 0
from EIDCube]
I think you can use this :
SELECT
{} ON 0,
([Geography].[Admin].[BeiJing],[Geography].[Admin].[Province].[District].[test]) ON 1
FROM [EIDCube]
Edit 1 : My previous answer was wrong.
So now I think the better solution is to create a new hierarchy [admin2] for the geography dimension composed of the level [Facility] only and to use this query.
SELECT
{} ON 0,
([Geography].[Admin].[BeiJing],[Geography].[Admin2].[Facility].[test]) ON 1
FROM [EIDCube]
Related
I need to merge the result 2 queries into one table. Queries are similar except one of WHERE conditions.
As far as I was able to find out while googling it is impossible to do as MDX have internal connections in database design.
I have tried to use this way: Merge 2 MDX queries
But it turns out that in 1 hour I get this error:
XML for Analysis parser: The XML for Analysis request timed out before it was completed.
I have tried to make new members like that:
member new_A AS
aggregate
(
K
,
A
)
And then
select { new_A, ...
select { A , B , C , D } on 0,
non empty { Y * Z } on 1
from X
where (except(K), L, M, N, P);
select { A , B , C , D } on 0,
non empty { Y * Z } on 1
from X
where (K, L, M, N, P);
What I need to get in the end is a table that contains values of elements A,B,C,D as columns for condition K only and for all except condition K just next to it. it can be either A, new_A, B, new_B, etc or A, B, C, D , new_A, new_B, etc.
P.S. database is extremely big and the faster it works the better :)
So i have tried to map your problem to AdventureWorks sample database.
In my problem i am trying report [internet Sales Amount] for some countries for a set of subcategories. Then I edit my query to report all subcategories except "Road Bikes" in main columns and for road bikes i use measures.RoadBikes.
Query 1
with member
measures.RoadBikes
as
( ([Product].[Subcategory].&[2],[Measures].[Internet Sales Amount]))
select
non empty
{
({[Customer].[Country].&[Australia],[Customer].[Country].&[Canada],[Customer].[Country].&[France],[Customer].[Country].&[United Kingdom],[Customer].[Country].&[United States]},
[Measures].[Internet Sales Amount]
),
({[Customer].[Country].&[Australia],[Customer].[Country].&[Canada],[Customer].[Country].&[France],[Customer].[Country].&[United Kingdom],[Customer].[Country].&[United States]},
measures.RoadBikes
)
}
on columns,
non empty
[Date].[Month of Year].[Month of Year]
on
rows
from
[Adventure Works]
where
({[Product].[Subcategory].&[31],[Product].[Subcategory].&[1],[Product].[Subcategory].&[2],[Product].[Subcategory].&[37],[Product].[Subcategory].&[3]})
Result
Edit the query
with member measures.UsRoadBikes as ([Product].[Subcategory].&[2],[Measures].[Internet Sales Amount])
select non empty
{({[Customer].[Country].&[Australia],[Customer].[Country].&[Canada],[Customer].[Country].&[France],[Customer].[Country].&[United Kingdom],[Customer].[Country].&[United States]},
[Measures].[Internet Sales Amount])}
on columns,
non empty
({[Product].[Subcategory].&[31],[Product].[Subcategory].&[1],[Product].[Subcategory].&[2],[Product].[Subcategory].&[37],[Product].[Subcategory].&[3]},
[Date].[Month of Year].[Month of Year]
) on rows
from [Adventure Works]
Result
Thanks everyone!
It was decided to run queries in parallel to speed up.
Return data to be populated into dataset and then Linq to be used to work with it.
I wanted to do the trend analysis between the dates. For an instance current date- 30 days
30-60 days and so on.Below is the snippet of comparable sql query but same I wanted to do in MDX.
SQL
SELECT
ROUND
(
(
(
(
SELECT
SUM(del_pri_impr)
FROM
reporting.so_sli_calc_val a,
reporting.user_group_tenant b,
reporting.salesorder c
WHERE
created_on BETWEEN DATE(now()-30) AND DATE(now())
)
-
(
SELECT
SUM(del_pri_impr)
FROM
reporting.so_sli_calc_val a,
reporting.user_group_tenant b,
reporting.salesorder c
WHERE
created_on BETWEEN DATE(now()-60) AND DATE(now()-30)
)
)
/
(
SELECT
SUM(del_pri_impr)
FROM
reporting.so_sli_calc_val a,
reporting.user_group_tenant b,
reporting.salesorder c
WHERE
created_on BETWEEN DATE(now()-60) AND DATE(now()-30)
) *100
)
,
0
) AS trend
MDX:
WITH
SET [~FILTER] AS
{[Created_Date.Created_Hir].[Created_On].[2014-04-01]:[Created_Date.Created_Hir].[Created_On].[2014-04-30]}
SET [~ROWS] AS
{[Sales Order Attributes SO.Sales_order].[Sales Order ID].Members}
SELECT
NON EMPTY {[Measures].[CONT_AMT_GROSS], [Measures].[CONT_AMT_NET]} ON COLUMNS,
NON EMPTY [~ROWS] ON ROWS
FROM [SALES_ORDER]
WHERE [~FILTER]
As of now I have hard coded the dates, that will come from parameters.
I am facing difficulty in creating the second set and how to do subtraction between two sets in MDX.
You already have the logic on how to obtain sets of date corresponding to "last 30 days from now" and "last 60 to last 30 days from now". So, I am going to skip that part.
NOTE - You would have to use the parameter values while building these sets.
What you want to do here is first find the values corresponding to these sets of dates and then perform operations on them.
You can proceed like this -
WITH
SET [~FILTER] AS
{[Created_Date.Created_Hir].[Created_On].[2014-04-01]:[Created_Date.Created_Hir].[Created_On].[2014-04-30]}
SET [~ROWS] AS
{[Sales Order Attributes SO.Sales_order].[Sales Order ID].Members}
SET [Last30Days] AS
...
SET [Last60ToLast30Days] AS
...
MEMBER [~Last30Days - Now] AS
Aggregate
(
[Last30Days],
[Measures].[SomeMeasure]
)
MEMBER [~Last60Days - Last30Days] AS
Aggregate
(
[Last60ToLast30Days],
[Measures].[SomeMeasure]
)
MEMBER [~Measure] AS
([~Last30Days - Now]-[~Last60Days - Last30Days] )/([~Last60Days - Last30Days] * 100), format_string = '#,##0'
SELECT
NON EMPTY {
[Measures].[CONT_AMT_GROSS],
[Measures].[CONT_AMT_NET],
[~Measure]
} ON COLUMNS,
NON EMPTY [~ROWS] ON ROWS
FROM [SALES_ORDER]
Format_String takes care of rounding.
Not sure if I totally agree with Sourav's answer as I think some form of aggregation will be needed; creating tuples with sets in them may raise an exception.
Here is a simple model, against AdvWrks, that is tested and will do a subtraction for you:
WITH
SET [Set1] AS
[Date].[Calendar].[Date].&[20060301]
:
[Date].[Calendar].[Date].&[20070308]
SET [Set2] AS
[Date].[Calendar].[Date].&[20070308]
:
[Date].[Calendar].[Date].&[20080315]
MEMBER [Date].[Calendar].[All].[Set1Agg] AS
aggregate([Set1])
MEMBER [Date].[Calendar].[All].[Set2Agg] AS
aggregate([Set2])
MEMBER [Date].[Calendar].[All].[x] AS
(
[Date].[Calendar].[All].[Set1Agg]
,[Measures].[Internet Sales Amount]
)
MEMBER [Date].[Calendar].[All].[y] AS
(
[Date].[Calendar].[All].[Set2Agg]
,[Measures].[Internet Sales Amount]
)
MEMBER [Date].[Calendar].[All].[x-y] AS
[Date].[Calendar].[All].[x] - [Date].[Calendar].[All].[y]
SELECT
{
[Date].[Calendar].[All].[x]
,[Date].[Calendar].[All].[y]
,[Date].[Calendar].[All].[x-y]
} ON 0
,[Product].[Category].[Category] ON 1
FROM [Adventure Works];
Reflecting against your code maybe something like the following:
WITH
SET [Set1] AS
[Created_Date.Created_Hir].[Created_On].[2014-04-01]
:
[Created_Date.Created_Hir].[Created_On].[2014-04-30]
SET [Set2] AS
[Created_Date.Created_Hir].[Created_On].[2014-03-01]
:
[Created_Date.Created_Hir].[Created_On].[2014-03-31]
MEMBER [Created_Date.Created_Hir].[All].[Set1Agg] AS
Aggregate([Set1])
MEMBER [Created_Date.Created_Hir].[All].[Set2Agg] AS
Aggregate([Set2])
MEMBER [Measures].[~Last30Days - Now] AS
(
[Created_Date.Created_Hir].[All].[Set1Agg]
,[Measures].[SomeMeasure]
)
MEMBER [Measures].[~Last60Days - Last30Days] AS
(
[Created_Date.Created_Hir].[All].[Set2Agg]
,[Measures].[SomeMeasure]
)
MEMBER [Measures].[~Measure] AS
([Measures].[~Last30Days - Now] - [Measures].[~Last60Days - Last30Days])
/
[Measures].[~Last60Days - Last30Days]
* 100
,format_string = '#,##0'
SET [~ROWS] AS
{
[Sales Order Attributes SO.Sales_order].[Sales Order ID].MEMBERS
}
SELECT
NON EMPTY
{
[Measures].[CONT_AMT_GROSS]
,[Measures].[CONT_AMT_NET]
,[Measures].[~Measure]
} ON COLUMNS
,NON EMPTY
[~ROWS] ON ROWS
FROM [SALES_ORDER]
WHERE
[~FILTER];
Let's say I have two simple dimensions:
Products - with id and name
Salesmen - with id and name
My fact table is named SALES and contains the ids of the abovementioned.
I need to produce a query that will show the names of salesmen who sold all of the given products.
This code solves the problem for two items X and Y:
SELECT
{} on 0,
EXISTS(
EXISTS(
{[Salesmen].[Name].MEMBERS},
{[Products].[Name].&[X]}
)
,{[Products].[Name].&[Y]}
)
ON 1
FROM [Test];
The other version is:
SELECT
{} on 0,
INTERSECT(
NONEMPTY(
{[Salesmen].[Name].MEMBERS}
,([Products].[Name].&[X])
)
,NONEMPTY(
{[Salesmen].[Name].MEMBERS}
,([Products].[Name].&[Y])
)
)
ON 1
FROM [Test];
However, this method becomes troublesome if the list of given products is large, for example - 100 random products..
Do you have a property member_key for the hierarchy [Products].[Name] ? We can test like this:
WITH
MEMBER [Measures].[Meas1] AS
[Products].[Name].CurrentMember.PROPERTIES("KEY ID")
MEMBER [Measures].[Meas2] AS
[Products].[Name].CurrentMember.MEMBER_Key
MEMBER [Measures].[Meas3] AS
[Products].[Name].CurrentMember.MEMBERvalue
select
{
[Measures].[Meas1]
,[Measures].[Meas2]
,[Measures].[Meas3]
} on COLUMNS,
[Products].[Name].MEMBERS on ROWS
FROM [Test];
Hopefully one of the custom measures gives you a value? I'll assume Meas2 is working (swap to a different one if Meas1 or Meas3 is returning numbers)
WITH
MEMBER [Measures].[Meas2] AS
[Products].[Name].CurrentMember.MEMBER_Key
SET [ProdsetA] AS
FILTER(
[Products].[Name].MEMBERS
,[Measures].[Meas2] <100
)
SET [ProdsetB] AS
FILTER(
[Products].[Name].MEMBERS
,[Measures].[Meas2] >500
)
SELECT
{} on 0,
INTERSECT(
NONEMPTY(
{[Salesmen].[Name].MEMBERS}
,[ProdsetA]
)
,NONEMPTY(
{[Salesmen].[Name].MEMBERS}
,[ProdsetB]
)
)
ON 1
FROM [Test];
... the >100 and <500 are important. These are the criteria for the filter function to use. The custom set [ProdsetA] will only contain Products that have MEMBER_Key that are <100 whereas the custom set [ProdsetB] will only contain Products that have MEMBER_Key that are >500. You need to use the member values presented to you by the first script to decide what values 100 and 500 should be in your cube context (...I don't know the key values in your cube so just used 100 and 500 as placeholders)
I'm using the following but i think there's probably a much simpler method of excluding the All members from the results?
WITH
SET [Non_All_Distributors] AS
{FILTER(
[Distributor Name].members,
(InStr(1, [Distributor Name].CurrentMember.NAME, "All") = 0)
)}
SET [Non_All_Countries] AS
{FILTER(
[Geography Country].members,
(InStr(1, [Geography Country].CurrentMember.NAME, "All") = 0)
)}
SELECT
NON EMPTY
[Dimension].[Hierarchy].DEFAULTMEMBER
ON COLUMNS,
NON EMPTY
[Non_All_Distributors]
*
[Non_All_Countries]
*
Tail([Date].[Date - Calendar Month].[Calendar Day].Members,60)
*
{
[Measures].[Revenue],
[Measures].[NumClients]
}
ON ROWS
FROM [OURCUBE]
Just use
SELECT
NON EMPTY
[Dimension].[Hierarchy].DEFAULTMEMBER
ON COLUMNS,
NON EMPTY
[dimension of Distributor Name].[Distributor Name].[Distributor Name].Members
*
[dimension of Geography Country].[Geography Country].[Geography Country].Members
*
Tail([Date].[Date - Calendar Month].[Calendar Day].Members,60)
*
{
[Measures].[Revenue],
[Measures].[NumClients]
}
ON ROWS
FROM [OURCUBE]
There is no need to define sets here. you can directly state the distributor and country members in the rows clause.
By repeating the attribute name, you restrict the attribute hierarchy - which you refer to by [dim].[attrib name] to the level below the All member, which happens to have the same name as the attribute again. An attribute hierarchy has two levels: level 0 contains the 'All' member and level 1 all the members of the attribute. (This is true only if you did not do special configurations like setting the attribute as non aggregateabable, but I assume the standard case, as you have All members in your hierarchies.
Apart from being more simple, this statement will run much faster, as Filter is a real performance killer in many cases.
I would use the Descendants function and the AFTER option as following; this way you get all the members of the hierarchy below the all member:
select
[Measures].[Amount] on 0,
Descendants([Customers].[Geography].[All], 1, AFTER ) on 1
from [Sales]
(edited: with a request working with MSAS Adv. Works : removed the distance param)
select
Measures].[Order Count] on 0,
Descendants( [Geography].[Geography].[All], , AFTER ) on 1
from [Adventure Works]
I have the following Problem:
Select
{
[Measures].[PerformanceTotalYtd]
} on columns,
Non Empty{
Except(([Desk].[DeskName].[Trade].Members,[Time].[Year-Month-Day].[Day].&[2012]&[1]&[10]),([Desk].[DeskName].[Trade].Members,[Time].[Year-Month-Day].[Day].&[2012]&[1]&[09]))
} on rows
from [Cube]
where ([Entity].[Entity].&[9], [Audience].[View].&[GOD])
It exists a Dimension with the Name Desk. This Dimension has a Hierarchy with the name DeskName. The lowest Level ist Trade.
Desk: -Total -Segment -BusinessArea -Department -4th Level Portfolio -Desk -Trade
With the Query showing below, i want to show all Trades, that have the Measure "PerformanceTotalYtd" != NULL on the Date of 2012/01/10 except the Trades with the Measure "PerformanceTotalYtd" != NULL on the Date of 2012/01/09 !
Example:
Trades with Measure PerformanceTotalYtd on the 2012/01/10:
ABC 12,99
DEF 3,22
GHI 55,60
Trades with Measure PerformanceTotalYtd on the 2012/01/09:
ABC 80,00
DEF 8,78
I want the following Result because the Trade "GHI" doesn't exists on the 2012/01/09 and is new:
GHI 55,60
My Query showing below have this result:
ABC 12,99
DEF 3,22
GHI 55,60
It doesn't delete the existing Trades from the 2012/01/09.
I have a Solution in SQL but want to make it in MDX:
SELECT DD.Code, Sum(PerformanceTotalYtd) as TOTAL
FROM [Reporting_DB].[Star].[Fact_PerformanceTotal] FIS
inner join Star.Dimension_Desk DD on FIS.DeskID = DD.DeskID
WHERE FIS.TimeID = 20120110 and FIS.EntityID = 9 AND DD.Code not in ( SELECT DD.Code
FROM [Reporting_DB_HRE].[Star].[Fact_PerformanceTotal] FIS inner join Star.Dimension_Desk DD on FIS.DeskID = DD.DeskID WHERE FIS.TimeID = 20120109 and FIS.EntityID = 9 group by DD.Code)group by DD.Code
Can anybody help me please? I can't find a solution.
Sorry for my bad english!
Alex
I have found a similar example in the Adventure Works cube:
The set {[Customer].[City].&[Bell Gardens]&[CA], [Customer].[City].&[Bellevue]&[WA], [Customer].[City].&[Bellflower]&[CA]} has 3 values for [Measures].[Internet Sales Amount] in [Date].[Calendar Year].&[2002], and only 2 values in [Date].[Calendar Year].&[2004]. So we need to show measure value for member in 2002 where measure value == null in 2004.
The next MDX query achieves the desired result:
with set S as '{[Customer].[City].&[Bell Gardens]&[CA], [Customer].[City].&[Bellevue]&[WA], [Customer].[City].&[Bellflower]&[CA]}'
select
[Measures].[Internet Sales Amount] on 0,
non empty { Filter(S, IsEmpty(([Date].[Calendar Year].&[2004], [Measures].[Internet Sales Amount]))) } on 1
from [Adventure Works]
where ([Date].[Calendar Year].&[2002])
I tried to modify your example accordingly, but can't test it. Here it is:
select
{ [Measures].[PerformanceTotalYtd] } on 0,
non empty { Filter([Desk].[DeskName].[Trade].Members, IsEmpty(([Time].[Year-Month-Day].[Day].&[2012]&[1]&[09], [Measures].[PerformanceTotalYtd]))) } on 1
from [Cube]
where ([Entity].[Entity].&[9], [Audience].[View].&[GOD], [Time].[Year-Month-Day].[Day].&[2012]&[1]&[10])
In short: use Filter instead of Except.
I have the Solution for my Problem. Following Query shows the same Result as the Query of Dmitry Polyanitsa! Have a nice Day guys!
with
set [Trades Today] as NonEmpty([Desk].[DeskName].[Trade].Members, ([Measures].[PerformanceTotalYtd], [Time].[Year-Month-Day].[Day].&[2012]&[1]&[10]))
set [Trades Yesterday] as NonEmpty([Desk].[DeskName].[Trade].Members, ([Measures].[PerformanceTotalYtd], [Time].[Year-Month-Day].[Day].&[2012]&[1]&[9]))
set [Trades Difference] as Except([Trades Today], [Trades Yesterday])
Select
{
[Measures].[PerformanceTotalYtd]
} on columns,
Non Empty{
[Trades Difference]
} on rows
from [Cube]
where ([Entity].[Entity].&[9], [Audience].[View].&[GOD])