Since in MDX you can specify the member [all] to add the aggregation between all the members of the dimension, if I want to show the totals of a certain measure I can build a query like
SELECT {
[MyGroup].[MyDimension].[MyDimension].members,
[MyGroup].[MyDimension].[all]
} *
[Measures].[Quantity] on 0
FROM [MyDatabase]
Now I want to filter MyDimension for a bunch of values and show the total of the selected values, but of course if I generate the query
SELECT {
[MyGroup].[MyDimension].[MyDimension].&[MyValue1],
[MyGroup].[MyDimension].[MyDimension].&[MyValue2],
[MyGroup].[MyDimension].[all]
} *
[Measures].[Quantity] on 0
FROM [MyDatabase]
it shows the Quantity for MyValue1, MyValue2 and the total of all MyDimension members, not just the ones I selected.
I investigated a bit and came up to a solution that include the generation of a sub query to filter my values
SELECT {
[MyGroup].[MyDimension].[MyDimension].members, [MyGroup].[MyDimension].[all]
} * [Measures].[Quantity] ON 0
FROM (
SELECT {
[MyGroup].[MyDimension].[MyDimension].&[MyValue1],
[MyGroup].[MyDimension].[MyDimension].&[MyValue2]
} ON 0
FROM [MyDatabase]
)
Assuming this works, is there a simplier or more straight forward approach to achieve this?
I tried to use the SET statement to define my custom tuple sets but then I couldn't manage to show the total.
Keep in mind that in my example I kept things as easy as possible, but in real cases I could have multiple dimension on both rows and columns as well as multiple calculated measures defined with MEMBER statement.
Thanks!
What you have done is standard - it is the simple way!
One thing to bear in mind when using a sub-select is that it is not a full filter, in that the original All is still available. I think this is in connection with the query processing of the clauses in mdx - here is an example of what I mean:
WITH
MEMBER [Product].[Product Categories].[All].[All of the Products] AS
[Product].[Product Categories].[All]
SELECT
[Measures].[Internet Sales Amount] ON 0
,NON EMPTY
{
[Product].[Product Categories].[All] //X
,[Product].[Product Categories].[All].[All of the Products] //Y
,[Product].[Product Categories].[Category].MEMBERS
} ON 1
FROM
(
SELECT
{
[Product].[Product Categories].[Category].&[4]
,[Product].[Product Categories].[Category].&[1]
} ON 0
FROM [Adventure Works]
);
So line marked X will be the sum of categories 4 and 1 but line Y will sill refer to the whole of Adventure Works:
This behavior is useful although a little confusing when using All members in the WITH clause.
Related
Is it possible to add condition within the in clause of postgresql
for example
select ... where (t1.subject,t2.weight) in ((1,2),(2,3))
I want to check whether subject is 1 but weight can be >= 2 not just 2 and so on. So that condition would logically look somewhat like
select ... where (t1.subject,t2.weight) in ((1,>2),(2,>3))
No, this is not possible. You need to write
…
WHERE t1.subject = 1 AND t2.weight > 2
OR t1.subject = 2 AND t2.weight > 3;
You can select value of object using subquery. Simple just select query subject which are having weight greater than >=2.
select ... where (t1.subject,t2.weight) in (select subject FROM ... where weight >=2 ,select subject FROM ... where weight >=3 );
id datetime new_column datetime_rankx
1 12.01.2015 18:10:10 12.01.2015 18:10:10 1
2 03.12.2014 14:44:57 03.12.2014 14:44:57 1
2 21.11.2015 11:11:11 03.12.2014 14:44:57 2
3 01.01.2011 12:12:12 01.01.2011 12:12:12 1
3 02.02.2012 13:13:13 01.01.2011 12:12:12 2
3 03.03.2013 14:14:14 01.01.2011 12:12:12 3
I want to make new column, which will have minimum datetime value for each row in group by id.
How could I do it in Power BI desktop using DAX query?
Use this expression:
NewColumn =
CALCULATE(
MIN(
Table[datetime]),
FILTER(Table,Table[id]=EARLIER(Table[id])
)
)
In Power BI using a table with your data it will produce this:
UPDATE: Explanation and EARLIER function usage.
Basically, EARLIER function will give you access to values of different row context.
When you use CALCULATE function it creates a row context of the whole table, theoretically it iterates over every table row. The same happens when you use FILTER function it will iterate on the whole table and evaluate every row against the filter condition.
So far we have two row contexts, the row context created by CALCULATE and the row context created by FILTER. Note FILTER use the EARLIER to get access to the CALCULATE's row context. Having said that, in our case for every row in the outer (CALCULATE's row context) the FILTER returns a set of rows that correspond to the current id in the outer context.
If you have a programming background it could give you some sense. It is similar to a nested loop.
Hope this Python code points the main idea behind this:
outer_context = ['row1','row2','row3','row4']
inner_context = ['row1','row2','row3','row4']
for outer_row in outer_context:
for inner_row in inner_context:
if inner_row == outer_row: #this line is what the FILTER and EARLIER do
#Calculate the min datetime using the filtered rows
...
...
UPDATE 2: Adding a ranking column.
To get the desired rank you can use this expression:
RankColumn =
RANKX(
CALCULATETABLE(Table,ALLEXCEPT(Table,Table[id]))
,Table[datetime]
,Hoja1[datetime]
,1
)
This is the table with the rank column:
Let me know if this helps.
what mdx query logic could i implement for this example to get two rows in result set for hrid = 1 with 1/1/16 as min date(start) for first row where someattribut shows up on column with value 'A'
and 1/15/16 as min date(start) for second row where someattribute has value of 'B' and measure.whatevers has its aggregation for whatever data corresponds to that dimension row.
Im trying to just look at january 2016
everything ive tried i seem to get min date values of 1/1/1900 or both rows have value of 1/1/2016 or i get errors since i cant figure it out.
heres my mdx sample:
WITH MEMBER [Measures].[Start] as
(
-- min date that the combination of someattribute and hrid have certain
-- value withing the range of the where clause restriction of january 2016
SELECT {
[Measures].[Start]
, [Measures].[Whatevers]
} ON COLUMNS
, NON EMPTY {
[Agent].[HRID].children
* [Agent].[someAtribute].Members
} ON ROWS
FROM [RADM_REPORTING]
WHERE (
[Date].[Date View].[Month].&[201601]
)
this works, but it feels kind of like a hack or maybe it feels like its not robust, I am not familiar enough with mdx to be able to make that call.
WITH MEMBER [Measures].[Start] as
filter([Date].[Date View].[Month].&[201601].children,
[Measures].[Whatevers]).item(0).membervalue
Here is a potential direction that is more general:
WITH
MEMBER [Measures].[Start] AS
Min
(
(EXISTING
[Date].[Date].[Date].MEMBERS)
,IIF
(
[Measures].[Internet Sales Amount] = 0
,NULL
,[Date].[Date].CurrentMember.MemberValue
)
)
SELECT
NON EMPTY
{
[Measures].[Start]
,[Measures].[Internet Sales Amount]
} ON COLUMNS
,NON EMPTY
[Product].[Product Categories].[Product] ON ROWS
FROM [Adventure Works]
WHERE
[Date].[Calendar].[Calendar Year].&[2005];
It gives the following:
I am pretty new to SSAS, OLAP and MDX syntax.
So I have this MDX to query the cube by TSQL (by linked server to SSAS) and it works fine:
select * from openquery(GCUBE,
'SELECT NON EMPTY { [Measures].[Valore] } ON COLUMNS,
NON EMPTY {
( [Prodotti].[Top Marca].[Top Marca].ALLMEMBERS
* [Prodotti].[Top Codice].[Top Codice].ALLMEMBERS
* [Agenti].[Vw Agenti].[Vw Agenti].ALLMEMBERS
* [Calendario].[AnnoMese].[Mese].ALLMEMBERS
* [Prodotti].[Ordinamento].[Ordinamento].ALLMEMBERS
* [Prodotti].[Top].[Top].ALLMEMBERS )
}
DIMENSION PROPERTIES MEMBER_CAPTION
ON ROWS FROM ( SELECT ( { [Calendario].[Anno].&[2012] } )
ON COLUMNS FROM ( SELECT ( { [Agenti].[Vw Agenti].&[005] } )
ON COLUMNS FROM [Vendite])) WHERE ( [Calendario].[Anno].&[2012] )'
)
Well, the [Prodotti].[Top Marca] is a dimension based on a table with the 50 top selling brands and this MDX is filtered by a specific ID Agent [Vw Agenti] = 005.
The purpose of the query is to find out how the agent is selling the company's 50 top selling brands.
The query works fine but there is one brand not sold by this agent and I need to show the empty row.
The figure below shows the missing record relative to the position (rank) 31.
I understand the concept about NON EMPTY but I can't find the right syntax to also show the empty record.
How should I modify the MDX?
I tried to remove NON EMPTY but I get a generic error:
Cannot execute the query against OLE DB provider "MSOLAP" for linked server "GCUBE"
Do I need to change the dimension Top Marca in the cube?
Thanks in advance to anyone who can help me or give the right tips to solve this.
I'm not a specialist of SSAS/TSQL, but I would try a simple request first :
SELECT
[Measures].[Valore]ON COLUMNS,
NON EMPTY [Prodotti].[Top Marca].[Top Marca].ALLMEMBERS ON ROWS
FROM ( SELECT { [Calendario].[Anno].&[2012] } ON COLUMNS
FROM ( SELECT { [Agenti].[Vw Agenti].&[005] } ON COLUMNS
FROM [Vendite]
)
) '
Any way to run it without this TSQL stuff?
I don't know if this is possible or not, or if my limited knowledge of MDX is pushing me in the wrong direction...
The cube I'm dealing with has two different dimensions for dates, [Statement Dates] and [Premium Dates]. Further in the hierarchy of each looks like this:
[Statement Dates].[Statement Year].[2008]
[Payment Dates].[Payment Year].[2008]
For the business logic I'm implementing I need to do something like:
select
({ [Measures].[Commission] }) on columns,
({[Products].[Product Category]}) on rows
from [Cube]
where
(
IIF( [Products].[Product Category].CurrentMember.Name = "Some Category",
[Statement Dates].[Statement Year].[2008],
[Payment Dates].[Payment Year].[2008] )
)
So I need it to discriminate what dimension to use for filtering the year based on what product category is being used.
This parses ok and the query runs, but the numbers seem to suggest that the IIF statement is always returning false.
Because the WHERE clause gets evaluated first the .CurrentMember function in the IIF will only be seeing "All Product Cateogories". In which case the [Products].[Product Category].CurrentMember.Name will never be equal to "Some Category" as the only product category in context is "All Product Cateogories".
One possible work around would be to do a calculation like the following:
WITH MEMBER Measures.Commission2 as
SUM(
{[Products].[Product Category].[Product Category].Members}
, IIF( [Products].[Product Category].CurrentMember.Name = "Some Category"
, ([Statement Dates].[Statement Year].[2008],[Measures].[Commission])
, ([Payment Dates].[Payment Year].[2008].[Measures].[Commission]) )
)
select
({ [Measures].[Commission2] }) on columns
, ({[Products].[Product Category]}) on rows
from [Cube]
You could also do a scoped assignement in the calculation script in your cube to do this sort of thing.