Why AVG function perform the SUM? - sum

I would to execute a query with a calculated member which returns the AVG (of the measure) of the Coil belonging to a particular LINESPEED.
The query is:
With
Member [Measures].[Avg1] As
AVG(
([LINESPEED].currentmember,
[GRUPPO].[Coil].currentmember)
,
[Measures].[KPI1]
)
SELECT [Measures].[Avg1] on 0,
non empty {[LINESPEED].children} On 1
from[HDGL]
But the AVG function compute exactly the sum of the KPIs of the coil related to a particular LINESPEED!!
Why?

Your formula is using a single tuple, so AVG() is equivalent to SUM() :
AVG( ([LINESPEED].currentmember, [GRUPPO].[Coil].currentmember), ...)

Related

MDX aggregate out a dimension

I'm trying to compute outcome frequencies, i.e., count divided by total.
I can't work out how to get a total in MDX.
Data looks like this.
The fact is just a 1 so their sum is the number of experiments with the given outcome.
It's easy in SQL
SELECT Session, Outcome, fi / N AS p
FROM (
SELECT Session, Outcome, CAST(COUNT(*) AS float) AS fi, CAST(SUM(COUNT(*)) OVER (PARTITION BY Session) AS float) AS N GROUP BY Session, Outcome
) T
Is it possible in MDX? If so: how?
I've tried these:
CREATE MEMBER CURRENTCUBE.Measures.Experiments AS SUM([Outcomes] , Measures.[Actual Outcome]);
CREATE MEMBER CURRENTCUBE.Measures.ExperimentsA AS SUM([Outcomes].[(All)] , Measures.[Actual Outcome]);
CREATE MEMBER CURRENTCUBE.Measures.ExperimentsAM AS SUM([Outcomes].AllMembers , Measures.[Actual Outcome]);
The first and third just give (null) and the second is just the same as the existing measure -- which makes no sense.
CREATE MEMBER CURRENTCUBE.[Measures].[Experiments]
AS
SUM([Outcomes].[All], [Measures].[Actual Outcomes])
;
So: what is the difference between [All] and [(All)]?

MDX: Only except in calculated member

Is it not possible to just have one except clause in a calculated member? (Without using aggregate)
Like this:
MEMBER [Agency].[AgencyName].[Trade] AS (
EXCEPT([Agency].[AgencyName].[All].children, [Agency].[AgencyName].&[Direct Business])
)
In case of sum aggregation go for:
([Agancy].[AgancyName].[All],[Measures].[MyMeasure]) - ([Agancy].[AgancyName].&[Direct Business], [Measures].[MyMeasure])

DAX formula for - MAX of COUNT

I have the below dataset:
using the measure:
BalanceCount := COUNT(Balances[Balance])
which gives me the result:
However, I want the Grand Total to show the maximum amount of the BalanceCount, which is 2.
NewMeasure:=
MAXX(
SUMMARIZE(
FactTable
,FactTable[Account]
,FactTable[MonthEnd]
)
,[BalanceCount]
)
SUMMARIZE() groups by the columns specified, and MAXX() iterates through the table specified, returning the maximum of the expression in the second argument evaluated for each row in its input table.
Since the filter context will limit the rows of the fact table, we'll only have the appropriate subsets in each column/row grand total.
I found a solution that works for this particular case. It will not work if columns other than Account and MonthEnd are included in the filter context.
MaxBalanceCount:=
MAXX ( SUMMARIZE (
Balances,
Balances[Account],
Balances[MonthEnd]
),
CALCULATE ( COUNTROWS ( Balances ) )
)

Calculating percentile values in SSAS

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]
)

MDX - calculated member with unrelated dimension

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].