I have the following calculated member which represents the quantity of "overstocked" products:
WITH
MEMBER [Measures].[Overstocked Items Count] AS
FILTER(
[Items].[Item No].CHILDREN,
[Measures].[Overstocked Qty] > 0
).COUNT
It works just fine for any linked to the measure group dimension except for the Items dimension itself and the reasons are obvious. Is there a way to create a calculated member that would respect the context it is evaluated in? So basically if this member is evaluated against an item group code I need items count by those groups, not the entire items set.
EXISTING is a useful keyword that can add the current context to your measure:
WITH
MEMBER [Measures].[Overstocked Items Count] AS
FILTER(
EXISTING([Items].[Item No].CHILDREN),
[Measures].[Overstocked Qty] > 0
).COUNT
EXISTING is very good when you want to know the members present from a different hierarchy within the same dimension. e.g. say you have U.S.A selected from the country hierarchy (in geography dimension) and you need to count state/county members from a stateCounty hierarchy that is also part of the geography dimension then EXISTING is the correct choice.
If you want to go across dimensions so say you have U.S.A selected and you'd like to count customer, from the customer dimension who are associated with the U.S.A then I don't think EXISTING will work - you'll need to explore either EXISTS or NONEMPTY.
Related
I have a hierarchy in a dimension in my cube, and a fact table that references that dimension. Let's call that a hierarchy of departments and the fact table contains billing targets set for each department (on a record-per-day basis if that's of any interest).
The data is aggregated as in a usual hierarchy in a multidimensional cube.
The problem is that the data in the fact table is not just limited to the "leaf" departments in the hierarchy tree, and so each node/department may or may not have an actual value for a billing target.
I need to have my measure returning the actual value for any node if there is a value, or the sum of the values of it's descendants (if they themselves have actual values, then ignore their descendants).
I can return the value at any given node by using the .DATAMEMBER property and add a condition to substitute the null (if that is the case) with the sum of descendants as so:
with member DirectD as (iif(([Department].[Departments].currentmember.datamember, [Measures].[Department Billing Target]) = null,
([Measures].[Department Billing Target]),
([Department].[Departments].currentmember.datamember, [Measures].[Department Billing Target])))
The problem is that I cannot ensure that the same logic applies to every node "down" the hierarchy.
The MembersWithData setting is set to NonLeafDataHidden in the dimension.
[Measures].[Department Billing Target] is a calculated member, so it looks like Aggregate is not an option.
As an example, I'd like to get the value of 3000 if I query the billing target for department A (image 1):
For department C on Image 2 I need to get 1400 (E, while having descendants, has an actual value which takes precedence over the sum of it's children).
Any help would be greatly appreciated.
The Hierarchy that you mention seems to be a parentchild hierarchy since you say "The problem is that the data in the fact table is not just limited to the "leaf" departments in the hierarchy tree". Based on this, the problem is that we need to solve is
1)Foreach member of you hierarchy we call the base attribute.
2)If the measure value for the base attribute is null we retuen the summed up value
3)If the measure value for the base attribute is not null then we retuen the indivisual members value. Below is the code piece, there can be some syntax issues but would explain the idea.
The below code is a similar example on adventure works(I did add FullName attribute in the employee dimension). In the picture on right is a parent child hierarchy's, base attribute. This picture show all the employee who had sales. On the left is the hierarchy, notice how the values change in the Test measure for people who are present on the right hand side. For example take a look at "Amy E. Alberts"
The code is
with member [Measures].test as
case when [Employee].[Employees].currentmember.name='All Employees'
then [Measures].[Reseller Sales Amount]
when (strtomember('[Employee].[Full Name].['+[Employee].[Employees].currentmember.name+']'),[Measures].[Reseller Sales Amount])=null
then [Measures].[Reseller Sales Amount]
else (strtomember('[Employee].[Full Name].['+[Employee].[Employees].currentmember.name+']'),[Measures].[Reseller Sales Amount])
end
select {[Measures].[Reseller Sales Amount],[Measures].test}
on columns,
[Employee].[Employees].members
on rows from [Adventure Works]
In the end, I have added the following solution that is working so far:
IIF(NOT ISEMPTY(([Department].[Departments].CURRENTMEMBER.DATABEMBER, [Measures].[Department Billing Target Canonical])),
([Department].[Departments].CURRENTMEMBER.DATABEMBER, [Measures].[Department Billing Target Canonical]),
IIF(ISEMPTY(SUM(descendants([Department].[Departments].CURRENTMEMBER, [Department].[Departments], AFTER), IIF(
ISEMPTY(([Department].[Departments].CURRENTMEMBER.parent.DATABEMBER, [Measures].[Department Billing Target Canonical])),
([Department].[Departments].CURRENTMEMBER.DATABEMBER, [Measures].[Department Billing Target Canonical]),
NULL))),
([Department].[Departments].CURRENTMEMBER.DATABEMBER, [Measures].[Department Billing Target Canonical]),
SUM(descendants([Department].[Departments].CURRENTMEMBER, [Department].[Departments], AFTER), IIF(
ISEMPTY(([Department].[Departments].CURRENTMEMBER.parent.DATABEMBER, [Measures].[Department Billing Target Canonical])),
([Department].[Departments].CURRENTMEMBER.DATABEMBER, [Measures].[Department Billing Target Canonical]),
NULL))))
Granted it may not be the prettiest solution (in fact I'm pretty sure it's one of the ugliest), but it works for me.
The gist of it is that the algorithm checks if the parent node of the current one has any data (currentmember.parent.datamember) and if so, substitutes the current member's value with NULL. All those values are piled up in a set, and the sum of it's "contents" is the resulting value. The outmost IIF is there to cover a sort of an edge case.
EDIT: There is also a feeling that this whole issue is just a matter of some SSAS setting that has to be changed. This setting continues to elude me.
I am trying to replicate the following sql statement into MDX so that I can create a calculated member in the cube using the base loaded members instead of having to calculate it outside the cube in the table and then loading it
SUM(CASE WHEN ((A.SALES_TYPE_CD = 1) AND (A.REG_SALES=0))
THEN A.WIN_SALES
ELSE 0
END) AS Z_SALES
I am currently loading SALES_TYPE_CD as a dimension and REG_SALES and WIN_SALES as measures.
I also have a few other dimensions in the cube but for simplicity, lets just say I have 2 other dimensions, LOCATION and ITEM
The dimension has LOCATION has 3 levels, "Region"->"District"->"Store", ordered from top to bottom level.
The dimension has ITEM has 3 levels, "CLASS"->"SUBCLASS"->"SKU", ordered from top to bottom level.
The dimension has SALES TYPE has 2 levels, "SALES_TYPE_GROUP"->"SALES_TYPE_CD", ordered from top to bottom level.
I know that I cannot create a simple calculated member in the cube which crossjoins the "SALES_TYPE" dimension with another dimension to get the answer I want.
I would think that it would be a more complicated MDX statement something like :
CREATE MEMBER CURRENTCUBE.[Measures].[Z_Sales]
AS 'sum(filter(crossjoin(leaves(), [Sales Type].[Sales Type].
[Sales_Type_CD].&[1]), [Measures].[REG_SALES]=0),[Measures].
[WIN_SALES])',
FORMAT_STRING = '#,#',
VISIBLE = 1 ;
But this does not seem to return the desired result.
What would be the proper MDX code to generate the desired result?
I did a bunch of testing with the data and I now know that there is no way I can get the right answer by using MDX alone in this scenario. Like "Greg" and "Tab" suggested, the only way would be to have reg sales as a dimension. Since this is a measure, that is out of the question because of the large number of possibilities for the value which has a data type of decimal (18,2)
Thanks for taking the time to answer the question.
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.
BACKGROUND: I've been using MDX for a bit but I am by no means an expert at it - looking for some performance help. I'm working on a set of "Number of Stores Authorized / In-Stock / Selling / Etc" calculated measures (MDX) in a SQL Server Analysis Services 2012 Cube. I had these calculations performing well originally, but discovered that they weren't aggregating across my product hierarchy the way I needed them to. The two hierarchies predominantly used in this report are Business -> Item and Division -> Store.
For example, in the original MDX calcs the Stores In-Stock measure would perform correctly at the "Item" level but wouldn't roll up a proper sum to the "Business" level above it. At the business level, we want to see the total number of store/product combinations in-stock, not a distinct or MAX value as it appeared to do originally.
ORIGINAL QUERY RESULTS: Here's an example of it NOT working correctly (imagine this is an Excel Pivot Table):
[FILTER: CURRENT WEEK DAYS]
[BUSINESS] [AUTH. STORES] [STORES IN-STOCK] [% OF STORES IN STOCK]
[+] Business One 2,416 2,392 99.01%
[-] Business Two 2,377 2,108 93.39%
-Item 1 2,242 2,094 99.43%
-Item 2 2,234 1,878 84.06%
-Item 3 2,377 2,108 88.68%
-Item N ... ... ...
FIXED QUERY RESULTS: After much trial and error, I switched to using a filtered count of a CROSSJOIN() of the two hierarchies using the DESCENDANTS() function, which yielded the correct numbers (below):
[FILTER: CURRENT WEEK DAYS]
[BUSINESS] [AUTH. STORES] [STORES IN-STOCK] [% OF STORES IN STOCK]
[+] Business One 215,644 149,301 93.90%
[-] Business Two 86,898 55,532 83.02%
-Item 1 2,242 2,094 99.43%
-Item 2 2,234 1,878 99.31%
-Item 3 2,377 2,108 99.11%
-Item N ... ... ...
QUERY THAT NEEDS HELP: Here is the "new" query that yields the results above:
CREATE MEMBER CURRENTCUBE.[Measures].[Num Stores In-Stock]
AS COUNT(
FILTER(
CROSSJOIN(
DESCENDANTS(
[Product].[Item].CURRENTMEMBER,
[Product].[Item].[UPC]
),
DESCENDANTS(
[Division].[Store].CURRENTMEMBER,
[Division].[Store].[Store ID]
)
),
[Measures].[Inventory Qty] > 0
)
),
FORMAT_STRING = "#,#",
NON_EMPTY_BEHAVIOR = { [Inventory Qty] },
This query syntax is used in a bunch of other "Number of Stores Selling / Out of Stock / Etc."-type calculated measures in the cube, with only a variation to the [Inventory Qty] condition at the bottom or by chaining additional conditions.
In its current condition, this query can take 2-3 minutes to run which is way too long for the audience of this reporting. Can anyone think of a way to reduce the query load or help me rewrite this to be more efficient?
Thank you!
UPDATE 2/24/2014: We solved this issue by bypassing a lot of the MDX involved and adding flag values to our named query in the DSV.
For example, instead of doing a filter command in the MDX code for "number of stores selling" - we simply added this to the fact table named query...
CASE WHEN [Sales Qty] > 0
THEN 1
ELSE NULL
END AS [Flag_Selling]
...then we simply aggregated these measures as LastNonEmpty in the cube. They roll up much faster than the full-on MDX queries.
It should be much faster to model your conditions into the cube, avoiding the slow Filter function:
If there are just a handful of conditions, add an attribute for each of them with two values, one for condition fulfilled, say "cond: yes", and one for condition not fulfilled, say "cond: no". You can define this in a view on the physical fact table, or in the DSV, or you can model it physically. These attributes can be added to the fact table directly, defining a dimension on the same table, or more cleanly as a separate dimension table referenced from the fact table. Then define your measure as
CREATE MEMBER CURRENTCUBE.[Measures].[Num Stores In-Stock]
AS COUNT(
CROSSJOIN(
DESCENDANTS(
[Product].[Item].CURRENTMEMBER,
[Product].[Item].[UPC]
),
DESCENDANTS(
[Division].[Store].CURRENTMEMBER,
[Division].[Store].[Store ID]
),
{ [Flag dim].[cond].[cond: yes] }
)
)
Possibly, you even could define the measure as a standard count measure of the fact table.
In case there are many conditions, it might make sense to add just a single attribute with one value for each condition as a many-to-many relationship. This will be slightly slower, but still faster than the Filter call.
I believe you can avoid the cross join as well as filter completely. Try using this:
CREATE MEMBER CURRENTCUBE.[Measures].[Num Stores In-Stock]
AS
CASE WHEN [Product].[Item Name].CURRENTMEMBER IS [Product].[Item Name].[All]
THEN
SUM(EXISTS([Product].[Item Name].[Item Name].MEMBERS,[Business].[Business Name].CURRENTMEMBER),
COUNT(
EXISTS(
[Division].[Store].[Store].MEMBERS,
(
[Business].[Business Name].CURRENTMEMBER,
[Product].[Item Name].CURRENTMEMBER
),
"Measure Group Name"
)
))
ELSE
COUNT(
EXISTS(
[Division].[Store].[Store].MEMBERS,
(
[Business].[Business Name].CURRENTMEMBER,
[Product].[Item Name].CURRENTMEMBER
),
"Measure Group Name"
)
)
END
I tried it using a dimension in my cube and using Area-Subsidiary hierarchy.
The case statement handles the situation of viewing data at Business level. Basically, the SUM() across all members of Item Names used in CASE statement calculates values for individual Item Names and then sums up all the values. I believe this is what you needed.
Say I have a measure, foo, in a cube, and I have a reporting requirement that users want to see the following measures in a report:
total foo
total foo excluding instances where foo > 10
total foo excluding instances where foo > 30
What is the best way to handle this?
In the past, I have added Named Calculations which return NULL if foo > 10 or just foo otherwise.
I feel like there has to be a way to accomplish this in MDX (something like Filter([Measures].[foo], [Measures].[foo] > 10)), but I can't for the life of me figure anything out.
Any ideas?
The trick is that you need to apply the filter on your set, not on your measure.
For example, using the usual Microsoft 'warehouse and sales' demo cube, the following MDX will display the sales for all the stores where sales were greater than $2000.
SELECT Filter([Store].[Stores].[Store].members, [Unit Sales] > 2000) ON COLUMNS,
[Unit Sales] ON ROWS
FROM [Warehouse and Sales]
I met similar problem when use saiku (backend with Mondrain), as I haven't found any clear solution of "add filter on measure", I added it here, and that may be useful for other guy.
In Saiku3.8, you could add filter on UI: "column"->"filter"->"custom", then you may see a Filter MDX Expression.
Let's suppose we want clicks in Ad greater than 1000, then add the following line there:
[Measures].[clicks] > 1000
Save and close, then that filter will be valid for find elem with clicks greater than 1000.
The MDX likes below (suppose dt as dimension and clicks as measure, we want to find dt with clicks more than 1000)
WITH
SET [~ROWS] AS
Filter({[Dt].[dt].[dt].Members}, ([Measures].[clicks] > 1000))
SELECT
NON EMPTY {[Measures].[clicks]} ON COLUMNS,
NON EMPTY [~ROWS] ON ROWS
FROM [OfflineData]
i think you have two choices:
1- Add column to your fact(or view on data source view that is based on fact table)like:
case when unit_Price>2000 then 1
else 0
end as Unit_Price_Uper_Or_Under_10
and add a fictitious Dimension based on this columns value.
and add named query for New Dimension(say Range_Dimension in datasourceview :
select 1 as range
union all
select 0 as range
and after taht you cant used this filter like other dimension and attribute.
SELECT [Store].[Stores].[Store].members ON COLUMNS,
[Unit Sales] ON ROWS
FROM [Warehouse and Sales]
WHERE [Test_Dimension].[Range].&[1]
the problem is for every range you must add When condition and only if the range is static this solution is a good solution.
and for dynamic range it's better to formulate the range (based on disceretizing method )
2- add dimension with granularity near fact table based on fact table
for example if we have fact table with primary key Sale_id.we can add
dimension based on fact table with only one column sale_Id and in dimension Usage tab
we can relate this new dimension and measure group with relation type Fact and
after that in mdx we can use something like :
filter([dim Sale].[Sale Id].[Sale Id].members,[Measures].[Unit Price]>2000)