dimension table has below attributes
sysID, birthdate,country of residence,ISindicator, defautlindicator,os indicator not related to each other .
i am trying to process the dimension but it is failing
thanks
Related
I have the following error :
" Errors in the OLAP storage engine: Rigid relationships between attributes cannot be changed during incremental processing of a dimension. The error occurred when processing attribute 'Month'.. Source attribute: 'Date'. Key column value(s) of the source attrbibute: '112234' ".
What happened :
I made insert yesterday with record '112234' in the source, after which I processed the dimension, but I realized I was wrong. I did an update in the source, changing '112234' to '112233', after which I tried to process the dimension again, but received the above error message.
I thought that was because of incremental issue. So I waited for today to do the insert with today's key, '112235', but at the dimesion processing I got the same error as before, even though the value is higher than the one from yesterday.
How can I get rid of '112234' and to get the dimension to take the latest value, '112235', and increment from there? --> I don't want to change the relationships.
I'm here again. I'm developing an example of tabular model on Analysis Services and I've an error that I'm not able to solve.
This is my tables diagram just now:
The relevant tables are MARCHAMOS, ARFABRI and DimFecha (the top ones). MARCHAMOS and ARFABRI are joined by 2 relationships (2 fields of MARCHAMOS could be paired with 1 field of ARFABRI (depends of the situation)).
Now I'm trying to get a measure with the following DAX query:
UnidadesFrescosCompradas:= countx(
calculatetable(
filter(
marchamos;
not isempty (relatedtable('ARFABRI'))
);
MID(MARCHAMOS[REGIS03]; 1; 1) = "1";
TIPOS_COCHINILLO[GRUPO]=0;
userelationship(MARCHAMOS[REGIS28];ARFABRI[ARFA01]);
userelationship(ARFABRI[ARFA06]; DimFecha[Fecha])
);
[regis01])
As you can see, I'm telling the system the relationships that it must use (one of them is from MARCHAMOS to ARFABRI and the other one is from ARFABRI to DimFecha). But I get this error:
If I remove the "userelationship(ARFABRI[ARFA06]; DimFecha[Fecha])" caluse of the filter, the error disappears, but the result is not correct.
I don't understand this, since both relationships are not over the same tables.
Any hint?
Thank's in advance
You can USERELATIONSHIP with both active and inactive relationships. It looks like you have an ambiguity in that you have two eligible relationships for MARCHAMOS and ARFABRI.
Since the ending point column for ARFABRI is the same in both relationships you get the error.
Can you delete the inactive relationship?
I have removed an attribute from a dimension (edited a view that feeds my dsv) because it is not wanted/needed anymore.
Now when I try to process that dimension, i get the following error;
OLE DB error: OLE DB or ODBC error: Invalid column name 'EngNation'.; 42S22.".
EngNation being the attribute i have deleted.
Why is it trying to process a column that doesn't exist anymore? I have refreshed the dsv and the column isn't there anymore. I've even gone through the xml-code but can't find a trace of the attribute anywhere. I just don't understand what else I have missed.
I've tried searching the web but have not been able to find an answer to my problem, any input much appreciated.
There is an update that fixes this:
https://support.microsoft.com/en-ca/help/2897265/fix-invalid-column-name-error-when-you-run-some-mdx-queries-against-ro
But if you are in a position where you cannot apply the update for whatever reason, you can see if you scenario matches ours and I will explain how I got around this error:
Three fact tables (views)
- Budget (derived from a view from an application)
- Actuals (derived from a view from an application)
- Forecast (derived from a view from an application)
Two write back tables for Forecast and Budget.
Two Dimensions
- Time
- Account Hierarchy
Three Measures:
- Actuals
- Budget
- Measure
Originally, I had three measures on each of the fact tables (views) that were Budget, Actuals, Forecast (think three views that are pretty much the exact same with three measures). When I made it so that only the actuals view had an actuals measure, the forecast view only had a forecast measure, and the budget view only had a budget measure, everything seemed to work.
The missing column error is very misleading as the column and relationship was fine.
I'm trying to add a new column to my SSAS cube. The column is a date field, and links to my DimDate table (a Date dimension). This date represents the project completion date.
However.... not all of the projects have a project completion date due to old projects not ever being assigned this value. And this is expected. We don't want to put bogus dates into the field just to get SSAS to work.
When processing the cube, it crashes with:
Errors in the OLAP storage engine: The attribute key cannot be found when
processing: Table: 'dbo_FactMyTable', Column: 'MyDate_id', Value: '0'.
The attribute is 'Date Id'.
I can't disable "missing values" for the entire project because in most cases, this really is an error. How can I disable missing values for this dimension?
Or is there a better way to handle missing dates/values like this?
Small correction - based on your question, you need to change Processing error handling for special Measure Group, not Dimension. You can do it for all dimensions linked to some measure group, but not to specific dimension.
You can process individual measure group with _Table: 'dbo_FactMyTable'_ first with necessary missing value settings, and then - process rest of your cube with default settings.
Main problem here - how to process rest of the cube. You might have sophisticated system which creates processing XMLA scripts dynamically based on data update knowledge (I do it with SSIS); in this case you would not ask this question. Suppose your environment is simpler - you update cube and would like to process it as a whole completely. In such scenario I would sudgest the following workflow:
Process Default all Dimensions (will do initial processing or in structure changes)
Process Update all Dimensions
Process Cube with Unprocess - invalidating it
Process your special measure group
Process Cube with Process Default
This will first update Dimensions, then - clear processing status flag from all measure groups in the Cube. After that you process your measure group with special flags; this set processing status for this MG. And then during Process Default on Cube - only unprocessed MGs will be covered, which excludes your special MG from processing scope.
The answer is a bit complicated, but this article did a great job of explaining it, including screen shots for the SSAS-challenged like me.
http://msbusinessintelligence.blogspot.com/2015/06/handling-null-dates-in-sql-server.html?m=1
I have a dimension with attribute AGE.
I have applied discretization on that attribute where the bucket count is 20.
Everything works fine when we have enough values for AGE column in the underlying database.
But recently we updated the table and none but one row has value in AGE column.
Now I am getting processing error saying there is not enough value to create the bucket.
Can I bypass this error and still process the cube? I want the cube not to give processing error even if we do not have enough data in the underlying table to create buckets.
Unfortunately, no. The only way is to re-tune DiscretizationMethod property to None manually.
I also tried changing directly in XML:
From Automatic to None:
But failed as expected: no changes were applied.