The Attribute Key Cannot Be Found When Trying To Process Mining Structure
Oct 29, 2007
Hi,
I know, this is a common OLAP Error, but In fact I'm having trouble with this while trying to process a DM Mining Structure.
I'm currently working on a website that gets data from its users and analyzes it using SSAS. The thing is each time we add a new "analysis criterium" (sorry I'm trying to translate our french BI language in English...), we have to build a new mining structure, which needs data about users who have actually answered the question associated with this criterium. Some times, there are thousands, and some other only dozens, which is the case for the structure I'm having trouble with.
I got only 2 hundred tuples in the learning set. So lots of the common criteria weren't filled: I removed them using a stored procedure before feeding the structure, so that I got no column with only "null" values.
Of course, I know that 200 learning cases is really not enough to build an accurate model, but the purpose was just a proof of concept for machine driven Mining Structure building, and that was supposed to work even with so few cases.
When I process the MS, it fires: (Sorry it's in french, translation follows)
Erreurs dans le moteur de stockage OLAP : La clé d'attribut est introuvable : Table : _x0032_0_EtudeIphone_Apprentissage, Colonne : EtudeIphone, Valeur : le nouvel iPhone (téléphone tactile et musical dApple). Erreurs dans le moteur de stockage OLAP : La clé d'attribut a été convertie en un membre inconnu parce que cette dernière est introuvable. Attribut Id de la dimension : 20_EtudeIPhone ~MC-Id de la base de données : ClassificationVDCE, Enregistrement : 2.
Badly translated it says "Errors in OLAP Storage Engine: Attribute Key not found Table:<StrangeTable> Column <MyPredictableColumn> Value <OneOfTheInterestingValues>
Errors in OLAP Storage Engine: Attribute key not found: converted to an unknown member. Attribute Id from dimension..."
Why? Too few cases? I have structures based on the same template but associated with other criteria and they work perfectly.
I'm ready to answer any question, and give any detail.
Thanks in advance.
I posted a related thread before about this error below when I process a dimension. And seems that the solution by using "ClearCache" can not fingure out the issue when I want to process a mining structure...... .
OLE DB error: OLE DB or ODBC error: There is not enough procedure cache to run this procedure, trigger, or SQL batch. Retry later, or ask your SA to reconfigure SQL Server with more procedure cache. ; Sort failed because there is insufficient procedure cache for the configured number of sort buffers. Please retry the query after configuring lesser number of sort buffers.
Could someone please give me some suggestions? Your help will be very appreciated:-)
I would like to develop an application that can create Data Mining structures and a mining model in SQL Server 2005 with VB.NET. I tried the code from book Data Mining with SQL server 2005 in chapter 14 but did not work. Any good idea?
Thank you very much for your help. The errors that I can see in the code that you gave in your answer are the following and they are more or less the same as I had previously
I tried the code but initially I have encounter the following problems.
1. In any line that have the declaration As Server, As Database like in Public Function CreateDatabase(ByVal srv As Server, ByVal databaseName As String) As Database gives me the problem that type Database is not declared the same type Server is not declared and it does not give me any option.
2. In addition to that for As DataSource, As RelationalDataSource, As RelationalDataSourceView, As ScalarMiningStructureColumn, As DataSourceViewBinding, gives me the problem that type is not declared.
3. Finally in mc = New MiningModelColumn("Yearly income", Utils.GetSyntacticallyValidID("Yearly income", Type.GetType(MiningModelColumn))) is not accesible in this context because it is 'Private'. I have some more problems but I thing that by solving the above that I referred I will solve the rest.
I perform data mining on all products and a specific product category. Do I need to create 2 data source views, one for all products and the other one for the specific product category? Afterward, I run the Data Mining Wizard 2 times to create 2 mining structures. I also need to add the same mining model (e.g. Bayes, Cluster) to each of these mining structures. Is there any simple way to do it?
I just found that I am not able to view the accuracy chart for my mining model. The error message is: no mining models are selected for comparision. Which is quite strange.
Hoping someone will have a solution for this error
Errors in the metadata manager. The data type of the '~CaseDetail ~MG-Fact Voic~6' measure must be the same as its source data type. This is because the aggregate function is not set to count or distinct count.
Is the problem due to the data type of the column used in the mining structure is Long, and the underlying field in the cube has a type of BigInt,or am I barking up the wrong tree?
I'm a beginner with SQL 2012 SSDT & SSMS. I get this error message when I try to deploy my project:
"Error 6 Error (Data mining): KEY SEQUENCE columns are not supported at the case level. The 'Customer Key' column of the 'TK448 Ch09 Cube Clustering' mining structure contains content that is not valid. 0 0 " I am finding it hard to locate the content that is not valid. I've been trying to find a answer for this problem but can't seem to find anything. How can I locate the content that is not valid and change or delete it so that I can deploy this solution?
Can somebody help me with the following error while deploying my cube:
The attribute key cannot be found : dbo_fact_table, Column: datetime Value 25/10/1901 4:18:00 pm...
The year 1901 is included in the time period of the time dimension. The calendar includes the following dates : 1/1/1753 - 31/12/2007 (Time binding) Why this referential integrity error occurs ??
Please help me because it is urgent and I cannot find a solution..
Why I got different results for the same attribute value displayed in my mining model? Any suggestions on what I may have missed for that?
In my case, the mining structure is with case table which is the fact table, within this mining structure, I dragged other attributes from its related dimensional tables as well. E.g The schema of the mining structure is as below:
Then in my training model (using Microsoft Clustering algorithm), the content contained within the training model is very strange, e.g there are different results for the same value of attribute 'Agent Level' . Why did that happen and how can I figure it out? There should only one result for each value of each attribute within one mining model?
Please shed me some light on this issue and I am looking forward to hearing from you shortly for your kind advices and thanks a lot in advance.
I'm trying to build a association model in the Standard Edition based on an existing cube. I keep getting the error:
Error (Data mining): The 'Product Recommendations' mining model has 60385 attributes. This number of attributes exceeds the attribute limit of 5000 allowed by the current version of the algorithm associated with the mining model.
I created Cube Slice filters and those limit the Customer and Product dimensions (Product is Nested) to well under 5000. The error message also does not change. The number of attributes is equal to the number of rows in the Product dimension, but I expected the cube slice to reduce the number. I tested all the SQL used while it processes and with the MDXFilters the number of rows returned is well under 5000.
So, in short, the final questions is, is it possible to create a mining model in standard edition based on an existing cube where the nested dimension in the model has more than 5000 rows? Is there some other way to filter the query?
I guess my only choice on this if there isn't a way is to extract the data into relational table with only the rows I want to analyze....that's a huge pain and doesn't really make sense when the filters should limit the model size.
What is annoying on this is I can't find one reference anywhere on the microsoft site that this limit even exists within the product...
I've tried those two operations in the Management Studio. Though we can create a mining structure and mining model in Management Studion, but we cannot process the analysis-service database.
(1) I create only a mining structure through CREATE MINING STRUCTURE. No error reported. But if I process the analysis-service database in Management Studio I always get error
'Error : The '<mining_structure__name>' structure does not contain bindings to data (or contain bindings that are not valid) and cannot be processed.
I then tried to create it by creating and running an XMLA script. It was successful. However, it's much harder to learn XMLA.
If any of you created an analysis-service database in Mgt Studio, and create a mining structure in the same place using DMX script, can you process the database?
(2) Is there any use of CREATE MINING STRUCTURE operation without binding to any table? Examples I saw so far did not show relating it to do. In my experience processing the analysis-service database with that mining structure is doomed to fail.
(3) Is there any way we can create mining structure through CREATE MINING
STRUCTURE operation in Management Studio and use RELATED TO clause
to bind it to any Relationship to an attribute column (mandatory only if it applies), indicated by the RELATED TO clause
(4) If this is the fact, is there any use of CREATE MINING STRUCTURE operation? If we use BI Dev Studio, it's much easier to use the wizard.
(5) I found I cannot create a mining model inside a mining structure through operation CREATE MINING MODEL. If you call that operation, you end up having a mining model and a mining structure with the same name. I found that in order to create a mining model inside a mining structure you have to call operation ALTER MINING STRUCTURE ADD MINING MODEL. Is it true this is the only way?
I 've read that there is a workaround for this issue by customizing errors at processing time but I am not glad to have to ignore errors, also the cube process is scheduled so ignore errors is not a choice at least a good one.
This is part of my cube where the error is thrown.
DimTime PK (int)MyMonth (int, Example = 201501, 201502, 201503, etc.) Another Columns FactBudget PK (int)Month (int, Example = 201501, 201502, 201503, etc.)
I set the relation between DimTime and FactBudget doing DimTime MyMonth as Primary Key and FactBudget Month as Foreign Key. The cube built without problem, when processing the errror: The attribute key cannot be found when processingwas thrown.
It was thrown due to FactBudget has some Month values (201510, 201511, 201512 in example) which DimTime don't, so the integrity is broken.
My actual question: is there a way or pattern to redesign this DWH to correctly deploy and process?
I am working with several tables, but for now I just mention 4 : one is fact table (named Usage), and 3 dimensional tables Periods, Products, and Regions. The fact table contains references to the dimensional tables. Table Periods contain two other columns month and year.
I created a cube containing columns from those 4 tables. Deployment was successful. Trouble comes when I want to create a mining structure using Time Series containing these columns :
- Period - Amount (of money) - Product name - Region name
When I choose to use cube (instead of table) as source for mining structure, I'm forced to choose only one dimension (among the Periods, Products, and Regions). Whatever dimension I choose I end up being unable to use the column period as the Time-Key column. Effectively I cannot use Time Series method since I cannot use the column period.
(1) Why is this so [why Visual Studio forced us to use only one dimension from the cube] ? (2) Why Visual Studio eliminates the column period, column that has relationship with the time dimension? (3) What is the use of Cube anyway to the mining? Is there still any use for it? (4) What is the solution to that kind of problem I face?
Just found that we are not able to define multiple key columns for a mining structure in SQL Server 2005 Data Mining engine, just wondering is there other way to define multiple key columns for a mining structure there? As in many cases, the table we are mining are with composite key consisting of different foriengn keys, e.g. A fact table are with transaction information and other foreign keys. If I am not able to define these composite key here for this fact table, I will have to have a named calculation in data source view to have a key column which is based on these original composite keys? Is this a better way to solve this problem or there is any other alternatives to figure it out?
Hope my question is clear for your help and I am looking forward to heaing from you shortly for your kind advices and help and thanks a lot in advance.
Can anyone spot what i am missing here ? The problem is that i am getting a null object for e.TextData in the t_OnEvent(object sender, TraceEventArgs e) function below. I am trying to get event- notifications while processing the data mining structure.
I got a quite a strange problem with Mining structure for OLAP data source though. The problem is: I am not able to edit the mining structure in the mining structure editor. The whole data source view within the mining structure editor is greyed. Could please anyone here give me any advices for that?
Thank you very much in advance for any help for that.
I've tried to use the export command to export a mining model from management studio, but it returns that export statement is not supported for OLAP mining structures, Ive checked the EXPORT(DMX) reference I can't see any note that it is not applicable on OLAP structures.
I am a bit confused for the model evaluation (lift chart), should we map all the columns for both the mining structure and the case table? I mean for those predictive models, we have a predict column, shouldnt we ignore the mapping of the predictive column between the mining structure and the case table? But it seemes we are not allowed to miss the predictive column mapping between the mining structure and the case table.
Why is that? Could any experts here give me some explanation on that?
Hope my question is clear for your help.
Thanks a lot and I am looking forward to hearing from you shortly.
and I received the following error message. Any Ideas? What is wrong with this? Thank you in advance
<Batch xmlns="http://schemas.microsoft.com/analysisservices/2003/engine"> <Parallel> <Process xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <Object> <DatabaseID>test27</DatabaseID> <MiningStructureID>test27 MiningStructureName</MiningStructureID> <MiningModelID>test27 miningmodelName</MiningModelID> </Object> <Type>ProcessFull</Type> <WriteBackTableCreation>UseExisting</WriteBackTableCreation> </Process> </Parallel> </Batch> Processing Mining Structure 'test27 MiningStructureName' completed successfully. Start time: 26/3/2007 11:36:18 μμ; End time: 26/3/2007 11:36:18 μμ; Duration: 0:00:00 Processing Dimension 'test27 MiningStructureName ~MC-SUMCODE' failed. Start time: 26/3/2007 11:36:18 μμ; End time: 26/3/2007 11:36:18 μμ; Duration: 0:00:00 Processing Dimension Attribute '(All)' completed successfully. Start time: 26/3/2007 11:36:18 μμ; End time: 26/3/2007 11:36:18 μμ; Duration: 0:00:00 Processing Dimension Attribute 'OZOS NUM MANY' failed. Start time: 26/3/2007 11:36:18 μμ; End time: 26/3/2007 11:36:18 μμ; Duration: 0:00:00 SQL queries 1 SELECT DISTINCT [VISIT].[OZOS_NUM_MANY] AS [VISITOZOS_NUM_MANY0_0] FROM [VISIT] AS [VISIT] Error Messages 1 OLE DB error: OLE DB or ODBC error: Operation canceled; HY008. Processing Dimension Attribute 'STAFF_YES' failed. 1 rows have been read. Start time: 26/3/2007 11:36:18 μμ; End time: 26/3/2007 11:36:18 μμ; Duration: 0:00:00 SQL queries 1 SELECT [VISIT].[STAFF_YES] AS [VISITSTAFF_YES0_0] FROM [VISIT] AS [VISIT] Error Messages 1 OLE DB error: OLE DB or ODBC error: Requested conversion is not supported.. Errors in the OLAP storage engine: An error occurred while the 'STAFF_YES' attribute of the 'test27 MiningStructureName ~MC-SUMCODE' dimension from the 'test27' database was being processed. Processing Dimension Attribute 'D_G_OZODIS_IPER' completed successfully. Start time: 26/3/2007 11:36:18 μμ; End time: 26/3/2007 11:36:18 μμ; Duration: 0:00:00 Errors and Warnings from Response OLE DB error: OLE DB or ODBC error: Requested conversion is not supported.. Errors in the OLAP storage engine: An error occurred while the 'STAFF_YES' attribute of the 'test27 MiningStructureName ~MC-SUMCODE' dimension from the 'test27' database was being processed. Errors in the OLAP storage engine: The process operation ended because the number of errors encountered during processing reached the defined limit of allowable errors for the operation. OLE DB error: OLE DB or ODBC error: Operation canceled; HY008. Errors in the OLAP storage engine: An error occurred while the dimension, with the ID of 'test27 MiningStructureName ~MC-SUMCODE', Name of 'test27 MiningStructureName ~MC-SUMCODE' was being processed. Errors in the OLAP storage engine: An error occurred while the 'OZOS NUM MANY' attribute of the 'test27 MiningStructureName ~MC-SUMCODE' dimension from the 'test27' database was being processed. Errors in the high-level relational engine. The database operation was cancelled because of an earlier failure. Errors in the OLAP storage engine: An error occurred while the dimension, with the ID of 'test27 MiningStructureName ~MC-SUMCODE', Name of 'test27 MiningStructureName ~MC-SUMCODE' was being processed. Errors in the OLAP storage engine: An error occurred while the 'D_G_OZODIS_IPER' attribute of the 'test27 MiningStructureName ~MC-SUMCODE' dimension from the 'test27' database was being processed. Manolis
I am trying to write some DMX queries to create and populate a mining model as a SSMS analysis services project. I followed the following steps:
1. Create the mining model using a CREATE MINING MODEL ... query.
2. Followed by the - INSERT INTO MINING MODEL ... query, which fetches prediction data from another mining model to populate the mining model.
3. I now want to use this new model for prediction, which requires processing the mining model first. When I process the model, it throws the following error:
Error (Data mining): The 'XYZ_Structure' structure does not contain bindings to data (or contains bindings that are not valid) and cannot be processed.
Please suggest if I am making a mistake in the above procedure. I will appreciate all help in overcoming this issue.
Auxilliary question: How do I process the mining model programmatically?
I have started working on SSAS since last week, I need to perform some calculations on the data fetched from the cube based on the parameters. SSRS is used to display the output and SSAS is used as a data source.
How i could perform the operations on the data fetched from the cube in SSAS? Does SSAS provides the storage structure like temp table in stored procedure where we can perform the various operations before sending final data back to the client side tool(SSRS)?
OR Is there any alternative way to perform the operations based on the input provided through the parameters
I have an execute process task set up to run ftp.exe and a script argument. The ftp.exe is referenced in the executable field without a qualified path. The package just seems to know it's there relatively. I need to change this to run a secured ftp executable that I recently installed on my pc. I put the new executable in the WindowsSystem32 folder where the old ftp.exe is stored. But when I put the new executable in the executable field, it says the 'File/Process "FTPS.exe" is not in path'. I get the same error when I fully qualify the path. Is there something I need to do with the new executable for SSIS to pick it up without having to fully qualify the path?
How to right choose key column in"Mining Structure" for Microsoft Analysis Services?
I have table:
"Incoming goods"
Create table Income ( ID int not null identity(1, 1) [Date] datetime not null, GoodID int not null, PriceDeliver decimal(18, 2) not null, PriceSalse decimal(18, 2) not null, CONSTRAINT PK_ Income PRIMARY KEY CLUSTERED (ID), CONSTRAINT FK_IncomeGood foreign key (GoodID) references dbo.Goods ( ID ) )
I'm trying to build a relationship(regression) between “Price Sale” from Good and “Price Deliver”.But I do not know what column better choose as “key column”: ID or GoodID ?
I am wondering where can I store my mining results in data mining engine? For example, I got mining results like accuracy chart, decision trees, and other formats of results based on different mining algorithms I used for my data mining, so where can I actually store the results for reporting service use later? Is it possible to do that in SQL Server 2005?
Thanks a lot for any help and guidance in advance.
I had to change the key columns of a dimension attribute to fix an error. I did this in BIDS. The change was from a single key column to a composite key column. Now I am getting these error when I process the cube:
Measure group attribute key column x does not match source attribute ..
I looked at the cube XMLA definition under mesaure groups and it still shows a single key column with inherited binding. However, the BIDS does not give me an option correct this in any way. I have had to do this once before and the only option seems to be removing the dimension from the cube and add it back in. But that is very error prone since I lose any specific settings at the cube dimension level not to mention aggregations no longer include the dimension, etc.
Not seeing an alternative, I went through each measure group (I have 7) and changed the key columns manually in the XMLA and saved the cube. This worked, but I don't understand why BIDS automatically doesn't do it.
Is this a flaw in the BIDS or I should be missing something.
I have MS Time Seeries model using a database of over a thousand products each of which has hundreds of cases. It amazingly takes only a few minutes to finish processing the model, but when I click Mining Model Viewer to view the models, it takes many hours to show up. Once the window is open, I can choose model for different products almost instantly. Is this normal?
Hi, I have just run a simple data set through a model to predict a simple true or false value (i.e. binary output) The Lift Chart/Mining Legend in Analysis Services shows three results Score, Population Correct (%), and Predict Probability (%)
Population Correct I beleive is the percentage of predictions it got right out of the total number of predictions it tried to make. Is this correct?
However, I cant work out how the other two are derived in particular the 'SCORE'. To give a live example the scores were as follows:
Model Score Pop Correct Pred Probability Decision Trees 0.83 76.59% 54.28% Neural Network 0.75 67.63% 50.05% Ideal Model 100.00%
Can anyone help with this and give a detailed explanation?
