I have a meta-data driven pipeline and a mapping data flow to load my data. When I try to run this pipeline, I get the following error.
{"message":"at Derive 'TargetSATKey'(Line 42/Col 26): Column 'PersonVID' not found. The stream is either not connected or column is unavailable. Details:at Derive 'TargetSATKey'(Line 42/Col 26): Column 'PersonVID' not found. The stream is either not connected or column is unavailable","failureType":"UserError","target":"Data Vault Load","errorCode":"DFExecutorUserError"}
When I debug the mapping data flow, all the components in the data flow work as intended.
I guess that my source connection parameters aren't flowing through properly. Below is an email of my source connection
Please let me know if you have any thoughts and questions
I found a resolution to my problem. The error was the data being passed in was a string but when the variable was unpacked my variable value didn't have a quote around it. Putting in the quotes fixed it.
For example
'BusinessEntityID'
Please let me know if there are any questions
Related
With the Copy Data transformation it is possible to retrieve data from a REST call (array with flat json objects, similar to Odata) and copy the contents to a flat table keeping the data types from the source but without the necessity to set the schema for that specific data.
When I try to recreate this with Data Flow, I can't get this to work. When I check the Data Preview of my Source I get a hierarchy with a body (with my odata like data) and a header. And if I send that to my sink (Avro) it will be saved in this same hierarchical structure (including the header). I know I can fix this manually by using a Select operation (body.column1, body.column2, etc.), but I want to make my Data Flow dynamic so I'm able to use it with multiple tables/endpoints.
So I receive it like this with my REST source:
link
And I want it to be like this at my Sink without hardcoding my schema:
link
The only work around I can come up with is retrieving the data using Copy Data, put it somewhere temporarily and then use my data flow to further transform the data. Is there a more easy way to do this? I cannot imagine that I'm the only one that has this issue.
Hopefully it's clear and somebody is able to help. Thank you very much in advance.
Data flow projection will get schema from API including body and header. Hence, when you use auto mapping everything going to be saved.
Below work arounds you can think of,
As you mentioned, using copy data first and then data flow to further transform.
Use select or derived column transformations and transform your data to get all column names and then finally use sink. For this you can opt with Column pattern matching syntax. So that one condition can be meet with multiple columns to transform.
Check below link to know about column pattern mappings.
https://learn.microsoft.com/en-us/azure/data-factory/concepts-data-flow-column-pattern
We have a stage variable using DateFromDaysSince(Date Column) in datastage transformer. Due to some invalid dates , datastage job is getting failed . We have source with oracle.
When we check the dates in table we didnt find any issue but while transformation is happening job is getting failed
Error: Invalid Date [:000-01-01] used for date_from_days_since type conversion
Is there any possibility to capture those failure records into reject file and make the parallel job run successfull .. ?
Yes it is possible.
You can use the IsValidDate or IsValidTimestamp function to check that - check out the details here
These functions could be used in a Transformer condition to move rows not showing the expected type to move to a reject file (or peek).
When your data is retrieved from a database (as mentioned) the database ensures the datatype already - if the data is stored in the appropriate format. I suggest checking the retrieval method to avoid unnecessary checks or rejects. Different timestamp formats could be an issue.
I'm using Copy Data.
When there is some data error. I would export them to a blob.
But in this case, the Pipelines's status is still Succeeded. I want to set it to false. Is it possible?
When there is some data error.
It depends on what error you mentioned here.
1.If you mean it's common incompatibility or mismatch error, ADF supports built-in feature named Fault tolerance in Copy Activity which supports below 3 scenarios:
Incompatibility between the source data type and the sink native
type.
Mismatch in the number of columns between the source and the sink.
Primary key violation when writing to SQL Server/Azure SQL
Database/Azure Cosmos DB.
If you configure to log the incompatible rows, you can find the log file at this path: https://[your-blob-account].blob.core.windows.net/[path-if-configured]/[copy-activity-run-id]/[auto-generated-GUID].csv.
If you want to abort the job as soon as any error occurs,you could set as below:
Please see this case: Fault tolerance and log the incompatible rows in Azure Blob storage
2.If you are talking about your own logic for the data error,may some business logic. I'm afraid that ADF can't detect that for you, though it's also a common requirement I think. However,you could follow this case (How to control data failures in Azure Data Factory Pipelines?) to do a workaround. The main idea is using custom activity to divert the bad rows before the execution of copy activity. In custom activity, you could upload the bad rows into Azure Blob Storage with .net SDK as you want.
Update:
Since you want to log all incompatible rows and enforce the job failed at the same time, I'm afraid that it can not be implemented in the copy activity directly.
However, I came up with an idea that you could use If Condition activity after Copy Activity to judge if the output contains rowsSkipped. If so, output False,then you will know there are some skip data so that you could check them in the blob storage.
I'm attempting to pull data from the Square Connect v1 API using ADF. I'm utilizing a Copy Activity with a REST source. I am successfully pulling back data, however, the results are unexpected.
The endpoint is /v1/{location_id}/payments. I have three parameters, shown below.
I can successfully pull this data via Postman.
The results are stored in a Blob and are as if I did not specify any parameters whatsoever.
Only when I hardcode the parameters into the relative path
do I get correct results.
I feel I must be missing a setting somewhere, but which one?
You can try setting the values you want into a setVariable activity, and then have your copyActivity reference those variables. This will tell you whether it is an issue with the dynamic content or not. I have run into some unexpected behavior myself. The benefit of the intermediate setVariable activity is twofold. Firstly it coerces the datatype, secondly, it lets you see what the value is.
My apologies for not using comments. I do not yet have enough points to comment.
I am trying to learn a mirth system with a channel that is pulling from a database for its source and outputting hl7 messages for its destination(s). The SQL query pulls the correct data from the source--but Mirth does not output all of the data in the right spots in the HL7 message. The destinations show that it is outputting Template:${message.encodedData}. What does that mean? Where can I see the template that it using. The destinations don'y have any filters or transformers so I am confused.
message.encodedData is the fully transformed message - after any transformation steps.
The transformer is also where you can specify the output template for how you want the data to look. Simply load up a sample template message in the output template of the transformer (message template tab in the transformer) and then create a series of message builder steps. Your output message will be in the variable tmp, and your sql results will be in the variable msg.
So, if your first column is patientID (Select patientiD as patientID ...), you would create a message builder steps along the lines of
mapped segment: tmp['PID']['PID.3']['PID.3.2']
mapping: msg['patientID'];
I don't have exact syntax in front of me right now, but that's the basic idea.
I think "transformed" is the status of the message right after the transformers are executed and "encoded" message is the status after the message that comes from the transformers is encoded into the specified channel outbound datatype. In some cases those messages will be the same but not in all the cases.
Also, is very difficult to find updated and comprehensive Mirth documentation.