Is there a way in Azure Synapse to have a parameter in a filter transformation of a pipeline?
And if so, is there a way to trigger the pipeline via API and pass the value in the call?
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I would like to create a Synapse Pipeline for batch inferencing with data ingestion to store the data into data lake and then use this as input to call a batch endpoint already created (through ML Execute Pipeline) Then, capture the output into the data lake (appended to a table) to continue the next steps...
The documentation from Microsoft to setup such a scenario is very poor and everything I tried is failing.
Below is the Azure Machine Learning Execute Pipeline configuration. I need to pass the value for the dataset_param with data asset instance already available as below.
But, it complains that the dataset_param is not provided. Not sure, how to pass this value...
Here is the original experiment / pipeline / endpoint created by the DevOps pipeline. I just call this endpoint above from the Synapse Pipeline
I am trying to pass the following variables from the azure DevOps library as variables to the data factory pipeline. For some reason, the variables are not populating in the data factory pipeline.
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When I check the pipeline I don't see the variables populated.
So is my understanding correct if we provide variables (eg moris#aix.com, lowes#aix.com, and so on)
will this be populated in the data factory pipeline as a variable too? If yes then I am unable o figure out the reason why is not getting updated with the variables in the data factory
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From the images it seems to me that you are mixing up two types of pipelines:
Azure DevOps pipelines
Azure Data Factory pipelines
The first type (Azure DevOps) can be used to deploy an Azure Data Factory resource, and you can include Azure DevOps variable groups. You could then propagate these variables as global variables in the Data Factory and subsequently use them in Data Factory pipeline tasks.
To answer your questions: Yes, it is possible to populate Data Factory pipelines from Azure DevOps variable groups, but it does not happen automatically.
Edit: For this use case (Email adresses) I would rather use a parametrized lookup activity in Data Factory, which reads the Email adresses from a .csv-file in a storage account.
I am new to Azure Data Factory pipelines.
I want guidance on how to call an Azure Batch Job via a Azure Data Factory pipeline and monitor the batch job for failure/completion - is this possible ?
Regards
I found the following articles which I am working through...
https://learn.microsoft.com/en-us/azure/data-factory/v1/data-factory-data-processing-using-batch
Is there a way to create an Azure ADF Pipeline to ingest the incoming POST requests? I have this gateway app (outside Azure) that is able to publish data via REST as it arrives from the application and this data needs to be ingested into a Data Lake. I am utilizing the REST calls from another pipeline to pull the data but this basically needs to do the reverse - the data will be pushed and i need to be constantly 'listening' to those calls...
Is this something an ADF pipeline should do or maybe there are any other Azure components able to do it?
Previous comment is right and is one of the approach to get it working but would need bit of coding (for azure function).
There could also be an alternate solution to cater to your requirement is with Azure Logic Apps and Azure data factory.
Step 1: Create a HTTP triggered logic app which would be invoked by your gateway app and data will be posted to this REST callable endpoint.
Step 2: Create ADF pipeline with a parameter, this parameter holds the data that needs to be pushed to the data lake. It could be raw data and can be transformed as a step within the pipeline before pushing it to the data lake.
Step 3: Once logic app is triggered, you can simply use Azure data factory actions to invoke the data factory pipeline created in step 2 and pass the posted data as a pipeline parameter to your ADF pipeline.
This should be it, with this - you can spin up your code-less solution.
If your outside application is already pushing via REST, why not have it make calls directly to the Data Lake REST APIs? This would cut out the middle steps and bring everything under your control.
Azure Data Factory is a batch data movement service. If you want to push the data over HTTP, you can implement a simple Azure Function to accept the data and write it to the Azure Data Lake.
See Azure Functions HTTP triggers and bindings overview
Is it possible to somehow package and execute already written azure function as a custom activity in azure data factory?
My workflow is next:
I want to use azure function (which is doing some data processing) in ADF pipeline as a custom activity. This custom activity is just one of the activities in pipeline but its key to be executed.
Is it possible to somehow package and execute already written azure
function as a custom activity in azure data factory?
As I know, there is no way to do that so far. In my opinion, you do not need to package the Azure Function. I suggest you using Web Activity to invoke the endpoint of your Azure Function which could merge into previous pipeline nicely.