I have a process that dumps json files into Azure Storage Blobs. I'm using an Azure Data Factory to Upsert the blobs to a Azure CosmosDB.
Once the json is upserted to CosmosDB I want it removed from storage.
I can add a Delete action to the workflow, but that risks deleting a json file that has not yet been processed.
Is it possible to set the Data Factory to 'Delete after Upsert' or simlar?
Any other suggestions?
EDIT: Adding image.
Step1: Create Pipeline
Step2: Select Dataflow activity
Step3: Here you will see Delete Source files after completion option. As shown in below screenshot.
In the ADF activity, you'll see this option on your Source transformation:
Related
I am trying to delete a file that is located in a sharepoint directory after successful copy activity. The Delete Activity is having the following properties:
Linked Service : HTTP
DataSet : Excel
Additional Header: #{concat('Authorization: Bearer ',activity('GetToken').output.access_token)}
Here, GetToken is the Web Activity in ADF that generates a token number for accessing SharePoint.
When I am running the pipeline, I am getting the below error:
Invalid delete activity payload with 'folderPath' that is required and cannot be empty.
I have no clue on how to tackle this.
As per my understanding you are trying to delete a file in Sharepoint online using Azure Data Factory.
Currently delete activity in ADF only supports the below data stores and not sharepoint online. which is why you are receiving the above error.
Azure Blob storage
Azure Data Lake Storage Gen1
Azure Data Lake Storage Gen2
Azure Files
File System
FTP
SFTP
Amazon S3
Amazon S3 Compatible Storage
Google Cloud Storage
Oracle Cloud Storage
HDFS
Image: Delete activity Supported Data stores
Ref: Delete activity supported data sources
As a workaround you may try exploring HTTP connector. OR you can use custom activity and write your own code to delete files from SharePoint.
Hope this info helps.
I am creating a dataset in Azure Data Factory. This dataset will be a Parquet file within a directory under a certain container in an ADLS Gen2 account. The container name is 'raw', and the directory that I want to place the file into is source/system1/FullLoad. When I click on Browse next to File path, I am able to access the container, but I cannot access the directory. When I hit folder 'source', I get the error shown below.
How can I drill to the desired directory? As the error message indicates, I suspect that it's something to do with permissions to access the data (the Parquet file doesn't exist yet, as it will be used as a sink in a copy activity that hasn't been run yet), but I don't know how to resolve.
Thanks for confirming putting the resolution for others if anyone face this issue.
The user or managed identity you are using for your data factory should have storage data blob contributor access on the storage account. You can check it from azure portal, go to your storage account, navigate to the container and then directory, click on Access Control on the left panel and check role assignment. If it is missing add the role assignment of storage data blob contributor to your managed identity.
I'm trying to work with a custom activity in Data Factory to execute in a batch accounts pool a python batch stored in a blob storage.
I followed the Microsoft tutorial https://learn.microsoft.com/en-us/azure/batch/tutorial-run-python-batch-azure-data-factory
My problem is when I execute the ADF pipeline the activity failed:
When I check in the Batch Explorer tool, I got this BlobAccessDenied message:
Depending of the execution, it happens on all ADF reference files but also for my batch file.
I have linked the Storage Account to the Batch Accounts
I'm new to this and I'm not sure of what I must do to solve this.
Thank you in advance for your help.
I tried to reproduce the issue and it is working fine for me.
Please check the following points while creating the pipeline.
Check if you have pasted storage account connection string at line number 6 in main.py file
You need to create a Blob Storage and a Batch Linked Services in the Azure Data Factory(ADF). These linked services will be required in “Azure Batch” and “Settings” Tabs when configure ADF Pipeline. Please follow below snapshots to create Linked Services.
In ADF Portal, click on left ‘Manage’ symbol and then click on +New to create Blob Storage linked service.
Search for “Azure Blob Storage” and then click on Continue
Fill the required details as per your Storage account, test the connection and then click on apply.
Similarly, search for Azure Batch Linked Service (under Compute tab).
Fill the details of your batch account, use the previously created Storage Linked service under “Storage linked service name” and then test the connection. Click on save.
Later, when you will create custom ADF pipeline, under “Azure Batch” Tab, provide the Batch Linked Service Name.
Under “Settings” Tab, provide the Storage Linked Service name and other required information. In "Folder Path", provide the Blob name where you have main.py and iris.csv files.
Once this is done, you can Validate, Debug, Publish and Trigger the pipeline. Pipeline should run successfully.
Once pipeline ran successfully, you will see the iris_setosa.csv file in your output Blob.
Step to reproduce:
I created a Copy Data first in the pipeline to simple transfer CSV files frol Azure VM to Azure Blob storage. I always use IRPOC1 as a connection via integration runtime and connect using SAS URI and SAS Token to my Blob Storage
After validate and run my first Copy Data, I successfully have CSV file transfer from my VM to Blob storage
I tried to add a new Data Flow after the Copy Data activity
In my Data Flow, my source is the Blob storage containing the CSV files transferred from VM, my Sink is my Azure SQL Database with successful connection
However, when I ran validation, I got the error message on my Data Flow Source:
Linked Service with self-hosted integration runtime is not supported in data flow.
I saw someone replied on Microsoft Azure Document issue Github that I need to use Copy Data to transfer data to Blob first. Then use the source from this blob with data. This is what I did but I still have the same error. Could you please let me know how I can fix this?
The Data Flow source dataset must use a Linked Service that uses an Azure IR, not a self-hosted IR.
Go to the dataset in your data flow Source, click "Open". In the dataset page, click "Edit" next to Linked Service.
In the Linked Service dialog, make sure you are using an Azure Integration Runtime, not a Self-hosted IR.
Is there any way to copy the data from azure data lake storage to database present in azure analysis server using azure data factory ?
I am trying to use copy activity to do the same task but I don't know how to specify the Analysis Server Database as the destination in output dataset.
For the data connector not in data factory support list, you can write custom activity to access your data
Here is the doc: https://learn.microsoft.com/en-us/azure/data-factory/data-factory-use-custom-activities
Thanks,
Charles