Start with adding a Lookup activity to your pipeline where you configure it to run your SQL query against Snowflake.
Then add a Set Variable activity, set the type to Array
and configure the value to be the output of the Lookup activity.
Example of your Expression:
@activity('LookupActivityName').output.value
Then you can create Azure Function or Logic App:
- Write a function that accepts an HTTP POST request with the data payload.
- Inside the function, process the payload and write it to a CSV file in the Azure Storage Account.
import azure.functions as func
import csv
from azure.storage.blob import BlobServiceClient
def main(req: func.HttpRequest) -> func.HttpResponse:
logging.info('Python HTTP trigger function processed a request.')
data = req.get_json()
# Process data and write to CSV
csv_content = "column1,column2\n"
for item in data:
csv_content += f"{item['column1']},{item['column2']}\n"
# Save CSV to Azure Blob Storage
connection_string = "YourAzureStorageConnectionString"
blob_service_client = BlobServiceClient.from_connection_string(connection_string)
container_name = "your-container-name"
blob_name = "output.csv"
blob_client = blob_service_client.get_blob_client(container=container_name, blob=blob_name)
blob_client.upload_blob(csv_content, overwrite=True)
return func.HttpResponse(f"CSV file created successfully.", status_code=200)
```Or you can create a Logic App with an HTTP request trigger :
- Add actions to process the input data and create a CSV file.
- Save the CSV file to your Azure Storage Account.
Now comes the part to configure Web Activity in ADF:
- Add a Web Activity to your pipeline.
- Set the URL to the endpoint of your Azure Function or Logic App.
- Configure the method to POST.
- Set the body to pass the data stored in the variable.
```json
{
"data": @variables('YourVariableName')
}