Hi Yasar Shaikh,
Using Azure Data Factory for automating the file movement between Azure File Shares. Azure Data Factory provides a robust and scalable way to handle data movement and transformation.
Steps to Set Up Azure Data Factory for File Movement
Create an Azure Data Factory Instance:
- Go to the Azure portal and create a new Data Factory instance.
Create Linked Services:
- Create linked services for both the source (transaction optimized file share) and the destination (cool-tier file share) storage accounts.
Create Datasets:
- Create datasets for the source and destination file shares.
Create a Pipeline:
- Create a new pipeline in Azure Data Factory.
- Add a Copy Data activity to the pipeline.
- Configure the source and destination datasets in the Copy Data activity.
Add a Filter Activity:
- Use a filter activity to filter files based on the last access time.
- You can use a custom activity or a stored procedure to filter files that haven't been accessed for a specified number of days.
Add a Delete Activity:
- After the files are copied to the destination, add a delete activity to remove the files from the source.
Example Pipeline Configuration
Here’s a high-level overview of how the pipeline might look:
Copy Data Activity:
- Source: Transaction optimized file share dataset.
- Destination: Cool-tier file share dataset.
Filter Activity:
- Use a custom activity to filter files based on the last access time.
Delete Activity:
- Delete files from the source file share after successful copy.
Automate the Pipeline
- Schedule the pipeline to run at regular intervals using triggers in Azure Data Factory.
Additional Resources
- Azure Data Factory Documentation
Copy Data Tool in Azure Data Factory
If you have any other questions or are still running into more issues, let me know in the "comments" and I would be happy to help you.