Forum Discussion
Community ChampionView Files in Fabric Warehouse table
In Lakehouse, we can click View Files to see the underlying Parquet and delta log files, and checkpoint files.
Is this not possible for a Warehouse table in the Fabric user interface? Why not?
I'd like to visually verify how many parquet files and delta log files gets created when using certain T-SQL commands. I'd also like to verify the managed table maintenance operations, by seeing which parquet files, delta log .json files and checkpoint files are present.
Thanks!
Hi frithjof_v
In the Lakehouse, you can indeed click "View Files" to see the underlying Parquet, delta log, and checkpoint files. However, this functionality is not available for Warehouse tables in the Fabric user interface. The primary reason for this difference is that the Warehouse and Lakehouse are designed to serve different purposes and have different underlying architectures.
The Lakehouse is designed to handle both structured and unstructured data, providing a unified platform for data storage and analytics. It allows you to directly interact with the underlying files, which is useful for data engineers and scientists who need to understand and manage the raw data files.
On the other hand, the Warehouse is optimized for structured data and SQL-based analytics. It abstracts away the underlying file management to provide a more streamlined and user-friendly experience for business analysts and other users who primarily interact with data through SQL queries. This abstraction helps to simplify the user experience and improve performance but at the cost of not exposing the underlying files directly in the user interface.
Best Regards,
Jing
Community Support Team
1 Reply
Hi frithjof_v
In the Lakehouse, you can indeed click "View Files" to see the underlying Parquet, delta log, and checkpoint files. However, this functionality is not available for Warehouse tables in the Fabric user interface. The primary reason for this difference is that the Warehouse and Lakehouse are designed to serve different purposes and have different underlying architectures.
The Lakehouse is designed to handle both structured and unstructured data, providing a unified platform for data storage and analytics. It allows you to directly interact with the underlying files, which is useful for data engineers and scientists who need to understand and manage the raw data files.
On the other hand, the Warehouse is optimized for structured data and SQL-based analytics. It abstracts away the underlying file management to provide a more streamlined and user-friendly experience for business analysts and other users who primarily interact with data through SQL queries. This abstraction helps to simplify the user experience and improve performance but at the cost of not exposing the underlying files directly in the user interface.
Best Regards,
Jing
Community Support Team