Forum Discussion
Spark Session configuration
- 10 months ago
Hi lsabetta ,
The issue happens because your Lakehouse table is stored in Delta format, not plain Parquet.
When you overwrite the table, new Parquet files are created, but old ones remain in the folder for versioning.
If you read the folder directly as Parquet, it loads both the old and new files - that’s why you see duplicate or outdated records.To fix this, make sure you read the table as a Delta table instead of as raw Parquet.
This ensures that only the latest valid version of the data is returned, without mixing older files.Thank you.
Hi lsabetta
You should use Power BI Dataflow Gen 2.
This is how it works :
Either use Notebooks ( Python ( Pandas) + Data Lake + Delta Lake ) or Use Power BI Dataflow Gen 2 ( UI + UX).
Yes You can read the tables in Lakehouse using Python Pandas library. ( pd.read_tables)