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If you read the folder directly as Parquet, it loads both the old and new files - that’s why you see duplicate or outdated records.To fix this, make sure you read the table as a Delta table instead of as raw Parquet.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 BhaveshPatel ,
Could you please give me an example of how to read the tables in a Lakehouse only with python?
Hi Isabella,
This is how it works using Pandas:
- lsabetta10 months agoFrequent Visitor
Hi BhaveshPatel
The problem that has reading the parquet is that if I overwrite the table, the parquet brings me the new records and the old ones.