DataflowGen2 on MS Fabric: Optimize column profiling on millions of rows (1-5mil)

[Anonymous]

Hello, 

I have datasets residing on hive_metastore of Azure Databricks storage, in the range of 1-5 millions of records. I wish to use the Column Profiling feature on the entire dataset after loading the data using Get Data experience on a DataflowGen2 object . 

When I am changing from "Column profiling based on top 1000 rows" to "Column profiling based on entire dataset" , the processing takes forever when applied on the 1 million dataset, and happens instataneously when applied on the 1000 rows one. 

What steps shall I take to optimize the performance here, to perform column profiling on entire data set?

[miguel · Accepted solution]

This is something that we don't have full control over. It relies on 3 specific components:

• Data source: and the resources available for it
• Connector: owned by the Databricks team
• Power Query editor: it effectively runs the queries that the connector tells it to run and it tries to later cache the results if they're fully computed

I can pass your feedback to the Databricks team, but there's nothing beyond what you're doing today that can impact the performance of the profiling for such scenario.