hello Kedro Community! I hope you're all doing well! Here with a quick #snowpark related question. We are leveraging the Kedro SnowParkTable catalog entry, but an issue we're running into, is that our pipeline runs are taking longer than 240 min, which seems to be the max allowable time for a SnowPark session. As a result, when we try write data back as a SnowPark table, we are getting the following error

SnowparkSQLException: (1304): 390114 (08001): None: Authentication token has expired.  The user must authenticate again.

. Has anyone encountered this before, or have any suggestions? Some thoughts we have had are: 1. Breaking up our pipeline into multiple runs, initialising a new session with each run 2. Creating a custom dataset which creates a new session with each dataset load/write Any inputs would be massively appreciated.

Hello! Thanks for reaching out. I don't have an immediate answer, but I'll look into it and get back to you soon.

thanks very much @Jitendra Gundaniya, appreciate it!

So I’d also look into understanding where your bottleneck is DataFrame.explain() should give you some pointers on where the effort is

Does Snowflake / Snowpark still only work with Python 3.8? What dataset type would you recommend for new Python versions?