Issues with using Databricks-Connect and Petastorm

[YSF]

Has anyone successfully used Petastorm + Databricks-Connect + Delta Lake?

The use case is being able to use DeltaLake as a data store regardless of whether I want to use the databricks workspace or not for my training tasks.

I'm using a cloud-hosted jupyterlab environment(in Paperspace), and trying to use Petastorm + Databricks Connect.

What I'm trying to do:

• Connect to cluster via databricks-connect
• Read in data from delta lake using a databricks spark cluster

• Use Petastorm to convert the dataframe into a pytorch ready object

The exact same code, on the same cluster works when using the databricks notebook environment. But when running the `make_spark_converter()` function in my hosted jupyterlab environment it throws me a "Unable to infer schema" error. Even though if I check the `.schema` attribute of the dataframe I'm giving it, it shows me a spark compatible schema.

[Hubert-Dudek · Accepted solution]

I would not definitely use Databricks-Connect in production.

[YSF]

because its janky or why? I don't need it for customer facing production. More so for if I'm using my own HPC or local workstation, but I want to access data from delta lake. Figured it was easier/preferable to setting up my own spark environment locally. I'm paying for databricks might as well get the benefits of the runtime.

Can you elaborate on your answer?

[Kaniz]

Hi @Yusuf Khan​ , Please go through the link here.