Problems with xgboost.spark model loading from MLflow.

[Data_Cowboy]

When loading an xgboost model from mlflow following the provided instructions in Databricks hosted MLflow the input sizes I am showing on the job are over 1 TB. Is anyone else using an xgboost.spark model and noticing the same behavior?

Below are some screenshots showing the input size. The job has been running over 15 minutes just to load the model from MLflow.

[Data_Cowboy · Accepted solution]

Getting rid of the call to the full dbfs artifact path seemed to fix the issue for me.

[dbx-user7354]

Thank you very much @Data_Cowboy !!! I had the same issue. I even had 14 TiB 😄 

Databricks should really fix this

[Data_Cowboy]

@dbx-user7354 Glad to hear this solution worked out for you. Makes me feel good that I came back and answered my own post 😀