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Resolved! Problems with xgboost.spark model loading from MLflow.
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 som...
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Thank you very much @Data_Cowboy !!! I had the same issue. I even had 14 TiB Databricks should really fix this
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- 5177 Views
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MLFlow model loading taking long time and "model serving" failing during init
I am trying to load a simple Minmaxscaler model that was logged as a run through spark's ML Pipeline api for reuse. On average it takes 40+ seconds just to load the model with the following example: This is fine and the model transforms my data corre...
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Hello,Any solutions found for this issue?I'm serving up a large number of models at a time, but since we converted to PySpark (due to our data demands), the mlflow.spark.load_model() is taking hours.Part of the reason to switch to spark was to help w...
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