A data scientist is utilizing MLflow to track their machine learning experiments. After completing a series of runs for the experiment with experiment ID exp_id, the data scientist wants to programmatically work with the experiment run data in a Spark DataFrame. They have an active MLflow Client client and an active Spark session spark.
Which of the following lines of code can be used to obtain run-level results for exp_id in a Spark DataFrame?
To get run-level results for a specific experiment ID in a Spark DataFrame, you should use the line of code spark.read.format('mlflow-experiment').load(exp_id). This format is specifically designed to load MLflow experiment data into Spark DataFrames, allowing easy manipulation and analysis of the experiment results.
Doc: https://docs.databricks.com/en/query/formats/mlflow-experiment.html#load-data-using-experiment-ids
Correct Answer is E. if you want to work with the experiment run data in a Spark DataFrame, you can use E. spark.read.format(“mlflow-experiment”).load(exp_id)
https://docs.databricks.com/en/query/formats/mlflow-experiment.html#load-data-using-experiment-ids
Agree with BookNinja. Correct Answer is E - Doc: https://docs.databricks.com/en/query/formats/mlflow-experiment.html