CERTIFIED-MACHINE-LEARNING-PROFESSIONAL · Question #46
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 programmat
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Question
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?
Options
- Aclient.list_run_infos(exp_id)
- Bspark.read.format("delta").load(exp_id)
- CThere is no way to programmatically return row-level results from an MLflow Experiment.
- Dmlflow.search_runs(exp_id)
- Espark.read.format("mlflow-experiment").load(exp_id)
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