Which parameter is used to pass a Spark session object to SparkTrials?

The parameter used to pass a Spark session object to SparkTrials is 'spark_session'. This parameter is specifically designed to accept an instance of the Spark session, which is crucial for executing distributed tasks within the Databricks environment. When you want to utilize the capabilities of SparkTrials for hyperparameter tuning or other distributed machine learning tasks, it is essential to provide a valid Spark session to ensure that the operations can leverage the Spark framework for performance and scalability.

A Spark session serves as the entry point for interacting with the underlying Spark functionalities and is required for executing Spark computations. Using the 'spark_session' parameter allows SparkTrials to integrate seamlessly with the existing Spark context, providing access to distributed data processing.

The other options do not refer to the correct terminology or parameter used for passing the Spark session object in this context. Hence, using 'spark_session' is the appropriate and necessary choice for ensuring that SparkTrials operates correctly within a Spark environment.