SparkTrials is only used for parallelizing model training and cannot be used for hyperparameter tuning.

SparkTrials integrates with Hyperopt to distribute hyperparameter evaluations across a Spark cluster, enabling parallelization for tuning single-node models, but it has limitations in terms of scalability and complexity.

SparkTrials is a standalone tool for parallelization and does not integrate with Hyperopt.

SparkTrials is only used for tuning hyperparameters of distributed models, not single-node models.