PYSPARK PRACTICEPySpark PracticeAdvancedQuestion 1 of 20%CachingInterview questionSelect one answerWhen is caching a DataFrame most useful?AWhen an expensive result is reused and the memory/storage trade-off is justifiedBFor every DataFrame by defaultCTo guarantee a join has no duplicatesDTo replace checkpointing in all cases PreviousSubmit answer