Answer-first summary for fast verification
Answer: Spark RDD Persistence
The correct answer is **Spark RDD Persistence**. This feature allows for the caching or persisting of intermediate data in memory, which is crucial for reducing computation time during iterative processing. By storing and reusing data in memory, it avoids the need to recompute from the original source, making it especially beneficial for machine learning tasks that involve multiple iterations. While Spark MLlib offers machine learning functionalities, RDD Persistence is a core Spark feature designed for efficient data caching in distributed computations.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
Your team is working on a distributed machine learning model that requires iterative processing. Which Spark feature enables the caching of intermediate data in memory to speed up iterative computations?
A
Spark SQL
B
Spark MLlib
C
Spark GraphX
D
Spark RDD Persistence
No comments yet.