Databricks Certified Associate Developer for Apache Spark — Question 99

Which of the following statements about the Spark DataFrame is true?

Answer options

• A. Spark DataFrames are mutable unless they've been collected to the driver.
• B. A Spark DataFrame is rarely used aside from the import and export of data.
• C. Spark DataFrames cannot be distributed into partitions.
• D. A Spark DataFrame is a tabular data structure that is the most common Structured API in Spark.
• E. A Spark DataFrame is exactly the same as a data frame in Python or R.

Correct answer: D

Explanation

The correct answer is D because a Spark DataFrame is indeed a tabular data structure that provides a structured API for working with data in Spark. Option A is incorrect as Spark DataFrames are immutable. Option B is misleading since Spark DataFrames are commonly used for various data processing tasks, not just for data import and export. Option C is false because one of the key features of Spark DataFrames is their ability to be distributed across partitions for parallel processing. Option E is inaccurate as Spark DataFrames have distinct characteristics that differentiate them from data frames in Python or R.