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

Question

Options

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

• B
  6% (1)
• D
  89% (16)
• E
  6% (1)

Explanation

A Spark DataFrame is a distributed, tabular data structure organized into named columns - it is the most common Structured API in Spark and the primary abstraction for data manipulation. The other statements are false: (A) Spark DataFrames are immutable; every transformation returns a new DataFrame rather than modifying the existing one. (B) DataFrames are the core of Spark's ETL, analytics, and ML workflows, not a niche import/export tool. (C) DataFrames are inherently distributed across partitions - that distribution is the source of Spark's parallelism. (E) While conceptually similar to pandas or R data frames, Spark DataFrames are distributed across a cluster and immutable, which are fundamental differences.

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