Databricks Machine Learning Associate exam dumps

Databricks Machine Learning Associate practice question 336 of 656

Databricks Certified Machine Learning Associate. Associate level, Databricks. Free question with the correct answer and a full explanation.

Databricks Machine Learning Associate Question 336

Select 3

Why might using the Pandas API on Spark with InternalFrame be slower compared to native Spark operations?

  1. A

    InternalFrame creates additional metadata to maintain compatibility with the Pandas API, which introduces overhead.

  2. B

    InternalFrame automatically optimizes Spark's query execution, making operations slower.

  3. C

    InternalFrame requires extra transformations to align Spark DataFrame operations with Pandas semantics.

  4. D

    InternalFrame causes data movement between Spark partitions to emulate Pandas-like row-based operations.

  5. E

    InternalFrame is designed to prioritize memory efficiency over computational speed.

Show answer and explanation

Correct answers: A, C, D

Explanation

The Pandas API on Spark uses an InternalFrame to manage metadata and ensure compatibility with Pandas semantics. This introduces additional overhead, transformations, and potential data movement, making it slower than native Spark operations. Native Spark is optimized for distributed computing, whereas the InternalFrame prioritizes functionality that mimics Pandas' behavior.

  • A. Correct.

    Correct: InternalFrame maintains metadata to bridge the Pandas API with Spark, which adds processing overhead and reduces performance compared to native Spark.

  • B. Incorrect.

    Incorrect: InternalFrame does not optimize Spark's query execution; instead, it introduces complexity to support Pandas-like behavior.

  • C. Correct.

    Correct: InternalFrame requires additional transformations to ensure Pandas-style behavior, which can slow down operations compared to native Spark.

  • D. Correct.

    Correct: InternalFrame may cause extra data movement between partitions to match Pandas-like operations, leading to slower performance.

  • E. Incorrect.

    Incorrect: InternalFrame is not explicitly designed for memory efficiency but rather for compatibility with the Pandas API.

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