Exam Associate-Developer-Apache-Spark-3.5 Topic 1 Question 44 Discussion

Actual exam question for Databricks's Associate-Developer-Apache-Spark-3.5 exam
Question #: 44
Topic #: 1
A data engineer is reviewing a Spark application that applies several transformations to a DataFrame but notices that the job does not start executing immediately.
Which two characteristics of Apache Spark's execution model explain this behavior?
Choose 2 answers:

Suggested Answer: B,E Vote an answer

Comprehensive and Detailed Explanation From Exact Extract:
Apache Spark employs a lazy evaluation model for transformations. This means that when transformations (e.
g.,map(),filter()) are applied to a DataFrame, Spark does not execute them immediately. Instead, it builds a logical plan (lineage) of transformations to be applied.
Execution is deferred until an action (e.g.,collect(),count(),save()) is called. At that point, Spark's Catalyst optimizer analyzes the logical plan, optimizes it, and then executes the physical plan to produce the result.
This lazy evaluation strategy allows Spark to optimize the execution plan, minimize data shuffling, and improve overall performance by reducing unnecessary computations.

by Hobart at Oct 13, 2025, 09:08 AM

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