Unlock the key to acing the Databricks Certified Associate Developer for Apache Spark certification exam by understanding the role of stages in Apache Spark’s execution model.
Table of Contents
Question
Which of the following identifies multiple narrow operations that are executed in sequence?
A. Slot
B. Job
C. Stage
D. Task
E. Executor
Answer
C. Stage
Explanation
A stage in the Databricks Certified Associate Developer for Apache Spark certification Exam represents a set of one or more tasks that are executed as a single unit. Stages are a fundamental concept in Apache Spark, as they define the boundaries between the different phases of a Spark application’s execution.
Specifically, a stage identifies a set of narrow transformations that are executed in sequence. Narrow transformations are those that can be executed independently on each partition, without requiring data shuffling or exchange between partitions.
In contrast, a job encompasses the entire set of stages required to execute a Spark action. A task represents the smallest unit of work that is executed on an individual partition by an executor. An executor is the process that actually runs the Spark tasks, and a slot refers to the resources allocated to a single executor.
Therefore, the correct answer that identifies multiple narrow operations executed in sequence is a stage.
Databricks Certified Associate Developer for Apache Spark certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Databricks Certified Associate Developer for Apache Spark exam and earn Databricks Certified Associate Developer for Apache Spark certification.