Learn about the different types of processes that can induce a stage boundary in Apache Spark and their significance in optimizing the performance of Spark applications. Get prepared for the Databricks Certified Associate Developer for Apache Spark certification exam.

Question

Which of the following types of processes induces a stage boundary?

A. Shuffle
B. Caching
C. Executor failure
D. Job delegation
E. Application failure

Answer

A. Shuffle

Explanation

In Apache Spark, a stage is a unit of work that consists of a series of tasks that can be executed in parallel. A stage boundary is induced when a shuffle operation is required, such as when data needs to be redistributed across partitions.

Shuffle is the process of redistributing data across the partitions of a dataset, typically to prepare for a subsequent operation such as a join or aggregate. During a shuffle, data is exchanged between nodes in the cluster, which can be a time-consuming operation.

Caching, executor failure, job delegation, and application failure do not induce a stage boundary.

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