Databricks-Spark-Assoc Spark Architecture and Components Practice Question
Which term describes the unit of work that is dispatched by the Driver to a specific Executor?
⚠ Common exam trap
Candidates frequently confuse 'Task' with 'Job' or 'Stage'. They often think a job is the smallest unit of execution, failing to realize that tasks are the granular units running on individual partitions.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Task
A Task is the smallest unit of execution in Spark. The Driver takes a stage, splits it into multiple tasks based on the partitions of the data, and schedules them for parallel processing on executors. Knowing this is critical for performance tuning; if a job has too many tasks, the overhead of scheduling becomes significant, while too few tasks fail to leverage the available cluster parallelism.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Job
Why it's wrong here
A job is triggered by an action and consists of one or more stages. It is a high-level representation of the computation graph, not the atomic unit of work performed by an executor. The Driver breaks jobs into stages and then tasks, which are then distributed to executors.
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Stage
Why it's wrong here
Stages are a collection of tasks that can be performed without a shuffle. They represent boundaries in the DAG caused by wide dependencies. While stages are important for scheduling, they are not the individual units sent to executors, as executors operate on tasks, not entire stages at once.
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Task
Why this is correct
A task is a single execution unit that runs on one partition of data. It is the final level of granularity in Spark's execution model. The Driver sends these tasks to executors to perform the actual transformations defined in the user's Spark application code on distributed data partitions.
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Executor
Why it's wrong here
An executor is the process that hosts the execution environment, not the unit of work itself. It is a long-lived container that runs tasks. Confusing the execution engine with the work item prevents an understanding of how Spark distributes processing across a cluster of nodes for horizontal scaling.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-Spark-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-Spark-Assoc exam.