Databricks-Spark-Assoc Spark Architecture and Components Practice Question
A Spark application running on a Databricks cluster uses a broadcast variable to distribute a small lookup table to all executors. During execution, the driver serializes the broadcast variable and sends it to each executor. Which component is responsible for storing the broadcast data on the executor side and making it available to tasks?
⚠ Common exam trap
The trap here is assuming that the Task Scheduler or Shuffle Service handles broadcast data storage, when it is actually the Block Manager.
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
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Block Manager
Broadcast variables are distributed to executors using a BitTorrent-like protocol, and each executor's Block Manager stores the data. The Block Manager caches the broadcast data in memory and makes it available to tasks. This avoids shipping the data with each task, reducing network overhead and memory usage. The Block Manager is integral to Spark's storage layer.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Block Manager
Why this is correct
The Block Manager on each executor is responsible for storing broadcast data. When the driver broadcasts a variable, it sends the data to each executor's Block Manager, which caches it in memory (and optionally on disk). Tasks can then access the broadcast variable locally without network overhead. This is a core part of Spark's broadcast mechanism.
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Task Scheduler
Why it's wrong here
The Task Scheduler schedules tasks on executors but does not store broadcast data. It is responsible for launching tasks and handling retries. Broadcast data storage is handled by the Block Manager, which is a separate component. The Task Scheduler may reference broadcast variables but does not manage their storage or distribution.
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Shuffle Service
Why it's wrong here
The Shuffle Service (e.g., external shuffle service) manages shuffle data, not broadcast variables. It stores intermediate shuffle files for fetch by reducers. Broadcast variables are distributed via a different mechanism involving the Block Manager. Thus, the Shuffle Service is not involved in storing broadcast data on executors.
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DAG Scheduler
Why it's wrong here
The DAG Scheduler creates stages and submits tasks but does not handle data storage. It operates at the stage level and does not interact with broadcast variables. The storage of broadcast data is a runtime concern handled by the Block Manager on each executor. Therefore, the DAG Scheduler is not responsible for this.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
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.