Databricks-Spark-Assoc Spark Architecture and Components Practice Question
A Spark application is running on a Databricks cluster with 3 worker nodes, each having 4 cores. The application uses the default configuration. How many tasks can run concurrently across the cluster?
⚠ Common exam trap
The trap here is summing the number of nodes and cores instead of multiplying them, or forgetting that concurrency is based on total cores across the cluster.
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
✓
12
The maximum number of concurrent tasks in a Spark cluster is equal to the total number of cores available across all executors. In this scenario, with 3 worker nodes each having 4 cores, the total is 12 cores. Therefore, up to 12 tasks can run in parallel, assuming each task uses one core and there is no dynamic allocation or other constraints.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
4
Why it's wrong here
This is the number of cores per worker node, but concurrency is aggregated across the cluster. The total number of cores across all nodes determines the maximum concurrent tasks. With 3 nodes, the total is 12 cores, so 12 tasks can run in parallel, not just 4.
- ✗
3
Why it's wrong here
This would be the number of worker nodes, but concurrency is determined by the total number of cores available across all executors. Each core can run one task at a time. With 3 nodes and 4 cores each, there are 12 cores, so 12 tasks can run concurrently, not 3.
- ✗
7
Why it's wrong here
This number does not correspond to any obvious default. It might be a miscalculation, such as adding nodes and cores (3+4=7), but concurrency is based on the product of nodes and cores per node, not the sum. The correct number is 12.
- ✓
12
Why this is correct
In Spark, each task runs on one core. The total number of cores across all executors determines the maximum number of concurrent tasks. With 3 worker nodes, each with 4 cores, there are 12 cores available. Assuming default configuration where each node runs one executor using all cores, the cluster can run 12 tasks concurrently.
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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.