Preparing Practice Exam…
Please wait a moment while the system generates the exam questions, answers, and study session.
Please wait a moment while the system generates the exam questions, answers, and study session.
Databricks Certified Associate Developer for Apache Spark · Databricks
Select one answer.
Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.
- Correct answer : A — Three separate jobs, because Spark launches one job per action, and each job is then broken into stages and tasks that run on the executors. A . Correct. Each action triggers Spark's lazy-evaluated transformations to actually execute, and the driver submits a distinct job per action, which is then split into stages and tasks. B . Incorrect. Spark does not defer job submission to the end of the script; each action independently triggers its own job as soon as it is called. C . Incorrect. `count()` still requires reading and aggregating the underlying partitions across executors; it is not resolved purely inside the driver without executor work. D . Incorrect. Each action produces its own job in the Spark UI; `collect()` and `count()` are not merged into a job triggered by an unrelated `write.parquet` call on a different DataFrame. E . Incorrect. Job counting is tied to actions, not to shared lineage or a shared SparkSession; three actions on three DataFrames still produce three jobs even under one session.