Databricks-DE-Assoc Data Ingestion and Loading Practice Question
A data engineer wants to run an incremental ingestion job every six hours. They want to ensure that each run processes all available data and then shuts down the cluster to save costs. Which Trigger should be used in the Structured Streaming code?
⚠ Common exam trap
Candidates frequently choose Trigger.Once, failing to recognize that Trigger.AvailableNow is the modern, scalable replacement for batch-style streaming jobs.
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
✓
Trigger.AvailableNow
Trigger.AvailableNow is the modern replacement for Trigger.Once. It provides better scalability by processing all available data in multiple micro-batches if necessary, while still allowing the job to terminate once all data is processed. This is ideal for cost-effective, periodic batch-style processing of streaming data sources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Trigger.ProcessingTime('6 hours')
Why it's wrong here
This trigger keeps the stream and the cluster running continuously, processing data at the specified interval. It does not shut down the cluster after processing, which would fail to meet the requirement of saving costs by only running the cluster when there is data to be processed periodically.
- ✗
Trigger.Once
Why it's wrong here
While Trigger.Once processes data and then stops, it is limited to a single micro-batch. For very large volumes of data, this single batch might be too large for the cluster to handle efficiently, potentially leading to out-of-memory errors or extremely long processing times compared to more modern alternatives.
- ✓
Trigger.AvailableNow
Why this is correct
Trigger.AvailableNow is designed for this exact use case. It processes all currently available data from the source, potentially splitting it into multiple smaller micro-batches for better performance and stability. Once all data is processed, the query terminates, allowing the cluster to be shut down automatically.
- ✗
Trigger.Continuous('1 minute')
Why it's wrong here
Continuous trigger mode is intended for ultra-low latency applications and requires the cluster to remain active at all times. It is not suitable for a periodic ingestion job that aims to minimize costs by only running for a short duration every six hours before shutting down the infrastructure.
About these practice questions
Courseiva writes every Databricks-DE-Assoc question from scratch — 276 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
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-DE-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-DE-Assoc exam.