The answer is to set retries=2 on the Dataflow operator. This configuration works because Airflow’s retry mechanism operates at the individual task level, meaning when a task fails, only that specific task is re-executed with its retry count, leaving all upstream tasks—such as the MongoDB extraction and BigQuery load—untouched and their successful outputs intact. On the Google Professional Data Engineer exam, this scenario tests your understanding of Airflow’s task-level retry logic versus workflow-level reruns, a common trap where candidates mistakenly apply retries to the entire DAG or use a backfill. The key distinction is that retries on a single operator isolate the failure to that step, avoiding redundant data movement and preserving completed work. Memory tip: think “task retry, not DAG replay”—if you set retries on the operator, only that task gets another chance.
PDE Designing data processing systems Practice Question
This PDE practice question tests your understanding of designing data processing systems. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A financial services company uses Cloud Composer to orchestrate daily batch jobs. One job extracts data from MongoDB to Cloud Storage, then loads into BigQuery, and finally runs a Dataflow pipeline for aggregations. The Dataflow job fails intermittently. They want to automatically restart only the failed Dataflow job without re-running the earlier extraction and load. Which Airflow operator configuration should they use?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set retries=2 on the Dataflow operator
Option C is correct because setting retries=2 on the Dataflow operator instructs Airflow to automatically restart only that specific task upon failure, without affecting upstream tasks (MongoDB extraction, BigQuery load). This isolates the retry to the Dataflow job, preserving the earlier completed work and avoiding redundant data movement.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Implement a SlaMiss sensor
Why it's wrong here
Used for monitoring SLA misses, not for retrying tasks.
✗
Use a DAG with depends_on_past=True
Why it's wrong here
Controls scheduling based on previous DAG run success, not task-level retry.
✓
Set retries=2 on the Dataflow operator
Why this is correct
Retries automatically re-run the failed task without affecting upstream tasks.
Related concept
Read the scenario before looking for a memorised answer.
✗
Set trigger_rule='one_success' for downstream tasks
Why it's wrong here
Controls when downstream tasks run, but does not retry the failed task.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between task-level retry mechanisms and dependency/trigger rules, so the trap here is confusing `retries` (which restarts the failed task) with `trigger_rule` or `depends_on_past` (which only affect task scheduling or downstream execution).
Detailed technical explanation
How to think about this question
Under the hood, Airflow’s retry mechanism uses the task instance’s `try_number` and `max_retries` to re-schedule the task via the scheduler’s executor (e.g., Celery or Kubernetes). Each retry creates a new task instance with an incremented attempt count, and the operator’s `retry_delay` (default 5 minutes) controls the wait between attempts. In real-world scenarios, intermittent Dataflow failures due to quota limits or transient network issues are effectively handled by retries, while upstream tasks remain in `success` state, avoiding costly re-extraction.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Designing data processing systems — This question tests Designing data processing systems — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set retries=2 on the Dataflow operator — Option C is correct because setting retries=2 on the Dataflow operator instructs Airflow to automatically restart only that specific task upon failure, without affecting upstream tasks (MongoDB extraction, BigQuery load). This isolates the retry to the Dataflow job, preserving the earlier completed work and avoiding redundant data movement.
What should I do if I get this PDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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