PDE Ingesting and Processing the Data Practice Question
A company uses Dataflow to process data with Apache Beam in Python. The pipeline reads from Pub/Sub, applies a ParDo that calls an external API for enrichment, and writes to BigQuery. The external API has rate limits and occasionally fails. To improve reliability, which THREE strategies should be implemented? (Choose 3)
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
✓
Batch multiple requests to the external API using a side input
Retry logic with exponential backoff, a dead letter queue for failed records, and batching requests reduce API pressure and handle failures gracefully.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch from Python to Java SDK for better performance
Why it's wrong here
Language change does not address API failures.
- ✗
Increase the number of Dataflow workers to reduce load per worker
Why it's wrong here
This may increase API calls and worsen rate limiting.
- ✓
Batch multiple requests to the external API using a side input
Why this is correct
Batching reduces the number of API calls, helping with rate limits.
- ✓
Implement retry logic with exponential backoff in the external API call
Why this is correct
Handles transient failures while respecting rate limits.
- ✓
Use a dead letter pattern to write failed records to a separate sink
Why this is correct
Allows later reprocessing without losing data.
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