DEA-C01 Data Operations and Support Practice Question
A data engineer is designing a data pipeline that processes streaming data. The pipeline must be able to handle duplicate records and ensure exactly-once processing semantics. Which THREE AWS services or features should the engineer consider? (Choose three.)
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
✓
Amazon EMR with Apache Flink for exactly-once semantics.
The three correct options are A, C, and E. Option A (Amazon EMR with Apache Flink) supports exactly-once processing semantics through checkpointing and fault tolerance. Option C (Amazon Kinesis Data Streams with sequence numbers) enables deduplication to achieve exactly-once processing. Option E (Amazon Kinesis Data Analytics for Apache Flink with idempotent sinks) ensures exactly-once delivery by recognizing and ignoring duplicates. Options B and D are incorrect: Amazon Kinesis Data Firehose provides at-least-once delivery, and Amazon DynamoDB Streams also provides at-least-once delivery, not exactly-once semantics.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Amazon EMR with Apache Flink for exactly-once semantics.
Why this is correct
Flink on EMR provides exactly-once processing via checkpointing.
- ✗
Amazon Kinesis Data Firehose with automatic retries.
Why it's wrong here
Firehose provides at-least-once delivery, not exactly-once.
- ✓
Amazon Kinesis Data Streams with sequence numbers for deduplication.
Why this is correct
Sequence numbers enable deduplication for exactly-once processing.
- ✗
Amazon DynamoDB Streams for change data capture.
Why it's wrong here
DynamoDB Streams is at-least-once.
- ✓
Amazon Kinesis Data Analytics for Apache Flink with idempotent sinks.
Why this is correct
Kinesis Data Analytics supports exactly-once with Flink.
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