DEA-C01 Data Operations and Support Practice Question
Which THREE considerations are important when designing a data pipeline that uses AWS Glue to process streaming data from Amazon Kinesis Data Streams? (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
✓
Set the number of Glue workers to match the number of shards for optimal parallelism
A, B, and C are correct. A: Setting the number of Glue workers to match the number of shards ensures optimal parallelism and resource utilization. B: Ensuring sufficient shards in Kinesis Data Streams is essential to handle the expected record rate and avoid throttling. C: Configuring checkpointing in AWS Glue streaming jobs prevents data loss and allows resumption from the last checkpoint on failure. D (batch window) is not appropriate for streaming pipelines as it introduces latency and is more suited for batch processing. E (converting to Avro) is a general data optimization but not a critical consideration specifically for Glue streaming with Kinesis.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Set the number of Glue workers to match the number of shards for optimal parallelism
Why this is correct
Each worker can consume one shard.
- ✓
Ensure the Kinesis stream has enough shards to handle the expected record rate
Why this is correct
Shard count determines throughput.
- ✓
Configure checkpointing to prevent data loss on failure
Why this is correct
Checkpointing allows resume from last processed record.
- ✗
Use batch window to accumulate data before processing
Why it's wrong here
Streaming processing should be near real-time, not batch window.
- ✗
Convert data to Avro format for better compression
Why it's wrong here
Data format choice is independent of streaming considerations.
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