SAP-C02 Continuous Improvement for Existing Solutions Practice Question
A company runs a data processing pipeline on AWS using AWS Glue and Amazon Redshift. Recently, the pipeline has been failing due to insufficient memory in the Glue job. The team wants to improve the pipeline to handle larger datasets without manual intervention. Which solution is MOST cost-effective?
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
✓
Enable job bookmarking and configure incremental processing to reduce data volume per run.
The most cost-effective solution is to enable job bookmarking and configure incremental processing. This reduces the data volume processed per run, thereby preventing memory issues without increasing costs. Increasing DPUs (Option E) would linearly increase cost. Changing Redshift node type (Option B) does not address Glue memory. Replacing Glue with EMR (Option C) adds complexity and may not be more cost-effective. Partitioning input data into more files (Option D) does not directly solve memory issues and can actually increase overhead.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable job bookmarking and configure incremental processing to reduce data volume per run.
Why this is correct
Reduces the amount of data processed each time, preventing memory exhaustion.
- ✗
Use a larger node type for the Amazon Redshift cluster to offload processing.
Why it's wrong here
Redshift does not handle Glue job memory.
- ✗
Replace AWS Glue with Amazon EMR and use spot instances for cost savings.
Why it's wrong here
EMR may be cheaper but requires significant re-architecture.
- ✗
Partition the input data in Amazon S3 into more files with smaller sizes.
Why it's wrong here
Does not reduce total data volume processed per run.
- ✗
Increase the number of DPUs (Data Processing Units) for the Glue job.
Why it's wrong here
Increases cost without addressing the root cause of memory spikes.
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