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Continuous Improvement for Existing SolutionshardMultiple ChoiceObjective-mapped

SAP-C02 Continuous Improvement for Existing Solutions Practice Question

A company has a data pipeline that uses AWS Glue to process large datasets in Amazon S3. The pipeline runs daily and takes over 12 hours to complete. The company wants to reduce the processing time. Which approach would be MOST 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

Increase the number of DPUs allocated to the Glue job.

Increasing the number of DPUs (data processing units) allocated to the Glue job allows for greater parallelism, which directly reduces processing time for CPU-bound or memory-bound workloads. Option A is incorrect because increasing the timeout does not improve performance; it only prevents the job from failing due to time limits. Option B is incorrect because S3 Transfer Acceleration speeds up data transfer to S3, not the processing within Glue. Option D is incorrect because while converting to Parquet can improve read performance and reduce data volume, it does not address the core processing bottleneck if the job is compute-intensive; the most effective immediate step is to increase DPUs.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increase the Glue job timeout setting to 24 hours.

    Why it's wrong here

    Longer timeout does not speed up processing.

  • Enable S3 Transfer Acceleration on the source bucket.

    Why it's wrong here

    Transfer Acceleration improves upload speed, not Glue job processing.

  • Increase the number of DPUs allocated to the Glue job.

    Why this is correct

    More DPUs provide more parallelism and reduce runtime.

  • Convert the input data from CSV to Parquet format.

    Why it's wrong here

    Parquet improves read performance but may not significantly reduce processing time if the bottleneck is compute.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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