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Data Operations and SupportmediumMultiple ChoiceObjective-mapped

DEA-C01 Data Operations and Support Practice Question

An AWS Glue job that performs data transformation on large Parquet files in Amazon S3 is taking a long time to complete. The job uses the default number of DPUs. Which change would most likely improve the job's performance?

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 'Max capacity' (number of DPUs) for the job.

Increasing the number of DPUs (Option A) adds more parallelism and memory, which directly improves the performance of the Glue job when processing large Parquet files. Option B (coalesce) reduces the number of output files but does not speed up the transformation itself. Option C (reduce partitions) may lead to data skew or out-of-memory errors. Option D (change to CSV) would make processing slower because CSV is less efficient than Parquet.

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 'Max capacity' (number of DPUs) for the job.

    Why this is correct

    More DPUs provide more compute resources.

  • Use 'coalesce' to reduce the number of output files.

    Why it's wrong here

    Coalesce reduces partitions, which can slow processing.

  • Reduce the number of partitions in the source data.

    Why it's wrong here

    Fewer partitions may cause memory issues.

  • Change the input format from Parquet to CSV.

    Why it's wrong here

    CSV is less efficient than Parquet.

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

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