DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is troubleshooting a daily batch ingestion pipeline that uses AWS Glue to read CSV files from Amazon S3 and write Parquet files to another S3 bucket. The job runs successfully but takes significantly longer than expected. The engineer notices that the input data is highly skewed with many small files. Which is the most effective optimization to reduce job duration?
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 the 'groupFiles' option in the S3 source configuration
The 'groupFiles' option in AWS Glue's S3 source configuration allows Glue to combine small files into larger splits, reducing the number of tasks and the overhead associated with processing many small files. This directly addresses the high skew and small file issue, significantly reducing job duration. Option A is incorrect because changing the output format from Parquet to JSON would likely increase file size and processing time, not reduce it. Option C is incorrect because increasing DPUs may improve parallelism but does not solve the file-level overhead; it could even be wasteful if the bottleneck is task scheduling. Option D is incorrect because enabling the schema registry is unrelated to file grouping; it is used for schema management and validation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Change the output format to JSON
Why it's wrong here
JSON is text-based and row-oriented, so it removes Parquet's columnar compression and predicate pushdown, worsening runtime on skewed small files. JSON output suits downstream consumers needing human-readable interchange, not a batch job whose bottleneck is file count and partition skew.
- ✓
Enable the 'groupFiles' option in the S3 source configuration
Why this is correct
The 'groupFiles' option coalesces multiple small CSV files into larger partitions during the S3 read, reducing per-file overhead and task count. This directly addresses the many-small-files skew identified in the stem, cutting the job's overall duration.
- ✗
Increase the number of DPUs allocated to the job
Why it's wrong here
Adding DPUs scales worker count but leaves the skewed partition and many-small-files layout unchanged, so one task still dominates and file-open overhead persists. Extra DPUs suit CPU- or memory-bound jobs with balanced partitions, not skew caused by uneven key distribution.
- ✗
Enable the 'use_glue_schema_registry' option
Why it's wrong here
Schema registry integration validates and resolves record schemas during streaming reads; it does not coalesce small files or redistribute skewed partitions. It is the right choice when Glue must enforce Avro schema versions against a Kafka or Kinesis stream, not for compacting many small CSV objects before Parquet conversion.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.