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CompTIA DataX DY0-001 (V1) Practice Question

During a performance review of a cloud-based data lake, engineers notice that most analytical queries read only a handful of numeric columns out of hundreds stored in high-volume IoT event logs that arrive as nested JSON objects. They want to cut scan time and storage costs by converting the raw ingestion files to a different format. The ideal replacement format must preserve the events' nested schema, enable column pruning and predicate push-down for efficient querying, and provide high compression without hurting read performance. Which file format best satisfies all of these requirements?

  • Serialize the events as Apache Avro binary files.

  • Keep the events as RFC 4180-compliant CSV text to maximize compatibility.

  • Compress the existing JSON files using GZIP without changing the file format.

  • Convert the events to Apache Parquet files (for example, with Snappy compression).

CompTIA DataX DY0-001 (V1)
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