AWS Certified Data Engineer - Associate DEA-C01Demo

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QuestionQ49

Data Ingestion and Transformation

A company plans to use Apache Spark jobs running on an Amazon EMR cluster to process streaming data. The Spark jobs will transform the data and store it in an Amazon S3 bucket. The company will use Amazon Athena for analysis.

The company must optimize the data format for analytical queries.

Which solutions meet these requirements with the SHORTEST query times?

Choose two
  • A Use Avro format. Use AWS Glue Data Catalog to track schema changes.
  • B Use ORC format. Use AWS Glue Data Catalog to track schema changes.
  • C Use Apache Parquet format. Use an external Amazon DynamoDB table to track schema changes.
  • D Use Apache Parquet format. Use AWS Glue Data Catalog to track schema changes.
  • E Use ORC format. Store schema definitions in separate files in Amazon S3.
Explanation

Apache Parquet and ORC are columnar formats optimized for Athena analytics. They reduce scanned data through column-oriented compression, predicate pushdown, and parallel reads, producing faster queries than row-oriented Avro. AWS Glue Data Catalog provides the table and schema metadata Athena uses to query data stored in Amazon S3.

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