AWS Certified Data Engineer - Associate DEA-C01Demo

By Amazon · Question Mode

QuestionQ336

Data Operations and Support

A data engineer is improving query performance in Amazon Athena notebooks that use Apache Spark to analyze large datasets stored in Amazon S3. The data is partitioned.

An AWS Glue crawler updates the partitions.

The data engineer needs to minimize the volume of data scanned to improve the efficiency of Athena queries.

Which solution meets these requirements?

  • A Apply partition filters in the queries.
  • B Increase the frequency of AWS Glue crawler invocations to update the data catalog more often.
  • C Organize the data that is in Amazon S3 by using a nested directory structure.
  • D Configure Spark to use in-memory caching for frequently accessed data.
Explanation

Filtering queries by partition keys enables partition pruning: Athena reads data only from partitions that match the predicates, reducing the data scanned and improving query performance and cost efficiency.

Learn more

Community Discussion

No comments yet. Be the first to start the discussion!