Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

An AWS Glue Spark job joins a 500 GB clickstream fact table stored as partitioned Parquet files in Amazon S3 with a 40 MB reference table of country codes. The join causes lengthy shuffle stages and high network traffic. Without adding nodes or executors, which code change will most effectively reduce shuffle and shorten the job's runtime?

  • Repartition both DataFrames by a randomly generated salt column, then perform the join.

  • Raise the spark.sql.shuffle.partitions configuration value to double the current setting.

  • Convert both datasets from Parquet to CSV so the executor reads smaller individual files.

  • Apply the broadcast() or /*+ BROADCAST */ hint to the country-codes DataFrame before performing the join.

AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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