AWS Certified Data Engineer - Associate DEA-C01Demo

By Amazon · Question Mode

QuestionQ172

Data Operations and Support

A company uses an Amazon Redshift provisioned cluster for its database. The Redshift cluster contains five reserved ra3.4xlarge nodes and uses key distribution.

A data engineer observes that one node frequently has CPU utilization above 90%. SQL queries that execute on that node are queued. During daily operations, the other four nodes generally have CPU utilization below 15%.

The data engineer wants to retain the current number of compute nodes. The data engineer also wants to distribute the load more evenly across all five compute nodes.

Which solution meets these requirements?

  • A Change the sort key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.
  • B Change the distribution key to the table column that has the largest dimension.
  • C Upgrade the reserved node from ra3.4xlarge to ra3.16xlarge.
  • D Change the primary key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.
Explanation

With KEY distribution, rows are placed according to values in the distribution-key column. A poorly chosen key can create data skew, causing one compute node to perform disproportionately more work. Selecting the appropriate distribution key—using the largest dimension based on the size of the filtered dataset—improves data colocation and balances workload across the existing nodes. Sort keys affect block pruning, and primary keys do not determine Redshift data placement.

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