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DEA-C01 · Question #171

DEA-C01 Question #171: Real Exam Question with Answer & Explanation

The correct answer is C: AUTO distribution. AUTO distribution allows Amazon Redshift to automatically manage the distribution style based on the size of the table. With this option, Redshift chooses the most optimal distribution method, and as the table grows, it will adjust the distribution style to maintain performance.

Data Store Management

Question

A company uses Amazon Redshift as its data warehouse service. A data engineer needs to design a physical data model. The data engineer encounters a de-normalized table that is growing in size. The table does not have a suitable column to use as the distribution key. Which distribution style should the data engineer use to meet these requirements with the LEAST maintenance overhead?

Options

  • AALL distribution
  • BEVEN distribution
  • CAUTO distribution
  • DKEY distribution

Explanation

AUTO distribution allows Amazon Redshift to automatically manage the distribution style based on the size of the table. With this option, Redshift chooses the most optimal distribution method, and as the table grows, it will adjust the distribution style to maintain performance. This minimizes maintenance overhead since the system adapts without the need for manual tuning. ALL distribution copies the entire table to all nodes. It can be useful for small, static tables but is inefficient for large or growing tables as it increases storage and I/O costs significantly. EVEN distribution distributes rows evenly across all nodes. While it reduces data skew, it may not be optimal for larger tables where certain queries would benefit from co-locating data to minimize cross-node traffic. KEY distribution places data based on the values in a specific column (distribution key). Since the question states that no suitable column exists for a distribution key, this method would not be

Topics

#Redshift Data Distribution#AUTO Distribution Style#Physical Data Modeling#Data Warehouse Performance

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