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Data Store ManagementmediumMultiple SelectObjective-mapped

Redshift Query Performance — Sort Keys and Compression Encodings

Which TWO actions can help improve query performance in Amazon Redshift? (Choose two.)

Quick Answer

The answer is to define appropriate sort keys and apply compression encodings to columns. Sort keys improve Amazon Redshift query performance by physically co-locating rows with similar values on disk, which allows the query optimizer to use zone maps to skip irrelevant data blocks during table scans, reducing I/O and speeding up range-restricted queries and merge joins. Compression encodings further reduce storage footprint and the amount of data read from disk, making scans faster. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of Redshift’s physical design choices; a common trap is to confuse sort keys with distribution keys or to think that compression only saves storage without affecting query speed. Remember the memory tip: “Sort to skip, compress to shrink”—sort keys let you skip blocks, compression shrinks what you read.

⚠ Common exam trap

Watch out — candidates often assume scaling out (adding nodes) always speeds up individual queries, but in Redshift, query performance is more dependent on data layout (sort keys, distribution, compression) than on cluster size, and adding nodes primarily benefits concurrent workloads rather than single-query latency.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Use appropriate sort keys for tables.

Defining appropriate sort keys in Amazon Redshift enables the query optimizer to use zone maps to skip irrelevant data blocks during table scans, significantly reducing the amount of data read from disk. Sort keys also improve the effectiveness of merge joins and the performance of range-restricted queries by physically co-locating rows with similar sort key values on disk.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use appropriate sort keys for tables.

    Why this is correct

    Sort keys help the query optimizer scan less data.

  • Disable SSL encryption for connections.

    Why it's wrong here

    Disabling SSL does not improve performance.

  • Use VARCHAR instead of CHAR for fixed-length strings.

    Why it's wrong here

    Choosing data type is not a primary performance improvement technique.

  • Apply compression encodings to columns.

    Why this is correct

    Compression reduces storage and I/O, improving performance.

  • Increase the number of nodes in the cluster.

    Why it's wrong here

    Scaling up may help but is not always the solution and adds cost.

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Same concept, more angles

1 more way this is tested on DEA-C01

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. Which TWO actions can improve query performance on an Amazon Redshift cluster? (Choose two.)

medium
  • A.Define appropriate sort keys
  • B.Increase the number of nodes
  • C.Use EVEN distribution style for all tables
  • D.Use columnar compression
  • E.Run VACUUM command regularly

Why A: Defining appropriate sort keys in Amazon Redshift physically orders data on disk by the sort key columns, enabling the query optimizer to use zone maps to skip large blocks of data that do not match query predicates. This drastically reduces the amount of data scanned, especially for range-restricted queries, improving I/O and overall query performance.

Last reviewed: Jun 24, 2026

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