Step-by-step Through a Spectrum Query
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This course covers Amazon Redshift Spectrum, including what it is, what it does, how it works, and some points to take into consideration when using Redshift Spectrum.

Learning Objectives

  • How to manage cold data in Redshift using Amazon S3
  • What Amazon Redshift Spectrum is and does
  • How Spectrum Queries work
  • Supported data formats of Spectrum
  • File optimization using Spectrum
  • Amazon Redshift Spectrum Considerations

Intended Audience

This course is intended for people that want to learn more about Amazon Redshift Spectrum and how it can be used to perform SQL queries on data stored in Amazon S3.


To get the most from this course, you should have a basic understanding of Amazon Redshift, Amazon Athena, AWS Glue, and data analytics concepts.


Step-by-Step Through a Spectrum Query. When an external table is queried using Spectrum, the process is like a standard query on a Redshift cluster. The query starts in the cluster's Leader Node and the Leader Node optimizes it and determines which parts are to be run locally on the cluster and in which parts go to Spectrum. The Leader Node sends a Query Plan to all of the compute nodes. The compute nodes obtain partition information from the data catalog and ignore the ones they do not need. The compute nodes request data from the Spectrum nodes and the Spectrum nodes scan the data stored in S3 and then filter, join and aggregate the data as needed. The final aggregation and joins, however, are done in the local Redshift cluster. First in the compute nodes and then finally in the Leader Node. The final step is when the Leader Node aggregates the data and returns the required output.

About the Author
Learning Paths

Stephen is the AWS Certification Specialist at Cloud Academy. His content focuses heavily on topics related to certification on Amazon Web Services technologies. He loves teaching and believes that there are no shortcuts to certification but it is possible to find the right path and course of study.

Stephen has worked in IT for over 25 years in roles ranging from tech support to systems engineering. At one point, he taught computer network technology at a community college in Washington state.

Before coming to Cloud Academy, Stephen worked as a trainer and curriculum developer at AWS and brings a wealth of knowledge and experience in cloud technologies.

In his spare time, Stephen enjoys reading, sudoku, gaming, and modern square dancing.