AWS Certified Data Analytics Specialty 2021 – Hands-On - Redshift Resizing (Elastic Versus Classic) and New Redshift Fea

The video tutorial explains how to resize Amazon Redshift clusters using Elastic and Classic Resize methods. Elastic Resize allows quick addition or removal of nodes with minimal downtime, while Classic Resize is used for changing node types, which can take longer. Snapshot Restore Resize is a strategy to minimize downtime during Classic Resize. New features like RA3 nodes and Data Lake Export are introduced, allowing independent scaling of compute and storage and exporting queries to S3 in Parquet format.

What is a key advantage of using Elastic Resize for Redshift clusters?

• It supports all node types without limitations.

• It provides unlimited scaling options.

• It minimizes downtime while adding or removing nodes.

• It allows changing node types quickly.

Which method should be used if you need to change the node type in a Redshift cluster?

• Data Lake Export

• Classic Resize

• Snapshot Restore

• Elastic Resize

How does the snapshot restore resize technique help during a Classic Resize?

• It reduces the time needed for resizing.

• It allows the cluster to remain writable.

• It keeps the cluster available by using a copy.

• It automatically adjusts node types.

What is a benefit of using RA3 nodes in Redshift?

• They provide unlimited storage capacity.

• They enable independent scaling of compute and storage.

• They automatically optimize query performance.

• They allow for simultaneous scaling of compute and storage.

Why is the Apache Parquet format beneficial for Redshift Data Lake Export?

• It automatically encrypts data.

• It is faster to unload and uses less storage.

• It is compatible with all AWS services.

• It supports real-time data processing.