AWS Certified Data Analytics Specialty 2021 - Hands-On! - Amazon Redshift Resizing (Elastic vs. Classic) and new Redshif

The video tutorial explains how to resize Amazon Redshift clusters using elastic and classic resize methods. Elastic resize allows quick adjustments with minimal downtime, while classic resize is more involved and can take longer. The tutorial also covers snapshot restore resize to minimize downtime during classic resize. New features like RA3 nodes and Redshift data lake export are introduced, enabling independent scaling of compute and storage, and efficient data export in Parquet format.

What is a key advantage of using elastic resize for a Redshift cluster?

• It requires a complete cluster shutdown.

• It can be used to scale storage independently.

• It minimizes downtime to a few minutes.

• It allows changing the node types.

Which of the following is a limitation of elastic resize?

• It requires a full backup before resizing.

• It can only be performed during off-peak hours.

• It is limited to doubling or halving the cluster size for certain node types.

• It can only be used with RA3 nodes.

What is a potential drawback of using classic resize for a Redshift cluster?

• It requires additional storage capacity.

• It can only be used with DC-2 nodes.

• It may result in the cluster being read-only for an extended period.

• It automatically scales compute and storage together.

How does snapshot restore resize help during a classic resize operation?

• It allows for immediate write access to the new cluster.

• It enables the old cluster to continue receiving data while the new cluster is being resized.

• It reduces the cost of resizing operations.

• It automatically upgrades the node types.

What is a benefit of using RA3 nodes in Redshift?

• They allow for simultaneous scaling of compute and storage.

• They automatically partition data by date.

• They enable independent scaling of compute and storage capacities.

• They are compatible only with Redshift Spectrum.