AWS Certified Data Analytics Specialty 2021 - Hands-On! - Amazon Redshift Integration/Workload Management (WLM)/Vacuum/A

The video tutorial covers Amazon Redshift's integration with various AWS services like S3, DynamoDB, and EMR. It explains workload management, concurrency scaling, and short query acceleration. The tutorial also discusses the vacuum command and anti-patterns to avoid in Redshift usage.

Which AWS service can be used to automate data movement and transformation in and out of Redshift tables?

• Amazon S3

• AWS Data Pipeline

• AWS Glue

• AWS Lambda

Which AWS service can migrate your data into Amazon Redshift?

• AWS Glue

• Amazon EC2

• AWS Database Migration Service

• AWS Lambda

What is the primary purpose of Redshift Workload Management (WLM)?

• To manage data storage

• To automate data backup

• To prioritize workloads and manage query queues

• To enhance data security

How does concurrency scaling benefit a Redshift cluster?

• By enhancing data visualization

• By reducing storage costs

• By automatically adding cluster capacity for increased read queries

• By improving data encryption

What is the maximum number of queues you can define in manual workload management?

• 8

• 12

• 5

• 10

What is the default concurrency level for the super user queue in manual workload management?

• 10

• 5

• 1

• 15

What is the purpose of short query acceleration in Redshift?

• To enhance data encryption

• To increase storage capacity

• To automate data backup

• To prioritize short running queries over longer ones

Which command in Redshift is used to recover space from deleted rows?

• RECOVER

• VACUUM

• CLEAN

• DELETE

What is an anti-pattern for using Redshift?

• Using it for OLAP queries

• Using it for small datasets

• Using it for data analytics

• Using it with S3

Which type of vacuum operation reinitializes interleaved indexes?

• VACUUM SORT ONLY

• VACUUM REINDEX

• VACUUM DELETE ONLY

• VACUUM FULL