Book Image

AWS Certified Database – Specialty (DBS-C01) Certification Guide

By : Kate Gawron
5 (1)
Book Image

AWS Certified Database – Specialty (DBS-C01) Certification Guide

5 (1)
By: Kate Gawron

Overview of this book

The AWS Certified Database – Specialty certification is one of the most challenging AWS certifications. It validates your comprehensive understanding of databases, including the concepts of design, migration, deployment, access, maintenance, automation, monitoring, security, and troubleshooting. With this guide, you'll understand how to use various AWS databases, such as Aurora Serverless and Global Database, and even services such as Redshift and Neptune. You’ll start with an introduction to the AWS databases, and then delve into workload-specific database design. As you advance through the chapters, you'll learn about migrating and deploying the databases, along with database security techniques such as encryption, auditing, and access controls. This AWS book will also cover monitoring, troubleshooting, and disaster recovery techniques, before testing all the knowledge you've gained throughout the book with the help of mock tests. By the end of this book, you'll have covered everything you need to pass the DBS-C01 AWS certification exam and have a handy, on-the-job desk reference guide.
Table of Contents (24 chapters)
1
Part 1: Introduction to Databases on AWS
Free Chapter
2
Chapter 1: AWS Certified Database – Specialty Overview
5
Part 2: Workload-Specific Database Design
12
Part 3: Deployment and Migration and Database Security
16
Part 4: Monitoring and Optimization
20
Part 5: Assessment
21
Chapter 16: Exam Practice

Performance tuning and maintaining a Redshift cluster

Tuning an Amazon Redshift database can make a huge difference to the costs and performance of your application. Amazon Redshift has six main areas you should consider when tuning it:

  • Massively parallel processing
  • Columnar data storage
  • Data compression
  • Query optimizer
  • Result caching
  • Compiled code

We will start by looking at massively parallel processing, which we mentioned briefly in the Overview of Amazon Redshift section.

Massively parallel processing

Parallel processing is when your workload is split across multiple strands to allow for faster querying. In theory, it will be quicker for your work to be done by four different strands simultaneously than by one, even with the overhead of merging the individual strands at the end. With most RDBMSs, the parallelism is contained in a single node, so the maximum speed of the query is limited by the overall resource to that one node, and limits...