The data build tool (dbt) is an effective data transformation tool and it supports key AWS analytics services - Redshift, Glue, EMR and Athena. In part 4 of the dbt on AWS series, we discuss data transformation pipelines using dbt on Amazon EMR on EKS. Subsets of IMDb data are used as source and data models are developed in multiple layers according to the dbt best practices.
We'll discuss how to provision and manage Spark jobs on EMR on EKS with Terraform. Amazon EKS Blueprints for Terraform will be used for provisioning EKS, EMR virtual cluster and related resources. Also Spark job autoscaling will be managed by Karpenter where two Spark jobs with and without Dynamic Resource Allocation (DRA) will be compared.
EMR on EKS is a deployment option in EMR that allows you to automate the provisioning and management of open-source big data frameworks on EKS. It can be an effective way of running spark jobs to manage big data (as well as non-big data) workloads. In this post, weβll discuss EMR on EKS with simple and elaborated examples.