AWS Big Data Blog
Author: Ashwini Kumar
Ashwini Kumar is a Senior Specialist Solutions Architect at AWS based in Delhi, India. Ashwini has more than 18 years of industry experience in systems integration, architecture and software design with more recent experience in Cloud architecture, DevOps, Containers, and Big Data engineering. He helps customers to optimize their cloud spend, minimize compute waste, and improve performance at scale on AWS. He focuses on architectural best practices for various workloads with services including EC2 Spot, AWS Graviton, EC2 Auto Scaling, Amazon EKS, Amazon ECS, and AWS Fargate.
Query big data with resilience using Trino in Amazon EMR with Amazon EC2 Spot Instances for less cost
New enhancements in Trino with Amazon EMR provide improved resiliency for running ETL and batch workloads on Spot Instances with reduced costs. This post showcases the resilience of Amazon EMR with Trino using fault-tolerant configuration to run long-running queries on Spot Instances to save costs. We simulate Spot interruptions on Trino worker nodes by using AWS Fault Injection Simulator (AWS FIS).