Public cloud usage for Hadoop workloads is accelerating, and consequently, Hadoop components have adapted to leverage cloud infrastructure, including object storage and elastic compute. Hive, Spark, and Impala are able to read input and write output directly to AWS S3 storage. Since data persisted in S3 lives beyond cluster lifecycles, users can now leverage tools to spin up Hadoop clusters for specific time periods or workloads, grow and shrink the cluster as needed, and terminate clusters when the clusters are no longer being used. Therefore, Hadoop clusters in the public cloud can be both transient and elastic in nature.
Jennifer Wu, Eugene Fratkin, Andrei Savu, and Tony Wu explore best practices for Hadoop deployments in the public cloud and provide detailed guidance for deploying, configuring, and managing Hive, Spark, and Impala in the public cloud as they walk you through using existing tools to create and configure Hive, Spark, and Impala deployments in the AWS environment with considerations for network settings, AWS instances types, and security options. They also demonstrate how Hadoop clusters can also be easily deployed into Azure and Google Cloud Platform. Once deployed, you’ll be able to grow and shrink clusters to accommodate your workloads.
Jennifer Wu is director of product management for cloud at Cloudera, where she focuses on cloud strategy and solutions. Before joining Cloudera, Jennifer worked as a product line manager at VMware, working on the vSphere and Photon system management platforms.
Eugene Fratkin is a director of engineering at Cloudera leading cloud infrastructure efforts. He was one of the founding members of the Apache MADlib project (scalable in-database algorithms for machine learning). Previously, Eugene was a cofounder of a Sequoia Capital-backed company focusing on applications of data analytics to problems of genomics. He holds PhD in computer science from Stanford University’s AI lab.
Andrei Savu is a software engineer at Cloudera, where he’s working on Cloudera Director, a product that makes Hadoop deployments in cloud environments easy and more reliable for customers.
Tony Wu is a team lead of the Partner Enablement Cloud Hardware Infrastructure and Platform (CHIP) team at Cloudera, which is responsible for Microsoft Azure integration for Cloudera Director. Tony focuses on integrating partner solutions (cloud and hardware) with Cloudera software. He is also part of the team responsible for the EMC DSSD integration with Cloudera’s Distribution of Hadoop (CDH) and Cloudera Manager (CM).
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