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Big Data Now: 2016 Edition
book

Big Data Now: 2016 Edition

by O'Reilly Media, Inc.
February 2017
Beginner to intermediate
160 pages
3h 43m
English
O'Reilly Media, Inc.
Content preview from Big Data Now: 2016 Edition

Chapter 4. Cloud Infrastructure

In this chapter, Rich Morrow outlines the differentiators between the major cloud service providers—Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP)—as a guide for choosing where to launch a managed or unmanaged Hadoop cluster. Then Michael Li and Ariel M’ndange-Pfupfu compare AWS and GCP in terms of cost, performance, and runtime of a typical Spark workload. Finally, Arti Garg and Parviz Deyhim explore how tools like AWS Auto Scaling enable customers to automatically provision resources to meet real-time demand (i.e., scale up or scale down), leading to significant cost savings.

Where Should You Manage a Cloud-Based Hadoop Cluster?

You can read this post on oreilly.com here.

It’s no secret that Hadoop and public cloud play very nicely with each other. Rather than having to provision and maintain a set number of servers and expensive networking equipment in house, Hadoop clusters can be spun up in the cloud as a managed service, letting users pay only for what they use, only when they use it.

The scalability and per-workload customizability of public cloud is also unmatched. Rather than having one predefined set of servers (with a set amount of RAM, CPU, and network capability) in-house, public cloud offers the ability to stand up workload-specific clusters with varying amounts of those resources tailored for each workload. The access to “infinite” amounts of hardware that public cloud offers is also a ...

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Publisher Resources

ISBN: 9781492049197