You're reading from AWS for Solutions Architects The definitive guide to AWS Solutions Architecture for migrating to, building, scaling, and succeeding in the cloud

Product type Paperback

Published in Apr 2023

Publisher Packt

ISBN-13 9781803238951

Length 692 pages

Edition 2nd Edition

Tools

AWS

Concepts

Cloud Computing

Authors (4):

Neelanjali Srivastav

Saurabh Shrivastava

Alberto Artasanchez

Imtiaz Sayed

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Table of Contents (19) Chapters

AWS for Solutions Architects, Second Edition: Design your cloud infrastructure by implementing DevOps, containers, and Amazon Web Services

1 Understanding AWS Principles and Key Characteristics FREE CHAPTER

2 Understanding AWS Well-Architected Framework and Getting Certified

3 Leveraging the Cloud for Digital Transformation

4 Networking in AWS

5 Storage in AWS – Choosing the Right Tool for the Job

6 Harnessing the Power of Cloud Computing

7 Selecting the Right Database Service

8 Best Practices for Application Security, Identity, and Compliance

9 Dive efficiency with Cloud Operation Automation and DevOps in AWS

10 Bigdata and streaming data processing in AWS

11 Datawarehouse, Data Query and Visualization in AWS

12 Machine Learning, IoT, and Blockchain in AWS

13 Containers in AWS

14 Microservice and Event-Driven Architectures

15 Domain-Driven Design

16 Data Lake Patterns – Integrating Your Data across the Enterprise

17 Availability, Reliability, and Scalability Patterns

18 AWS Hands-On Lab and Use Case

Understanding EMR file system

To run a large data workload, you need scalable storage and a file system to support that storage. One major differentiation for EMR is its support for S3, for which AWS built a propriety file system called EMRFS (EMR file system), which continues supporting other traditional file systems. Let's look into file systems supported by EMR:

HDFS (Hadoop Distributed File System) - HDFS is a distributed, scalable, and portable file system for Hadoop. An advantage of HDFS is data awareness between the Hadoop cluster nodes managing the clusters and the Hadoop cluster nodes managing the individual steps. For more information, see https://hadoop.apache.org/docs/stable/. The leader and core nodes use HDFS. One advantage is that it's fast; a disadvantage is its ephemeral storage which is reclaimed when the cluster ends. It's best used for caching the results produced by intermediate job-flow steps.
EMRFS (EMR File System) - EMRFS is an implementation of...

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Table of Contents (19) Chapters