Learning Big Data with Amazon Elastic MapReduce
- Length: 242 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2014-10-29
- ISBN-10: 1782173439
- ISBN-13: 9781782173434
- Sales Rank: #3400693 (See Top 100 Books)
Easily learn, build, and execute real-world Big Data solutions using Hadoop and AWS EMR
About This Book
- Learn how to solve big data problems using Apache Hadoop
- Use Amazon Elastic MapReduce to create and maintain cluster infrastructure for big data analytics
- A step-by-step guide exploring the vast set of services provided by Amazon on the cloud
Who This Book Is For
This book is aimed at developers and system administrators who want to learn about Big Data analysis using Amazon Elastic MapReduce. Basic Java programming knowledge is required. You should be comfortable with using command-line tools. Prior knowledge of AWS, API, and CLI tools is not assumed. Also, no exposure to Hadoop and MapReduce is expected.
In Detail
Amazon Elastic MapReduce is a web service used to process and store vast amount of data, and it is one of the largest Hadoop operators in the world. With the increase in the amount of data generated and collected by many businesses and the arrival of cost-effective cloud-based solutions for distributed computing, the feasibility to crunch large amounts of data to get deep insights within a short span of time has increased greatly.
This book will get you started with AWS so that you can quickly create your own account and explore the services provided, many of which you might be delighted to use. This book covers the architectural details of the MapReduce framework, Apache Hadoop, various job models on EMR, how to manage clusters on EMR, and the command-line tools available with EMR. Each chapter builds on the knowledge of the previous one, leading to the final chapter where you will learn about solving a real-world use case using Apache Hadoop and EMR. This book will, therefore, get you up and running with major Big Data technologies quickly and efficiently.
Table of Contents
Chapter 1. Amazon Web Services
Chapter 2. MapReduce
Chapter 3. Apache Hadoop
Chapter 4. Amazon EMR – Hadoop on Amazon Web Services
Chapter 5. Programming Hadoop on Amazon EMR
Chapter 6. Executing Hadoop Jobs on an Amazon EMR Cluster
Chapter 7. Amazon EMR – Cluster Management
Chapter 8. Amazon EMR – Command-line Interface Client
Chapter 9. Hadoop Streaming and Advanced Hadoop Customizations
Chapter 10. Use Case – Analyzing CloudFront Logs Using Amazon EMR
