Big Data: Principles and best practices of scalable realtime data systems

Big Data: Principles and best practices of scalable realtime data systems
Nathan Marz (Author), James Warren (Author)

New!: $49.99 $26.36 (as of 05/11/2013 08:31 PST)

Hardware

Services like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database. As scale and demand increase, so does Complexity. Fortunately, scalability and simplicity are not mutually exclusive—rather than using some trendy technology, a different approach is needed. Big data systems use many machines working in parallel to store and process data, which introduces fundamental challenges unfamiliar to most developers.

Big Data shows how to build these systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy to understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to use them in practice, and how to deploy and operate them once they're built.

Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

• Rank: #57295 in Books
• Published on: 2013-09-28
• Original language: English
• Number of items: 1
• Binding: Paperback
• 425 pages

Hadoop Real World Solutions Cookbook

Hadoop Real World Solutions Cookbook
Jonathan R. Owens (Author), Brian Femiano (Author), Jon Lentz (Author)

Download: $16.19 (as of 02/17/2013 10:47 PST)

Hardware

In Detail

Helping developers become more comfortable and proficient with solving problems in the Hadoop space. People will become more familiar with a wide variety of Hadoop related tools and best practices for implementation.

Hadoop Real World Solutions Cookbook will teach readers how to build solutions using tools such as Apache Hive, Pig, MapReduce, Mahout, Giraph, HDFS, Accumulo, Redis, and Ganglia.

Hadoop Real World Solutions Cookbook provides in depth explanations and code examples. Each chapter contains a set of recipes that pose, then solve, technical challenges, and can be completed in any order. A recipe breaks a single problem down into discrete steps that are easy to follow. The book covers (un)loading to and from HDFS, graph analytics with Giraph, batch data analysis using Hive, Pig, and MapReduce, machine learning approaches with Mahout, debugging and troubleshooting MapReduce, and columnar storage and retrieval of structured data using Apache Accumulo.

Hadoop Real World Solutions Cookbook will give readers the examples they need to apply Hadoop technology to their own problems.

Approach

Cookbook recipes demonstrate Hadoop in action and then explain the concepts behind the code.

Who this book is for

This book is ideal for developers who wish to have a better understanding of Hadoop application development and associated tools, and developers who understand Hadoop conceptually but want practical examples of real world applications.

• Rank: #36216 in eBooks
• Published on: 2013-02-07
• Released on: 2013-02-07
• Format: Kindle eBook
• Number of items: 1