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Hadoop: The Definitive Guide
by Tom White

Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters.

You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN).

  • Store large datasets with the Hadoop Distributed File System (HDFS)
  • Run distributed computations with MapReduce
  • Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence
  • Discover common pitfalls and advanced features for writing real-world MapReduce programs
  • Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud
  • Load data from relational databases into HDFS, using Sqoop
  • Perform large-scale data processing with the Pig query language
  • Analyze datasets with Hive, Hadoop’s data warehousing system
  • Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems

Data-intensive Text Processing with MapReduce
by Jimmy Lin, Chris Dyer

Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader “think in MapReduce”, but also discusses limitations of the programming model as well.

This volume is a printed version of a work that appears in the Synthesis Digital Library of Engineering and Computer Science. Synthesis Lectures provide concise, original presentations of important research and development topics, published quickly, in digital and print formats. For more information visit

Eloquent JavaScript, 2nd Ed.
by Marijn Haverbeke

JavaScript lies at the heart of almost every modern web application, from social apps to the newest browser-based games. Though simple for beginners to pick up and play with, JavaScript is a flexible, complex language that you can use to build full-scale applications.

Eloquent JavaScript, 2nd Edition dives deep into the JavaScript language to show you how to write beautiful, effective code. Author Marijn Haverbeke immerses you in example code from the start, while exercises and full-chapter projects give you hands-on experience with writing your own programs. As you build projects such as an artificial life simulation, a simple programming language, and a paint program, you’ll learn:
–The essential elements of programming, including syntax, control, and data
–How to organize and clarify your code with object-oriented and functional programming techniques
–How to script the browser and make basic web applications
–How to use the DOM effectively to interact with browsers
–How to harness Node.js to build servers and utilities

This edition is thoroughly revised and modernized to reflect the current state of Java­Script and web browsers, with brand-new material, such as a chapter on code performance in Java­Script, and expanded coverage of recursion and closures. All source code is available online in an inter­active sandbox, where you can edit the code, run it, and see its output instantly.

Isn’t it time you became fluent in the language of the Web?

Includes an exclusive chapter, only available in the No Starch Press edition!

Nuclear war survival skills
by Cresson H. Kearny

Mining of Massive Datasets
by Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets and clustering. This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction.

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