Version Control with Git - Powerful tools and techniques for collaborative software development

In order to thoroughly understand what makes Linux tick and why it works so well on a wide variety of systems, you need to delve deep into the heart of the kernel. The kernel handles all interactions between the CPU and the external world, and determines which programs will share processor time, in what order. It manages limited memory so well that hundreds of processes can share the system efficiently, and expertly organizes data transfers so that the CPU isn't kept waiting any longer than necessary for the relatively slow disks.

The third edition of Understanding the Linux Kernel takes you on a guided tour of the most significant data structures, algorithms, and programming tricks used in the kernel. Probing beyond superficial features, the authors offer valuable insights to people who want to know how things really work inside their machine. Important Intel-specific features are discussed. Relevant segments of code are dissected line by line. But the book covers more than just the functioning of the code; it explains the theoretical underpinnings of why Linux does things the way it does.

This edition of the book covers Version 2.6, which has seen significant changes to nearly every kernel subsystem, particularly in the areas of memory management and block devices. The book focuses on the following topics:

• Memory management, including file buffering, process swapping, and Direct memory Access (DMA)
• The Virtual Filesystem layer and the Second and Third Extended Filesystems
• Process creation and scheduling
• Signals, interrupts, and the essential interfaces to device drivers
• Timing
• Synchronization within the kernel
• Interprocess Communication (IPC)
• Program execution

Understanding the Linux Kernel will acquaint you with all the inner workings of Linux, but it's more than just an academic exercise. You'll learn what conditions bring out Linux's best performance, and you'll see how it meets the challenge of providing good system response during process scheduling, file access, and memory management in a wide variety of environments. This book will help you make the most of your Linux system.

Until now, design patterns for the MapReduce framework have been scattered among various research papers, blogs, and books. This handy guide brings together a unique collection of valuable MapReduce patterns that will save you time and effort regardless of the domain, language, or development framework you’re using.

Each pattern is explained in context, with pitfalls and caveats clearly identified to help you avoid common design mistakes when modeling your big data architecture. This book also provides a complete overview of MapReduce that explains its origins and implementations, and why design patterns are so important. All code examples are written for Hadoop.

• Summarization patterns: get a top-level view by summarizing and grouping data
• Filtering patterns: view data subsets such as records generated from one user
• Data organization patterns: reorganize data to work with other systems, or to make MapReduce analysis easier
• Join patterns: analyze different datasets together to discover interesting relationships
• Metapatterns: piece together several patterns to solve multi-stage problems, or to perform several analytics in the same job
• Input and output patterns: customize the way you use Hadoop to load or store data

"A clear exposition of MapReduce programs for common data processing patterns—this book is indespensible for anyone using Hadoop."

--Tom White, author of Hadoop: The Definitive Guide

Three of CouchDB's creators show you how to use this document-oriented database as a standalone application framework or with high-volume, distributed applications. With its simple model for storing, processing, and accessing data, CouchDB is ideal for web applications that handle huge amounts of loosely structured data. That alone would stretch the limits of a relational database, yet CouchDB offers an open source solution that's reliable, scales easily, and responds quickly.

CouchDB works with self-contained data that has loose or ad-hoc connections. It's a model that fits many real-world items, such as contacts, invoices, and receipts, but you'll discover that this database can easily handle data of any kind. With this book, you'll learn how to work with CouchDB through its RESTful web interface, and become familiar with key features such as simple document CRUD (create, read, update, delete), advanced MapReduce, deployment tuning, and more.

• Understand the basics of document-oriented storage and manipulation
• Interact with CouchDB entirely though HTTP using its RESTful interface
• Model data as self-contained JSON documents
• Handle evolving data schemas naturally
• Query and aggregate data in CouchDB using MapReduce views
• Replicate data between nodes
• Tune CouchDB for increased performance and reliability

“[Chertkow and Feehan] are the ideal mentors for aspiring indie musicians who want to navigate an ever-changing music industry.” —Billboard Magazine

Newly revised and expanded, the acclaimed handbook for musicians looking to write, record, and promote without a label 

More musicians are recording, distributing, marketing, and selling their own music now than ever before in history. The Indie Band Survival Guide is the critically-acclaimed, do-it-yourself modern classic that has been telling them how for years.