By staying current, remaining relevant, and adapting to emerging course needs, this market-leading text has continued to define the operating systems course. This Seventh Edition not only presents the latest and most relevant systems, it also digs deeper to uncover those fundamental concepts that have remained constant throughout the evolution of today's operation systems. With this strong conceptual foundation in place, students can more easily understand the details related to specific systems. New Adaptations * Increased coverage of user perspective in Chapter 1. * Increased coverage of OS design throughout. * A new chapter on real-time and embedded systems (Chapter 19). * A new chapter on multimedia (Chapter 20). * Additional coverage of security and protection. * Additional coverage of distributed programming. * New exercises at the end of each chapter. * New programming exercises and projects at the end of each chapter. * New student-focused pedagogy and a new two-color design to enhance the learning process.

    You've got the programming chops, you're up on the latest tech, you're sitting at your workstation... now what? New Programmer's Survival Manual gives your career the jolt it needs to get going: essential industry skills to help you apply your raw programming talent and make a name for yourself. It's a no-holds-barred look at what really goes on in the office--and how to not only survive, but thrive in your first job and beyond. Programming at industry level requires new skills - you'll build programs that dwarf anything you've done on your own. This book introduces you to practices for working on large-scale, long-lived programs at a professional level of quality. You'll find out how to work efficiently with your current tools, and discover essential new tools. But the tools are only part of the story; you've got to get street-smart too. Succeeding in the corporate working environment requires its own savvy. You'll learn how to navigate the office, work with your teammates, and how to deal with other people outside of your department. You'll understand where you fit into the big picture and how you contribute to the company's success. You'll also get a candid look at the tougher aspects of the job: stress, conflict, and office politics. Finally, programming is a job you can do for the long haul. This book helps you look ahead to the years to come, and your future opportunities--either as a programmer or in another role you grow into. There's nothing quite like the satisfaction of shipping a product and knowing, "I built that." Whether you work on embedded systems or web-based applications, in trendy technologies or legacy systems, this book helps you get from raw skill to an accomplished professional.

    As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way.Expanded from Tyler Akidau's popular blog posts Streaming 101 and Streaming 102, this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You'll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax.You'll explore:How streaming and batch data processing patterns compareThe core principles and concepts behind robust out-of-order data processingHow watermarks track progress and completeness in infinite datasetsHow exactly-once data processing techniques ensure correctnessHow the concepts of streams and tables form the foundations of both batch and streaming data processingThe practical motivations behind a powerful persistent state mechanism, driven by a real-world exampleHow time-varying relations provide a link between stream processing and the world of SQL and relational algebra

    "Machine learning," the process of automating tasks once considered the domain of highly-trained analysts and mathematicians, is the key to efficiently extracting useful information from this sea of raw data. Machine Learning in Action is a unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. In it, the author uses the flexible Python programming language to show how to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification.