But with so many distributed databases and tools available today, it’s often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.Throughout the book, you’ll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You’ll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed.This book examines:Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable log structured storage engines, with differences and use-cases for eachDistributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns, from UDP to reliable consensus protocolsDatabase clusters: Discover how to achieve consistent models for replicated data

    Readers will progress from building a basic physics engine to creating intelligent moving objects and complex systems, setting the foundation for further experiments in generative design. Subjects covered include forces, trigonometry, fractals, cellular automata, self-organization, and genetic algorithms. The book's examples are written in Processing, an open-source language and development environment built on top of the Java programming language. On the book's website (http://www.natureofcode.com), the examples run in the browser via Processing's JavaScript mode.

    Cooper details many of these meta functions to explain his central thesis: programmers need to seriously re-evaluate the many user-hostile concepts deeply embedded within the software development process. Rather than provide users with a straightforward set of options, programmers often pile on the bells and whistles and ignore or de-prioritise lingering bugs. For the average user, increased functionality is a great burden, adding to the recurrent chorus that plays: "computers are hard, mysterious, unwieldy things." (An average user, Cooper asserts, who doesn't think that way or who has memorised all the esoteric commands and now lords it over others, has simply been desensitised by too many years of badly designed software.) Cooper's writing style is often overblown, with a pantheon of cutesy terminology (i.e. "dancing bearware") and insider back-patting. (When presenting software to Bill Gates, he reports that Gates replied: "How did you do that?" to which he writes: "I love stumping Bill!") More seriously, he is also unable to see beyond software development's importance--a sin he accuses programmers of throughout the book. Even with that in mind, the central questions Cooper asks are too important to ignore: Are we making users happier? Are we improving the process by which they get work done? Are we making their work hours more effective? Cooper looks to programmers, business managers and what he calls "interaction designers" to question current assumptions and mindsets. Plainly, he asserts that the goal of computer usage should be "not to make anyone feel stupid." Our distance from that goal reinforces the need to rethink entrenched priorities in software planning. -- Jennifer Buckendorff, Amazon.com

    The Art of Game Design: A Book of Lenses shows that the same basic principles of psychology that work for board games, card games and athletic games also are the keys to making top-quality video games. Good game design happens when you view your game from many different perspectives, or lenses. While touring through the unusual territory that is game design, this book gives the reader one hundred of these lenses—one hundred sets of insightful questions to ask yourself that will help make your game better. These lenses are gathered from fields as diverse as psychology, architecture, music, visual design, film, software engineering, theme park design, mathematics, writing, puzzle design, and anthropology. Anyone who reads this book will be inspired to become a better game designer—and will understand how to do it.

    Focus is on an in-depth analysis and exposition of not-so-obvious coding errors in the sample code provided. The theme is to answer the questions 'How couild I have automatically detected this bug' and 'How could I have prevented this bug'? Chapters include programmer attitudes, techniques and debugging methodology. A particularly revealing chapter is "Treacheries of the Trade", should be required reading for all C maniacs. The author has been a professional programmer for seventeen years and draws heavily (and candidly) on actual coding problems and practices based on years of experience at Microsoft.

    And I mean all the time. Every day there’s a new cloud-based dating app; a new cloud-based gizmo for your house; a new cloud-based game; or a thousand other new things—all in the cloud.The cloud is everywhere! Everything is in the cloud! What does it mean! Let’s slow down. Take a deep breath. That’s good. Take another. Excellent. This book teaches you all about the cloud. I’ll let you in on a little secret: the cloud is not that hard to understand. It’s not. It’s just that nobody has taken the time to explain to you what the cloud is. They haven’t, have they?Deep down I think this is because they don’t understand the cloud either, but I do. I’ve been a programmer and writer for over 30 years. I’ve been in cloud computing since the very start, and I’m here to help you on your journey to understand the cloud. Consider me your tour guide. I’ll be with you every step of the way, but not in a creepy way.I take my time with this book. I go slow and easy, so you can build up an intuition about what the cloud really is, one idea at a time. When you finish reading, you’ll understand the cloud. When you hear someone say some new cool thing is in the cloud, you’ll understand exactly what they mean. That’s a promise. How do I deliver on that promise? I use lots and lots of pictures. I use lots and lots of examples. We’ll reveal the secret inner-workings of AWS, Netflix, Facebook Messenger, Amazon Kindle, Apple iCloud, Google Maps, Nest and cloud DVRs. You’ll learn by seeing and understanding; no matter if you're a complete beginner, someone who knows a little and wants to learn more, or a programmer looking to change their career to the cloud.The cloud is the future. You don't want to miss out on the future, do you? Read this book and we'll discover it together.I’m excited. This will be fun. Let’s get started!

    Developers need to understand how to use constraints as guiderails that ensure desired outcomes, and how seemingly small changes can affect a system's properties.

    Even though most engineers don't think much about them, this short book shows you why logs are worthy of your attention.Based on his popular blog posts, LinkedIn principal engineer Jay Kreps shows you how logs work in distributed systems, and then delivers practical applications of these concepts in a variety of common uses--data integration, enterprise architecture, real-time stream processing, data system design, and abstract computing models.Go ahead and take the plunge with logs; you're going love them.Learn how logs are used for programmatic access in databases and distributed systemsDiscover solutions to the huge data integration problem when more data of more varieties meet more systemsUnderstand why logs are at the heart of real-time stream processingLearn the role of a log in the internals of online data systemsExplore how Jay Kreps applies these ideas to his own work on data infrastructure systems at LinkedIn

    In the late 1990s, it provided an optimistic model for public

    This book demystifies agile methodologies: why they’re designed the way they are, what problems they address, and the values, principles, and ideas they embody.Learning Agile helps you recognize the principles that apply to development problems specific to your team, company, and projects. You’ll discover how to use that information to guide your choice of methodologies and practices.With this book you’ll learn:Values that effective software teams possessThe methodologies that embody those valuesThe practices that make up those methodologiesAnd principles that help you bring those values, methodologies, and practices to your team and your company

    Work at your own pace through a series of lessons and practical exercises, and then assess your skills with practice tests on CD—featuring multiple, customizable testing options.Maximize your performance on the exam by learning how to:Create database objectsWork with dataModify dataTroubleshoot and optimize queriesYou also get an exam discount voucher—making this book an exceptional value and a great career investment.

    Aging computer systems present complex technical challenges for organizations both large and small, and Kill It with Fire provides sound strategies for spearheading modernization efforts.Kill It with Fire examines aging computer systems, the evolution of technology over time, and how organizations can modernize, maintain, and future-proof their current systems.In playful and engaging prose, Marianne Bellotti uses real-world case studies to illustrate the technical challenges of modernizing complex legacy systems, as well as the organizational challenges of time-intensive maintenance efforts. The book explains how to evaluate existing architecture, create upgrade plans, and handle communication structures. Team exercises and historical analyses of complex computer systems make this a valuable resource for those in both older and newer companies, and will help readers restore or create systems built to evolve as time goes on.

    As a professional C++ developer and former Harvard teaching fellow, I know what you need to know to be a great C++ programmer, and I know how to teach it, one step at a time. I know where people struggle, and why, and how to make it clear. I cover every step of the programming process, including:Getting the tools you need to program and how to use them*Basic language feature like variables, loops and functions*How to go from an idea to code*A clear, understandable explanation of pointers*Strings, file IO, arrays, references*Classes and advanced class design*C++-specific programming patterns*Object oriented programming*Data structures and the standard template library (STL)Key concepts are reinforced with quizzes and over 75 practice problems.

    To leverage the performance and power of multiprocessor programming, also known as multicore programming, programmers need to learn the new principles, algorithms, and tools.The book will be of immediate use to programmers working with the new architectures. For example, the next generation of computer game consoles will all be multiprocessor-based, and the game industry is currently struggling to understand how to address the programming challenges presented by these machines. This change in the industry is so fundamental that it is certain to require a significant response by universities, and courses on multicore programming will become a staple of computer science curriculums.This book includes fully-developed Java examples detailing data structures, synchronization techniques, transactional memory, and more.Students in multiprocessor and multicore programming courses and engineers working with multiprocessor and multicore systems will find this book quite useful.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.