The book covers lambdas, streams, and functional-style programming. With Java 8's functional features you can now write more concise code in less time, and also automatically benefit from multicore architectures. It's time to dig in!

    Revised and updated for the Elixir 1.7, Elixir in Action, Second Edition teaches you how to apply Elixir to practical problems associated with scalability, fault tolerance, and high availability. Along the way, you'll develop an appreciation for, and considerable skill in, a functional and concurrent style of programming.

    It provides a high-productivity programming model that promotes cleaner code architecture, test-driven development, and powerful extensibility, combined with all the benefits of ASP.NET.ASP.NET MVC 4 contains a number of significant advances over previous versions. New mobile and desktop templates (employing adaptive rendering) are included together with support for jQuery Mobile for the first time. New display modes allow your application to select views based on the browser that's making the request while Code Generation Recipes for Visual Studio help you auto-generate project-specific code for a wide variety of situtations including NuGet support.In this fourth edition, the core model-view-controller (MVC) architectural concepts are not simply explained or discussed in isolation, but are demonstrated in action. You'll work through an extended tutorial to create a working e-commerce web application that combines ASP.NET MVC with the latest C# language features and unit-testing best practices. By gaining this invaluable, practical experience, you'll discover MVC's strengths and weaknesses for yourself--and put your best-learned theory into practice.The book's authors, Steve Sanderson and Adam Freeman, have both watched the growth of ASP.NET MVC since its first release. Steve is a well-known blogger on the MVC Framework and a member of the Microsoft Web Platform and Tools team. Adam started designing and building web applications 15 years ago and has been responsible for some of the world's largest and most ambitious projects. You can be sure you are in safe hands.

    Updated to cover Internet Explorer 7, Microsoft's vastly improved browser, this new edition includes content on positioning, lists and generated content, table layout, user interface, paged media, and more.Simply put, Cascading Style Sheets (CSS) is a way to separate a document's structure from its presentation. The benefits of this can be quite profound: CSS allows a much richer document appearance than HTML and also saves time -- you can create or change the appearance of an entire document in just one place; and its compact file size makes web pages load quickly.CSS: The Definitive Guide, 3rd Edition, provides you with a comprehensive guide to CSS implementation, along with a thorough review of all aspects of CSS 2.1. Updated to cover Internet Explorer 7, Microsoft's vastly improved browser, this new edition includes content on positioning, lists and generated content, table layout, user interface, paged media, and more. Author Eric Meyer tackles the subject with passion, exploring in detail each individual CSS property and how it interacts with other properties. You'll not only learn how to avoid common mistakes in interpretation, you also will benefit from the depth and breadth of his experience and his clear and honest style. This is the complete sourcebook on CSS.The 3rd edition contains:Updates to reflect changes in the latest draft version of CSS 2.1Browser notes updated to reflect changes between IE6 and IE7Advanced selectors supported in IE7 and other major browsers includedA new round of technical edits by a fresh set of editorsClarifications and corrected errata, including updated URLs ofreferenced online resources

    Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms.Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works.Topics include:Data Structures and AlgorithmsStrings and TextNumbers, Dates, and TimesIterators and GeneratorsFiles and I/OData Encoding and ProcessingFunctionsClasses and ObjectsMetaprogrammingModules and PackagesNetwork and Web ProgrammingConcurrencyUtility Scripting and System AdministrationTesting, Debugging, and ExceptionsC Extensions

    For decades, technology leaders have struggled to balance agility, reliability, and security. The consequences of failure have never been greater whether it's the healthcare.gov debacle, cardholder data breaches, or missing the boat with Big Data in the cloud.And yet, high performers using DevOps principles, such as Google, Amazon, Facebook, Etsy, and Netflix, are routinely and reliably deploying code into production hundreds, or even thousands, of times per day.Following in the footsteps of The Phoenix Project, The DevOps Handbook shows leaders how to replicate these incredible outcomes, by showing how to integrate Product Management, Development, QA, IT Operations, and Information Security to elevate your company and win in the marketplace."Table of contentsPrefaceSpreading the Aha! MomentIntroductionPART I: THE THREE WAYS1. Agile, continuous delivery and the three ways2. The First Way: The Principles of Flow3. The Second Way: The Principle of Feedback4. The Third Way: The Principles of Continual LearningPART II: WHERE TO START5. Selecting which value stream to start with6. Understanding the work in our value stream…7. How to design our organization and architecture8. How to get great outcomes by integrating operations into the daily work for developmentPART III: THE FIRST WAY: THE TECHNICAL PRACTICES OF FLOW9. Create the foundations of our deployment pipeline10. Enable fast and reliable automated testing11. Enable and practice continuous integration12. Automate and enable low-risk releases13. Architect for low-risk releasesPART IV: THE SECOND WAY: THE TECHNICAL PRACTICES OF FEEDBACK14*. Create telemetry to enable seeing abd solving problems15. Analyze telemetry to better anticipate problems16. Enable feedbackso development and operation can safely deploy code17. Integrate hypothesis-driven development and A/B testing into our daily work18. Create review and coordination processes to increase quality of our current workPART V: THE THRID WAY: THE TECHNICAL PRACTICES OF CONTINUAL LEARNING19. Enable and inject learning into daily work20. Convert local discoveries into global improvements21. Reserve time to create organizational learning22. Information security as everyone’s job, every day23. Protecting the deployment pipelinePART VI: CONCLUSIONA call to actionConclusion to the DevOps HandbookAPPENDICES1. The convergence of Devops2. The theory of constraints and core chronic conflicts3. Tabular form of downward spiral4. The dangers of handoffs and queues5. Myths of industrial safety6. The Toyota Andon Cord7. COTS Software8. Post-mortem meetings9. The Simian Army10. Transparent uptimeAdditional ResourcesEndnotes

    Lambda enables users to develop code that executes in response to events - API calls, file uploads, schedules, etc - and upload it without worrying about managing traditional server metrics such as disk space, memory, or CPU usage. With its "per execution" cost model, Lambda can enable organizations to save hundreds or thousands of dollars on computing costs. With in-depth walkthroughs, large screenshots, and complete code samples, the reader is guided through the step-by-step process of creating new functions, responding to infrastructure events, developing API backends, executing code at specified intervals, and much more. Introduction to AWS Computing Evolution of the Computing Workload Lambda Background The Internals The Basics Functions Languages Resource Allocation Getting Set Up Hello World Uploading the Function Working with Events AWS Events Custom Events The Context Object Properties Methods Roles and Permissions Policies Trust Relationships Console Popups Cross Account Access Dependencies and Resources Node Modules OS Dependencies OS Resources OS Commands Logging Searching Logs Testing Your Function Lambda Console Tests Third-Party Testing Libraries Simulating Context Hello S3 Object The Bucket The Role The Code The Event The Trigger Testing When Lambda Isn’t the Answer Host Access Fine-Tuned Configuration Security Long-Running Tasks Where Lambda Excels AWS Event-Driven Tasks Scheduled Events (Cron) Offloading Heavy Processing API Endpoints Infrequently Used Services Real-World Use Cases S3 Image Processing Shutting Down Untagged Instances Triggering CodeDeploy with New S3 Uploads Processing Inbound Email Enforcing Security Policies Detecting Expiring Certificates Utilizing the AWS API Execution Environment The Code Pipeline Cold vs. Hot Execution What is Saved in Memory Scaling and Container Reuse From Development to Deployment Application Design Development Patterns Testing Deployment Monitoring Versioning and Aliasing Costs Short Executions Long-Running Processes High-Memory Applications Free Tier Calculating Pricing CloudFormation Reusable Template with Minimum Permissions Cross Account Access CloudWatch Alerts AWS API Gateway API Gateway Event Creating the Lambda Function Creating a New API, Resource, and Method Initial Configuration Mapping Templates Adding a Query String Using HTTP Request Information Within Lambda Deploying the API Additional Use Cases Lambda Competitors Iron.io StackHut WebTask.io Existing Cloud Providers The Future of Lambda More Resources Conclusion

    And how to move all of this data becomes nearly as important as the data itself. If you� re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds.Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you� ll learn Kafka� s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer.Understand publish-subscribe messaging and how it fits in the big data ecosystem.Explore Kafka producers and consumers for writing and reading messagesUnderstand Kafka patterns and use-case requirements to ensure reliable data deliveryGet best practices for building data pipelines and applications with KafkaManage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasksLearn the most critical metrics among Kafka� s operational measurementsExplore how Kafka� s stream delivery capabilities make it a perfect source for stream processing systems

    Star Schema: The Complete Reference offers in-depth coverage of design principles and their underlying rationales. Organized around design concepts and illustrated with detailed examples, this is a step-by-step guidebook for beginners and a comprehensive resource for experts.This all-inclusive volume begins with dimensional design fundamentals and shows how they fit into diverse data warehouse architectures, including those of W.H. Inmon and Ralph Kimball. The book progresses through a series of advanced techniques that help you address real-world complexity, maximize performance, and adapt to the requirements of BI and ETL software products. You are furnished with design tasks and deliverables that can be incorporated into any project, regardless of architecture or methodology.Master the fundamentals of star schema design and slow change processingIdentify situations that call for multiple stars or cubesEnsure compatibility across subject areas as your data warehouse growsAccommodate repeating attributes, recursive hierarchies, and poor data qualitySupport conflicting requirements for historic dataHandle variation within a business process and correlation of disparate activitiesBoost performance using derived schemas and aggregatesLearn when it's appropriate to adjust designs for BI and ETL tools

    But the state-of-the-art has moved forward dramatically since Meyers last updated this book in 1997. (For instance, there s now STL. Design patterns. Even new functionality being added through TR1 and Boost.) So Meyers has done a top-to-bottom rewrite, identifying the 55 most valuable techniques you need now to be exceptionally effective with C++. Over half of this edition s content is new. Templates broadly impact C++ development, and you ll find them everywhere. There s extensive coverage of multithreaded systems. There s an entirely new chapter on resource management. You ll find substantial new coverage of exceptions. Much is gained, but nothing s lost: You ll find the same depth of practical insight that first made Effective C++ a classic all those years ago. Bill Camarda, from the July 2005 href="http://www.barnesandnoble.com/newslet... Only

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    And then we wonder why software is notorious for being delivered late and full of bugs, while other engineers routinely deliver finished bridges, automobiles, electrical appliances, etc., on time and with only minor defects. This book sets out to redress this imbalance. Members of my advanced development team at Adobe who took the course based on the same material all benefited greatly from the time invested. It may appear as a highly technical text intended only for computer scientists, but it should be required reading for all practicing software engineers." --Martin Newell, Adobe Fellow"The book contains some of the most beautiful code I have ever seen." --Bjarne Stroustrup, Designer of C++"I am happy to see the content of Alex's course, the development and teaching of which I strongly supported as the CTO of Silicon Graphics, now available to all programmers in this elegant little book." --Forest Baskett, General Partner, New Enterprise Associates"Paul's patience and architectural experience helped to organize Alex's mathematical approach into a tightly-structured edifice--an impressive feat!" --Robert W. Taylor, Founder of Xerox PARC CSL and DEC Systems Research Center Elements of Programming provides a different understanding of programming than is presented elsewhere. Its major premise is that practical programming, like other areas of science and engineering, must be based on a solid mathematical foundation. The book shows that algorithms implemented in a real programming language, such as C++, can operate in the most general mathematical setting. For example, the fast exponentiation algorithm is defined to work with any associative operation. Using abstract algorithms leads to efficient, reliable, secure, and economical software.This is not an easy book. Nor is it a compilation of tips and tricks for incremental improvements in your programming skills. The book's value is more fundamental and, ultimately, more critical for insight into programming. To benefit fully, you will need to work through it from beginning to end, reading the code, proving the lemmas, and doing the exercises. When finished, you will see how the application of the deductive method to your programs assures that your system's software components will work together and behave as they must.The book presents a number of algorithms and requirements for types on which they are defined. The code for these descriptions--also available on the Web--is written in a small subset of C++ meant to be accessible to any experienced programmer. This subset is defined in a special language appendix coauthored by Sean Parent and Bjarne Stroustrup.Whether you are a software developer, or any other professional for whom programming is an important activity, or a committed student, you will come to understand what the book's experienced authors have been teaching and demonstrating for years--that mathematics is good for programming, and that theory is good for practice.

    This introduction is ideal for beginners: it requires no previous programming experience and all concepts are explained from first principles via carefully chosen examples. Each chapter includes exercises that range from the straightforward to extended projects, plus suggestions for further reading on more advanced topics. The author is a leading Haskell researcher and instructor, well-known for his teaching skills. The presentation is clear and simple, and benefits from having been refined and class-tested over several years. The result is a text that can be used with courses, or for self-learning. Features include freely accessible Powerpoint slides for each chapter, solutions to exercises and examination questions (with solutions) available to instructors, and a downloadable code that's fully compliant with the latest Haskell release.

    Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.