Effectively implement features and components for any computing environment Key Features *Explore the latest features of VMware Horizon 7.7 *Virtualize your desktop infrastructure using new features introduced in Horizon *Implement App Volumes and User Environment Manager in your infrastructure Book Description This third edition of Implementing VMware Horizon 7.7 has been updated to get you up to speed with VMware Horizon 7.7 by showing you how to use its key features and deploying an end-user computing infrastructure for your own organization. The book begins by guiding you on how to deploy all the core requirements for a VMware Horizon infrastructure. It then moves on to show you how to provision and administer end-user computing resources using VMware Horizon. You’ll not only be able to deploy the core VMware Horizon features, but you’ll also be able to implement new features, such as the Just-in-Time Management Platform (JMP) and the Horizon Console. You’ll also focus on the latest features and components of the Horizon platform and learn when and how they are used. By the end of the book, you will have developed a solid understanding of how your organization can benefit from the capabilities VMware Horizon offers and how each of its components is implemented. What you will learn *Work with the different products that make up VMware Horizon *Implement a multi-site VMware Horizon Pod using the Cloud Pod Architecture feature *Deploy and configure VMware Horizon’s optional components *Implement and maintain Microsoft RDSH, Horizon Linux, and Windows Desktop Pools and RDSH Application Pools *Configure and manage Horizon remotely using PowerCLI *Learn about the Microsoft Windows Group Policy templates for Horizon *Understand how to manage the SSL certificates for each of the VMware Horizon components Who this book is for If you’re a system administrator, solutions architect, or desktop engineer looking to level up your skills working with VMware's Horizon ecosystem and want to build a successful deployment strategy for desktops and applications, this book is for you.

Work through recipes to unlock the full potential of the next generation graphics API―Vulkan About This Book ?This book explores a wide range of modern graphics programming techniques and GPU compute methods to make the best use of the Vulkan API ?Learn techniques that can be applied to a wide range of platforms desktop, smartphones, and embedded devices Who This Book Is For This book is ideal for developers who know C/C++ languages, have some basic familiarity with graphics programming, and now want to take advantage of the new Vulkan API in the process of building next generation computer graphics. Some basic familiarity of Vulkan would be useful to follow the recipes. OpenGL developers who want to take advantage of the Vulkan API will also find this book useful. What You Will Learn?Work with Swapchain to present images on screen ?Create, submit, and synchronize operations processed by the hardware ?Create buffers and images, manage their memory, and upload data to them from CPU ?Explore de*or sets and set up an interface between application and shaders ?Organize drawing operations into a set of render passes and subpasses ?Prepare graphics pipelines to draw 3D scenes and compute pipelines to perform mathematical calculations ?Implement geometry projection and tessellation, texturing, lighting, and post-processing techniques ?Write shaders in GLSL and convert them into SPIR-V assemblies ?Find out about and

"Key Features ?Get to the grips with the latest version of Apache Spark ?Utilize Spark's machine learning library to implement predictive analytics ?Leverage Spark's powerful tools to load, analyze, clean, and transform your data Book De*ion Spark ML is the machine learning module of Spark. It uses in-memory RDDs to process machine learning models faster for clustering, classification, and regression. This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. What you will learn ?Get hands-on with the latest version of Spark ML ?Create your first Spark program with Scala and Python ?Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2 ?Access public machine learning datasets and use Spark to load, process, clean, and transform data ?Use Spark's machine learning library to implement programs by utilizing well-known machine learning models ?Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models ?Write Spark functions to evaluate the performance of your machine learning models "

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide About This Book ?Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow ?Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide ?Real-world contextualization through some deep learning problems concerning research and application Who This Book Is For The book is intended for a general audience of people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will Learn ?Learn about machine learning landscapes along with the historical development and progress of deep learning ?Learn about deep machine intelligence and GPU computing with the latest TensorFlow 1.x ?Access public datasets and utilize them using TensorFlow to load, process, and transform data ?Use TensorFlow on real-world datasets, including images, text, and more ?Learn how to evaluate the performance of your deep learning models ?Using deep learning for scalable object detection and mobile computing ?Train machines quickly to learn from data by exploring reinforcement learning techniques ?Explore active areas of deep learning research and applications

Do you want to make sense of your data? Do you want to create interactive charts, data trees, info-graphics, geospatial charts, and maps efficiently? This book is your ideal choice to master interactive data visualization with D3.js V4. The book includes a number of extensive examples that to help you hone your skills with data visualization. Throughout nine chapters these examples will help you acquire a clear practical understanding of the various techniques, tools and functionality provided by D3.js. You will first setup your D3.JS development environment and learn the basic patterns needed to visualize your data. After that you will learn techniques to optimize different processes such as working with selections; animating data transitions; creating graps and charts, integrating external resources (static as well as streaming); visualizing information on maps; working with colors and scales; utilizing the different D3.js APIs; and much more. The book will also guide you through creating custom graphs and visualizations, and show you how to go from the raw data to beautiful visualizations. The extensive examples will include working with complex and realtime data streams, such as seismic data, geospatial data, scientific data, and more. Towards the end of the book, you will learn to add more functionality on top of D3.js by using it with other external libraries and integrating it with Ecma* 6 and Type*

Writing concurrent and parallel programming applications is an integral skill for any Java programmer. Java 9 comes with a host of fantastic features, including significant performance improvements and new APIs. This book will take you through all the new APIs, showing you how to build parallel and multi-threaded applications. The book covers all the elements of the Java Concurrency API, with essential recipes that will help you take advantage of the exciting new capabilities. You will learn how to use parallel and reactive streams to process massive data sets. Next, you will move on to create streams and use all their intermediate and terminal operations to process big collections of data in a parallel and functional way. Further, you ll discover a whole range of recipes for almost everything, such as thread management, synchronization, executors, parallel and reactive streams, and many more. At the end of the book, you will learn how to obtain information about the status of some of the most useful components of the Java Concurrency API and how to test concurrent applications using different tools. What you will learn ?Find out to manage the basic components of the Java Concurrency API ?Use synchronization mechanisms to avoid data race conditions and other problems of concurrent applications ?Separate the thread management from the rest of the application with the Executor framework ?Solve problems using a parallelized version of the divide and conquer paradigm with the Fork / Join framework ?Process massive data sets in an optimized way using streams and reactive streams ?See which data structures we can use in concurrent applications and how to use them ?Practice efficient techniques to test concurrent applications ?Get to know tips and tricks to design concurrent applications

This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided. Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GAN). You will also explore non-traditional uses of neural networks as Style Transfer. Finally, you will look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks. What you will learn ?Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm ?Fine-tune a neural network to improve the quality of results ?Use deep learning for image and audio processing ?Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases ?Identify problems

Spatial statistics has the potential to provide insight that is not otherwise available through traditional GIS tools. This book is designed to introduce you to the use of spatial statistics so you can solve complex geographic analysis. The book begins by introducing you to the many spatial statistics tools available in ArcGIS. You will learn how to analyze patterns, map clusters, and model spatial relationships with these tools. Further on, you will explore how to extend the spatial statistics tools currently available in ArcGIS, and use the R programming language to create custom tools in ArcGIS through the ArcGIS Bridge using real-world examples. At the end of the book, you will be presented with two exciting case studies where you will be able to practically apply all your learning to analyze and gain insights into real estate data. What you will learn ?Get to know how to measure geographic distributions ?Perform clustering analysis including hot spot and outlier analysis ?Conduct data conversion tasks using the Utilities toolset ?Understand how to use the tools provided by the Mapping Clusters toolset in the Spatial Statistics Toolbox ?Get to grips with the basics of R for performing spatial statistical programming ?Create custom ArcGIS tools with R and ArcGIS Bridge ?Understand the application of Spatial Statistics tools

Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. What you will learn ?Get a solid understanding of the data processing toolbox available in Java ?Explore the data science ecosystem available in Java

Learn how to run new and old Windows applications in Docker containers. About This Book ? Package traditional .NET Frameworks apps and new .NET Core apps as Docker images, and run them in containers for increased efficiency, portability, and security ? Design and implement distributed applications that run across connected containers, using enterprise-grade open source software from public Docker images ? Build a full Continuous Deployment pipeline for a .NET Framework application, and deploy it to a highly-available Docker swarm running in the cloud Who This Book Is For If you want to modernize an old monolithic application without rewriting it, smooth the deployment to production, or move to DevOps or the cloud, then Docker is the enabler for you. This book gives you a solid grounding in Docker so you can confidently approach all of these scenarios. What You Will Learn ? Comprehend key Docker concepts: images, containers, registries, and swarms ? Run Docker on Windows 10, Windows Server 2016, and in the cloud ? Deploy and monitor distributed solutions across multiple Docker containers ? Run containers with high availability and fail-over with Docker Swarm ? Master security in-depth with the Docker platform, making your apps more secure ? Build a Continuous Deployment pipeline by running Jenkins in Docker ? Debug applications running in Docker containers using Visual Studio ? Plan the adoption of Docker in your own organization In Detail Docker is a platform for running server applications in lightweight units called containers. You can run Docker on Windows Server 2016 and Windows 10, and run your existing apps in containers to get significant improvements in efficiency, security, and portability. This book teaches you all you need to know about Docker on Windows, from 101 to deploying highly-available workloads in production. This book takes you on a Docker journey, starting with the key concepts and simple examples of how to run .NET Framework and .NET Core apps in Windows Docker containers. Then it moves on to more complex examples—using Docker to modernize the architecture and development of traditional ASP.NET and SQL Server apps. The examples show you how to break up monoliths into distributed apps and deploy them to a clustered environment in the cloud, using the exact same artifacts you use to run them locally. To help you move confidently to production, it then explains Docker security, and the management and support options. The book finishes with guidance on getting started with Docker in your own projects, together with some real-world case studies for Docker implementations, from small-scale on-premises apps to very large-scale apps running on Azure. Style and approach Using a step-by-step approach, this book shows you how to use Docker on Windows. It includes practical examples and real-world technical and business scenarios that will help you effectively implement Docker in your environment.There are over 50 examples of Dockerized applications, using C# .NET projects as the source and packaging them into Docker images.

Build cloud native applications in Python About This Book ? This is the only reliable resource that showcases the tools and techniques you need build robust and resilient cloud native applications in Python ? Learn how to architect your application on both, the AWS and Azure clouds for high availability ? Assess, monitor, and troubleshoot your applications in the cloud Who This Book Is For This book is ideal for developers with a basic knowledge of Python who want to learn to build, test, and scale their Python-based applications. No prior experience of writing microservices in Python is required. What You Will Learn ? Get to know “the way of the cloud”, including why developing good cloud software is fundamentally about mindset and discipline ? Know what microservices are and how to design them ? Create reactive applications in the cloud with third-party messaging providers ? Build massive-scale, user-friendly GUIs with React and Flux ? Secure cloud-based web applications: the do’s, don’ts, and options ? Plan cloud apps that support continuous delivery and deployment In Detail Businesses today are evolving so rapidly that having their own infrastructure to support their expansion is not feasible. As a result, they have been resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This book will be the one stop for you to learn all about building cloud-native architectures in Python. It will begin by introducing you to cloud-native architecture and will help break it down for you. Then you’ll learn how to build microservices in Python using REST APIs in an event driven approach and you will build the web layer. Next, you’ll learn about Interacting data services and building Web views with React, after which we will take a detailed look at application security and performance. Then, you’ll also learn how to Dockerize your services. And finally, you’ll learn how to deploy the application on the AWS and Azure platforms. We will end the book by discussing some concepts and techniques around troubleshooting problems that might occur with your applications after you’ve deployed them. This book will teach you how to craft applications that are built as small standard units, using all the proven best practices and avoiding the usual traps. It's a practical book: we're going to build everything using Python 3 and its amazing tooling ecosystem. The book will take you on a journey, the destination of which, is the creation of a complete Python application based on microservices over the cloud platform Style and approach Filled with examples, this book takes a step-by-step approach to teach you each and every configuration you need to make your application highly available and fault tolerant.

Build a variety of real-world applications by taking advantage of the newest features of Java 9 About This Book ? See some of the new features of Java 9 and be introduced to parts of the Java SDK ? This book provides a set of diverse, interesting projects that range in complexity from fairly simple to advanced and cover HTTP 2.0 ? Take advantage of Java's new modularity features to write real-world applications that solve a variety of problems Who This Book Is For This book is for Java developers who are already familiar with the language. Familiarity with more advanced topics, such as network programming and threads, would be helpful, but is not assumed. What You Will Learn ? Learn how to package Java applications as modules by using the Java Platform Module System ? Implement process management in Java by using the all-new process handling API ? Integrate your applications with third-party services in the cloud ? Interact with mail servers using JavaMail to build an application that filters spam messages ? Learn to use JavaFX to build rich GUI based applications, which are an essential element of application development ? Write microservices in Java using platform libraries and third-party frameworks ? Integrate a Java application with MongoDB to build a cloud-based note taking application In Detail Java is a powerful language that has applications in a wide variety of fields. From playing games on your computer to performing banking transactions, Java is at the heart of everything. The book starts by unveiling the new features of Java 9 and quickly walks you through the building blocks that form the basis of writing applications. There are 10 comprehensive projects in the book that will showcase the various features of Java 9. You will learn to build an email filter that separates spam messages from all your inboxes, a social media aggregator app that will help you efficiently track various feeds, and a microservice for a client/server note application, to name a few. The book covers various libraries and frameworks in these projects, and also introduces a few more frameworks that complement and extend the Java SDK. Through the course of building applications, this book will not only help you get to grips with the various features of Java 9, but will also teach you how to design and prototype professional-grade applications with performance and security considerations. Style and approach This is a learn-as-you-build practical guide to building full-fledged applications using Java 9. With a project-based approach, we’ll improve your Java skills. You will experience a variety of solutions to problems with Java.

Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book ? Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. ? Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. ? Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn ? Acquaint yourself with important elements of Machine Learning ? Understand the feature selection and feature engineering process ? Assess performance and error trade-offs for Linear Regression ? Build a data model and understand how it works by using different types of algorithm ? Learn to tune the parameters of Support Vector machines ? Implement clusters to a dataset ? Explore the concept of Natural Processing Language and Recommendation Systems ? Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.

Take your C++ coding to the next level by leveraging the latest features and advanced techniques to building high performing, reliable applications. About This Book ? Get acquainted with the latest features in C++ 17 ? Take advantage of the myriad of features and possibilities that C++ offers to build real-world applications ? Write clear and expressive code in C++, and get insights into how to keep your code error-free Who This Book Is For This book is for experienced C++ developers. If you are a novice C++ developer, then it’s highly recommended that you get a solid understanding of the C++ language before reading this book What You Will Learn ? Write modular C++ applications in terms of the existing and newly introduced features ? Identify code-smells, clean up, and refactor legacy C++ applications ? Leverage the possibilities provided by Cucumber and Google Test/Mock to automate test cases ? Test frameworks with C++ ? Get acquainted with the new C++17 features ? Develop GUI applications in C++ ? Build portable cross-platform applications using standard C++ features In Detail C++ has come a long way and has now been adopted in several contexts. Its key strengths are its software infrastructure and resource-constrained applications. The C++ 17 release will change the way developers write code, and this book will help you master your developing skills with C++. With real-world, practical examples explaining each concept, the book will begin by introducing you to the latest features in C++ 17. It encourages clean code practices in C++ in general, and demonstrates the GUI app-development options in C++. You’ll get tips on avoiding memory leaks using smart-pointers. Next, you’ll see how multi-threaded programming can help you achieve concurrency in your applications. Moving on, you’ll get an in-depth understanding of the C++ Standard Template Library. We show you the concepts of implementing TDD and BDD in your C++ programs, and explore template-based generic programming, giving you the expertise to build powerful applications. Finally, we’ll round up with debugging techniques and best practices.By the end of the book, you’ll have an in-depth understanding of the language and its various facets. Style and approach This straightforward guide will help you level up your skills in C++ programming, be it for enterprise software or for low-latency applications like games. Filled with real-world, practical examples, this book will take you gradually up the steep learning curve that is C++.

Learn the ins and outs of the Industrial Internet of Things through subjects ranging from its history and evolution, right up to what the future holds. About This Book ? Define solutions that can connect existing systems and newer cloud-based solutions to thousands of thousands of edge devices and industrial machines ? Identify, define, and justify Industrial Internet of Things (IIoT) projects, and design an application that can connect to and control thousands of machines ? Leverage the power and features of a platform to monitor, perform analytics, and maintain the Industrial Internet Who This Book Is For Architects who are interested in learning how to define solutions for the Industrial Internet will benefit immensely from this book. Relevant architect roles include enterprise architects, business architects, information architects, cloud solution architects, software architects, and others. The content is also relevant for technically inclined line of business leaders investing in these solutions. What You Will Learn ? Learn the history of the Industrial Internet and why an architectural approach is needed ? Define solutions that can connect to and control thousands of edge devices and machines ? Understand the significance of working with line of business leadership and key metrics to be gathered ? Connect business requirements to the functional architecture ? Gain the right expectation as to the capabilities of Industrial Internet applications and how to assess them ? Understand what data and analytics components should be included in your architecture solution ? Understand deployment trade-offs, management and security considerations, and the impact of emerging technologies In Detail The Industrial Internet or the IIoT has gained a lot of traction. Many leading companies are driving this revolution by connecting smart edge devices to cloud-based analysis platforms and solving their business challenges in new ways. To ensure a smooth integration of such machines and devices, sound architecture strategies based on accepted principles, best practices, and lessons learned must be applied. This book begins by providing a bird's eye view of what the IIoT is and how the industrial revolution has evolved into embracing this technology. It then describes architectural approaches for success, gathering business requirements, and mapping requirements into functional solutions. In a later chapter, many other potential use cases are introduced including those in manufacturing and specific examples in predictive maintenance, asset tracking and handling, and environmental impact and abatement. The book concludes by exploring evolving technologies that will impact IIoT architecture in the future and discusses possible societal implications of the Industrial Internet and perceptions regarding these projects. By the end of this book, you will be better equipped to embrace the benefits of the burgeoning IIoT. Style and approach This book takes a comprehensive approach to the Industrial Internet, thoroughly acquainting the reader with the concepts and philosophy of the IIoT. It provides a basis for defining an IIoT solution in a thoughtful manner and creating what will be viewed as a successful project.

Learning the new system’s programming language for all Unix-type systems About This Book ? Learn how to write system's level code in Golang, similar to Unix/Linux systems code ? Ramp up in Go quickly ? Deep dive into Goroutines and Go concurrency to be able to take advantage of Go server-level constructs Who This Book Is For Intermediate Linux and general Unix programmers. Network programmers from beginners to advanced practitioners. C and C++ programmers interested in different approaches to concurrency and Linux systems programming. What You Will Learn ? Explore the Go language from the standpoint of a developer conversant with Unix, Linux, and so on ? Understand Goroutines, the lightweight threads used for systems and concurrent applications ? Learn how to translate Unix and Linux systems code in C to Golang code ? How to write fast and lightweight server code ? Dive into concurrency with Go ? Write low-level networking code In Detail Go is the new systems programming language for Linux and Unix systems. It is also the language in which some of the most prominent cloud-level systems have been written, such as Docker. Where C programmers used to rule, Go programmers are in demand to write highly optimized systems programming code. Created by some of the original designers of C and Unix, Go expands the systems programmers toolkit and adds a mature, clear programming language. Traditional system applications become easier to write since pointers are not relevant and garbage collection has taken away the most problematic area for low-level systems code: memory management. This book opens up the world of high-performance Unix system applications to the beginning Go programmer. It does not get stuck on single systems or even system types, but tries to expand the original teachings from Unix system level programming to all types of servers, the cloud, and the web. Style and approach This is the first book to introduce Linux and Unix systems programming in Go, a field for which Go has actually been developed in the first place.

A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book ? Learn about the various challenges in real-time data processing and use the right tools to overcome them ? This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems ? A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn ? Get an introduction to the established real-time stack ? Understand the key integration of all the components ? Get a thorough understanding of the basic building blocks for real-time solution designing ? Garnish the search and visualization aspects for your real-time solution ? Get conceptually and practically acquainted with real-time analytics ? Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you’ll be equipped with a clear understanding of how to solve challenges on your own. We’ll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You’ll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to deploy the solutions in production environments in the best possible manner. Style and Approach In this practical guide to real-time analytics, each chapter begins with a basic high-level concept of the topic, followed by a practical, hands-on implementation of each concept, where you can see the working and execution of it. The book is written in a DIY style, with plenty of practical use cases, well-explained code examples, and relevant screenshots and diagrams.

Harness the power and simplicity of Informatica PowerCenter 10.x to build and manage efficient data management solutions About This Book ? Master PowerCenter 10.x components to create, execute, monitor, and schedule ETL processes with a practical approach. ? An ideal guide to building the necessary skills and competencies to become an expert Informatica PowerCenter developer. ? A comprehensive guide to fetching/transforming and loading huge volumes of data in a very effective way, with reduced resource consumption Who This Book Is For If you wish to deploy Informatica in enterprise environments and build a career in data warehousing, then this book is for you. Whether you are a software developer/analytic professional and are new to Informatica or an experienced user, you will learn all the features of Informatica 10.x. A basic knowledge of programming and data warehouse concepts is essential. What You Will Learn ? Install or upgrade the components of the Informatica PowerCenter tool ? Work on various aspects of administrative skills and on the various developer Informatica PowerCenter screens such as Designer, Workflow Manager, Workflow Monitor, and Repository Manager. ? Get practical hands-on experience of various sections of Informatica PowerCenter, such as navigator, toolbar, workspace, control panel, and so on ? Leverage basic and advanced utilities, such as the debugger, target load plan, and incremental aggregation to process data ? Implement data warehousing concepts such as schemas and SCDs using Informatica ? Migrate various components, such as sources and targets, to another region using the Designer and Repository Manager screens ? Enhance code performance using tips such as pushdown optimization and partitioning In Detail Informatica PowerCenter is an industry-leading ETL tool, known for its accelerated data extraction, transformation, and data management strategies. This book will be your quick guide to exploring Informatica PowerCenter’s powerful features such as working on sources, targets, transformations, performance optimization, scheduling, deploying for processing, and managing your data at speed. First, you’ll learn how to install and configure tools. You will learn to implement various data warehouse and ETL concepts, and use PowerCenter 10.x components to build mappings, tasks, workflows, and so on. You will come across features such as transformations, SCD, XML processing, partitioning, constraint-based loading, Incremental aggregation, and many more. Moreover, you’ll also learn to deliver powerful visualizations for data profiling using the advanced monitoring dashboard functionality offered by the new version. Using data transformation technique, performance tuning, and the many new advanced features, this book will help you understand and process data for training or production purposes. The step-by-step approach and adoption of real-time scenarios will guide you through effectively accessing all core functionalities offered by Informatica PowerCenter version 10.x. Style and approach You'll get hand-on with sources, targets, transformations, performance optimization, scheduling, deploying for processing, and managing your data, and learn everything you need to become a proficient Informatica PowerCenter developer.

A complete guide to build robust and scalable web applications with Spring and Angular. About This Book ? This hands on guide will teach you how to build an end-to-end modern web application using Spring and Angular. ? It is easy to read and will benefit Java developers who have been used to develop the back-end part of web application while front-end (UI) has been left for UI developers. ? Learn the core aspects involved in developing the backend and the UI, right from designing to integrating and deploying. Who This Book Is For This book is targeted towards Java Web Developers with a basic knowledge of Spring who want to build complete web applications in a fast and effective way. They will want to gain a stronghold on both frontend and backend development to advance in their careers. What You Will Learn ? Set up development environment for Spring Web App and Angular app. ? Process web request and response and build REST API endpoints. ? Create data access components using Spring Web MVC framework and Hibernate ? Use Junit 5 to test your application ? Learn the fundamental concepts around building Angular ? Configure and use Routes and Components. ? Protect Angular app content from common web vulnerabilities and attacks. ? Integrate Angular apps with Spring Boot Web API endpoints ? Deploy the web application based on CI and CD using Jenkins and Docker containers In Detail Spring is the most popular application development framework being adopted by millions of developers around the world to create high performing, easily testable, reusable code. Its lightweight nature and extensibility helps you write robust and highly-scalable server-side web applications. Coupled with the power and efficiency of Angular, creating web applications has never been easier. If you want build end-to-end modern web application using Spring and Angular, then this book is for you. The book directly heads to show you how to create the backend with Spring, showing you how to configure the Spring MVC and handle Web requests. It will take you through the key aspects such as building REST API endpoints, using Hibernate, working with Junit 5 etc. Once you have secured and tested the backend, we will go ahead and start working on the front end with Angular. You will learn about fundamentals of Angular and Type* and create an SPA using components, routing etc. Finally, you will see how to integrate both the applications with REST protocol and deploy the application using tools such as Jenkins and Docker. Style and approach This is a straightforward guide that shows how to build a complete web application in Angular and Spring.

Learn to build applications faster and better by leveraging the real power of Boost and C++ About This Book ? Learn to use the Boost libraries to simplify your application development ? Learn to develop high quality, fast and portable applications ? Learn the relations between Boost and C++11/C++4/C++17 Who This Book Is For This book is for developers looking to improve their knowledge of Boost and who would like to simplify their application development processes. Prior C++ knowledge and basic knowledge of the standard library is assumed. What You Will Learn ? Get familiar with new data types for everyday use ? Use smart pointers to manage resources ? Get to grips with compile-time computations and assertions ? Use Boost libraries for multithreading ? Learn about parallel execution of different task ? Perform common string-related tasks using Boost libraries ? Split all the processes, computations, and interactions to tasks and process them independently ? Learn the basics of working with graphs, stacktracing, testing and interprocess communications ? Explore different helper macros used to detect compiler, platform and Boost features In Detail If you want to take advantage of the real power of Boost and C++ and avoid the confusion about which library to use in which situation, then this book is for you. Beginning with the basics of Boost C++, you will move on to learn how the Boost libraries simplify application development. You will learn to convert data such as string to numbers, numbers to string, numbers to numbers and more. Managing resources will become a piece of cake. You’ll see what kind of work can be done at compile time and what Boost containers can do. You will learn everything for the development of high quality fast and portable applications. Write a program once and then you can use it on Linux, Windows, MacOS, Android operating systems. From manipulating images to graphs, directories, timers, files, networking – everyone will find an interesting topic. Be sure that knowledge from this book won’t get outdated, as more and more Boost libraries become part of the C++ Standard. Style and approach Clear step-by-step recipes that will help you take advantage of the real power of Boost.

Find out how to craft effective, business-oriented Java EE 8 applications that target customer’s demands in the age of Cloud platforms and container technology. About This Book ? Understand the principles of modern Java EE and how to realize effective architectures ? Gain knowledge of how to design enterprise software in the age of automation, Continuous Delivery and Cloud platforms ? Learn about the reasoning and motivations behind state-of-the-art enterprise Java technology, that focuses on business Who This Book Is For This book is for experienced Java EE developers who are aspiring to become the architects of enterprise-grade applications, or software architects who would like to leverage Java EE to create effective blueprints of applications. What You Will Learn ? What enterprise software engineers should focus on ? Implement applications, packages, and components in a modern way ? Design and structure application architectures ? Discover how to realize technical and cross-cutting aspects ? Get to grips with containers and container orchestration technology ? Realize zero-dependency, 12-factor, and Cloud-native applications ? Implement automated, fast, reliable, and maintainable software tests ? Discover distributed system architectures and their requirements In Detail Java EE 8 brings with it a load of features, mainly targeting newer architectures such as microservices, modernized security APIs, and cloud deployments. This book will teach you to design and develop modern, business-oriented applications using Java EE 8. It shows how to structure systems and applications, and how design patterns and Domain Driven Design aspects are realized in the age of Java EE 8. You will learn about the concepts and principles behind Java EE applications, and how to effect communication, persistence, technical and cross-cutting concerns, and asynchronous behavior. This book covers Continuous Delivery, DevOps, infrastructure-as-code, containers, container orchestration technologies, such as Docker and Kubernetes, and why and especially how Java EE fits into this world. It also covers the requirements behind containerized, zero-dependency applications and how modern Java EE application servers support these approaches. You will also learn about automated, fast, and reliable software tests, in different test levels, scopes, and test technologies. This book covers the prerequisites and challenges of distributed systems that lead to microservice, shared-nothing architectures. The challenges and solutions of consistency versus scalability will further lead us to event sourcing, event-driven architectures, and the CQRS principle. This book also includes the nuts and bolts of application performance as well as how to realize resilience, logging, monitoring and tracing in a modern enterprise world. Last but not least the demands of securing enterprise systems are covered. By the end, you will understand the ins and outs of Java EE so that you can make critical design decisions that not only live up to, but also surpass your clients' expectations. Style and approach This book focuses on solving business problems and meeting customer demands in the enterprise world. It covers how to create enterprise applications with reasonable technology choices, free of cargo-cult and over-engineering. The aspects shown in this book not only demonstrate how to realize a certain solution, but also explain its motivations and reasoning.