Harness the power of PolyBase data virtualization software to make data from a variety of sources easily accessible through SQL queries while using the T-SQL skills you already know and have mastered. PolyBase Revealed shows you how to use the PolyBase feature of SQL Server 2019 to integrate SQL Server with Azure Blob Storage, Apache Hadoop, other SQL Server instances, Oracle, Cosmos DB, Apache Spark, and more. You will learn how PolyBase can help you reduce storage and other costs by avoiding the need for ETL processes that duplicate data in order to make it accessible from one source. PolyBase makes SQL Server into that one source, and T-SQL is your golden ticket. The book also covers PolyBase scale-out clusters, allowing you to distribute PolyBase queries among several SQL Server instances, thus improving performance. With great flexibility comes great complexity, and this book shows you where to look when queries fail, complete with coverage of internals, troubleshooting techniques, and where to find more information on obscure cross-platform errors. Data virtualization is a key target for Microsoft with SQL Server 2019. This book will help you keep your skills current, remain relevant, and build new business and career opportunities around Microsoft’s product direction. What You Will LearnInstall and configure PolyBase as a stand-alone service, or unlock its capabilities with a scale-out cluster Understand how PolyBase interacts with outside data sources while presenting their data as regular SQL Server tables Write queries combining data from SQL Server, Apache Hadoop, Oracle, Cosmos DB, Apache Spark, and more Troubleshoot PolyBase queries using SQL Server Dynamic Management Views Tune PolyBase queries using statistics and execution plans Solve common business problems, including "cold storage" of infrequently accessed data and simplifying ETL jobs Who This Book Is For SQL Server developers working in multi-platform environments who want one easy way of communicating with, and collecting data from, all of these sources

Get up to speed on the game-changing developments in SQL Server 2019. No longer just a database engine, SQL Server 2019 is cutting edge with support for machine learning (ML), big data analytics, Linux, containers, Kubernetes, Java, and data virtualization to Azure. This is not a book on traditional database administration for SQL Server. It focuses on all that is new for one of the most successful modernized data platforms in the industry. It is a book for data professionals who already know the fundamentals of SQL Server and want to up their game by building their skills in some of the hottest new areas in technology. SQL Server 2019 Revealed begins with a look at the project's team goal to integrate the world of big data with SQL Server into a major product release. The book then dives into the details of key new capabilities in SQL Server 2019 using a “learn by example” approach for Intelligent Performance, security, mission-critical availability, and features for the modern developer. Also covered are enhancements to SQL Server 2019 for Linux and gain a comprehensive look at SQL Server using containers and Kubernetes clusters. The book concludes by showing you how to virtualize your data access with Polybase to Oracle, MongoDB, Hadoop, and Azure, allowing you to reduce the need for expensive extract, transform, and load (ETL) applications. You will then learn how to take your knowledge of containers, Kubernetes, and Polybase to build a comprehensive solution called Big Data Clusters, which is a marquee feature of 2019. You will also learn how to gain access to Spark, SQL Server, and HDFS to build intelligence over your own data lake and deploy end-to-end machine learning applications. What You Will LearnImplement Big Data Clusters with SQL Server, Spark, and HDFS Create a Data Hub with connections to Oracle, Azure, Hadoop, and other sourcesCombine SQL and Spark to build a machine learning platform for AI applicationsBoost your performance with no application changes using Intelligent PerformanceIncrease security of your SQL Server through Secure Enclaves and Data ClassificationMaximize database uptime through online indexing and Accelerated Database RecoveryBuild new modern applications with Graph, ML Services, and T-SQL Extensibility with JavaImprove your ability to deploy SQL Server on Linux Gain in-depth knowledge to run SQL Server with containers and KubernetesKnow all the new database engine features for performance, usability, and diagnosticsUse the latest tools and methods to migrate your database to SQL Server 2019Apply your knowledge of SQL Server 2019 to Azure Who This Book Is For IT professionals and developers who understand the fundamentals of SQL Server and wish to focus on learning about the new, modern capabilities of SQL Server 2019. The book is for those who want to learn about SQL Server 2019 and the new Big Data Clusters and AI feature set, support for machine learning and Java, how to run SQL Server with containers and Kubernetes, and increased capabilities around Intelligent Performance, advanced security, and high availability.

Design, build, and justify an optimal Microsoft IoT footprint to meet your project needs. This book describes common Internet of Things components and architecture and then focuses on Microsoft’s Azure components relevant in deploying these solutions. Microsoft-specific topics addressed include: deploying edge devices and pushing intelligence to the edge; connecting IoT devices to Azure and landing data there, applying Azure Machine Learning, analytics, and Cognitive Services; roles for Microsoft solution accelerators and managed solutions; and integration of the Azure footprint with legacy infrastructure. The book concludes with a discussion of best practices in defining and developing solutions and creating a plan for success. What You Will LearnDesign the right IoT architecture to deliver solutions for a variety of project needs Connect IoT devices to Azure for data collection and delivery of services Use Azure Machine Learning and Cognitive Services to deliver intelligence in cloud-based solutions and at the edge Understand the benefits and tradeoffs of Microsoft's solution accelerators and managed solutions Investigate new use cases that are described and apply best practices in deployment strategies Integrate cutting-edge Azure deployments with existing legacy data sources Who This Book Is For Developers and architects new to IoT projects or new to Microsoft Azure IoT components as well as readers interested in best practices used in architecting IoT solutions that utilize the Azure platform

This book highlights the developments, discoveries, and practical and advanced experiences related to responsive distributed computing and how it can support the deployment of trajectory-based applications in smart systems. Smart Trajectories: Metamodeling, Reactive Architecture for Analytics and Smart Applications deals with the representation and manipulation of smart trajectories in various applications and scenarios. Presented in three parts, the book first discusses the foundation and principles for spatial information systems, complex event processing, and building a reactive architecture. Next, the book discusses modeling and architecture in relation to smart trajectory metamodeling, mining and big trajectory data, and clustering trajectories. The final section discusses advanced applications and trends in the field, including congestion trajectory analytics and real-time Big Data analytics in cloud ecosystems. Metamodeling, distributed architectures, reactive programming, Big Data analytics, NoSQL databases, connected objects, and edge-fog-cloud computing form the basis of the concepts and applications discussed. The book also presents a number of case studies to demonstrate smart trajectories related to spatiotemporal events such as traffic congestion and pedestrian accidents. This book is intended for graduate students in computer engineering, spatial databases, complex event processing, distributed systems, and geographical information systems (GIS). The book will also be useful for practicing traffic engineers, city managers, and environmental engineers interested in monitoring and security analysis.