This book takes a step-by-step, practical approach and is filled with examples and illustrations. This book is written for a wide audience that includes teachers, system administrators, and first time developers. It also appeals to the Sakai open source community, potential community members, and decision makers working in education.

This step-by-step tutorial will take you through Oracle PeopleSoft Financial Management 9.1 and show you how to implement it into your business. It is written in an easy-to-read style, with a strong emphasis on real-world, practical examples with step-by-step explanations. This book will establish a solid foundation for your efforts to become a successful PeopleSoft Financials practitioner. If you are a functional implementation analyst, a business analyst, or a business user who plans to start using PeopleSoft applications, this book is for you. Reading this book will equip you with the basic skills to configure and maintain PeopleSoft financial applications.

Explore the capabilities of Dynamics NAV 2016 and discover all you need to implement it About This Book Learn the key roles of your Dynamics NAV partner and the roles within your customer’s organization Create configuration packages and perform data migration on your own Find out how to troubleshoot your problems effectively with your Dynamics NAV partner Who This Book Is For This book is for Dynamics NAV partners and end users who want to know everything about Dynamics NAV implementations. It is aimed at those who want to be project managers or get involved with Dynamics NAV, but do not have the expertise to write code themselves. What You Will Learn Study the roles within a Dynamics NAV partner and within a customer’s company Create reusable data migration packages Work with the debugger to pinpoint error messages Get to grips with the key tables used in data reporting and analysis Successfully upgrade your installation to the latest version Manage and expand your existing installation with additional functionalities Explore the free third-party add-ons that can leverage your existing installation In Detail Microsoft Dynamics NAV 2016 is an Enterprise Resource Planning (ERP) application used in all kinds of organizations around the world. It provides a great variety of functionality out-of-the-box in different topics such as accounting, sales, purchase processing, logistics, or manufacturing. It also allows companies to grow the application by customizing the solution to meet specific requirements. This book is a hands-on tutorial on working with a real Dynamics NAV implementation. You will learn about the team from your Microsoft Dynamics NAV partner as well as the team within the customer’s company. This book provides an insight into the different tools available to migrate data from the client’s legacy system into Microsoft Dynamics NAV. If you are already live with Microsoft Dynamics NAV, this books talks about upgrades and what to expect from them. We’ll also show you how to implement additional or expanding functionalities within your existing Microsoft Dynamics NAV installation, perform data analysis, debug error messages, and implement free third-party add-ons to your existing installation. This book will empower you with all the skills and knowledge you need for a successful implementation. Style and approach This book is step-by-step guide to implementing Dynamics NAV from start to finish.

Write efficient, clean, and reusable code with ScalaAbout This BookUnleash the power of Scala and apply it in the real worldIncrease your efficiency by leveraging the power of Creational, Structural, Behavioural, and Functional design patternsBuild object oriented and functional applications quickly and effectivelyWho This Book Is ForIf you want to increase your understanding of Scala and apply it to real-life application development, then this book is for you. We’ve also designed the book to be used as a quick reference guide while creating applications. Previous Scala programming knowledge is expected.What You Will LearnImmerse yourself in industry-standard design patterns—structural, creational, and behavioral—to create extraordinary applicationsFeel the power of traits and their application in ScalaImplement abstract and self types and build clean design patternsBuild complex entity relationships using structural design patternsCreate applications faster by applying functional design patternsIn DetailScala has become increasingly popular in many different IT sectors. The language is exceptionally feature-rich which helps developers write less code and get faster results. Design patterns make developer’s lives easier by helping them write great software that is easy to maintain, runs efficiently and is valuable to the company or people concerned.You will learn about the various features of Scala and be able to apply well-known, industry-proven design patterns in your work. The book starts off by focusing on some of the most interesting features of Scala while using practical real-world examples. We will also cover the popular "Gang of Four" design patterns and show you how to incorporate functional patterns effectively. By the end of this book, you will have enough knowledge and understanding to quickly assess problems and come up with elegant solutions.Style and approachThe design patterns in the book will be explained using real-world, step-by-step examples. For each design pattern, there will be hints about when to use it and when to look for something more suitable. This book can also be used as a practical guide, showing you how to leverage design patterns effectively.

Understand everything you need to know about Oracle’s Integration Cloud Service and how to utilize it optimally for your business About This Book The only guide to Integration Cloud Service in the market Focused on practical action to deliver business value A professional’s guide to an expensive product, providing comprehensive training, and showing how to extract real business value from the product Who This Book Is For This book is ideal for any IT professional working with ICS, any Oracle application or cloud solution developer or analyst who wants to work with ICS to deliver business value. What You Will Learn Use ICS to integrate different systems together without needing to be a developer Gain understanding of what a number of technologies and standards provide – without needing to understand the fine details of those standards and technologies Understand the use of connectors that Oracle provide from technology based connections such as file and database connections to SaaS solutions ranging from Salesforce to Twitter Enrich data and extend SaaS integration to route to different instances Utilize a number of tools to help develop and check that your integrations work before connecting to live systems Introduce and explain integration concepts so that the integrations created are maintainable and sustainable for the longer term Provide details on how to keep up to date with the features that Oracle and partners provide in the future Get special connections developed to work with ICS In Detail Businesses are built on data, and applications that access that data. In modern businesses the same cloud-based data stores and applications might be accessed by hundreds of different applications from thousands of different devices via APIs. To make this happen, APIs must be wired together i.e. integrated. Oracle Integration Cloud Service provides a complete method for integrating enterprise applications in the cloud. Integration Cloud Service (ICS) provides a cloud hosted means to integrate systems together using a graphical means to define and represent integrations. This book will be a comprehensive, hands-on guide to building successful, high-availability integrations on ICS. This book sets out to demonstrate how ICS can be used to effectively implement integrations that work both in the cloud and on premise. It starts with a fast, practical introduction to what ICS can do for your business and then shows how ICS allows you to develop integrations not only quickly but in a way that means they are maintainable and extensible. Gradually it moves into more advanced integrations, showing how to achieve sophisticated results with ICS and work with external applications. Finally the book shows you how to monitor cloud apps and go beyond ICS to build even more powerful integrated applications. By the end of the book, you will the knowledge on how to use ICS to solve your own integration needs and harness the technologies in a maintainable and sustainable manner. Style and approach This book will take a pragmatic approach and will be a business-focused guide to delivering business value with ICS.

Expert tabular modeling techniques for building and deploying cutting-edge business analytical reporting solutions About This Book Build and deploy Tabular Model projects from relational data sources Leverage DAX and create high-performing calculated fields and measures Create ad-hoc reports based on a Tabular Model solution Useful tips to monitor and optimize your tabular solutions Who This Book Is For This book is for SQL BI professionals and Architects who want to exploit the full power of the new Tabular models in Analysis Services. Some knowledge of previous versions of Analysis services would be helpful but is not essential. What You Will Learn Learn all about Tabular services mode and how it speeds up development Build solutions using sample datasets Explore built-in actions and transitions in SSAS 2016 Implement row-column, and role-based security in a Tabular Data model Realize the benefits of in-memory and DirectQuery deployment modes Get up to date with the new features added to SQL Server 2016 Analysis Services Optimize Data Models and Relationships Usage In Detail SQL Server Analysis Service (SSAS) has been widely used across multiple businesses to build smart online analytical reporting solutions. It includes two different types of modeling for analysis services: Tabular and Multi Dimensional. This book covers Tabular modeling, which uses tables and relationships with a fast in-memory engine to provide state of the art compression algorithms and query performance. The book begins by quickly taking you through the concepts required to model tabular data and set up the necessary tools and services. As you learn to create tabular models using tools such as Excel and Power View, you’ll be shown various strategies to deploy your model on the server and choose a query mode (In-memory or DirectQuery) that best suits your reporting needs. You’ll also learn how to implement key and newly introduced DAX functions to create calculated columns and measures for your model data. Last but not least, you’ll be shown techniques that will help you administer and secure your BI implementation along with some widely used tips and tricks to optimize your reporting solution. By the end of this book, you’ll have gained hands-on experience with the powerful new features that have been added to Tabular models in SSAS 2016 and you’ll be able to improve user satisfaction with faster reports and analytical queries. Style and approach This book takes a practical, recipe-based approach where each recipe lists the steps to address or implement a solution. You will be provided with several approaches to creating a business intelligence semantic model using analysis services.

Make the most of your NAV deployment by extending and customizing it with a variety of expert tools About This Book Extend Dynamics in a cost-effective manner by using tools that are ready at your disposal Solve common business problems with the valuable features and flexibility of Dynamics NAV Follow practical and easy-to-grasp examples, illustrations, and coding to make the most out of Dynamics NAV in your organisation Who This Book Is For This book is for Dynamics NAV developers and administrators who have a good knowledge level and understanding of Dynamics NAV application development and administration. What You Will Learn Develop a module in Dynamics NAV using C/AL Build relationships with COM technologies Develop and integrate COM with Dynamics NAV 2016 Call the framework members from C/AL Develop an event in the .NET framework and see how to subscribe to it using C/AL Automate the deployment into Dynamics NAV Develop Windows Client Control add-Ins Deploy your resource automatically from Visual Studio Install and Configure Windows Client Control add-Ins Integrate Dynamics NAV with Sharepoint In Detail Microsoft Dynamics NAV is an enterprise resource planning (ERP) software suite for organizations. The system offers specialized functionality for manufacturing, distribution, government, retail, and other industries. Its integrated development environment enables customizations with minimal disruption to business processes. The book starts explaining the new features of Dynamics NAV along with how to create and modify a simple module. Moving on, you will learn the importance of thinking beyond the boundaries of C/AL development and the possibilities opened by with it. Next, you will get to know how COM can be used to extend the functionalities of Dynamics NAV. You’ll find out how to extend the Dynamics NAV 2016 version using .NET interoperability and will see the steps required to subscribe to .NET events in order to extend Dynamics NAV. Finally, you’ll see the cmdlets available to manage extension packages. By the end of the book, you will have the knowledge needed to become more efficient in selecting the extending methods, developing and deploying them to the Dynamics NAV, and practicing the best practices. Style and approach The book follows a practical recipe-based approach focusing on real-world scenarios and giving you all the information you need to build a strong Dynamics NAV implementation.

Become an advanced practitioner with this progressive set of master classes on application-oriented machine learning About This Book ? Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects ? More than 15 open source Java tools in a wide range of techniques, with code and practical usage. ? More than 10 real-world case studies in machine learning highlighting techniques ranging from data ingestion up to analyzing the results of experiments, all preparing the user for the practical, real-world use of tools and data analysis. Who This Book Is For This book will appeal to anyone with a serious interest in topics in Data Science or those already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have experience with the fundamentals of machine learning and now have a desire to explore the area further, are up to grappling with the mathematical complexities of its algorithms, and you wish to learn the complete ins and outs of practical machine learning. What You Will Learn ? Master key Java machine learning libraries, and what kind of problem each can solve, with theory and practical guidance. ? Explore powerful techniques in each major category of machine learning such as classification, clustering, anomaly detection, graph modeling, and text mining. ? Apply machine learning to real-world data with methodologies, processes, applications, and analysis. ? Techniques and experiments developed around the latest specializations in machine learning, such as deep learning, stream data mining, and active and semi-supervised learning. ? Build high-performing, real-time, adaptive predictive models for batch- and stream-based big data learning using the latest tools and methodologies. ? Get a deeper understanding of technologies leading towards a more powerful AI applicable in various domains such as Security, Financial Crime, Internet of Things, social networking, and so on. In Detail Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science. This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today. On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain. Style and approach A practical guide to help you explore machine learning—and an array of Java-based tools and frameworks—with the help of practical examples and real-world use cases.

Build smarter and efficient database application systems for your organization with SQL Server 2017 About This Book ? Build database applications by using the development features of SQL Server 2017 ? Work with temporal tables to get information stored in a table at any time ? Use adaptive querying to enhance the performance of your queries Who This Book Is For Database developers and solution architects looking to design efficient database applications using SQL Server 2017 will find this book very useful. In addition, this book will be valuable to advanced analysis practitioners and business intelligence developers. Database consultants dealing with performance tuning will get a lot of useful information from this book as well. Some basic understanding of database concepts and T-SQL is required to get the best out of this book. What You Will Learn ? Explore the new development features introduced in SQL Server 2017 ? Identify opportunities for In-Memory OLTP technology ? Use columnstore indexes to get storage and performance improvements ? Exchange JSON data between applications and SQL Server ? Use the new security features to encrypt or mask the data ? Control the access to the data on the row levels ? Discover the potential of R and Python integration ? Model complex relationships with the graph databases in SQL Server 2017 In Detail Microsoft SQL Server 2017 is the next big step in the data platform history of Microsoft as it brings in the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. Compared to its predecessor, SQL Server 2017 has evolved into Machine Learning with R services for statistical analysis and Python packages for analytical processing. This book prepares you for more advanced topics by starting with a quick introduction to SQL Server 2017’s new features and a recapitulation of the possibilities you may have already explored with previous versions of SQL Server. The next part introduces you to enhancements in the Transact-SQL language and new database engine capabilities and then switches to a completely new technology inside SQL Server: JSON support. We also take a look at the Stretch database, security enhancements, and temporal tables. Furthermore, the book focuses on implementing advanced topics, including Query Store, columnstore indexes, and In-Memory OLTP. Towards the end of the book, you’ll be introduced to R and how to use the R language with Transact-SQL for data exploration and analysis. You’ll also learn to integrate Python code in SQL Server and graph database implementations along with deployment options on Linux and SQL Server in containers for development and testing. By the end of this book, you will have the required information to design efficient, high-performance database applications without any hassle. Style and approach This book is a detailed guide to mastering the development features offered by SQL Server 2017, with a unique learn-as-you-do approach. All the concepts are explained in a very easy-to-understand manner and are supplemented with examples to ensure that you—the developer—are able to take that next step in building more powerful, robust applications for your organization with ease.

A comprehensive guide to mastering the most advanced Hadoop 3 concepts Key Features * Get to grips with the newly introduced features and capabilities of Hadoop 3 * Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem * Sharpen your Hadoop skills with real-world case studies and code Book Description Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency. With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals. By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines. What you will learn * Gain an in-depth understanding of distributed computing using Hadoop 3 * Develop enterprise-grade applications using Apache Spark, Flink, and more * Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance * Explore batch data processing patterns and how to model data in Hadoop * Master best practices for enterprises using, or planning to use, Hadoop 3 as a data platform * Understand security aspects of Hadoop, including authorization and authentication Who this book is for If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You’ll also find this book useful if you’re a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.

Over 170 advanced recipes to search, analyze, deploy, manage, and monitor data effectively with Elasticsearch 5.x About This Book Deploy and manage simple Elasticsearch nodes as well as complex cluster topologies Write native plugins to extend the functionalities of Elasticsearch 5.x to boost your business Packed with clear, step-by-step recipes to walk you through the capabilities of Elasticsearch 5.x Who This Book Is For If you are a developer who wants to get the most out of Elasticsearch for advanced search and analytics, this is the book for you. Some understanding of JSON is expected. If you want to extend Elasticsearch, understanding of Java and related technologies is also required. What You Will Learn Choose the best Elasticsearch cloud topology to deploy and power it up with external plugins Develop tailored mapping to take full control of index steps Build complex queries through managing indices and documents Optimize search results through executing analytics aggregations Monitor the performance of the cluster and nodes Install Kibana to monitor cluster and extend Kibana for plugins Integrate Elasticsearch in Java, Scala, Python and Big Data applications In Detail Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. This book is your one-stop guide to master the complete Elasticsearch ecosystem. We’ll guide you through comprehensive recipes on what’s new in Elasticsearch 5.x, showing you how to create complex queries and analytics, and perform index mapping, aggregation, and *ing. Further on, you will explore the modules of Cluster and Node monitoring and see ways to back up and restore a snapshot of an index. You will understand how to install Kibana to monitor a cluster and also to extend Kibana for plugins. Finally, you will also see how you can integrate your Java, Scala, Python, and Big Data applications such as Apache Spark and Pig with Elasticsearch, and add enhanced functionalities with custom plugins. By the end of this book, you will have an in-depth knowledge of the implementation of the Elasticsearch architecture and will be able to manage data efficiently and effectively with Elasticsearch. Style and approach This book follows a problem-solution approach to effectively use and manage Elasticsearch. Each recipe focuses on a particular task at hand, and is explained in a very simple, easy to understand manner.

Get the most out of the Elastic Stack for various complex analytics using this comprehensive and practical guide About This Book Your one-stop solution to perform advanced analytics with Elasticsearch, Logstash, and Kibana Learn how to make better sense of your data by searching, analyzing, and logging data in a systematic way This highly practical guide takes you through an advanced implementation on the ELK stack in your enterprise environment Who This Book Is For This book cater to developers using the Elastic stack in their day-to-day work who are familiar with the basics of Elasticsearch, Logstash, and Kibana, and now want to become an expert at using the Elastic stack for data analytics. What You Will Learn Build a pipeline with help of Logstash and Beats to visualize Elasticsearch data in Kibana Use Beats to ship any type of data to the Elastic stack Understand Elasticsearch APIs, modules, and other advanced concepts Explore Logstash and it’s plugins Discover how to utilize the new Kibana UI for advanced analytics See how to work with the Elastic Stack using other advanced configurations Customize the Elastic Stack and plugin development for each of the component Work with the Elastic Stack in a production environment Explore the various components of X-Pack in detail. In Detail Even structured data is useless if it can’t help you to take strategic decisions and improve existing system. If you love to play with data, or your job requires you to process custom log formats, design a scalable analysis system, and manage logs to do real-time data analysis, this book is your one-stop solution. By combining the massively popular Elasticsearch, Logstash, Beats, and Kibana, elastic.co has advanced the end-to-end stack that delivers actionable insights in real time from almost any type of structured or unstructured data source. If your job requires you to process custom log formats, design a scalable analysis system, explore a variety of data, and manage logs, this book is your one-stop solution. You will learn how to create real-time dashboards and how to manage the life cycle of logs in detail through real-life scenarios. This book brushes up your basic knowledge on implementing the Elastic Stack and then dives deeper into complex and advanced implementations of the Elastic Stack. We’ll help you to solve data analytics challenges using the Elastic Stack and provide practical steps on centralized logging and real-time analytics with the Elastic Stack in production. You will get to grip with advanced techniques for log analysis and visualization. Newly announced features such as Beats and X-Pack are also covered in detail with examples. Toward the end, you will see how to use the Elastic stack for real-world case studies and we’ll show you some best practices and troubleshooting techniques for the Elastic Stack. Style and approach This practical guide shows you how to perform advanced analytics with the Elastic stack through real-world use cases. It includes common and some not so common scenarios to use the Elastic stack for data analysis.

"Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. About This Book ?Explore and create intelligent systems using cutting-edge deep learning techniques ?Implement deep learning algorithms and work with revolutionary libraries in Python ?Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more Who This Book Is For This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired. What You Will Learn ?Get a practical deep dive into deep learning algorithms ?Explore deep learning further with Theano, Caffe, Keras, and TensorFlow ?Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines ?Dive into Deep Belief Nets and Deep Neural Networks ?Discover more deep learning algorithms with Dropout and Convolutional Neural Networks ?Get to know device strategies so you can use deep learning algorithms and libraries in the real world In Detail With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries. The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results. Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques. Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside. Style and approach Python Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects. "

Design, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API About This Book ? Learn about the design and implementation of streaming applications, machine learning pipelines, deep learning, and large-scale graph processing applications using Spark SQL APIs and Scala. ? Learn data exploration, data munging, and how to process structured and semi-structured data using real-world datasets and gain hands-on exposure to the issues and challenges of working with noisy and "dirty" real-world data. ? Understand design considerations for scalability and performance in web-scale Spark application architectures. Who This Book Is For If you are a developer, engineer, or an architect and want to learn how to use Apache Spark in a web-scale project, then this is the book for you. It is assumed that you have prior knowledge of SQL querying. A basic programming knowledge with Scala, Java, R, or Python is all you need to get started with this book. What You Will Learn ? Familiarize yourself with Spark SQL programming, including working with DataFrame/Dataset API and SQL ? Perform a series of hands-on exercises with different types of data sources, including CSV, JSON, Avro, MySQL, and MongoDB ? Perform data quality checks, data visualization, and basic statistical analysis tasks ? Perform data munging tasks on publically available datasets ? Learn how to use Spark SQL and Apache Kafka to build streaming applications ? Learn key performance-tuning tips and tricks in Spark SQL applications ? Learn key architectural components and patterns in large-scale Spark SQL applications In Detail In the past year, Apache Spark has been increasingly adopted for the development of distributed applications. Spark SQL APIs provide an optimized interface that helps developers build such applications quickly and easily. However, designing web-scale production applications using Spark SQL APIs can be a complex task. Hence, understanding the design and implementation best practices before you start your project will help you avoid these problems. This book gives an insight into the engineering practices used to design and build real-world, Spark-based applications. The book's hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL. It starts by familiarizing you with data exploration and data munging tasks using Spark SQL and Scala. Extensive code examples will help you understand the methods used to implement typical use-cases for various types of applications. You will get a walkthrough of the key concepts and terms that are common to streaming, machine learning, and graph applications. You will also learn key performance-tuning details including Cost Based Optimization (Spark 2.2) in Spark SQL applications. Finally, you will move on to learning how such systems are architected and deployed for a successful delivery of your project. Style and approach This book is a hands-on guide to designing, building, and deploying Spark SQL-centric production applications at scale.

Master the principles and techniques of multithreaded programming with the Java 8 Concurrency APIAbout This BookImplement concurrent applications using the Java 8 Concurrency API and its new componentsImprove the performance of your applications or process more data at the same time, taking advantage of all of your resources.Construct real-world examples related to machine learning, data mining, image processing, and client/server environmentsWho This Book Is ForIf you are a competent Java developer with a good understanding of concurrency but have no knowledge of how to effectively implement concurrent programs or use streams to make processes more efficient, then this book is for you.What You Will LearnDesign concurrent applications by converting a sequential algorithm into a concurrent oneDiscover how to avoid all the possible problems you can get in concurrent algorithmsUse the Executor framework to manage concurrent tasks without creating threadsExtend and modify Executors to adapt their behavior to your needsSolve problems using the divide and conquer technique and the Fork/Join frameworkProcess massive data sets with parallel streams and Map/Reduce implementationControl data-race conditions using concurrent data structures and synchronization mechanismsTest and monitor concurrent applicationsIn DetailConcurrency programming allows several large tasks to be divided into smaller sub-tasks, which are further processed as individual tasks that run in parallel. All the sub-tasks are combined together once the required results are achieved; they are then merged to get the final output. The whole process is very complex. This process goes from the design of concurrent algorithms to the testing phase where concurrent applications need extra attention. Java includes a comprehensive API with a lot of ready-to-use components to implement powerful concurrency applications in an easy way, but with a high flexibility to adapt these components to your needs.The book starts with a full de*ion of design principles of concurrent applications and how to parallelize a sequential algorithm. We'll show you how to use all the components of the Java Concurrency API from basics to the most advanced techniques to implement them in powerful concurrency applications in Java.You will be using real-world examples of complex algorithms related to machine learning, data mining, natural language processing, image processing in client / server environments. Next, you will learn how to use the most important components of the Java 8 Concurrency API: the Executor framework to execute multiple tasks in your applications, the phaser class to implement concurrent tasks divided into phases, and the Fork/Join framework to implement concurrent tasks that can be split into smaller problems (using the divide and conquer technique). Toward the end, we will cover the new inclusions in Java 8 API, the Map and Reduce model, and the Map and Collect model. The book will also teach you about the data structures and synchronization utilities to avoid data-race conditions and other critical problems. Finally, the book ends with a detailed de*ion of the tools and techniques that you can use to test a Java concurrent application.Style and approach A complete guide implementing real-world examples with algorithms related to machine learning, data mining, and natural language processing in client/server environments. All the examples are explained in a step-by-step approach.

This book is written in a practical and friendly style with practical tutorials, exercises, and detailed images which will help you master the third dimension. This book is intended for everyone who wants to create accurate 3D models in AutoCAD, like architecture, engineering, or design professionals, and students. Only basic understanding of 2D AutoCAD is needed.

A practical tutorial containing clear, step-by-step explanations of all the concepts required to understand the technology involved in virtualizing your application infrastructure. Each chapter uses real-world scenarios so that the readers can put into practice what they learn immediately and with the right guidance. Each topic is written defining a common need and developing the process to solve it using Microsoft App-V. This book is for system administrators or consultants who want to master and dominate App-V, and gain a deeper understanding of the technology in order to optimize App V implementations. Even though the book does not include basic steps like installing App-V components or sequencing simple applications; application virtualization beginners will receive a comprehensive look into App-V before jumping into the technical process of each chapter.

Throughout the book, we will follow a fictional company, the case study will help you in implementing FIM 2010 R2. All the examples in the book will relate to this fictive company and you will be taken from design, to installation, to configuration of FIM 2010 R2. If you are implementing and managing FIM 2010 R2 in your business, then this book is for you. You will need to have a basic understanding of Microsoft based infrastructure using Active Directory. If you are new to Forefront Identity Management, the case-study approach of this book will help you to understand the concepts and implement them.

If you are a developer who implements ElasticSearch in your web applications and want to sharpen your understanding of the core elements and applications, this is the book for you. It is assumed that you’ve got working knowledge of JSON and, if you want to extend ElasticSearch, of Java and related technologies.

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

This book follows an example-driven, simplified, and practical approach to using OpenCL for general purpose GPU programming.If you are a beginner in parallel programming and would like to quickly accelerate your algorithms using OpenCL, this book is perfect for you! You will find the diverse topics and case studies in this book interesting and informative. You will only require a good knowledge of C programming for this book, and an understanding of parallel implementations will be useful, but not necessary.