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.

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.

Master the art of developing message-based applications with RabbitMQAbout This BookLearn how to administer, manage, and extend your own message broker, RabbitMQDevelop clients to make a message bridge between your software systems using RabbitMQDiscover how to achieve proficiency with RabbitMQ with the well-defined de*ions of the topicsWho This Book Is ForIf you are an intermediate-level RabbitMQ developer, who wants to achieve professional-level expertise in the subject, this book is for you. You’ll also need to have a decent understanding of message queuing.What You Will LearnAdminister RabbitMQ using different toolsUnderstand the roots and details of messaging, message brokers, and AMQP protocolScale the RabbitMQ server using the clusters and high availability techniquesExtend RabbitMQ by developing the Erlang OTP-based applications that use the RabbitMQ APIManage the RabbitMQ server using its powerful toolsMonitor the RabbitMQ Server using different open source tools such as Nagios, Munin, and ZabbixEnsure your RabbitMQ’s security using SSL, SASL, and access controlDevelop RabbitMQ clients using Java, Python, and C# with an industry exampleIn DetailRabbitMQ is one of the most powerful Open Source message broker software, which is widely used in tech companies such as Mozilla, VMware, Google, AT&T, and so on. RabbitMQ gives you lots of fantastic and easy-to-manage functionalities to control and manage the messaging facility with lots of community support. As scalability is one of our major modern problems, messaging with RabbitMQ is the main part of the solution to this problem.This book explains and demonstrates the RabbitMQ server in a detailed way. It provides you with lots of real-world examples and advanced solutions to tackle the scalability issues.You’ll begin your journey with the installation and configuration of the RabbitMQ server, while also being given specific details pertaining to the subject. Next, you’ll study the major problems that our server faces, including scalability and high availability, and try to get the solutions for both of these issues by using the RabbitMQ mechanisms. Following on from this, you’ll get to design and develop your own plugins using the Erlang language and RabbitMQ’s internal API. This knowledge will help you to start with the management and monitoring of the messages, tools, and applications. You’ll also gain an understanding of the security and integrity of the messaging facilities that RabbitMQ provides. In the last few chapters, you will build and keep track of your clients (senders and receivers) using Java, Python, and C#.Style and approach An easy-to-follow guide, full of hands-on examples based around managing, monitoring, extending, and securing RabbitMQ and its internal tools. You will learn how to develop your own clients using Java, Python, and C#.

Leverage the power of Scala with different tools to build scalable, robust data science applicationsAbout This BookA complete guide for scalable data science solutions, from data ingestion to data visualizationDeploy horizontally scalable data processing pipelines and take advantage of web frameworks to build engaging visualizationsBuild functional, type-safe routines to interact with relational and NoSQL databases with the help of tutorials and examples providedWho This Book Is ForIf you are a Scala developer or data scientist, or if you want to enter the field of data science, then this book will give you all the tools you need to implement data science solutions.What You Will LearnTransform and filter tabular data to extract features for machine learningImplement your own algorithms or take advantage of MLLib’s extensive suite of models to build distributed machine learning pipelinesRead, transform, and write data to both SQL and NoSQL databases in a functional mannerWrite robust routines to query web APIsRead data from web APIs such as the GitHub or Twitter APIUse Scala to interact with MongoDB, which offers high performance and helps to store large data sets with uncertain query requirementsCreate Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizationsDeploy scalable parallel applications using Apache Spark, loading data from HDFS or HiveIn DetailScala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and *ing language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines.This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala.Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and modelling your data, starting from simple concurrency constructs such as parallel collections and futures, through to actor systems and Apache Spark. As well as Scala’s emphasis on functional structures and immutability, you will learn how to use the right parallel construct for the job at hand, minimizing development time without compromising scalability. Finally, you will learn how to build beautiful interactive visualizations using web frameworks.This book gives tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed with building data science and data engineering solutions.Style and approachA tutorial with complete examples, this book will give you the tools to start building useful data engineering and data science solutions straightaway

Learn Database design, development,and administration using the feature-rich SQL Developer 4.1 interfaceAbout This BookExplore all the SQL Developer 4.1 features useful for Oracle database developers, architects, and administratorsUnderstand how this free tool from Oracle has evolved over the years and has become a complete tool that makes life easy for Oracle and third-party database usersThe author, Ajith Narayanan, has a total of 10+ years of work experience as an Oracle [APPS] DBAWho This Book Is ForThis book is intended for Oracle developers who are responsible for database management. You are expected to have programming knowledge of SQL and PL/SQL, and must be familiar with basic Oracle database concepts.What You Will LearnInstall and navigate through all the advanced features of SQL Developer that were introduced in version 4.1Browse, create, edit, and delete (drop) database objectsUse the SQL worksheet to run SQL statements and *s, edit and debug PL/SQL code, manipulate and export (unload) dataCarry out all DBA-related activities such as exporting/importing, tuning, and analyzing database performance issuesQuickly analyze, create, and edit the data model using data modelerExtend the SQL developer capabilities by exploring the APEX related pages, enabling and working with RESTful servicesUse the available reports and create new custom reports with custom *sGrasp how to connect to third-party databases and work smoothly with themIn DetailAt times, DBAs support 100s of databases at work. In such scenarios, using a command-line tool like putty adds to the difficulty, while SQL Developer makes the life of a developer, DBA, or DB architect easier by providing a graphical user interface equipped with features that can bolster and enhance the user experience and boost efficiency. Features such as DBA panel, Reports, Data Modeler, and Data Miner are just a few examples of its rich features, and its support for APEX, REST Services, timesten, and third-party database drivers demonstrate its extensibility.You may be a newbie to databases or a seasoned database expert, either way this book will help you understand the database structure and the different types of objects that organize enterprise data in an efficient manner. This book introduces the features of the SQL Developer 4.1 tool in an incremental fashion, starting with installing them, making the database connections, and using the different panels. By sequentially walking through the steps in each chapter, you will quickly master SQL Developer 4.1.Style and approachThis book follows a step-by-step approach and is in a conversational and easy-to-follow style. Screenshots , and detailed explanations of the basic and advanced features of SQL Developer 4.1 that will make your work and life easy.

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.

Over 90 hands-on recipes to help you learn and master the intricacies of Apache Hadoop 2.X, YARN, Hive, Pig, Oozie, Flume, Sqoop, Apache Spark, and Mahout About This Book Implement outstanding Machine Learning use cases on your own analytics models and processes. Solutions to common problems when working with the Hadoop ecosystem. Step-by-step implementation of end-to-end big data use cases. Who This Book Is For Readers who have a basic knowledge of big data systems and want to advance their knowledge with hands-on recipes. What You Will Learn Installing and maintaining Hadoop 2.X cluster and its ecosystem. Write advanced Map Reduce programs and understand design patterns. Advanced Data Analysis using the Hive, Pig, and Map Reduce programs. Import and export data from various sources using Sqoop and Flume. Data storage in various file formats such as Text, Sequential, Parquet, ORC, and RC Files. Machine learning principles with libraries such as Mahout Batch and Stream data processing using Apache Spark In Detail Big data is the current requirement. Most organizations produce huge amount of data every day. With the arrival of Hadoop-like tools, it has become easier for everyone to solve big data problems with great efficiency and at minimal cost. Grasping Machine Learning techniques will help you greatly in building predictive models and using this data to make the right decisions for your organization. Hadoop Real World Solutions Cookbook gives readers insights into learning and mastering big data via recipes. The book not only clarifies most big data tools in the market but also provides best practices for using them. The book provides recipes that are based on the latest versions of Apache Hadoop 2.X, YARN, Hive, Pig, Sqoop, Flume, Apache Spark, Mahout and many more such ecosystem tools. This real-world-solution cookbook is packed with handy recipes you can apply to your own everyday issues. Each chapter provides in-depth recipes that can be referenced easily. This book provides detailed practices on the latest technologies such as YARN and Apache Spark. Readers will be able to consider themselves as big data experts on completion of this book. This guide is an invaluable tutorial if you are planning to implement a big data warehouse for your business. Style and approach An easy-to-follow guide that walks you through world of big data. Each tool in the Hadoop ecosystem is explained in detail and the recipes are placed in such a manner that readers can implement them sequentially. Plenty of reference links are provided for advanced reading.

Master the art of machine learning with .NET and gain insight into real-world applications About This Book Based on .NET framework 4.6.1, includes examples on ASP.NET Core 1.0 Set up your business application to start using machine learning techniques Familiarize the user with some of the more common .NET libraries for machine learning Implement several common machine learning techniques Evaluate, optimize and adjust machine learning models Who This Book Is For This book is targeted at .Net developers who want to build complex machine learning systems. Some basic understanding of data science is required. What You Will Learn Write your own machine learning applications and experiments using the latest .NET framework, including .NET Core 1.0 Set up your business application to start using machine learning. Accurately predict the future using regressions. Discover hidden patterns using decision trees. Acquire, prepare, and combine datasets to drive insights. Optimize business throughput using Bayes Classifier. Discover (more) hidden patterns using KNN and Na?ve Bayes. Discover (even more) hidden patterns using K-Means and PCA. Use Neural Networks to improve business decision making while using the latest ASP.NET technologies. Explore “Big Data”, distributed computing, and how to deploy machine learning models to IoT devices – making machines self-learning and adapting Along the way, learn about Open Data, Bing maps, and MBrace In Detail .Net is one of the widely used platforms for developing applications. With the meteoric rise of Machine learning, developers are now keen on finding out how can they make their .Net applications smarter. Also, .NET developers are interested into moving into the world of devices and how to apply machine learning techniques to, well, machines. This book is packed with real-world examples to easily use machine learning techniques in your business applications. You will begin with introduction to F# and prepare yourselves for machine learning using .NET framework. You will be writing a simple linear regression model using an example which predicts sales of a product. Forming a base with the regression model, you will start using machine learning libraries available in .NET framework such as Math.NET, Numl.NET and Accord.NET with the help of a sample application. You will then move on to writing multiple linear regressions and logistic regressions. You will learn what is open data and the awesomeness of type providers. Next, you are going to address some of the issues that we have been glossing over so far and take a deep dive into obtaining, cleaning, and organizing our data. You will compare the utility of building a KNN and Naive Bayes model to achieve best possible results. Implementation of Kmeans and PCA using Accord.NET and Numl.NET libraries is covered with the help of an example application. We will then look at many of issues confronting creating real-world machine learning models like overfitting and how to combat them using confusion matrixes, scaling, normalization, and feature selection. You will now enter into the world of Neural Networks and move your line of business application to a hybrid scientific application. After you have covered all the above machine learning models, you will see how to deal with very large datasets using MBrace and how to deploy machine learning models to Internet of Thing (IoT) devices so that the machine can learn and adapt on the fly. Style and approach This book will guide you in learning everything about how to tackle the flood of data being encountered these days in your .NET applications with the help of popular machine learning libraries offered by the .NET framework.

This hands-on guide is aimed at practitioners of data science. The book assumes some previous skills with Julia and skills in coding in a *ing language such as Python or R, or a compiled language such as C or Java.

This book is for Elasticsearch users who want to extend their knowledge and develop new skills. Prior knowledge of the Query DSL and data indexing is expected.

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.

In order to make the most of the book, you should have a C++ programming background, knowledge of GNU/Linux systems, and general skills in computer science. No previous background in ROS is required, as this book takes you from the ground up.

This cookbook has recipes written in simple, easy to understand format with lots of screenshots and insightful tips and hints. If you are an Oracle Database Administrator, Security Manager or Security Auditor looking to secure the Oracle Database or prevent it from being hacked, then this book is for you. This book assumes you have a basic understanding of security concepts.

This is a practical book with step-by-step guidelines to integrate Silverlight 4 applications in a SharePoint 2010 Server environment. This book focuses on the integration of the two technologies and is not a primer for any of the individual technologies. It offers clear examples to successfully perform the most important integration tasks. If you are an application developer who wants to implement Silverlight 4 applications within a SharePoint 2010 environment, this book is for you. We assume that the reader has prior knowledge of Silverlight and SharePoint 2010 and this book focuses more on the integration of Silverlight with SharePoint 2010.

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.

Covering SQL Developer fundamentals as well more intermediate and advanced topics, this book uses in-depth explanation and detailed examples to help you get the most out of Oracle SQL Developer. The book has a modular structure, so that you can dip into any chapter that covers your current area of focus and get going. This book is for Oracle developers who want to ease their database development, and enhance their productivity using Oracle SQL Developer. You should have a programming knowledge of SQL and PL/SQL, and a general familiarity with Oracle database concepts.

This is a practical guide providing comprehensive solutions for SQL query problems, and is full of concrete real-world examples to help you create and troubleshoot your SQL queries in SAP Business One. If you are a system administrator who uses SQL query as your tool of choice for solving specific problems throughout SAP Business One, then this book is for you. It may also be useful if you are a developer or consultant using this technology, and can benefit end users by improving your search for important business information. A rudimentary knowledge of SAP Business One and SQL Server is required to use this book efficiently. Examples covered are relevant to SBO 2007A users, for which the 8.8 release is mostly compatible. All SQL query examples within the book are verified under SQL Server 2005, so they are guaranteed to run under this release, in addition to SQL Server 2008. Non-SAP Business One users can also gain knowledge from the many examples throughout the book. It is hard to find another book with so many SQL query examples.

This book is written in a clear conversational style, which emphasizes a practical learn-by-doing approach. This step by step guide has illustrative examples to implement Ext JS library features in your Oracle APEX applications If you are an Oracle APEX application developer who wants to take APEX applications to the next level by taking advantage of Ext JS features, this book is for you. Prior knowledge of Oracle APEX is required, however, no prior knowledge of Ext JS is required.