Design documents and implement real world e-commerce applications with Couchbase About This Book Get acquainted with Couchbase architecture and design your document-based data schema Implement full text search using industry standard elastic search plugins Develop critical and high performance applications using this hands-on tutorial guide Who This Book Is For If you are new to the NoSQL document system or have little or no experience in NoSQL development and administration and are planning to deploy Couchbase for your next project, then this book is for you. It would be helpful to have a bit of familiarity with Java. What You Will Learn Get acquainted with the concept of NoSQL databases and configure your Couchbase database cluster Maintain Couchbase effectively using the web-based administrative console with ease Enable partition capabilities by making use of Buckets Analyze important design considerations for maintaining relationship between various documents Use Couchbase SDK Java API to store and retrieve document Write views using map/reduce to retrieve documents efficiently Get familiar with N1QL and how to use it in Java applications Integrate Couchbase with Elasticsearch to implement full text search Configure XDCR for disaster recovery and develop ecommerce application using Couchbase In Detail NoSQL database systems have changed application development in terms of adaptability to dynamics schema and scalability. Compared with the currently available NoSQL database systems, Couchbase is the fastest. Its ease of configuration and powerful features for storing different schema structures, retrieval using map reduce and inbuilt disaster recovery by replicating document across the geographical region, make it one of the most powerful, scalable and comprehensive NoSQL in the market. Couchbase also introduces smart client API for various programming language to integrate the database with the application easily, yet providing very complex features like cluster health awareness. This book achieves its goal by taking up an end-to-end development structure, right from understanding NOSQL document design to implementing full fledged eCommerce application design using Couchbase as a backend. Starting with the architecture of Couchbase to get you up and running, this book quickly takes you through designing a NoSQL document and implementing highly scalable applications using Java API. You will then be introduced to document design and get to know the various ways to administer Couchbase. Followed by this, learn to store documents using bucket. Moving on, you will then learn to store, retrieve and delete documents using smart client base on Java API. You will then retrieve documents using SQL like syntax call N1QL. Next, you will learn how to write map reduce base views. Finally, you will configure XDCR for disaster recovery and implement an eCommerce application using Couchbase. Style and approach The book starts from absolute basics and slowly moves to more advanced topics ensuring at every step that all concepts and terms are understood by the reader to have complete understanding at every stage. Technical and complex terms are explained in clear and simple language, thus making this book a perfect companion for those who have started their journey to NoSQL using Couchbase

Today’s highly interactive websites pose a challenge for traditional SQL databases—the ability to scale rapidly and serve loads of concurrent users. With this concise guide, you’ll learn how to build web applications on top of Couchbase Server 2.0, a NoSQL database that can handle websites and social media where hundreds of thousands of users read and write large volumes of information. Using food recipe information as examples, this book demonstrates how to take advantage of Couchbase’s document-oriented database design, and how to store and query data with various CRUD operations. Discover why Couchbase is better than SQL databases with memcached tiers for managing data from the most interactive portions of your application. Learn about Couchbase Server’s cluster-based architecture and how it differs from SQL databases Choose a client library for Java, .NET, Ruby, Python, PHP, or C, and connect to a cluster Structure data in a variety of formats, from serialized objects, a stream of raw bytes, or as JSON documents Learn core storage and retrieval methods, including document IDs, expiry times, and concurrent updates Create views with map/reduce and learn Couchbase mechanisms for querying and selection

This book describes important methodologies, tools and techniques from the fields of artificial intelligence, basically those which are based on relevant conceptual and formal development. The coverage is wide, ranging from machine learning to the use of data on the Semantic Web, with many new topics. The contributions are concerned with machine learning, big data, data processing in medicine, similarity processing in ontologies, semantic image analysis, as well as many applications including the use of machine leaning techniques for cloud security, artificial intelligence techniques for detecting COVID-19, the Internet of things, etc. The book is meant to be a very important and useful source of information for researchers and doctoral students in data analysis, Semantic Web, big data, machine learning, computer engineering and related disciplines, as well as for postgraduate students who want to integrate the doctoral cycle.

Get the authoritative guide to Dapr, the distributed application runtime that works with new and existing programming languages alike. Written by the model’s creators, this introduction shows you how Dapr not only unifies stateless, stateful, and actor programming models but also runs everywhere—in the cloud or on the edge. Authors Haishi Bai and Yaron Schneider, both with Microsoft’s Azure CTO team, explain that, with Dapr, you don’t need to include any SDKs or libraries in your user code. Instead, you automatically get flexible binding, state management, the actor pattern, pub-sub, reliable messaging, and many more features. This book shows developers, architects, CIOs, students, and computing enthusiasts how to get started with Dapr. Learn the new programming model for cloud native applications Write high-performance distributed applications without drilling into technical details Use Dapr with any language or framework to write microservices easily Learn how Dapr provides consistency and portability through open APIs and extensible, community-driven components Explore how Dapr handles state, resource bindings, and pub-sub messaging to enable resilient event-driven architectures that scale Integrate cloud applications with various SaaS offerings, such as machine learning

Summary Machine Learning Systems: Designs that scale is an example-rich guide that teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. Foreword by Sean Owen, Director of Data Science, Cloudera Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology If you’re building machine learning models to be used on a small scale, you don't need this book. But if you're a developer building a production-grade ML application that needs quick response times, reliability, and good user experience, this is the book for you. It collects principles and practices of machine learning systems that are dramatically easier to run and maintain, and that are reliably better for users. About the Book Machine Learning Systems: Designs that scale teaches you to design and implement production-ready ML systems. You'll learn the principles of reactive design as you build pipelines with Spark, create highly scalable services with Akka, and use powerful machine learning libraries like MLib on massive datasets. The examples use the Scala language, but the same ideas and tools work in Java, as well. What's Inside Working with Spark, MLlib, and Akka Reactive design patterns Monitoring and maintaining a large-scale system Futures, actors, and supervision About the Reader Readers need intermediate skills in Java or Scala. No prior machine learning experience is assumed. About the Author Jeff Smith builds powerful machine learning systems. For the past decade, he has been working on building data science applications, teams, and companies as part of various teams in New York, San Francisco, and Hong Kong. He blogs (https: //medium.com/@jeffksmithjr), tweets (@jeffksmithjr), and speaks (www.jeffsmith.tech/speaking) about various aspects of building real-world machine learning systems. Table of Contents PART 1 - FUNDAMENTALS OF REACTIVE MACHINE LEARNING Learning reactive machine learning Using reactive tools PART 2 - BUILDING A REACTIVE MACHINE LEARNING SYSTEM Collecting data Generating features Learning models Evaluating models Publishing models Responding PART 3 - OPERATING A MACHINE LEARNING SYSTEM Delivering Evolving intelligence

Summary AOP in .NET introduces aspect-oriented programming to .NET developers and provides practical guidance on how to get the most benefit from this technique in your everyday coding. The book's many examples concentrate on modularizing non-functional requirements that often sprawl throughout object-oriented projects. Even if you've never tried AOP before, you'll appreciate the straightforward introduction using familiar C#-based examples. AOP tools for .NET have now reached the level of practical maturity Java developers have relied on for many years, and you'll explore the leading options, PostSharp, and Castle DynamicProxy. About the Technology Core concerns that cut across all parts of your application, such as logging or authorization, are difficult to maintain independently. In aspect-oriented programming (AOP) you isolate these cross-cutting concerns into their own classes, disentangling them from business logic. Mature AOP tools like PostSharp and Castle DynamicProxy now offer .NET developers the level of support Java coders have relied on for years. About this Book AOP in .NET introduces aspect-oriented programming and provides guidance on how to get the most practical benefit from this technique. The book's many examples concentrate on modularizing non-functional requirements that often sprawl throughout object-oriented projects. You'll appreciate its straightforward introduction using familiar C#-based examples. This book requires no prior experience with AOP. Readers should know C# or another OO language. What's Inside Clear and simple introduction to AOP Maximum benefit with minimal theory PostSharp and Castle DynamicProxy Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Author Matthew D. Groves is a developer with over ten years of professional experience working with C#, ASP.NET, JavaScript, and PHP. Table of Contents PART 1 GETTING STARTED WITH AOP Introducing AOP Acme Car Rental PART 2 THE FUNDAMENTALSOF AOP Call this instead: intercepting methods Before and after: boundary aspects Get this instead: intercepting locations Unit testing aspects PART 3 ADVANCED AOP CONCEPTS AOP implementation types Using AOP as an architectural tool Aspect composition: example and execution

Implement, automate, build, operate, and optimize databases and other data-persistent technologies efficiently by leveraging the right set of DevOps best practices Key Features Implement core operational capabilities via automated pipelines, including testing and rollbacks Create infrastructure, deploy software, test execution, and monitor operations using the as-code strategy Automate common implementation patterns for databases with declarative orchestration frameworks Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn today's rapidly evolving world of DevOps, traditional silos are a thing of the past. Database administrators are no longer the only experts; site reliability engineers (SREs) and DevOps engineers are database experts as well. This blurring of the lines has led to increased responsibilities, making members of high-performing DevOps teams responsible for end-to-end ownership. This book helps you master DevOps for databases, making it a must-have resource for achieving success in the ever-changing world of DevOps. You’ll begin by exploring real-world examples of DevOps implementation and its significance in modern data-persistent technologies, before progressing into the various types of database technologies and recognizing their strengths, weaknesses, and commonalities. As you advance, the chapters will teach you about design, implementation, testing, and operations using practical examples, as well as common design patterns, combining them with tooling, technology, and strategies for different types of data-persistent technologies. You’ll also learn how to create complex end-to-end implementation, deployment, and cloud infrastructure strategies defined as code. By the end of this book, you’ll be equipped with the knowledge and tools to design, build, and operate complex systems efficiently.What you will learn Apply DevOps best practices to data-persistent technologies Get to grips with architectural-level design and implementation Explore the modern data journey and data modeling with database technology Master the operation of large-scale systems with zero-touch automation Achieve speed, resilience, security, and operability at different scales Design DevOps teams with end-to-end ownership models Who this book is for This book is for newcomers as well as seasoned SREs, DevOps engineers, and system engineers who are interested in large-scale systems with a heavy focus on data-persistent technologies. Database administrators looking to level up in the world of DevOps will also find this book helpful. Experience with cloud Infrastructure, basic development, and operations will help you get the most out of this book.

The book Advances in Distance Learning in Times of Pandemic is devoted to the issues and challenges faced by universities in the field of distance learning in COVID-19 times. It covers both the theoretical and practical aspects connected to distance education. It elaborates on issues regarding distance learning, its challenges, assessment by students and their expectations, the use of tools to improve distance learning, and the functioning of e-learning in the industry 4.0 and society 5.0 eras. The book also devotes a lot of space to the issues of Web 3.0 in university e-learning, quality assurance, and knowledge management. The aim and scope of this book is to draw a holistic picture of ongoing online teaching-activities before and during the lockdown period and present the meaning and future of e-learning from students’ points of view, taking into consideration their attitudes and expectations as well as industry 4.0 and society 5.0 aspects. The book presents the approach to distance learning and how it has changed, especially during a pandemic that revolutionized education. It highlights • the function of online education and how that has changed before and during the pandemic. • how e-learning is beneficial in promoting digital citizenship. • distance learning characteristic in the era of industry 4.0 and society 5.0. • how the era of industry 4.0 treats distance learning as a desirable form of education. The book covers both scientific and educational aspects and can be useful for university-level undergraduate, postgraduate and research-grade courses and can be referred to by anyone interested in exploring the diverse aspects of distance learning.

Learn how to use Power BI to deliver the insights needed to help your enterprise survive and thrive Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Learn simple through to advanced Power BI features in a clear, concise way using real-world examples Develop powerful analytical models and reports that extract key business insights Publish, share and collaborate on impressive reports, dashboards, apps, and goals Book DescriptionTo succeed in today's transforming business world, organizations need business intelligence capabilities to make smarter decisions faster than ever before. This updated second edition of Learn Power BI takes you on a journey of data exploration and discovery, using Microsoft Power BI to ingest, cleanse, and organize data in order to unlock key business insights that can then be shared with others. This newly revised and expanded edition of Learn Power BI covers all of the latest features and interface changes and takes you through the fundamentals of business intelligence projects, how to deploy, adopt, and govern Power BI within your organization, and how to leverage your knowledge in the marketplace and broader ecosystem that is Power BI. As you progress, you will learn how to ingest, cleanse, and transform your data into stunning visualizations, reports, and dashboards that speak to business decision-makers. By the end of this Power BI book, you will be fully prepared to be the data analysis hero of your organization – or even start a new career as a business intelligence professional.What you will learn Get up and running quickly with Power BI Understand and plan your business intelligence projects Connect to and transform data using Power Query Create data models optimized for analysis and reporting Perform simple and complex DAX calculations to enhance analysis Discover business insights and create professional reports Collaborate via Power BI dashboards, apps, goals, and scorecards Deploy and govern Power BI, including using deployment pipelines Who this book is for If you’re an IT manager, data analyst, or BI user new to using Power BI for solving business intelligence problems, this book is for you. You’ll also find this book helpful if you want to migrate from other BI tools to create powerful and interactive dashboards. No experience of working with Power BI is expected.