Mastering RabbitMQ provides a comprehensive guide to developing and scaling message-driven applications using RabbitMQ. From installation and configuration to advanced concepts like cluster management and high availability, this book equips you with the knowledge and practical skills to ensure robust and efficient messaging solutions. What this Book will help me do Effectively set up and configure RabbitMQ for scalable applications. Implement robust messaging solutions using RabbitMQ's administrative tools. Leverage clustering and high availability for fault-tolerant systems. Create custom RabbitMQ plugins using Erlang for extended capabilities. Monitor and secure RabbitMQ environments leveraging popular tools and practices. Author(s) Yusuf Aytas and the co-authors bring a wealth of technical knowledge and practical experience in messaging systems and RabbitMQ. With years of expertise in software engineering and hands-on implementations in enterprise environments, they provide insights that combine theory with real-world application. Who is it for? This book is ideal for developers and IT professionals with basic knowledge of RabbitMQ seeking to master advanced usage and best practices. It caters to those looking to design, develop, and maintain robust messaging systems efficiently. Perfect for those with a background in message queuing, it provides an in-depth understanding to take your expertise to the next level.

This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it’s often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed data in real time. This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on. Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data. Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into that pattern.

Examine the different roles and capabilities of logistic firms and understand their future development and strategic growth.

In this book, noted expert Andrew Okungbowa explains SAP Asset Accounting (FI-AA) in SAP-ERP, including its associated business benefits, and guides you through the considerable complexities of SAP-ERP configuration. Using FI-AA for fixed asset management enables you to manage assets in multinational companies across a broad range of industries and produce reports to meet various needs in line with legal requirements. Configuring SAP-ERP can be a daunting exercise, however, and there are few resources that address these issues. Asset Accounting Configuration in SAP ERP fills that resource gap by covering the major aspects of SAP FI-AA for anyone with SAP experience and the basic accounting knowledge and bookkeeping skills necessary to apply configuration. It provides configuration explanations in the simplest forms possible and provides step-by-step guidance with illustrations and practical examples.

This book is your introduction in the world of graph databases, and the benefits they can bring to your applications. Neo4j is the most established graph database on the market, and it's always improving to bring more of its benefits to you. Beginning Neo4j will take you from the installation of Neo4j through to building a full application with Neo4j at its heart, and everything in between. Using this book, you'll get everything up and running, and then learn how to use Neo4j to build up recommendations, relationships, and calculate the shortest route between two locations. With example data models, and an application putting everything together, this book will give you everything you need to really get started with Neo4j. Neo4j is being used by social media and ecommerce industry giants. You can take advantage of Neo4j's powerful features and benefits - add Beginning Neo4j to your library today.

This book is a step-by-step guide for learning how to use Spark for different types of big-data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, MLlib, and Spark ML. Big Data Analytics with Spark shows you how to use Spark and leverage its easy-to-use features to increase your productivity. You learn to perform fast data analysis using its in-memory caching and advanced execution engine, employ in-memory computing capabilities for building high-performance machine learning and low-latency interactive analytics applications, and much more. Moreover, the book shows you how to use Spark as a single integrated platform for a variety of data processing tasks, including ETL pipelines, BI, live data stream processing, graph analytics, and machine learning. The book also includes a chapter on Scala, the hottest functional programming language, and the language that underlies Spark. You’ll learn the basics of functional programming in Scala, so that you can write Spark applications in it. What's more, Big Data Analytics with Spark provides an introduction to other big data technologies that are commonly used along with Spark, such as HDFS, Avro, Parquet, Kafka, Cassandra, HBase, Mesos, and so on. It also provides an introduction to machine learning and graph concepts. So the book is self-sufficient; all the technologies that you need to know to use Spark are covered. The only thing that you are expected to have is some programming knowledge in any language.

This is a book for enterprise architects, database administrators, and developers who need to understand the latest developments in database technologies. It is the book to help you choose the correct database technology at a time when concepts such as Big Data, NoSQL and NewSQL are making what used to be an easy choice into a complex decision with significant implications. The relational database (RDBMS) model completely dominated database technology for over 20 years. Today this "one size fits all" stability has been disrupted by a relatively recent explosion of new database technologies. These paradigm-busting technologies are powering the "Big Data" and "NoSQL" revolutions, as well as forcing fundamental changes in databases across the board. Deciding to use a relational database was once truly a no-brainer, and the various commercial relational databases competed on price, performance, reliability, and ease of use rather than on fundamental architectures. Today we are faced with choices between radically different database technologies. Choosing the right database today is a complex undertaking, with serious economic and technological consequences. Next Generation Databases demystifies today’s new database technologies. The book describes what each technology was designed to solve. It shows how each technology can be used to solve real word application and business problems. Most importantly, this book highlights the architectural differences between technologies that are the critical factors to consider when choosing a database platform for new and upcoming projects. Introduces the new technologies that have revolutionized the database landscape Describes how each technology can be used to solve specific application or business challenges Reviews the most popular new wave databases and how they use these new database technologies

Master the SAP product ecosystem, the client environment, and the feasibility of implementing critical business process with the required technical and functional configuration. SAP Project Management Pitfalls is the first book to provide you with real examples of the pitfalls that you can avoid, providing you with a road-map to a successful implementation. Jay Kay, a SAP Program Manager for Capgemini, first takes a deep dive into common pitfalls in implementing SAP ERP projects in a complex IT landscape. You will learn about the potential causes of failures, study a selection of relevant project implementation case studies in the area, and see a range of possible countermeasures. Jay Kay also provides background on each - the significance of each implementation area, its relevance to a service company that implements SAP projects, and the current state of research. Key highlights of the book: Tools and techniques for project planning and templates for allocating resources Industry standards and innovations in SAP implementation projects in the form of standard solutions aimed at successful implementation Managing SAP system ECC upgrades, EHP updates and project patches Learn effective ways to implement robust SAP release management practices (change management, BAU) Wearing a practitioner’s insight, Jay Kay explores the relevance of each failed implementation scenario and how to support your company or clients to succeed in a SAP implementation. There are many considerations when implementing SAP, but as you will learn, knowledge, insight, and effective tools to mitigate risks can take you to a successful implementation project.

Dive into the world of geospatial analysis with Python in this comprehensive guide. This book will take you through the essentials of GIS, remote sensing, elevation data, and real-time data, all using Python. You will learn to analyze and visualize geospatial data effectively, building skills and understanding that are practical and relevant. What this Book will help me do Automate geospatial workflows using Python. Create thematic maps with Python tools for better spatial insights. Understand various forms of geospatial data and how to manage them. Develop GIS applications and elevation data models using minimal lines of Python code. Utilize Python for real-time data tracking and storm modeling. Author(s) Joel Lawhead is an experienced geospatial software developer and Python programmer with extensive expertise in GIS and geospatial data analysis. With a deep understanding of Python's applications in geography, Joel brings a practical focus to his writing. His engaging style ensures that technical concepts are accessible and thoroughly explained. Who is it for? This book is ideal for Python developers, researchers, and analysts who want to enhance their GIS and geospatial analysis capabilities. If you are familiar with Python or another scripting language and have a foundational understanding of digital mapping, this book will help you advance your knowledge and skills. Whether you're analyzing spatial data or building geospatial applications, this guide is made for you.

Elasticsearch Indexing focuses on empowering developers to create optimized and user-friendly search experiences using Elasticsearch. By learning how to configure indices and mapping strategies, and leveraging analyzers effectively, you will gain proficiency in delivering fast and relevant search results tailored to modern user expectations. What this Book will help me do Understand how Elasticsearch stores data and how it reduces costs Develop advanced mapping strategies to improve index performance Utilize Elasticsearch analyzers for efficient search query processing Optimize ElasticSearch clusters for scalability and stability Perform strategic indexing to minimize resource usage while maximizing functionality Author(s) Huseyin Akdogan is a seasoned software developer specializing in search technologies and scalability. With his deep expertise and practical insights, he brings a metric-driven approach to optimizing Elasticsearch. His book reflects his dedication to making technical concepts accessible and actionable for developers. Who is it for? This book is ideal for developers looking to gain expertise in Elasticsearch. It caters to individuals with a foundational understanding of search systems who wish to optimize their indexing and search result delivery. If you are focused on improving user search experiences tailored to scalable needs, this book is perfect for you.

Build an enterprise search engine using Apache Solr: index and search documents; ingest data from varied sources; apply various text processing techniques; utilize different search capabilities; and customize Solr to retrieve the desired results. Apache Solr: A Practical Approach to Enterprise Search explains each essential concept--backed by practical and industry examples--to help you attain expert-level knowledge. The book, which assumes a basic knowledge of Java, starts with an introduction to Solr, followed by steps to setting it up, indexing your first set of documents, and searching them. It then introduces you to information retrieval and its implementation in Apache Solr; this will help you understand your search problem, decide the approach to build an effective solution, and use various metrics to evaluate the results. The book next covers the schema design and techniques to build a text analysis chain for cleansing, normalizing and enriching your documents and addressing different types of search queries. It describes various popular matching techniques which are generally applied to improve the precision and recall of searches. You will learn the end-to-end process of data ingestion from varied sources, metadata extraction, pre-processing and transformation of content, various search components, query parsers and other advanced search capabilities. After covering out-of-the-box features, Solr expert Dikshant Shahi dives into ways you can customize Solr for your business and its specific requirements, along with ways to plug in your own components. Most important, you will learn about implementations for Solr scoring, factors affecting the document score, and tuning the score for the application at hand. The book explains why textual scoring is not sufficient for practical ranking of documents and ways to integrate real-world factors for contributing to the document ranking. You'll see how to influence user experience by providing suggestions and recommendations. You'll also see integration of Solr with important related technologies such as OpenNLP and Tika. Additionally, you will learn about scaling Solr using SolrCloud. This book concludes with coverage of semantic search capabilities, which is crucial for taking the search experience to the next level. By the end of Apache Solr, you will be proficient in designing and developing your search engine.

Dive into the world of Apache Solr with this focused guide on indexing. Learn to harness Solr's powerful indexing features through real-world examples that help you efficiently fetch relevant data. From setting up Solr to mastering advanced techniques, this book ensures you are equipped to program and optimize Solr for a variety of applications. What this Book will help me do Gain a solid understanding of Solr indexing, analyzers, and tokenizers. Index diverse data sources, such as databases and documents, using Solr. Utilize Apache Tika to process PDFs and integrate Apache Nutch for web crawling. Implement distributed data indexing and facilitate real-time index updates. Apply learned indexing techniques to create robust solutions like e-commerce applications. Author(s) None Handiekar and None Johri are seasoned Apache Solr experts with years of practical experience. Having worked on diverse projects, they bring an enriched understanding of indexing and optimization. Their writing reflects a hands-on approach aimed at developers keen on mastering Solr effectively and efficiently. Who is it for? This book is designed for developers who are new to Solr yet aspire to deepen their understanding of its indexing capabilities. If you are interested in learning how to index using Solr's rich set of functionalities, this guide is for you. It provides practical steps for developers at an introductory level to start building more complex solutions. Perfect for developers eager to optimize their Solr indexing.

Learning RabbitMQ offers developers and system administrators a clear and practical guide to mastering RabbitMQ, the popular message-broker solution. By going through concrete scenarios and examples, this book equips you with the skills to configure, manage, and optimize RabbitMQ instances effectively. What this Book will help me do Understand and apply common messaging patterns using RabbitMQ. Set up and manage RabbitMQ clusters with high availability. Integrate RabbitMQ with popular tools like Spring, MuleESB, and Docker. Optimize RabbitMQ performance and ensure secure messaging. Troubleshoot and extend RabbitMQ for different use cases. Author(s) None Toshev, the author of Learning RabbitMQ, is an expert in middleware and distributed systems, with extensive hands-on experience working with message brokers. Toshev's practical approach and clear explanations make complex topics easy to understand, helping readers effectively apply best practices when using RabbitMQ. Who is it for? This book is for developers and system administrators who aim to incorporate RabbitMQ as part of their applications. Beginners with a basic understanding of messaging will find it foundational, while experienced users will appreciate the advanced insights on integration, performance tuning, and troubleshooting.

The W3C XQuery 3.1 standard provides a tool to search, extract, and manipulate content, whether it's in XML, JSON or plain text. With this fully updated, in-depth tutorial, you’ll learn to program with this highly practical query language. Designed for query writers who have some knowledge of XML basics, but not necessarily advanced knowledge of XML-related technologies, this book is ideal as both a tutorial and a reference. You’ll find background information for namespaces, schemas, built-in types, and regular expressions that are relevant to writing XML queries.

This brief book is a basic introduction to SQLite for iOS and Android developers. The book includes a simple introduction to SQL, a discussion of when to use SQLite, and chapters devoted to using SQLite with the most likely programming languages: Java, PHP, Swift and Objective-C. It then goes through adding simple database functionality to an Android or iOS app and finally a chapter on managing the app’s life cycle.

One of the most useful features of today’s modern browsers is the ability to store data right on the user’s computer or mobile device. Even as more people move toward the cloud, client-side storage can still save web developers a lot of time and money, if you do it right. This hands-on guide demonstrates several storage APIs in action. You’ll learn how and when to use them, their plusses and minuses, and steps for implementing one or more of them in your application.

Practical Guide to MongoDB: Architecting, Developing, and Administering MongoDB begins with a short introduction to the basics of NoSQL databases and then introduces readers to MongoDB—the leading document based NoSQL database, acquainting them step-by-step with all aspects of MongoDB. Practical Guide to MongoDB covers the data model, underlying architecture, coding with Mongo Shell, and administrating the MongoDB platform, among other topics. The book also provides clear guidelines and practical examples for architecting, developing, and deploying applications using the MongoDB platform. Database developers, architects, and administrators will find useful information covering all aspects of the MongoDB platform and how to put it to use practically. The "one-size-fits-all" thinking regarding traditional RDBMSs has been challenged in the last few years by the emergence of diversified NoSQL databases. More than 120 NoSQL databases are now available in the market, and the leader by far is MongoDB. With so many companies opting for MongoDB as their NoSQL database of choice, there's a need for a practical how-to combined with expert advice for getting the most out of the software. Practical Guide to MongoDB provides readers with: A solid understanding of NoSQL databases An understanding of how to get started with MongoDB Methodical coverage of the architecture, development, and administration of MongoDB A plethora of "How to’s" enabling you to use the technology most efficiently to solve the problems you face

Everything you need to make the most of building information modeling If you're looking to get involved in the world of BIM, but don't quite know where to start, Building Information Modeling For Dummies is your one-stop guide to collaborative building using one coherent system of computer models rather than as separate sets of drawings. Inside, you'll find an easy-to-follow introduction to BIM and hands-on guidance for understanding drivers for change, the benefits of BIM, requirements you need to get started, and where BIM is headed. The future of BIM is bright—it provides the industry with an increased understanding of predictability, improved efficiency, integration and coordination, less waste, and better value and quality. Additionally, the use of BIM goes beyond the planning and design phase of the project, extending throughout the building life cycle and supporting processes, including cost management, construction management, project management, and facility operation. Now heavily adopted in the U.S., Hong Kong, India, Singapore, France, Canada, and countless other countries, BIM is set to become a mandatory practice in building work in the UK, and this friendly guide gives you everything you need to make sense of it—fast. Demonstrates how BIM saves time and waste on site Shows you how the information generated from BIM leads to fewer errors on site Explains how BIM is based on data sets that describe objects virtually, mimicking the way they'll be handled physically in the real world Helps you grasp how the integration of BIM allows every stage of the life cycle to work together without data or process conflict Written by a team of well-known experts, this friendly, hands-on guide gets you up and running with BIM fast.

Big data is an emerging phenomenon that has enormous implications and impacts upon business strategy, profitability, and process improvements. All service systems generate big data these days, especially human-centered service systems. It has been characterized as the collection, analysis and use of data characterized by the five Vs: volume, velocity, variety, veracity, and value (of data). This booklet will help middle, senior, and executive managers to understand what big data is; how to recognize, collect, process, and analyze it; how to store and manage it; how to obtain useful information from it; and how to assess its contribution to operational, tactical, and strategic decision-making in service-oriented organizations.

No matter what DBMS you are using—Oracle, DB2, SQL Server, MySQL, PostgreSQL—misunderstandings can always arise over the precise meanings of terms, misunderstandings that can have a serious effect on the success of your database projects. For example, here are some common database terms: attribute, BCNF, consistency, denormalization, predicate, repeating group, join dependency. Do you know what they all mean? Are you sure? The New Relational Database Dictionary defines all of these terms and many, many more. Carefully reviewed for clarity, accuracy, and completeness, this book is an authoritative and comprehensive resource for database professionals, with over 1700 entries (many with examples) dealing with issues and concepts arising from the relational model of data. DBAs, database designers, DBMS implementers, application developers, and database professors and students can find the information they need on a daily basis, information that isn’t readily available anywhere else.