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Author: Michael Frampton Publisher: Apress ISBN: 1484221494 Category : Computers Languages : en Pages : 375
Book Description
See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack—sharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more. What You’ll Learn Install a private cloud onto the local cluster using Apache cloud stack Source, install, and configure Apache: Brooklyn, Mesos, Kafka, and Zeppelin See how Brooklyn can be used to install Mule ESB on a cluster and Cassandra in the cloud Install and use DCOS for big data processing Use Apache Spark for big data stack data processing Who This Book Is For Developers, architects, IT project managers, database administrators, and others charged with developing or supporting a big data system. It is also for anyone interested in Hadoop or big data, and those experiencing problems with data size.
Author: Michael Frampton Publisher: Apress ISBN: 1484221494 Category : Computers Languages : en Pages : 375
Book Description
See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack—sharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more. What You’ll Learn Install a private cloud onto the local cluster using Apache cloud stack Source, install, and configure Apache: Brooklyn, Mesos, Kafka, and Zeppelin See how Brooklyn can be used to install Mule ESB on a cluster and Cassandra in the cloud Install and use DCOS for big data processing Use Apache Spark for big data stack data processing Who This Book Is For Developers, architects, IT project managers, database administrators, and others charged with developing or supporting a big data system. It is also for anyone interested in Hadoop or big data, and those experiencing problems with data size.
Author: Segall, Richard S. Publisher: IGI Global ISBN: 1799827704 Category : Computers Languages : en Pages : 237
Book Description
With the development of computing technologies in today’s modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.
Author: Management Association, Information Resources Publisher: IGI Global ISBN: 1799891593 Category : Computers Languages : en Pages : 904
Book Description
The quick growth of computer technology and development of software caused it to be in a constant state of change and advancement. This advancement in software development meant that there would be many types of software developed in order to excel in usability and efficiency. Among these different types of software was open source software, one that grants permission for users to use, study, change, and distribute it freely. Due to its availability, open source software has quickly become a valuable asset to the world of computer technology and across various disciplines including education, business, and library science. The Research Anthology on Usage and Development of Open Source Software presents comprehensive research on the design and development of open source software as well as the ways in which it is used. The text discusses in depth the way in which this computer software has been made into a collaborative effort for the advancement of software technology. Discussing topics such as ISO standards, big data, fault prediction, open collaboration, and software development, this anthology is essential for computer engineers, software developers, IT specialists and consultants, instructors, librarians, managers, executives, professionals, academicians, researchers, and students.
Author: Management Association, Information Resources Publisher: IGI Global ISBN: 1668436639 Category : Computers Languages : en Pages : 1988
Book Description
Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.
Author: Joe Celko Publisher: Newnes ISBN: 0124072208 Category : Computers Languages : en Pages : 245
Book Description
Joe Celko's Complete Guide to NoSQL provides a complete overview of non-relational technologies so that you can become more nimble to meet the needs of your organization. As data continues to explode and grow more complex, SQL is becoming less useful for querying data and extracting meaning. In this new world of bigger and faster data, you will need to leverage non-relational technologies to get the most out of the information you have. Learn where, when, and why the benefits of NoSQL outweigh those of SQL with Joe Celko's Complete Guide to NoSQL. This book covers three areas that make today's new data different from the data of the past: velocity, volume and variety. When information is changing faster than you can collect and query it, it simply cannot be treated the same as static data. Celko will help you understand velocity, to equip you with the tools to drink from a fire hose. Old storage and access models do not work for big data. Celko will help you understand volume, as well as different ways to store and access data such as petabytes and exabytes. Not all data can fit into a relational model, including genetic data, semantic data, and data generated by social networks. Celko will help you understand variety, as well as the alternative storage, query, and management frameworks needed by certain kinds of data. - Gain a complete understanding of the situations in which SQL has more drawbacks than benefits so that you can better determine when to utilize NoSQL technologies for maximum benefit - Recognize the pros and cons of columnar, streaming, and graph databases - Make the transition to NoSQL with the expert guidance of best-selling SQL expert Joe Celko
Author: Pierre-Yves BONNEFOY Publisher: Packt Publishing Ltd ISBN: 1837634777 Category : Computers Languages : en Pages : 490
Book Description
Learn the essentials of data integration with this comprehensive guide, covering everything from sources to solutions, and discover the key to making the most of your data stack Key Features Learn how to leverage modern data stack tools and technologies for effective data integration Design and implement data integration solutions with practical advice and best practices Focus on modern technologies such as cloud-based architectures, real-time data processing, and open-source tools and technologies Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data. This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics. By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.What you will learn Discover the evolving architecture and technologies shaping data integration Process large data volumes efficiently with data warehousing Tackle the complexities of integrating large datasets from diverse sources Harness the power of data warehousing for efficient data storage and processing Design and optimize effective data integration solutions Explore data governance principles and compliance requirements Who this book is for This book is perfect for data engineers, data architects, data analysts, and IT professionals looking to gain a comprehensive understanding of data integration in the modern era. Whether you’re a beginner or an experienced professional enhancing your knowledge of the modern data stack, this definitive guide will help you navigate the data integration landscape.
Author: Raul Estrada Publisher: Apress ISBN: 1484221753 Category : Computers Languages : en Pages : 277
Book Description
Learn how to integrate full-stack open source big data architecture and to choose the correct technology—Scala/Spark, Mesos, Akka, Cassandra, and Kafka—in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses. Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer: The language: Scala The engine: Spark (SQL, MLib, Streaming, GraphX) The container: Mesos, Docker The view: Akka The storage: Cassandra The message broker: Kafka What You Will Learn: Make big data architecture without using complex Greek letter architectures Build a cheap but effective cluster infrastructure Make queries, reports, and graphs that business demands Manage and exploit unstructured and No-SQL data sources Use tools to monitor the performance of your architecture Integrate all technologies and decide which ones replace and which ones reinforce Who This Book Is For: Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer
Author: Judith S. Hurwitz Publisher: John Wiley & Sons ISBN: 1118644174 Category : Computers Languages : en Pages : 336
Book Description
Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.
Author: Michael Frampton
Author: Michael Frampton
Author: Segall, Richard S.
Author: Management Association, Information Resources
Author: Management Association, Information Resources
Author: Joe Celko
Author: Anatoly Alikhanov
Author: Pierre-Yves BONNEFOY
Author: Raul Estrada
Author: Judith S. Hurwitz
Author: Mothiram Rajasekaran