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Author: Raul Estrada
Publisher: Apress
ISBN: 1484221753
Category : Computers
Languages : en
Pages : 277
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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: Raul Estrada
Publisher: Apress
ISBN: 1484221753
Category : Computers
Languages : en
Pages : 277
Get Book Here
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: Segall, Richard S.
Publisher: IGI Global
ISBN: 1522531432
Category : Computers
Languages : en
Pages : 1078
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Book Description
The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.
Author: Segall, Richard S.
Publisher: IGI Global
ISBN: 1799827704
Category : Computers
Languages : en
Pages : 237
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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: Michael Frampton
Publisher: Apress
ISBN: 1484221494
Category : Computers
Languages : en
Pages : 375
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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: Stephen H. Kaisler
Publisher: Business Expert Press
ISBN: 1949991474
Category : Business & Economics
Languages : en
Pages : 144
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Book Description
Volume II of this series discusses the technology used to implement a big data analysis capability within a service-oriented organization. It discusses the technical architecture necessary to implement a big data analysis capability, some issues and challenges in big data analysis and utilization that an organization will face, and how to capture value from it. It will help readers understand what technology is required for a basic capability and what the expected benefits are from establishing a big data capability within their organization.
Author: Mohammed Guller
Publisher: Apress
ISBN: 1484209648
Category : Computers
Languages : en
Pages : 290
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Book Description
Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis. You will learn 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. In addition, this book will help you become a much sought-after Spark expert. Spark is one of the hottest Big Data technologies. The amount of data generated today by devices, applications and users is exploding. Therefore, there is a critical need for tools that can analyze large-scale data and unlock value from it. Spark is a powerful technology that meets that need. You can, for example, use Spark to perform low latency computations through the use of efficient caching and iterative algorithms; leverage the features of its shell for easy and interactive Data analysis; employ its fast batch processing and low latency features to process your real time data streams and so on. As a result, adoption of Spark is rapidly growing and is replacing Hadoop MapReduce as the technology of choice for big data analytics. This book provides an introduction to Spark and related big-data technologies. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, and MLlib. Big Data Analytics with Spark is therefore written for busy professionals who prefer learning a new technology from a consolidated source instead of spending countless hours on the Internet trying to pick bits and pieces from different sources. The book also provides a chapter on Scala, the hottest functional programming language, and the program 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, like Hive, Avro, Kafka and so on. 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 know is programming in any language. There is a critical shortage of people with big data expertise, so companies are willing to pay top dollar for people with skills in areas like Spark and Scala. So reading this book and absorbing its principles will provide a boost—possibly a big boost—to your career.
Author: Kohei Arai
Publisher: Springer Nature
ISBN: 3030551873
Category : Technology & Engineering
Languages : en
Pages : 794
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Book Description
The book Intelligent Systems and Applications - Proceedings of the 2020 Intelligent Systems Conference is a remarkable collection of chapters covering a wider range of topics in areas of intelligent systems and artificial intelligence and their applications to the real world. The Conference attracted a total of 545 submissions from many academic pioneering researchers, scientists, industrial engineers, students from all around the world. These submissions underwent a double-blind peer review process. Of those 545 submissions, 177 submissions have been selected to be included in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have enabled a larger number of problems to be tackled more effectively.This branching out of computational intelligence in several directions and use of intelligent systems in everyday applications have created the need for such an international conference which serves as a venue to report on up-to-the-minute innovations and developments. This book collects both theory and application based chapters on all aspects of artificial intelligence, from classical to intelligent scope. We hope that readers find the volume interesting and valuable; it provides the state of the art intelligent methods and techniques for solving real world problems along with a vision of the future research.
Author: Theresa Payton
Publisher: Rowman & Littlefield
ISBN: 1538167832
Category : Computers
Languages : en
Pages : 369
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Book Description
A thorough update to a classic in the field of privacy and big data. We have a global privacy problem. The average person provides more information about themselves to more outsiders than any time in history. Corporations, governments and even our neighbors can know where we are at times, can quickly learn our preferences and priorities and see who we meet. The past decade has brought deep changes in the collection of our private information, the regulation of that collection, and in people’s sensitivity to loss of privacy. The nascent privacy-threatening technology trends of a decade ago have blossomed into relentless data-capturing systems that police and companies have come to rely on. To address the expansion of personal data capture, entire data regulatory regimes have arisen throughout the world, with new regulations added each year. People are more concerned, regulators are more aggressive, yet data collection continues to increase with consequences around the world. Social media use has fragmented in the past five years, spreading personal information over dozens of platforms. Even most of our new televisions have started collecting second-by-second information about our households recently, and some of those televisions can recognize the individuals watching and the devices they carry. Amazon just activated a new worldwide network using bandwidth from personal wifi of Echo devices and Ring security systems. The beat of new intrusions never seems to end. These data trends are relentless, and yet response to the pandemic accelerated them. Rapid development of “contactless everything” became the norm. Contact tracing apps became acceptable. QR codes for everything from menus to contact information were created quickly. Businesses are faced with hybrid in office and remote workforces. More people are dependent on online and mobile technologies for food, medicine, and even human connection. And each of these contacts can be captured somewhere and logged in a file for marketing or surveillance. People want to keep their lives private, but they don’t know how. The second edition of Privacy in the Age of Big Data addresses the significant advances in data-driven technology, their intrusion deeper in our lives, the limits on data collection newly required by governments in North America and Europe, and the new security challenges of world rife with ransomware and hacking. This thoroughly updated edition demonstrates personal privacy vulnerabilities and shows ways to live a safer, more private life. Other privacy books tend to focus deeply on the evils of large tech companies or more academic and technical concerns. But Privacy in the Age of Big Data, second edition, helps regular people understand the privacy threats and vulnerabilities in their daily lives and will provide solutions for maintaining better privacy while enjoying a modern life. Unlike other books, this one shows what you can do to make a difference to understand your current digital footprint and what you need to do to claw back your privacy and secure it in the future. While PRIVACY IN THE AGE OF BIG DATA will have cross-sectional appeal to many demographics, working adults 25-60 and CEOs and Boards of businesses are the primary demographic--young enough to know we need to do something to protect privacy and old enough to remember what happens when we haven’t in the past. With down-to-earth prose and examples pulled from daily life, the writing style will attract buyers of all education levels.
Author: Melvin Burgess
Publisher: Macmillan
ISBN: 0312608624
Category : Juvenile Fiction
Languages : en
Pages : 355
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Book Description
Translated into 28 different languages and adapted for the stage and television, "Smack"--a Carnegie Medal winner--is the original cautionary tale about modern drug abuse.
Author: Leonard Barolli
Publisher: Springer
ISBN: 331993659X
Category : Technology & Engineering
Languages : en
Pages : 1167
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Book Description
This book provides a platform of scientific interaction between the three challenging and closely linked areas of ICT-enabled-application research and development: software intensive systems, complex systems and intelligent systems. Software intensive systems strongly interact with other systems, sensors, actuators, devices, other software systems and users. More and more domains are using software intensive systems, e.g. automotive and telecommunication systems, embedded systems in general, industrial automation systems and business applications. Moreover, web services offer a new platform for enabling software intensive systems. Complex systems research is focused on the overall understanding of systems rather than their components. Complex systems are characterized by the changing environments in which they interact. They evolve and adapt through internal and external dynamic interactions. The development of intelligent systems and agents, which are increasingly characterized by their use of ontologies and their logical foundations, offer impulses for both software intensive systems and complex systems. Recent research in the field of intelligent systems, robotics, neuroscience, artificial intelligence, and cognitive sciences are vital for the future development and innovation of software intensive and complex systems.
