Datastream A Complete Guide
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| Author | : Charu C. Aggarwal |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 365 |
| Release | : 2007-04-03 |
| Genre | : Computers |
| ISBN | : 0387475346 |
This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions. The book is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.
| Author | : Joao Gama |
| Publisher | : CRC Press |
| Total Pages | : 256 |
| Release | : 2010-05-25 |
| Genre | : Business & Economics |
| ISBN | : 1439826129 |
Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents
| Author | : Andrew Psaltis |
| Publisher | : Simon and Schuster |
| Total Pages | : 314 |
| Release | : 2017-05-31 |
| Genre | : Computers |
| ISBN | : 1638357242 |
Summary Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology As humans, we're constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them. About the Book Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you'll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you'll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details. What's Inside The right way to collect real-time data Architecting a streaming pipeline Analyzing the data Which technologies to use and when About the Reader Written for developers familiar with relational database concepts. No experience with streaming or real-time applications required. About the Author Andrew Psaltis is a software engineer focused on massively scalable real-time analytics. Table of Contents PART 1 - A NEW HOLISTIC APPROACH Introducing streaming data Getting data from clients: data ingestion Transporting the data from collection tier: decoupling the data pipeline Analyzing streaming data Algorithms for data analysis Storing the analyzed or collected data Making the data available Consumer device capabilities and limitations accessing the data PART 2 - TAKING IT REAL WORLD Analyzing Meetup RSVPs in real time
| Author | : RAMANA |
| Publisher | : RAMANA |
| Total Pages | : 3830 |
| Release | : 2024-04-18 |
| Genre | : Antiques & Collectibles |
| ISBN | : |
Here is a description for the book *"Python Mastery: A Complete Guide to Programming Excellence"*: Unlock your full potential as a programmer with *"Python Mastery: A Complete Guide to Programming Excellence"*. This comprehensive book is designed to guide you from the fundamentals of Python programming to advanced concepts and best practices. Through clear explanations and hands-on exercises, you'll gain a solid understanding of core topics such as data types, control structures, functions, and modules. Dive deeper into object-oriented programming, file handling, and libraries like NumPy and Pandas. Explore powerful techniques for debugging, testing, and optimizing your code. Whether you're a beginner or an experienced developer, this guide will help you achieve mastery in Python and elevate your programming skills to new heights.
| Author | : Albert Bifet |
| Publisher | : MIT Press |
| Total Pages | : 262 |
| Release | : 2018-03-16 |
| Genre | : Computers |
| ISBN | : 0262346052 |
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.
| Author | : Michael Frampton |
| Publisher | : Apress |
| Total Pages | : 375 |
| Release | : 2018-01-18 |
| Genre | : Computers |
| ISBN | : 1484221494 |
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 | : James Densmore |
| Publisher | : O'Reilly Media |
| Total Pages | : 277 |
| Release | : 2021-02-10 |
| Genre | : Computers |
| ISBN | : 1492087807 |
Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack. You'll learn common considerations and key decision points when implementing pipelines, such as batch versus streaming data ingestion and build versus buy. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions. You'll learn: What a data pipeline is and how it works How data is moved and processed on modern data infrastructure, including cloud platforms Common tools and products used by data engineers to build pipelines How pipelines support analytics and reporting needs Considerations for pipeline maintenance, testing, and alerting
| Author | : Mothiram Rajasekaran |
| Publisher | : Leilani Katie Publication |
| Total Pages | : 185 |
| Release | : 2024-04-26 |
| Genre | : Computers |
| ISBN | : 9363487407 |
Mothiram Rajasekaran, Senior Solution Consultant, Cloudera, USA.
| Author | : Sharma Chakravarthy |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 341 |
| Release | : 2009-04-09 |
| Genre | : Computers |
| ISBN | : 0387710035 |
The systems used to process data streams and provide for the needs of stream-based applications are Data Stream Management Systems (DSMSs). This book presents a new paradigm to meet the needs of these applications, including a detailed discussion of the techniques proposed. Ii includes important aspects of a QoS-driven DSMS (Data Stream Management System) and introduces applications where a DSMS can be used and discusses needs beyond the stream processing model. It also discusses in detail the design and implementation of MavStream. This volume is primarily intended as a reference book for researchers and advanced-level students in computer science. It is also appropriate for practitioners in industry who are interested in developing applications.
| Author | : Sergio Flesca |
| Publisher | : Springer |
| Total Pages | : 490 |
| Release | : 2017-05-29 |
| Genre | : Technology & Engineering |
| ISBN | : 3319618938 |
This book offers readers a comprehensive guide to the evolution of the database field from its earliest stages up to the present—and from classical relational database management systems to the current Big Data metaphor. In particular, it gathers the most significant research from the Italian database community that had relevant intersections with international projects. Big Data technology is currently dominating both the market and research. The book provides readers with a broad overview of key research efforts in modelling, querying and analysing data, which, over the last few decades, have became massive and heterogeneous areas.
