Large-scale data analytics with python and spark, Triguero, Isaac (universidad De Granada) Galar, Mikel (public University Of Navarre)
Автор: Guller, Mohammed Название: Big data analytics with spark ISBN: 1484209656 ISBN-13(EAN): 9781484209653 Издательство: Springer Рейтинг: Цена: 4634.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Drabas, Tomasz Lee, Denny Название: Pyspark cookbook ISBN: 1788835360 ISBN-13(EAN): 9781788835367 Издательство: Неизвестно Рейтинг: Цена: 8458.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This cookbook presents recipes on leveraging the power of Python and putting it to use in the Apache Spark ecosystem. By the end of this book, you will be able to solve any problem associated with building effective, data-intensive applications and performing machine learning and structured streaming using PySpark.
Автор: Das, Himansu Название: Real-Time Data Analytics For Large Scale Sensor Data ISBN: 0128180145 ISBN-13(EAN): 9780128180143 Издательство: Elsevier Science Рейтинг: Цена: 22401.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the development of software methods, techniques and tools, applications, governance and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. The book captures the essence of real-time IoT based solutions that require a multidisciplinary approach for catering to on-the-fly processing, including methods for high performance stream processing, adaptively streaming adjustment, uncertainty handling, latency handling, and more.
Автор: Digital Colibri, Lai Rudy, Potaczek Bartlomiej Название: Hands-On Big Data Analytics with PySpark ISBN: 183864413X ISBN-13(EAN): 9781838644130 Издательство: Неизвестно Рейтинг: Цена: 4964.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this book, you`ll learn to implement some practical and proven techniques to improve aspects of programming and administration in Apache Spark. Techniques are demonstrated using practical examples and best practices. You will also learn how to use Spark and its Python API to create performant analytics with large-scale data.
Автор: Franco Galeano Manuel Ignacio Название: Big Data Processing with Apache Spark ISBN: 1789808812 ISBN-13(EAN): 9781789808810 Издательство: Неизвестно Рейтинг: Цена: 7355.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Processing big data in real-time is challenging due to scalability, information consistency, and fault tolerance. This book shows you how you can use Spark to make your overall analysis workflow faster and more efficient. You`ll learn all about the core concepts and tools within the Spark ecosystem, like Spark Streaming, the Spark Streaming ...
Описание: This book will get you to grips with the Spark Python API. You`ll explore how Python can be used with Spark to build scalable and reliable data-intensive applications.
Описание: Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. This book is your guide to getting ...
Автор: Tekinerdogan, Bedir Название: Model Management And Analytics For Large Scale Systems ISBN: 0128166495 ISBN-13(EAN): 9780128166499 Издательство: Elsevier Science Рейтинг: Цена: 19370.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics.
This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management.
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