Name: Programming Big Data Applications: Scalable Tools and Frameworks for Your Needs (en Inglés)
Price: 147.83 USD
Availability: InStock
Author: Talia, Domenico ; Trunfio, Paolo ; Marozzo, Fabrizio
ISBN: 9781800615045

portada Programming Big Data Applications: Scalable Tools and Frameworks for Your Needs (en Inglés)

Programming Big Data Applications: Scalable Tools and Frameworks for Your Needs (en Inglés)

Formato

Libro Físico

Autor

Domenico Talia

Paolo Trunfio

Fabrizio Marozzo

Editorial

World Scientific Publishing Europe Ltd

Idioma

Inglés

N° páginas

232

Encuadernación

Tapa Dura

ISBN13

9781800615045

Categorías

Programación informática/desarrollo de software
Minería de datos («data mining»)
Aprendizaje automático («machine learning»)

Programming Big Data Applications: Scalable Tools and Frameworks for Your Needs (en Inglés)

Domenico Talia (Autor) · Paolo Trunfio (Autor) · Fabrizio Marozzo (Autor) · World Scientific Publishing Europe Ltd · Tapa Dura

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Reseña del libro "Programming Big Data Applications: Scalable Tools and Frameworks for Your Needs (en Inglés)"

In the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. These data, commonly referred to as big data, are challenging current storage, processing and analysis capabilities. New models, languages, systems and algorithms continue to be developed to effectively collect, store, analyze and learn from big data.Programming Big Data Applications introduces and discusses models, programming frameworks and algorithms to process and analyze large amounts of data. In particular, the book provides an in-depth description of the properties and mechanisms of the main programming paradigms for big data analysis, including MapReduce, workflow, BSP, message passing, and SQL-like. Through programming examples it also describes the most used frameworks for big data analysis like Hadoop, Spark, MPI, Hive and Storm. Each of the different systems is discussed and compared, highlighting their main features, their diffusion (both within their community of developers and among users), and their main advantages and disadvantages in implementing big data analysis applications.