Big data analytics beyond Hadoop : real-time applications with Storm, Spark, and more Hadoop alternatives /

Master alternative Big Data technologies that can do what Hadoop can't: real-time analytics and iterative machine learning. When most technical professionals think of Big Data analytics today, they think of Hadoop. But there are many cutting-edge applications that Hadoop isn't well suited...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Agneeswaram, Vijay Srinivas
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Upper Saddle River, NJ : Pearson Education, ©2014.
Colección:FT Press Analytics Ser.
Temas:
Apache Hadoop.
Apache Hadoop
Electronic data processing.
Big data.
Data mining.
Business intelligence.
Information storage and retrieval systems.
Data Mining
Information Systems
Données volumineuses.
Exploration de données (Informatique)
Systèmes d'information.
COMPUTERS > General.
Big data
Business intelligence
Data mining
Electronic data processing
Information storage and retrieval systems
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • 1. Introduction: Why look beyond Hadoop map-reduce?
  • 2. What is the Berkeley data analytics stack (BDAS)?
  • 3. Realizing machine learning algorithms with spark
  • 4. Realizing machine learning algorithms in real time
  • 5. Graph processing paradigms
  • 6. Conclusions: big data analytics beyond Hadoop map-reduce
  • Appendix A. Code sketches.

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