Big Data SMACK A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka /

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Integrate full-stack open-source fast data pipeline architecture and choose the correct technology-Spark, Mesos, Akka, Cassandra, and Kafka (SMACK)-in every layer. Fast data is becoming a requirement for many enterprises. So far, however, the focus has largely been on collecting, aggregating, and cr...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Estrada, Raul (Autor), Ruiz, Isaac (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berkeley, CA : Apress : Imprint: Apress, 2016.
Edición:1st ed. 2016.
Temas:
Big data.
Database management.
Artificial intelligence-Data processing.
Big Data.
Database Management.
Data Science.
Acceso en línea:Texto Completo

MARC

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505 0 |a Part 1. Introduction -- Chapter 1. Big Data, Big Problems -- Chapter 2. Big Data, Big Solutions -- Part 2. Playing SMACK -- Chapter 3. The Language: Scala -- Chapter 4. The Model: Akka -- Chapter 5. Storage. Apache Cassandra -- Chapter 6. The View -- Chapter 7. The Manager: Apache Mesos -- Chapter 8. The Broker: Apache Kafka -- Part 3. Improving SMACK -- Chapter 9. Fast Data Patterns -- Chapter 10. Big Data Pipelines -- Chapter 11. Glossary. 
520 |a Integrate full-stack open-source fast data pipeline architecture and choose the correct technology-Spark, Mesos, Akka, Cassandra, and Kafka (SMACK)-in every layer. Fast data is becoming a requirement for many enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases organizations need more than one paradigm to perform efficient analyses. Big Data SMACK explains each technology and, more importantly, how to integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples. The book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by each technology. This book covers the five main concepts of data pipeline architecture and how to integrate, replace, and reinforce every layer: The engine: Apache Spark The container: Apache Mesos The model: Akka< The storage: Apache Cassandra The broker: Apache Kafka. 
650 0 |a Big data. 
650 0 |a Database management. 
650 0 |a Artificial intelligence-Data processing. 
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650 2 4 |a Data Science. 
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776 0 8 |i Printed edition:  |z 9781484221747 
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950 |a Professional and Applied Computing (R0) (SpringerNature-43716) 

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