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

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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Main Authors: Estrada, Raul, Ruiz, Isaac (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berkeley, CA Apress 2016, 2016
Edition:1st ed. 2016
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Summary: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
Physical Description:XXV, 264 p. 74 illus., 52 illus. in color online resource
ISBN:9781484221754