Apress | Big Data SMACK: A Guide To Apache Spark, Mesos, Akka, Cassandra, And Kafka (2016 EN)

Author: Raul Estrada Aparicio , Isaac Ruiz
Full Title: Big Data SMACK: A Guide To Apache Spark, Mesos, Akka, Cassandra, And Kafka
Publisher: Apress; 1st ed. edition (September 29, 2016)
Year: 2016
ISBN: 978-1-484221-74-7
Pages: 264
Language: English
Genre: Networking & Cloud Computing: Storage
File type: PDF (True)
Quality: 10/10
Price: $39.99


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


What you’ll learn:
✓ How to make big data architecture without using complex Greek letter architectures.
✓ How to build a cheap but effective cluster infrastructure.
✓ How to make queries, reports, and graphs that business demands.
✓ How to manage and exploit unstructured and No-SQL data sources.
✓ How use tools to monitor the performance of your architecture.
✓ How to integrate all technologies and decide which replace and which reinforce.

Who this book is for:
This book is for developers, data architects, and data scientists looking for how to integrate the most successful big data open stack architecture and how to choose the correct technology in every layer.

-------------
Our members see more. Join us!