Fast Data Processing Systems with SMACK stack

Course details

SMACK is an open source full stack for big data architecture. It is a combination of Spark, Mesos, Akka, Cassandra, and Kafka. This stack is the newest technique developers have begun to use to tackle critical real-time analytics for big data. This highly practical tutorial will teach you how to integrate these technologies to create a highly efficient data analysis system for fast data processing.Well start off with an introduction to SMACK and show you when to use it. First youll get to grips with functional thinking and problem solving using Scala. Next youll come to understand the Akka architecture. Then youll get to know how to improve the data structure architecture and optimize resources using Apache Spark. Moving forward, youll learn how to perform linear scalability in databases with Apache Cassandra. Youll grasp the high throughput distributed messaging systems using Apache Kafka. Well show you how to build a cheap but effective cluster infrastructure with Apache Mesos. Finally, you will deep dive into the different aspects of SMACK using 2 practical case studies. By the end of the video, you will be able to integrate all the components of the SMACK stack and use them together to achieve highly effective and fast data processing.

About The Author

Ral Estrada Apariciois a programmer since 1996 and Java Developer since 2001. He loves functional languages such as Scala, Elixir, Clojure, and Haskell. He also loves all the topics related to Computer Science. With more than 12 years of experience in High Availability and Enterprise Software, he has designed and implemented architectures since 2003.

His specialization is in systems integration and has participated in projects mainly related to the financial sector. He has been an enterprise architect for BEA Systems and Oracle Inc., but he also enjoys Mobile Programming and Game Development. He considers himself a programmer before an architect, engineer, or developer.

He is also a Crossfitter in San Francisco, Bay Area, now focused on Open Source projects related to Data Pipelining such as Apache Flink, Apache Kafka, and Apache Beam.

Raul is a supporter of free software, and enjoys to experiment with new technologies, frameworks, languages, and methods.