Book Image

Fast Data Processing Systems with SMACK Stack

By : Raúl Estrada
Book Image

Fast Data Processing Systems with SMACK Stack

By: Raúl Estrada

Overview of this book

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 guide will teach you how to integrate these technologies to create a highly efficient data analysis system for fast data processing. We’ll start off with an introduction to SMACK and show you when to use it. First you’ll get to grips with functional thinking and problem solving using Scala. Next you’ll come to understand the Akka architecture. Then you’ll get to know how to improve the data structure architecture and optimize resources using Apache Spark. Moving forward, you’ll learn how to perform linear scalability in databases with Apache Cassandra. You’ll grasp the high throughput distributed messaging systems using Apache Kafka. We’ll show you how to build a cheap but effective cluster infrastructure with Apache Mesos. Finally, you will deep dive into the different aspect of SMACK using a few case studies. By the end of the book, 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.
Table of Contents (15 chapters)
Fast Data Processing Systems with SMACK Stack
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface

The Apache Mesos architecture


Mesos is an open source platform for sharing the resources of commodity machines between different distributed applications (later we see they are called frameworks in the Mesos ecosystem), such as Spark, Cassandra, and Kafka among others. Mesos objective is to run as a centralized cluster manager that pools all the physical resources of each cluster member and makes them available as a single source of highly available resources for all the different applications.

Let's take a simple example, a startup has bought eight machines for its humble data center, each one has 8 CPUs and 64 GB of RAM, and previously had a four node cluster where each machine had 4 CPUs and 16 GB of RAM. With Apache Mesos, we can make a virtual cluster that emulates a single machine with (8*8 + 4*4) 80 CPUs and (8*64 + 4*16) 576 GB of RAM. So easily we can have at our fingertips the power of ancestral mainframes. On this cluster we can run multiple distributed applications. The sharing...