Author: Raúl Estrada Full Title: Fast Data Processing Systems With SMACK Stack Publisher: Packt Publishing - ebooks Account (January 5, 2017) Year: 2016 ISBN-13: 9781786467201 (978-1-78646-720-1) ISBN-10: 1786467208 Pages: 376 Language: English Genre: Computer Science: Databases & Big Data File type: PDF (True, but nonnative Cover) Quality: 9/10 Price: 34.99 € 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. What You Will Learn: — Design and implement a fast data Pipeline architecture — Think and solve programming challenges in a functional way with Scala — Learn to use Akka, the actors model implementation for the JVM — Make on memory processing and data analysis with Spark to solve modern business demands — Build a powerful and effective cluster infrastructure with Mesos and Docker — Manage and consume unstructured and No-SQL data sources with Cassandra — Consume and produce messages in a massive way with Kafka ------------- Our members see more. Join us!
