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...is a collective term for characteristics that the two institutions share.
█ Fast Data Processing Systems with SMACK stack
█
▄
█ by Ra·l Estrada Aparicio
█ Publisher: Packt Publishing
▓ Release Date: June 2017
▓ ISBN: 9781788298452
▒ Running time: 6:30:22
▒ Topic: Cassandra
░ Scale: 29x50mb
░ Downloads: (■) Included ( ) Without
░
░ Lecture Date: 09/2017
░ Lecture Link: https://goo.gl/wL624X
░
:
| Build data processing platforms that can take on even the hardest
| of your data troubles!
|
| About This Video
|
| This highly practical tutorial shows you how to use the best of
| the big data technologies to solve your response-critical problems
| Learn the art of making cheap-yet-effective big data architecture
| without using complex Greek-letter architectures
| Use this easy-to-follow video to build fast data processing
| systems for your organization
| In Detail
|
| 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.WeÆll start off with an introduction to SMACK
| and show you when to use it. First youÆll get to grips with
| functional thinking and problem solving using Scala. Next youÆll
| come to understand the Akka architecture. Then youÆll get to know
| how to improve the data structure architecture and optimize
| resources using Apache Spark. Moving forward, youÆll learn how to
| perform linear scalability in databases with Apache Cassandra.
| YouÆll grasp the high throughput distributed messaging systems
| using Apache Kafka. WeÆll 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.
,