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Big Data SMACK: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka [Paperback]

$34.99     $39.99   13% Off     (Free Shipping)
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  • Category: Books (Computers)
  • Author:  Estrada, Raul, Ruiz, Isaac
  • Author:  Estrada, Raul, Ruiz, Isaac
  • ISBN-10:  1484221745
  • ISBN-10:  1484221745
  • ISBN-13:  9781484221747
  • ISBN-13:  9781484221747
  • Publisher:  Apress
  • Publisher:  Apress
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Nov-2016
  • Pub Date:  01-Nov-2016
  • SKU:  1484221745-11-SPRI
  • SKU:  1484221745-11-SPRI
  • Item ID: 100166026
  • List Price: $39.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Nov 01 to Nov 03
  • Notes: Brand New Book. Order Now.

Learn how to integrate full-stack open source big data architecture and to choose the correct technologyScala/Spark, Mesos, Akka, Cassandra, and Kafkain every layer. 

Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses.

Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer:

  • The language: Scala
  • The engine: Spark (SQL, MLib, Streaming, GraphX)
  • The container: Mesos, Docker
  • The view: Akka
  • The storage: Cassandra
  • The message broker: Kafka
  • What You Will Learn:

    • Make big data architecture without using complex Greek letter architectures
    • Build a cheap but effective cluster infrastructure
    • Make queries, reports, and graphs that business demands
    • Manage and exploit unstructured and No-SQL data sources
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