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Fast Data Processing Systems with SMACK Stack

You're reading from  Fast Data Processing Systems with SMACK Stack

Product type Book
Published in Dec 2016
Publisher Packt
ISBN-13 9781786467201
Pages 376 pages
Edition 1st Edition
Languages
Author (1):
Raúl Estrada Raúl Estrada
Profile icon Raúl Estrada

Table of Contents (15) Chapters

Fast Data Processing Systems with SMACK Stack
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. An Introduction to SMACK 2. The Model - Scala and Akka 3. The Engine - Apache Spark 4. The Storage - Apache Cassandra 5. The Broker - Apache Kafka 6. The Manager - Apache Mesos 7. Study Case 1 - Spark and Cassandra 8. Study Case 2 - Connectors 9. Study Case 3 - Mesos and Docker

Spark Streaming


When studying calculus, one thing that remains clear is that life is not a discreet process, it is continuous; and life does not come in small packages, it is a continuously flowing stream.

As discussed in the first chapter, the fresher the information, the greater the benefit of the data. Many modern applications of machine-learning should be calculated in real-time.

Spark Streaming is the module for managing data flows. Much of Spark is built with the concept of RDD. Spark Streaming provides the concept of DStreams, or Discretized Streams. A DStream is a sequence of information related to time. It is very important to emphasize that an internal DStream is a sequence of RDD, hence the name discretized.

Just as RDDs have two transformations, DStreams also offer two types of operations:

  • Transformations (whose result is another DStream)
  • Output operations aimed at writing information to external systems

DStreams have many of the operations available in the RDDs, plus newer time-related...

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