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Distributed Computing in Java 9

You're reading from   Distributed Computing in Java 9 Leverage the latest features of Java 9 for distributed computing

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787126992
Length 304 pages
Edition 1st Edition
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Table of Contents (17) Chapters Close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Customer Feedback
1. Quick Start to Distributed Computing FREE CHAPTER 2. Communication between Distributed Applications 3. RMI, CORBA, and JavaSpaces 4. Enterprise Messaging 5. HPC Cluster Computing 6. Distributed Databases 7. Cloud and Distributed Computing 8. Big Data Analytics 9. Testing, Debugging, and Troubleshooting 10. Security

Chapter 8. Big Data Analytics

Big data (as embodied by Hadoop clusters) and Big Compute (as embodied by MPI clusters) provide unique capabilities for storing and processing large volumes of data. Hadoop clusters make distributed computing readily accessible to the Java community, while MPI clusters provide high parallel efficiency for compute-intensive workloads. Bringing the big data and Big Compute communities together is an active area of research. Projects such as Apache ZooKeeper provide a centralized infrastructure and service that enables synchronization across a cluster, which is the way to achieve distributed computing in big data systems.

In this chapter, we will cover the following:

  • What is big data?
  • Big data characteristics
  • NoSQL databases
  • Hadoop, MapReduce, and HDFS
  • Distributed computing for big data
  • ZooKeeper for distributed computing

While technologies such as Hadoop, Hbase, Accumulo, and Cassandra allow us to store, query, and index large volumes of complex data, Dynamic Distributed...

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