Mastering Apache Cassandra 3.x: An expert guide to improving database scalability and availability without compromising performance, 3rd Edition

Mastering Apache Cassandra 3.x: An expert guide to improving database scalability and availability without compromising performance, 3rd EditionReviews
Author: Aaron Ploetz
Pub Date: 2018
ISBN: 978-1789131499
Pages: 348
Language: English
Format: EPUB
Size: 12 Mb

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Build, manage, and configure high-performing, reliable NoSQL database for your applications with Cassandra
With ever-increasing rates of data creation, the demand for storing data fast and reliably becomes a need. Apache Cassandra is the perfect choice for building fault-tolerant and scalable databases. Mastering Apache Cassandra 3.x teaches you how to build and architect your clusters, configure and work with your nodes, and program in a high-throughput environment, helping you understand the power of Cassandra as per the new features.
Once you’ve covered a brief recap of the basics, you’ll move on to deploying and monitoring a production setup and optimizing and integrating it with other software. You’ll work with the advanced features of CQL and the new storage engine in order to understand how they function on the server-side. You’ll explore the integration and interaction of Cassandra components, followed by discovering features such as token allocation algorithm, CQL3, vnodes, lightweight transactions, and data modelling in detail. Last but not least you will get to grips with Apache Spark.
By the end of this book, you’ll be able to analyse big data, and build and manage high-performance databases for your application.
What you will learn

  • Write programs more efficiently using Cassandra’s features more efficiently
  • Exploit the given infrastructure, improve performance, and tweak the Java Virtual Machine (JVM)
  • Use CQL3 in your application in order to simplify working with Cassandra
  • Configure Cassandra and fine-tune its parameters depending on your needs
  • Set up a cluster and learn how to scale it
  • Monitor a Cassandra cluster in different ways
  • Use Apache Spark and other big data processing tools