9781491933664-1491933666-Cassandra: The Definitive Guide: Distributed Data at Web Scale

Cassandra: The Definitive Guide: Distributed Data at Web Scale

ISBN-13: 9781491933664
ISBN-10: 1491933666
Edition: 2
Author: Eben Hewitt, Jeff Carpenter
Publication date: 2016
Publisher: O'Reilly Media
Format: Paperback 367 pages
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Book details

ISBN-13: 9781491933664
ISBN-10: 1491933666
Edition: 2
Author: Eben Hewitt, Jeff Carpenter
Publication date: 2016
Publisher: O'Reilly Media
Format: Paperback 367 pages

Summary

Cassandra: The Definitive Guide: Distributed Data at Web Scale (ISBN-13: 9781491933664 and ISBN-10: 1491933666), written by authors Eben Hewitt, Jeff Carpenter, was published by O'Reilly Media in 2016. With an overall rating of 3.9 stars, it's a notable title among other Data Modeling & Design (Databases & Big Data, Data Mining, Data Processing, Cloud Computing, Networking & Cloud Computing, Databases, Software) books. You can easily purchase or rent Cassandra: The Definitive Guide: Distributed Data at Web Scale (Paperback) from BooksRun, along with many other new and used Data Modeling & Design books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.33.

Description

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This expanded second edition—updated for Cassandra 3.0—provides the technical details and practical examples you need to put this database to work in a production environment.

Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s non-relational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility.

  • Understand Cassandra’s distributed and decentralized structure
  • Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell
  • Create a working data model and compare it with an equivalent relational model
  • Develop sample applications using client drivers for languages including Java, Python, and Node.js
  • Explore cluster topology and learn how nodes exchange data
  • Maintain a high level of performance in your cluster
  • Deploy Cassandra on site, in the Cloud, or with Docker
  • Integrate Cassandra with Spark, Hadoop, Elasticsearch, Solr, and Lucene
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