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Mastering Apache Cassandra 3.x: An expert guide to improving database scalability and availability without compromising performance, 3rd Edition 3rd Revised edition [Pehme köide]

  • Formaat: Paperback / softback, 348 pages, kõrgus x laius: 93x75 mm
  • Ilmumisaeg: 31-Oct-2018
  • Kirjastus: Packt Publishing Limited
  • ISBN-10: 1789131499
  • ISBN-13: 9781789131499
Teised raamatud teemal:
  • Formaat: Paperback / softback, 348 pages, kõrgus x laius: 93x75 mm
  • Ilmumisaeg: 31-Oct-2018
  • Kirjastus: Packt Publishing Limited
  • ISBN-10: 1789131499
  • ISBN-13: 9781789131499
Teised raamatud teemal:
Build, manage, and configure high-performing, reliable NoSQL database for your applications with Cassandra

Key Features

Write programs more efficiently using Cassandra's features with the help of examples Configure Cassandra and fine-tune its parameters depending on your needs Integrate Cassandra database with Apache Spark and build strong data analytics pipeline

Book DescriptionWith 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 youve covered a brief recap of the basics, youll move on to deploying and monitoring a production setup and optimizing and integrating it with other software. Youll work with the advanced features of CQL and the new storage engine in order to understand how they function on the server-side. Youll 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, youll 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

Who this book is forMastering Apache Cassandra 3.x is for you if you are a big data administrator, database administrator, architect, or developer who wants to build a high-performing, scalable, and fault-tolerant database. Prior knowledge of core concepts of databases is required.
Table of Contents

Quick Start
Cassandra Architecture
Effective CQL
Configuring a Cluster
Performance Tuning
Managing a Cluster
Monitoring
Application Development
Integration with Apache Spark
Appendix - References
Aaron Ploetz is the NoSQL Engineering Lead for Target, where his DevOps team supports Cassandra, MongoDB, and Neo4j. He has been named a DataStax MVP for Apache Cassandra three times and has presented at multiple events, including the DataStax Summit and Data Day Texas. Aaron earned a BS in Management/Computer Systems from the University of Wisconsin-Whitewater, and an MS in Software Engineering from Regis University. He and his wife, Coriene, live with their three children in the Twin Cities area. Tejaswi Malepati is the Cassandra Tech Lead for Target. He has been instrumental in designing and building custom Cassandra integrations, including web-based SQL interface and data validation frameworks between Oracle and Cassandra. Tejaswi earned a master's degree in computer science from the University of New Mexico, and a bachelor's degree in Electronics and Communication from Jawaharlal Nehru Technological University in India. He is passionate about identifying and analyzing data patterns in datasets using R, Python, Spark, and Cassandra. Nishant Neeraj is an independent software developer with experience in developing and planning out architectures for massively scalable data storage and data processing systems. Over the years, he has helped to design and implement a wide variety of products and systems for companies, ranging from small start-ups to large multinational companies. Currently, he helps drive WealthEngine's core product to the next level by leveraging a variety of big data technologies.