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Learning Apache Cassandra. Managing fault-tolerant, scalable data with high performance - Second Edition Sandeep Yarabarla

Język publikacji: angielskim
Learning Apache Cassandra. Managing fault-tolerant, scalable data with high performance - Second Edition Sandeep Yarabarla - okladka książki

Learning Apache Cassandra. Managing fault-tolerant, scalable data with high performance - Second Edition Sandeep Yarabarla - okladka książki

Autor:
Sandeep Yarabarla
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
360
Dostępne formaty:
     PDF
     ePub
     Mobi

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Cassandra is a distributed database that stands out thanks to its robust feature set and intuitive interface, while providing high availability and scalability of a distributed data store. This book will introduce you to the rich feature set offered by Cassandra, and empower you to create and manage a highly scalable, performant and fault-tolerant database layer.

The book starts by explaining the new features implemented in Cassandra 3.x and get you set up with Cassandra. Then you’ll walk through data modeling in Cassandra and the rich feature set available to design a flexible schema. Next you’ll learn to create tables with composite partition keys, collections and user-defined types and get to know different methods to avoid denormalization of data. You will then proceed to create user-defined functions and aggregates in Cassandra. Then, you will set up a multi node cluster and see how the dynamics of Cassandra change with it. Finally, you will implement some application-level optimizations using a Java client.

By the end of this book, you'll be fully equipped to build powerful, scalable Cassandra database layers for your applications.

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O autorze książki

Sandeep Yarabarla is a professional software engineer working for Verizon Labs, based out of Palo Alto, CA. After graduating from Carnegie Mellon University, he has worked on several big data technologies for a spectrum of companies. He has developed applications primarily in Java and Go. His experience includes handling large amounts of unstructured and structured data in Hadoop, and developing data processing applications using Spark and MapReduce. Right now, he is working with some cutting-edge technologies such as Cassandra, Kafka, Mesos, and Docker to build fault-tolerant and highly scalable applications.

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