Real-time Analytics with Storm and Cassandra - Brossura

Saxena, Shilpi

Brossura

ISBN 10: 1784395498 ISBN 13: 9781784395490

Casa editrice: Packt Publishing, 2015

Riassunto

Solve real-time analytics problems effectively using Storm and Cassandra

About This Book

• Create your own data processing topology and implement it in various real-time scenarios using Storm and Cassandra
• Build highly available and linearly scalable applications using Storm and Cassandra that will process voluminous data at lightning speed
• A pragmatic and example-oriented guide to implement various applications built with Storm and Cassandra

Who This Book Is For

If you want to efficiently use Storm and Cassandra together and excel at developing production-grade, distributed real-time applications, then this book is for you. No prior knowledge of using Storm and Cassandra together is necessary. However, a background in Java is expected.

What You Will Learn

• Integrate Storm applications with RabbitMQ for real-time analysis and processing of messages
• Monitor highly distributed applications using Nagios
• Integrate the Cassandra data store with Storm
• Develop and maintain distributed Storm applications in conjunction with Cassandra and In Memory Database (memcache)
• Build a Trident topology that enables real-time computing with Storm
• Tune performance for Storm topologies based on the SLA and requirements of the application
• Use Esper with the Storm framework for rapid development of applications

In Detail

This book will teach you how to use Storm for real-time data processing and to make your applications highly available with no downtime using Cassandra.

The book starts off with the basics of Storm and its components along with setting up the environment for the execution of a Storm topology in local and distributed mode. Moving on, you will explore the Storm and Zookeeper configurations, understand the Storm UI, set up Storm clusters, and monitor Storm clusters using various tools. You will then add NoSQL persistence to Storm and set up a Cassandra cluster. You will do all this while being guided by the best practices for Storm and Cassandra applications. Next, you will learn about data partitioning and consistent hashing in Cassandra through examples and also see high availability features and replication in Cassandra. Finally, you'll learn about different methods that you can use to manage and maintain Cassandra and Storm.

Su questo libro

L'autore

Shilpi Saxena

Shilpi Saxena is a seasoned professional, who is leading in management with an edge of being a technology evangelist. She is an engineer who has exposure to a variety of domains (machine to machine space, health care, telecom, hiring, and manufacturing). She has experience in all aspects of conception and execution of enterprise solutions. She has been architecting, managing and delivering solutions in the big data space for the last 3 years, handling high performance geographically distributed teams of elite engineers. Shilpi has more than 12 years (3 years in the big data space) of experience in development and execution of various facets of enterprise solutions both in product/services dimensions of the software industry. An engineer by degree and profession, she has worn varied hats―developer, technical leader, product owner, tech manager, and so on, and she has seen all flavors the industry has to offer. She has architected and worked through some of the pioneers' production implementation in big data on Storm and Impala with auto scaling in AWS. To know more about her, visit her LinkedIn profile at http://in.linkedin.com/pub/shilpi-saxena/4/552/a30.

Product Description

Real-Time Analytics With Storm And Cassandra by Shilpi Saxena, 9781784395490, Packt Publishing, 2015, Paperback

Dettagli dell'edizione

• Editore: Packt Publishing
• Data di pubblicazione: 2015
• Lingua: Inglese
• ISBN 10: 1784395498
• ISBN 13: 9781784395490
• Rilegatura: Copertina flessibile
• Numero di pagine: 220
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile