Getting Started with Hazelcast - Second Edition: Get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application - Tapa blanda

Sinopsis

Get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application

About This Book

• Store and pass data in your application using Hazelcast's scalable and resilient collections, working with real code and examples to see what is really going on
• Introduction to data grids, and their power of bringing data and code closer together in order to build bigger, better applications that can cope with a cloud scale world
• Hands-on examples to progressively walk you through all the powerful features and capabilities on offer

Who This Book Is For

This book is a great introduction for Java developers, software architects, or DevOps looking to enable scalable and agile data within their applications. Providing in-memory object storage, cluster-wide state and messaging, or even scalable task execution, Hazelcast helps solve a number of issues that have troubled technologists for years.

What You Will Learn

• Learn and store numerous data types in different distributed collections
• Set up a cluster from the ground up
• Work with truly distributed queues and topics for cluster-wide messaging
• Make your application more resilient by listening into cluster internals
• Run tasks within and alongside our stored data
• Filter and search our data using MapReduce jobs
• Discover the new JCache standard and one of its first implementations

In Detail

This book is an easy-to-follow, hands-on introduction that guides you through this innovative new technology. It covers everything from data grids to the simple-to-use distributed data storage collections. Queuing and topic messaging capabilities, as well as locking and transaction support to guard against concurrency race-conditions, are some of the topics that we will cover. We will then move on to distributed task execution, in-place data manipulations and big data analytical processing using MapReduce.

At the end of all this, you will be armed with everything you need to bring amazing power and data scalability to your applications, as well as making them truly global and ready for a worldwide audience.

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