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

Getting Started with Hazelcast - Second Edition

This ebook is included in a Mapt subscription
Mat Johns

Get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application
$0.00
$27.99
$34.99
$29.99p/m after trial
RRP $27.99
RRP $34.99
Subscription
eBook
Print + eBook
Start 30 Day Trial
Subscribe and access every Packt eBook & Video.
 
  • 4,000+ eBooks & Videos
  • 40+ New titles a month
  • 1 Free eBook/Video to keep every month
Start Free Trial
 
Preview in Mapt

Book Details

ISBN 139781785285332
Paperback162 pages

Book Description

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.

Table of Contents

Chapter 1: What is Hazelcast?
Starting out as usual
Data deciding to hang around
Therein lies the problem
Breaking the mould
Moving to new ground
Summary
Chapter 2: Getting off the Ground
Let's get started
Showing off straightaway
Mapping back to the real world
Sets, lists, and queues
Many things at a time
Searching and indexing
What happens when we reach our limits?
Summary
Chapter 3: Going Concurrent
Atomic control
Distributed locking
Transactionally rolling on
Spreading the word
Summary
Chapter 4: Divide and Conquer
Divvying up the data
Backups everywhere and nowhere
Scaling up the cluster
Having some of our data everywhere
Grouping and separating nodes
Network partitioning
Maintaining quorum
Summary
Chapter 5: Listening Out
Listening to the goings-on
The sound of our own data
Programmatic configuration ahead of time
Events unfolding in the wider world
Moving data around the place
Extending quorum
Summary
Chapter 6: Spreading the Load
All power to the compute
Running once, running everywhere
Placing tasks next to the data
Summary
Chapter 7: Gathering Results
What is this big data hype all about?
Putting theory into practice
Simplifying just aggregating up
Summary
Chapter 8: Typical Deployments
All heap and nowhere to go
Stepping back from the cluster
Serialization and classes
Getting straight to the point
Architectural overview
Summary
Chapter 9: From the Outside Looking In
What about the rest of us?
Memcache
Going RESTful
Summary
Chapter 10: Going Global
Getting set up in the cloud
Spreading out around the globe
Summary
Chapter 11: Playing Well with Others
Don't pass what you need, depend on it
Transparently caching others' data
Cacheable methods with the Spring cache
Caching by standard
Collection persistence
Web session storage
Cluster management
Summary

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

Authors

Table of Contents

Chapter 1: What is Hazelcast?
Starting out as usual
Data deciding to hang around
Therein lies the problem
Breaking the mould
Moving to new ground
Summary
Chapter 2: Getting off the Ground
Let's get started
Showing off straightaway
Mapping back to the real world
Sets, lists, and queues
Many things at a time
Searching and indexing
What happens when we reach our limits?
Summary
Chapter 3: Going Concurrent
Atomic control
Distributed locking
Transactionally rolling on
Spreading the word
Summary
Chapter 4: Divide and Conquer
Divvying up the data
Backups everywhere and nowhere
Scaling up the cluster
Having some of our data everywhere
Grouping and separating nodes
Network partitioning
Maintaining quorum
Summary
Chapter 5: Listening Out
Listening to the goings-on
The sound of our own data
Programmatic configuration ahead of time
Events unfolding in the wider world
Moving data around the place
Extending quorum
Summary
Chapter 6: Spreading the Load
All power to the compute
Running once, running everywhere
Placing tasks next to the data
Summary
Chapter 7: Gathering Results
What is this big data hype all about?
Putting theory into practice
Simplifying just aggregating up
Summary
Chapter 8: Typical Deployments
All heap and nowhere to go
Stepping back from the cluster
Serialization and classes
Getting straight to the point
Architectural overview
Summary
Chapter 9: From the Outside Looking In
What about the rest of us?
Memcache
Going RESTful
Summary
Chapter 10: Going Global
Getting set up in the cloud
Spreading out around the globe
Summary
Chapter 11: Playing Well with Others
Don't pass what you need, depend on it
Transparently caching others' data
Cacheable methods with the Spring cache
Caching by standard
Collection persistence
Web session storage
Cluster management
Summary

Book Details

ISBN 139781785285332
Paperback162 pages
Read More

Read More Reviews