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  • Book Overview & Buying Getting Started with Hazelcast, Second Edition
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Getting Started with Hazelcast, Second Edition

Getting Started with Hazelcast, Second Edition

By : Matthew Johns
3.3 (3)
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Getting Started with Hazelcast, Second Edition

Getting Started with Hazelcast, Second Edition

3.3 (3)
By: Matthew Johns
Buy this Book

Overview of this book

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.
Table of Contents (14 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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Trademarks
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1
1. What is Hazelcast?
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1. What is Hazelcast?
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Starting out as usual
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Data deciding to hang around
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Therein lies the problem
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Breaking the mould
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Moving to new ground
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Summary
2
2. Getting off the Ground
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2. Getting off the Ground
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Let's get started
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Showing off straightaway
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Mapping back to the real world
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Sets, lists, and queues
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Many things at a time
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Searching and indexing
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What happens when we reach our limits?
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Summary
3
3. Going Concurrent
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3. Going Concurrent
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Atomic control
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Distributed locking
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Transactionally rolling on
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Spreading the word
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Summary
4
4. Divide and Conquer
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4. Divide and Conquer
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Divvying up the data
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Backups everywhere and nowhere
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Scaling up the cluster
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Having some of our data everywhere
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Grouping and separating nodes
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Network partitioning
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Maintaining quorum
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Summary
5
5. Listening Out
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5. Listening Out
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Listening to the goings-on
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The sound of our own data
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Programmatic configuration ahead of time
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Events unfolding in the wider world
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Moving data around the place
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Extending quorum
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Summary
6
6. Spreading the Load
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6. Spreading the Load
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All power to the compute
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Running once, running everywhere
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Placing tasks next to the data
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Summary
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7. Gathering Results
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7. Gathering Results
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What is this big data hype all about?
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Putting theory into practice
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Simplifying just aggregating up
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Summary
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8. Typical Deployments
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8. Typical Deployments
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All heap and nowhere to go
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Stepping back from the cluster
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Serialization and classes
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Getting straight to the point
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Architectural overview
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Summary
9
9. From the Outside Looking In
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9. From the Outside Looking In
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What about the rest of us?
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Memcache
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Going RESTful
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Summary
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10. Going Global
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10. Going Global
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Getting set up in the cloud
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Spreading out around the globe
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Summary
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11. Playing Well with Others
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11. Playing Well with Others
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Don't pass what you need, depend on it
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Transparently caching others' data
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Cacheable methods with the Spring cache
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Caching by standard
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Collection persistence
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Web session storage
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Cluster management
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Summary
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A. Configuration Summary
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A. Configuration Summary
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Cluster name
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Management center
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General properties
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WAN replication configuration
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Local network/interface binding
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Cluster discovery (multicast-, unicast-, or EC2-based)
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Map configuration
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Listeners notified on map events
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Listeners notified on topic broadcast
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Cluster-wide listener registration
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Index
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Index

Architectural overview

As we have seen, there are a few different types of deployment we could use; which one you choose really depends on your application's make-up. Each has a number of trade-offs, but most deployments tend to use one of the first two, with the client and server cluster approach the usual favorite unless we have a mostly compute-focused application where the former is a simpler setup.

So, let's have a look at the various architectural setups that we can employ and what situations they are best suited to.

Peer-to-peer clusters

This is the standard example that we have been mostly using until now: each node houses both our application and the data persistence and processing. It is most useful when we have an application that is primarily focused towards asynchronous or high-performance computing and executes a lot of tasks on the cluster. The greatest drawback is the inability to scale our application and data capacity separately.

Smart clients and server clusters

This is a more...

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Tech Concepts
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Programming languages
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Getting Started with Hazelcast, Second Edition
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