Book Image

IBM WebSphere eXtreme Scale 6

By : Anthony Chaves
Book Image

IBM WebSphere eXtreme Scale 6

By: Anthony Chaves

Overview of this book

A data grid is a means of combining computing resources. Data grids provide a way to distribute object storage and add capacity on demand in the form of CPU, memory, and network resources from additional servers. All three resource types play an important role in how fast data can be processed, and how much data can be processed at once. WebSphere eXtreme Scale provides a solution to scalability issues through caching and grid technology. Working with a data grid requires new approaches to writing highly scalable software; this book covers both the practical eXtreme Scale libraries and design patterns that will help you build scalable software. Starting with a blank slate, this book assumes you don't have experience with IBM WebSphere eXtreme Scale. It is a tutorial-style guide detailing the installation of WebSphere eXtreme Scale right through to using the developer libraries. It covers installation and configuration, and discusses the reasons why a data grid is a viable middleware layer. It also covers many different ways of interacting with objects in eXtreme Scale. It will also show you how to use eXtreme Scale in new projects, and integrate it with relational databases and existing applications. This book covers the ObjectMap, Entity, and Query APIs for interacting with objects in the grid. It shows client/server configurations and interactions, as well as the powerful DataGrid API. DataGrid allows us to send code into the grid, which can be run where the data lives. Equally important are the design patterns that go alongside using a data grid. This book covers the major concepts you need to know that prevent your client application from becoming a performance bottleneck. By the end of the book, you'll be able to write software using the eXtreme Scale APIs, and take advantage of a linearly scalable middleware layer.
Table of Contents (15 chapters)
IBM WebSphere eXtreme Scale 6
Credits
About the Author
About the Reviewers
Preface

Hash map refresher (or crash course)


Locks on objects need to be stored somewhere accessible to different threads. Much like how objects are stored in buckets in the BackingMap, locks are also stored in buckets. This brings us to the numberOfBuckets and numberOfLockBuckets settings on a BackingMap. These settings are implementation details of a BackingMap, but it's important to know these details in order to assign optimum settings for concurrency and performance. BackingMaps use a hash table data structure to store objects.

Let's review a basic implementation of the hash map data structure so we know what the number of buckets means. Hash maps store objects in buckets. A bucket is a place for a value object keyed with a key object. A good key object is an integer, and as luck would have it, the hashCode() method on java.lang.Object returns an integer value. Because every object in Java inherits from java.lang.Object, we have the hashCode() method available to any object we create. We should...