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

Deadlocks


We can avoid the OptimisticCollisionException by using the pessimistic lock strategy. The pessimistic strategy assumes that objects can and will be updated simultaneously by multiple threads. By assuming that multiple threads will be writing to objects in a BackingMap, we give up a little concurrency, but we don't need to handle OptimisticCollisionExceptions. Where the optimistic lock strategy only briefly holds S or X locks, the pessimistic strategy holds locks for the duration of the transaction. The pessimistic lock strategy also makes the U lock available for use.

When we use a get method to retrieve an object from a BackingMap, our transaction in thread 1 obtains an S lock on that object and holds it for the duration of the transaction. When thread 2 uses a get method to retrieve the same object, the S lock held by thread 1 will not block thread 2 from obtaining an S lock. Now that both threads have S locks, they modify the state of the object and use a put method to push...