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

Hitting the wall


IBM recommends no less than 10 shards per container. If we have less than 10 shards per container, the difference in load starts on a noticeable increase. Hopefully, this situation happens only at or near the end of the planned grid lifetime. If each container holds just one shard, then we have reached the end of the road for scalability. Should you need to grow the grid beyond the planned number of JVMs, an outage is unavoidable.

Avoid this situation with realistic planning up front to determine how many JVMs are required. Despite good planning, we can always reach the point where we have too few shards per JVM. If the planning stage used accurate data for determining the number of JVMs required, and shards/JVM is dropping, then you're experiencing faster-than-expected growth.

If you reach the point where five years of expected resources are simply not enough, then you have an enviable problem. Popularity to the point of burning through five years of data grid capacity is...