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

Preferred zones


Locating ObjectGrid containers in different cities is a common use. Consider our ObjectGrid deployment policy file with zones named rack1, rack2, rack3, and rack4 running in New York City (NYC), and zones named rack1a and rack2a running in Boston. Working with the grid a client in NYC will read from primary and synchronous replicas with very low latency. A client will only read from an asynchronous replica in Boston if no shard in NYC is available to fulfill the request.

However, a grid client in Boston, will also prefer to read from primary and synchronous replicas in NYC. Each read and write request will make an RPC, not to the asynchronous replicas in Boston, but to the shards in NYC. Making this RPC for every grid request kills throughput because of the latency involved in going to a shard located in NYC. The Boston-based asynchronous replicas are essentially backups, in case all shards in NYC become unavailable.

We stress that locality of reference is very important in...