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Oracle RAC Grid Evolution

Oracle RAC Cluster Tips by Burleson Consulting

This is an excerpt from the bestselling book Oracle Grid & Real Application Clusters.  To get immediate access to the code depot of working RAC scripts, buy it directly from the publisher and save more than 30%.

Evolution of Oracle Grid

Over the last decade, Grid technologies have emerged out of research and development institutions in both academia and industry. In the early 1990?s, work in meta-computing and related fields involved the development of custom solutions to Grid Computing problems. From 1997 onward, the open source Global Toolkit Version 2 (GT2) emerged as the de-facto standard for Grid Computing. GT2 initiative defined protocols, APIs and services used in grid deployments worldwide.

GT2 creation was a remarkable event, as it pioneered the creation of interoperable grid systems and helped to develop many grid programming tools. Many standards evolved in due course, notably the GridFTP data transfer protocol and elements of Grid Security Infrastructure. However, these standards were neither formal nor subject to public review.

In 2002, Open Grid Services Architecture (OGSA) standard emerged as a consensus standard. This became a true community standard with multiple implementations, including OGSA based Global Tool Kit 3.0. OGSA now provides a foundation and framework wherein one can define a wide range of interoperable, portable services.

Now, many researchers and industry supporters believe that the formation of OGSA technical specifications will give enough impetus for the formation of expanding the set of interoperable services and systems that address scalability issues, increased degree of virtualization, extensive sharing and increased quality services. With participation of key IT industry leaders, the grid concept is being applied toward solving more and more projects, and also there will be more sharing and virtualization in the future.

Oracle Grid vs. Cluster Computing

The Grid is not a Cluster. The key distinction between clusters and grids lies mainly in the way the resources are managed. In the case of clusters, the resource allocation is performed by a centralized resource manager and all nodes cooperatively work together as a single unified resource. The result of such aggregation is to present a single system image (SSI). Clusters are generally built for a specific purpose, for instance to host a parallel database server, or for hosting an application server. In the case of Grids, each node has its own resource manager and does not aim for providing a single system view. They, in turn, provide a pool of resources for a variety of users and applications. We also notice that the autonomous resources in Grid can span across single or multiple organizations.

In a way, Grid encompasses a bigger framework and provides wider and loosely coupled aggregation of servers and other related resources.

Grid?s architecture employs specialized scheduling software that identifies available resources and allocates tasks for processing accordingly. Requests for resources are processed wherever it is most efficient or wherever a specific function resides. Computers or nodes located in the grid are able to act independently without centralized control, handling requests as they are made and scheduling others. If one set of resources isn't available, they will simply use another.

Grid Goals and Objectives

The main attraction for using the Grid paradigm is to run an existing application on a different machine or group of machines. The machine on which the application is normally run might be unusually busy due to an unusual peak in activity. The job could be run on an idle machine elsewhere on the grid. In order for this to occur, the application must be executable remotely and without undue overhead. The remote machine must meet any special hardware, software, or resource requirements imposed by the application.

If the applications are grid-enabled, they can be moved to under-utilized machines during such peaks. Some grid implementations can migrate the partially completed jobs. In general, a grid can provide a consistent way to balance the loads on a wider federation of resources.

Utilization of Parallel CPU Activity

Many of the modern applications are written with algorithms to exploit the CPU power across many hosts or servers. Grids with networks of multiple servers provide a very good opportunity for these parallel applications to exploit the multiple processors. A CPU intensive grid application can be thought of as a collection of many smaller sub-jobs, each executing on a different machine in the grid. To the extent that these sub-jobs do not need to communicate with each other, the more scalable the application becomes.


This is an excerpt from the bestselling book Oracle Grid & Real Application Clusters, Rampant TechPress, by Mike Ault and Madhu Tumma.

You can buy it direct from the publisher for 30%-off and get instant access to the code depot of Oracle tuning scripts.



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