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Oracle RAC - Types of Grid computing

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%.

Virtual Computing Systems and RAC

Grid extends the existing distributed computing resources further into a more unified and collaborative structure. Grid also enables the heterogeneous systems to work together to form the image of a large virtual computing system offering a variety of virtual resources. The users of the grid can be organized dynamically into a number of virtual organizations, each with different policy requirements. These virtual organizations can share their resources collectively as a larger grid.

The participants and users of the grid can be members of several real and virtual organizations. The grid can help in enforcing security rules among them and implement policies, which can resolve priorities for both resources and users.

Additional RAC Resources and RAC Resource Balancing

In addition to CPU and Storage resources, a grid can also provide access to increased quantities of other resources and to special equipment, software, licenses, and other services. For applications that are grid enabled, the grid can offer a resource balancing effect by scheduling grid jobs on machines with low utilization as well.

This re-balance feature is quite significant for handling occasional peak loads of activity in parts of larger organizations. This can happen in two ways:

- An unexpected peak can be routed to relatively idle machines in the grid.
- If the grid is already fully utilized, the lowest priority work being performed on the grid can be temporarily suspended or even cancelled and performed again later to make room for the higher priority work.

Without a grid infrastructure, such balancing decisions are difficult to prioritize and execute. Therefore, processing the batch jobs can be achieved more quickly by spreading them across more resources.

Secure and Federated Data Access

In a large-scale distributed environment, there are many heterogeneous data sources, files, databases, XML documents and so on. Users often end up coding very complex applications to access them. The collaborative work requires that all the data is available in some uniform way. Grid can be a solution in this area as well.

There are several forces driving the progression toward the Grid Computing paradigm. Among them are the relentless increase in microprocessor performance, and the availability, reliability, and bandwidth of global networking. New scientific experiments are producing a data explosion and the need for sharing such community data.

Oracle Grid Types

In a way, Grid Architecture is still in the evolving stage. There are many variations and types of Grids. They are often based on one?s own needs and their own understanding.

There is no standard in categorization of grids. Many Research Analysts, IT vendors, and Computer scientists began classifying the grid and grid variations based their own understanding and vision. Some base it on the functionality and some base it on the architecture and some on the built-in components. Many organizations have different focuses, thus resulting in different classifications. Grid computing can be used in a variety of ways to address various kinds of application requirements. Often, grids are categorized by the type of solutions that they best address.

Again, there are no hard and fast rules or boundaries between these grid types and often grids may be a combination of two or more of these.

For example, Clubby Analytics, a research analysis organization, categorizes the Grids into four types:

Compute Grids ? These are the grids designed for exploiting unused computing power or the CPU cycles. They have been in use for scientific, engineering and space research for a long time.

Information Grids ? These grids are more like peer-to peer services, primarily for the purpose of collaborative computing, file sharing. These are also sometimes called ?data grids?, which provide standards based federated data sharing for business applications.

Service Grids ? These types of Grids combine the physical elements of grid interconnection (high speed, fabric-like network interconnect) with web services program to program architecture to deliver an environment that allows different applications, running on varied operating environments, to run and interoperate.

Intelligent Grids ? These grids will consist of basic grid network interconnect elements combined with systems/storage/network management hardware/software enhancements (and maybe even applications and database management capabilities) that will enable grid devices to automatically manage themselves or other devices on the network.

Looking at another example, Sun Microsystems has a different vision for Grids. They classify grids into Cluster Grids, Campus Grids, and Global Grids. This classification is based on the geographical dispersion of the servers.

Cluster Grids - Cluster Grids consist of one or more systems working together to provide a single point of access to users. Typically owned and used by a small number of users, such as a project or department, Cluster Grids support both high-throughput and high-performance jobs. Resources in the grid can be focused on a narrow set of repetitive tasks, or made to work in true parallel fashion to execute a complex job.

Campus Grids - As capacity needs and demands for greater economy increase, organizations can combine their Cluster Grids into Campus Grids. Campus Grids enable multiple projects or departments to share computing resources in a cooperative way.

Global Grids - When application needs exceed the capacity of a Campus Grid, organizations can tap partner resources through a Global Grid. Designed to support and address the needs of multiple sites and organizations sharing resources, Global Grids provide the power of distributed resources to users anywhere in the world.

The following is IBM?s spin on Grids. They define three types of Grids. The three primary types of grids are summarized below.

Computational Grid - A computational grid is focused on setting aside resources specifically for computing power. In this type of grid, most of the machines are high-performance servers.

Scavenging Grid - A scavenging grid is most commonly used with large numbers of desktop machines. Machines are scavenged for available CPU cycles and other resources. Owners of the desktop machines are usually given control over when their resources are available to participate in the grid.

Data Grid - A data grid is responsible for housing and providing access to data across multiple organizations. Users are not concerned with where this data is located as long as they have access to the data. For example, there may be two universities doing life science research, each with unique data. A data grid would allow them to share their data, manage the data, and manage security issues such as who has access to what data.

However, most researchers seem to prefer to define Girds loosely into two types: Computational Grids and Data Grids. The Computational grids are mainly focusing on the utilization of CPU cycles the so-called processing power from the under-utilized computers. There are many community projects that have been launched, and they are soliciting unused processing power from community members. In the commercial world, within the secured walls of the enterprise, there is good scope for similar exercises to pool unused resources. They all aim at harnessing and executing the jobs in parallel, and achieving higher throughput and better response times.

At the same time, another major requirement is to process, analyze and summarize huge chunks of data located in different locations and different forms. That is where the concept of Data Grid is making strides. Data Grids focus on discovering, collecting and aggregating various forms of data and presenting the data seamlessly to the users for effective processing.

There is a definite case for data and computational grids as these are the key resources, which are in high usage and demand.


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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