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Oracle RAC Grid Computing Fundamentals

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%.

Grid Computing Fundamentals

CPU cycles, or more appropriately the idle CPU cycles, are in demand. In addition, the CPU cycles are available in the servers, which are under-utilized. For processing a large problem in a fairly small amount of time, more CPU cycles are needed. The availability of such resources concurrently (in parallel mode) helps to compute much faster than a single server and its built-in processors.

The next important component is the availability of the data. Where is the data to process and then provide the results? The data is stored in organized and structured databases. While storage systems physically store the data blocks on media devices such as disk drives in the storage arrays, provided mostly notably by, EMC, Hitachi and IBM, the servers fetch and process in the name of relational databases.

The two important resources processing power and storage systems are the main areas of attention for grid planners and grid users.

What is Oracle Grid Computing?

Back in 1998, Carl Kesselman and Ian Foster in the book ?The Grid: Blueprint for a New Computing Infrastructure,? while attempting to give a broader vision of Grid, wrote:

?A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities.?

Subsequently, Ian Foster with Steve Tuecke, redefined the definition stating that Grid Computing is concerned with ?coordinated source sharing and problem solving in dynamic, multi-institutional virtual organizations.? They further noted:

?The sharing that we are concerned with is not primarily file exchange but rather direct access to computers, software, data, and other resources, as is required by a range of collaborative problem solving and resource-brokering strategies emerging in industry, science, and engineering. This sharing is, necessarily, highly controlled, with resource providers and consumers defining clearly and carefully just what is shared, who is allowed to share, and the conditions under which sharing occurs. A set of individuals and/or institutions defined by such sharing rules form what we call a virtual organization.?

However, from the client, user, or consumer point of view, Grid computing is seen more of a utility of computing. Users do not care where their problem is computed or analyzed and where the data comes from. They are merely interested in getting the results, and getting it done faster and cheaper. From the server side, grid is all about the pooling resources, virtualization, and provisioning.

Simply put, Grid Computing is the pool of computers actively glued into a ?virtual computer? by the other related components such as middleware software, interconnects, networking devices and storage units. It is distributed computing taken to a higher evolutionary level. With standards being worked out for the effective sharing of resources from the Grid Pool and with the proper security access levels; Grid is a new class of infrastructure.

Based on the technological changes occurring in the contemporary period, Ian Foster gives an interesting justification for developing and implementing Grid Computing. In his words:

?The annual doubling of data storage capacity, as measured in bits per unit area, has already reduced the cost of a terabyte disk farm to less than $10 000. Anticipating that the trend will continue, the designers of major physics experiments are planning petabyte data archives. Scientists who create sequences of high-resolution simulations are also planning petabyte archives.

Such large data volumes demand more from our analysis capabilities. Dramatic improvements in microprocessor performance mean that the lowly desktop or laptop is now a powerful computational engine. Nevertheless, computer power is falling behind storage. By doubling "only" every 18 months or so, computer power takes five years to increase by a single order of magnitude. Assembling the computational resources needed for large-scale analysis at a single location is becoming infeasible. The solution to these problems lies in dramatic changes taking place in networking?

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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