Call now: 252-767-6166  
Oracle Training Oracle Support Development Oracle Apps

 E-mail Us
 Oracle Articles
New Oracle Articles

 Oracle Training
 Oracle Tips

 Oracle Forum
 Class Catalog

 Remote DBA
 Oracle Tuning
 Emergency 911
 RAC Support
 Apps Support
 Oracle Support

 SQL Tuning

 Oracle UNIX
 Oracle Linux
 Remote s
 Remote plans
 Application Server

 Oracle Forms
 Oracle Portal
 App Upgrades
 SQL Server
 Oracle Concepts
 Software Support

 Remote S


 Consulting Staff
 Consulting Prices
 Help Wanted!


 Oracle Posters
 Oracle Books

 Oracle Scripts

Don Burleson Blog 









Parallel Processing

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%.

Parallel processing is a vital part of any high performance computing model. It involves the utilization of large amounts of computing resources to complete a complex task or problem. The resources specific to parallel processing are CPU and memory. Originally confined to use in scientific applications, parallel processing has quickly made inroads into commercial and business applications that need high performance computing facilities like data mining, decision support, and risk management applications.

Parallel execution or processing involves the division of a task into several smaller tasks and making the system work on each of these smaller tasks in parallel. In simple terms, if multiple processors engage a computing task, it is generally executed faster. Parallel processing thereby improves response time and increases throughput by utilizing all of the available computing resources. Parallel execution helps systems scale performance by making optimal use of the hardware resources. In a parallel processing system, multiple processes may reside on a single computer or may be spread across several computers or nodes, as in an Oracle10g RAC cluster.

Some basic requirements for achieving parallel execution and better performance are:

* Computer system/servers with built in multiple processors and better message facilitation among processors.

* Operating system capable of managing the multiple processors.

* Clustered nodes with application software, such as Oracle RAC, that can parallel across the nodes.

There are many distinct benefits and advantages of utilizing parallel execution, such as:

* Better response times:  As the computing tasks are engaged by a group of processors, the tasks are completed in a smaller amount of time.

* Higher Throughput:  Parallel processing results in faster execution of tasks, increasing throughput. A large number of tasks can be performed in a given unit of time.

* Better Price/Performance:  It is usually more expensive to make one very fast single CPU instead of using several slower ones.

Types of Parallelism

There are many types of parallelism. Some of the types are as follows:

* Pipeline Parallelism:  In this type of processing, long sequences of operations, or tasks, are parallel, but there are also overlapping sequential processes during which no parallel tasks are possible. The relational model fits into this model very well. The output of some relational operators becomes the input for other operators; therefore, some waiting time is involved. There is a considerable amount of time saved in the completion of a task through the proper use of pipeline parallelism.

* Independent or Natural Parallelism:   - In this type of parallelism, the tasks do not depend on other tasks. As a result, total execution time is considerably reduced. Sometimes this type is called ?embarrassingly parallel.?

* Inter-query and Intra-query Parallelism:   - Transactions are independent. No transaction requires the output of another transaction to complete. Many CPUs can be kept busy by assigning each task or query to a separate CPU. This type of parallelism, utilizing many separate, independent queries at the same time, is called inter-query parallelism. This is a natural solution for OLTP-type operations. Even some small DSS operations work this way. Hence, the greater the number of CPUs available on a database server, the better the performance will be, in most situations. To speed up the execution of a single large and complex query, this model decomposes it into smaller problems.  It then executes these smaller tasks concurrently by assigning them separate CPUs. This type of parallelism is a natural solution for DSS-type operations where a single transaction analyzes, computes, and updates thousands of database blocks.


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.


Oracle Training at Sea
oracle dba poster

Follow us on Twitter 
Oracle performance tuning software 
Oracle Linux poster


Burleson is the American Team

Note: This Oracle documentation was created as a support and Oracle training reference for use by our DBA performance tuning consulting professionals.  Feel free to ask questions on our Oracle forum.

Verify experience! Anyone considering using the services of an Oracle support expert should independently investigate their credentials and experience, and not rely on advertisements and self-proclaimed expertise. All legitimate Oracle experts publish their Oracle qualifications.

Errata?  Oracle technology is changing and we strive to update our BC Oracle support information.  If you find an error or have a suggestion for improving our content, we would appreciate your feedback.  Just  e-mail:  

and include the URL for the page.


Burleson Consulting

The Oracle of Database Support

Oracle Performance Tuning

Remote DBA Services


Copyright © 1996 -  2017

All rights reserved by Burleson

Oracle ® is the registered trademark of Oracle Corporation.

Remote Emergency Support provided by Conversational