Oracle7 Server Tuning

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Types of Applications

There are thousands of types of applications that you can build on top of an Oracle Server. This section attempts to categorize the most popular types of applications and describe the design considerations for each. Each section lists topics that are crucial for performance for that type of system.

Refer to the Oracle7 Server Concepts manual, the Oracle7 Server Application Developer's Guide, and the Oracle7 Server Administrator's Guide for more information on these topics and how to implement them in your system.

Online Transaction Processing (OLTP)

Online transaction processing (OLTP) applications are high-throughput, insert/update intensive systems. These systems are characterized by constantly growing large volumes of data that several hundred users access concurrently. Typical OLTP applications are airline reservation systems, large order-entry applications, and banking applications. The key goals of an OLTP system are availability, speed, concurrency, and recoverability.

Figure 2 - 1 illustrates the interaction between an OLTP application and an Oracle Server.

Figure 2 - 1. Online Transaction Processing Systems

When you design an OLTP system, you must ensure that the large number of concurrent users does not interfere with the system's performance. You must also avoid excessive use of indexes and clusters because these structures slow down insert and update activity. The following topics are crucial in tuning an OLTP system:

Refer to the Oracle7 Server Concepts manual and the Oracle7 Server Administrator's Guide for a description of each of these topics. Read about these topics before designing your system and decide which features can benefit your particular situation.

Decision Support

Decision support applications distill large amounts of information into understandable reports. Typically, decision support applications perform queries on the large amount of data gathered from OLTP applications. Decision makers in an organization use these applications to determine what strategies the organization should take based on the available information.

Figure 2 - 2 illustrates the interaction between a decision support application and an Oracle Server.

Figure 2 - 2. Decision Support Systems

An example of a decision support system is a marketing tool that determines the buying patterns of consumers based on information gathered from demographic studies. The demographic data is gathered and entered into the system, and the marketing staff queries this data to determine which items sell best in which locations. This report helps to decide which items to purchase and market in the various locations.

The key goals of a decision support system are speed, accuracy, and availability.

When you design a decision support system, you must ensure that queries on large amounts of data can perform within a reasonable time frame. Decision makers often need reports on a daily basis, so you may need to guarantee that the report can complete overnight. The key to performance in a decision support system is properly tuned queries and proper use of indexes, clusters, and hashing. The parallel query option can also benefit decision support systems. The following topics are crucial in tuning a decision support system:

Scientific Applications

Scientific or statistical systems often perform complex calculations on large amounts of data. Often the data represents complicated datatypes, like latitude or pressure. These applications are characterized by diverse datatypes and sophisticated SQL calculations used to produce summary reports.

Figure 2 - 3 illustrates the interaction between a scientific application and an Oracle Server.

Figure 2 - 3. Scientific Applications

An example of a scientific or statistical system is a meteorological application that gathers data from weather satellites. The application performs complicated statistical analysis of the data to predict future weather patterns.

The key goals of scientific applications are accuracy and speed.

When you design a scientific or statistical system, you must ensure that complicated queries are not consuming all of the system resources. Properly tuning queries is the primary concern in these systems. The following topics are crucial in tuning a scientific or statistical system:


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