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Oracle Performance Tuning

The Oracle database offers a host of tuning opportunities. Tuning can happen during system analysis, logical design, physical design, application design, and at virtually every stage of the database development life cycle. This module will discuss the importance of Oracle tuning and explain how the Oracle components are laid out and why tuning is absolutely required for all Oracle databases.
We will also discuss the great importance of tuning during the development process. No amount of tuning can remedy a poorly designed table structure. By the end of this module, you should be able to:
  1. Describe the layout of the Oracle components
  2. Describe how database design effects performance
  3. Contrast third normal form and de-normalized design
  4. Describe the characteristics of a high-performing database
  5. Identify Oracle physical components that effect performance
  6. Identify five Oracle components that can be tuned
  7. Identify the metrics of Oracle performance

Database Systems

Oracle DBMS

Remember, Oracle is one of the world's most complex database management systems, and it comes with a bewildering number of tuning options. As we go through this course, do not be too concerned if you do not feel comfortable with all of the new concepts. I promise that we will revisit all topics that are important. We will start with a review of the Oracle architecture with a focus on tuning.

How does Database Design effect Performance

The design of a database can have a significant impact on its performance. A well-designed database can be faster and more efficient, while a poorly designed database can be slow and cumbersome. There are several factors that can affect database performance, including:
  1. Table design: The way that tables are designed and structured can affect performance. For example, using the appropriate data types and choosing the right primary keys can help to improve performance.
  2. Indexing: Indexes can improve the performance of SELECT, INSERT, UPDATE, and DELETE statements by enabling faster data retrieval. However, too many indexes can slow down writes and consume additional storage space.
  3. Normalization: Normalizing a database can help to reduce redundancy and improve performance by breaking data into smaller, more manageable pieces. However, normalization can also make it more difficult to retrieve data, as it may require more JOINs to combine data from multiple tables.
  4. Partitioning: Partitioning a large table can improve the performance of SELECT statements by allowing the database to access only the data it needs. However, partitioning can also make it more complex to manage the data and can impact the performance of other types of statements.
  5. Query optimization: The way that queries are written can also have an impact on performance. Using efficient JOIN types and writing queries that take advantage of indexes can improve performance.
  6. Hardware and configuration: The hardware and configuration of the database server can also affect performance. For example, using faster CPUs, more memory, or faster storage can improve the performance of a database.