Oracle Database 10g: SQL Tuning Workshop

This course is designed to give the experienced SQL Developer or DBA a firm foundation in SQL tuning techniques. The participant learns the necessary knowledge and skills to effectively tune SQL in the Oracle Database 10g Release 1. They learn about tuning methodology as well proactive tuning and reactive tuning methods. Students are introduced to the benefits of the new automatic tuning mechanisms available in Oracle Database 10g. On completion of the course they are able to compare and contrast the steps involved to tune manually as in prior releases as well as use the automatic SQL tuning features provided in the current release. Students gain a thorough conceptual understanding of the Oracle Optimizer, and reinforce instructor-led learning with structured hands-on practices. The course uses a series of challenge-level workshops, allowing students to "play, discover, and learn" at their own level and pace. The students learn to use the Oracle diagnostic tools and facilities: Automatic SQL Tuning components, EXPLAIN, SQL Trace and TKPROF, SQL*Plus AUTOTRACE. Students also learn to influence the behavior of the Optimizer by changing the physical schema and modifying SQL statement syntax.

This course counts towards the Hands-on course requirement for the Oracle Database 10g Administrator Certification. Only instructor-led inclass or instructor-led online formats of this course will meet the Certification Hands-on Requirement. Self Study CD-Rom and Knowledge Center courses are excellent study and reference tools but DO NOT meet the Hands-on Requirement for certification.

Audience:

• Technisch consultant
• Applicatie Ontwikkelaar met PL/SQL
• Applicatie Ontwikkelaar met Java

Course Objectives:

• Describe the basic steps in processing SQL statements
• Describe the causes of performance problems
• Understand where SQL tuning fits in an overall tuning methodology
• Describe Automatic SQL Tuning
• Use the diagnostic tools to gather information about SQL statement processing
• Understand Optimizer behavior
• Influence the optimizer behavior
• Influence the physical data model so as to avoid performance problems