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Course Outline

Application Tuning Methodology

Database and Instance Architecture

  • Server processes
  • Memory structures (SGA, PGA)
  • Parsing and shared cursors
  • Data files, log files, and parameter files

Execution Plan Analysis

  • Hypothetical plans (EXPLAIN PLAN, SQL*Plus AutoTrace)
  • Actual execution plans (V$SQL_PLAN, TKPROF, AWR)

Performance Monitoring and Bottleneck Identification

  • Monitoring current instance status via data dictionary views
  • Monitoring historical data
  • Application tracing (SQL*Trace, TKPROF, TRACESESS)

Optimization Processes

  • Characteristics of cost-based optimization and its controls
  • Determining optimization strategies

Managing Cost-Based Optimization

  • Session and instance parameters
  • Hints
  • Query plan patterns

Statistics and Histograms

  • Impact of statistics and histograms on performance
  • Methods for collecting statistics and histograms
  • Strategies for collecting and estimating statistics
  • Statistics management: blocking, copying, editing, collection automation, and monitoring changes
  • Dynamic sampling (temporary tables, complex predicates)
  • Multi-column and expression-based statistics
  • System statistics

Logical and Physical Database Structure

  • Tablespaces
  • Segments
  • Extents
  • Blocks

Data Storage Methods

  • Physical aspects of tables
  • Temporary tables
  • Index-organized tables
  • External tables
  • Partitioned tables (range, list, hash, composite)
  • Physical table reorganization

Materialized Views and Query Rewrite Mechanisms

Data Indexing Methods

  • Creating B-TREE indexes
  • Index properties
  • Index types: unique, composite, function-based, reverse
  • Compressed indexes
  • Index rebuild and coalescing
  • Virtual indexes
  • Clustered and non-clustered indexes
  • Bitmap indexes and joins

Case Study: Full Table Scans

  • Impact of block size and storage on table-level performance
  • Conventional and direct-path data loading
  • Predicate ordering

Case Study: Index-Based Data Access

  • Index access methods (UNIQUE SCAN, RANGE SCAN, FULL SCAN, FAST FULL SCAN, MIN/MAX SCAN)
  • Utilizing function-based indexes
  • Index selectivity (Clustering Factor)
  • Composite indexes and SKIP SCAN
  • NULL values and indexes
  • Index-organized tables (IOT)
  • Impact of indexes on DML operations

Case Study: Sorting

  • Sort memory usage
  • Index sorting
  • Linguistic sorting
  • Effect of data distribution on sorting (Clustering Factor)

Case Study: Joins and Subqueries

  • Join methods: MERGE, HASH, NESTED LOOP
  • Joins in OLTP and OLAP systems
  • Join order determination
  • Outer Joins
  • Anti-Joins
  • Semi-Joins
  • Simple subqueries
  • Correlated subqueries
  • Views and WITH clauses

Other Cost-Based Optimizer Operations

  • Buffer Sort
  • INLIST ITERATOR
  • VIEW
  • FILTER
  • COUNT STOPKEY
  • Result Cache

Distributed Queries

  • Reading query plans involving dblink usage
  • Selecting the driving table

Parallel Processing

Requirements

  • Proficiency in SQL fundamentals and knowledge of the Oracle database environment (preferably after completing 'Native SQL for Programmers - Workshops' training)
  • Practical experience working with Oracle
 28 Hours

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