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 Duration 28 hours

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

Analysis of Command Execution Plans

  • Hypothetical plans (EXPLAIN PLAN, SQLPlus AutoTrac XPlane)
  • Actual execution plans (V$SQL_PLAN, XPlane, AWR)

Performance Monitoring and Bottleneck Identification

  • Monitoring real-time instance status via system dictionary views
  • Reviewing historical performance data
  • Application tracing (SQLTrace, TkProf, TreSess)

Optimization Process

  • Cost optimization properties and governance
  • Determining optimization requirements

Controlling the Cost-Based Optimizer Through:

  • Session and instance parameters
  • Hints
  • Query plan patterns

Statistics and Histograms

  • The impact of statistics and histograms on performance
  • Methods for collecting statistics and histograms
  • Strategies for counting and estimating statistics
  • Statistics management: blocking, copying, editing, automated collection, and change monitoring
  • Dynamic data sampling (temporary tables, complex predicates)
  • Multi-column statistics and expression-based statistics
  • System statistics

Logical and Physical Database Structure

  • Tablespaces
  • Segments
  • Extensions (EXTENTS)
  • Blocks

Data Storage Methods

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

Materialized Views and QUERY REWRITE Mechanisms

Data Indexing Techniques

  • Constructing B-Tree indexes
  • Index characteristics
  • Index types: unique, multi-column, functional, and reverse-key
  • Index compression
  • Index rebuilding and coalescing
  • Virtual indexes
  • Private and public synonyms for indexes
  • Bitmap indexes and bitmap joins

Case Study – Full Data Scans

  • The effect of table and block-level placement on read performance
  • Conventional vs. direct-path data loading
  • Predicate ordering

Case Study – Index-Based Data Access

  • Index read methods (UNIQUE SCAN, RANGE SCAN, FULL SCAN, FAST FULL SCAN, MIN/MAX SCAN)
  • Utilizing functional indexes
  • Index selectivity (Clustering Factor)
  • Multi-column indexes and SKIP SCAN
  • Handling NULL values in indexes
  • Index-Organized Tables (IOT)
  • Impact of indexes on DML operations

Case Study – Sorting

  • In-memory sorting
  • Index sorting
  • Linguistic sorting
  • The impact of entropy on sorting (Clustering Factor)

Case Study – Joins and Subqueries

  • Join algorithms: MERGE, HASH, NESTED LOOP
  • Joins in OLTP and OLAP environments
  • Switching order optimization
  • Outer joins
  • Anti-joins
  • Semi-joins (incomplete joins)
  • Simple subqueries
  • Correlated subqueries
  • Views and the WITH clause

Other Cost-Based Optimizer Operations

  • Buffer Sort
  • INLIST ITERATOR
  • VIEW operations
  • FILTER operations
  • Count Stop Key
  • Result Cache

Distributed Queries

  • Reading query plans involving DB Links
  • Selecting leading tables

Parallel Processing

Requirements

  • Proficiency in basic SQL concepts and a solid understanding of the Oracle database environment (completion of the 'Native SQL for Programmers' workshop on Oracle 11g is recommended)
  • Hands-on practical experience working with Oracle databases

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