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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

Analysis of Command Execution Plans

  • Explanatory plans (EXPLAIN PLAN, SQLPlus AutoTrace, XPlan)
  • Actual execution plans (V$SQL_PLAN, XPlan, AWR)

Performance Monitoring and Bottleneck Identification

  • Monitoring current instance status via system dictionary views
  • Reviewing historical dictionary data
  • Application tracing tools (SQLTrace, TkProf, Tresess)

Optimization Processes

  • Understanding cost optimization properties and controls
  • Methods for determining optimization paths

Controlling the Cost-Based Optimizer

  • Session and instance parameters
  • Use of optimizer 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: locking, copying, editing, automating collection, and monitoring changes
  • Dynamic data sampling (temporary tables, complex predicates)
  • Multi-column and expression-based statistics
  • System-level statistics

Logical and Physical Database Structure

  • Tablespaces
  • Segments
  • Extensions (EXTENTS)
  • Blocks

Data Storage Methods

  • Physical characteristics of tables
  • Temporary tables
  • Index-organized tables
  • External tables
  • Table partitioning (range, list, hash, composite)
  • Physical table reorganization

Materialized Views and Query Rewrite Mechanisms

Data Indexing Techniques

  • Creating B-TREE indexes
  • Index properties
  • Index types: unique, multi-column, function-based, and reverse-key
  • Index compression
  • Rebuilding and coalescing indexes
  • Virtual indexes
  • Private and public indexes
  • Bitmap indexes and bitmap joins

Case Study: Full Table Scans

  • Impact of table and block level placement on read performance
  • Conventional vs. direct path data loading
  • Predicate ordering effects

Case Study: Index-Based Data Access

  • Index read methods (UNIQUE SCAN, RANGE SCAN, FULL SCAN, FAST FULL SCAN, MIN/MAX SCAN)
  • Utilizing function-based indexes
  • Index selectivity and 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 Operations

  • Memory-based sorting
  • Index-assisted sorting
  • Linguistic sorting
  • Effect of entropy on sorting (Clustering Factor)

Case Study: Joins and Subqueries

  • Join algorithms: MERGE, HASH, and NESTED LOOP
  • Joins in OLTP vs. OLAP environments
  • Join ordering
  • Outer Joins
  • Anti-joins
  • Semi-joins
  • Simple subqueries
  • Correlated subqueries
  • Views and the WITH clause

Other Cost-Based Optimizer Operations

  • Buffer Sort
  • INLIST iterators
  • View access
  • FILTER operations
  • Count Stop Key
  • Result Cache

Distributed Queries

  • Analyzing query plans involving DBLinks
  • Selecting leading tables in distributed queries

Parallel Processing

Requirements

  • Proficiency in basic SQL and a solid understanding of the Oracle database environment (completion of 'Native SQL for Programmers' or similar training on Oracle 11g is recommended).
  • Hands-on practical experience working with Oracle.
 28 Hours

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