Oracle Database Performance Tuning - Fundamentals

Explore performance management and performance engineering meeting expectations via service level agreements. Adopt a whole brain approach that blends science and art, logic and creativity to get the performance benefit.

Master performance by learning to ride a bike: practice builds skill, balance, and ease, while perseverance and continuous learning help you tackle challenges in managing performance.

Discover that there is no universal fix for performance issues; success depends on the specific database situation and a situational approach to performance tuning.

Learn practical Oracle database performance tuning fundamentals through driving analogies that link basic administration, performance management, and optimization to real-world problem solving.

Deliver an intro to performance engineering as a software discipline, showing how to design, build, deploy, and test systems with nonfunctional requirements like concurrent users, data volume, and workload modeling.

Identify the root cause of performance issues by diagnosing symptoms, collecting data, and reproducing problems to guide targeted tuning decisions.

Define performance management as allocating resources to prioritize high priority transactions over low priority ones during heavy workloads, focusing on managing performance rather than tuning.

Assess whether performance outcomes arise from design decisions or luck by prioritizing performance engineering and nonfunctional requirements before building, testing, and deploying in production.

Explore how memory, IO, and disk are used efficiently; use bind variables and prepared statements to reduce parsing and shared pool churn, and prefer index lookups over full scans.

optimize database performance by enforcing solid connection management, avoiding costly connect and disconnect cycles during peak load, and writing clean sql that prevents cartesian joins and unnecessary function calls.

Understand sql response time by separating execution time into cpu processing and wait time; analyze wait events, locks, memory delays, and target tuning to reduce both components.

Understand db time as the sum of all work the database performs during the elapsed period, excluding idle time, and use cpu and wait to gauge how busy it is.

Compare dictionary and locally managed tablespaces, extents and contention, and manual versus automatic segment space management, including high watermark, free lists, and PCD/BCT concepts for inserts and updates.

Explore how an 8 kb block size and 1 kb rows with varying percent free space (50% vs 0%) to accommodate updates affect blocks, buffer cache, and IO.

Assess your workload, whether transaction processing or data analytics, and choose a block size that maximizes concurrency and minimizes waits; benchmark sizes to balance rows per block, IO, and slots.

Identify the root causes of database slowdowns using the automatic workload repository (AWR), diagnostic data, and performance metrics from dynamic performance views and snapshots.

An AWR report compares metrics from two close snapshots to reveal what happened in a chosen time window, using the same instance and short snapshot intervals.

Explore Oracle database performance tuning through case studies that teach troubleshooting, out-of-the-box thinking, and identifying performance problems, from slow applications to hardware and resource considerations.

Explore storage techniques in Oracle database, including heap tables, partitioning and pruning, local vs global indexes, index organized tables, clustering, and materialized views, and their impact on query performance.