Oracle Database Performance Tuning

Prepare a Linux Oracle VirtualBox appliance for practice by using a pre-built VM or creating from scratch, install guest additions, and configure bridged networking and hosts file.

Prepare the practice environment by creating an Oracle VirtualBox appliance rv1, installing the Oracle database and idb, installing swingbench, configuring snapshots, and adding the stress rpm.

Configure putty, save V1, set keep-alive to nine seconds, create the staging directory for VM host file exchange, then install Oracle software from the staging folder.

Use the DBCA utility to create a non-container database, configure the listener, set PGA sizes, set the same password for system users, and prepare tnsnames.ora with the server IP.

Prepare and populate the course schema for Oracle database performance tuning by importing a data pump dump, configuring staging scripts, and verifying created objects.

Install and configure the swing bench benchmarking tool, connect to the SOTU schema, create ATP and warehouse workload configs, test the connection, and save benchmarks.

Install and use the stress tool to simulate Linux load, configuring CPU, memory, I/O, and disk resources. Create and delete VirtualBox snapshots to roll back appliance, maintaining a production environment.

Explore the core areas of Oracle database performance tuning, focusing on tuning tools and instance tuning, and identify performance issue attributes like scope, permanence, reproducibility, and errors.

Explore Oracle's performance tuning methodology, from setting targets and gathering symptoms to testing solutions with database replay, using Oracle performance tools to diagnose and resolve issues.

Describe Oracle database performance unique areas and performance issue attributes, learn the performance methodology, and model a typical system workload with peak and normal hours.

Examine how server hardware and application layers affect Oracle database performance, including CPU, memory, storage, and network resources, monitoring utilization, and reducing IO contention with efficient queries.

Examine the IT systems technology stack, identify where performance bottlenecks arise from the database to the application, measure performance, and tune the database layer to meet design-level goals.

Explore Oracle database performance tuning tools—performance views, data dictionary views, the automatic database diagnostic monitor, AWR, and Oracle Enterprise Manager—to guide tuning with statistics_level values basic, typical, or all.

Explore time model 1 of 3 in Oracle database performance tuning, detailing db time, ideal waiting events, and how db wait time and execution relate to performance.

Explore the time model to understand database workload through db time, dp time, and wait times in a hierarchical, microsecond view. Use it to measure performance and gauge change impact.

Explore the time model's hierarchical structure, differentiate foreground db time from background elapsed time, and compute total wait time by subtraction, with hourly snapshot and awr reports for scalability.

Prepare your environment by downloading and deploying the scripts. Run time model 1 to measure database time, wait time, and operation-type percentages that reveal where the database spends its time.

Practice 2 demonstrates how escalating workload affects the time model, using swing bench benchmarks, snapshots, and a history table to track DCP and wait time across load levels.

Explore two types of statistics views—instance activity statistics and segment statistics—to describe and query database operations and wait times, using views that expose statistics names and values.

Learn how Oracle instance activity statistics are classified into eight classes, with statistics belonging to multiple classes, such as 8 and 64. Use wr reports to compare stats with baselines.

Investigate Oracle database performance bottlenecks by examining wait events and using event views to identify what resources are waited on and the root causes behind them.

Learn how Oracle wait events are classified into weight classes, and how to retrieve and interpret with event statistics at instance, session, and service levels to analyze performance.

Learn to read Oracle wait events from current sessions, interpret state and wait times, and identify common events like buffer busy weights, db file sequential read, and library cache waits.

Practice 3 guides you to view instance activity and wait events, retrieve system and session statistics, and use the AWR comparison report to study changes in statistics over time.

Practice 3: view instance activity and wait events to tune oracle database performance by querying views, displaying wait time by event class, and interpreting session logs.

Explore instance activity and wait events to troubleshoot Oracle performance, using client sessions and lock contention scenarios to observe wait times and interpret with event parameters.

Explore how the Oracle AWR uses hourly snapshots managed by the manageability monitor to detect performance issues and support AWR reports and AWR comparison reports.

Manage AWR snapshots by configuring purging policy, enabling captures, and setting retention and frequency to balance space with performance diagnostics; note required licenses and the basic versus cubical statistics levels.

Learn to manage AWR snapshots using the work load repository, configuring interval, retention, and top N settings, with practical guidelines for matching workload cycles.

Learn to manage AWR snapshots by creating and deleting snapshots, selecting lightweight, regular, or heavyweight modes, and assessing disk space needs.

Manage automatic workload repository (AWR) settings, adjust statistics level to typical or all, modify the AWR interval, and create or delete AWR snapshots while reviewing existing snapshots.

Explore how to view and manage space used by AWR snapshots and optimizer backup statistics, adjust retention periods, and predict growth to reduce storage in Oracle database performance tuning.

Learn to generate and use AWR reports to diagnose performance issues, develop a strategy for reading AWR reports, and retrieve performance history for a specific SQL statement.

Learn a practical strategy for interpreting AWR reports to identify bottlenecks, set performance targets, baseline healthy system performance, and iteratively tune Oracle database performance.

Explore how to read Oracle's AWR reports to diagnose database performance issues. Identify top wait events, workload sections, and memory and CPU metrics to guide targeted optimizations.

Analyze AWR reports by examining efficiency percentages, data blocks in the farkash, library hit percent, and CPU versus pass times to diagnose contention and performance issues.

Identify top foreground events by total wait time in the AWR report to spot performance bottlenecks and interpret weight classes such as log file sync and commit.

Explore how AWR reports 6 of 9 reveal host and instance cbo usage, time values, operating system statistics, and ratio of total cbo time to busy time for performance diagnosis.

Explore the main AWR report sections, examine wait events and time model statistics, and use the weight events histogram to see how wait time distributes across statements.

Explore how AWR reports reveal execution plans and performance history, compare plans, and link snapshots to diagnose performance fluctuations of statements in Oracle databases.

Learn to use AWR reports to diagnose performance issues, including reading strategy, AWR auto reports, and the AWR comparison report, with Oracle reference documentation and the troubleshooting assistant.

Learn to generate and interpret AWR comparison reports to troubleshoot Oracle database performance bottlenecks by pairing issue and steady state snapshots and using scripts.

Generate and analyze AWR reports from normal application workload and issue periods by creating two snapshots and producing a report, then interpret DB time versus elapsed time to diagnose performance.

Analyze AWR reports to interpret load profile and DB time per second, note log file sync as the dominant wait event, and review instance efficiency and commit class.

Analyze AWR reports for a warehouse workload using snapshots and benchmarks to identify contention, DP time differences, wait metrics, and maintenance window impact.

Simulate a 10-minute stress to trigger a performance issue, capture AWR snapshots, compare issue versus baseline reports, and read the AWR header to assess CPU time and host activity.

Learn to use AWR reports to diagnose a performance issue from a code change, comparing old and new snapshots to identify the db time drivers.

Master reading AWR comparison reports to diagnose bottlenecks by comparing pairs, generating snapshot ideas, and labeling reports; identify CPU load and host configuration differences during steady-state execution.

Explore using AWR SQL reports to analyze a specific statement's performance history, comparing multiple execution plans across many sessions and the most recent three snapshots.

Explore managing AWR baselines to preserve snapshots beyond the retention period, including static and moving window baselines, creation and expiry, and using baselines for performance tuning.

Learn how to manage AWR baseline templates, including single and repeating templates, to schedule baselines with start and end times, expiration, and weekday-based recurrence.

Learn to create single and repeating AWR baseline templates, understand duration constraints and activation, query baseline data via the dba_hist_baseline_template view, and consider automating baselines with a job.

Create and manage AWR baselines and templates to capture snapshots from chosen windows; note that baseline templates are not reliable, so consider a scheduled job for baselines instead.

Explore metrics and event history in Oracle database tuning. Describe metrics, identify metric views and their update frequencies, and use AWR snapshots to trace changes in statistics.

Learn to interpret metrics and event histograms to distinguish normal application load from IO bottlenecks by examining time-bucket wait distributions and histogram data in reports.

learn to configure server generated alerts in Oracle database by setting threshold values for key metrics, understanding warning and critical levels, and managing alerts with Oracle Enterprise Manager.

Explore server-generated alerts for Oracle databases, including threshold concepts, default 85% warming and 97% critical for tablespaces, and how to retrieve thresholds via a procedure or dba_thresholds.

practice demonstrates configuring a database to generate alerts when the wait time percent exceeds normal values and shows measuring this metric with AWR reports and system metrics.

Configure server-generated alerts to monitor wait percent thresholds, with warning at 70% and critical at 90%, and validate alerts through test runs and threshold views.

Adaptive thresholds automatically adjust to workload trends using a system moving window baseline to set warming and critical alerts, while time-based and static thresholds offer alternatives.