Be an Effective DBA using Oracle 10g Automatic Database Diagnostic Monitor

Edward HayrabedianSemantec Bulgaria OOD

Agenda

Oracle 10g and Oracle 9i Database Manageability Comparison Self-Managing Database Automatic Workload Repository (AWR)

Features Configuration Collection Process Database Statistics Metrics

Automatic Database Diagnostic Monitor (ADDM) Features Problems which can be detected Using ADDM

Drawbacks Test cases & Examples

Using literals instead of bind variables Concurrent updates

Oracle 10g and Oracle 9i Database Manageability Comparison How to compare?

A set of basic and typical DBA tasks are measured on a common set of metrics

Used typical DBA tasks A sample of 21 tasks covering all the key DBA functionality, grouped in 5 categories Each group of tasks has an associated weight value. It defines how much of the DBA

work it takes

What type of metrics? Time – the total time that a DBA spends in caring out the task Steps – the number of steps required to complete the task

Category WeightInstallation and Simple “Out-of-Box” Setup 13%

Day-to-Day Database Administration 27%

Backup & Recovery 6%

Performance Diagnostics & Tuning 34%Miscellaneous 20%

Oracle 10g and Oracle 9i Database Manageability Comparison Test Results – Task Time Comparison (minutes)

Installation and Simple

Setup

Day-to-Day Database

Administration

Backup & Recovery

Performance Diagnostics &

Tuning

Total

Oracle 9i 45 35 46 19 147

Oracle 10g 29 13 17 5 64

Oracle 10g Time Savings

36% 63% 63% 74% 56%

Weighting Factor

13% 27% 6% 34%

Weighted Time Saving

5% 17% 4% 25% 50%

Workday = 8 hr---------------------- 9i tasks = 163min10g tasks = 41min---------------------- Saving = 122 min

DBA need 50% less time to perform their function

Oracle 10g and Oracle 9i Database Manageability Comparison Test Results – Complexity Comparison (steps)

Installation and Simple “Out-of-Box”

Setup

Day-to-Day Database

Administration

Backup & Recovery

Performance Diagnostics &

Tuning

Total

Oracle 9i 7 15 19 15 56

Oracle 10g 4 9 6 5 24

Oracle 10g Step Savings

43% 40% 68% 67% 57%

Oracle 10g took 67% fewer steps to complete the performance diagnostics & tuning tasks

Self-Managing Database

Manual regular health checks, monitoring activities and bottleneck investigations are replaced by automatic statistics collection, storage and analysis

Introduction of the Advisory Framework Automatic Database Diagnostic Monitor (ADDM) SQL Tuning Advisor – automates the tuning of SQL statements and gives an advice

SQL Access Advisor – provides an expert advice on materialized vies, indexes and MV logs

Segment Advisor – responsible for space issues involving a database object. Analyzes the growth trends and shrink possibility for the segments

Undo Advisor - suggests parameter values and how much additional space will be needed to support flashback for a specified time. However, most of the undo tuning (like undo retention) is automatic in Oracle 10g

Redo Logfile size Advisor - determines the optimal smallest online redo log file size, based on the current fast_start_mttr_target setting and MTTR statistics

Automatic Shared Memory Tuning - no longer need to tune SGA individual memory pools. Only 2 memory parameters should be set and their values is recommended by ADDM

Automatic Workload Repository (AWR)Features

Automatic Workload Repository (AWR) – new persistent store, which

automatically collects and stores statistics

Called periodically at configured time interval More precise and granular information is collected

(compared to StatsPack snapshots) The statistics survive database reboots and crashes An efficient capture algorithm is used Provide historical analysis – no need to repeat the workload Completely self-managed The statistics are accessible to external users, who can

build their own performance monitoring tools

Automatic Workload Repository (AWR)Configuration

AWR can be managed either via: the Enterprise Manager, or PL/SQL API (dbms_workload_repository package)

Two of the most important procedures are: modify_snapshot_settings - defines the interval and

retention of snapshot generation create_snapshot – takes a new snapshot

Examples #1 and #2

Automatic Workload Repository (AWR)Collection Process

Collection Process – the new MMON BG process captures in-memory statistics from SGA and transfers them to the Workload repository

The statistic_level parameter - controls the number and type of statistics collected and stored (a dynamic init.ora parameter)

Basic – almost all advisors are turned off Typical - default All

Automatic Workload Repository (AWR)Database Statistics The better Oracle kernel is instrumented the better diagnosis –

developing a tool located inside the server allows to resolve hard to diagnose problems by adding more instrumentation

Increase to over of 700 wait events Easier high-level analysis based on grouping the wait events in the

following categories: Application Administration Commit Concurrency Configuration User I/O Network Communications Idle

Time model – Time is used as a common currency for comparing across modules. Most of the advisors report their findings in time

The new most important “db_time” statistics – The total time spent in db calls. The reduction of db_time can be used as a measure of the effectiveness of the tuning efforts

Automatic Workload Repository (AWR)Metrics

Metrics – delta values between the snapshots

Metrics are normalized by: Time Transaction SQL statement, and so on..

The rate of change is important rather than statistic’s absolute value

Alerting thresholds can be set based on 183 predefined metrics

User-defined metrics (alerts) can be created Examples #3 and #4

Automatic Database Diagnostic Monitor (ADDM) - Features ADDM is an advisory framework that provides expert recommendations

to improve DB performance Build into the 10g kernel Called periodically after each AWR run Findings are presented in a convenient fashion Reports the impact of each finding Recommendations and step-by-step instructions Using time as a common metric between components Focusing on the activities that the DB spends most db_time time, and

then drills down through a sophisticated problem classification tree to determine the root cause

Documents also the non-problem areas of the system

Automatic Database Diagnostic Monitor (ADDM) -

Problems which can be detected CPU bottlenecks Poor connection management Excessive parsing Lock contention IO capacity Under sizing of Oracle memory structures e.g. PGA, buffer cache,

log buffer High load SQL statements High PL/SQL and Java time High checkpoint load and cause e.g. small log files, aggressive

MTTR setting RAC specific issues

Automatic Database Diagnostic Monitor (ADDM) -

Using ADDM

Accessed either via Enterprise Manager or PL/SQL API (dbms_advisor package)

The main procedures of the dbms_advisor package Create_task Execute task – generates the report Get task report – gets the report text

Findings Recommendations

Drawbacks

The documentation is not complete and not enough

The web based Enterprise Manager is slow and buggy (I won’t comment the user interface design :)

It is not clear what type of problems won’t be detected

The ADDM and AWR are too new to be proved by the Oracle user community

Summary

Oracle makes a significant step to makes complicated things simple to manage

Give ADDM a try – there is nothing to lose and maybe something to earn

ADDM allows to do more for less time – just be effective

It is time to show some examples …

Examples

Test cases & Examples

Example #1 - Managing AWR via the EM Example #2 - Creating a snapshot via the PL/SQL API Example #3 - Manage Metrics in EM Example #4 - User-defined Metrics in EM

Test case #1 – Using Literals instead of bind variables Test case #2 – Concurrent updates

Example #1 - Managing AWR via EM

Movie #1 - Managing AWR via EM

Example #2 – Creating AWR Snapshot via the PL/SQL API

Movie #2 – Creating Snapshot via PL/SQL

Example #3 - Manage Metrics in EM

Movie #3 - Manage Metrics in EM

Example #4 - User-defined Metrics in EM

Movie #4 - User-defined Metrics in EM

Test case #1 – Using Literals instead of bind variablesWhat will be shown

The bad practice of using literals will be effectively detected by ADDM

The number of steps performed by a DBA in Oracle 10g is obviously less than in Oracle 9i

declarel_start_snapshot_id number;l_end_snapshot_id number;n number;

beginl_start_snapshot_id := dbms_workload_repository.create_snapshot();dbms_output.put_line('Start snapshot id : ' || to_char(l_start_snapshot_id));

--for i in 1..100000 loopn := dbms_random.random;execute immediate 'select ' || to_char(n) || ' from dual'

into n;end loop;

--l_end_snapshot_id := dbms_workload_repository.create_snapshot();dbms_output.put_line('End snapshot id : ' || to_char(l_end_snapshot_id));

end;

Test case #1 – Using Literals instead of bind variables

The code

Test case #1 – Using literals instead of bind variables

Movie #5

Test Case #2 – Concurrent Updates What will be shown

ADDM will catch a performance problem with application locks due to concurrent updates against one row

Reactive Performance Diagnostics

The Active Sessions graph – diagnosing the problem becomes ‘point and click’ !

ADDM recommendations and findings

Test Case #2 – Concurrent UpdatesThe code

Two sessions are concurrently running:

beginfor i in 1..300 loop

update t set x = i;dbms_lock.sleep(1);commit;

end loop;end;/

Test Case #2 – Concurrent UpdatesMovie #6 - Reactive tuning/monitoring

References

Oracle Database 10g and Oracle9 i Database Manageability Comparison February 2004 Copyright © 2004 Oracle Corporation

Oracle Database 10g New Features Oracle 10g Reference for Advanced Tuning & Administration by Mike Ault, Daniel Liu and Madhu Tumma

Oracle Database 10g: The Self-Managing Database An Oracle White Paper Nov. 2003

The Self-Managing Database: Automatic Performance Diagnosis An Oracle White Paper Nov. 2003