Download SQL Performance Analyzer: Testing the Impact of System

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Oracle 11g Real Application Testing: Avoiding Performance
Regressions with SQL Performance Analyzer
Khaled Yagoub, Pete Belknap, Benoit Dageville, Karl Dias
Database Manageability Group
Presentation Outline
• SQL Performance Analyzer Overview
• Common Usage Scenarios
• Workflow Phases
• SQL Performance Analyzer Interface
• Enterprise Manager
• Command Line
• Q/A
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SQL Performance Analyzer: Overview
SQL Workload
(SQL text + binds)
SQL plans + stats
Pre-change
Compare
SQL Performance
Analysis Report
•
Helps users predict the impact of
system changes on SQL workload
response time
•
Builds different versions of SQL
workload performance (i.e., SQL
execution plans and statistics)
•
Analyzes performance differences
•
Offers fine-grained performance
analysis on individual SQL
•
Integrated with SQL tuning set,
SQL plan baselines, and SQL
tuning advisor to form an End-toend solution
SQL plans + stats
Post-change
Common Usage Scenarios
•
•
•
•
•
•
Database upgrades and patches
Database parameter changes
Schema changes
Statistics gathering
Implementation of tuning recommendations
OS/hardware changes
SQL Performance Analyzer: Workflow
Production
Test
Make Change
Steps
(1)
Capture
SQL (STS)
(2)
(3)
Transport
STS
(6)
(4)
Execute SQL
Pre-change
(5)
Execute SQL Compare
Post-change Perf.
Reiterate
No
Done?
(7)
Production Change /
(7)
Tuning Deployment
Yes
Tuned System
Step 1: Capture SQL Workload
•
SQL Tuning Set (STS) used to store &
manage SQL workload
•
STS includes complete execution
context
Cursor Cache
Incremental Capture
SQL Tuning Set
Production Database
•
SQL Text, bind variables, parsing schema
•
Execution plans and run-time statistics
•
Number of executions
•
STS can be built from AWR, Cursor
Cache, user workload and existing STS
•
Incremental capture used to populate
STS from cursor cache over a time
period
•
Negligible performance overhead (<2 %)
•
Filtering and ranking capabilities filters
out undesirable SQL
Step 2: Move SQL Workload to Test System
Test
Production
Cursor Cache
SQL Tuning Set
•
•
•
•
Export/Import
SQL Tuning Set
Test system should resemble production (stats… )
Copy SQL tuning set to staging table (“pack”)
Transport staging table to test system (datapump, db link, etc.)
Copy SQL tuning set from staging table (“unpack”)
Step 3: Execute SQL Before Making Change
•
Establishes SQL workload performance
baseline before change
•
Each SQL “test-executed” once in
isolation with production context
•
SQL Trial: SQL execution plans and
run-time statistics captured
Test Execute
•
DDL skipped
Execution Plan &
Statistics
•
Only query part of DML is executed
•
Customizable global and per-SQL time
limit to handle long running/run-away
SQL
•
Option to do Explain Plan only analysis
•
Remote test-execute using database
link (on 10.2 and up)
SQL Tuning Set
Fetch Next SQL
Save Result
SQL Performance Analyzer
Step 4: Execute SQL After Making Change
SQL Tuning Set
•
Manually implement the planned change
• Database upgrade, patches
• Optimizer statistics refresh
• Schema changes
• Database parameter changes
• Validate tuning actions, e.g., SQL Profile
creation, Partitioning, etc.
• Hardware changes, e.g., Enabling direct
IO, File System to ASM conversion, etc.
•
Re-execute SQL after change
• Gathers new SQL execution plans and
run-time statistics (SQL Trial)
Fetch Next SQL
Test Execute
Execution Plan &
Statistics
Save Result
Completed
SQL Performance Analyzer
Step 5: Compare & Analyze Performance
Completed
Completed
•
•
Compare
SQL Performance
•
• Buffer Gets
• CPU Time
• Elapsed Time
• Optimizer Cost
Weigh SQL using original number of
executions
SPA Report shows change impact
on both workload, individual
SQL
•
•
•
•
Analysis Report
•
SQL Performance Analyzer
Compare performance using
different metrics, e.g.,
Improved SQL
Regressed SQL
Unchanged SQL
SQL with plan changes
Fix regressed SQL using SQL
Tuning Advisor or SQL Plan
Baselines
SQL Performance Analyzer Report
3
2
1
4
SQL Performance Analyzer Report
Regressed SQL Statements
Step 6: Reiterate
Regression Remediation
Two recommended solutions
to fix regressed SQL:
• Create SQL Plan Baselines: Helps
revert to previous stable plans
• SQL Tuning Advisor: Helps
explore better execution plans
Step 6: Reiterate
Report before using Plan Baselines
2
1
Step 6: Reiterate
Report after using Plan Baselines
Change Accepted
No Regressions after SPM fix
2
1
Step 7: Production Change & Tuning
Deployment
• Implement validated changes permanently on
production
• Transport any tuning solution to production
•
•
•
•
•
Export/Import SQL Plan Baselines
Export/Import SQL Profiles
Make schema changes
Gather new optimizer statistics
Change parameter values
Enterprise Manager Interface
SQL Performance Analyzer Home Page
Enterprise Manager Interface
Guided Workflow
Enterprise Manager Interface
Parameter Change Workflow
Parameter Changes
SPA Report
1
2
Parameter Changes
SQL Tuning Advisor Recommendations
Parameter Changes
SPA Report After Profiles Implemented
Change Accepted
1
Command Line Interface
dbms_sqlpa PL/SQL Package
-- create an empty sql tuning set
exec dbms_sqltune.create_sqlset(‘my_sts’);
-- incrementally capture sql from the sql cache
exec dbms_sqltune.capture_cursor_cache_sqlset( sqlset_name => 'my_sts', time_limit => 24*60*60, repeat_interval => 5*60);
-- create an analysis task
Var tname varchar2(30);
exec :tname := dbms_sqlpa.create_analysis_task(sqlset_name => ‘my_sts’ –
task_name => ‘my_task’);
Command Line Interface
dbms_sqlpa PL/SQL Package
-- before change execution
exec dbms_sqlpa.execute_analysis_task(:tname, execution_type=>'test execute');
-- make your change here
-- alter session set …
-- after change execution
exec dbms_sqlpa.execute_analysis_task(:tname,
-
execution_type=>'test execute');
-- compare the before and after execution using buffer_gets
exec dbms_sqlpa.set_analysis_task_parameter(:tname, -
'comparison_metric', 'buffer_gets');
exec dbms_sqlpa.execute_analysis_task(task_name => :tname, execution_type=>'compare performance');
Command Line Interface
dbms_sqlpa PL/SQL Package
Projected Workload Change Impact:
------------------------------------------Overall Impact
: 49.18%
Improvement Impact : 61.48%
Regression Impact
: -12.3%
SQL Statement Count
------------------------------------------SQL Category SQL Count Plan Change Count
Overall
12
9
Improved
1
1
Regressed
3
3
Unchanged
8
5
SQL Statements Sorted by their Absolute Value of Change Impact on the Workload
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
| Impact on | Metric | Metric | Impact
| % Workload | % Workload | Plan
|
| object_id | sql_id
| Workload | Before | After | on SQL
| Before
| After
| Change |
--------------------------------------------------------------------------------------------------------|
26 | 8answpy3djcj5 |
61.48% |
67 |
7 |
89.55% |
68.65% |
14.11% | y
|
|
29 | gcfysssf6hykh |
-4.1% |
3 |
7 | -133.33% |
3.07% |
14.11% | y
|
|
30 | 8yyjua0yhcc92 |
-4.1% |
3 |
7 | -133.33% |
3.07% |
14.11% | y
|
|
32 | 0782mpfq27aq5 |
-4.1% |
3 |
7 | -133.33% |
3.07% |
14.11% | y
|
---------------------------------------------------------------------------------------------------------
SQL Performance Analyzer
Data Dictionary Views
• Modified views in Oracle Database 11g:
• DBA{USER}_ADVISOR_TASKS:details about the advisor task
• DBA{USER}_ADVISOR_FINDINGS:analysis findings
• New views in Oracle Database 11g:
• DBA{USER}_ADVISOR_EXECUTIONS:metadata information for
a task execution
• DBA{USER}_ADVISOR_SQLPLANS: SQL execution plans
• DBA{USER}_ADVISOR_SQLSTATS: SQL compilation and
execution statistics
Summary
• Enables identification of SQL performance changes (e.g.,
regressions) before end-users can be impacted
• Helps with any change that impacts SQL execution plans (e.g., DB
upgrades, Optimizer statistics refresh, schema changes, etc.)
• Automates SQL performance tracking of hundreds of thousands of
SQL statements – impossible to do manually
• Prevents side effects to database content when executing SQL.
• Keeps history of all experiments performed on SQL workloads.
• Integrated with SQL Tuning Advisor and SQL Plan Baselines for
regression remediation
• GUI provides predefined workflows for Database upgrades and
parameter changes
SQL Performance Analyzer
In-house Testing
• SQL Performance Regression Bugs
• Errors + performance degradations caused by code changes
• SQL tuning set with 500K SQL statements
• Nightly runs
• SQL Plan Management
• Failures in reproducing execution plans
• Partitioning Advisor
• Verify partition recommendations
• SQL Tuning Advisor
• SQL Profiles, index recommendations
• SQL Repair Advisor
Real Application Testing: Tools of the Trade
SQL Performance Analyzer
Database Replay
What is it?
• Predicts SQL performance deviations
before end-users can be impacted
• Replays real database workload
on test system
What Purpose?
• Assess impact of change on SQL
response time
• Assess impact of change on
workload throughput
How it works?
• Executes each SQL, stored in SQL
Tuning Set, in isolation using
production context and then
compares before and after execution
plans and run-time statistics
• Captures workloads and replays it
with production context including
concurrency, synchronization
& dependencies
When to use?
• Unit testing of SQL with the goal to
identify the set of SQL statements
with improved/regressed performance
• Comprehensive testing of all
sub-systems of the database
server using real production
workload
SQL Performance Analyzer and Database Replay are complimentary