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Published byWinifred Shaw Modified over 9 years ago
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Simplified SQL Performance Management in Oracle Database 11g
Pete Belknap
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The following is intended to outline our general product direction
The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.
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Agenda SQL Tuning Challenges Oracle Database 11g Solutions Q & A
Automatic SQL Tuning Improvements to SQL Tuning Advisor Fully automating SQL tuning Real-time SQL Monitoring Track high response-time SQL Find the most expensive plan operation Q & A
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SQL Tuning Challenges Oracle Database 10g introduced SQL advisors to simplify application and SQL tuning Remaining challenges SQL Tuning still reactive Painful to find and investigate long-running SQL Oracle Database 11g solutions Automatic SQL Tuning Real-time SQL Monitoring
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<Insert Picture Here>
Automatic SQL Tuning <Insert Picture Here> The Self-Managing Database
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Challenges of Manual SQL Tuning
Requires expertise in several domains SQL optimization: adjust the execution plan Access design: provide fast data access SQL design: use appropriate SQL constructs Time consuming Plans are complicated Each SQL statement is unique and each execution can be different Potentially large number of statements to tune Testing proposed changes is labor-intensive Many possible ways to a solution Never ending task SQL workload always evolving Plan regressions
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Simplifying SQL Tuning SQL Tuning Advisor, since Oracle Database 10g
Recommendations Automatic Tuning Optimizer SQL Tuning Advisor Statistics Analysis Gather Missing or Stale Statistics SQL Profiling Create a SQL Profile DBA Access Path Analysis Add Missing Indexes SQL Structure Analysis Modify SQL Constructs
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SQL Profiling Technology Transparent SQL tuning
No SQL Profile SQL Profiling Use SQL Profile (future executions) SQL Profile use ? ? ? Plan 3 Plan 2 Plan 1 Search Space add ? ? ? ? ? Plan 3 ? Search Space Plan 3 Plan 1 Plan 2 Plan 1 Plan 2 Validates estimates using dynamic sampling and partial execution Validates only relevant estimates
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SQL Profiling Technology (2) Trying alternative plans (new in 11g)
Profile Selection (3) (1) Estimate Correction Correction Factors Alternative Plan Analysis Corrections + O_F_E Corrections + O_F_E (2) Corrections + O_F_E 8.1.7 Alternate Plan Set Try some interesting alternatives: plans from old releases Feed correction factors into alternative plan selection But which is the best?
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Testing SQL Profiles (1) Measuring actual benefit with test-execution (new in 11g)
Naïve: Execute in Order P1 P2 Finish, P2 wins! But what if P1 never completes? Timeout! P1 It would be great to run them concurrently…. P1 P2 P2 wins, kill P1! But then I take 2 CPUs, and N in the general case…
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Testing SQL Profiles (2) Measuring actual benefit with test-execution
Solution: Tournament Execution P1 P2 Round 1: 15 sec P1 P2 Round 2: 30 sec 16 sec Your winner, with a knockout in the second round, P2!
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Testing SQL Profiles (3) Choosing appropriate metrics, comparison strategy
“Winner” and “Loser” depends on your point of view Need a statistic that is repeatable and comprehensive. ELAPSED_TIME: comprehensive, but includes row lock waits; I/O time depends on buffer cache state. Not repeatable. CPU_TIME: very repeatable, but not comprehensive for I/O. BUFFER_GETS: very repeatable, but ignores CPU expense; overly pessimistic for some plans Combine the best elements of each CPU_TIME should improve (most reliable statistic) Benefit Reported: ratio of CPU_TIME + BUFFER_GETS*10ms Conservatively consider every buffer get to be an I/O, but allow large CPU improvements to overrule small buffer gets regressions
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Improvements in Oracle Database 11g Better SQL Profiling
SQL Tuning Recommendations Automatic Tuning Optimizer SQL Tuning Advisor Gather Missing or Stale Statistics Statistics Analysis SQL Profiling Create a SQL Profile show verified benefit Fix potential regression after upgrade Verify benefit through test-execution DBA Access Path Analysis Add Missing Indexes SQL Structure Analysis Modify SQL Constructs
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Agenda SQL Tuning Challenges Oracle Database 11g Solutions Q & A
Automatic SQL Tuning Improvements to SQL Tuning Advisor Fully automating SQL tuning Real-time SQL Monitoring Track high response-time SQL Find the most expensive plan operation Q & A
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SQL Tuning in Oracle Database 10g End-to-end Workflow
Evaluate Recommendations DBA Implement DBA Workload Generate Recommendations SQL Tuning Advisor SQL Tuning Candidates DBA Invoke Advisor ADDM one hour AWR A good end-to-end solution, but manual intervention is required
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Improvements in Oracle Database 11g Fully-Automated Tuning Workflow
Implement SQL Profiles Test SQL Profiles Workload Generate Recommendations SQL Tuning Candidates Choose Candidate SQL one week AWR It’s Automatic! DBA View Reports / Control Process
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Picking Candidate SQL (1)
S4, 1 minute Week’s Top SQL, Ordered by DB Time S3, 5 minutes S2, 8 minutes S1, 10 minutes I could just pick from the top down… AWR But I will miss SQLs with important hotspots! AWR Average Exec Hourly Daily Weekly Let’s try a more balanced approach: OK, but where do I start?
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Picking Candidate SQL (2)
AWR Weekly Average Exec Daily Hourly Candidate List 20% 10% 65% 5% Eventually we need one list to tune from: merge the buckets. All buckets are not created equal: focus on the week, but don’t forget about the others. Focus on the SQLs we have not seen recently: Don’t re-tune SQLs if nothing has changed!
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Tuning Flow Tuning activities per SQL
Candidate SQLs Store reporting data Fetch next SQL Accept Profile Tune SQL If < 3X benefit, recommend for DBA consideration Fix potential regressions Look for indexes, statistics, as with standard tuning Require 3X benefit Both CPU and I/O times must improve Evaluate Profile Tournament competition
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Focus on SQL Profiles First step in automating SQL tuning
Auto-testing/implementing is limited to profiles because: No lengthy, expensive set-up process (building an index takes time) Private to the current compilation No change to user SQL (does not change semantics) SQL-level recommendation, can be effectively tested Easily reversed by the DBA Testing is done for regular SQL Tuning Advisor tasks as well!
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Automatic SQL Tuning Defaults Sensible defaults with flexible configurations
Out-of-the-box defaults: Runs in each maintenance window (MAINTENANCE_WINDOW_GROUP) SQL profiles are tested but not implemented DBA can configure using EM: Whether / When / How long it runs Resources it uses Whether it implements profiles How many profiles it implements
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Automatic SQL Tuning Task
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Automatic SQL Tuning Configuration
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Automatic SQL Tuning Result Summary
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Automatic SQL Tuning Result Recommendations
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Automatically Tuned SQL Details Drilldown
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Conclusions Manual SQL tuning is painful even for the experts
Oracle 10g SQL Tuning Advisor quickly gives DBA good choices Oracle 11g Automatic SQL Tuning automates the process by making the easy decisions DBA can control as much of the process as he wants
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Q & A
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Real-Time SQL Monitoring
<Insert Picture Here> Shining new light on SQL Performance
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Problem: Managing High Response-Time SQLs
Monitoring: tracking high response-time SQL What is that expensive SQL (ETL, DDL, batch, report, …) I started up to? Do I have any high response-time SQL running on my OLTP system? Any SQL executing parallel? Investigating: why is this execution so expensive? Plan has hundreds of operations -- where is the time being spent? Why is a particular operation so expensive? SQL runs parallel, is DOP appropriate? is there a skew? What is going on inside a SQL execution??? Single SQL Execution
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Solution: Real-time SQL Monitoring Looking inside the SQL
Enabled out-of-the-box with no performance impact Automatically monitors SQL executions that: consume more than 5 seconds of CPU or I/O time are running parallel: PQ, PDML, PDDL Monitors each execution independently Exposes monitoring statistics at multiple levels Global execution level Plan operation level (Plan Tuning) Parallel Execution level (PX Tuning) Guides your tuning efforts Single SQL Execution
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How does it work? t = 5 t = 6 t = 7 PGA SGA Update execution statistics in PGA continuously After 5 seconds for serial / immediately for parallel, target for monitoring (reserve SGA space) Push statistics to SGA every second Separate entries for each Parallel Execution Server Each execution of each SQL identifiable in ASH via execution key PX Servers share an execution key, but have a different Session ID Statistics available for at least 5 minutes Not vulnerable to cursor age-outs
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New Statistics Exposed
For each SQL Execution (V$SQL_MONITOR): Resource Consumption: ELAPSED_TIME, CPU_TIME, FETCHES, BUFFER_GETS, DISK_READS, DIRECT_WRITES, APPLICATION/CONCURRENCY/CLUSTER/USER_IO_WAIT_TIME, PLSQL/JAVA_EXEC_TIME For each Plan Operation (V$SQL_PLAN_MONITOR): Production: STARTS (#executions), OUTPUT_ROWS Memory/Temp usage: WORKAREA_MEM, WORKAREA_TEMPSEG For each second of session activity (V$ACTIVE_SESSION_HISTORY): SQL Execution Key: SQL_ID, SQL_EXEC_START, SQL_EXEC_ID Row source information: SQL_PLAN_LINE_ID/OPERATION/OPTIONS
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V$ Additions New V$ Views added; existing views supplemented
V$ACTIVE_SESSION_HISTORY (SAMPLE_TIME, SESSION_ID, SESSION_SERIAL#) With Execution Key, Plan Line ID/Operation DBA_HIST_ACTIVE_SESS_HISTORY (DBID, SNAP_ID, INSTANCE_NUMBER, SAMPLE_TIME, SESSION_ID, SESSION_SERIAL#) V$SESSION (SID, SERIAL#) With Execution Key V$SQL_MONITOR (SQL_ID, SQL_EXEC_START, SQL_EXEC_ID) V$SESSION_LONGOPS (SID, SERIAL#, OPNAME) With Execution Key, Plan Line ID/Operation V$SQL_PLAN_MONITOR (SQL_ID, SQL_EXEC_START, SQL_EXEC_ID, PLAN_LINE_ID) V$SQL_PLAN (SQL_ID, CHILD_NUMBER, PLAN_HASH_VALUE, ID)
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How do I use it? 11g Enterprise Manager Grid Control ( DB Control) Additional reporting (available today): DBMS_SQLTUNE.REPORT_SQL_MONITOR Get reports in HTML, XML, or Text
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Enterprise Manager Flow (1)
SQL Details Monitoring Details Top Activity Session Details
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Enterprise Manager Flow (2)
Monitoring List Monitoring Details
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SQL Monitoring List
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SQL Monitoring Details Core concepts
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SQL Monitoring Details Core concepts
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SQL Monitoring Details Core concepts
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SQL Monitoring Details Core concepts
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SQL Monitoring Details (Parallelism) Core concepts
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SQL Monitoring Details (Parallelism) Core concepts
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SQL Monitoring Details (Parallelism) Core concepts
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SQL Monitoring Details Big Plans
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SQL Monitoring Details Big Plans
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SQL Monitoring Details Big Plans
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SQL Monitoring Details Big Plans
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SQL Monitoring Details Big Plans
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SQL Monitoring Details Poor Indexing
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SQL Monitoring Details Partially Parallelized
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SQL Monitoring Details Partially Parallelized
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SQL Monitoring Details Partially Parallelized
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SQL Monitoring Details FORCE PARALLEL QUERY PARALLEL 4
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SQL Monitoring Details FORCE PARALLEL QUERY PARALLEL 4
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SQL Monitoring Details Advanced PQ Skews
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SQL Monitoring Details Advanced PQ Skews
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SQL Monitoring Details Advanced PQ Skews
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SQL Monitoring Details Advanced PQ Skews
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Conclusion Real-Time SQL Monitoring is
Monitoring and tuning for high response-time SQLs New, fine-grained SQL statistics tracked automatically updated while the SQL runs highly visible and accessible at no cost to your production system The only way to know what’s happening inside single SQL execution The quickest way to the root cause of a performance problem: If you can find the problem, you can fix it!
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Q & A
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