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SQL Elapsed Time Analysis
SQL Elapsed Time
Analysis
Craig A. Shallahamer Founder - OraPub, Inc.
SQL Elapsed Time Analysis
OraPub is about Oracle performance.
• OraPub is all about Oracle performance management; systematic and quantitative firefighting and predictive analysis.
• Web site started in 1995 and the company was founded in 1998 by Craig Shallahamer.
• OraPub has always been about disseminating Oracle database centric technical information.
• Consulting, training, books, papers, and products are now being offered.
• We have been on-site in 24 countries and our resources have been received in probably every country where there are DBAs.
• Training • Unique Blog • Free Tools
• Free Papers • Books
• Products • Consul8ng
Resources
SQL Elapsed Time Analysis
Short resume...kind of... • Studies economics, mathematics, and computer science at
university in California, US. • Started working with Oracle technology in 1989 as a Forms 2.3
developer on Oracle version 5. • Soon after started performance firefighting...daily! • Co-found both Oracle’s Core Technology and System
Performance Groups. • Left Oracle to start OraPub, Inc. in 1998. • Authored 24 technical papers and worked in 24 countries. • Authors and teaches his classes Oracle Performance
Firefighting, Adv Oracle Performance Analysis, and Oracle Forecasting & Predictive Analysis.
• Authored the books, Forecasting Oracle Performance and Oracle Performance Firefighting.
• Oracle ACE Director. • Frequent blog contributor: A Wider View
SQL Elapsed Time Analysis
My two books...
OraPub discount code: IS11
SQL Elapsed Time Analysis
One presentation with two parts.
• “The average” can be misleading.
• Modeling E time leads to insights.
SQL Elapsed Time Analysis
Working with limited information. SQL ordered by Elapsed DB/Inst: LOOK/LOOK Snaps: 80298-80310!-> Resources reported for PL/SQL code includes the resources used by all SQL! statements called by the code.!-> Total DB CPU (s): 22,800!-> Captured SQL accounts for 109.8% of Total DB CPU!-> SQL reported below exceeded 1.0% of Total DB CPU!! CPU CPU per Elapsd Old! Time (s) Executions Exec (s) %Total Time (s) Physical Reads Hash Value!---------- ------------ ---------- ------ ---------- --------------- ----------! 474.59 38,479 0.01 19.9 479909.89 923,822,548 4166296332!BEGIN pkg_com_unite.st_execute_commune( i_daemon_id => :daemon_id, !i_reload_subult_true_false => :reload_subult_true_false, !i_dump_caches => :dump_caches, i_add_seq2_id => :add_seq2_id, !i_dump_seq2_id => :dump_seq2_id, i_remove_seq2_id => :remove_seq2_id, !i_multi_seq2_chg_true_false => :multi_seq2!
Total Elapsed Time : 479,909.89 seconds Total ExecuFons : 38,479 exec
SQL Elapsed Time Analysis
So the average E time is...
E = 479909.89 secs / 38,479 exec! = 12.47 sec/exec!
source: Init Hist Work 2.nb
SQL Elapsed Time Analysis
It’s more likely to be like this...
More? “log normal”
SQL Elapsed Time Analysis
Even more likely...
SQL Elapsed Time Analysis
What can we do?
We don’t want to mislead others.
We need to truly understand the situation if we are making decisions
based on this information.
SQL Elapsed Time Analysis
We have a variety of collection options. • SQL Trace. Valid option.
– Must have ability to parse the trace files producing E times. – Can trace on sql_id. – Must be the production system.
• Instrument SQL. Valid option. – May not be practical or possible.
• Stopwatch. Risky. – Limited scope and very few samples. – OK for a specific user situation.
• Benchmark or Isolated Testing. Very risky. – If you want real results, you need a real situation (HW, data, arrivals, concurrency).
• OraPub E Time Collector. Valid, but grabs a core. – Free tool. OraPub search: “sql elapsed time” – Gathers at sql_id and plan_hash_value level. – Grabs and holds a CPU core, ouch!
• OraPub E Sampler. Valid but not free. – Un-noticeable impact with same results as tracing or instrumentation! – Gathers at sql_id level and samples stored in Oracle table. – Licensed like a box of candy. – Beta version available for Insync attendees....free! More? “SQL sampler”
SQL Elapsed Time Analysis
How good is sampled data?
This is smoothed histogram of elapsed Fmes for a specific sql_id (query) collected using SQL Trace, instrumentaFon, and OP Elapsed Fme Sampler (normal). Over a 5 minute period, around 80 samples where gathered from each collecFon method.
All three collecFons methods produce the same results!
More? True SQL Elapsed
SQL Elapsed Time Analysis
Let’s take a look at some
real data from
real systems.
SQL Elapsed Time Analysis
#1: Showing all samples.
source: Aber3129
Samples : 230!Mean : 57168!Median : 60000!Max : 793996!Collector: OP E Time!
SQL Elapsed Time Analysis
#1: Showing most samples.
source: Aber3129
Samples : 230!Mean : 57168!Median : 60000!Max : 793996!Collector: OP E Time!!
SQL Elapsed Time Analysis
#2: Showing most samples.
source: Garret1jqj
Samples : 368!Mean : 158!Median : 23!Max : 2840!Collector: OP E Time!
SQL Elapsed Time Analysis
#3: Showing all samples.
source: Garret8qt
Samples : 506!Mean : 48!Median : 26!Max : 476!Collector: OP E Time!
SQL Elapsed Time Analysis
#4: Showing all samples.
source: Garret 0u2t
Samples : 179!Mean : 38.72 ms!Median : 38.04 ms!Max : 58.40 ms!Collector: OP E Sampler!
SQL Elapsed Time Analysis
Experimental Examples.
source: E Analysis 1a (final).nb
SQL Elapsed Time Analysis
Conclusions about average E. • Average elapsed time for a specific SQL
statement can be very misleading. • Elapsed times are not normally distributed. • The average elapsed time is not the typical
elapsed time. • The modes are the typical elapsed times. • If the mode is not available, then the median
can be used, in some cases. • If you need to communicate typical elapsed
times, you need to gather real data. More? “SQL elapsed”
SQL Elapsed Time Analysis
Modeling elapsed time
E = units of work x time per unit
E (time/exec) = WL(work/exec) x RT(time/work)
SQL Elapsed Time Analysis
Example of elapsed time.
Supposed a query must access 100,000 logical IOs and each LIO takes 0.020ms. Therefore, the elapsed Fme will be 2,000ms or 2.0 seconds.
E (ms/exec) = units of work (LIO/exec) X time per work (ms/LIO)!!2000 ms/exec = 100,000 LIO/exec X 0.020 ms/LIO !
SQL Elapsed Time Analysis
When we tune, WL is reduced. • SQL tuning fundamentally reduces the
work required to execute a statement. • Since less work is required then generally,
the elapsed time will decrease! • If your tuning prowess reduces the work
from 100,000 PIOs to 50,000 PIOs then you can expect the elapsed time to decrease by 50%.
• But does this really occur in reality? hum...
SQL Elapsed Time Analysis
Experimental results!
Tuned SQL
Stmt Logical IO
Stmt LIO Change
Median Elapsed Time (s)
Median Elapsed Time (s) Change
Samples
No 355289 -‐ 14.22 -‐ 243
Yes 161495 -‐54.55% 5.88 -‐58.67% 339
• CollecFon interval was 2 hours. • OraPub’s Elapsed Time Sampler was used to collect elapsed Fmes. • LIO numbers gathered from v$sysstat. • Time based on Fmestamp data type.
source: E Analysis 1a.xlsx, 256 latches
SQL Elapsed Time Analysis
Ways to reduce UOW process time. • There are many ways to reduce the time it
takes to process a single unit of work. • There are direct methods and indirect
methods. • Indirect: Because processes share and
compete for resources, when the big issue is resolved, many other issues become less intense.
• Direct: Tuning Oracle directly reduces the time required to process a piece of work. Hum...
SQL Elapsed Time Analysis
Experimental results!
CBC Latches
Instance RT
(ms/lio) Change
Instance WL
(lio/ms)
SQL Stmt Median Elapsed Time (s)
Change Samples
256 0.03623 -‐ 120 14.224 -‐ 243
32768 0.00856 -‐76.36% 227 2.968 -‐79.13% 399
• CollecFon interval was 2 hours. • OraPub’s Elapsed Time Sampler was used to collect elapsed Fmes. • RT components gathered from v$sysstat, v$sys_Fme_model, and v$system_event. • Time based on Fmestamp data type.
source: E Analysis 1a.xlsx, not tuned
SQL Elapsed Time Analysis
This graph shows the work process time.
source: More Latches RT Compare...xlsx
-‐76% RT Change
+96% WL Change
SQL Elapsed Time Analysis
All situations elapsed times.
SQL Elapsed Time Analysis
The point? #1 – Average is misleading.
• It is easy to calculate the average elapsed time...even from Statspack.
• But saying, “The average elapsed time is X.” will most likely mislead everyone.
• The median or mode(s) is a much better representation of the typical elapsed times.
• If you need to communicate typical elapsed times, you need to gather real data.
SQL Elapsed Time Analysis
The point? #2 – Modeling SQL E. • Two basic ways to reduce elapsed times:
– Reduce work to be done.
– Reduce time to process each piece of work.
• SQL statement elapsed time can be simply modeled.
• SQL statement elapsed time can be anticipated.
SQL Elapsed Time Analysis
Want to dig deeper? • Craig’s Blog – A W i d e r V i e w
• Training from OraPub
– Oracle Performance Firefighting (I)
– Adv Oracle Performance Analysis (II)
• Books
– Oracle Performance Firefighting (C. Shallahamer)
• Chapter 9 is FREE to download
Melbourne & Perth in Q2 2012
SQL Elapsed Time Analysis
Thank You!
