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Transcript
Wait-Time Based Oracle
Performance Management
Prepared for UNYOUG
Presented by Matt Larson
CTO, Confio Software
Who am I?




2
Founder and CTO of database performance
software company
Former DBA consultant specializing in Oracle
performance tuning
Co-author of three Oracle books (Oracle
Development Unleashed, Oracle Unleashed
2nd Edition, Oracle8 Server Unleashed)
Co-author of two other database related
books
Agenda






3
Foundation
Case Study
Case Study
Case Study
Case Study
Q&A
One: PL/SQL Issue
Two: Full Table Scans
Three: Inefficient Indexes
Four: Locking Problems
Working the Wrong Problems

After spending an agonizing week tuning
Oracle buffers to minimize I/O operations,
management typically rewards you with:
•
•
•
•
4
A.
B.
C.
D.
An all expense paid vacation
A free lunch
A stale donut
Reward? Nobody even noticed!
Tuning Success (or lack thereof)

Your role in the rollout of a new customer
facing application results in:
•
•
•
•
5
A.
B.
C.
D.
Keys to drive the CEO’s Porsche
Keys to use the executive restroom
A mop to use in the executive restroom
Your office has been moved to the restroom
Conventional Tools Measure System
Health…
 Assumption: If I make the database

healthy, users benefit
Symptoms
• DBA finds “big” problem and fixes it, users
report no impact
• Lots of data to review and things to fix, not
sure which to do first
• Unclear view of performance leads to
Finger-pointing
It’s your Code!
IT staff
6
It’s your
Database!
Developer or
vendor
…RMM Focuses on User Wait-Time
SQL
Request
SQL
Response
7
1. Identify each bottleneck affecting the user
2. Rank bottlenecks by user impact
3. Implement proven suggestions
4. Set correct expectations on impact of fix
5. Show proof the fix helped users
RMM: Confio’s Underlying Methodology

Resource Mapping Methodology: Industry
best-practice optimizing performance tuning for
maximum business impact

Three Key Principles of RMM
1. SQL View: All statistics at SQL statement level
2. Time View: Measure Time, not number of times a
resource is utilized
3. Full View: Separately measure every resource to
isolate source of problems
8
Illustrating example: SQL View Principle





9
Example: ‘CEO’ measuring ‘employee’ output
Averaging over entire company gives no useful data
Must measure each job separately
DBA must manage database similarly
Measure and identify bottlenecks for each SQL independently
Illustrating example: Time View Principle





10
Example: ‘CEO’ counting ‘tasks’ vs. ‘time to complete’
Counting system statistics not meaningful
Must measure Time to complete
System stats (buffer size, hit ratios, I/O counts) do not identify
where database customers are waiting
Identify and optimize Wait Time for each SQL as best indicator of
performance
Illustrating example: Full View Principle
 Example: ‘CEO’ measuring results with blind spot hiding key



11
processes
Without direct visibility, valuable info is lost
Must have visibility to every process step
Distinctly identify and measure each Oracle resource for each
distinct SQL
RMM-compliant Performance Tool Types
Two Primary Types of Tools

Session Specific Tools
• Tools that focus on one session at a time often by tracing the
process
• Examples: tkprof (Oracle), OraSRP Profiler (open source)

Continuous DB Wide Monitoring Tools
• Tools that focus on all sessions by sampling Oracle
• Example: Confio Ignite

12
Both tools have a place in the organization
Tracing


Tracing with wait events complies with RMM
Should be used cautiously in non-batch environments
due to session statistics skew
• 80 out of 100 sessions have no locking contention issues
• 20 out of 100 have spent 99% of time waiting for locked
rows
• If you trace one of the “80” sessions, it appears as if you
have no locking issues (and spend time trying to tune other
items that may not be important)
• If you trace one of the “20” sessions, it appears as if you
could fix the locking problems and reduce your wait time by
99%
13
Tracing (cont)






14
Very precise statistics, may be only way to get
certain statistics
Bind variable information is available
Different types of tracing available providing
detail analysis even deeper than wait events
Ideal if a known problem is going to occur in
the future (and known session)
Difficult to see trends over time
Primary audience is technical user
Continuous DB Wide Monitoring Tools




24/7 sampling provides real-time and
historical perspective
Allows DBA to go back in time and retrieve
information even if problem was not expected
Not the level of detail provided by tracing
Most of these tools have trend reports that
allow communication with others outside of
the group
• What is starting to perform poorly?
• What progress have we made while tuning?
15
16
Case Study One
PL/SQL Issue
Problem Observed

Critical situation: application performance
unsatisfactory
• Response time between 240 and 900 seconds
• Most times users shutdown application
• Very high network traffic (3x—4x normal),
indicating time-outs and user refreshes
• “CritSit” declared: major effort to resolve problem
18
Wait Events During Problem
library
cache lock
library
cache pin
19
Investigation
20
What does RMM tell us?
21

Which SQL:

Which Resource:

How much time:
CERN_PROFILE
Truncate
library cache pin
library cache lock
up to 16 Hours of
wait time per hour
Results

Found an invalid trigger
• Insert statement was trying to fire trigger
• Truncate was locked behind it



22
Response time improvement from 60,000
seconds (worst case) to 0 seconds
Configured alert to notify DBA when the
problem starts next time
Problem should not occur for 22 hours without
anyone knowing
Case Study Two
DB File Scattered Reads
Problem Observed

Problem: Login taking 4 minutes for each user
everyday they started their day
• High wait accumulation from 6:30 – 8:30 am
• 600 Users X 4 Minutes = 40 Hours Every Day
• 40 Hours lost productivity every day

Applied RMM approach to problem
identification
• Identify Wait Time, offending SQL, offending
Resource
24
Wait Events During Problem
25
Investigation
26
What does RMM tell us?
27

Which SQL:

Which Resource:

How much time:
LoginLookup
UpdateInventory
Scattered Read
Buffer Busy Waits
40+ Hour
Every Day
Hypotheses: Oracle Interpretations
Two Alternative paths for optimization:
I.
Eliminate Full Table Scan
•
II.
Improve response time
•

There isn’t a need to read the whole table, so we need to
find the right shortcut
We need to read most or all of the table anyway, so let’s
just figure out how to do it faster
Key Questions:
1. Is full table scan necessary?
2. What causes a full table scan for this SQL Statement?
28
I. Unnecessary Full Table Scan?
Solutions:
1. Add / Modify index(es) on the table
2. Update table and/or index statistics if proper
index not being used
3. Add hint to use existing index
4. Optimize the application
29
Full Table Scan is Needed
Two alternative paths for optimization:
I. Eliminate Full Table Scan
• There isn’t a need to read the whole table, so we
need to find the right shortcut
II. Improve response time
• We need to read most or all of the table anyway,
so let’s just figure out how to do it faster
30
II. Improve Response Time for Db
File Scattered Reads
Solutions:
1. Use Parallel Reads
2. Set Database Parameters
3. Improve I/O Speed
4. Optimize the application
5. Larger Database Caches (64-bit)
31
1. Use Parallel Reads = Faster FTS

Parallel Reads
• Can be set at the table level (use with caution)
Alter table customer parallel degree 4;
• Normally used by hinting in the SQL Statement


select /*+ FULL(customer) PARALLEL(customer, 4) */ customer_name
from customer;
A delicate tradeoff
• sacrifice the performance of others for the running query.
Not necessarily efficient, just faster
• Parallel Reads may actually do twice the work of a sequential
query but have four workers, thus finishing in half the time
while using 8x resource
32
2. Set database parameters



33
DB_FILE_MULTIBLOCK_READ_COUNT
• specifies the maximum number of blocks read in one I/O operation
during a sequential scan
• Impacts the optimizer
• Reduces number of I/Os required
• For OLTP, typically between 4 to 16
• Optimizer will more likely to FTS if set too high
Ensure that the database read requests are
synced up with the O/S.
This gets tricky if different block sizes are
used in different tablespaces
3. Improve I/O speed


Get your SA involved
Investigate I/O sub-system
• Iostat, vmstat, sar, … for potential problems
• Monitor during high activity

Investigate contention at the disk/controller
level.
• Learn which disks share common resources
• Use more disks to spread I/O and reduce hot spots

34
Investigate caching on disk sub-system and
current memory usage
4. Optimizing the Application



Review application – do you have access to
code for changes?
Understand the code around the problem SQL
Techniques to Optimize a statement:
• Reduce the number of calls for a SQL
– Caching the data in the application
– Creating a summary table (perhaps via a materialized view)
– Eliminating the need for the data
• Retrieve Less Data with each statement
– Add fields to the WHERE clause
• Combine SQLs for fewer calls
– Combine several SQLs with different bind variables into one large statement that
retrieves all the data in one shot
35
5. Larger Database Caches (64-bit)


Larger cache means fewer disk reads
May need large increase to have significant
impact
Performance
Gain
% of database in
memory
36
Results


Added indexes to underlying tables
Added Materialized View
Full Table
Scan Fixed
37
Case Study Three
DB File Sequential Reads
Problem Observed




Data Warehouse loads were taking too long
Noticed high wait times on db file sequential
read wait event
DBAs were confused – why are data load
inserts “reading” data
Applied RMM approach to problem
identification
• Identify Wait Time, offending SQL, offending
Resource
39
Investigation
SQL
Sequential read time
Sequential read time
by object for SQL
40
What does RMM tell us?
41


Which SQL:
Which Resource:

How much time:
3 Insert Statements
DB File Sequential
Read
5 hour+
90% of wait time
Investigating db file sequential reads




Often considered a “good” read
DB file sequential reads normally occur during
index lookups
Often a single-block read although it may
retrieve more than one block.
Sequential Read may also be seen for reads
from:
• datafile headers
• rebuilding the control file
• dumping datafile headers
42
Hypotheses: Oracle Interpretations of
Sequential Reads
Causes of excessive wait times:
I. Reading too many index leaf blocks
II. Not finding block in buffer cache forces disk
read
III. Slow disk reads
IV. Contention for certain blocks
V. High Read time on INSERT statements
43
I. Reading too many index and table
blocks (cont)
1.
2.
3.
4.
44
Rebuild Fragmented Indexes
•
alter index rebuild [online];
Compress Indexes
•
•
alter index rebuild compress;
Uses more CPU
Multi-column indexes
•
•
Avoid the table lookup
Will create a larger index
Pre-sort Table data
II. Not finding block in buffer cache forces
disk read



45
Db File sequential reads occur because the
block is not in the buffer cache.
How do we make sure more blocks are
already in the cache?
Solutions
1. Increase the size of the buffer cache(s)
2. Put the object in a cache where it is less likely to
get flushed out
III. Slow disk reads




46
With databases, it often comes down to this –
the disk just needs to be faster
Put certain objects on the fastest disk
O/S file caching using special software that
makes normal files perform like raw files
Increase Storage System Caching – such as
an EMC cache
Results





47
Inserts were updating indexes that had low
cardinality leading columns
Reordered columns in the index and got a
50% performance improvement
Log file sync wait event was then the largest
wait event
Data was being committed too often
Tuning is an iterative process
Case Study Four
Enqueue
Problem Observed

Problem: High Wait on CPPFPROD
• Accumulated wait 9.5 hours (34,000 sec) during
3.00-4.00am hour
• End users were complaining loudly

Applied RMM approach to problem
identification:
• Identify Wait Time, offending SQL, offending
Resource
49
Investigation: Drill down to Top SQL &
Identify likely source of Problem
50
What is blocking session waiting on?



51
Idle Session
DB File Scattered Reads
Another session
Idle Session Scenario
Sally


Update customer 147
Goes to Lunch
Jim
Locked trying to update customer 147
Jim will needlessly wait a long time. DBA can kill
Sally’s session IF they can tell that the session
is idle.
52
Missing Index Scenario
Sally


Update customer 147
Selects from order table
with missing index
Jim
Locked trying to update customer 147
DBA can tell that Jim is really waiting because of
a missing index on the order table – even
though Jim isn’t using the order table.
53
Idle Session Scenario
Sally


Update customer 147
Selects from order table
with missing index
Jim
Updated warehouse 22
Locked trying to update customer 147
Bob
Locked trying to update warehouse
22
A chain of locks occurs even though both locked
users aren’t accessing the table with missing
indexes
54
Wait Events for Development






55
Tuning SQL for optimal performance
Debug/test/integrate/pilot process
Understand impact on existing database
Understand Oracle impact on application
performance
View into production for better development
prioritization and feedback
Reduce finger-pointing
Conclusion



Conventional Tuning focus on “system
health” and lead to finger-pointing and
confusion
Wait event tuning implemented according to
RMM is the new way to tune
Two RMM-compliant tools types
•
•

56
Tracing tools
Continuous DB-wide monitoring tools
Questions & Answers
Who is Confio?


57
Oracle product is “Ignite for Oracle”, fast install, free
trial at www.confio.com
Organizations who trust Confio to monitor their most
critical applications include:
Thank you for coming
Matt Larson
Founder/Chief Technology Officer
Contact Information
• [email protected]
• 303-938-8282 ext. 110
• Company website
www.confio.com
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