1. One Picture is Worth a Thousand Words
Amihay Gonen,
Oracle Domain expert, Dell

2. Who Am I More than 20 years work as an Oracle DBA and developer
Worked with Oracle since version 7
Most of the time in R&D departments on BIG DATA projects
Managed several DBA teams for more than 10 years.
Currently works as an Oracle domain expert in DELL, as part of the FogLight development team.
Hobbies : Playing chess , running and developing database-oriented tools
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3. Preface David McCandless said in his TED talk:
"By visualizing information, we turn it into a landscape that you can explore with your eyes, a sort of information map.
And when you're lost in information, an information map is kind of useful."
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4. Preface
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5. Agenda Oracle performance Tools Data visualization methods
Poor man’s Heat Map from AWR
Root cause analysis
Future
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6. Oracle performance Tools
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7. The Evolution of Oracle Performance Tools
UtlBstat-UtlEstat (Oracle 7)
StatsPack (Oracle 8,8i)
Automatic Workload Repository – (Oracle 10G and above)
Active Session History (Oracle 10) Automatic Database Diagnostic Monitor
The Evolution of Oracle Performance Tools
utlBstat/Etstat – collect basic key metrics like system wait statstics , data dictionary statstics and library cache
StatsPack – add extra information include TopSql … to complete …
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8. Oracle performance Tools- StatsPack
Collects more data, including high-resource SQL.
Pre-calculates many ratios such as cache hit ratios, rates, and transaction statistics.
Separates data collection from report generation.
No extra license ($$)
Support only 9i metrics
No built-in retention scheme.
Focus on history only
Farther reading:
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9. The evolution of Oracle performance utilities - AWR
ADDM
Server alerts
AWR/ ASH
Advisors
Confidential
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10. The evolution of Oracle performance Tools - AWR
A DWH like repository for all performance metrics
Repository tables are part of the database (SYSAUX tablespace )
Data is retrieved in a “snapshot” once an hour and retained for 7 days (configurable)
Baseline enables to compare between different periods (snapshot range)
Basic Report - awrrpt.sql
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11. The Evolution of Oracle Performance Tools - Server Alerts
Database Self-Monitoring
Alerts triggered when
A problem occurs
Data does not match expected values for metrics
Alert thresholds are configurable (OEM or DBMS_SERVER_ALERT)
View alerts
OEM
DBA_OUTSTANDING_ALERTS
Asynchronous notification (for example: )
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12. Oracle performance Tools- ADDM
A report from the AWR to identify potential performance bottlenecks (“human like”)
Report is combined of the following parts :
Finding issues
Description of the issue
Fix it Recommendation
Symptoms which lead to its discovery
ADDM report (task) generation is part of AWR snapshot (default one an hour)
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13. The Evolution of Oracle Performance Tools - Advisory
(Automatic) SQL Tuning Advisor – provides recommendations for improving the efficiency of an SQL query or a set of SQL queries
Memory Advisors
Memory
SGA
Buffer Cache
PGA
Undo Advisor
(Automatic) Segment Advisor
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14. Data Visualization Methods
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15. Data Visualization Methods Details …
Simplest form of data
Compare between different metrics in a point in time
Enables to detect macro patterns and also to pay attention for detail information
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16. Data Visualization Methods
first glance impression
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17. Data Visualization Methods - HeatMap
Computers are good with numbers People are good with pictures
Quickly focus “hot” areas
Get the “global” picture
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18. Data Visualization Methods - TimeLine
Answer What/When questions
Know the process to have better understanding
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19. Data Visualization Methods - Magic Square
Compare 2-dimension easily
Use common standard in the industry
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20. Poor Man’s Heat Map from AWR
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21. Data Visualization Methods - HeatMap
What are the busiest hours ?
Display in one picture data of one week or more
Focus in the general picture
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22. Data Visualization Methods - HeatMap
Detect patterns
Confidential
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23. Data Visualization Methods - HeatMap
How to bake your “own” heat map – my receipt ….
Use popular HeatMap.js library –
Query the AWR views to get performance data :
X axis – hour in a day
Y axis – Day list
Count – Value of the metric
Max – Max value ( calculate heat values)
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24. Data Visualization Methods - HeatMap
How to bake your “own” heat map – my receipt ….
Use smart queries
select mod((s.snap_id-first_value(s.snap_id) over (order by s.snap_id)),24) x,
trunc((s.snap_id-first_value(s.snap_id) over (order by s.snap_id))/24) y,
nvl(round((value-lag(value) over (order by s.snap_id))/ ),0) count
from DBA_HIST_SYS_TIME_MODEL m
join DBA_HIST_SNAPSHOT s
on m.snap_id=s.snap_id
where stat_name='DB time';
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25. Data Visualization Methods - HeatMap
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26. Root Cause Analysis
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27. Root Cause Analysis
Hi I’m Bob , I’m the DBA on duty ,
How may I assist you ?
My name is John.
My DB suddenly works slower than I am used to
No problem, please provide me connection details ?
Sure , I’ll send by the SSH connection details
Confidential
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28. Root Cause Analysis
What to-do
next ?
Confidential
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29. Root Cause Analysis – Top Down
Data Visualization
Table Chart (awr report)
* Focus on the sql detail
Line Chart
* What are the peak time ?
* Is the metric out of it’s baseline
Information Visualization
HeatMap
* What are the busiest hours ?
* is there a trend ?
* What is the problematic resource (Cpu, I/O , Application behavior )
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30. Root Cause Analysis
Hmm… let’s focus on 11/2/2014 \
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31. Hmm… Interesting wait class changed from User I/O to Application
Root Cause aAnalysis
Hmm… Interesting wait class changed from User I/O to Application
The system wait class has changed from User I/O to Application wait , it worth focusing on the hours of 3:00 and 4:00 am plus 6:00 and 7:00 AM. \
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32. Root Cause Analysis
Ok , got the problem… \
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33. Future
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34. Future The ratio databases per DBA is increasing .
DBAs expected to achieve more in less time
One of Keys to success is to pick the right tool for the right problem.
For code example :
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35. Thank you
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