Self healing Database system

1. Automatic Performance
Diagnosis and Tuning in Oracle
Self-healing Database System
1

2. Presenters
Tanvir Rahman
2015-2-60-027
Md. Mohaiminul Hasan
2015-2-60-084
Mohammad Salman Hossain Bhuiyan
2015-2-60-085
2

3. Database System
3

4. System Performance Diagnosis
Q: Which entity causes performance degradation?
-Size of buffer cache
-I/O capacity
-CPU capacity
-Database locks
-Bandwidth
-SQL statement
-SQL optimization
4

5. Tuning
5

6. Problem Behind Manual Tuning
1. Abundant expertise.
2. Not time efficient
3. Misdirected
4. Methodology without having
holistic view
5. Regenerate the problem
6

7. Solution
7

8. Database Time
• Common Currency
Figure 1:Database time from a single user’s perspective
8

9. Automatic Database Diagnosis Monitor
(ADDM)
• Oracle 10g self-managing framework
• Goal: Find root-causes of problems
• Which component of database consume significant time?
• What is the top issue affecting overall throughput?
9

10. Data for ADDM
• Collect Data from each node of DB Time-graph
• Active Session History
10

11. Active Session History (ASH)
11

12. Challenges of ASH
• Sampling too frequent: “MINIMAL INTRUISON PRINCIPLE” violation
• Infrequent sampling: Failure of finding root cause
12

13. Minimal Intrusion Principle
• Performance should not be degraded because of “measurements
collection”
13

14. Data: Non-numeric in nature
Full log of database setting (Not changes frequently)
• Size of memory components
• Number of CPUs using by the system
• Special query optimizer setting
14

15. - AWR
- ADDM
- Recommendation
- Oracle 10g Advisors
- In memory
15
Self-Managing Database Framework
Figure 2: ADDM and the Self-Managing Database framework

16. Self-Managing Loop
ADDM’s role in Self-Managing Database
• Observe Phase
• Diagnose Phase
• Resolve Phase
16

17. Observe Phase
• Automatic and continues
• Collect relevant measurements and statistics
• Precise timing information
• Automatic Workload Repository (AWR): the main component
17

18. AWR
• Store of performance data
• The database captures system & stores performance data in AWR
• Each collection as Snapshot
• ADDM takes two most recent snapshots
18

19. Diagnose Phase
• Fetch data from AWR
• Analyze Data
• Set of advisors
• ADDM itself an Advisor
• SQL tuning Advisor
• Segment Advisor
• Memory Advisor
- If any advisor consumes substantial amount of time to analysis, ADDM
takes part.
19

20. Resolve Phase
• Apply recommendation automatically or manually
• Considered for future performance measurement
• Closes iteration of particular tuning loop
• Tuning loop till desired performance level
20

21. Experiments and Results
• Hard to quantify
• Need survey
• Real ADDM usage: Experience of Qualcomm
• Updated Oracle version 8.1.7.4 to 10g.
• Significant Performance Fall
• ADDM recommendation: SQL update statement causes 90% system load
• SQL Tuning Advisor: Create index
Reason: A patch was missing in updated version
21

22. Conclusion
• Comprehensive tuning solution
• Database time of various component
• Marginal effect of component on Database
• Omit reconstruct the problem
• DBTime-graph isolate the root cause
• ADDM provides Recommendation
22