Physical Designs and performance tunning

1. Indexing strategies and good physical
designs for performance tuning
Kenneth Ureña
http://www.sqlcr.com
@sqlcr
/SpanishPASSVC

2. Agenda
 The journey of a transaction
 Performance degradation factors
 Physical Designs
 Indexing
 Coding best practices

3. THE JOURNEY OF A TRANSACTION

4. Actual empty
Virtual
Log
File
Truncated
- Sequential Access
- Just 1 file Active
- Recommended
Raid 1 ó 1 + 0
- Commit, backup log
trigger I/O
- Random Access
- Multiple datafiles Active
- Recommended Raid 1/1+0
5+0 / 5
- Checkpoint, backup, load /
unload Cache
Full Empty Full Empty
Empty Full Empty Full

5. PERFORMANCE DEGRADATION
FACTORS

6. Hardware Software
DB Performance Degradation life cycle
Overload
Degraded PerformanceCPU / Memory
Storage
Peripheral
Database
Data
Algorithm

7. • Sata, SAS, SSD (Types of Hard Drives)
• Big performance difference between Sequential IO vs
Random IO
• IOPS (In Out Per Second)
• IOPS Estimated = 1 / ((seek time / 1000) + (latency / 1000))
Storage
Reference
http://www.cloudbyte.com/docs/Whitepaper_CloudByte_Measuring-Storage-Performance.pdf

8. • Average read seek time: 3.4 ms
• Average write seek time: 3.9 ms
• Average latency: 2.0 ms
• Seek time = (Average read seek time + Average write seek time) / 2
= (3.4 + 3.9) / 2 = 3.65 ms
• IOPS Estimated = 1 / ((seek time / 1000) + (latency / 1000))
= 1 / ((3.65/1000) + (2.0 / 1000)
= 176.9911 ~ 175 IOPS
SAS - 600GB 15K - Seagate
Reference
http://www.seagate.com/www/en-us/products/enterprise-hard-drives/cheetah-15k#tTabContentSpecifications

9. Raids
• Raid 0
• Raid 1
• Raid 5
• Raid 1 + 0

10. Raid 0 (Stripping)
 Logical Drive Characteristics
 IOPS = #Disk * IOPS Estimated
 Size = #Disks * Size disk
 Pros
 High performance
 Low cost
 Cons
 Fault tolerance
2
4
6
1
2
3
4
5
6
1
3
5
Raid 0
(Striping)
Disk1 Disk2
Logical
Drive

11. Raid 1 (Mirroring)
 Logical Drive Characteristics
 IOPS = (#Disk / 2) * IOPS Estimated
 Size = (#Disk / 2) * Size disk
 Pros
 Fault tolerance
 Cons
 Higher cost
1
2
3
4
5
6
Raid 1
(Mirror)
Disk1 Disk2
Logical
Drive
1
2
3
4
5
6
1
2
3
4
5
6

12. Raid 5
 Logical Drive Characteristics
 IOPS = (#Disk - 1) * IOPS Estimated
 Size = (#Disk - 1) * Size disk
 Pros
 Fault tolerance
 Cost Effective
 Cons
 Recalculation on raid failure
 Parity calculation
1
2
3
4
5
6
Disk2
Logical
Drive
Disk1
1
3
P
2
P
5
P
4
6
Raid 5
Disk3

13. 2
4
6
1
2
3
4
5
6
Disk3
Logical
Drive
2
4
6
Disk4
Raid 1Raid 1
Raid 0
1
3
5
Disk2
1
3
5
Disk1
Raid 1 + 0
 Logical Drive Characteristics
 IOPS = (#Disk /2) * IOPS Estimated
 Size = (#Disk / 2) * Size disk
 Pros
 Fault tolerance
 Cons
 Cost

14. Database Files
Random
Access
Multiple
Actives
Data
File Sequential
Access
One
Active
Log
File

15. PHYSICAL DESIGNS

16. Physical Designs
• Choosing the right Raid for the Database File
• Split the files in order to get the expected Access behavior

17. Scenario #1
• 1 User Database
• High OLTP Traffic
• High TempDB consumption
• 16 Cores Server

18. Scenario #1 (Proposal 1)
Raid 1+0 Drive
SAS
TempDB UserDB
Raid 5 Drive
SAS
Raid 1+0 Drive
SAS

19. Scenario #1 (Proposal 2)
Raid 1+0 Drive
SAS
TempDB UserDB
Raid 1+0 Drive
SAS
Raid 1+0 Drive
SAS

20. Scenario #1 (Proposal 3)
TempDB UserDB
Raid 1+0 Drive
SSD
Raid 1+0 Drive
SAS

21. Scenario #2
• multiple User Database
• High OLTP Traffic
• High TempDB consumption
• multiple Cores Server

22. Scenario #2 (Proposal 1)
Raid 1+0 Drive
SAS
TempDB
Raid 1+0 Drive
SAS
Raid 1+0 Drive
SAS
UserDBN
Raid 1+0 Drive
SAS
Raid 1 Drive
SSD
UserDB1

23. INDEXING

24. Indexes and OrganizationTable structure
Image from
SQL server 2008 books online

25. Indexes and OrganizationHeap Table
Image from:
SQL server 2008 books online

26. Indexes and OrganizationClustered Table
Image from:
SQL server 2008 books online

27. Clustered (example)
Image from:
http://www.sqlservercentral.com/images/4695.jpg

28. Indexes and OrganizationNonClustered
Index
Image from:
SQL server 2008 books online

29. Column Index
Image from
http://magenic.com/

30. Data access patters
 Seek
 Scan
 Bookmark Lookup

31. CODING BEST PRACTICES

32. Coding Best Practices
 Maximize coverage
 Avoid conversions (implicit/explicit)
 Avoid row by row access (cursor pattern)
 Avoid unnecessary sorting
 Choose the right index for the expected data
pattern access method

33. Q&A
Thank you
Kenneth Ureña
http://www.sqlcr.com
@sqlcr
/SpanishPASSVC