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High Performance, Reliable Secondary Storage

Uğur Tılıkoğlu
Gebze Institute of Technology
Overview
 Introduction
 Background
 Disk Terminology
 Data Paths
 Technology Trends
 Disk Array Basics
 Data Striping and Redundancy
 Basic Raid Organizations
 Performance and Cost Comparisons
 Reliability
 Implementation Considerations
2
Overview
 Advanced Topics
 Improving Small Write Performance for RAID Level 5
 Declustered Parity
 Exploiting On-Line Spare Disks
 Data Striping in Disk Arrays
 Performance and Reliability Modeling
 Opportunities for Future Research
 Experience with Disk Arrays
 Interaction among New Organizations
 Scalability, Massively Parallel Computers and Small Disks
 Latency
3
Introduction
 RAID: Redundant Arrays of Inexpensive / Independent

Disks
 Improvements in microprocessors and memory
systems require larger, higher-performance secondary
storage systems
 Microprocessors performance increase rate > Disk
performance increase rate
 Disk arrays: multiple, independent disks  large,
high-performance logical disk
4
Background
 Disk Terminology
 Data Paths
 Technology Trends

5
Disk Terminology

6
Data Paths

7
Technology Trends

8
Disk Array Basics
 Data Striping and Redundancy
 Basic Raid Organizations
 Performance and Cost Comparisons
 Reliability

 Implementation Considerations

9
Data Striping and Redundancy
 Data Striping
 Distribute data over multiple disks
 Service in parallel
 More disks  More performance

10
Data Striping and Redundancy
 More disks  More unreliable
 100 disks  1/100 reliability of a single disks
 Redundancy
 Two categories
 Granularity of data interleaving
 Method of computing redundant information and
distribute accross the disk array

11
Data Striping and Redundancy
 Data interleaving
 Fine grained
 Advantages:



access all the disks
high transfer rate

 Disadvantages



only one I/O request serviced at any time
All disks waste time positioning for every request

12
Data Striping and Redundancy
 Data interleaving
 Coarse grained
 Advantages:



Multiple small requests serviced simultaneously
Large requests can access all the disks

13
Data Striping and Redundancy
 Redundancy
 Two main problems
 Computing the redundant information: Parity
 Selecting a method for distributing the redundant
information accross the disk array

14
Basic Raid Organizations
 Nonredundant (RAID Level 0)
 Lowest cost
 Best write performance
 No best read performance
 Any single disk failure result data loss

15
Basic Raid Organizations
 Mirrored (RAID Level 1)
 Twice number of disks
 Data also written to redundant disk
 If a disk fails, the other copy is used

16
Basic Raid Organizations
 Memory Style ECC (RAID Level 2)
 Contain parity disks
 Parity disk proportional to data disks
 Efficiency increases when data disk number increases
 Multiple parity disks are needed to identify the failed
disk, but only one is needed to recover

17
Basic Raid Organizations
 Bit-Interleaved Parity (RAID Level 3)
 Bit-wise data is used
 Disk controller can identify which disk has failed
 A single parity disk is used
 Read  all disks, Write  all disks + parity disk

18
Basic Raid Organizations
 Block-Interleaved Parity (RAID Level 4)
 Same as Level 3 but blocks (striping units) are used
 Read & write < striping unit  one disk
 Parity calculation  xor new data with old data
 Four I/O: write new data, read old data and old parity,
write new parity
 Bottleneck at parity disk

19
Basic Raid Organizations
 Block-Interleaved Distributed-Parity (RAID Level 5)
 Solves bottleneck problem at Level 4
 Best small read, larger read and large write performance
 Small writes are inefficient because of read-modifywrite

20
Basic Raid Organizations
 P + Q Redundancy (RAID Level 6)
 Have stronger codes to solve multiple failures
 Operate in much the same manner as Level 5
 Small writes are inefficient because of 6 I/O requests
due to update both P and Q information

21
Performance and Cost
Comparisons
 Ground Rules and Observations
 Reliability, performance and cost
 Disk arrays are throughput oriented
 I/Os per second per dollar
 Configuration
 RAID 5 can operate as RAID 1 and RAID 3 by configuring
striping unit

22
Performance and Cost
Comparisons
 Comparisons – Small Read & Writes

23
Performance and Cost
Comparisons
 Comparisons – Large Read & Writes

24
Performance and Cost
Comparisons
 Comparisons – RAID 3 & 5 & 6

25
Reliability
 Basic Reliability
 RAID 5




MTTF: mean time to failure, MTTR: mean time to repair
N: total number of disks, G: parity group size
100 disks each had MTTF of 200.000 hours, MTTR of 1 hour,
partiy group size 16  mean time to failure of the system is
about 3000 years !!!

26
Reliability
 Basic Reliability
 RAID 6




MTTF: mean time to failure, MTTR: mean time to repair
N: total number of disks, G: parity group size
100 disks each had MTTF of 200.000 hours, MTTR of 1
hour, partiy group size 16  mean time to failure of the
system is about 38.000.000 years !!!

27
System Crashes and Parity
Inconsistency
 System crash: power failure, operator error, hardware

breakdown, software crash etc.
 Causes parity inconsistencies in both bit-interleaved
and block-interleaved disk arrays
 System crash may occur more frequently than disk
failures
 To avoid the loss of parity on system
crashes, information sufficient to recover parity mus
be logged on a non-volatile storage (nvram) before
each write operation.
28
Uncorrectable Bit Errors
 What is bit error? It is unclear
 Data is incorrectly written or magnetic media

gradually damaged
 Some manifacturers developed an approach; monitors
the warnings given by disks and notifies an operator
when it feels the disk is about to fail.

29
Correlated Disk Failures
 Environmental and manufacturing factors
 Example: earthquake

30
Reliability Revisited
 Double disk failure
 System crash followed by a disk failure
 Disk failure followed by an uncorrectable bit error

during reconstruction

31
Reliability Revisited

32
Reliability Revisited

33
Reliability Revisited

34
Implementation Considerations
 Avoiding Stale Data
 When a disk fails, failed disk must be marked as invalid.
Invalid mark prevents user from reading corrupted data
on the failed disk
 When an invalid logical sector is reconstructed to a
spare disk, the logical sector must be marked as valid.

35
Implementation Considerations
 Regenerating Parity after a System Crash
 Before servicing any write request, the corresponding
parity sectors must be marked inconsistent
 When bringing a system up from a system crash, all
inconsistent parity sectors must be regenerated

36
Implementation Considerations
 Operating with a Failed Disk
 Demand reconstruction: access to a parity stripe with an
invalid sector triggers reconstruction of the appropriate
data immediately onto a spare disk. A background
process scans the entire disk.
 Parity sparing: before servicing a write request, the
invalid sector is reconstructed and relocated to
overwrite its corresponding parity sector

37
Implementation Considerations
 Orthagonal Raid

38
Advanced Topics
 Improving Small Write Performance for RAID Level 5
 Declustered Parity
 Exploiting On-Line Spare Disks
 Data Striping in Disk Arrays

 Performance and Reliability Modeling

39
Improving Small Write
Performance for RAID Level 5
 Buffering and Caching
 Write buffering (async writes): Collect small writes in a
buffer and write as a large data
 Read caching: reduce four I/O access to three, old data is
read from cache

40
Improving Small Write
Performance for RAID Level 5
 Floating Parity
 Shortens the read-modify-write time
 Many free blocks
 New parity block is writted rotationally nearest
unallocated block following the old parity block
 Implemented on disk controller

41
Improving Small Write
Performance for RAID Level 5
 Floating Parity
 Shortens the read-modify-write time
 Many free blocks
 New parity block is writted rotationally nearest
unallocated block following the old parity block
 Implemented on disk controller

42
Improving Small Write
Performance for RAID Level 5
 Parity Logging
 Delaying the read of old parity and write of the new
parity
 Difference is temporarily logged
 Logs are grouped together and large contiguous blocks
are updated more efficiently

43
Declustered Parity
 Distributes the increased load uniformly over all disks

44
Exploiting On-Line Spare Disks
 Distributed Sparing

45
Exploiting On-Line Spare Disks
 Parity Sparing

46
Data Striping in Disk Arrays
 Disk positioning time is wasted work
 Idle times are same as disk positioning
 Data striping or interleaving is, distributing data

among multiple disks.
 Researchers work on data striping unit size to
maximize the throughput

47
Data Striping in Disk Arrays
 P: average disk positioning time
 X: average disk transfer rate
 L: concurrency
 Z: request size

 N: array size in disks

48
Performance and Reliability
Modeling
 Performance
 Kim: response time equations
 Kim & Tantawi: approximate service time equations
 Chen & Towsley
 Lee & Katz
 Reliability
 Markov

49
Opportunities for Future Research
 Experience with Disk Arrays
 Interaction among New Organizations
 Scalability, Massively Parallel Computers and Small

Disks
 Latency

50

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RAID: High-Performance, Reliable Secondary Storage

  • 1. High Performance, Reliable Secondary Storage Uğur Tılıkoğlu Gebze Institute of Technology
  • 2. Overview  Introduction  Background  Disk Terminology  Data Paths  Technology Trends  Disk Array Basics  Data Striping and Redundancy  Basic Raid Organizations  Performance and Cost Comparisons  Reliability  Implementation Considerations 2
  • 3. Overview  Advanced Topics  Improving Small Write Performance for RAID Level 5  Declustered Parity  Exploiting On-Line Spare Disks  Data Striping in Disk Arrays  Performance and Reliability Modeling  Opportunities for Future Research  Experience with Disk Arrays  Interaction among New Organizations  Scalability, Massively Parallel Computers and Small Disks  Latency 3
  • 4. Introduction  RAID: Redundant Arrays of Inexpensive / Independent Disks  Improvements in microprocessors and memory systems require larger, higher-performance secondary storage systems  Microprocessors performance increase rate > Disk performance increase rate  Disk arrays: multiple, independent disks  large, high-performance logical disk 4
  • 5. Background  Disk Terminology  Data Paths  Technology Trends 5
  • 9. Disk Array Basics  Data Striping and Redundancy  Basic Raid Organizations  Performance and Cost Comparisons  Reliability  Implementation Considerations 9
  • 10. Data Striping and Redundancy  Data Striping  Distribute data over multiple disks  Service in parallel  More disks  More performance 10
  • 11. Data Striping and Redundancy  More disks  More unreliable  100 disks  1/100 reliability of a single disks  Redundancy  Two categories  Granularity of data interleaving  Method of computing redundant information and distribute accross the disk array 11
  • 12. Data Striping and Redundancy  Data interleaving  Fine grained  Advantages:   access all the disks high transfer rate  Disadvantages   only one I/O request serviced at any time All disks waste time positioning for every request 12
  • 13. Data Striping and Redundancy  Data interleaving  Coarse grained  Advantages:   Multiple small requests serviced simultaneously Large requests can access all the disks 13
  • 14. Data Striping and Redundancy  Redundancy  Two main problems  Computing the redundant information: Parity  Selecting a method for distributing the redundant information accross the disk array 14
  • 15. Basic Raid Organizations  Nonredundant (RAID Level 0)  Lowest cost  Best write performance  No best read performance  Any single disk failure result data loss 15
  • 16. Basic Raid Organizations  Mirrored (RAID Level 1)  Twice number of disks  Data also written to redundant disk  If a disk fails, the other copy is used 16
  • 17. Basic Raid Organizations  Memory Style ECC (RAID Level 2)  Contain parity disks  Parity disk proportional to data disks  Efficiency increases when data disk number increases  Multiple parity disks are needed to identify the failed disk, but only one is needed to recover 17
  • 18. Basic Raid Organizations  Bit-Interleaved Parity (RAID Level 3)  Bit-wise data is used  Disk controller can identify which disk has failed  A single parity disk is used  Read  all disks, Write  all disks + parity disk 18
  • 19. Basic Raid Organizations  Block-Interleaved Parity (RAID Level 4)  Same as Level 3 but blocks (striping units) are used  Read & write < striping unit  one disk  Parity calculation  xor new data with old data  Four I/O: write new data, read old data and old parity, write new parity  Bottleneck at parity disk 19
  • 20. Basic Raid Organizations  Block-Interleaved Distributed-Parity (RAID Level 5)  Solves bottleneck problem at Level 4  Best small read, larger read and large write performance  Small writes are inefficient because of read-modifywrite 20
  • 21. Basic Raid Organizations  P + Q Redundancy (RAID Level 6)  Have stronger codes to solve multiple failures  Operate in much the same manner as Level 5  Small writes are inefficient because of 6 I/O requests due to update both P and Q information 21
  • 22. Performance and Cost Comparisons  Ground Rules and Observations  Reliability, performance and cost  Disk arrays are throughput oriented  I/Os per second per dollar  Configuration  RAID 5 can operate as RAID 1 and RAID 3 by configuring striping unit 22
  • 23. Performance and Cost Comparisons  Comparisons – Small Read & Writes 23
  • 24. Performance and Cost Comparisons  Comparisons – Large Read & Writes 24
  • 25. Performance and Cost Comparisons  Comparisons – RAID 3 & 5 & 6 25
  • 26. Reliability  Basic Reliability  RAID 5    MTTF: mean time to failure, MTTR: mean time to repair N: total number of disks, G: parity group size 100 disks each had MTTF of 200.000 hours, MTTR of 1 hour, partiy group size 16  mean time to failure of the system is about 3000 years !!! 26
  • 27. Reliability  Basic Reliability  RAID 6    MTTF: mean time to failure, MTTR: mean time to repair N: total number of disks, G: parity group size 100 disks each had MTTF of 200.000 hours, MTTR of 1 hour, partiy group size 16  mean time to failure of the system is about 38.000.000 years !!! 27
  • 28. System Crashes and Parity Inconsistency  System crash: power failure, operator error, hardware breakdown, software crash etc.  Causes parity inconsistencies in both bit-interleaved and block-interleaved disk arrays  System crash may occur more frequently than disk failures  To avoid the loss of parity on system crashes, information sufficient to recover parity mus be logged on a non-volatile storage (nvram) before each write operation. 28
  • 29. Uncorrectable Bit Errors  What is bit error? It is unclear  Data is incorrectly written or magnetic media gradually damaged  Some manifacturers developed an approach; monitors the warnings given by disks and notifies an operator when it feels the disk is about to fail. 29
  • 30. Correlated Disk Failures  Environmental and manufacturing factors  Example: earthquake 30
  • 31. Reliability Revisited  Double disk failure  System crash followed by a disk failure  Disk failure followed by an uncorrectable bit error during reconstruction 31
  • 35. Implementation Considerations  Avoiding Stale Data  When a disk fails, failed disk must be marked as invalid. Invalid mark prevents user from reading corrupted data on the failed disk  When an invalid logical sector is reconstructed to a spare disk, the logical sector must be marked as valid. 35
  • 36. Implementation Considerations  Regenerating Parity after a System Crash  Before servicing any write request, the corresponding parity sectors must be marked inconsistent  When bringing a system up from a system crash, all inconsistent parity sectors must be regenerated 36
  • 37. Implementation Considerations  Operating with a Failed Disk  Demand reconstruction: access to a parity stripe with an invalid sector triggers reconstruction of the appropriate data immediately onto a spare disk. A background process scans the entire disk.  Parity sparing: before servicing a write request, the invalid sector is reconstructed and relocated to overwrite its corresponding parity sector 37
  • 39. Advanced Topics  Improving Small Write Performance for RAID Level 5  Declustered Parity  Exploiting On-Line Spare Disks  Data Striping in Disk Arrays  Performance and Reliability Modeling 39
  • 40. Improving Small Write Performance for RAID Level 5  Buffering and Caching  Write buffering (async writes): Collect small writes in a buffer and write as a large data  Read caching: reduce four I/O access to three, old data is read from cache 40
  • 41. Improving Small Write Performance for RAID Level 5  Floating Parity  Shortens the read-modify-write time  Many free blocks  New parity block is writted rotationally nearest unallocated block following the old parity block  Implemented on disk controller 41
  • 42. Improving Small Write Performance for RAID Level 5  Floating Parity  Shortens the read-modify-write time  Many free blocks  New parity block is writted rotationally nearest unallocated block following the old parity block  Implemented on disk controller 42
  • 43. Improving Small Write Performance for RAID Level 5  Parity Logging  Delaying the read of old parity and write of the new parity  Difference is temporarily logged  Logs are grouped together and large contiguous blocks are updated more efficiently 43
  • 44. Declustered Parity  Distributes the increased load uniformly over all disks 44
  • 45. Exploiting On-Line Spare Disks  Distributed Sparing 45
  • 46. Exploiting On-Line Spare Disks  Parity Sparing 46
  • 47. Data Striping in Disk Arrays  Disk positioning time is wasted work  Idle times are same as disk positioning  Data striping or interleaving is, distributing data among multiple disks.  Researchers work on data striping unit size to maximize the throughput 47
  • 48. Data Striping in Disk Arrays  P: average disk positioning time  X: average disk transfer rate  L: concurrency  Z: request size  N: array size in disks 48
  • 49. Performance and Reliability Modeling  Performance  Kim: response time equations  Kim & Tantawi: approximate service time equations  Chen & Towsley  Lee & Katz  Reliability  Markov 49
  • 50. Opportunities for Future Research  Experience with Disk Arrays  Interaction among New Organizations  Scalability, Massively Parallel Computers and Small Disks  Latency 50