RAID

COP 5611Advanced Operating Systems

Adapted from Andy Wang’s slides at FSU

Parallel Disk Access and RAID

One disk can only deliver data at its maximum rate

So to get more data faster, get it from multiple disks simultaneously

Saving on rotational latency and seek time

Utilizing Disk Access Parallelism

Some parallelism available just from having several disks

But not muchInstead of satisfying each access from one

disk, use multiple disks for each accessStore part of each data block on several

disks

Disk Parallelism Example

open(foo) read(bar) write(zoo)

FileSystem

Data Striping

Transparently distributing data over multiple disks

Benefits – Increases disk parallelism Faster response for big requests

Major parameters are number of disks and size of data interleaf

Fine-Grained Vs. Coarse-Grained Data Interleaving Fine grain data interleaving

+ High data rate for all requests But only one request per disk array Lots of time spent positioning

Coarse-grain data interleaving+ Large requests access many disks+ Many small requests handled at once Small I/O requests access few disks

Reliability of Disk Arrays

Without disk arrays, failure of one disk among N loses 1/Nth of the data

With disk arrays (fine grained across all N disks), failure of one disk loses all data

N disks 1/Nth as reliable as one disk

Adding Reliability to Disk Arrays

Buy more reliable disksBuild redundancy into the disk array

Multiple levels of disk array redundancy possible

Most organizations can prevent any data loss from single disk failure

Basic Reliability Mechanisms

Duplicate dataParity for error detectionError Correcting Code for detection and

correction

Parity Methods

Can use parity to detect multiple errors But typically used to detect single error

If hardware errors are self-identifying, parity can also correct errors

When data is written, parity must be written, too

Error-Correcting Code

Based on Hamming codes, mostlyNot only detect error, but identify which bit

is wrong

RAID Architectures

Redundant Arrays of Independent DisksBasic architectures for organizing disks

into arraysAssuming independent control of each

diskStandard classification scheme divides

architectures into levels

Non-Redundant Disk Arrays (RAID Level 0)

No redundancy at allSo, what we just talked aboutAny failure causes data loss

Non-Redundant Disk Array Diagram (RAID Level 0)

open(foo) read(bar) write(zoo)

FileSystem

Mirrored Disks (RAID Level 1)

Each disk has second disk that mirrors its contents Writes go to both disks No data striping

+ Reliability is doubled

+ Read access faster

- Write access slower

- Expensive and inefficient

Mirrored Disk Diagram (RAID Level 1)

open(foo) read(bar) write(zoo)

FileSystem

Memory-Style ECC (RAID Level 2)

Some disks in array are used to hold ECCE.g., 4 data disks require 3 ECC disks

+ More efficient than mirroring

+ Can correct, not just detect, errors

- Still fairly inefficient

Memory-Style ECC Diagram (RAID Level 2)

open(foo) read(bar) write(zoo)

FileSystem

Bit-Interleaved Parity (RAID Level 3)

Each disk stores one bit of each data block

One disk in array stores parity for other disks

+ More efficient that Levels 1 and 2

- Parity disk doesn’t add bandwidth

- Can’t correct errors

Bit-Interleaved RAID Diagram (Level 3)

open(foo) read(bar) write(zoo)

FileSystem

Block-Interleaved Parity (RAID Level 4)

Like bit-interleaved, but data is interleaved in blocks of arbitrary size Size is called striping unit Small read requests use 1 disk

+ More efficient data access than level 3

+ Satisfies many small requests at once

- Parity disk can be a bottleneck

- Small writes require 4 I/Os

Block-Interleaved Parity Diagram (RAID Level 4)

open(foo) read(bar) write(zoo)

FileSystem

Block-Interleaved Distributed-Parity (RAID Level 5)

Sort of the most general level of RAIDSpread the parity out over all disks+ No parity disk bottleneck+ All disks contribute read bandwidth– Requires 4 I/Os for small writes

Block-Interleaved Distributed-Parity Diagram (RAID Level 5)

open(foo) read(bar) write(zoo)

FileSystem

Where Did RAID Look For Performance Improvements?Parallel use of disks

Improve overall delivered bandwidth by getting data from multiple disks

Biggest problem is small write performance

But we know how to deal with small writes . . .