CS5226 2002 Hardware Tuning Xiaofang Zhou School of Computing, NUS Office: S16-08-20 Email: [email protected] URL: zxf.

CS5226 2002

Hardware Tuning

Xiaofang ZhouSchool of Computing, NUS

Office: S16-08-20Email: [email protected]: www.itee.uq.edu.au/~zxf

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Outline

Part 1: Tuning the storage subsystem RAID storage system Choosing a proper RAID level

Part 2: Enhancing the hardware configuration

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Modern Storage Subsystem

More than just a disk Disks, or disk arrays Connections between disks and

processors Software to manage and config.

devices A logical volume for multiple devices A file system to manage data layout

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RAID Storage System Redundant Array of Inexpensive

Disks Combine multiple small, inexpensive

disk drives into a group to yield performance exceeding that of one large, more expensive drive

Appear to the computer as a single virtual drive

Support fault-tolerant by redundantly storing information in various ways

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Data Striping

Disk 2 Disk 3 Disk 4 Disk 5 Disk 6Disk 1

1 2 3 4 5 6 7 8 9 10 11 …

File blocks (e.g., 8KB per block)

Stripe unit: blocks 1-6, 7-12, …

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Parity Check - Classical An extra bit added to a byte to reveal

errors in storage or transmission Even (odd) parity means that the parity

bit is set so that there are an even (odd) number of one bits in the word, including the parity bit

A single parity bit can only reveal single bit errors since if an even number of bits are wrong then the parity bit will not change

It is not possible to tell which bit is wrong

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Parity Check - Checksum A computed value based on the content

of a block of data Transmitted or stored along with the data to

detect data corruption Recomputed at the receiver end to compare with

the one received Detects all errors with old bits of errors, and most

errors with event number of bits It is computed by summing the bytes of the

data block ignoring overflow Other parity check methods, such as

Hamming Code, corrects errors

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RAID Types Five types of array architectures, RAID 1 ~

5 Different disk fault-tolerance Different trade-offs in features and performance

A non-redundant array of disk drives if often referred to RAID 0

Only RAID 1, 3 and 5 are commonly used RAID 2 and 4 do not offer any significant

advantages over these other types Certain combination is possible (10, 35 etc)

RAID 10 = RAID 1 + RAID 0

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RAID 0 - Striping No redundancy

No fault tolerance High I/O performance

Parallel I/O

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RAID 1 – Mirroring Provide good fault tolerance

Works ok if one disk in a pair is down One write = a physical write on each disk One read = either read both or read the less busy one

Could double the read rate

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RAID 3 - Parallel Array with Parity Fast read/write

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RAID 5 – Parity Checking For error correction, rather than full

redundancy Each stripe unit has an extra parity stripe

Parity stripes are distributed

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RAID 5 Read/Write Read: parallel stripes read from multiple

disks Good performance

Write: 2 reads + 2 writes Read old data stripe; read parity stripe (2 reads) XOR old data stripe with replacing one. Take result of XOR and XOR with parity stripe. Write new data stripe and new parity stripe (2

writes).

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RAID 10 – Striped Mirroring RAID 10 = Striping + mirroring

An striped array of RAID 1 arrays High performance of RAID 0, and high tolerance of

RAID 1 (at the cots of doubling disks)

.. More information about RAID disks at http://www.acnc.com/04_01_05.html

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Comparing RAID LevelsRAID 0 RAID 1 RAID 5 RADI 10

Read High 2X High High

Write High 1X Medium High

Fault tolerance

No Yes Yes Yes

Disk utilisation

High Low High Low

Key problems

All data lost when one disk fails

Use twice disk space

Lower throughput with disk failure

Very expensive, not scalable

Key advantages

High I/O performance

Very high I/O performance

A good overall balance

High reliability with good performance

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What RAID Provides Fault tolerance

It does not prevent disk drive failures It enables real-time data recovery

High I/O performance Mass data capacity Configuration flexibility Lower protected storage costs Easy maintenance

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Hardware vs. Software RAID Software RAID

Software RAID: run on the server’s CPU Directly dependent on server CPU performance and

load Occupies host system memory and CPU operation,

degrading server performance Hardware RAID

Hardware RAID: run on the RAID controller’s CPU Does not occupy any host system memory. Is not

operating system dependent Host CPU can execute applications while the array

adapter's processor simultaneously executes array functions: true hardware multi-tasking

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RAID Levels - Data

Settings:accounts( number, branchnum, balance);create clustered index c on accounts(number);

100000 rows Cold Buffer Dual Xeon (550MHz,512Kb), 1Gb RAM,

Internal RAID controller from Adaptec (80Mb), 4x18Gb drives (10000RPM), Windows 2000.

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RAID Levels - Transactions

No Concurrent Transactions: Read Intensive: select avg(balance) from accounts;

Write Intensive, e.g. typical insert:insert into accounts values (690466,6840,2272.76);

Writes are uniformly distributed.

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RAID Levels SQL Server7 on

Windows 2000 (SoftRAID means striping/parity at host)

Read-Intensive: Using multiple disks

(RAID0, RAID 10, RAID5) increases throughput significantly.

Write-Intensive: Without cache, RAID 5

suffers. With cache, it is ok.

Write-Intensive

0

40

80

120

160

Soft-RAID5

RAID5 RAID0 RAID10 RAID1 SingleDisk

Th

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t (t

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Read-Intensive

0

20000

40000

60000

80000

Soft-RAID5

RAID5 RAID0 RAID10 RAID1 SingleDisk

Th

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sec)

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Which RAID Level to Use? Log File

RAID 1 is appropriate Fault tolerance with high write throughput. Writes are

synchronous and sequential. No benefits in striping. Temporary Files

RAID 0 is appropriate. No fault tolerance. High throughput.

Data and Index Files RAID 5 is best suited for read intensive apps or

if the RAID controller cache is effective enough. RAID 10 is best suited for write intensive apps.

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Controller Prefecthing No, Write-back Yes Read-ahead:

Prefetching at the disk controller level. No information on access pattern. Better to let database management system

do it. Write-back vs. write through:

Write back: transfer terminated as soon as data is written to cache.

Batteries to guarantee write back in case of power failure

Write through: transfer terminated as soon as data is written to disk.

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SCSI Controller Cache - Data

Settings:employees(ssnum, name, lat, long, hundreds1,hundreds2);

create clustered index c on employees(hundreds2);

Employees table partitioned over two disks; Log on a separate disk; same controller (same channel).

200 000 rows per table Database buffer size limited to 400 Mb. Dual Xeon (550MHz,512Kb), 1Gb RAM, Internal RAID

controller from Adaptec (80Mb), 4x18Gb drives (10000RPM), Windows 2000.

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SCSI (not disk) Controller Cache - Transactions

No Concurrent Transactions:update employees set lat = long, long = lat where hundreds2 = ?;

cache friendly: update of 20,000 rows (~90Mb) cache unfriendly: update of 200,000 rows (~900Mb)

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SCSI Controller Cache SQL Server 7 on Windows

2000. Adaptec ServerRaid

controller: 80 Mb RAM Write-back mode

Updates Controller cache

increases throughput whether operation is cache friendly or not.

Efficient replacement policy!

2 Disks - Cache Size 80Mb

0

500

1000

1500

2000

cache friendly (90Mb) cache unfriendly (900Mb)

Th

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/se

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no cache

cache

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Enhancing Hardware Config. Add memory

Cheapest option to get a better performance

Can be used to enlarge DB buffer pool Better hit ratio If used for enlarge OS buffer (as disk

cache), it benefits but to other apps as well Add disks Add processors

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Add Disks Larger disk ≠better performance

Bottleneck is disk bandwidth Add disks for

A dedicated disk for the log Switch RAID5 to RAID10 for update-intensive

apps Move secondary indexes to another disk for

write-intensive apps Partition read-intensive tables across many

disks Consider intelligent disk systems

Automatics replication and load balancing

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Add Processors Function parallelism

Use different processors for different tasks GUI, Query Optimisation, TT&CC, different types

of apps, different users Operation pipelines:

E.g., scan, sort, select, join…

Easy for RO apps, hard for update apps Data partition parallelism

Partition data, thus the operation on the data

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Parallel Join Processing Algorithm: decompose and processing in

parallel T = R S Let f: A (1..n) (a hash function) R = i=1..n Ri, Ri = {r R | f(r.A) = i} S = i=1..n Si, Si = {s S | f(s.A) = i} T = i=1..n Ri Si

Issues However, data distribution, task decomposition

and load balancing are non-trivial

A

A

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Parallelism

Some tasks are easier to be parallelised E.g., scan, join, sum, min

Some tasks are not so easy E.g., sorting, avg, nested-queries

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Parallel DB Architectures Shared memory

Tightly coupled, easy-to-use, but not scalable (bottlenecks when accessing shared memory and disks)

Shared nothing A distributed with message-passing as the

only communication mechanism Highly scalable Difficult for load distribution and balancing

Shared disk A trade-off, but towards the shared-memory

end

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Summary

In this module, we have covered: The storage subsystem

RAID: what are they and which one to use?

Memory, disks and processors When to add what?