Elmasri 6e Ch17 Week2 HW DiskStorage

8/10/2019 Elmasri 6e Ch17 Week2 HW DiskStorage

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Chapter 17

Disk Storage, BasicFile Structures, andHashing


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Disk Storage Devices

Preferred secondary storage device for highstorage capacity and low cost.

Data stored as magnetized areas on magnetic

disk surfaces. A diskpackcontains several magnetic disks

connected to a rotating spindle.

Disks are divided into concentric circular tracks

on each disk surface. Track capacities vary typically from 4 to 50 Kbytes

or more


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Typical Hard Drive Platter,Head,

ActuatorCylinder,

Track

Sector (physical),

Block (logical),

Gap


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Top View


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Typical Numbers

Diameter: 1 inch 15 inches

Cylinders: 100 2000

Surfaces: 1 (CDs)

(Tracks/cyl) 2 (floppies) 30

Sector Size: 512B 50K

Capacity: 360 KB (old floppy)

1 TB


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Goal

How to lay out data on disk

How to move it to/from memory

I want

block X

block x

in memory


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Seek Time: S


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Average Random Seek Time: S

TypicalS: 10 ms 40 ms


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Rotational Delay: R

R = 1/2

revolution

typical

R = 8.33 ms(3600 RPM)


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Transfer Rate: t

typical t: 10s 100s MB/second

transfer time: block size / t


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Other Delays

CPU time to issue I/O

Contention for controller

Contention for bus, memory

Typical Value: 0


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Buffering: Single Buffer

Single Buffer

(1) Read B1 Buffer

(2) Process Data in Buffer

(3) Read B2 Buffer

(4) Process Data in Buffer ...

Say:

P = time to process/block

R = time to read in 1 blockn = # blocks

Single buffer time = n(P+R)


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Buffering: Double Buffering


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Buffering: Double Buffering

Say P R

P = Processing time/block

R = IO time/block

n = # blocks

Double buffering time = R + nP

Single buffering time = n(R+P)


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Disk Storage Devices (cont.)

A track is divided into smaller blocksor sectors

because it usually contains a large amount of information

The division of a track into sectorsis hard-coded on the

disk surface and cannot be changed.

A track is divided into blocks.

The block size B is fixed for each system.

Typical block sizes range from B=512 bytes to B=4096 bytes.

Whole blocks are transferred between disk and main

memory for processing.


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A read-write headmoves to the track that contains theblock to be transferred. Disk rotation moves the block under the read-write head for

reading or writing.

A physical disk block (hardware) address consists of:

a cylinder number (imaginary collection of tracks of same radius from all recorded

surfaces)

the track number or surface number (within the cylinder)

and block number (within track).

Reading or writing a disk block is time consumingbecause of the seek time sand rotational delay (latency)rd.

Double buffering can be used to speed up the transfer ofcontiguous disk blocks.


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What are the data items we want to

store?

a salary

a name

a date

a picture

What we have available: Bytes


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00000000

To represent

Integer(short): 2 bytes

e.g., 35 is

Characters

various coding schemes suggested, most

popular is ASCII (1 byte encoding) Example:

A: 1000001

a: 1100001

5: 0110101

Boolean

TRUE FALSE

00100011

0000 00001111 1111


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To represent

Dates

Integer, # days since Jan 1, 1900

8 characters, YYYYMMDD

Time Integer, seconds since midnight

characters, HHMMSSFF

Stringof characters

Null terminated Length given

Fixed length


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Records

Fixed length records

Variable length records

usually length given at beginning

Record- Collection of related data items (called

FIELDS) E.g.: Employee record:

name field,

salary field, date-of-hire field, ...


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Record Types

FIXED vs VARIABLE FORMAT

A SCHEMA (not record) contains following

information

# fields type of each field

order in record

meaning of each field


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Record Types: Example: fixed format and length

Employee record

(1) E#, 2 byte integer

(2) E.name, 10 char. Schema

(3) Dept, 2 byte code


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Record Types : Variable format

Record itself contains format Self Describing


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Record Types : Variable format

Variable format useful for

sparse records

repeating fields

evolving formats

EXAMPLE: var format record with repeating fields

Employee one or more children

Key is to allocate maximum number of repeating

fields (if not used null)


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Record header

data at beginning that describes record and may

contain:

record type

record length time stamp

null-value bitmap

Record header has a bitmap to store whether fieldis NULL

Only store non-NULL fields in record

other stuff ...


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Separate Storage of Large Values

Store fields with large values separately

E.g., image or binary document

Records have pointers to large field content


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Goal Data Items

Records

Blocks

Files

Memory

Key Point Fixedlength items

Variablelength items

usually length given at

beginning

Also Type of an item:Tells us how to interpret

(plus size if fixed)


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placing records into blocks


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Options for storing records in blocks:

(1) separating records

(2) spanned vs. unspanned

(3) sequencing

(4) indirection


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Records

Fixed and variable length records

Records contain fields which have values of aparticular type

E.g., amount, date, time, age Fields themselves may be fixed length or variable

length

Variable length fields can be mixed into one

record: Separator characters or length fields are needed

so that the record can be parsed.


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Separating records

Block

1. no need to separate - fixed size recs.

2. special marker

3. give record lengths (or offsets) within each record

in block header


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Blocking

Blocking:

Refers to storing a number of records in one blockon the disk.

Blocking factor (bfr) refers to the number ofrecords per block.

There may be empty space in a block if anintegral number of records do not fit in one block.

Spanned Records: Refers to records that exceed the size of one or

more blocks and hence span a number of blocks.


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Files of Records

A fileis a sequenceof records, where each record is a

collection of data values (or data items).

A file descriptor(or file header) includes information that

describes the file, such as the field namesand their data

types, and the addresses of the file blocks on disk.

Records are stored on disk blocks.

The blocking factorbfrfor a file is the (average) number

of file records stored in a disk block.

A file can have fixed-lengthrecords or variable-length

records.


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Files of Records (cont.)

File records can be unspannedor spanned

Unspanned: no record can span two blocks

Spanned: a record can be stored in more than one block

The physical disk blocks that are allocated to hold the

records of a file can be contiguous, linked, or indexed. In a file of fixed-length records, all records have the same

format.

Usually, unspanned blocking is used with such files.

Files of variable-length records require additionalinformation to be stored in each record, such asseparatorcharactersand field types.

Usually spanned blocking is used with such files.


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Spanned vs. Unspanned

Unspanned: records must be within one block

Spanned


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With spanned records:

Unspanned is much simpler, but may waste space

Spanned essential if

record size > block size


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Operation on Files Typical file operations include:

OPEN: Readies the file for access, and associates a pointer that will refer

to a currentfile record at each point in time. FIND: Searches for the first file record that satisfies a certain condition, and

makes it the current file record.

FINDNEXT: Searches for the next file record (from the current record) thatsatisfies a certain condition, and makes it the current file record.

READ: Reads the current file record into a program variable.

INSERT: Inserts a new record into the file & makes it the current filerecord.

DELETE: Removes the current file record from the file, usually by markingthe record to indicate that it is no longer valid.

MODIFY: Changes the values of some fields of the current file record.

CLOSE: Terminates access to the file.

REORGANIZE: Reorganizes the file records.

For example, the records marked deleted are physically removed fromthe file or a new organization of the file records is created.

READ_ORDERED: Read the file blocks in order of a specific field of thefile.


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Unordered Files

Also called a heapor a pilefile.

New records are inserted at the end of the file.

A linear searchthrough the file records is

necessary to search for a record. This requires reading and searching half the file

blocks on the average, and is hence quite

expensive.

Record insertion is quite efficient.

Reading the records in order of a particular field

requires sorting the file records.


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Ordered Files: Sequencing

Also called a sequentialfile.

File records are kept sorted by the values of an orderingfield.

Insertion is expensive: records must be inserted in the correct order.

It is common to keep a separate unordered overflow(ortransaction) file for new records to improve insertion efficiency;

this is periodically merged with the main ordered file. A binary searchcan be used to search for a record on its ordering

fieldvalue.

This requires reading and searching log2of the file blocks on theaverage, an improvement over linear search.

Reading the records in order of the ordering field is quite efficient.

Ordered Files (cont )


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Ordered Files (cont.)

Sequencing Options

1. Next record physically

contiguous

2. Linked

3. Overflow area


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Indirection

How does one refer to records?

Many options:

Physical Indirect


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Indirection: identifying a record

1. Purely Physical

E.g., Record Address or ID =

Device ID

Cylinder #

Track #

Block # Offset in block

Block ID


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Indirection: identifying a record

2. Fully Indirect

Record ID is arbitrary bit string


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Block header

data at beginning that describes block

May contain:

File ID (or RELATION or DB ID)

This block ID

Record directory

Pointer to free space

Type of block (e.g. contains recs type 4; isoverflow, )

Pointer to other blocks like it

Timestamp ...


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Example: Indirection in block


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Tuple Identifier (TID)

TID is

Page identifier

Slot number

Slot stores either record or pointer (TID)

TID of a record is fixed for all time


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TID Operations

Insertion

Set TID to record location (page, slot)

Moving record

e.g., update variable-size or reorganization Case 1: TID points to record

Replace record with pointer (new TID)

Case 2: TID points to pointer (TID)

Replace pointer with new pointer


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TID: Block 1, Slot 2


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TID: Block 1, Slot 2 unchanged

Move record to

Block 2 slot 3 -> TID does not change!


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TID: Block 1, Slot 2 unchanged

Move record to

Block 2 slot 2-> TID does not change!


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TID Properties

TID of record never changes

Can be used safely as pointer to record

(e.g., in index)

At most one level of indirection Relatively efficient

Changes to physical addresschanging max 2

pages


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Average Access Times

The following table shows the average access

time to access a specific record for a given type

of file


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Options for storing records in blocks

We covered

(1) separating records

(2) spanned vs. unspanned

(3) sequencing(4) indirection


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Now what?

Insertion of new record

Deletion of existing records

Buffer management

Deletion


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Block

Options:

Immediately reclaim space

Mark deleted

May need chain of deleted records (for re-use)

Need a way to mark:

special characters

delete field

in map

Tradeoffs

How expensive?

How much space wasted


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Concern with deletions

Dangling pointers

Options

Who cares?

Tombstones E.g., Leave MARK in map or old location

Physical IDs


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Concern with deletions

Dangling pointers

Option#1: Who cares?

Option#2: Tombstones

E.g., Leave MARK in map or old location (1) Physical IDs

(2) Logical IDs


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Insert

Easy case: records not in sequence

Insert new record at end of file or in deleted slot

If records are variable size, not as easy...

Hard case: records in sequence

If free space close by, not too bad...

Or use overflow idea...


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Interesting problems:

How much free space to

leave in each block,

track, cylinder?

How often do Ireorganize file +

overflow?


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BUFFER MANAGEMENT

Buffer manager intelligently shuffles data from main memory to disk:

It is transparent to higher levels of DBMS operation


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Buffer Management in a DBMS

Data must be in RAM for DBMS to operate on it!

Table of pairs ismaintained

DB

MAIN MEMORY

DISK

disk page

free frame

Page Requests from Higher Levels

BUFFER POOL

choice of frame dictated

by replacement policy

READWRITE

INPUT

OUTUPT


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When a page is requested

Apageis the unit of memory we request

If Page in the pool

Great no need to go to disk!

If not? Choose a frame to replace.

If there is a free frame, use it!

Terminology: We pin a page (means its in use)

If not? We need to choose a page to remove! How DBMS makes choice is a replacement

policy


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Buffer Manager

Manages blocks (pages) cached from disk in

main memory

Usually -> fixed size buffer (M pages)

DB requests page from Buffer Manager Case 1: page is in memory -> return address

Case 2: page is on disk -> load into memory,

return address


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Buffer Manager: Goal

Reduce the amount of I/O

Maximize the hit rate

Ratio of number of page accesses that are fulfilled

without reading from disk -> Need strategy to decide when to load from disk

and what to remove from the buffer


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Once we choose a page to remove

A page is dirty, if its contents have been changed

after writing

Buffer Manager keeps a dirty bit

Say we choose to evict P

If P is dirty, we write it to disk

If P is not dirty, then what?

Buffer Manager Organization


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Buffer Manager Organization Bookkeeping

Need to map (hash table) page-ids to locations in buffer (page

frames) Per page store fix count, dirty bit,

Manage free space

Replacement strategy

If page is requested but buffer is full Which page to emit remove from buffer???

FIFO

LRU

Clock

LRU-K GCLOCK

Clock-Pro

ARC

LFU


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FIFO

First In, First Out

Replace page that has been in the buffer for the

longest time

Implementation: E.g., pointer to oldest page(circular buffer)

Simple, but not prioritizing frequently accessedpages


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LRU

Least Recently Used

Replace page that has not been accessed for the

longest time

Implementation:

List, ordered by LRU

Access a page, move it to list tail

Widely applied and reasonable performance


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Least Recently Used (LRU)

Order pages by the time of last accessed Always replace the least recently accessed

P5, P2, P8, P4, P1, P9, P6, P3, P7

Access P6

P6, P5, P2, P8, P4, P1, P9, P3, P7


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Clock

Frames are organized clock-wise

Pointer S to current frame

Each frame has a reference bit

Page is loaded or accessed -> bit = 1

Find page to replace (advance pointer)

Return first frame with bit = 0

If current is referenced, then unset ref bit andmove on

On the way set all bits to 0

Whenever a bit is referenced, set the bit


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Simplified Buffer Manager Flowchart

Request a Page

Find a page P that is

unpinned according to policy.

Return Frame

handle to caller

Flush P to

Disk

Dirty


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ROW VS COLUMN STORE


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Row vs. Column Store

So far we assumed that fields of a record arestored contiguously (row store)...

Another option is to store all values of a field

together (column store)


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Row Store

Example: Order consists of

id, cust, prod, store, price, date, qty


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Column Store

Example: Order consists of

id, cust, prod, store, price, date, qty


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Row vs Column Store

Advantages of Column Store

more compact storage (fields need not start at

byte boundaries)

Efficient compression, efficient reads on data mining operations

Advantages of Row Store

writes (multiple fields of one record) more efficient

efficient reads for record access (OLTP)


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HASHING


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Hashed Files

Hashing for disk files is called External Hashing The file blocks are divided into M equal-sized buckets, numbered

bucket0, bucket1, ..., bucketM-1.

Typically, a bucket corresponds to one (or a fixed number of) diskblock.

One of the file fields is designated to be the hash keyof the file. The record with hash key value K is stored in bucket i, where i=h(K),

and h is the hashing function.

Search is very efficient on the hash key.

Collisions occur when a new record hashes to a bucket that is already

full. An overflow file is kept for storing such records.

Overflow records that hash to each bucket can be linked together.


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Hashed Files (cont.)

There are numerous methods for collision resolution, including thefollowing:

Open addressing: Proceeding from the occupied positionspecified by the hash address, the program checks thesubsequent positions in order until an unused (empty) position isfound.

Chaining: For this method, various overflow locations are kept,usually by extending the array with a number of overflowpositions. In addition, a pointer field is added to each recordlocation. A collision is resolved by placing the new record in anunused overflow location and setting the pointer of the occupiedhash address location to the address of that overflow location.

Multiple hashing: The program applies a second hash function ifthe first results in a collision. If another collision results, theprogram uses open addressing or applies a third hash functionand then uses open addressing if necessary.

Hashed Files (cont )


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To reduce overflow records, a hash file is typicallykept 70-80% full.

The hash function h should distribute the recordsuniformly among the buckets

Otherwise, search time will be increased becausemany overflow records will exist.

Main disadvantages of static external hashing:

Fixed number of buckets M is a problem if thenumber of records in the file grows or shrinks.

Ordered access on the hash key is quite inefficient(requires sorting the records).

Hashed Files - Overflow Handling


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Dynamic And Extendible Hashed


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Files

Dynamic and Extendible Hashing Techniques Hashing techniques are adapted to allow the dynamic

growth and shrinking of the number of file records.

These techniques include the following:dynamic hashing,

extendible hashing, andlinear hashing. Both dynamic and extendible hashing use the binary

representationof the hash value h(K) in order to access

a directory.

In dynamic hashing the directory is a binary tree. In extendible hashing the directory is an array of size 2d

where d is called the global depth.

Dynamic And Extendible Hashing


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(cont.)

The directories can be stored on disk, and they expand orshrink dynamically. Directory entries point to the disk blocks that contain the

stored records.

An insertion in a disk block that is full causes the block to

split into two blocks and the records are redistributedamong the two blocks. The directory is updated appropriately.

Dynamic and extendible hashing do not require anoverflow area.

Linear hashing does require an overflow area but doesnot use a directory. Blocks are split in linear orderas the file expands.

Extendible


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Hashing


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RAID

Parallelizing Disk Access using RAID


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Technology.

Secondary storage technology must take steps tokeep up in performance and reliability withprocessor technology.

A major advance in secondary storage

technology is represented by the development ofRAID, which originally stood for RedundantArrays of Inexpensive Disks.

The main goal of RAID is to even out the widely

different rates of performance improvement ofdisks against those in memory andmicroprocessors.

RAID Technology (cont )


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RAID Technology (cont.)

A natural solution is a large array of small independent

disks acting as a single higher-performance logical disk. A concept called data stripingis used, which utilizes

parallelism to improve disk performance.

Data striping distributes data transparently over multipledisks to make them appear as a single large, fast disk.


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RAID Technology (cont.)

Different raid organizations were defined based on differentcombinations of the two factors of granularity of data interleaving(striping) and pattern used to compute redundant information.

Raid level 0 has no redundant data and hence has the best writeperformance at the risk of data loss

Raid level 1 uses mirrored disks.

Raid level 2 uses memory-style redundancy by using Hammingcodes, which contain parity bits for distinct overlapping subsets ofcomponents. Level 2 includes both error detection and correction.

Raid level 3 uses a single parity disk relying on the disk controllerto figure out which disk has failed.

Raid Levels 4 and 5 use block-level data striping, with level 5

distributing data and parity information across all disks. Raid level 6 applies the so-called P + Q redundancy scheme

using Reed-Soloman codes to protect against up to two diskfailures by using just two redundant disks.

Use of RAID Technology (cont.)


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gy ( )

Different raid organizations are being used under different situations

Raid level 1 (mirrored disks) is the easiest for rebuild of a disk from

other disks It is used for critical applications like logs

Raid level 2 uses memory-style redundancy by using Hammingcodes, which contain parity bits for distinct overlapping subsets ofcomponents. Level 2 includes both error detection and correction.

Raid level 3 (single parity disks relying on the disk controller to figureout which disk has failed) and level 5 (block-level data striping) arepreferred for Large volume storage, with level 3 giving higher transferrates.

Most popular uses of the RAID technology currently are:

Level 0 (with striping), Level 1 (with mirroring) and Level 5 with an

extra drive for parity. Design Decisions for RAID include:

Level of RAID, number of disks, choice of parity schemes, andgrouping of disks for block-level striping.

Use of RAID Technology (cont.)


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Storage Area Networks

The demand for higher storage has risen considerably inrecent times.

Organizations have a need to move from a static fixeddata center oriented operation to a more flexible anddynamic infrastructure for information processing.

Thus they are moving to a concept of Storage AreaNetworks (SANs).

In a SAN, online storage peripherals are configured asnodes on a high-speed network and can be attached and

detached from servers in a very flexible manner. This allows storage systems to be placed at longer

distances from the servers and provide differentperformance and connectivity options.


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Storage Area Networks (cont.)

Advantages of SANs are: Flexible many-to-many connectivity among servers and

storage devices using fiber channel hubs and switches.

Up to 10km separation between a server and a storage

system using appropriate fiber optic cables. Better isolation capabilities allowing non-disruptive addition

of new peripherals and servers.

SANs face the problem of combining storage options from

multiple vendors and dealing with evolving standards ofstorage management software and hardware.

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Elmasri 6e Ch17 Week2 HW DiskStorage