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Data Structures and Algorithms - Chapter 9: Hashing pot

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Tiêu đề Hashing Pot
Trường học HCMUT
Chuyên ngành Data Structures and Algorithms
Năm xuất bản 2008
Thành phố Ho Chi Minh City
Định dạng
Số trang 54
Dung lượng 124,32 KB

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Size Binary Sequential Sequential Average Worst Case CSE Faculty - HCMUT 01 December 2008... Each key has only one address Cao Hoang Tru 6 CSE Faculty - HCMUT 01 December 2008... e Coll

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CSE Faculty - HCMUT

Cao Hoang Tru

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Basic Concepts

e Sequential search: O(n) | Requiring several

> key comparisons

Cao Hoang Tru 2 CSE Faculty - HCMUT 01 December 2008

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Size Binary Sequential Sequential

(Average) (Worst Case)

CSE Faculty - HCMUT 01 December 2008

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Each key has only one address

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e Collision: the location of the data to be inserted is

already occupied by the synonym data

Cao Hoang Tru

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CSE Faculty - HCMUT

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— Compact address space

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CSE Faculty - HCMUT 01 December 2008

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the address space (storage size) Is

as large as the key space

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160252 > 102

045128 > 051

19

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Spreading the data more evenly across the address space

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Pseudorandom

y=ax+c

For maximum efficiency, a and c should be prime numbers

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e Each collision resolution method can be used

pendently with each hash function

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number of filled elements

become more than 75% full

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hashing tends to cause data to group within the list

e As data are added and collisions are resolved,

= Clustering: data are unevenly distributed across the list

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Cao Hoang Tru

CSE Faculty - HCMUT

[9] [10] [11] [12] [13]

31 Q1 December 2008

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Collision Resolution

e Secondary clustering: data become grouped

along a collision path throughout a list

Insert Aj, Bo, Co, Dy 4, Ey, Fo

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e When a collision occurs, an unoccupiec

searched for placing the new element in

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Open Addressing

e Hash function:

h: U > {0, ., m — 1}

set of keys addresses

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Open Addressing

e Hash and probe function:

hp: Ux {0, ., m-— 1} > {0, ., m— 1}

set of keys probe numbers addresses

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CSE Faculty - HCMUT

Cao Hoang Tru

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CSE Faculty - HCMUT

Cao Hoang Tru

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Harry Eagle 166702 ——>

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Linear Probing

Hash Function

002

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Harry Eagle 166702 ——>

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Linear Probing

Hash Function

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— data tend to remain near their home address

(significant for disk addresses)

— quite simple to implement

— produces primary clustering

CSE Faculty - HCMUT Cao Hoang Tru

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POs

kiểu for"

— time required to square numbers

— produces secondary clustering

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K AY Ể

3V `

° The new address is a function of the collision

address and the key

newAddress = (collisionAddress + offset) MOD listSize

hp(k, i) = (hp(k, i-1) + [k/m]) MOD m

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Linked List Resolution

Cao Hoang Tru

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Vv Chris Walljasper (572556)

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Cao Hoang Tru

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linear probing

53 Q1 December 2008

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