Basics of Hash Table--Data Structure

Intro:

API: Python: Dict; JAVA: HashMap

Applications: File Systems; Password Verification; Store Optimization

IP Address:

Main Loop

log - array of log lines(time,IP)
C - mapping from IPs to counters
i - first unprocessed log line
j - first line in current 1h window

i←0

j←0
C←∅
Each second

UpdateAccessList

(log, i, j, C)

UpdateAccessList(log, i, j, C)

while log[i].time≤ Now():

C[log[i].IP]← C[log[i].IP] + 1

i←i+1

while log[j].time≤ Now()− 3600:

C[log[j].IP]← C[log[j].IP]− 1

j←j+1

AccessedLastHour(IP, C)

return C[IP]> 0

Direct Addressing

Need a data structure for

C
There are 232different IP(v4) addresses

Convert IP to 32-bit integer
Create an integer array A of size 232

Use A[int(IP)]as C[IP]

int(IP)

return IP[1]·224+IP[2]·216+IP[3]·28+IP[4]

UpdateAccessList(log, i, j, A)

while log[i].time≤ Now():

A[int(log[i].IP)]← A[int(log

[i].IP)] + 1

i←i+1

while log[j].time≤ Now()− 3600:

A[int(log[j].IP)]← A[int(log[j].IP)]− 1

j←j+1

AccessedLastHour(IP)

return A[int(IP)]> 0

Asymptotics

UpdateAccessListis O(1)per log line

AccessedLastHouris O(1)
But need 232memory even for few IPs

IPv6: 2128won’t fit in memory

In general: O(N)memory, N= |S|

List-based Mapping：

Direct addressing requires too much memory

Let’s store only active IPs
Store them in a list
Store only last occurrence of each IP

Keep the order of occurrence

UpdateAccessList(log, i, L)

while log[i].time≤ Now():

log_line← L.FindByIP(log[i].IP)

if log_line！=NULL:

L.Erase(log_line)

L.Append(log[i])

i←i+1

while L.Top().time≤ Now()− 3600:

L.Pop()

AccessedLastHour(IP, L)

return L.FindByIP(IP)！=NULL

Asymptotics

n is number of active IPs
Memory usage is Θ(n)
L.Append,L.Top,L.Popare Θ(1)

L.Findand L.Eraseare Θ(n)

UpdateAccessListis Θ(n)per log line

AccessedLastHouris Θ(n)

Encoding IPs

Encode IPs with small numbers
I.e. numbers from 0 to 999
Different codes for currently active IPs

Hash Function

De nition

For any set of objectsS and any integer
m >0, a function h: S→ {0,1,...,m−1}is called a hash function.

De nition

m is called thecardinality of hash function h.

Desirable Properties

h should be fast to compute.

Different values for different objects.

Direct addressing withO(m)memory.

Want small cardinalitym.

Impossible to have all different values ifnumber of objects|S|is more than m.

Collisions

De nition

When h(o1) = h(o2)and o1̸=o2, this is acollision.

Map

Store mapping from objects to other objects:

Filename → location of the file on disk

Student ID → student name
Contact name → contact phone number

Definition

Map from S to V is a data structure with methodsHasKey(O),Get(O),Set(O,v),whereO ∈S,v∈ V.

h :S → {0,1, . . . ,m −1}
O,O′∈S
v,v′∈V
A ← array ofm lists (chains) of pairs(O,v)

HasKey(O)

L ←A[h(O)]
for (O′,v′)in L:

if O′== O:

return true

return false

Get(O)

L ←A[h(O)]
for (O′,v′)in L:

if O′== O:

return v′

return n/a

Set(O,v)

L ←A[h(O)]

for pin L:

if p.O== O:

p.v← v

return

L.Append(O, v)

Set

De nition

Set is a data structure with methodsAdd(O),Remove(O),Find(O).

Examples

IPs accessed during last hourStudents on campus
Keywords in a programming language

h :S → {0,1, . . . ,m −1}
O,O′∈S
A ← array ofm lists (chains) of objectsO

Find(O)

L ←A[h(O)]

for O′in L:

if O′== O:

return true

return false

Add(O)

L ←A[h(O)]

for O′in L:

if O′== O:

return

L.Append(O)

Remove(O)

if not Find(O):

return

L ←A[h(O)]

L.Erase(O)

Hash Table:

Definition

An implementation of a set or a map usinghashing is called a hash table.

Programming Language:

Set:

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