COMPSCI4094- Bond Energy Alg Solved

The assignment
In this assignment you are required to implement the Bond Energy Algorithm of vertical fragmentation. Your code should contains two separate procedures AA Generator and CA Generator, where AA Generator takes the input of all attributes of a relation, a set of queries and their access frequencies at different sites, and produces the output of an affinity matrix AA, and CA Generator takes input of an affinity matrix AA and produces a clustered affinity matrix CA. For description of the BEA algorithm, definitions of AA and CA, please see lecture slides/textbook.

In this assignment, the Attribute Affinity is measured by the extended Otsuka-Ochiai coefficient (https://en.wikipedia.org/wiki/Yanosuke Otsuka) instead of the traditional method described in the textbook. The following equations show the details of the computation, where n is the number of attributes, and m is the number of sites, Aik is the number of times Attribute Ai is accessed by Query qk, considering of all sites. For the result of division, you must round it up to the nearest integer.

 ,

 
S1
S2
S3
q1
15
20
10
q2
5
0
0
q3
25
25
25
q4
5
0
0
Example
For AA Generator:

Input

• The relation, called PROJ, has the following features Ai:

Label     Name A1             PNO A2                PNAME
A3         BUDGET A4              LOC

•    Queries (qi):

q1: SELECT BUDGET FROM PROJ WHERE PNO=Value q2: SELECT PNAME, BUDGET FROM PROJ q3: SELECT PNAME FROM PROJ WHERE LOC=Value q4: SELECT SUM(BUDGET) FROM PROJ WHERE LOC=Value

•    Access frequency matrix ACC, where Si denotes the i-th site:

Output

•    The attribute affinity matrix AA:

A1
A2
A3
A4
                                                                           A1     45
0
41
0
                                                                           A2     0
71
1
71
                                                                           A3     41
1
38
1
                                                                           A4     0

For CA Generator:

Input

• The attribute affinity matrix AA:
71
1
71
A1
A2
A3
A4
                                                                           A1     45
0
41
0
                                                                           A2     0
71
1
71
                                                                           A3     41
1
38
1
                                                                           A4     0

Output

• The attribute affinity matrix CA:
71
1
71
A1
A3
A4
A2
                                                                           A1     45
41
0
0
                                                                           A3     41
38
1
1
                                                                           A4     0
1
71
71
                                                                           A2     0
1
71
71

•    Note:

i.        The auto-marker script compiles and runs the two cpp files named “AAGenera-tor.cpp” and “CAGenerator.cpp” one by one.

ii.      The auto-marker script will compile your AAGenerator.cpp and CAGenerator.cpp bythe following command:

g++ -std=c++11 AAGenerator.cpp -o runAA g++ -std=c++11 CAGenerator.cpp -o runCA

iii.    Your AAGenerator.cpp should accept three input text files in the order of Attributes(att), Queries (query) and Access Frequencies (acc), which are randomly generated by the system, then output and print the required attribute affinity matrix (aa). Your CAGenerator.cpp should accept input affinity matrix (aa) provided by the system rather than reading your AAGenerator’s output AA, then output and print the clustered affinity matrix (CA) as the output. In this way of testing AA and CA separately, your marks will be maximized — you will receive marks for your correct CAGenerator coding even if your AAGenerator produces incorrect AA.

iv.     The file path and the file name in your local machine will not work with our websub-mission system.