代写Database Development and Design (DTS207TC)代做Python语言

Database Development and Design (DTS207TC)

Assessment 001: Individual Coursework

Due: Dec 15th, 2024 @ 23:59 Weight: 60%

Maximum Marks: 100

Overview & Outcomes

This course work will be assessed for the following learning outcomes:

A. Identify and apply the principles underpinning transaction management within DBMS.

B. Demonstrate an understanding of advanced SQL topics.

E. State the main concepts in data warehousing and data mining.

Submission

You must submit the following files to LMO: 1)A report named as Your_Student_ID.pdf.

2)A directory containing all your source code, named as Your_Student_ID_code.

NOTE: The report shall be in A4 size, size 11 font, and shall not exceed 8 pages in length. You can include only key code snippets in your reports. The complete source code can be placed in the attachment.

Assessment Tasks

Matrix multiplication is a fundamental operation in linear algebra where two matrices are multiplied to produce a new matrix. Specifically, if we have two matrices A and B, the product  of these matrices, denoted as AB, is calculated by taking the dot product of the rows of A with the columns of B. For example, for two matrices of dimension 2x2, their matrix multiplication formula is

To test your proficiency in SQL under an open-book setting, this assignment requires you to implement matrix multiplication using SQL. It is divided into the following steps:

1)   The Python function in the attachment is capable of generating an N-dimensional square

matrix composed of random numbers in the format of (row_id, col_id, value). First, use a Python program to invoke this function and generate such a matrix, then import it into a table M in PostgreSQL. Additionally, discuss the impact of database transaction mechanisms on the performance of record insertion. Record the program running time (ideally, <10s) when N=500 and take a screenshot. (20 marks)

2)   Perform. a “pivot” operation on the table M from 1) (write the PL/pgSQL manually without using crosstab) to generate a data table A. You can design your own schema for table A,  but ensure that each row of the matrix is placed in a separate record. Note that N cannot be predetermined in the program. Provide a screenshot of the computation results when  N=3 and perform. a correctness check. Provide another screenshot of the running time (ideally, <1s) when N=500. (20 marks)

3)   Using PL/pgSQL, perform a matrix transposition on table A from 2) and store the results in another table with the same schema as A. Provide a screenshot of the computation results when N=3 and perform. a correctness check. Provide another screenshot of the running time (ideally, <1s) when N=500. (20 marks)

4)   Using PL/pgSQL, calculate the matrix multiplication of the matrix stored in table A from 2) with itself, and store the results in another table with the same schema as A. Provide a screenshot of the computation results when N=3 and perform. a correctness check. Provide another screenshot of the running time (ideally, <1 min) when N=500. (20 marks)

5)   For the above tasks 1-4, check the program's running time when N=1700. Provide

corresponding screenshots. The ideal running times should not exceed: 2 minutes for task 1, 10 seconds for task 2, 10 seconds for task 3, and 30 minutes for task 4. (20 marks)

NOTE:

a.    Provide a brief introduction to the program logic in your own words; including code snippets is encouraged, but please do not directly paste the entire program into the report without explanation;

b.   For your full academic development, the use of generative AI to gain inspiration is allowed  for this assignment; however, out of mutual respect, please do not directly paste its output into your assignment and submit it;

c.   To prove that you have indeed completed this assignment and did not rely solely on generative AI, please provide screenshots of the running results for each task.