代写INFS3200、代写SQL/Java编程语言

日期：2023-03-19 12:22

INFS3200 Advanced Database Systems

Assignment (25%)

Semester 1, 2023

Deadline: 4pm Friday, 26 May 2023

Submit: Online Submission on the Blackboard INFS3200 Course Website

Introduction

The assignment contains four parts with seven questions (total marks 25 for 25% of the course)

to demonstrate your understanding of multiple topics, including distributed database, data

warehousing, data integration and data quality management. Meanwhile, coding is required for

some questions to show your problem-solving ability. This assignment must be performed

individually.

Important Notes:

1. As UQ has provided the Lab environment for this assignment, you don’t need to install

the required software systems on your own machine. The software environment problems

on your own computer machine cannot be used to ask for extension of submission.

2. Each dataset used in this assignment contains thousands of records, which is hard to be

checked record-by-record manually. Therefore, it is recommended to have a handy text

editor tool (e.g. Microsoft Excel, Notepad++ or Sublime Text on Windows) to view and

search the contents in CSV files. Please use search function (i.e., Ctrl+F keys) in text

editor to look through values. Also, please don’t change the data unintentionally while

viewing or searching, as it may affect your assignment results.

3. You should complete Prac 3 before working on the coding part of this assignment (i.e.,

Part 4 of this assignment). Although the assignment is independent to the three practicals,

the code introduced in Prac 3 can be a starting point of this assignment as the tasks are

similar.

4. You implement your code in SQL, Java or Python, you may choose the ones that you feel

comfortable. The code must be companied by minimum comments so that tutors can

understand the structure of your coding and the objective of each snippet. If you

performed this assignment on your own Laptop machine instead of the UQ provided

software environment, you must ensure that the codes submitted by you are all able to

execute correctly on UQ provided Lab environment, either remotely via Internet

connection, or locally in UQ GPS Building Lab 78-116.

Submission Requirements:

Please include all your answers in a word/pdf document. Pack the documents with your code

folder (which contains at least “src” and “data” folders, shown as below) into a .zip/.rar file and

submit it to the Blackboard INFS3200 course Website. The name of both the zip file and the

document should contain your student ID, your name and “Assignment”, shown as follows:

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Please format your document nicely, in terms of consistent font, font size and spacing. The

answers are suggested to follow the below structure (No need to repeat questions if not necessary,

fonts and spacing are not limited):

…

Part 1.

Question 1: Your answers…

Question 2: Your answers…

Part 2.

…

WARNING: This assignment must be completed individually, Artificial Intelligence tools

cannot be used to generate any part of solutions for this assignment. Any form of answer-

sharing with other people is not acceptable and, once identified, will be penalized. Contract

cheating will be investigated and it will result in heavy penalty.

Preliminary: Dataset Description

In this assignment, we have four datasets about book information from four different sources.

The data schemas are listed below:

Book1 (id, title, authors, pubyear, pubmonth, pubday, edition, publisher, isbn13,

language, series, pages)

Book2 (id, book_title, authors, publication_year, publication_month, publication_day,

edition, publisher_name, isbn13, language, series, pages)

Book3 (ID, Title, Author1, Author2, Author3, Publisher, ISBN13, Date, Pages,

ProductDimensions, SalesRank, RatingsCount, RatingValue, PaperbackPrice,

HardcoverPrice, EbookPrice, AudiobookPrice)

Book4 (ID, Title, UsedPrice, NewPrice, Author, ISBN10, ISBN13, Publisher,

Publication_Date, Pages, Dimensions)

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Part 1: [6 marks] Database Schema and Fragmentation

Read the above schemas carefully and understand the meaning of the attributes. If you don’t

know the meaning of a certain attribute, check the data under it or Google its meaning (especially

for some abbreviations, like ISBN). Answer the following questions based on your

understanding.

Question 1: [2 marks] Given four datasets that are stored in one relational database as separate

relations.

(1) Write an SQL query “Find the top 15 books that have the highest ratings and 10 books

that have the lowest ratings, return their ranks (sorted in descending order), titles,

publishers and number of pages”.

(2) Which table schema(s) is/are used to answer the above query?

Question 2: [4 marks] Given that Book1 is stored in a distributed database A, and two queries

that are most frequently asked on A are:

? Find all books whose publisher name is “XXX” (or among multiple publishers), return

their book titles and author info.

? Find all books that are published in a given year, return their book IDs,

languages,number of pages, HardcoverPrice and EbookPrice.

Answer the following questions:

(1) [2 marks] If the goal of A is to handle each query by a dedicated local site (no information

needed from the other site), which fragmentation strategy should be used to fragment

Book1 table? If only two fragments are generated, write their schemas (if vertically

fragmented) or predicates (if horizontally fragmented), respectively. (Note: there are lots

of valid fragmentation solutions, just provide one of them.)

(2) [2 marks] Assuming that we horizontally fragment the table into three fragments based on

the following predicate:

Fragment 1: pages ≤ 200

Fragment 2: 200 < pages ≤ 600

Fragment 3: pages > 800

Is this set of predicates valid? If so, please explain (using plain English) the insertion

process if we want to insert a new record into Book1. If not, please generate a valid

predicate set using minterm predicates (show the calculation process). Also, explain the

insertion process for a new record after the valid predicate set is made.

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Part 2: [7 marks] Data Warehouse Design

In this part, we design a Data Warehouse on book sales w.r.t. the Book1, Book2, Book3, and

Book4 datasets. Particularly, we need to use data from the given assignment datasets and create

a Data Warehouse Schema. The designed Data Warehouse will contain summary data, such as

the total sales of each publisher, for each day and each language. The following shows just an

example:

Day Publisher Language Sales

07/15/1984 AAAI Press English 11

05/05/1990 Springer International Publishing English 23

06/04/1995 Springer London English 15

12/11/2000 IEEE Computer Society Press English 30

04/03/2004 AAAI Press Spanish 2

05/01/2008 Springer International Publishing Spanish 13

11/19/2012 Springer London Spanish 5

08/06/2014 IEEE Computer Society Press Spanish 22

Question 3: Design a Data Warehouse Schema that can accommodate the above example,

answer the following questions:

(1) [1 mark] Show the schema and point out the dimensions and fact table. Given that we

have a dimension table for each dimension and there are 4000 records in the fact table.

Among all dimension tables and the fact table, which table has the most records? Why?

Question 4: Now we want to the create bitmap indices for the given model:

(1) [2 marks] What are the advantages of building a bitmap index? Which type of column is

not suitable for bitmap index?

(2) [2 marks] Suppose the “Publisher” column only contains four distinct values and

“Language” only contains two, which are all shown in the above example. Please create

bitmap indices for both “Publisher” and “Language”.

(3) [2 marks] Explain how to use the bitmap indices to find the total sales of “English” books

published by “AAAI Press”.

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Part 3: [4 marks] Data Integration

Given that the data warehouse loads data from the above four sources (Book 1,2,3,4), you are

asked to integrate their data and address various data quality issues. In this part, those database

sources (i.e., owners) only give you their schemas (shown in Preliminary part), and you are asked

to design an integrated schema based on the given schemas (i.e., the data records within tables

Book 1,2,3,4 are supposedly not available for you at this stages).

Question 5: Now you define a global schema (using the approach namely, Global as a View)

which can integrate data from all four sources.

(1) [2 marks] Design a global schema which will combine the common attributes from each

schema together. Your design should include any information that is represented in all four

schemas. If an attribute cannot be found or derived in the given schemas, then it should be

left out of your global schema.

(2) [1 marks] Identify structural heterogeneity issues that may occur during your integration

by an example in the schemas together with the possible resolution.

(3) [1 marks] Identify semantic heterogeneity issues that may occur during your integration

by an example in the schemas together with the possible resolution.

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Part 4: [8 marks] Data Quality Issues

Now assume you are provided with the actual data from each source, namely “Book1.csv”,

“Book2.csv”, “Book3.csv” and “Book4.csv” (see the Assignment provided datasets). As it is

very common that the same book is recorded by different sources, it is crucial to identify the

redundant information by merging and eliminate the duplicated records during the data

integration process, which relies on the data linkage techniques to be used. In this regard, we

provide a human-labelled gold-standard dataset (refer to Prac 3 Part 2.2 for more information

about gold-standard), named as “Book1and2_pair.csv”, which lists all correct matchings

between Book1 and Book2. It will be used in the following tasks. Its schema is as follows:

Book1and2_pair (Book1_ID, Book2_ID)

In a CSV file, you need to note that the attributes are separated by comma (,). If two commas

appear consecutively, it means the value in the corresponding field between two commas is

NULL (i.e., absent). Furthermore, if an attribute field contains comma naturally, the field will

be enclosed by a double quote ("") to differentiate the actual comma notation inside attribute

from the outside comma separator. For example, a record in Book2 is as follows:

1725,Informix Unleashed,"John McNally, Jose Fortuny, Jim Prajesh, Glenn Miller",

97,6,28,1,Sams,9.78E+12,,Unleashed Series,1195

According to Book 2 schema, we can infer the following fields:

id=1725,

book_title=Informix Unleashed,

authors= John McNally, Jose Fortuny, Jim Prajesh, Glenn Miller,

…

isbn13=9.78E+12

language=NULL,

series=Unleashed Series,

pages=1195.

Here, since there are commas in “authors” field, the whole field is enclosed by a notation of

double quotes. Also, since there are two consecutive commas before “Unleashed Series”, it

means that the language is NULL.

In this part, you are asked to answer the following questions by writing code to complete the

tasks (if “code required” is specified) and provide your answers based on the code results.

Please store all the code you wrote during this part and submit them to Blackboard Course

Website as a part of your assignment submission.

Question 6: Sample records from “Book3.csv” to measure its data quality:

(1) [1 mark] By sampling the records whose id is the multiple of 100 (i.e. 0, 100, 200, 300, …),

how many records are there in the sample set (code required)?

(2) [1 mark] Among the samples found in Question 6-(1), how many fields containing NULL

values are presented (code required)?

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(3) [2 marks] Calculate the Empo (error per million opportunities) according to your samples

(only NULL value is considered). (Hint: you can sample the records manually to validate

the correctness of your program results)

Question 7: Perform data linkage on Book1 and Book2 using the methods mentioned in Prac 3:

(1) [2 marks] Given two author strings from Book1 and Book2 that refer to the same author

list:

a. “Richmond Shee, Kirtikumar Deshpande and K. Gopalakrishnan;”

b. “K. Gopalakrishnan, Kirtikumar Deshpande, and Richmond Shee”

Which distance function is more likely to regard them as similar (between two approaches

of edit distance and Jaccard distance)? And Why?

(2) [2 marks] Perform the data linkage between Book1 and Book2 data. When linking their

results, use Jaccard coefficient with 3-gram tokenization as the similarity measure and

perform the comparison only on the “book title” field. The book pairs whose similarity is

higher than 0.75 are regarded as matched pairs. Compare your output with the gold-

standard dataset and write down the precision, recall and F-measure (code required).

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