[Dataset]: You will be given a dataset that contains 2D points. The dataset will be provided in a text ﬁle as the following format:
id 1 x 1 y 1
id 2 x 2 y 2
id n x n y n
Speciﬁcally, the ﬁrst line gives the number of points in the dataset. Then, every subsequent line gives a point’s id, x-, and y-coordinates. Your program should build an R-tree in memory from the dataset.
[Range Query]: You will be given a set of 100 range queries in a text ﬁle whose format is:
x 1 x’ 1 y 1 y’ 1
x 2 x’ 2 y 2 y’ 2
x 100 x’ 100 y 100 y’ 100
That is, each line speciﬁes a query whose rectangle is [x, x′] [y, y′]. Then, we will measure its query eﬃciency as follows.
You should output to a disk ﬁle:
Firstly, your program should display the time of answering queries by reading the entire dataset sequentially. This time serves as the sequential-scan benchmark to be compared with the cost of your query algorithms that leverage the R-tree.
Secondly, display the number of points returned by each query-note: we need only the number of points retrieved , instead of the details of those points.
Thirdly, display the total running time of answering all the 100 queries, and the average time of each query (i.e., divide the total running time by 100).
Programming Language]: Python, Java, C++ (including variants like C, C#, ...), or any other
language approved by the instructor. You can implement the R-tree by using the existing libraries provided in the programming language of your choice (i.e., some standard libraries or the libraries for R-Tree).
[Deliverables]: Your submission includes the following components:
Source Code: The code you have developed yourself. Make sure your code can be run in the standard general programming
Report: Your report should include the following:
A brief description of the main functions in your source code;
A clear speciﬁcation of the requirements for executing your code such as, OS environ- ment, placement of input ﬁles, any input parameters, etc.
Zip all your code and report into a single file, and name the ﬁle in the following format:
Marking: Your total mark earned for this assignment is based on:
• [Queries: 60 marks]
[Sequential-Scan Based Method (10 marks)]: If your program correctly an- swers m (out of 100) queries by reading the entire dataset (reading all the data points) sequentially, you get 10 · (m/100) marks for this part.
∗ [R-Tree Based Method (40 marks)]: If your program correctly answers m (out of 100) queries by searching the R-Tree, you get 40 · (m/100) marks for this part.
Eﬃciency: 10 marks. If the average query time is at least 5 times faster than sequential scan, you get 10 marks for this part. If at least 2 times faster (but less than 5 times), you get 5 If less than 2 times faster, no marks.
• [The Report: 40 marks]
Function Description: 30 If your report includes a clear description of all the functions in your source code, you get 30 marks. If only part of your functions is introduced, you will be given the marks based on the proportion of the correct answers.
Requirement Description: 10 If your report includes a clear description of the requirements for executing your code such as, OS environment, placement of input ﬁles, any input parameters, etc, and your report includes the screenshots of the run- ning results (e.g., the average execution time of both sequential-scan and R-Tree based methods, etc.), you get 10 marks.
• [Bonus: 10 marks]
Implementing the R-Tree by Using Standard Libraries Only (5 marks). S- tudents are encouraged to implement the R-Tree by using standard libraries provided by the program languages rather than using the existing R-Tree If you can correctly implement the R-Tree without the help of the existing R-Tree libraries, you get 5 marks as the bonus.
Analysing the Working of R-Tree: (5 marks). In addition to coding, students are encouraged to provide a high-quality report that contains a detailed analysis of the working of R-Tree. You need to select no less than 10 data points from the given dataset, and one query from the given queries. Then, if you can clearly and correctly analyse the process of the R-Tree construction and the query process (the search should traverse several nodes of the tree, and during the construction of the R-Tree, there should be an overﬂow and a node splitting), you get 5 marks as the bonus.
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