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Use the YelpAPI Package to collect Yelp data (Businesses and Reviews) for Chicago downtown area Use EdgeDB to create the Graph-Relational Data Model

INSTRUCTIONS TO CANDIDATES
ANSWER ALL QUESTIONS

 

Assignment Instructions:

Download the assignment's IPYNB script (Chicago_Yelp_Reviews.ipynb Download Chicago_Yelp_Reviews.ipynb) to your personal computer Updated and run the provided IPYNB script on your personal development computer

Install EdgeDB on your personal development computer Create your Yelp API Key from the Yelp website

Create a Google Developer Account and get your geocoder.ApiKey

 

Assignment Objectives:

Use the YelpAPI Package to collect Yelp data (Businesses and Reviews) for Chicago downtown area Use EdgeDB to create the Graph-Relational Data Model for Yelp data (Businesses and Reviews)

Use EdgeDB client libraries (https://www.edgedb.com/docs/clients/index (https://www.edgedb.com/docs/clients/index) Links to an external site.) to execute four experiments, and provide a comparative analysis of your research results:

 

Experiment 1: Use EdgeQL/Python Blocking API ( https://www.edgedb.com/docs/clients/python/api/blocking_client (https://www.edgedb.com/docs/clients/python/api/blocking_client) Links to an external site.) to query and perform data analysis for Yelp data Experiment 2: Use GraphQL Over HTTP /Python to (https://www.edgedb.com/docs/clients/graphql/index)query (https://www.edgedb.com/docs/clients/graphql/index)query) Links to an external site.and perform data analysis for Yelp data

Experiment 3: Use EdgeQL/Python AsycIO API (https://www.edgedb.com/docs/clients/python/api/asyncio_client (https://www.edgedb.com/docs/clients/python/api/asyncio_client) Links to an external site.) to query and perform data analysis for Yelp data Experiment 4: Use EdgeQL Over HTTP /Python (https://www.edgedb.com/docs/clients/http/index (https://www.edgedb.com/docs/clients/http/index) Links to an external site.) to query and perform data analysis for Yelp data

Comparative Analysis: Review performance across the four experiments on the Yelp data.

Assignment Deliverables and File Formats

 

Deliverables

 

The paper summarizing your work should consist of no more than four pages of text, double-spaced. Figures and tables may go in an appendix and do not count as part of the four pages. The paper should be provided as an Adobe Acrobat pdf file. (MS Word files are NOT acceptable.) Think of this paper as comprising all sections of a written research report. Ensure that proper English grammar is used throughout. Use tables and figures as needed to document your work.

Program files should be provided as plain text. Python, Go, and R are the recommended programming languages. These may be supplemented by SQL plain text files showing database queries. Plain text files are needed so your instructor can execute your programs to check your work. Feel free to start with jump-start code provided by the instructor or TA.

Include output from programs, such as console listings/logs, text files, and graphics output (pdf, png, or jpg) for visualizations.

If you use the Data Science Computing Cluster or School of Professional Studies database servers or systems, include Linux logs of your sessions as plain text files. Linux logs may be generated by using the script process at the beginning of your session, as demonstrated in the tutorial handouts for the DSCC servers.

If you use Jupyter notebook to work on this assignment, ensure that, in addition to your ipynb script, you include a plain text .py file of your program and an html file showing the results from executing your script. Ensure that all code and visualizations are fully visible in the files that you submit. List of file names and descriptions of files in the zip-compressed folder/directory. This should be a plain text file.

 

File Formats (.zip and .pdf files may be posted to Canvas for grading)

 

Create a folder or directory with all supplementary files with your last name at the beginning of the folder name, compress that folder with zip compression, and post the zip-archived folder under the assignment link in Canvas. (Use zip, not StuffIt, RAR, 7z, or any other compression method.)

Recognizing that long file names can pose problems on systems that have limited path lengths, ensure that file names are short but descriptive. For example, the file for the paper could have the form lastname-assignment-6-paper.pdf The compressed zip file should be similarly named as lastname-assignmet- 6.zip

Formatting Python code: when programming in Python, refer to Kenneth Reitz’ PEP 8: The Style Guide (https://pep8.org/) for Python Code. There is also the Google style guide (https://google.github.io/styleguide/pyguide.html) for Python. Comment often and in detail.

 

Grading Guidelines (100 points total)

 

Written report (50 points)

 

Abstract, Introduction, and Literature Review (10 points) What is this research about and what did you learn? Why did you engage in this research? Who else has conducted research like this? Cite sources for database systems and tools. Methods (10 points) How did you conduct this research? Provide a detailed review of the design and execution of the benchmark study.

Results (10 points) What did you learn from this research?

Conclusions (10 points) So, what does this research mean to data engineers, data scientists, or management? Which database systems, tools, or software components do you recommend? Exposition (10 points) Proper use of English grammar and punctuation. Adherence to Chicago Author/Date style for citations and references.

 

Programming (50 points)

 

Database programming. (50 points) Provide complete documentation, data sets, listings, visualizations, and code for the four experiments and comparative analysis. Each component is worth 10 points.

 

Reference

Buna, Samer. 2021. GraphQL in Action. Shelter Island: Manning [ISBN-13: 978-1617295683]

 

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