Congratulations on being selected to participate in our technical test. It consists of a programming challenge and it will address different skills. Read the instructions carefully and we wish you the best of luck.
Fork this repository and once you have finished your challenge, grant access to the Github user "kavlac". Upload all your deliverables to your forked repository. We will use it to evaluate your test.
We want you to develop a project that makes uses of the MovieLens dataset. It consists of three goals and the details on each one of them is given below.
The first goal of this challenge is to obtain and prepare the data you will work with.
In order to do so, you must download a publicly available dataset. You can find the details about what data is stored and how it is structured in the instructions.
Then, you are asked to write a program to read the input files for the dataset and create a database out of it. You can choose to use the database in memory, in files, or in a database management system, as long as you process and consume this data in the upcoming parts.
The second goal of this challenge is to make the processed data available for consumption.
To do such, you must implement a REST API and it should provide the following methods:
- List movies by year: given a year, we want to know what movies match the given year;
- List movies by year and genre: given a year and a genre, we want to know what movies match the given year and are of the given genre;
- List top K rated movies: given a number K, we want to know the best K rated movies in descending order.
The third goal of this challenge is to consume the methods of the REST API.
Thus, you are asked to implement a client application that accesses such an API. It must have a graphical interface to interact with users to consume the three methods above. It is up to you how to design the user interface, as long as it is usable.
You must provide the following artifacts:
- The source-code of the programs that you implemented;
- A set of instructions on how to prepare the environment, build the programs, run each part of the challenge, and how to use your project;
- Comments on what technologies and patterns you used and the reasons to do so, as well as the decisions you made throughout the challenge;
- Any other artifact you find relevant for your overall evaluation.
- Make sure your instructions are easy to follow and that each step works as expected;
- Our main environment is Windows, so please make sure that your solution works on it;
- If you want, you can show us how you can set up your project using Docker;
- We suggest you implement the challenge using the following languages (you can use more than one of them if you want): C#, Java, and/or JavaScript;
- Testing is more than welcome;
- Show us everything you know about best practices in Git;
- Think carefully about your code quality, in terms of maintainability, readability, and simplicity;
- Do not overengineer your solution.
Backend
- gradle 7
- java 8
- postgres
*Url: http://localhost:8680
Frontend
- nodejs v12.18.3
- yarn v1.22.4
- @quasar/cli v1.0.5
*Install: npm install npm i yarn npm install -g quasar-cli
*Run: quasar dev *Build: quasar build
*Url: http://localhost:8080
- movies.backup.
- Java RESTful API with Spring Boot Framework.
- PostgreSQL database.
- Liquibase.
- JPA.
- Hibernate.
- OpenCSV.
- Uploading file screenshot.png.
- Movies by year demo screenshot.png.
- Movies by year and genre demo screenshot.png.
- Top k rated movies.png.
- Just was necessary to load two files from publicly available dataset.
- Those files (movies.csv and ratings.csv) were enough to populate the database and provide the requested on 'Making the Data Available' section.