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Relationship Visualizer App | UI

Project Description | Live Demo

  • This is a MERN stack CRUD application. The App uses Depth First Search (DFS) to traverse the User's graph and find the degree of separation along with the exact path between the 2 selected nodes. Each node is a User which contains all the user data like User ID, Name, Relation Type between the users, etc. Users and Relations can be added or deleted.
  • The top 5 paths along with the Degree of Separation are displayed on the UI.
  • The App is developed using the MERN stack, React & Chakra UI for the frontend along with Redux for state management. Node and Express for Backend and MongoDB for the database.
  • Used Heroku to deploy the server and Netlify for the application UI.

Backend Code

https://github.com/100sarthak100/RelationshipVisualizer

Run Locally

  • Clone the repo in your machine.
// UI
mkdir client
cd client
git clone https://github.com/100sarthak100/RelationshipVisualizerUI
npm install

// Server
mkdir server
cd server
git clone https://github.com/100sarthak100/RelationshipVisualizer
npm install

  • Make a .env file in the server directory and copy your MongodB connection URI there along with the port number.

  • Change the baseUrl in the client/src/api/index.js file to the local url.

  • Then run the application

// client
npm start

// server
npm start
  • The server and the clinet can be accesed from here
Client -> http://localhost:3000/
Server -> http://localhost:5000/

Scope for Improvement

DFS | Time Complexity O(V + E)

  • The Application uses DFS graph traversal algorithm to traverse the User graph and return all the paths between 2 users.
  • The time complexity of DFS is O(V + E) where V is the number of users and E is the number of relation between them.
  • As the number of users and the relations increases the algorithm will take more time to return the result.
  • We can build a Graph Database on AWS Using Amazon DynamoDB and Titan, to scale our application for >=1M users. Amazon AWS
  • The application can later be optimized for mobile devices also.