Voting Analysis using Big Data Technologies

This project demonstrates a real-time voting analysis system using modern big data technologies. The system simulates a voting process, extracts data from an external API, processes it using Apache Kafka and Apache Spark, and visualizes the results with Streamlit.

Overview

Components

1. Data Extraction:

   • Data is fetched from the API:

     BASE_URL = 'https://randomuser.me/api/?nat=gb'
     

     Simulated voters are assigned to one of three parties:
     • Management Party
     • Savior Party
     • Tech Republic Party

2. Real-time Data Processing:

   • Apache Kafka is used for real-time streaming of voting data.
   • Apache Spark processes the data in real-time, aggregating results and performing analytics.

3. Visualization:

   • Streamlit provides an interactive dashboard to display voting results in real-time.