amitabhch822 / bigdata-mapreduce-movieratings-analysis

Big Data analysis project using MapReduce in Python to process movie ratings. Includes scripts for aggregating ratings and identifying the most rated movies, demonstrating data analysis on a large scale.

Big Data MapReduce Movie Ratings Analysis

Introduction

Welcome to the BigData-MapReduce-MovieRatings-Analysis repository. This project focuses on leveraging the power of big data processing techniques using MapReduce, implemented in Python with the mrjob library, to analyze movie ratings data.

Project Description

This repository contains a collection of scripts designed to process and analyze large datasets of movie ratings. The primary goals of this project include:

• Counting movie ratings.
• Identifying the most popular movies based on ratings.
• Demonstrating efficient data processing methods in a big data context.

Technical Requirements

To run these scripts, you will need:

• Python
• The mrjob library

Installation

To set up your environment for running these scripts, follow these steps:

1. Install the latest version of Python from Python's official website.
2. Install the mrjob library using pip: pip install mrjob

Usage

To run a MapReduce job, navigate to the script's directory and use the following command: python <script_name.py> <input_file> Replace <script_name.py> with the name of the script you want to run and <input_file> with the path to your data file.

Data Format

The scripts expect input data in the following format:

• Tab-separated values with fields: userID, movieID, rating and timestamp.

Contributing

Contributions to this project are welcome. Please adhere to the following guidelines:

• Fork the repository.
• Create a new branch for your features or fixes.
• Submit a pull request with a clear description of your changes.

Contact Information

For any questions or collaborations, feel free to contact me at [email protected] or https://github.com/AmitabhCh822.