https://github.com/dwija12903/bda-lab

This repository contains various lab files from my Big Data Analytics coursework
https://github.com/dwija12903/bda-lab

graphx networkx pysaprk-sql pyspark pyspark-mllib scala

Last synced: 24 days ago
JSON representation

This repository contains various lab files from my Big Data Analytics coursework

• Host: GitHub
• URL: https://github.com/dwija12903/bda-lab
• Owner: dwija12903
• Created: 2024-09-09T10:32:07.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-09-09T10:36:37.000Z (about 2 months ago)
• Last Synced: 2024-10-01T15:59:15.798Z (about 1 month ago)
• Topics: graphx, networkx, pysaprk-sql, pyspark, pyspark-mllib, scala
• Language: Jupyter Notebook
• Homepage:
• Size: 267 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# 📊 Big Data Analytics Lab Files

This repository contains various lab files from my **Big Data Analytics** coursework, covering topics such as **Scala**, **PySpark**, **RDD**, **SQL**, **GraphX**, **NetworkX**, **PageRank**, **Linear Regression**, and **Random Forest**.

### 💻 Lab Files Included:

1. **Scala Basics** 🚀

   - Scala programming language fundamentals for big data.

   

2. **RDD (Resilient Distributed Dataset)** ⚙️

   - Operations and transformations on RDDs in PySpark and Scala.

   

3. **SQL in PySpark** 🧮

   - Performing SQL operations on big data using PySpark SQL.

   

4. **PySpark** 🔥

   - Handling distributed data processing using PySpark.

5. **GraphX** 🔗

   - Working with graph data using GraphX in Scala.

   

6. **NetworkX** 🌐

   - Graph-based data analysis using NetworkX with PySpark.

   

7. **PageRank Algorithm** 📈

   - Implementation of the PageRank algorithm for ranking web pages using PySpark.

   

8. **Linear Regression** 📉

   - Machine learning implementation of Linear Regression for predictive analysis using PySpark MLlib.

   

9. **Random Forest** 🌲

   - Implementing the Random Forest algorithm for classification and regression tasks in PySpark MLlib.

## 🚀 How to Run

1. Clone the repository:

   ```bash

   git clone https://github.com//Big-Data-Analytics.git

   cd Big-Data-Analytics

   ```

2. Navigate to the respective folder and run the code using **PySpark** or **Scala**.

## ⚙️ Prerequisites

- **Scala** installed.

- **PySpark** environment set up.

- Python packages for **PySpark**, **NetworkX**, etc.

## 👩‍💻 Contributing

Feel free to contribute by improving the code, adding new features, or enhancing documentation. Fork the repository, create a branch, and submit a pull request.