Wikimedia Data Processing

Table of Contents

• Description
• Technologies Used
• Architecture Overview
• Setup and Run Instructions
  • Using IntelliJ
  • Using Docker Compose
• Monitoring and Logs
• References
• Troubleshooting
• Contributing
• License

Description

The Wikimedia Data Processing project is designed to handle and process large volumes of real-time streaming data from Wikimedia. The project leverages Kafka for efficient and scalable data ingestion and processing and utilizes MySQL for data storage, enabling analytical insights.

Key Features

• Real-Time Data Ingestion: Utilizes a Kafka producer to stream real-time data from Wikimedia.
• Data Processing: Consumes and processes real-time data via a Kafka consumer.
• Data Storage: Persists processed data into a MySQL database.
• Scalability: Built with Spring Boot microservices architecture for scalability and maintainability.

For accessing the real-time stream data from Wikimedia, visit: Wikimedia Stream

Technologies Used

Backend

• Java: Version 11
• Spring Boot: Version 2.5.12
• Apache Kafka: Distributed streaming platform
• Apache Maven: Version 3.8.4 for build automation

Database

• MySQL: Relational Database Management System

Tools

• Docker: Version 27.0.3 for containerization
• IntelliJ IDEA: 2024.1.4 (Community Edition)
• Docker Desktop: Version 4.31.1

Architecture Overview

The project follows a microservices architecture and comprises two main components:

1. Wikimedia Data Producer: A Kafka producer that reads real-time data from Wikimedia and publishes it to a Kafka topic.
2. Wikimedia Data Consumer: A Kafka consumer that reads data from the Kafka topic and stores it in a MySQL database.

Setup and Run Instructions

Using IntelliJ

Prerequisites

• Install Docker and Docker Compose
• Install Java 11
• Install Maven 3.8.4

Step-by-Step Setup

1. Clone the Repository:

   git clone https://github.com/tienhuynh-tn/Wikimedia-data-processing.git
   cd Wikimedia-data-processing

2. Build the Project:

   mvn clean install

3. Run Docker Services:

   • Start Kafka UI:

     docker compose -f ./docker/kafka-ui.yml up -d

   • Start MySQL Database:

     docker compose -f ./docker/mysql.yml up -d

4. Run Services in IntelliJ:

   • Open IntelliJ, import the project, and run the main classes for both producer and consumer modules.

Using Docker Compose

1. Edit application.yml Configuration:

   • Update the configuration to match the Docker environment (comment/uncomment as necessary).

2. Navigate to the Docker Directory:

   cd ./docker/

3. Build Docker Images:

   docker-compose build --no-cache

4. Start All Services:

   docker-compose up -d

5. View Application Logs:

   docker logs -f wikimedia-data-processing

Monitoring and Logs

• Kafka UI: Access Kafka UI at http://localhost:8080 to monitor Kafka topics and messages.
• Application Logs: Use docker logs -f <container_name> to view real-time logs for each service.

References

• Course: Building Microservices with Spring Boot & Spring Cloud by Ramesh Fadatare (Java Guides)

Troubleshooting

• Kafka Broker Not Starting: Ensure the zookeeper service is running before starting the Kafka broker.
• Connection Refused to MySQL: Check the MySQL host and port configurations, and verify Docker network settings.
• Kafka Connection Issues: When running with Docker Compose, you may encounter Connection to node -1 (localhost/127.0.0.1:9092) could not be established errors initially. This is expected; the project should stabilize after a few minutes.

Contributing

Contributions are welcome! Please submit a pull request or open an issue to get started.

License

© 2024 tienhuynh-tn. This project is licensed under the MIT License.