bigdata-vanhaydoi-framework 0.2.0

A short description of your project

Modular ETL Framework

About

This framework is designed for Extract - Transform - Load (ETL) operations, allowing you to process data from multiple source systems and load it into HDFS (Hadoop Distributed File System).

Project Tree

├── src

│ ├── config

│ ├── extract

│ ├── transform

│ ├── load

│ └── db_interaction

├── logs

├── tests

├── data

├── docs

├── output

├── .gitignore

├── config.ini

├── etl_db.db

├── main.py

├── requirements.txt

└── README.md

Descriptions

• src: Main source code directory.
  • config: Configuration files for the ETL process.
  • extract: Code for extracting data from source systems.
  • transform: Code for transforming the extracted data.
  • load: Code for loading the transformed data into HDFS.
  • db_interaction: Code for interacting with databases if needed.
• logs: Directory for storing log files generated during ETL process.
• tests: Directory for unit tests and testing-related files.
• data: Storage for input or intermediate data.
• docs: Documentation related to the ETL framework.
• output: Directory for final output files or data.
• .gitignore: File specifying excluded files/directories from version control.
• config.ini: Configuration file for connection details, API keys, etc.
• etl_db.db: Local database file if used.
• main.py: Main entry point for the ETL framework.
• requirements.txt: List of required Python packages.
• README.md: Main project documentation in Markdown.

Features

This ETL framework includes the following core features:

• Extract: Fetch data from various source systems.
• Transform: Clean, process, and transform the extracted data.
• Load: Load the transformed data into HDFS.

Tech Stack

The framework utilizes the following technologies:

• Programming Language: Python
• ETL Libraries/Frameworks: (Specify if applicable)
• Database System: (Specify if applicable)
• HDFS Setup: (Specify if applicable)

Installation

Follow these steps to set up the ETL framework:

1. Clone this repository: git clone <repository_url>
2. Navigate to the project directory: cd ETL_Framework
3. Install required packages: pip install -r requirements.txt
4. Configure settings in config.ini as needed.

How to Use

Perform ETL operations using the following steps:

1. Navigate to the project directory: cd ETL_Framework
2. Run the ETL process: python main.py
3. Monitor the logs in the logs directory for progress and issues.
4. Find the final output in the output directory.

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