🚀 Unlock FAST Full-Text Search in PostgreSQL! ⚡

🔍 Implementing Full-Text Search with tsvector for Faster, Ranked Results

Efficient search is critical for scalable applications. This project demonstrates the implementation of full-text search in PostgreSQL using tsvector to enhance search performance and ranking.

⚡ Approaches Compared

1. ILIKE (Pattern Matching): Works but only finds exact matches.
2. tsvector + tsquery (Full-Text Search): Efficiently indexes text, enabling powerful searches with ranking.

🗂 Project Structure

The repository is organized as follows:

• backend/: Contains the server-side codebase.
• frontend/: Contains the client-side codebase.
• database/: Contains database-related files, including SQL scripts for setting up tables and indexes.

🎥 Check this linkedin post video to understand better!

📸 Code Snippet Comparisons

🔍 Search Using ILIKE

❌ Failing search with LIKE

⚡ Optimized Query Using tsvector

📊 Data Source

The dataset was scraped from Scifi Stack Exchange for demonstration purposes.

🛠 Tech Stack

• Backend: Java
• Frontend: JavaScript, HTML, CSS
• Database: PostgreSQL with tsvector & tsquery

✨ Final Thoughts

🚀 Optimizing search performance can significantly enhance user experience and scalability. If you found this project helpful, feel free to ⭐ the repo, contribute, or share your thoughts!

💬 Let’s connect! Reach out on LinkedIn or start a discussion in the repo.

🔥 Happy Coding! 🚀