NASA APOD Search

A full-text search application for NASA's Astronomy Picture of the Day (APOD) archive. This application provides a modern interface to search through thousands of astronomy pictures and their descriptions.

Features

• Full-Text Search: Search through titles and explanations of NASA's astronomy pictures
• Advanced Search Capabilities:
  • Exact phrase matching for titles
  • Fuzzy matching for typo tolerance
  • Relevance-based sorting
• Year-based Filtering: Filter results by year with aggregated counts
• Responsive Grid Display: View results in a clean, organized table format
• Real-time Search: Search results update as you type
• Server-side Pagination: Efficient loading of large datasets

Tech Stack

• Frontend: Next.js with React
• UI Components: Material-UI (MUI)
• Search Engine: Elasticsearch
• Language: TypeScript
• Package Manager: pnpm

Prerequisites

• Node.js (v18 or higher)
• pnpm
• Elasticsearch (v8.x)
• Docker (optional, for running Elasticsearch)

Setup

1. Clone the repository

   git clone https://github.com/hamidfarmani/nasa-full-text-search.git
   cd nasa-full-text-search

2. Install dependencies

   pnpm install

3. Start Elasticsearch

   Make sure Elasticsearch is running on http://localhost:9200

   If using Docker:

   docker run -d --name elasticsearch -p 9200:9200 -e "discovery.type=single-node" elasticsearch:8.x

4. Load the data

   pnpm run load-data

5. Start the development server

   pnpm dev

Search Features

Text Search

• Searches across title and explanation fields
• Title matches are boosted for higher relevance
• Exact phrase matching for titles
• Fuzzy matching for typo tolerance
• Minimum match threshold for better quality results

Filtering

• Year-based filtering using Elasticsearch aggregations
• Real-time counts of items per year
• Combines with text search

Sorting

• Results are sorted by relevance when searching
• Chronological sorting (newest first) when not searching

Data Loading

The application includes a data loading script that:

• Creates the Elasticsearch index with proper mappings
• Loads APOD data in chunks to prevent overwhelming the server
• Includes error handling and retry logic
• Shows progress during loading

Elasticsearch Mapping

The application uses a custom Elasticsearch mapping that includes:

• Text fields with standard analyzer for better search
• Date fields with proper formatting
• Runtime fields for year extraction
• Keyword fields for exact matching
• Custom analyzers for improved search quality

Development

Available Scripts

• pnpm dev: Start development server
• pnpm build: Build for production
• pnpm start: Start production server
• pnpm load-data: Load data into Elasticsearch

Environment Variables

Create a .env.local file with:

ELASTICSEARCH_URL=http://localhost:9200

Contributing

1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request