feat: Configure database with Prisma and MySQL spatial support (Task 22)
- Set up MySQL 8.0+ with spatial data support (POINT SRID 4326) - Created Prisma schema with all models (User, Report, Event, etc.) - Added Clerk authentication support (clerk_id field) - Configured spatial indexes on location fields for performance - Created database migrations and applied to MySQL - Built spatial query utilities for geographical operations - Added database connection singleton and health checks - Created comprehensive documentation and test scripts Requirements: 1.1, 2.1, 3.2, 4.1
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@@ -173,7 +173,7 @@
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## Backend API Development
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- [x] 21. Set up backend project structure
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- [ ] 21. Set up backend project structure
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- Initialize Node.js project with Express
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- Configure TypeScript for backend
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- Set up folder structure: routes, controllers, services, middleware, utils
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@@ -181,7 +181,7 @@
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- Create environment configuration
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- _Requirements: All backend requirements_
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- [ ] 22. Configure database with Prisma and MySQL spatial support
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- [x] 22. Configure database with Prisma and MySQL spatial support
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- Set up MySQL 8.0+ with spatial data support
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- Create Prisma schema with all models (User, Report, Event, etc.)
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- Configure MySQL POINT spatial types for location fields
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101
server/DATABASE_SETUP.md
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server/DATABASE_SETUP.md
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# Database Setup Complete ✅
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## Task 22: Configure database with Prisma and MySQL spatial support
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### Completed Items
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✅ **MySQL 8.0+ with spatial data support**
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- Connected to MySQL 9.4.0 at 192.168.4.20:3306
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- Database: beach_litter_mapping
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- Spatial functions verified and working
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✅ **Prisma schema with all models**
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- User (with Clerk authentication support via clerk_id)
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- Report (with spatial location data)
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- Event (with spatial location data)
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- EventRegistration
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- Verification
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- EnvironmentalConcern
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- Hotspot (with spatial location data)
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✅ **MySQL POINT spatial types configured**
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- Reports table: location POINT SRID 4326
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- Events table: location POINT SRID 4326
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- Hotspots table: location POINT SRID 4326
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- All spatial columns use WGS 84 coordinate system (SRID 4326)
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✅ **Database migrations created and applied**
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- Migration 20241116000000_initial_setup: Initial schema
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- Migration 20241116000001_add_clerk_auth: Added Clerk authentication support
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- Migrations applied successfully to database
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✅ **Database indexes including spatial indexes**
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- Spatial indexes on all location POINT columns (reports, events, hotspots)
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- Standard indexes on foreign keys, dates, enums
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- Unique indexes on email, username, clerk_id
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- Composite indexes on latitude/longitude pairs
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### Files Created
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1. **server/prisma/schema.prisma** - Updated with Clerk auth and spatial types
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2. **server/prisma/migrations/** - Migration files for database setup
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3. **server/prisma/README.md** - Comprehensive database documentation
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4. **server/src/config/database.ts** - Prisma client singleton
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5. **server/src/utils/spatial.ts** - Spatial query utilities
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6. **server/src/scripts/testDatabase.ts** - Database verification script
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### Key Features
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**Clerk Authentication Integration:**
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- User table includes clerk_id field for Clerk integration
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- Removed password_hash dependency (handled by Clerk)
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- Ready for Clerk webhook synchronization
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**Spatial Query Support:**
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- Find reports/events within radius
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- Calculate distances between points
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- Identify hotspot clusters
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- Validate Irish coordinates
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- Bounding box queries
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**Performance Optimizations:**
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- Spatial indexes for fast geographical queries
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- Standard indexes on frequently queried fields
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- Connection pooling via Prisma
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- Query logging in development mode
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### Database Connection
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```env
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DATABASE_URL="mysql://beach_litter_user:BeachClean2024!@192.168.4.20:3306/beach_litter_mapping"
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```
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### Verification
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Run the test script to verify setup:
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```bash
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npx tsx src/scripts/testDatabase.ts
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```
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All tests passing:
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- ✅ Database connection
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- ✅ MySQL 9.4.0 detected
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- ✅ Spatial functions working
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- ✅ 7 tables created
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- ✅ 3 spatial indexes configured
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- ✅ Clerk authentication ready
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- ✅ Coordinate validation working
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### Next Steps
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The database is fully configured and ready for:
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- Task 23: Implement authentication system (Clerk integration)
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- Task 24: Build report API endpoints
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- Task 25: Implement file upload and EXIF processing
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### Requirements Satisfied
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- ✅ Requirement 1.1: GPS coordinate capture with spatial support
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- ✅ Requirement 2.1: Interactive map data storage
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- ✅ Requirement 3.2: Hotspot calculation infrastructure
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- ✅ Requirement 4.1: Event location storage
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253
server/prisma/README.md
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server/prisma/README.md
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# Database Configuration
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## Overview
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This project uses **MySQL 8.0+** with spatial data support for storing geographical information about beach litter reports, cleanup events, and environmental concerns.
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## Database Connection
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**Connection Details:**
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- Host: 192.168.4.20
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- Port: 3306
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- Database: beach_litter_mapping
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- User: beach_litter_user
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**Environment Variable:**
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```env
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DATABASE_URL="mysql://beach_litter_user:BeachClean2024!@192.168.4.20:3306/beach_litter_mapping"
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```
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## Spatial Data Support
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The database uses MySQL's spatial data types and functions:
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- **POINT type with SRID 4326**: Used for storing GPS coordinates (WGS 84 coordinate system)
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- **Spatial indexes**: Optimized for location-based queries
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- Tables with spatial data: `reports`, `events`, `hotspots`
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### Spatial Columns
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Each table with location data has:
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- `location` (POINT SRID 4326): Spatial column for efficient geographical queries
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- `latitude` (DECIMAL(10,8)): Decimal latitude for easy access
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- `longitude` (DECIMAL(11,8)): Decimal longitude for easy access
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## Schema Models
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### Users
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- Clerk-based authentication (clerkId field)
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- Profile information synced from Clerk
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- App-specific data: impact score, notification preferences, areas of interest
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### Reports
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- Litter reports with photos and GPS coordinates
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- Spatial indexing for location-based queries
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- Verification status tracking
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- Environmental concerns linked to reports
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### Events
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- Cleanup events with location and scheduling
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- Participant registration tracking
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- Completion data (litter collected, photos)
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### Verifications
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- Community-driven report verification
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- Tracks verify/dispute actions
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- Audit trail with timestamps
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### Environmental Concerns
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- Additional environmental issues beyond litter
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- Linked to reports
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- Severity levels and categorization
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### Hotspots
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- Calculated areas with high litter concentration
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- Spatial queries to identify clusters
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- Severity scoring based on report frequency
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## Indexes
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### Standard Indexes
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- Primary keys on all tables (UUID)
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- Foreign key indexes for relationships
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- Unique indexes on email, username, clerk_id
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- Date indexes for time-based queries
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- Enum indexes for filtering (litter_type, status, etc.)
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### Spatial Indexes
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- `idx_location` on reports.location
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- `idx_location` on events.location
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- `idx_location` on hotspots.location
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These spatial indexes enable efficient queries like:
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- Finding reports within a radius
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- Identifying nearby events
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- Calculating hotspot clusters
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## Migrations
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### Running Migrations
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```bash
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# Apply pending migrations
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npm run prisma:migrate
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# Deploy migrations (production)
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npx prisma migrate deploy
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# Create a new migration
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npx prisma migrate dev --name migration_name
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```
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### Migration History
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1. **20241116000000_initial_setup**: Initial database schema with all tables
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2. **20241116000001_add_clerk_auth**: Added Clerk authentication support (clerk_id field)
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## Prisma Client
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### Generate Client
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```bash
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npm run prisma:generate
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```
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### Usage Example
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```typescript
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import { PrismaClient } from '@prisma/client';
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const prisma = new PrismaClient();
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// Create a report with spatial data
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const report = await prisma.report.create({
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data: {
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userId: 'user-uuid',
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latitude: 53.3498,
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longitude: -6.2603,
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// Note: location POINT field is handled by database triggers or raw queries
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locationSource: 'gps',
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litterType: 'plastic',
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quantity: 'moderate',
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photoUrls: ['https://...'],
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},
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});
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// Find reports near a location (requires raw SQL for spatial queries)
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const nearbyReports = await prisma.$queryRaw`
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SELECT id, latitude, longitude,
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ST_Distance_Sphere(
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location,
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ST_GeomFromText('POINT(${longitude} ${latitude})', 4326)
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) as distance
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FROM reports
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WHERE ST_Distance_Sphere(
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location,
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ST_GeomFromText('POINT(${longitude} ${latitude})', 4326)
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) <= ${radiusInMeters}
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ORDER BY distance
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`;
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```
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## Spatial Query Examples
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### Find Reports Within Radius
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```sql
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SELECT *
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FROM reports
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WHERE ST_Distance_Sphere(
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location,
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ST_GeomFromText('POINT(-6.2603 53.3498)', 4326)
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) <= 5000; -- 5km radius
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```
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### Calculate Hotspots
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```sql
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SELECT
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ST_AsText(ST_Centroid(ST_Collect(location))) as center,
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COUNT(*) as report_count,
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AVG(latitude) as avg_lat,
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AVG(longitude) as avg_lng
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FROM reports
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WHERE created_at >= DATE_SUB(NOW(), INTERVAL 30 DAY)
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GROUP BY ST_GeoHash(location, 7)
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HAVING COUNT(*) >= 5;
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```
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### Find Nearest Event
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```sql
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SELECT id, title, location_name,
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ST_Distance_Sphere(
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location,
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ST_GeomFromText('POINT(-6.2603 53.3498)', 4326)
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) as distance
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FROM events
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WHERE status = 'upcoming'
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ORDER BY distance
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LIMIT 1;
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```
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## Database Maintenance
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### Backup
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```bash
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mysqldump -h 192.168.4.20 -u beach_litter_user -p beach_litter_mapping > backup.sql
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```
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### Restore
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```bash
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mysql -h 192.168.4.20 -u beach_litter_user -p beach_litter_mapping < backup.sql
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```
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### Prisma Studio
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View and edit data in a GUI:
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```bash
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npm run prisma:studio
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```
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## Performance Considerations
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1. **Spatial Indexes**: All location columns have spatial indexes for fast queries
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2. **Composite Indexes**: lat/lng pairs indexed for non-spatial queries
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3. **Date Indexes**: created_at, scheduled_date indexed for time-based filtering
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4. **Foreign Key Indexes**: All foreign keys automatically indexed
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5. **Enum Indexes**: litter_type, status, verification_status indexed for filtering
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## Troubleshooting
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### Connection Issues
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If you can't connect to the database:
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1. Check network connectivity to 192.168.4.20
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2. Verify MySQL is running on port 3306
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3. Confirm user credentials in .env file
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4. Check firewall rules
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### Migration Errors
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If migrations fail:
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1. Check database schema with `npx prisma db pull`
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2. Resolve conflicts manually if needed
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3. Mark migrations as applied: `npx prisma migrate resolve --applied migration_name`
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### Spatial Data Issues
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If spatial queries fail:
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1. Verify MySQL version is 8.0+
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2. Check that spatial indexes exist: `SHOW INDEX FROM reports`
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3. Ensure SRID 4326 is used consistently
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4. Use ST_GeomFromText() for creating POINT values
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## References
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- [Prisma Documentation](https://www.prisma.io/docs)
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- [MySQL Spatial Data Types](https://dev.mysql.com/doc/refman/8.0/en/spatial-types.html)
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- [MySQL Spatial Functions](https://dev.mysql.com/doc/refman/8.0/en/spatial-function-reference.html)
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- [Clerk Authentication](https://clerk.com/docs)
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-- CreateTable
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CREATE TABLE `users` (
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`id` VARCHAR(36) NOT NULL DEFAULT (UUID()),
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`clerk_id` VARCHAR(255) NOT NULL,
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`email` VARCHAR(255) NOT NULL,
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`username` VARCHAR(100) NOT NULL,
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`created_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP,
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`updated_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
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`first_name` VARCHAR(100) NULL,
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`last_name` VARCHAR(100) NULL,
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`avatar_url` VARCHAR(500) NULL,
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`impact_score` INTEGER NULL DEFAULT 0,
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`notification_email` BOOLEAN NULL DEFAULT true,
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`notification_in_app` BOOLEAN NULL DEFAULT true,
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`areas_of_interest` JSON NULL,
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UNIQUE INDEX `clerk_id`(`clerk_id`),
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UNIQUE INDEX `email`(`email`),
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UNIQUE INDEX `username`(`username`),
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INDEX `idx_clerk_id`(`clerk_id`),
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INDEX `idx_email`(`email`),
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INDEX `idx_username`(`username`),
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PRIMARY KEY (`id`)
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) DEFAULT CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci ENGINE=InnoDB;
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-- CreateTable
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CREATE TABLE `reports` (
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`id` VARCHAR(36) NOT NULL DEFAULT (UUID()),
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`user_id` VARCHAR(36) NOT NULL,
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`location` POINT NOT NULL SRID 4326,
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`latitude` DECIMAL(10, 8) NOT NULL,
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`longitude` DECIMAL(11, 8) NOT NULL,
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`location_source` ENUM('exif', 'gps', 'manual') NOT NULL,
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`photo_urls` JSON NOT NULL,
|
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`photo_timestamp` TIMESTAMP(0) NULL,
|
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`litter_type` ENUM('plastic', 'metal', 'glass', 'organic', 'hazardous', 'other') NOT NULL,
|
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`quantity` ENUM('minimal', 'moderate', 'significant', 'severe') NOT NULL,
|
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`description` TEXT NULL,
|
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`created_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP,
|
||||
`updated_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
|
||||
`submitted_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP,
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||||
`verification_status` ENUM('pending', 'verified', 'disputed') NULL DEFAULT 'pending',
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|
||||
INDEX `idx_created_at`(`created_at`),
|
||||
INDEX `idx_lat_lng`(`latitude`, `longitude`),
|
||||
INDEX `idx_litter_type`(`litter_type`),
|
||||
SPATIAL INDEX `idx_location`(`location`),
|
||||
INDEX `user_id`(`user_id`),
|
||||
PRIMARY KEY (`id`)
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||||
) DEFAULT CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci ENGINE=InnoDB;
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||||
|
||||
-- CreateTable
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CREATE TABLE `events` (
|
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`id` VARCHAR(36) NOT NULL DEFAULT (UUID()),
|
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`organizer_id` VARCHAR(36) NOT NULL,
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`title` VARCHAR(255) NOT NULL,
|
||||
`description` TEXT NOT NULL,
|
||||
`location` POINT NOT NULL SRID 4326,
|
||||
`latitude` DECIMAL(10, 8) NOT NULL,
|
||||
`longitude` DECIMAL(11, 8) NOT NULL,
|
||||
`location_name` VARCHAR(255) NOT NULL,
|
||||
`scheduled_date` TIMESTAMP(0) NOT NULL,
|
||||
`duration` INTEGER NOT NULL COMMENT 'Duration in minutes',
|
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`status` ENUM('upcoming', 'completed', 'cancelled') NULL DEFAULT 'upcoming',
|
||||
`participant_count` INTEGER NULL DEFAULT 0,
|
||||
`litter_collected` DECIMAL(10, 2) NULL COMMENT 'Kilograms collected',
|
||||
`photos` JSON NULL,
|
||||
`created_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP,
|
||||
`updated_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
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||||
|
||||
SPATIAL INDEX `idx_location`(`location`),
|
||||
INDEX `idx_scheduled_date`(`scheduled_date`),
|
||||
INDEX `idx_status`(`status`),
|
||||
INDEX `organizer_id`(`organizer_id`),
|
||||
PRIMARY KEY (`id`)
|
||||
) DEFAULT CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci ENGINE=InnoDB;
|
||||
|
||||
-- CreateTable
|
||||
CREATE TABLE `event_registrations` (
|
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`id` VARCHAR(36) NOT NULL DEFAULT (UUID()),
|
||||
`user_id` VARCHAR(36) NOT NULL,
|
||||
`event_id` VARCHAR(36) NOT NULL,
|
||||
`registered_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP,
|
||||
`attended` BOOLEAN NULL DEFAULT false,
|
||||
|
||||
INDEX `event_id`(`event_id`),
|
||||
UNIQUE INDEX `unique_user_event`(`user_id`, `event_id`),
|
||||
PRIMARY KEY (`id`)
|
||||
) DEFAULT CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci ENGINE=InnoDB;
|
||||
|
||||
-- CreateTable
|
||||
CREATE TABLE `verifications` (
|
||||
`id` VARCHAR(36) NOT NULL DEFAULT (UUID()),
|
||||
`report_id` VARCHAR(36) NOT NULL,
|
||||
`user_id` VARCHAR(36) NOT NULL,
|
||||
`verification_type` ENUM('verify', 'dispute') NOT NULL,
|
||||
`comment` TEXT NULL,
|
||||
`created_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP,
|
||||
|
||||
INDEX `user_id`(`user_id`),
|
||||
UNIQUE INDEX `unique_report_user`(`report_id`, `user_id`),
|
||||
PRIMARY KEY (`id`)
|
||||
) DEFAULT CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci ENGINE=InnoDB;
|
||||
|
||||
-- CreateTable
|
||||
CREATE TABLE `environmental_concerns` (
|
||||
`id` VARCHAR(36) NOT NULL DEFAULT (UUID()),
|
||||
`report_id` VARCHAR(36) NOT NULL,
|
||||
`concern_type` VARCHAR(100) NOT NULL COMMENT 'water_quality, erosion, wildlife_impact, algae_bloom, etc.',
|
||||
`severity` ENUM('low', 'medium', 'high', 'critical') NOT NULL,
|
||||
`description` TEXT NOT NULL,
|
||||
`created_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP,
|
||||
|
||||
INDEX `idx_concern_type`(`concern_type`),
|
||||
INDEX `report_id`(`report_id`),
|
||||
PRIMARY KEY (`id`)
|
||||
) DEFAULT CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci ENGINE=InnoDB;
|
||||
|
||||
-- CreateTable
|
||||
CREATE TABLE `hotspots` (
|
||||
`id` VARCHAR(36) NOT NULL DEFAULT (UUID()),
|
||||
`location` POINT NOT NULL SRID 4326,
|
||||
`latitude` DECIMAL(10, 8) NOT NULL,
|
||||
`longitude` DECIMAL(11, 8) NOT NULL,
|
||||
`radius` DECIMAL(10, 2) NOT NULL COMMENT 'Radius in meters',
|
||||
`report_count` INTEGER NOT NULL,
|
||||
`severity_score` DECIMAL(5, 2) NOT NULL,
|
||||
`last_report_date` TIMESTAMP(0) NOT NULL,
|
||||
`calculated_at` TIMESTAMP(0) NULL DEFAULT CURRENT_TIMESTAMP,
|
||||
|
||||
SPATIAL INDEX `idx_location`(`location`),
|
||||
INDEX `idx_severity_score`(`severity_score`),
|
||||
PRIMARY KEY (`id`)
|
||||
) DEFAULT CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci ENGINE=InnoDB;
|
||||
|
||||
-- AddForeignKey
|
||||
ALTER TABLE `reports` ADD CONSTRAINT `reports_ibfk_1` FOREIGN KEY (`user_id`) REFERENCES `users`(`id`) ON DELETE CASCADE ON UPDATE NO ACTION;
|
||||
|
||||
-- AddForeignKey
|
||||
ALTER TABLE `events` ADD CONSTRAINT `events_ibfk_1` FOREIGN KEY (`organizer_id`) REFERENCES `users`(`id`) ON DELETE CASCADE ON UPDATE NO ACTION;
|
||||
|
||||
-- AddForeignKey
|
||||
ALTER TABLE `event_registrations` ADD CONSTRAINT `event_registrations_ibfk_1` FOREIGN KEY (`user_id`) REFERENCES `users`(`id`) ON DELETE CASCADE ON UPDATE NO ACTION;
|
||||
|
||||
-- AddForeignKey
|
||||
ALTER TABLE `event_registrations` ADD CONSTRAINT `event_registrations_ibfk_2` FOREIGN KEY (`event_id`) REFERENCES `events`(`id`) ON DELETE CASCADE ON UPDATE NO ACTION;
|
||||
|
||||
-- AddForeignKey
|
||||
ALTER TABLE `verifications` ADD CONSTRAINT `verifications_ibfk_1` FOREIGN KEY (`report_id`) REFERENCES `reports`(`id`) ON DELETE CASCADE ON UPDATE NO ACTION;
|
||||
|
||||
-- AddForeignKey
|
||||
ALTER TABLE `verifications` ADD CONSTRAINT `verifications_ibfk_2` FOREIGN KEY (`user_id`) REFERENCES `users`(`id`) ON DELETE CASCADE ON UPDATE NO ACTION;
|
||||
|
||||
-- AddForeignKey
|
||||
ALTER TABLE `environmental_concerns` ADD CONSTRAINT `environmental_concerns_ibfk_1` FOREIGN KEY (`report_id`) REFERENCES `reports`(`id`) ON DELETE CASCADE ON UPDATE NO ACTION;
|
||||
@@ -0,0 +1,13 @@
|
||||
-- AlterTable: Add clerk_id column and remove password_hash
|
||||
ALTER TABLE `users` ADD COLUMN `clerk_id` VARCHAR(255) NULL;
|
||||
|
||||
-- Create unique index on clerk_id
|
||||
CREATE UNIQUE INDEX `clerk_id` ON `users`(`clerk_id`);
|
||||
|
||||
-- Create index for clerk_id lookups
|
||||
CREATE INDEX `idx_clerk_id` ON `users`(`clerk_id`);
|
||||
|
||||
-- Drop password_hash column (after data migration if needed)
|
||||
-- Note: In production, you would first migrate existing users to Clerk before dropping this column
|
||||
-- For now, we'll keep it to avoid data loss, but it should be removed after Clerk migration is complete
|
||||
-- ALTER TABLE `users` DROP COLUMN `password_hash`;
|
||||
3
server/prisma/migrations/migration_lock.toml
Normal file
3
server/prisma/migrations/migration_lock.toml
Normal file
@@ -0,0 +1,3 @@
|
||||
# Please do not edit this file manually
|
||||
# It should be added in your version-control system (i.e. Git)
|
||||
provider = "mysql"
|
||||
@@ -21,11 +21,13 @@ model User {
|
||||
notificationEmail Boolean? @default(true) @map("notification_email")
|
||||
notificationInApp Boolean? @default(true) @map("notification_in_app")
|
||||
areasOfInterest Json? @map("areas_of_interest")
|
||||
clerkId String? @unique(map: "clerk_id") @map("clerk_id") @db.VarChar(255)
|
||||
eventRegistrations EventRegistration[]
|
||||
organizedEvents Event[] @relation("EventOrganizer")
|
||||
reports Report[]
|
||||
verifications Verification[]
|
||||
|
||||
@@index([clerkId], map: "idx_clerk_id")
|
||||
@@index([email], map: "idx_email")
|
||||
@@index([username], map: "idx_username")
|
||||
@@map("users")
|
||||
|
||||
@@ -1,7 +1,55 @@
|
||||
/**
|
||||
* Database configuration and Prisma client singleton
|
||||
*/
|
||||
|
||||
import { PrismaClient } from '@prisma/client';
|
||||
|
||||
const prisma = new PrismaClient({
|
||||
log: process.env.NODE_ENV === 'development' ? ['query', 'error', 'warn'] : ['error'],
|
||||
});
|
||||
// PrismaClient is attached to the `global` object in development to prevent
|
||||
// exhausting your database connection limit.
|
||||
const globalForPrisma = global as unknown as { prisma: PrismaClient };
|
||||
|
||||
export const prisma =
|
||||
globalForPrisma.prisma ||
|
||||
new PrismaClient({
|
||||
log: process.env.NODE_ENV === 'development' ? ['query', 'error', 'warn'] : ['error'],
|
||||
});
|
||||
|
||||
if (process.env.NODE_ENV !== 'production') {
|
||||
globalForPrisma.prisma = prisma;
|
||||
}
|
||||
|
||||
/**
|
||||
* Connect to the database
|
||||
*/
|
||||
export async function connectDatabase() {
|
||||
try {
|
||||
await prisma.$connect();
|
||||
console.log('✅ Database connected successfully');
|
||||
} catch (error) {
|
||||
console.error('❌ Database connection failed:', error);
|
||||
process.exit(1);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Disconnect from the database
|
||||
*/
|
||||
export async function disconnectDatabase() {
|
||||
await prisma.$disconnect();
|
||||
console.log('Database disconnected');
|
||||
}
|
||||
|
||||
/**
|
||||
* Health check for database connection
|
||||
*/
|
||||
export async function checkDatabaseHealth(): Promise<boolean> {
|
||||
try {
|
||||
await prisma.$queryRaw`SELECT 1`;
|
||||
return true;
|
||||
} catch (error) {
|
||||
console.error('Database health check failed:', error);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
export default prisma;
|
||||
|
||||
137
server/src/scripts/testDatabase.ts
Normal file
137
server/src/scripts/testDatabase.ts
Normal file
@@ -0,0 +1,137 @@
|
||||
/**
|
||||
* Database connection and spatial support test script
|
||||
* Run with: npx tsx src/scripts/testDatabase.ts
|
||||
*/
|
||||
|
||||
import { prisma } from '../config/database';
|
||||
import { isWithinIreland } from '../utils/spatial';
|
||||
|
||||
async function testDatabaseConnection() {
|
||||
console.log('🔍 Testing database connection and spatial support...\n');
|
||||
|
||||
try {
|
||||
// Test 1: Basic connection
|
||||
console.log('1. Testing database connection...');
|
||||
await prisma.$queryRaw`SELECT 1 as test`;
|
||||
console.log(' ✅ Database connection successful\n');
|
||||
|
||||
// Test 2: Check MySQL version
|
||||
console.log('2. Checking MySQL version...');
|
||||
const version = await prisma.$queryRaw<Array<{ version: string }>>`SELECT VERSION() as version`;
|
||||
console.log(` ✅ MySQL version: ${version[0].version}\n`);
|
||||
|
||||
// Test 3: Verify spatial support
|
||||
console.log('3. Testing spatial support...');
|
||||
const spatialTest = await prisma.$queryRaw<Array<{ point: string; distance: number }>>`
|
||||
SELECT
|
||||
ST_AsText(ST_GeomFromText('POINT(-6.2603 53.3498)', 4326)) as point,
|
||||
ST_Distance_Sphere(
|
||||
ST_GeomFromText('POINT(-6.2603 53.3498)', 4326),
|
||||
ST_GeomFromText('POINT(-6.2603 53.3498)', 4326)
|
||||
) as distance
|
||||
`;
|
||||
console.log(` ✅ Spatial functions working: ${spatialTest[0].point}\n`);
|
||||
|
||||
// Test 4: Check tables exist
|
||||
console.log('4. Checking database tables...');
|
||||
const tables = await prisma.$queryRaw<Array<{ table_name: string }>>`
|
||||
SELECT table_name
|
||||
FROM information_schema.tables
|
||||
WHERE table_schema = DATABASE()
|
||||
ORDER BY table_name
|
||||
`;
|
||||
console.log(` ✅ Found ${tables.length} tables:`);
|
||||
tables.forEach(t => console.log(` - ${t.table_name}`));
|
||||
console.log('');
|
||||
|
||||
// Test 5: Check spatial indexes
|
||||
console.log('5. Checking spatial indexes...');
|
||||
const spatialIndexes = await prisma.$queryRaw<Array<{
|
||||
table_name: string;
|
||||
index_name: string;
|
||||
column_name: string;
|
||||
}>>`
|
||||
SELECT
|
||||
table_name,
|
||||
index_name,
|
||||
column_name
|
||||
FROM information_schema.statistics
|
||||
WHERE table_schema = DATABASE()
|
||||
AND index_type = 'SPATIAL'
|
||||
ORDER BY table_name, index_name
|
||||
`;
|
||||
console.log(` ✅ Found ${spatialIndexes.length} spatial indexes:`);
|
||||
spatialIndexes.forEach(idx =>
|
||||
console.log(` - ${idx.table_name}.${idx.column_name} (${idx.index_name})`)
|
||||
);
|
||||
console.log('');
|
||||
|
||||
// Test 6: Check User table structure
|
||||
console.log('6. Checking User table for Clerk support...');
|
||||
const userColumns = await prisma.$queryRaw<Array<{
|
||||
column_name: string;
|
||||
data_type: string;
|
||||
is_nullable: string;
|
||||
}>>`
|
||||
SELECT column_name, data_type, is_nullable
|
||||
FROM information_schema.columns
|
||||
WHERE table_schema = DATABASE()
|
||||
AND table_name = 'users'
|
||||
ORDER BY ordinal_position
|
||||
`;
|
||||
const hasClerkId = userColumns.some(col => col.column_name === 'clerk_id');
|
||||
if (hasClerkId) {
|
||||
console.log(' ✅ User table has clerk_id column (Clerk authentication ready)');
|
||||
} else {
|
||||
console.log(' ⚠️ User table missing clerk_id column');
|
||||
}
|
||||
console.log('');
|
||||
|
||||
// Test 7: Test coordinate validation
|
||||
console.log('7. Testing coordinate validation...');
|
||||
const dublinCoords = { lat: 53.3498, lng: -6.2603 };
|
||||
const londonCoords = { lat: 51.5074, lng: -0.1278 };
|
||||
|
||||
console.log(` Dublin (${dublinCoords.lat}, ${dublinCoords.lng}): ${
|
||||
isWithinIreland(dublinCoords.lat, dublinCoords.lng) ? '✅ Valid' : '❌ Invalid'
|
||||
}`);
|
||||
console.log(` London (${londonCoords.lat}, ${londonCoords.lng}): ${
|
||||
isWithinIreland(londonCoords.lat, londonCoords.lng) ? '❌ Should be invalid' : '✅ Correctly rejected'
|
||||
}`);
|
||||
console.log('');
|
||||
|
||||
// Test 8: Count existing records
|
||||
console.log('8. Checking existing data...');
|
||||
const userCount = await prisma.user.count();
|
||||
const reportCount = await prisma.report.count();
|
||||
const eventCount = await prisma.event.count();
|
||||
console.log(` Users: ${userCount}`);
|
||||
console.log(` Reports: ${reportCount}`);
|
||||
console.log(` Events: ${eventCount}`);
|
||||
console.log('');
|
||||
|
||||
console.log('✅ All database tests passed!\n');
|
||||
console.log('Database is ready for use with:');
|
||||
console.log(' - MySQL 8.0+ with spatial support');
|
||||
console.log(' - Clerk authentication (clerk_id field)');
|
||||
console.log(' - Spatial indexes on location columns');
|
||||
console.log(' - All required tables and relationships');
|
||||
|
||||
} catch (error) {
|
||||
console.error('❌ Database test failed:', error);
|
||||
throw error;
|
||||
} finally {
|
||||
await prisma.$disconnect();
|
||||
}
|
||||
}
|
||||
|
||||
// Run the test
|
||||
testDatabaseConnection()
|
||||
.then(() => {
|
||||
console.log('\n✅ Test completed successfully');
|
||||
process.exit(0);
|
||||
})
|
||||
.catch((error) => {
|
||||
console.error('\n❌ Test failed:', error);
|
||||
process.exit(1);
|
||||
});
|
||||
315
server/src/utils/spatial.ts
Normal file
315
server/src/utils/spatial.ts
Normal file
@@ -0,0 +1,315 @@
|
||||
/**
|
||||
* Spatial utility functions for working with MySQL spatial data types
|
||||
* and performing geographical calculations
|
||||
*/
|
||||
|
||||
import { PrismaClient } from '@prisma/client';
|
||||
|
||||
const prisma = new PrismaClient();
|
||||
|
||||
/**
|
||||
* Create a POINT geometry from latitude and longitude
|
||||
* @param latitude - Latitude in decimal degrees
|
||||
* @param longitude - Longitude in decimal degrees
|
||||
* @returns SQL fragment for creating a POINT
|
||||
*/
|
||||
export function createPoint(latitude: number, longitude: number): string {
|
||||
return `ST_GeomFromText('POINT(${longitude} ${latitude})', 4326)`;
|
||||
}
|
||||
|
||||
/**
|
||||
* Find reports within a radius of a given location
|
||||
* @param latitude - Center latitude
|
||||
* @param longitude - Center longitude
|
||||
* @param radiusMeters - Radius in meters
|
||||
* @param limit - Maximum number of results
|
||||
* @returns Array of reports with distance
|
||||
*/
|
||||
export async function findReportsNearby(
|
||||
latitude: number,
|
||||
longitude: number,
|
||||
radiusMeters: number,
|
||||
limit: number = 50
|
||||
) {
|
||||
const results = await prisma.$queryRaw<Array<{
|
||||
id: string;
|
||||
user_id: string;
|
||||
latitude: number;
|
||||
longitude: number;
|
||||
litter_type: string;
|
||||
quantity: string;
|
||||
distance: number;
|
||||
}>>`
|
||||
SELECT
|
||||
id,
|
||||
user_id,
|
||||
latitude,
|
||||
longitude,
|
||||
litter_type,
|
||||
quantity,
|
||||
ST_Distance_Sphere(
|
||||
location,
|
||||
ST_GeomFromText(${`POINT(${longitude} ${latitude})`}, 4326)
|
||||
) as distance
|
||||
FROM reports
|
||||
WHERE ST_Distance_Sphere(
|
||||
location,
|
||||
ST_GeomFromText(${`POINT(${longitude} ${latitude})`}, 4326)
|
||||
) <= ${radiusMeters}
|
||||
ORDER BY distance
|
||||
LIMIT ${limit}
|
||||
`;
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
/**
|
||||
* Find events within a radius of a given location
|
||||
* @param latitude - Center latitude
|
||||
* @param longitude - Center longitude
|
||||
* @param radiusMeters - Radius in meters
|
||||
* @param limit - Maximum number of results
|
||||
* @returns Array of events with distance
|
||||
*/
|
||||
export async function findEventsNearby(
|
||||
latitude: number,
|
||||
longitude: number,
|
||||
radiusMeters: number,
|
||||
limit: number = 50
|
||||
) {
|
||||
const results = await prisma.$queryRaw<Array<{
|
||||
id: string;
|
||||
title: string;
|
||||
location_name: string;
|
||||
latitude: number;
|
||||
longitude: number;
|
||||
scheduled_date: Date;
|
||||
distance: number;
|
||||
}>>`
|
||||
SELECT
|
||||
id,
|
||||
title,
|
||||
location_name,
|
||||
latitude,
|
||||
longitude,
|
||||
scheduled_date,
|
||||
ST_Distance_Sphere(
|
||||
location,
|
||||
ST_GeomFromText(${`POINT(${longitude} ${latitude})`}, 4326)
|
||||
) as distance
|
||||
FROM events
|
||||
WHERE status = 'upcoming'
|
||||
AND ST_Distance_Sphere(
|
||||
location,
|
||||
ST_GeomFromText(${`POINT(${longitude} ${latitude})`}, 4326)
|
||||
) <= ${radiusMeters}
|
||||
ORDER BY distance
|
||||
LIMIT ${limit}
|
||||
`;
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate hotspots based on report clustering
|
||||
* Identifies areas with 5+ reports within 500m in the last 30 days
|
||||
* @returns Array of hotspot locations with statistics
|
||||
*/
|
||||
export async function calculateHotspots() {
|
||||
const results = await prisma.$queryRaw<Array<{
|
||||
center_lat: number;
|
||||
center_lng: number;
|
||||
report_count: number;
|
||||
avg_severity: number;
|
||||
last_report_date: Date;
|
||||
}>>`
|
||||
SELECT
|
||||
AVG(latitude) as center_lat,
|
||||
AVG(longitude) as center_lng,
|
||||
COUNT(*) as report_count,
|
||||
AVG(CASE
|
||||
WHEN quantity = 'minimal' THEN 1
|
||||
WHEN quantity = 'moderate' THEN 2
|
||||
WHEN quantity = 'significant' THEN 3
|
||||
WHEN quantity = 'severe' THEN 4
|
||||
ELSE 0
|
||||
END) as avg_severity,
|
||||
MAX(created_at) as last_report_date
|
||||
FROM reports
|
||||
WHERE created_at >= DATE_SUB(NOW(), INTERVAL 30 DAY)
|
||||
GROUP BY ST_GeoHash(location, 7)
|
||||
HAVING COUNT(*) >= 5
|
||||
ORDER BY report_count DESC, avg_severity DESC
|
||||
`;
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate distance between two points in meters
|
||||
* @param lat1 - First point latitude
|
||||
* @param lon1 - First point longitude
|
||||
* @param lat2 - Second point latitude
|
||||
* @param lon2 - Second point longitude
|
||||
* @returns Distance in meters
|
||||
*/
|
||||
export async function calculateDistance(
|
||||
lat1: number,
|
||||
lon1: number,
|
||||
lat2: number,
|
||||
lon2: number
|
||||
): Promise<number> {
|
||||
const result = await prisma.$queryRaw<Array<{ distance: number }>>`
|
||||
SELECT ST_Distance_Sphere(
|
||||
ST_GeomFromText(${`POINT(${lon1} ${lat1})`}, 4326),
|
||||
ST_GeomFromText(${`POINT(${lon2} ${lat2})`}, 4326)
|
||||
) as distance
|
||||
`;
|
||||
|
||||
return result[0]?.distance || 0;
|
||||
}
|
||||
|
||||
/**
|
||||
* Validate if coordinates are within Irish boundaries
|
||||
* Approximate bounding box for Ireland
|
||||
* @param latitude - Latitude to validate
|
||||
* @param longitude - Longitude to validate
|
||||
* @returns True if coordinates are within Ireland
|
||||
*/
|
||||
export function isWithinIreland(latitude: number, longitude: number): boolean {
|
||||
// Ireland bounding box (approximate)
|
||||
const MIN_LAT = 51.4;
|
||||
const MAX_LAT = 55.4;
|
||||
const MIN_LNG = -10.5;
|
||||
const MAX_LNG = -5.5;
|
||||
|
||||
return (
|
||||
latitude >= MIN_LAT &&
|
||||
latitude <= MAX_LAT &&
|
||||
longitude >= MIN_LNG &&
|
||||
longitude <= MAX_LNG
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* Find reports within a bounding box
|
||||
* @param minLat - Minimum latitude
|
||||
* @param maxLat - Maximum latitude
|
||||
* @param minLng - Minimum longitude
|
||||
* @param maxLng - Maximum longitude
|
||||
* @returns Array of reports within the bounding box
|
||||
*/
|
||||
export async function findReportsInBounds(
|
||||
minLat: number,
|
||||
maxLat: number,
|
||||
minLng: number,
|
||||
maxLng: number
|
||||
) {
|
||||
const results = await prisma.$queryRaw<Array<{
|
||||
id: string;
|
||||
latitude: number;
|
||||
longitude: number;
|
||||
litter_type: string;
|
||||
quantity: string;
|
||||
created_at: Date;
|
||||
}>>`
|
||||
SELECT
|
||||
id,
|
||||
latitude,
|
||||
longitude,
|
||||
litter_type,
|
||||
quantity,
|
||||
created_at
|
||||
FROM reports
|
||||
WHERE latitude BETWEEN ${minLat} AND ${maxLat}
|
||||
AND longitude BETWEEN ${minLng} AND ${maxLng}
|
||||
ORDER BY created_at DESC
|
||||
`;
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
/**
|
||||
* Insert a report with spatial data
|
||||
* @param data - Report data including coordinates
|
||||
* @returns Created report
|
||||
*/
|
||||
export async function createReportWithLocation(data: {
|
||||
userId: string;
|
||||
latitude: number;
|
||||
longitude: number;
|
||||
locationSource: string;
|
||||
litterType: string;
|
||||
quantity: string;
|
||||
photoUrls: string[];
|
||||
photoTimestamp?: Date;
|
||||
description?: string;
|
||||
}) {
|
||||
// First create the report without the location POINT
|
||||
const report = await prisma.$executeRaw`
|
||||
INSERT INTO reports (
|
||||
id, user_id, latitude, longitude, location, location_source,
|
||||
litter_type, quantity, photo_urls, photo_timestamp, description
|
||||
) VALUES (
|
||||
UUID(),
|
||||
${data.userId},
|
||||
${data.latitude},
|
||||
${data.longitude},
|
||||
ST_GeomFromText(${`POINT(${data.longitude} ${data.latitude})`}, 4326),
|
||||
${data.locationSource},
|
||||
${data.litterType},
|
||||
${data.quantity},
|
||||
${JSON.stringify(data.photoUrls)},
|
||||
${data.photoTimestamp || null},
|
||||
${data.description || null}
|
||||
)
|
||||
`;
|
||||
|
||||
return report;
|
||||
}
|
||||
|
||||
/**
|
||||
* Update hotspots table with calculated data
|
||||
* Should be run periodically (e.g., every 15 minutes)
|
||||
*/
|
||||
export async function updateHotspotsTable() {
|
||||
// Clear old hotspots
|
||||
await prisma.$executeRaw`DELETE FROM hotspots WHERE calculated_at < DATE_SUB(NOW(), INTERVAL 1 HOUR)`;
|
||||
|
||||
// Calculate and insert new hotspots
|
||||
const hotspots = await calculateHotspots();
|
||||
|
||||
for (const hotspot of hotspots) {
|
||||
const severityScore = hotspot.report_count * hotspot.avg_severity;
|
||||
|
||||
await prisma.$executeRaw`
|
||||
INSERT INTO hotspots (
|
||||
id, latitude, longitude, location, radius,
|
||||
report_count, severity_score, last_report_date
|
||||
) VALUES (
|
||||
UUID(),
|
||||
${hotspot.center_lat},
|
||||
${hotspot.center_lng},
|
||||
ST_GeomFromText(${`POINT(${hotspot.center_lng} ${hotspot.center_lat})`}, 4326),
|
||||
500,
|
||||
${hotspot.report_count},
|
||||
${severityScore},
|
||||
${hotspot.last_report_date}
|
||||
)
|
||||
`;
|
||||
}
|
||||
|
||||
return hotspots.length;
|
||||
}
|
||||
|
||||
export default {
|
||||
createPoint,
|
||||
findReportsNearby,
|
||||
findEventsNearby,
|
||||
calculateHotspots,
|
||||
calculateDistance,
|
||||
isWithinIreland,
|
||||
findReportsInBounds,
|
||||
createReportWithLocation,
|
||||
updateHotspotsTable,
|
||||
};
|
||||
Reference in New Issue
Block a user