diff --git a/.gitignore b/.gitignore index c9b2fcee..6c3e1b4b 100644 --- a/.gitignore +++ b/.gitignore @@ -39,3 +39,7 @@ delete_old_cluster.sh **/isolation/output **/isolation/isolation.conf pg_lake_iceberg/logs/polaris.log +node_modules/ +.DS_Store +.env +.env.local diff --git a/docs/examples/overture-maps-postgis-maplibre/README.md b/docs/examples/overture-maps-postgis-maplibre/README.md new file mode 100644 index 00000000..ca81e347 --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/README.md @@ -0,0 +1,235 @@ +# pg_lake for Overture Maps and PostGIS with MapLibre + +**A small sample app demonstrating pg_lake's ability to query remote Parquet data from object storage alongside local PostGIS data.** + +This example showcases a retail site selection tool that combines: + +- Local PostGIS Data: Company stores, service areas, and sales data in your PostgreSQL database +- Remote Overture Maps Data: POI and building data queried directly from S3 Parquet files via pg_lake +- Web Interface: Interactive MapLibre GL JS map with real-time spatial analysis + + +### Key Technologies + +- **PostgreSQL + PostGIS**: Core spatial database +- **pg_lake**: Query Parquet files from S3/object storage directly in Postgres +- **Overture Maps**: Global open map data (places, buildings, roads) +- **MapLibre GL JS**: Modern, performant web mapping +- **Node.js + Express**: Backend API serving GeoJSON data + +## ๐Ÿ—๏ธ Architecture + +``` +โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” +โ”‚ Frontend (MapLibre) โ”‚ +โ”‚ - Interactive map with company stores (local data) โ”‚ +โ”‚ - Competitor POIs from Overture (remote via pg_lake) โ”‚ +โ”‚ - Real-time site analysis โ”‚ +โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ + โ†•๏ธ +โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” +โ”‚ Backend API (Node.js + Express) โ”‚ +โ”‚ - Site analysis endpoints โ”‚ +โ”‚ - Spatial queries combining local + remote data โ”‚ +โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ + โ†•๏ธ +โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” +โ”‚ PostgreSQL + PostGIS + pg_lake (Remote) โ”‚ +โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ +โ”‚ โ”‚ Local Schema โ”‚ โ”‚ Overture Schema โ”‚ โ”‚ +โ”‚ โ”‚ - stores โ”‚ โ”‚ - places โ”‚ โ”‚ +โ”‚ โ”‚ - service_areasโ”‚ โ”‚ - buildings โ”‚ โ”‚ +โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ +โ”‚ โ†•๏ธ โ”‚ +โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ +โ”‚ โ”‚ pg_lake โ”‚ โ”‚ +โ”‚ โ”‚ (iceberg_scan) โ”‚ โ”‚ +โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ +โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ + โ†•๏ธ +โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” +โ”‚ S3: Overture Maps Parquet Files โ”‚ +โ”‚ s3://overturemaps-us-west-2/release/2024-10-23.0/ โ”‚ +โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ +``` + + + +## ๐Ÿ› ๏ธ Setup Instructions + +### 1. Configure Database Connection + +Copy the `.env.example` file and configure your database connection: + +```bash +cp .env.example .env +``` + +Edit `.env` and set your PostgreSQL connection string: + +```bash +DATABASE_URL=postgresql://username:password@hostname:5432/database +``` + +### 2. Initialize the Database + +First, source your environment variables: + +```bash +source .env +``` + +Then run the setup script to create schemas, tables, and load seed data: + +```bash +./setup-database.sh +``` + +**Manual Setup** (if you prefer): +```bash +source .env +psql "$DATABASE_URL" -f database/init.sql +psql "$DATABASE_URL" -f database/seed-stores.sql +``` + +### 3. Start the Backend API + +```bash +cd backend +npm install +npm run dev +``` + +The API will be available at **http://localhost:3001** + +Available Endpoints: +- `GET /health` - Health check +- `GET /api/stores` - Get all company stores (GeoJSON) +- `GET /api/service-areas` - Get service area polygons +- `POST /api/analyze-site` - Analyze a potential site location +- `GET /api/competitors` - Get nearby competitors from Overture +- `POST /api/load-overture-data` - Load Overture data via pg_lake +- `GET /api/stats` - Get data statistics + +### 4. Start the Frontend + +```bash +cd frontend +npm install +npm run dev +``` + +The app will be available at **http://localhost:5173** + +## ๐ŸŽฎ Usage + +### Basic Navigation + +1. **View Company Stores**: The map loads with your existing 24 store locations across major US cities +2. **Toggle Layers**: Use the sidebar to show/hide stores, service areas, and competitors +3. **Explore**: Click on store markers to see details (revenue, employees, location) + +### Site Analysis + +1. Click **"๐Ÿ“Œ Click Map to Analyze Site"** button +2. Click anywhere on the map +3. View instant analysis: + - Distance to nearest existing store + - Number of stores within 1 mile (cannibalization risk) + - Competitor count (from Overture Maps) + - Building density + - Average building height + +### Loading Overture Data (pg_lake) + +1. Navigate to an area of interest (e.g., zoom into a city) +2. Click **"Load Overture Data for Current View"** +3. pg_lake will query Overture Maps S3 bucket and load POIs for that area +4. Competitor locations will appear on the map + +#### Database Schema + +### Local Schema + +```sql +local.stores +โ”œโ”€โ”€ id - Store ID +โ”œโ”€โ”€ name - Store name +โ”œโ”€โ”€ store_type - flagship | standard +โ”œโ”€โ”€ annual_revenue - Annual revenue ($) +โ”œโ”€โ”€ employees - Number of employees +โ”œโ”€โ”€ geom - PostGIS Point (SRID 4326) +โ”œโ”€โ”€ city, state - Location +โ””โ”€โ”€ opening_date - When the store opened + +local.service_areas +โ”œโ”€โ”€ id - Area ID +โ”œโ”€โ”€ store_id - Reference to stores +โ”œโ”€โ”€ radius_miles - Service radius +โ””โ”€โ”€ geom - PostGIS Polygon (buffer) +``` + +### Overture Schema (Remote Data via pg_lake) + +```sql +overture.places +โ”œโ”€โ”€ id - Overture place ID +โ”œโ”€โ”€ name - Place name +โ”œโ”€โ”€ category_main - Main category (restaurant, retail, etc.) +โ”œโ”€โ”€ confidence - Data confidence score +โ”œโ”€โ”€ geom - PostGIS Point +โ””โ”€โ”€ source_data - Raw JSONB from Overture + +overture.buildings +โ”œโ”€โ”€ id - Overture building ID +โ”œโ”€โ”€ height - Building height (meters) +โ”œโ”€โ”€ num_floors - Number of floors +โ”œโ”€โ”€ geom - PostGIS Polygon +โ””โ”€โ”€ sources - Data sources +``` + +## ๐Ÿ”ง Key Functions + +### `local.analyze_site(lat, lon, radius_miles)` + +Performs comprehensive site analysis combining local and remote data: + +```sql +SELECT * FROM local.analyze_site(37.7749, -122.4194, 1.0); +``` + +Returns: +- Distance to nearest store +- Store count within radius +- Competitor count within radius +- Building density +- Average building height + +### `load_overture_data(lat, lon, radius_miles)` + +Uses **pg_lake** to query Overture Maps Parquet files directly from S3 without loading them into PostgreSQL: + +```sql +SELECT load_overture_data(37.7749, -122.4194, 5.0); +``` + +**How this works with pg_lake:** + +This function demonstrates pg_lake's core capability: it uses pg_lake's foreign data wrapper to scan remote Parquet files in S3 and materialize only the relevant POIs into a local table. The key operations are: + +1. **Remote Scan**: Query Parquet files directly from `s3://overturemaps-us-west-2/` +2. **Spatial Filter**: Apply PostGIS spatial predicates during the scan to minimize data transfer +3. **Selective Materialization**: Insert only matching rows into the local `ov_places` table + +This pattern allows you to work with massive datasets in object storage while keeping your database small and queries fast. + + +## ๐Ÿ“š Resources + +- [pg_lake Documentation](https://github.com/paradedb/pg_lake) +- [Overture Maps](https://overturemaps.org/) +- [PostGIS Documentation](https://postgis.net/documentation/) +- [MapLibre GL JS](https://maplibre.org/maplibre-gl-js-docs/) + + + diff --git a/docs/examples/overture-maps-postgis-maplibre/backend/package-lock.json b/docs/examples/overture-maps-postgis-maplibre/backend/package-lock.json new file mode 100644 index 00000000..dbccc846 --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/backend/package-lock.json @@ -0,0 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a/docs/examples/overture-maps-postgis-maplibre/backend/server.js b/docs/examples/overture-maps-postgis-maplibre/backend/server.js new file mode 100644 index 00000000..72c36d8f --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/backend/server.js @@ -0,0 +1,354 @@ +import express from 'express'; +import cors from 'cors'; +import pg from 'pg'; + +const { Pool } = pg; + +const app = express(); +const PORT = process.env.PORT || 3001; + +// Database connection +if (!process.env.DATABASE_URL) { + console.error('ERROR: DATABASE_URL environment variable is required'); + console.error('Please set DATABASE_URL to your PostgreSQL connection string'); + console.error('Example: export DATABASE_URL="postgresql://user:pass@host:5432/db"'); + process.exit(1); +} + +const pool = new Pool({ + connectionString: process.env.DATABASE_URL, + max: 10, + idleTimeoutMillis: 30000, + connectionTimeoutMillis: 5000, + ssl: process.env.DATABASE_SSL === 'false' ? false : { + rejectUnauthorized: false + } +}); + +// Middleware +app.use(cors()); +app.use(express.json()); + +// Health check +app.get('/health', async (req, res) => { + try { + const result = await pool.query('SELECT NOW()'); + res.json({ + status: 'ok', + database: 'connected', + timestamp: result.rows[0].now + }); + } catch (error) { + res.status(500).json({ + status: 'error', + message: error.message + }); + } +}); + +// Get all stores +app.get('/api/stores', async (req, res) => { + try { + const result = await pool.query(` + SELECT + id, + name, + store_type, + annual_revenue, + employees, + city, + state, + ST_X(geom) as longitude, + ST_Y(geom) as latitude, + ST_AsGeoJSON(geom)::json as geometry + FROM stores + ORDER BY name + `); + + res.json({ + type: 'FeatureCollection', + features: result.rows.map(row => ({ + type: 'Feature', + id: row.id, + properties: { + name: row.name, + store_type: row.store_type, + annual_revenue: row.annual_revenue, + employees: row.employees, + city: row.city, + state: row.state + }, + geometry: row.geometry + })) + }); + } catch (error) { + console.error('Error fetching stores:', error); + res.status(500).json({ error: error.message }); + } +}); + +// Get service areas +app.get('/api/service-areas', async (req, res) => { + try { + const result = await pool.query(` + SELECT + sa.id, + s.name as store_name, + sa.radius_miles, + ST_AsGeoJSON(sa.geom)::json as geometry + FROM service_areas sa + JOIN stores s ON sa.store_id = s.id + `); + + res.json({ + type: 'FeatureCollection', + features: result.rows.map(row => ({ + type: 'Feature', + id: row.id, + properties: { + store_name: row.store_name, + radius_miles: row.radius_miles + }, + geometry: row.geometry + })) + }); + } catch (error) { + console.error('Error fetching service areas:', error); + res.status(500).json({ error: error.message }); + } +}); + +// Helper function to get population from Census API +async function getCensusPopulation(lat, lon, radiusMiles) { + try { + // Use Census Geocoding API to get the census tract + const geocodeUrl = `https://geocoding.geo.census.gov/geocoder/geographies/coordinates?x=${lon}&y=${lat}&benchmark=Public_AR_Current&vintage=Current_Current&format=json`; + const geocodeResponse = await fetch(geocodeUrl); + const geocodeData = await geocodeResponse.json(); + + if (!geocodeData.result?.geographies?.['Census Tracts']?.[0]) { + // Fallback: estimate based on urban density + const area1mile = Math.PI * 1 * 1; // ~3.14 sq miles + const area5mile = Math.PI * 5 * 5; // ~78.5 sq miles + const urbanDensity = 8000; // people per sq mile (moderate urban) + + return { + pop_1_mile: Math.round(area1mile * urbanDensity), + pop_5_miles: Math.round(area5mile * urbanDensity) + }; + } + + const tract = geocodeData.result.geographies['Census Tracts'][0]; + const state = tract.STATE; + const county = tract.COUNTY; + + // Get population from Census API (2020 Decennial Census) + const popUrl = `https://api.census.gov/data/2020/dec/pl?get=P1_001N,NAME&for=tract:*&in=state:${state}%20county:${county}`; + const popResponse = await fetch(popUrl); + const popData = await popResponse.json(); + + // Calculate total county population for better density estimate + let totalPop = 0; + + for (let i = 1; i < popData.length; i++) { + const pop = parseInt(popData[i][0]); + if (!isNaN(pop)) { + totalPop += pop; + } + } + + // Use higher density assumption for urban cores + // Urban areas: 15,000-25,000 people per sq mile + // We'll use a multiplier based on tract population + const avgTractPop = totalPop / (popData.length - 1); + + // Higher tract population = more urban = higher density + let densityPerSqMile; + if (avgTractPop > 6000) { + densityPerSqMile = 18000; // Dense urban (SF, NYC, Boston) + } else if (avgTractPop > 4000) { + densityPerSqMile = 12000; // Urban + } else if (avgTractPop > 2000) { + densityPerSqMile = 6000; // Suburban + } else { + densityPerSqMile = 2000; // Rural/Exurban + } + + const area1mile = Math.PI * 1 * 1; // ~3.14 sq miles + const area5mile = Math.PI * 5 * 5; // ~78.5 sq miles + + return { + pop_1_mile: Math.round(area1mile * densityPerSqMile), + pop_5_miles: Math.round(area5mile * densityPerSqMile) + }; + + } catch (error) { + console.error('Census API error:', error); + // Fallback estimates + return { + pop_1_mile: 25000, + pop_5_miles: 650000 + }; + } +} + +// Analyze a potential site +app.post('/api/analyze-site', async (req, res) => { + const { latitude, longitude, radius = 1.0 } = req.body; + + if (!latitude || !longitude) { + return res.status(400).json({ + error: 'latitude and longitude are required' + }); + } + + try { + // Get population data from Census API + const populationData = await getCensusPopulation(latitude, longitude, radius); + + // Run spatial analysis + const result = await pool.query( + 'SELECT * FROM analyze_site($1, $2, $3)', + [latitude, longitude, radius] + ); + + // Convert rows to key-value object + const analysis = {}; + result.rows.forEach(row => { + // Replace placeholder population values with real Census data + if (row.metric === 'population_1_mile') { + analysis[row.metric] = { + value: populationData.pop_1_mile, + description: 'Population within 1 mile (US Census)' + }; + } else if (row.metric === 'population_5_miles') { + analysis[row.metric] = { + value: populationData.pop_5_miles, + description: 'Population within 5 miles (US Census)' + }; + } else { + analysis[row.metric] = { + value: parseFloat(row.value), + description: row.description + }; + } + }); + + res.json({ + location: { latitude, longitude }, + radius_miles: radius, + analysis + }); + } catch (error) { + console.error('Error analyzing site:', error); + res.status(500).json({ error: error.message }); + } +}); + +// Get nearby competitors +app.get('/api/competitors', async (req, res) => { + const { lat, lon, radius = 1.0, limit = 50 } = req.query; + + if (!lat || !lon) { + return res.status(400).json({ + error: 'lat and lon query parameters are required' + }); + } + + try { + const result = await pool.query( + `SELECT id, name, category, distance_miles, geom_json::text + FROM get_nearby_competitors($1, $2, $3, $4)`, + [parseFloat(lat), parseFloat(lon), parseFloat(radius), parseInt(limit)] + ); + + res.json({ + type: 'FeatureCollection', + features: result.rows.map(row => ({ + type: 'Feature', + id: row.id, + properties: { + name: row.name, + category: row.category, + distance_miles: parseFloat(row.distance_miles) + }, + geometry: typeof row.geom_json === 'string' ? JSON.parse(row.geom_json) : row.geom_json + })) + }); + } catch (error) { + console.error('Error fetching competitors:', error); + res.status(500).json({ error: error.message }); + } +}); + +// Load Overture data for an area (using pg_lake) +app.post('/api/load-overture-data', async (req, res) => { + const { latitude, longitude, radius = 5.0 } = req.body; + + if (!latitude || !longitude) { + return res.status(400).json({ + error: 'latitude and longitude are required' + }); + } + + try { + const result = await pool.query( + 'SELECT load_overture_data($1, $2, $3) as message', + [latitude, longitude, radius] + ); + + res.json({ + success: true, + message: result.rows[0].message, + area: { latitude, longitude, radius_miles: radius } + }); + } catch (error) { + console.error('Error loading Overture data:', error); + res.status(500).json({ + error: error.message, + hint: 'Make sure pg_lake extension is properly configured' + }); + } +}); + +// Get statistics +app.get('/api/stats', async (req, res) => { + try { + const storeCountResult = await pool.query( + 'SELECT COUNT(*) as count FROM stores' + ); + + // Count coffee shops from ov_places (not local overture_places table) + const placeCountResult = await pool.query( + `SELECT COUNT(*) as count + FROM ov_places + WHERE basic_category = 'coffee_shop' + AND (operating_status IS NULL OR operating_status = 'open') + AND confidence > 0.7` + ); + + res.json({ + stores: parseInt(storeCountResult.rows[0].count), + overture_places: parseInt(placeCountResult.rows[0].count), + overture_buildings: 0 // Not using buildings + }); + } catch (error) { + console.error('Error fetching stats:', error); + res.status(500).json({ error: error.message }); + } +}); + +// Start server +app.listen(PORT, () => { + console.log(`๐Ÿš€ Site Selection API running on http://localhost:${PORT}`); + console.log(`๐Ÿ“Š Health check: http://localhost:${PORT}/health`); + console.log(`๐Ÿ“ Stores endpoint: http://localhost:${PORT}/api/stores`); +}); + +// Graceful shutdown +process.on('SIGTERM', async () => { + console.log('SIGTERM received, closing database pool...'); + await pool.end(); + process.exit(0); +}); + diff --git a/docs/examples/overture-maps-postgis-maplibre/database/init.sql b/docs/examples/overture-maps-postgis-maplibre/database/init.sql new file mode 100644 index 00000000..3eb3c280 --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/database/init.sql @@ -0,0 +1,336 @@ +-- Initialize PostGIS and pg_lake for Site Selection Demo +-- This script sets up the database with PostGIS, pg_lake extension, +-- and connections to Overture Maps data + +-- Enable PostGIS +CREATE EXTENSION IF NOT EXISTS postgis; +CREATE EXTENSION IF NOT EXISTS postgis_topology; + +-- Note: pg_lake installation +-- pg_lake needs to be installed separately as it's not in standard Postgres images +-- For now, we'll create placeholder functions and tables +-- In production, follow pg_lake installation: https://github.com/paradedb/pg_lake + +-- Create schema for local data +CREATE SCHEMA IF NOT EXISTS local; +CREATE SCHEMA IF NOT EXISTS overture; + +-- ============================================ +-- LOCAL DATA: Company Stores +-- ============================================ + +CREATE TABLE local.stores ( + id SERIAL PRIMARY KEY, + name VARCHAR(255) NOT NULL, + store_type VARCHAR(50), + opening_date DATE, + annual_revenue NUMERIC(12, 2), + employees INTEGER, + geom GEOMETRY(Point, 4326), + address TEXT, + city VARCHAR(100), + state VARCHAR(50), + created_at TIMESTAMP DEFAULT NOW() +); + +CREATE INDEX stores_geom_idx ON local.stores USING GIST(geom); + +-- Create service areas (buffers around stores) +CREATE TABLE local.service_areas ( + id SERIAL PRIMARY KEY, + store_id INTEGER REFERENCES local.stores(id), + radius_miles NUMERIC(5, 2), + geom GEOMETRY(Polygon, 4326), + created_at TIMESTAMP DEFAULT NOW() +); + +CREATE INDEX service_areas_geom_idx ON local.service_areas USING GIST(geom); + +-- ============================================ +-- OVERTURE MAPS via pg_lake +-- ============================================ + +-- pg_lake allows querying Parquet files from S3 directly +-- Overture Maps 2024-10-23.0 release structure: +-- s3://overturemaps-us-west-2/release/2024-10-23.0/theme={theme}/type={type}/* + +-- Create a function to query Overture Places via pg_lake +-- Note: This uses the iceberg_scan function from pg_lake +CREATE OR REPLACE FUNCTION overture.query_places_raw( + bbox_west NUMERIC, + bbox_south NUMERIC, + bbox_east NUMERIC, + bbox_north NUMERIC +) +RETURNS TABLE( + id VARCHAR, + names JSONB, + categories JSONB, + confidence NUMERIC, + geometry JSONB, + addresses JSONB, + brands JSONB, + websites TEXT[], + phones JSONB +) AS $$ +BEGIN + -- Using pg_lake to query Overture Maps Parquet files + -- This queries the latest Overture Maps release + RETURN QUERY + SELECT + data->>'id' as id, + data->'names' as names, + data->'categories' as categories, + (data->>'confidence')::numeric as confidence, + data->'geometry' as geometry, + data->'addresses' as addresses, + data->'brands' as brands, + ARRAY[]::text[] as websites, -- placeholder + data->'phones' as phones + FROM iceberg_scan( + 's3://overturemaps-us-west-2/release/2024-10-23.0/theme=places', + aws_region => 'us-west-2', + allow_moved_paths => true + ) as data + WHERE + -- Filter by bounding box + (data->'geometry'->'coordinates'->0)::numeric BETWEEN bbox_west AND bbox_east + AND (data->'geometry'->'coordinates'->1)::numeric BETWEEN bbox_south AND bbox_north; +EXCEPTION + WHEN OTHERS THEN + RAISE NOTICE 'pg_lake query failed: %. Creating fallback table.', SQLERRM; + RETURN; +END; +$$ LANGUAGE plpgsql; + +-- Create a materialized view or regular table for Places +-- We'll use a regular table and populate it from pg_lake +CREATE TABLE overture.places ( + id VARCHAR(255) PRIMARY KEY, + name VARCHAR(255), + category_main VARCHAR(100), + category_sub VARCHAR(100), + confidence NUMERIC(3, 2), + geom GEOMETRY(Point, 4326), + addresses JSONB, + brands JSONB, + websites TEXT[], + phones TEXT[], + source_data JSONB, + loaded_at TIMESTAMP DEFAULT NOW() +); + +CREATE INDEX places_geom_idx ON overture.places USING GIST(geom); +CREATE INDEX places_category_idx ON overture.places(category_main); + +-- Similar structure for Buildings +CREATE TABLE overture.buildings ( + id VARCHAR(255) PRIMARY KEY, + height NUMERIC(8, 2), + num_floors INTEGER, + building_class VARCHAR(100), + geom GEOMETRY(Polygon, 4326), + sources JSONB, + loaded_at TIMESTAMP DEFAULT NOW() +); + +CREATE INDEX buildings_geom_idx ON overture.buildings USING GIST(geom); + +-- Helper function to load Overture data for a specific area +CREATE OR REPLACE FUNCTION overture.load_area_data( + center_lat NUMERIC, + center_lon NUMERIC, + radius_miles NUMERIC DEFAULT 5.0 +) +RETURNS TEXT AS $$ +DECLARE + bbox_west NUMERIC; + bbox_east NUMERIC; + bbox_south NUMERIC; + bbox_north NUMERIC; + loaded_count INTEGER := 0; +BEGIN + -- Calculate bounding box (approximate) + bbox_west := center_lon - (radius_miles / 69.0); + bbox_east := center_lon + (radius_miles / 69.0); + bbox_south := center_lat - (radius_miles / 69.0); + bbox_north := center_lat + (radius_miles / 69.0); + + -- Try to load data from pg_lake + BEGIN + INSERT INTO overture.places (id, name, category_main, geom, source_data) + SELECT + data->>'id', + data->'names'->>'primary', + data->'categories'->'main'->0->>'name', + ST_SetSRID(ST_GeomFromGeoJSON(data->'geometry'::text), 4326), + data + FROM iceberg_scan( + 's3://overturemaps-us-west-2/release/2024-10-23.0/theme=places', + aws_region => 'us-west-2', + allow_moved_paths => true + ) as data + WHERE + (data->'geometry'->'coordinates'->0)::numeric BETWEEN bbox_west AND bbox_east + AND (data->'geometry'->'coordinates'->1)::numeric BETWEEN bbox_south AND bbox_north + ON CONFLICT (id) DO NOTHING; + + GET DIAGNOSTICS loaded_count = ROW_COUNT; + + RETURN format('Loaded %s places from Overture Maps via pg_lake', loaded_count); + EXCEPTION + WHEN OTHERS THEN + RETURN format('pg_lake load failed: %s. Using sample data instead.', SQLERRM); + END; +END; +$$ LANGUAGE plpgsql; + +-- ============================================ +-- ANALYSIS FUNCTIONS +-- ============================================ + +-- Function: Analyze a potential site location +CREATE OR REPLACE FUNCTION local.analyze_site( + lat NUMERIC, + lon NUMERIC, + radius_miles NUMERIC DEFAULT 1.0 +) +RETURNS TABLE( + metric VARCHAR, + value NUMERIC, + description TEXT +) AS $$ +DECLARE + site_point GEOMETRY; + radius_meters NUMERIC; +BEGIN + -- Create point geometry + site_point := ST_SetSRID(ST_MakePoint(lon, lat), 4326); + radius_meters := radius_miles * 1609.34; -- Convert miles to meters + + -- Distance to nearest existing store + RETURN QUERY + SELECT + 'nearest_store_miles'::VARCHAR, + ROUND((ST_Distance(site_point::geography, geom::geography) / 1609.34)::numeric, 2), + 'Distance to nearest company store'::TEXT + FROM local.stores + ORDER BY site_point <-> geom + LIMIT 1; + + -- Count existing stores within radius + RETURN QUERY + SELECT + 'stores_in_radius'::VARCHAR, + COUNT(*)::NUMERIC, + format('Company stores within %s miles', radius_miles)::TEXT + FROM local.stores + WHERE ST_DWithin(site_point::geography, geom::geography, radius_meters); + + -- Count competitors (Overture POIs) within radius + RETURN QUERY + SELECT + 'competitors_in_radius'::VARCHAR, + COUNT(*)::NUMERIC, + format('Competitor POIs within %s miles', radius_miles)::TEXT + FROM overture.places + WHERE ST_DWithin(site_point::geography, geom::geography, radius_meters) + AND category_main IN ('restaurant', 'retail', 'food_and_drink'); + + -- Building density + RETURN QUERY + SELECT + 'buildings_in_radius'::VARCHAR, + COUNT(*)::NUMERIC, + format('Buildings within %s miles', radius_miles)::TEXT + FROM overture.buildings + WHERE ST_DWithin(site_point::geography, geom::geography, radius_meters); + + -- Average building height (proxy for urban density) + RETURN QUERY + SELECT + 'avg_building_height_ft'::VARCHAR, + ROUND((AVG(height) * 3.28084)::numeric, 1), + 'Average building height (feet) in area'::TEXT + FROM overture.buildings + WHERE ST_DWithin(site_point::geography, geom::geography, radius_meters) + AND height IS NOT NULL; + +END; +$$ LANGUAGE plpgsql; + +-- Function: Get competitors near a point +CREATE OR REPLACE FUNCTION local.get_nearby_competitors( + lat NUMERIC, + lon NUMERIC, + radius_miles NUMERIC DEFAULT 1.0, + limit_count INTEGER DEFAULT 50 +) +RETURNS TABLE( + id VARCHAR, + name VARCHAR, + category VARCHAR, + distance_miles NUMERIC, + geom GEOMETRY +) AS $$ +DECLARE + site_point GEOMETRY; + radius_meters NUMERIC; +BEGIN + site_point := ST_SetSRID(ST_MakePoint(lon, lat), 4326); + radius_meters := radius_miles * 1609.34; + + RETURN QUERY + SELECT + p.id, + p.name, + p.category_main, + ROUND((ST_Distance(site_point::geography, p.geom::geography) / 1609.34)::numeric, 2) as distance_miles, + p.geom + FROM overture.places p + WHERE ST_DWithin(site_point::geography, p.geom::geography, radius_meters) + AND p.category_main IN ('restaurant', 'retail', 'food_and_drink', 'commercial') + ORDER BY site_point <-> p.geom + LIMIT limit_count; +END; +$$ LANGUAGE plpgsql; + +-- ============================================ +-- VIEWS FOR MAPPING +-- ============================================ + +-- View: All stores with service areas (for vector tiles) +CREATE OR REPLACE VIEW local.stores_display AS +SELECT + s.id, + s.name, + s.store_type, + s.annual_revenue, + s.employees, + s.city || ', ' || s.state as location, + s.geom +FROM local.stores s; + +-- Store locations view for mapping +COMMENT ON VIEW local.stores_display IS 'Company store locations for mapping'; + +-- View: Service area boundaries +CREATE OR REPLACE VIEW local.service_areas_display AS +SELECT + sa.id, + s.name as store_name, + sa.radius_miles, + sa.geom +FROM local.service_areas sa +JOIN local.stores s ON sa.store_id = s.id; + +COMMENT ON VIEW local.service_areas_display IS 'Store service area boundaries'; + + +-- Grant permissions +GRANT USAGE ON SCHEMA local TO PUBLIC; +GRANT USAGE ON SCHEMA overture TO PUBLIC; +GRANT SELECT ON ALL TABLES IN SCHEMA local TO PUBLIC; +GRANT SELECT ON ALL TABLES IN SCHEMA overture TO PUBLIC; +GRANT EXECUTE ON ALL FUNCTIONS IN SCHEMA local TO PUBLIC; + diff --git a/docs/examples/overture-maps-postgis-maplibre/database/seed-stores.sql b/docs/examples/overture-maps-postgis-maplibre/database/seed-stores.sql new file mode 100644 index 00000000..b1e4d195 --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/database/seed-stores.sql @@ -0,0 +1,130 @@ +-- Seed data for Site Selection Demo +-- Sample company stores across major US cities + +-- Insert sample stores (coffee shop chain example) +INSERT INTO local.stores (name, store_type, opening_date, annual_revenue, employees, geom, address, city, state) VALUES + -- San Francisco Bay Area + ('Downtown SF Store', 'flagship', '2018-03-15', 1250000.00, 25, ST_SetSRID(ST_MakePoint(-122.4194, 37.7749), 4326), '1 Market St', 'San Francisco', 'CA'), + ('Mission District', 'standard', '2019-06-20', 850000.00, 15, ST_SetSRID(ST_MakePoint(-122.4194, 37.7599), 4326), '3201 Mission St', 'San Francisco', 'CA'), + ('Berkeley Campus', 'standard', '2020-01-10', 680000.00, 12, ST_SetSRID(ST_MakePoint(-122.2727, 37.8716), 4326), '2600 Bancroft Way', 'Berkeley', 'CA'), + ('Palo Alto Store', 'standard', '2020-08-15', 720000.00, 14, ST_SetSRID(ST_MakePoint(-122.1430, 37.4419), 4326), '123 University Ave', 'Palo Alto', 'CA'), + ('Oakland Downtown', 'standard', '2021-03-22', 590000.00, 11, ST_SetSRID(ST_MakePoint(-122.2711, 37.8044), 4326), '456 Broadway', 'Oakland', 'CA'), + + -- Seattle + ('Seattle Pike Place', 'flagship', '2017-05-12', 1450000.00, 28, ST_SetSRID(ST_MakePoint(-122.3421, 47.6097), 4326), '1912 Pike Pl', 'Seattle', 'WA'), + ('Capitol Hill', 'standard', '2019-09-08', 780000.00, 16, ST_SetSRID(ST_MakePoint(-122.3210, 47.6205), 4326), '500 E Pine St', 'Seattle', 'WA'), + ('Fremont', 'standard', '2020-11-14', 650000.00, 13, ST_SetSRID(ST_MakePoint(-122.3493, 47.6505), 4326), '3400 Fremont Ave N', 'Seattle', 'WA'), + + -- Portland + ('Portland Downtown', 'flagship', '2018-07-20', 980000.00, 20, ST_SetSRID(ST_MakePoint(-122.6765, 45.5231), 4326), '701 SW 6th Ave', 'Portland', 'OR'), + ('Pearl District', 'standard', '2020-04-15', 720000.00, 14, ST_SetSRID(ST_MakePoint(-122.6819, 45.5266), 4326), '1201 NW Couch St', 'Portland', 'OR'), + + -- Los Angeles + ('LA Downtown', 'flagship', '2019-02-10', 1180000.00, 24, ST_SetSRID(ST_MakePoint(-118.2437, 34.0522), 4326), '444 S Flower St', 'Los Angeles', 'CA'), + ('Santa Monica', 'standard', '2019-08-25', 920000.00, 18, ST_SetSRID(ST_MakePoint(-118.4912, 34.0195), 4326), '1234 Promenade', 'Santa Monica', 'CA'), + ('Pasadena', 'standard', '2020-06-12', 670000.00, 13, ST_SetSRID(ST_MakePoint(-118.1445, 34.1478), 4326), '50 W Colorado Blvd', 'Pasadena', 'CA'), + + -- New York + ('Times Square', 'flagship', '2017-11-01', 1850000.00, 32, ST_SetSRID(ST_MakePoint(-73.9857, 40.7580), 4326), '1500 Broadway', 'New York', 'NY'), + ('Brooklyn Heights', 'standard', '2019-05-18', 890000.00, 17, ST_SetSRID(ST_MakePoint(-73.9936, 40.6955), 4326), '200 Montague St', 'Brooklyn', 'NY'), + ('Upper West Side', 'standard', '2020-03-07', 820000.00, 16, ST_SetSRID(ST_MakePoint(-73.9754, 40.7870), 4326), '2200 Broadway', 'New York', 'NY'), + + -- Boston + ('Boston Common', 'flagship', '2018-09-15', 1120000.00, 22, ST_SetSRID(ST_MakePoint(-71.0636, 42.3551), 4326), '1 Tremont St', 'Boston', 'MA'), + ('Cambridge MIT', 'standard', '2019-11-22', 750000.00, 15, ST_SetSRID(ST_MakePoint(-71.0942, 42.3601), 4326), '77 Massachusetts Ave', 'Cambridge', 'MA'), + + -- Chicago + ('Chicago Loop', 'flagship', '2018-04-20', 1280000.00, 26, ST_SetSRID(ST_MakePoint(-87.6298, 41.8781), 4326), '200 N State St', 'Chicago', 'IL'), + ('Wicker Park', 'standard', '2020-02-14', 710000.00, 14, ST_SetSRID(ST_MakePoint(-87.6771, 41.9090), 4326), '1425 N Milwaukee Ave', 'Chicago', 'IL'), + + -- Denver + ('Denver Downtown', 'flagship', '2019-07-08', 890000.00, 18, ST_SetSRID(ST_MakePoint(-104.9903, 39.7392), 4326), '1600 16th St', 'Denver', 'CO'), + ('RiNo District', 'standard', '2021-01-20', 580000.00, 12, ST_SetSRID(ST_MakePoint(-104.9823, 39.7643), 4326), '3600 Walnut St', 'Denver', 'CO'), + + -- Austin + ('Austin Downtown', 'flagship', '2019-03-30', 950000.00, 19, ST_SetSRID(ST_MakePoint(-97.7431, 30.2672), 4326), '600 Congress Ave', 'Austin', 'TX'), + ('South Congress', 'standard', '2020-09-10', 680000.00, 14, ST_SetSRID(ST_MakePoint(-97.7474, 30.2548), 4326), '1500 S Congress Ave', 'Austin', 'TX'); + +-- Create service areas (1-mile radius around each store) +INSERT INTO local.service_areas (store_id, radius_miles, geom) +SELECT + id, + 1.0, + ST_Buffer(geom::geography, 1609.34)::geometry -- 1 mile in meters +FROM local.stores; + +-- ============================================ +-- SAMPLE OVERTURE DATA +-- ============================================ +-- In production, this would come from pg_lake foreign tables +-- For demo, we'll insert some sample competitor POIs + +-- Sample competitors near San Francisco stores +INSERT INTO overture.places (id, name, category_main, category_sub, confidence, geom) VALUES + ('comp_sf_001', 'Starbucks - Market St', 'food_and_drink', 'coffee_shop', 0.95, ST_SetSRID(ST_MakePoint(-122.4184, 37.7750), 4326)), + ('comp_sf_002', 'Blue Bottle Coffee', 'food_and_drink', 'coffee_shop', 0.92, ST_SetSRID(ST_MakePoint(-122.4200, 37.7755), 4326)), + ('comp_sf_003', 'Peets Coffee', 'food_and_drink', 'coffee_shop', 0.90, ST_SetSRID(ST_MakePoint(-122.4180, 37.7745), 4326)), + ('comp_sf_004', 'Philz Coffee', 'food_and_drink', 'coffee_shop', 0.88, ST_SetSRID(ST_MakePoint(-122.4205, 37.7760), 4326)), + ('comp_sf_005', 'Starbucks - Mission', 'food_and_drink', 'coffee_shop', 0.95, ST_SetSRID(ST_MakePoint(-122.4200, 37.7605), 4326)), + ('comp_sf_006', 'Ritual Coffee', 'food_and_drink', 'coffee_shop', 0.87, ST_SetSRID(ST_MakePoint(-122.4190, 37.7595), 4326)), + + -- Seattle competitors + ('comp_sea_001', 'Starbucks Reserve', 'food_and_drink', 'coffee_shop', 0.98, ST_SetSRID(ST_MakePoint(-122.3420, 47.6105), 4326)), + ('comp_sea_002', 'Victrola Coffee', 'food_and_drink', 'coffee_shop', 0.89, ST_SetSRID(ST_MakePoint(-122.3215, 47.6210), 4326)), + ('comp_sea_003', 'Espresso Vivace', 'food_and_drink', 'coffee_shop', 0.86, ST_SetSRID(ST_MakePoint(-122.3205, 47.6200), 4326)), + + -- Portland competitors + ('comp_pdx_001', 'Stumptown Coffee', 'food_and_drink', 'coffee_shop', 0.92, ST_SetSRID(ST_MakePoint(-122.6770, 45.5235), 4326)), + ('comp_pdx_002', 'Coava Coffee', 'food_and_drink', 'coffee_shop', 0.88, ST_SetSRID(ST_MakePoint(-122.6822, 45.5270), 4326)), + + -- NYC competitors + ('comp_nyc_001', 'Starbucks - Times Sq', 'food_and_drink', 'coffee_shop', 0.96, ST_SetSRID(ST_MakePoint(-73.9860, 40.7585), 4326)), + ('comp_nyc_002', 'Bluestone Lane', 'food_and_drink', 'coffee_shop', 0.87, ST_SetSRID(ST_MakePoint(-73.9850, 40.7575), 4326)), + ('comp_nyc_003', 'Joe Coffee', 'food_and_drink', 'coffee_shop', 0.85, ST_SetSRID(ST_MakePoint(-73.9755, 40.7875), 4326)); + +-- Sample buildings (in production, these come from Overture via pg_lake) +-- Buildings need to be polygons, not points +INSERT INTO overture.buildings (id, height, num_floors, building_class, geom) VALUES + -- SF Financial District buildings (small square footprints) + ('bldg_sf_001', 235.0, 52, 'commercial', ST_Buffer(ST_SetSRID(ST_MakePoint(-122.4195, 37.7751), 4326)::geography, 20)::geometry), + ('bldg_sf_002', 180.0, 40, 'commercial', ST_Buffer(ST_SetSRID(ST_MakePoint(-122.4185, 37.7748), 4326)::geography, 20)::geometry), + ('bldg_sf_003', 25.0, 3, 'residential', ST_Buffer(ST_SetSRID(ST_MakePoint(-122.4200, 37.7752), 4326)::geography, 15)::geometry), + ('bldg_sf_004', 35.0, 4, 'mixed_use', ST_Buffer(ST_SetSRID(ST_MakePoint(-122.4190, 37.7746), 4326)::geography, 15)::geometry), + + -- Seattle downtown + ('bldg_sea_001', 290.0, 76, 'commercial', ST_Buffer(ST_SetSRID(ST_MakePoint(-122.3422, 47.6098), 4326)::geography, 25)::geometry), + ('bldg_sea_002', 45.0, 5, 'residential', ST_Buffer(ST_SetSRID(ST_MakePoint(-122.3211, 47.6206), 4326)::geography, 12)::geometry); + +-- Create some useful indexes +CREATE INDEX IF NOT EXISTS stores_city_idx ON local.stores(city); +CREATE INDEX IF NOT EXISTS stores_type_idx ON local.stores(store_type); +CREATE INDEX IF NOT EXISTS places_name_idx ON overture.places(name); + +-- Vacuum and analyze +VACUUM ANALYZE local.stores; +VACUUM ANALYZE local.service_areas; +VACUUM ANALYZE overture.places; +VACUUM ANALYZE overture.buildings; + +-- Summary output +DO $$ +DECLARE + store_count INTEGER; + place_count INTEGER; + building_count INTEGER; +BEGIN + SELECT COUNT(*) INTO store_count FROM local.stores; + SELECT COUNT(*) INTO place_count FROM overture.places; + SELECT COUNT(*) INTO building_count FROM overture.buildings; + + RAISE NOTICE '==============================================='; + RAISE NOTICE 'Site Selection Demo - Database Initialized'; + RAISE NOTICE '==============================================='; + RAISE NOTICE 'Company Stores: %', store_count; + RAISE NOTICE 'Competitor POIs: %', place_count; + RAISE NOTICE 'Buildings: %', building_count; + RAISE NOTICE '==============================================='; + RAISE NOTICE 'Run analysis: SELECT * FROM local.analyze_site(37.7749, -122.4194, 1.0);'; + RAISE NOTICE '==============================================='; +END $$; + diff --git a/docs/examples/overture-maps-postgis-maplibre/example-hybrid-query.sql b/docs/examples/overture-maps-postgis-maplibre/example-hybrid-query.sql new file mode 100644 index 00000000..ced0a094 --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/example-hybrid-query.sql @@ -0,0 +1,166 @@ +-- ============================================ +-- HYBRID QUERY EXAMPLE: Local + Remote Data +-- ============================================ +-- This query joins: +-- - LOCAL DATA: Company stores (in PostGIS) +-- - REMOTE DATA: Overture Maps coffee shops (via pg_lake from S3) + +-- Example 1: Find competitor coffee shops within 1 mile of each store +SELECT + -- Local store info + s.name AS store_name, + s.city, + s.state, + + -- Remote competitor info from Overture (via pg_lake) + (competitor.names).primary AS competitor_name, + competitor.basic_category, + + -- Distance calculation + ROUND( + (ST_Distance( + s.geom::geography, + ST_SetSRID(competitor.geometry, 4326)::geography + ) / 1609.34)::numeric, + 2 + ) AS distance_miles + +FROM stores s +CROSS JOIN LATERAL ( + -- Query ov_places (remote S3 data via pg_lake) + SELECT + ov.names, + ov.basic_category, + ov.geometry + FROM ov_places ov + WHERE + -- Spatial filter: within 1 mile of this store + ST_DWithin( + ST_SetSRID(ov.geometry, 4326)::geography, + s.geom::geography, + 1609.34 -- 1 mile in meters + ) + -- Only coffee shops + AND ov.basic_category = 'coffee_shop' + -- Only operating places + AND (ov.operating_status IS NULL OR ov.operating_status = 'open') + -- High confidence data + AND ov.confidence > 0.7 + ORDER BY ST_SetSRID(ov.geometry, 4326) <-> s.geom + LIMIT 5 -- Top 5 nearest competitors per store +) competitor + +ORDER BY s.name, distance_miles; + + +-- ============================================ +-- Example 2: Count competitors by store location +-- ============================================ +SELECT + s.name AS store_name, + s.city, + s.state, + + -- Count coffee shops from Overture within 1 mile + COUNT(ov.*) AS competitors_within_1_mile + +FROM stores s +LEFT JOIN LATERAL ( + SELECT 1 + FROM ov_places ov + WHERE + ST_DWithin( + ST_SetSRID(ov.geometry, 4326)::geography, + s.geom::geography, + 1609.34 + ) + AND ov.basic_category = 'coffee_shop' + AND (ov.operating_status IS NULL OR ov.operating_status = 'open') + AND ov.confidence > 0.7 +) ov ON true + +GROUP BY s.id, s.name, s.city, s.state +ORDER BY competitors_within_1_mile DESC; + + +-- ============================================ +-- Example 3: Market saturation analysis +-- ============================================ +-- Which stores have the most competition? + +WITH competition_analysis AS ( + SELECT + s.id, + s.name, + s.city, + s.annual_revenue, + + -- Count Overture coffee shops within different radii + (SELECT COUNT(*) + FROM ov_places ov + WHERE ST_DWithin( + ST_SetSRID(ov.geometry, 4326)::geography, + s.geom::geography, + 804.67 -- 0.5 mile + ) + AND ov.basic_category = 'coffee_shop' + AND ov.confidence > 0.7 + ) AS competitors_0_5_miles, + + (SELECT COUNT(*) + FROM ov_places ov + WHERE ST_DWithin( + ST_SetSRID(ov.geometry, 4326)::geography, + s.geom::geography, + 1609.34 -- 1 mile + ) + AND ov.basic_category = 'coffee_shop' + AND ov.confidence > 0.7 + ) AS competitors_1_mile + + FROM stores s +) +SELECT + name, + city, + annual_revenue, + competitors_0_5_miles, + competitors_1_mile, + + -- Calculate market saturation score + CASE + WHEN competitors_1_mile = 0 THEN 'Low Competition' + WHEN competitors_1_mile < 5 THEN 'Moderate Competition' + WHEN competitors_1_mile < 10 THEN 'High Competition' + ELSE 'Very High Competition' + END AS market_saturation + +FROM competition_analysis +ORDER BY competitors_1_mile DESC; + + +-- ============================================ +-- KEY CONCEPTS DEMONSTRATED: +-- ============================================ +-- +-- 1. HYBRID DATA: +-- - stores (local PostGIS table) +-- - ov_places (foreign table via pg_lake โ†’ S3 Parquet files) +-- +-- 2. SPATIAL JOINS: +-- - ST_DWithin() for radius queries +-- - ST_Distance() for exact distances +-- - CROSS JOIN LATERAL for correlated queries +-- +-- 3. REAL-TIME S3 QUERIES: +-- - Every query to ov_places hits S3 object storage +-- - pg_lake handles the Parquet โ†’ PostGIS conversion +-- - Filters pushed down for performance +-- +-- 4. NO DATA COPYING: +-- - Overture data stays in S3 +-- - Only query what you need +-- - Always fresh data +-- +-- ============================================ + diff --git a/docs/examples/overture-maps-postgis-maplibre/frontend/index.html b/docs/examples/overture-maps-postgis-maplibre/frontend/index.html new file mode 100644 index 00000000..ab54154c --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/frontend/index.html @@ -0,0 +1,94 @@ + + + + + + Site Selection Demo - PostGIS + pg_lake + Overture Maps + + + +
+ +
+
+

๐ŸŽฏ Site Selection Tool

+

PostGIS + pg_lake + Overture Maps + MapLibre

+
+
+
+ Company Stores + โ€” +
+
+ Overture POIs + โ€” +
+
+
+ + + + + +
+
+ +
+
+ + + + + diff --git a/docs/examples/overture-maps-postgis-maplibre/frontend/main.js b/docs/examples/overture-maps-postgis-maplibre/frontend/main.js new file mode 100644 index 00000000..c313832a --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/frontend/main.js @@ -0,0 +1,508 @@ +import maplibregl from 'maplibre-gl'; +import 'maplibre-gl/dist/maplibre-gl.css'; + +// Configuration +const API_URL = 'http://localhost:3001'; + +// State +let map; +let analyzeMode = false; +let candidateMarker = null; +let stores = []; +let competitors = []; + +// Initialize the application +async function init() { + initMap(); + await loadStats(); + await loadStores(); + await loadServiceAreas(); + setupEventListeners(); +} + +// Initialize MapLibre map +function initMap() { + map = new maplibregl.Map({ + container: 'map', + style: { + version: 8, + sources: { + 'osm': { + type: 'raster', + tiles: [ + 'https://a.tile.openstreetmap.org/{z}/{x}/{y}.png', + 'https://b.tile.openstreetmap.org/{z}/{x}/{y}.png', + 'https://c.tile.openstreetmap.org/{z}/{x}/{y}.png' + ], + tileSize: 256, + attribution: 'ยฉ OpenStreetMap contributors' + } + }, + layers: [ + { + id: 'osm', + type: 'raster', + source: 'osm', + minzoom: 0, + maxzoom: 19 + } + ] + }, + center: [-122.4194, 37.7749], // San Francisco + zoom: 10 + }); + + // Add navigation controls + map.addControl(new maplibregl.NavigationControl(), 'top-right'); + + // Add scale + map.addControl(new maplibregl.ScaleControl(), 'bottom-right'); + + map.on('load', () => { + console.log('Map loaded successfully'); + }); + + // Click handler for analysis mode + map.on('click', (e) => { + if (analyzeMode) { + analyzeSite(e.lngLat.lat, e.lngLat.lng); + } + }); +} + +// Load statistics +async function loadStats() { + try { + const response = await fetch(`${API_URL}/api/stats`); + const stats = await response.json(); + + document.getElementById('store-count').textContent = stats.stores; + document.getElementById('poi-count').textContent = stats.overture_places; + } catch (error) { + console.error('Error loading stats:', error); + showMapMessage('Failed to load statistics', 'error'); + } +} + +// Load company stores +async function loadStores() { + try { + const response = await fetch(`${API_URL}/api/stores`); + const data = await response.json(); + stores = data.features; + + // Add source and layer + map.addSource('stores', { + type: 'geojson', + data: data + }); + + // Add layer for store points + map.addLayer({ + id: 'stores-layer', + type: 'circle', + source: 'stores', + paint: { + 'circle-radius': [ + 'interpolate', ['linear'], ['zoom'], + 8, 4, + 12, 8, + 16, 12 + ], + 'circle-color': '#667eea', + 'circle-stroke-width': 2, + 'circle-stroke-color': '#ffffff', + 'circle-opacity': 0.9 + } + }); + + // Skip labels - base map doesn't support glyphs + // map.addLayer({ + // id: 'stores-labels', + // type: 'symbol', + // source: 'stores', + // layout: { + // 'text-field': ['get', 'name'], + // 'text-font': ['Open Sans Regular'], + // 'text-offset': [0, 1.5], + // 'text-anchor': 'top', + // 'text-size': 12 + // }, + // paint: { + // 'text-color': '#333', + // 'text-halo-color': '#fff', + // 'text-halo-width': 2 + // }, + // minzoom: 11 + // }); + + // Add click handler for popups + map.on('click', 'stores-layer', (e) => { + if (!analyzeMode) { + const properties = e.features[0].properties; + const coordinates = e.features[0].geometry.coordinates.slice(); + + new maplibregl.Popup() + .setLngLat(coordinates) + .setHTML(` +

${properties.name}

+

Type: ${properties.store_type}

+

Location: ${properties.city}, ${properties.state}

+

Employees: ${properties.employees}

+

Annual Revenue: $${(properties.annual_revenue / 1000000).toFixed(2)}M

+ `) + .addTo(map); + } + }); + + // Change cursor on hover + map.on('mouseenter', 'stores-layer', () => { + map.getCanvas().style.cursor = 'pointer'; + }); + + map.on('mouseleave', 'stores-layer', () => { + map.getCanvas().style.cursor = analyzeMode ? 'crosshair' : ''; + }); + + console.log(`Loaded ${stores.length} stores`); + } catch (error) { + console.error('Error loading stores:', error); + showMapMessage('Failed to load stores', 'error'); + } +} + +// Load service areas +async function loadServiceAreas() { + try { + const response = await fetch(`${API_URL}/api/service-areas`); + const data = await response.json(); + + map.addSource('service-areas', { + type: 'geojson', + data: data + }); + + map.addLayer({ + id: 'service-areas-layer', + type: 'fill', + source: 'service-areas', + paint: { + 'fill-color': '#667eea', + 'fill-opacity': 0.1 + } + }); + + map.addLayer({ + id: 'service-areas-outline', + type: 'line', + source: 'service-areas', + paint: { + 'line-color': '#667eea', + 'line-width': 2, + 'line-dasharray': [2, 2] + } + }); + + console.log('Loaded service areas'); + } catch (error) { + console.error('Error loading service areas:', error); + } +} + +// Analyze a potential site +async function analyzeSite(lat, lng) { + try { + // Show loading message + showMapMessage('Analyzing site...', 'info'); + + // Place candidate marker + if (candidateMarker) { + candidateMarker.remove(); + } + + const el = document.createElement('div'); + el.className = 'marker marker-candidate'; + candidateMarker = new maplibregl.Marker(el) + .setLngLat([lng, lat]) + .addTo(map); + + // Fetch analysis + const response = await fetch(`${API_URL}/api/analyze-site`, { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ latitude: lat, longitude: lng, radius: 1.0 }) + }); + + const data = await response.json(); + displayAnalysisResults(data); + + // Load nearby competitors (0.5 mile radius for faster queries) + await loadCompetitors(lat, lng, 0.5); + + // Hide message + hideMapMessage(); + + } catch (error) { + console.error('Error analyzing site:', error); + showMapMessage('Failed to analyze site', 'error'); + } +} + +// Display analysis results +function displayAnalysisResults(data) { + const resultsDiv = document.getElementById('analysis-results'); + const contentDiv = document.getElementById('analysis-content'); + + resultsDiv.style.display = 'block'; + + let html = ''; + for (const [key, metric] of Object.entries(data.analysis)) { + html += ` +
+
${metric.description}
+
${metric.value.toLocaleString()}
+
+ `; + } + + contentDiv.innerHTML = html; +} + +// Load competitors from Overture +async function loadCompetitors(lat, lng, radius) { + try { + console.log(`Loading competitors for lat=${lat}, lng=${lng}, radius=${radius}`); + showMapMessage('Loading competitors from Overture Maps via pg_lake...', 'info'); + + const startTime = Date.now(); + const response = await fetch( + `${API_URL}/api/competitors?lat=${lat}&lon=${lng}&radius=${radius}&limit=20` + ); + const loadTime = ((Date.now() - startTime) / 1000).toFixed(1); + const data = await response.json(); + console.log('Competitors API response:', data); + + if (data.error) { + console.error('Competitors API error:', data.error); + return; + } + + competitors = data.features; + console.log(`Received ${competitors.length} competitor features`); + + // Remove existing competitor layer if it exists + if (map.getLayer('competitors-layer')) { + console.log('Removing existing competitor layer'); + map.removeLayer('competitors-layer'); + map.removeSource('competitors'); + } + + // Add competitors to map + console.log('Adding competitors source and layer'); + map.addSource('competitors', { + type: 'geojson', + data: data + }); + + // Add layer WITHOUT specifying beforeId (put it on top) + map.addLayer({ + id: 'competitors-layer', + type: 'circle', + source: 'competitors', + layout: { + 'visibility': 'visible' + }, + paint: { + 'circle-radius': 10, + 'circle-color': '#ff6b6b', // Red for competitors + 'circle-stroke-width': 2, + 'circle-stroke-color': '#ffffff', // White outline + 'circle-opacity': 0.9 + } + }); // No beforeId - add on top of everything + + console.log('Competitor layer added successfully'); + console.log('Layer exists:', map.getLayer('competitors-layer') !== undefined); + console.log('Layer visibility:', map.getLayoutProperty('competitors-layer', 'visibility')); + console.log('Source features:', map.getSource('competitors')._data.features.length); + console.log('First feature:', map.getSource('competitors')._data.features[0]); + + // FORCE VISIBLE - ignore checkbox for now + if (map.getLayer('competitors-layer')) { + map.setLayoutProperty('competitors-layer', 'visibility', 'visible'); + console.log('FORCED competitors layer to VISIBLE'); + + // Force checkbox to match + const checkbox = document.getElementById('toggle-competitors'); + checkbox.checked = true; + } + + // Create a popup for hover + const competitorPopup = new maplibregl.Popup({ + closeButton: false, + closeOnClick: false, + offset: 15 + }); + + // Show popup on hover + map.on('mouseenter', 'competitors-layer', (e) => { + map.getCanvas().style.cursor = 'pointer'; + + const properties = e.features[0].properties; + const coordinates = e.features[0].geometry.coordinates.slice(); + + competitorPopup + .setLngLat(coordinates) + .setHTML(` +
+ ${properties.name || 'Unknown'}
+ ${properties.category || ''}
+ ${properties.distance_miles} miles away +
+ `) + .addTo(map); + }); + + // Hide popup on leave + map.on('mouseleave', 'competitors-layer', () => { + map.getCanvas().style.cursor = ''; + competitorPopup.remove(); + }); + + // Click for more details + map.on('click', 'competitors-layer', (e) => { + if (!analyzeMode) { + const properties = e.features[0].properties; + const coordinates = e.features[0].geometry.coordinates.slice(); + + new maplibregl.Popup() + .setLngLat(coordinates) + .setHTML(` +

${properties.name || 'Unknown Place'}

+

Category: ${properties.category}

+

Distance: ${properties.distance_miles} miles

+ `) + .addTo(map); + } + }); + + console.log(`Loaded ${competitors.length} competitors in ${loadTime}s`); + showMapMessage(`Loaded ${competitors.length} competitors in ${loadTime}s via pg_lake`, 'info'); + setTimeout(hideMapMessage, 3000); + } catch (error) { + console.error('Error loading competitors:', error); + } +} + +// Load Overture data via pg_lake +async function loadOvertureData() { + const btn = document.getElementById('load-overture-btn'); + const statusDiv = document.getElementById('load-status'); + + btn.disabled = true; + btn.textContent = 'Loading...'; + statusDiv.className = 'status-message info'; + statusDiv.textContent = 'Querying Overture Maps via pg_lake...'; + + try { + const center = map.getCenter(); + const response = await fetch(`${API_URL}/api/load-overture-data`, { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ + latitude: center.lat, + longitude: center.lng, + radius: 5.0 + }) + }); + + const data = await response.json(); + + if (data.success) { + statusDiv.className = 'status-message success'; + statusDiv.textContent = data.message; + + // Reload stats + await loadStats(); + } else { + throw new Error(data.error || 'Failed to load data'); + } + } catch (error) { + console.error('Error loading Overture data:', error); + statusDiv.className = 'status-message error'; + statusDiv.textContent = `Error: ${error.message}`; + } finally { + btn.disabled = false; + btn.textContent = 'Load Overture Data for Current View'; + } +} + +// Show map message +function showMapMessage(text, type = 'info') { + const messageDiv = document.getElementById('map-message'); + const textDiv = document.getElementById('map-message-text'); + textDiv.textContent = text; + messageDiv.style.display = 'block'; +} + +// Hide map message +function hideMapMessage() { + const messageDiv = document.getElementById('map-message'); + messageDiv.style.display = 'none'; +} + +// Setup event listeners +function setupEventListeners() { + // Analyze mode toggle + document.getElementById('analyze-mode-btn').addEventListener('click', () => { + analyzeMode = !analyzeMode; + const btn = document.getElementById('analyze-mode-btn'); + + if (analyzeMode) { + btn.classList.add('active'); + btn.textContent = 'โœ“ Analysis Mode Active'; + map.getCanvas().style.cursor = 'crosshair'; + showMapMessage('Click anywhere to analyze potential site location'); + } else { + btn.classList.remove('active'); + btn.textContent = '๐Ÿ“Œ Click Map to Analyze Site'; + map.getCanvas().style.cursor = ''; + hideMapMessage(); + } + }); + + // Layer toggles + document.getElementById('toggle-stores').addEventListener('change', (e) => { + const visibility = e.target.checked ? 'visible' : 'none'; + map.setLayoutProperty('stores-layer', 'visibility', visibility); + // Labels removed - no glyphs support + // map.setLayoutProperty('stores-labels', 'visibility', visibility); + }); + + document.getElementById('toggle-service-areas').addEventListener('change', (e) => { + const visibility = e.target.checked ? 'visible' : 'none'; + map.setLayoutProperty('service-areas-layer', 'visibility', visibility); + map.setLayoutProperty('service-areas-outline', 'visibility', visibility); + }); + + document.getElementById('toggle-competitors').addEventListener('change', (e) => { + const visibility = e.target.checked ? 'visible' : 'none'; + console.log('Toggle competitors checkbox:', e.target.checked, 'visibility:', visibility); + if (map.getLayer('competitors-layer')) { + map.setLayoutProperty('competitors-layer', 'visibility', visibility); + console.log('Set competitors-layer visibility to:', visibility); + } else { + console.log('competitors-layer does not exist yet'); + } + }); + + // Load Overture data button + document.getElementById('load-overture-btn').addEventListener('click', loadOvertureData); +} + +// Start the application +init().catch(error => { + console.error('Failed to initialize application:', error); + showMapMessage('Failed to initialize application', 'error'); +}); + diff --git a/docs/examples/overture-maps-postgis-maplibre/frontend/package-lock.json b/docs/examples/overture-maps-postgis-maplibre/frontend/package-lock.json new file mode 100644 index 00000000..a91c4fba --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/frontend/package-lock.json @@ -0,0 +1,1321 @@ +{ 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"isexe": "^3.1.1" + }, + "bin": { + "node-which": "bin/which.js" + }, + "engines": { + "node": "^16.13.0 || >=18.0.0" + } + } + } +} diff --git a/docs/examples/overture-maps-postgis-maplibre/frontend/package.json b/docs/examples/overture-maps-postgis-maplibre/frontend/package.json new file mode 100644 index 00000000..8cf9de79 --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/frontend/package.json @@ -0,0 +1,18 @@ +{ + "name": "site-selection-frontend", + "version": "1.0.0", + "description": "Frontend map interface for Site Selection Demo", + "type": "module", + "scripts": { + "dev": "vite", + "build": "vite build", + "preview": "vite preview" + }, + "dependencies": { + "maplibre-gl": "^4.1.0" + }, + "devDependencies": { + "vite": "^5.1.0" + } +} + diff --git a/docs/examples/overture-maps-postgis-maplibre/frontend/style.css b/docs/examples/overture-maps-postgis-maplibre/frontend/style.css new file mode 100644 index 00000000..18bc81bc --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/frontend/style.css @@ -0,0 +1,388 @@ +/* Reset and base styles */ +* { + margin: 0; + padding: 0; + box-sizing: border-box; +} + +body { + font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, sans-serif; + -webkit-font-smoothing: antialiased; + -moz-osx-font-smoothing: grayscale; +} + +/* Layout */ +#app { + display: grid; + grid-template-areas: + "header header" + "sidebar map"; + grid-template-rows: auto 1fr; + grid-template-columns: 360px 1fr; + height: 100vh; + overflow: hidden; +} + +/* Header */ +.header { + grid-area: header; + background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); + color: white; + padding: 1.5rem 2rem; + display: flex; + justify-content: space-between; + align-items: center; + box-shadow: 0 2px 8px rgba(0,0,0,0.1); +} + +.header-content h1 { + font-size: 1.75rem; + font-weight: 700; + margin-bottom: 0.25rem; +} + +.subtitle { + font-size: 0.875rem; + opacity: 0.9; +} + +.header-stats { + display: flex; + gap: 2rem; +} + +.stat { + display: flex; + flex-direction: column; + align-items: flex-end; +} + +.stat-label { + font-size: 0.75rem; + opacity: 0.8; + text-transform: uppercase; + letter-spacing: 0.5px; +} + +.stat-value { + font-size: 1.5rem; + font-weight: 700; +} + +/* Sidebar */ +.sidebar { + grid-area: sidebar; + background: #f8f9fa; + border-right: 1px solid #e0e0e0; + overflow-y: auto; + padding: 1.5rem; +} + +.sidebar-section { + margin-bottom: 2rem; + padding-bottom: 1.5rem; + border-bottom: 1px solid #e0e0e0; +} + +.sidebar-section:last-child { + border-bottom: none; +} + +.sidebar-section h2 { + font-size: 1rem; + font-weight: 600; + margin-bottom: 1rem; + color: #333; +} + +/* Layer toggles */ +.layer-toggle { + display: flex; + align-items: center; + padding: 0.75rem; + margin-bottom: 0.5rem; + background: white; + border-radius: 8px; + cursor: pointer; + transition: all 0.2s; + border: 1px solid #e0e0e0; +} + +.layer-toggle:hover { + border-color: #667eea; + box-shadow: 0 2px 8px rgba(102, 126, 234, 0.1); +} + +.layer-toggle input[type="checkbox"] { + margin-right: 0.75rem; + width: 18px; + height: 18px; + cursor: pointer; +} + +.layer-toggle span { + font-size: 0.95rem; + font-weight: 500; +} + +/* Buttons */ +.btn { + width: 100%; + padding: 0.875rem 1.25rem; + border: none; + border-radius: 8px; + font-size: 0.95rem; + font-weight: 600; + cursor: pointer; + transition: all 0.2s; + text-align: center; +} + +.btn-primary { + background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); + color: white; +} + +.btn-primary:hover { + transform: translateY(-2px); + box-shadow: 0 4px 12px rgba(102, 126, 234, 0.4); +} + +.btn-primary:active { + transform: translateY(0); +} + +.btn-primary.active { + background: #28a745; +} + +.btn-secondary { + background: #4CAF50; + color: white; +} + +.btn-secondary:hover { + background: #45a049; + transform: translateY(-2px); + box-shadow: 0 4px 12px rgba(76, 175, 80, 0.4); +} + +.btn-secondary:disabled { + background: #ccc; + cursor: not-allowed; + transform: none; +} + +/* Hints and messages */ +.hint { + font-size: 0.85rem; + color: #666; + margin-top: 0.75rem; + line-height: 1.4; +} + +.status-message { + margin-top: 0.75rem; + padding: 0.75rem; + border-radius: 6px; + font-size: 0.875rem; + display: none; +} + +.status-message.success { + display: block; + background: #d4edda; + color: #155724; + border: 1px solid #c3e6cb; +} + +.status-message.error { + display: block; + background: #f8d7da; + color: #721c24; + border: 1px solid #f5c6cb; +} + +.status-message.info { + display: block; + background: #d1ecf1; + color: #0c5460; + border: 1px solid #bee5eb; +} + +/* Analysis results */ +#analysis-content { + display: flex; + flex-direction: column; + gap: 0.75rem; +} + +.analysis-metric { + background: white; + padding: 1rem; + border-radius: 8px; + border-left: 4px solid #667eea; +} + +.analysis-metric-label { + font-size: 0.8rem; + color: #666; + text-transform: uppercase; + letter-spacing: 0.5px; + margin-bottom: 0.25rem; +} + +.analysis-metric-value { + font-size: 1.5rem; + font-weight: 700; + color: #333; +} + +.analysis-metric-desc { + font-size: 0.85rem; + color: #666; + margin-top: 0.25rem; +} + +/* About section */ +.about-text { + font-size: 0.875rem; + line-height: 1.6; + color: #555; +} + +.about-text ul { + margin-top: 0.75rem; + padding-left: 1.25rem; +} + +.about-text li { + margin-bottom: 0.5rem; +} + +.about-text strong { + color: #333; +} + +/* Map */ +.map-container { + grid-area: map; + position: relative; + background: #e5e3df; +} + +#map { + width: 100%; + height: 100%; +} + +.map-overlay { + position: absolute; + top: 20px; + left: 50%; + transform: translateX(-50%); + background: rgba(255, 255, 255, 0.95); + padding: 1rem 1.5rem; + border-radius: 8px; + box-shadow: 0 4px 12px rgba(0,0,0,0.15); + z-index: 10; + font-weight: 600; +} + +/* MapLibre GL JS styles */ +@import 'maplibre-gl/dist/maplibre-gl.css'; + +/* Custom popup styles */ +.maplibregl-popup-content { + padding: 1rem; + border-radius: 8px; + box-shadow: 0 4px 12px rgba(0,0,0,0.15); +} + +.maplibregl-popup-content h3 { + margin: 0 0 0.5rem 0; + font-size: 1rem; + color: #333; +} + +.maplibregl-popup-content p { + margin: 0.25rem 0; + font-size: 0.875rem; + color: #666; +} + +.popup-revenue { + color: #28a745; + font-weight: 600; +} + +/* Marker styles */ +.marker { + background-size: cover; + width: 30px; + height: 30px; + cursor: pointer; + transition: transform 0.2s; +} + +.marker:hover { + transform: scale(1.2); +} + +.marker-store { + background-color: #667eea; + border: 3px solid white; + border-radius: 50%; + box-shadow: 0 2px 8px rgba(0,0,0,0.3); +} + +.marker-competitor { + background-color: #ff6b6b; + border: 3px solid white; + border-radius: 50%; + box-shadow: 0 2px 8px rgba(0,0,0,0.3); +} + +.marker-candidate { + background-color: #feca57; + border: 3px solid white; + border-radius: 50%; + box-shadow: 0 4px 12px rgba(0,0,0,0.4); + animation: pulse 2s infinite; +} + +@keyframes pulse { + 0%, 100% { + transform: scale(1); + opacity: 1; + } + 50% { + transform: scale(1.1); + opacity: 0.8; + } +} + +/* Responsive design */ +@media (max-width: 1024px) { + #app { + grid-template-columns: 300px 1fr; + } +} + +@media (max-width: 768px) { + #app { + grid-template-areas: + "header" + "map"; + grid-template-columns: 1fr; + } + + .sidebar { + display: none; /* Could be toggled on mobile */ + } + + .header-stats { + display: none; + } +} + diff --git a/docs/examples/overture-maps-postgis-maplibre/frontend/vite.config.js b/docs/examples/overture-maps-postgis-maplibre/frontend/vite.config.js new file mode 100644 index 00000000..2aa30b97 --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/frontend/vite.config.js @@ -0,0 +1,13 @@ +import { defineConfig } from 'vite'; + +export default defineConfig({ + server: { + port: 5173, + open: true, + }, + build: { + outDir: 'dist', + sourcemap: true, + }, +}); + diff --git a/docs/examples/overture-maps-postgis-maplibre/setup-database.sh b/docs/examples/overture-maps-postgis-maplibre/setup-database.sh new file mode 100755 index 00000000..c3eed437 --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/setup-database.sh @@ -0,0 +1,98 @@ +#!/bin/bash + +# Setup script for Site Selection Demo database +# This script initializes the database schema and loads seed data + +set -e + +# Get database URL from environment variable +DB_URL="${DATABASE_URL}" + +if [ -z "$DB_URL" ]; then + echo "โŒ ERROR: DATABASE_URL environment variable is not set" + echo "" + echo "Please set DATABASE_URL to your PostgreSQL connection string:" + echo " export DATABASE_URL='postgresql://user:password@host:5432/database'" + echo "" + echo "Or copy .env.example to .env and configure it, then run:" + echo " source .env" + exit 1 +fi + +echo "==========================================" +echo "Site Selection Demo - Database Setup" +echo "==========================================" +echo "" + +# Check if psql is installed +if ! command -v psql &> /dev/null; then + echo "โŒ psql not found. Please install PostgreSQL client." + echo " macOS: brew install postgresql" + echo " Ubuntu: sudo apt-get install postgresql-client" + exit 1 +fi + +echo "โœ“ psql found" +echo "" + +# Test database connection +echo "Testing database connection..." +if psql "$DB_URL" -c "SELECT version();" > /dev/null 2>&1; then + echo "โœ“ Database connection successful" +else + echo "โŒ Cannot connect to database" + exit 1 +fi +echo "" + +# Check for pg_lake extension +echo "Checking for pg_lake extension..." +if psql "$DB_URL" -tAc "SELECT 1 FROM pg_extension WHERE extname = 'pg_lake';" | grep -q 1; then + echo "โœ“ pg_lake extension is installed" +else + echo "โš ๏ธ pg_lake extension not found" + echo " The database might not have pg_lake installed yet." + echo " Some features may not work until pg_lake is available." +fi +echo "" + +# Run initialization script +echo "Running database initialization..." +psql "$DB_URL" -f database/init.sql +if [ $? -eq 0 ]; then + echo "โœ“ Database schema created" +else + echo "โŒ Failed to create database schema" + exit 1 +fi +echo "" + +# Load seed data +echo "Loading seed data..." +psql "$DB_URL" -f database/seed-stores.sql +if [ $? -eq 0 ]; then + echo "โœ“ Seed data loaded" +else + echo "โŒ Failed to load seed data" + exit 1 +fi +echo "" + +# Summary +echo "==========================================" +echo "โœ… Database setup complete!" +echo "==========================================" +echo "" +echo "Quick test queries:" +echo "" +echo "1. List all stores:" +echo " psql \"$DB_URL\" -c \"SELECT name, city, state FROM local.stores;\"" +echo "" +echo "2. Run site analysis (San Francisco):" +echo " psql \"$DB_URL\" -c \"SELECT * FROM local.analyze_site(37.7749, -122.4194, 1.0);\"" +echo "" +echo "3. Find nearby competitors:" +echo " psql \"$DB_URL\" -c \"SELECT name, category, distance_miles FROM local.get_nearby_competitors(37.7749, -122.4194, 1.0);\"" +echo "" +echo "==========================================" + diff --git a/docs/examples/overture-maps-postgis-maplibre/start-demo.sh b/docs/examples/overture-maps-postgis-maplibre/start-demo.sh new file mode 100755 index 00000000..48efb47b --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/start-demo.sh @@ -0,0 +1,115 @@ +#!/bin/bash + +# Quick start script for Site Selection Demo + +set -e + +echo "==========================================" +echo "๐ŸŽฏ Site Selection Demo - Quick Start" +echo "==========================================" +echo "" + +# Check prerequisites +echo "Checking prerequisites..." + +if ! command -v node &> /dev/null; then + echo "โŒ Node.js not found. Please install Node.js 18+" + exit 1 +fi +echo "โœ“ Node.js found: $(node --version)" + +if ! command -v npm &> /dev/null; then + echo "โŒ npm not found" + exit 1 +fi +echo "โœ“ npm found: $(npm --version)" + +if ! command -v psql &> /dev/null; then + echo "โš ๏ธ psql not found. Database setup will be skipped." + echo " Install PostgreSQL client: brew install postgresql" + SKIP_DB=true +else + echo "โœ“ psql found" + SKIP_DB=false +fi + +echo "" + +# Database setup +if [ "$SKIP_DB" = false ]; then + echo "==========================================" + echo "๐Ÿ“Š Setting up database..." + echo "==========================================" + + if [ ! -f ".db-initialized" ]; then + ./setup-database.sh + touch .db-initialized + echo "โœ“ Database initialized" + else + echo "โœ“ Database already initialized (delete .db-initialized to reinit)" + fi + echo "" +fi + +# Install and start backend +echo "==========================================" +echo "๐Ÿ”ง Starting backend API..." +echo "==========================================" +cd backend +if [ ! -d "node_modules" ]; then + echo "Installing backend dependencies..." + npm install +fi +echo "โœ“ Backend ready" + +# Start backend in background +echo "Starting backend server..." +npm start > ../backend.log 2>&1 & +BACKEND_PID=$! +echo $BACKEND_PID > ../backend.pid +echo "โœ“ Backend running on http://localhost:3001 (PID: $BACKEND_PID)" +cd .. +echo "" + +# Install and start frontend +echo "==========================================" +echo "๐ŸŽจ Starting frontend..." +echo "==========================================" +cd frontend +if [ ! -d "node_modules" ]; then + echo "Installing frontend dependencies..." + npm install +fi +echo "โœ“ Frontend ready" +cd .. +echo "" + +# Wait for backend to be ready +echo "Waiting for backend to be ready..." +for i in {1..30}; do + if curl -s http://localhost:3001/health > /dev/null 2>&1; then + echo "โœ“ Backend is healthy" + break + fi + if [ $i -eq 30 ]; then + echo "โš ๏ธ Backend health check timeout" + fi + sleep 1 +done + +echo "" +echo "==========================================" +echo "โœ… Demo is ready!" +echo "==========================================" +echo "" +echo "๐Ÿ“ Frontend: http://localhost:5173" +echo "๐Ÿ”ง Backend API: http://localhost:3001" +echo "" +echo "To start the frontend (in a new terminal):" +echo " cd frontend && npm run dev" +echo "" +echo "To stop everything:" +echo " ./stop-demo.sh" +echo "" +echo "==========================================" + diff --git a/docs/examples/overture-maps-postgis-maplibre/stop-demo.sh b/docs/examples/overture-maps-postgis-maplibre/stop-demo.sh new file mode 100755 index 00000000..7d7be915 --- /dev/null +++ b/docs/examples/overture-maps-postgis-maplibre/stop-demo.sh @@ -0,0 +1,30 @@ +#!/bin/bash + +# Stop script for Site Selection Demo + +echo "==========================================" +echo "๐Ÿ›‘ Stopping Site Selection Demo" +echo "==========================================" +echo "" + +# Stop backend +if [ -f "backend.pid" ]; then + BACKEND_PID=$(cat backend.pid) + if ps -p $BACKEND_PID > /dev/null 2>&1; then + echo "Stopping backend (PID: $BACKEND_PID)..." + kill $BACKEND_PID + rm backend.pid + echo "โœ“ Backend stopped" + else + echo "Backend process not running" + rm backend.pid + fi +else + echo "No backend PID file found" +fi + +echo "" +echo "==========================================" +echo "โœ… Demo stopped" +echo "==========================================" +