GeoDash/examples/geodash_postgres.yml at main · cryptekbits/GeoDash · GitHub

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# GeoDash PostgreSQL Configuration
#
# This configuration file demonstrates how to set up GeoDash with PostgreSQL and PostGIS
# for advanced spatial query capabilities in production environments.

# Set to advanced mode to enable all features
mode: "advanced"

# Enable all features for PostgreSQL optimized setup
features:
  enable_fuzzy_search: true
  enable_location_aware: true
  enable_memory_caching: true
  enable_shared_memory: true
  enable_advanced_db: true
  # Disable auto fetch in production environments
  auto_fetch_data: false

# Data configuration
data:
  # Specify a custom data location for production deployments
  location: "/var/lib/geodash/data/cities.csv"
  # Optionally limit to specific countries for specialized applications
  # countries: "US,CA,MX,GB,FR,DE,ES,IT"
  countries: "ALL"
  download_url: "https://raw.githubusercontent.com/dr5hn/countries-states-cities-database/refs/heads/master/csv/cities.csv"
  # Larger batch size for faster imports on powerful database servers
  batch_size: 10000

# Database configuration
database:
  # Set type to PostgreSQL
  type: postgresql

  # PostgreSQL connection settings
  postgresql:
    host: "localhost"
    port: 5432
    database: "geodash"
    user: "geodash_user"
    password: "your_secure_password"  # Use environment variables in production
    # Enable PostGIS for spatial operations
    postgis: true

  # Optimize connection pooling for PostgreSQL
  pool:
    enabled: true
    # Adjust pool size based on your server capacity
    min_size: 5
    max_size: 20
    timeout: 30

# Search configuration optimized for PostgreSQL
search:
  # Fuzzy search with PostgreSQL's text search capabilities
  fuzzy:
    threshold: 75  # Slightly higher threshold for better precision
    enabled: true

  # PostGIS-based location-aware searching
  location_aware:
    enabled: true
    distance_weight: 0.4  # Increase weight for distance-based sorting
    country_boost: 25000

  # Larger cache size for production environments
  cache:
    enabled: true
    size: 10000
    ttl: 7200  # Longer TTL for more stable data

  # Generous limits for API use
  limits:
    default: 15
    max: 200

# Production logging configuration
logging:
  level: warning  # Use warning level in production to reduce log volume
  format: json  # JSON format for better log processing
  file: "/var/log/geodash/geodash.log"  # Log to file in production

# API configuration for production
api:
  host: "0.0.0.0"
  port: 8080
  debug: false
  # Adjust worker count based on available CPU cores
  workers: 8

  # CORS configuration for production
  cors:
    enabled: true
    # Restrict origins in production
    origins: ["https://your-domain.com", "https://api.your-domain.com"]
    methods: ["GET"]

  # Enable rate limiting in production
  rate_limit:
    enabled: true
    limit: 200
    window: 60

# PostgreSQL Performance Tuning Notes
#
# For optimal performance with GeoDash and PostgreSQL:
#
# 1. Create appropriate indexes:
#    - PostgreSQL will create btree indexes automatically
#    - PostGIS will handle spatial indexing
#
# 2. Configure PostgreSQL for your hardware:
#    - shared_buffers: 25% of available RAM
#    - effective_cache_size: 75% of available RAM
#    - work_mem: 32-64MB for complex queries
#    - maintenance_work_mem: 256MB for faster database maintenance
#
# 3. Ensure PostGIS is properly installed:
#    CREATE EXTENSION postgis;
#
# 4. Consider partitioning for very large datasets:
#    - Partition by country or continent for better query performance