# Quick Start Guide - Automotive Vehicle Database

## Database Status: ✅ OPERATIONAL

- **30,066** engines
- **1,213,401** vehicle configurations
- **93** years (1918-2026)
- **53** makes
- **1,937** models

---

## Access the Database

```bash
docker exec -it mvp-postgres psql -U postgres -d motovaultpro
```

---

## Essential Queries

### 1. Get All Available Years
```sql
SELECT * FROM available_years;
```

### 2. Get Makes for a Specific Year
```sql
SELECT * FROM get_makes_for_year(2024);
```

### 3. Get Models for Year + Make
```sql
SELECT * FROM get_models_for_year_make(2024, 'Ford');
```

### 4. Get Trims for Year + Make + Model
```sql
SELECT * FROM get_trims_for_year_make_model(2024, 'Ford', 'f-150');
```

### 5. Get Complete Vehicle Details
```sql
SELECT * FROM complete_vehicle_configs
WHERE year = 2024
  AND make = 'Ford'
  AND model = 'f-150'
LIMIT 10;
```

---

## Refresh the Database

```bash
# Re-generate SQL files from JSON source data
python3 etl_generate_sql.py

# Re-import into database
./import_data.sh
```

---

## Files Overview

| File | Purpose |
|------|---------|
| `etl_generate_sql.py` | Generate SQL import files from JSON |
| `import_data.sh` | Import SQL files into database |
| `migrations/001_create_vehicle_database.sql` | Database schema |
| `output/*.sql` | Generated SQL import files (90MB total) |

---

## Database Schema

```
engines
├── id (PK)
├── name
├── displacement
├── configuration (I4, V6, V8, etc.)
├── horsepower
├── torque
├── fuel_type
└── specs_json (full specifications)

vehicle_options
├── id (PK)
├── year
├── make
├── model
├── trim
├── engine_id (FK → engines)
└── transmission_id (FK → transmissions)
```

---

## Performance

- **Query Time:** < 50ms (indexed)
- **Database Size:** 219MB
- **Index Size:** 117MB

---

## Support

- **Full Documentation:** See `ETL_README.md`
- **Implementation Details:** See `IMPLEMENTATION_SUMMARY.md`