# Database Schema Documentation

## Overview

This document provides a comprehensive overview of the Mila Membership Management System database schema.

## Quick Links

- **DBML File:** [`database_schema.dbml`](./database_schema.dbml)
- **Visualize Online:** 
  - [dbdiagram.io](https://dbdiagram.io) - Upload the DBML file
  - [dbdocs.io](https://dbdocs.io) - Generate interactive documentation

## Schema Statistics

| Metric | Count |
|--------|-------|
| **Tables** | 11 |
| **Domains** | 4 (Accounts, Membership, MembershipFees, Authorization) |
| **Relationships** | 9 |
| **Indexes** | 25+ |
| **Triggers** | 1 (Full-text search) |

## Tables Overview

### Accounts Domain

#### `users`
- **Purpose:** User authentication and session management
- **Rows (Estimated):** Low to Medium (typically 10-50% of members)
- **Key Features:** 
  - Dual authentication (Password + OIDC)
  - Optional 1:1 link to members
  - Email as source of truth when linked

#### `tokens`
- **Purpose:** JWT token storage for AshAuthentication
- **Rows (Estimated):** Medium to High (multiple tokens per user)
- **Key Features:**
  - Token lifecycle management
  - Revocation support
  - Multiple token purposes

### Membership Domain

#### `members`
- **Purpose:** Club member master data
- **Rows (Estimated):** High (core entity)
- **Key Features:**
  - Complete member profile
  - Full-text search via tsvector
  - Bidirectional email sync with users
  - Flexible address and contact data

#### `custom_field_values`
- **Purpose:** Dynamic custom member attributes
- **Rows (Estimated):** Variable (N per member)
- **Key Features:**
  - Union type value storage (JSONB)
  - Multiple data types supported
  - One custom field value per custom field per member

#### `custom_fields`
- **Purpose:** Schema definitions for custom_field_values
- **Rows (Estimated):** Low (admin-defined)
- **Key Features:**
  - Type definitions
  - Immutable and required flags
  - Centralized custom field management

#### `settings`
- **Purpose:** Global application settings (singleton resource)
- **Rows (Estimated):** 1 (singleton pattern)
- **Key Features:**
  - Club name configuration
  - Member field visibility settings
  - Membership fee default settings
  - Environment variable support for club name

#### `groups`
- **Purpose:** Group definitions for organizing members
- **Rows (Estimated):** Low (typically 5-20 groups per club)
- **Key Features:**
  - Unique group names (case-insensitive)
  - URL-friendly slugs (auto-generated, immutable)
  - Optional descriptions
  - Many-to-many relationship with members

#### `member_groups`
- **Purpose:** Join table for many-to-many relationship between members and groups
- **Rows (Estimated):** Medium to High (multiple groups per member)
- **Key Features:**
  - Unique constraint on (member_id, group_id)
  - CASCADE delete on both sides
  - Efficient indexes for queries

### Authorization Domain

#### `roles`
- **Purpose:** Role-based access control (RBAC)
- **Rows (Estimated):** Low (typically 3-10 roles)
- **Key Features:**
  - Links users to permission sets
  - System role protection
  - Four hardcoded permission sets: own_data, read_only, normal_user, admin

## Key Relationships

```
User (0..1) ←→ (0..1) Member
       ↓              ↓
    Tokens (N)    CustomFieldValues (N)
       ↓                    ↓
    Role (N:1)        CustomField (1)

Member (1) → (N) MembershipFeeCycles
                    ↓
            MembershipFeeType (1)

Member (N) ←→ (N) Group
       ↓              ↓
  MemberGroups (N)  MemberGroups (N)

Settings (1) → MembershipFeeType (0..1)
```

### Relationship Details

1. **User ↔ Member (Optional 1:1, both sides optional)**
   - A User can have 0 or 1 Member (`user.member_id` can be NULL)
   - A Member can have 0 or 1 User (optional `has_one` relationship)
   - Both entities can exist independently
   - Email synchronization when linked (User.email is source of truth)
   - `ON DELETE SET NULL` on user side (User preserved when Member deleted)

2. **User → Role (N:1)**
   - Many users can be assigned to one role
   - `ON DELETE RESTRICT` - cannot delete role if users are assigned
   - Role links user to permission set for authorization

3. **Member → CustomFieldValues (1:N)**
   - One member, many custom_field_values
   - `ON DELETE CASCADE` - custom_field_values deleted with member
   - Composite unique constraint (member_id, custom_field_id)

4. **CustomFieldValue → CustomField (N:1)**
   - Custom field values reference type definition
   - `ON DELETE RESTRICT` - cannot delete type if in use
   - Type defines data structure

5. **Member → MembershipFeeType (N:1, optional)**
   - Many members can be assigned to one fee type
   - `ON DELETE RESTRICT` - cannot delete fee type if members are assigned
   - Optional relationship (member can have no fee type)

6. **Member → MembershipFeeCycles (1:N)**
   - One member, many billing cycles
   - `ON DELETE CASCADE` - cycles deleted when member deleted
   - Unique constraint (member_id, cycle_start)

7. **MembershipFeeCycle → MembershipFeeType (N:1)**
   - Many cycles reference one fee type
   - `ON DELETE RESTRICT` - cannot delete fee type if cycles exist

8. **Settings → MembershipFeeType (N:1, optional)**
   - Settings can reference a default fee type
   - `ON DELETE SET NULL` - if fee type is deleted, setting is cleared

9. **Member ↔ Group (N:N via MemberGroup)**
   - Many-to-many relationship through `member_groups` join table
   - `ON DELETE CASCADE` on both sides - removing member/group removes associations
   - Unique constraint on (member_id, group_id) prevents duplicates
   - Groups searchable via member search vector

## Important Business Rules

### Email Synchronization
- **User.email** is the source of truth when linked
- On linking: Member.email ← User.email (overwrite)
- After linking: Changes sync bidirectionally
- Validation prevents email conflicts

### Authentication Strategies
- **Password:** Email + hashed_password
- **OIDC:** Email + oidc_id (Rauthy provider)
- At least one method required per user

### Member Constraints
- First name and last name required (min 1 char)
- Email unique, validated format (5-254 chars)
- Join date cannot be in future
- Exit date must be after join date
- Phone: `+?[0-9\- ]{6,20}`
- Postal code: 5 digits

### CustomFieldValue System
- Maximum one custom field value per custom field per member
- Value stored as union type in JSONB
- Supported types: string, integer, boolean, date, email
- Types can be marked as immutable or required

## Indexes

### Performance Indexes

**members:**
- `search_vector` (GIN) - Full-text search (tsvector)
- `first_name` (GIN trgm) - Fuzzy search on first name
- `last_name` (GIN trgm) - Fuzzy search on last name
- `email` (GIN trgm) - Fuzzy search on email
- `city` (GIN trgm) - Fuzzy search on city
- `street` (GIN trgm) - Fuzzy search on street
- `notes` (GIN trgm) - Fuzzy search on notes
- `email` (B-tree) - Exact email lookups
- `last_name` (B-tree) - Name sorting
- `join_date` (B-tree) - Date filtering

**custom_field_values:**
- `member_id` - Member custom field value lookups
- `custom_field_id` - Type-based queries
- Composite `(member_id, custom_field_id)` - Uniqueness

**tokens:**
- `subject` - User token lookups
- `expires_at` - Token cleanup
- `purpose` - Purpose-based queries

**users:**
- `email` (unique) - Login lookups
- `oidc_id` (unique) - OIDC authentication
- `member_id` (unique) - Member linkage

## Full-Text Search

### Implementation
- **Trigger:** `members_search_vector_trigger()`
- **Function:** Automatically updates `search_vector` on INSERT/UPDATE
- **Index Type:** GIN (Generalized Inverted Index)

### Weighted Fields
- **Weight A (highest):** first_name, last_name
- **Weight B:** email, notes
- **Weight C:** city, street, house_number, postal_code, custom_field_values
- **Weight D (lowest):** join_date, exit_date

### Custom Field Values in Search
Custom field values are automatically included in the search vector:
- All custom field values (string, integer, boolean, date, email) are aggregated and added to the search vector
- Values are converted to text format for indexing
- Custom field values receive weight 'C' (same as city, etc.)
- The search vector is automatically updated when custom field values are created, updated, or deleted via database triggers

### Usage Example
```sql
SELECT * FROM members 
WHERE search_vector @@ to_tsquery('simple', 'john & doe');
```

## Fuzzy Search (Trigram-based)

### Implementation
- **Extension:** `pg_trgm` (PostgreSQL Trigram)
- **Index Type:** GIN with `gin_trgm_ops` operator class
- **Similarity Threshold:** 0.2 (default, configurable)
- **Added:** November 2025 (PR #187, closes #162)

### How It Works
Fuzzy search combines multiple search strategies:
1. **Full-text search** - Primary filter using tsvector
2. **Trigram similarity** - `similarity(field, query) > threshold`
3. **Word similarity** - `word_similarity(query, field) > threshold`
4. **Substring matching** - `LIKE` and `ILIKE` for exact substrings
5. **Modulo operator** - `query % field` for quick similarity check

### Indexed Fields for Fuzzy Search
- `first_name` - GIN trigram index
- `last_name` - GIN trigram index
- `email` - GIN trigram index
- `city` - GIN trigram index
- `street` - GIN trigram index
- `notes` - GIN trigram index

### Usage Example (Ash Action)
```elixir
# In LiveView or context
Member.fuzzy_search(Member, query: "john", similarity_threshold: 0.2)

# Or using Ash Query directly
Member
|> Ash.Query.for_read(:search, %{query: "john", similarity_threshold: 0.2})
|> Mv.Membership.read!()
```

### Usage Example (SQL)
```sql
-- Trigram similarity search
SELECT * FROM members 
WHERE similarity(first_name, 'john') > 0.2
   OR similarity(last_name, 'doe') > 0.2
ORDER BY similarity(first_name, 'john') DESC;

-- Word similarity (better for partial matches)
SELECT * FROM members 
WHERE word_similarity('john', first_name) > 0.2;

-- Quick similarity check with % operator
SELECT * FROM members 
WHERE 'john' % first_name;
```

### Performance Considerations
- **GIN indexes** speed up trigram operations significantly
- **Similarity threshold** of 0.2 balances precision and recall
- **Combined approach** (FTS + trigram) provides best results
- Lower threshold = more results but less specific

## Database Extensions

### Required PostgreSQL Extensions

1. **uuid-ossp**
   - Purpose: UUID generation functions
   - Used for: `gen_random_uuid()`, `uuid_generate_v7()`

2. **citext**
   - Purpose: Case-insensitive text type
   - Used for: `users.email` (case-insensitive email matching)

3. **pg_trgm**
   - Purpose: Trigram-based fuzzy text search and similarity matching
   - Used for: Fuzzy member search with similarity scoring
   - Operators: `%` (similarity), `word_similarity()`, `similarity()`
   - Added in: Migration `20251001141005_add_trigram_to_members.exs`

### Installation
```sql
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";
CREATE EXTENSION IF NOT EXISTS "citext";
CREATE EXTENSION IF NOT EXISTS "pg_trgm";
```

## Migration Strategy

### Ash Migrations
This project uses Ash Framework's migration system:

```bash
# Generate new migration
mix ash.codegen --name add_new_feature

# Apply migrations
mix ash.setup

# Rollback migrations
mix ash_postgres.rollback -n 1
```

### Migration Files Location
```
priv/repo/migrations/
├── 20250421101957_initialize_extensions_1.exs
├── 20250528163901_initial_migration.exs
├── 20250617090641_member_fields.exs
├── 20250620110850_add_accounts_domain.exs
├── 20250912085235_AddSearchVectorToMembers.exs
├── 20250926180341_add_unique_email_to_members.exs
├── 20251001141005_add_trigram_to_members.exs
└── 20251016130855_add_constraints_for_user_member_and_property.exs
```

## Data Integrity

### Foreign Key Behaviors

| Relationship | On Delete | Rationale |
|--------------|-----------|-----------|
| `users.member_id → members.id` | SET NULL | Preserve user account when member deleted |
| `custom_field_values.member_id → members.id` | CASCADE | Delete custom_field_values with member |
| `custom_field_values.custom_field_id → custom_fields.id` | RESTRICT | Prevent deletion of types in use |

### Validation Layers

1. **Database Level:**
   - CHECK constraints
   - NOT NULL constraints
   - UNIQUE indexes
   - Foreign key constraints

2. **Application Level (Ash):**
   - Custom validators
   - Email format validation (EctoCommons.EmailValidator)
   - Business rule validation
   - Cross-entity validation

3. **UI Level:**
   - Client-side form validation
   - Real-time feedback
   - Error messages

## Performance Considerations

### Query Patterns

**High Frequency:**
- Member search (uses GIN index on search_vector)
- Member list with filters (uses indexes on join_date, membership_fee_type_id)
- User authentication (uses unique index on email/oidc_id)
- CustomFieldValue lookups by member (uses index on member_id)

**Medium Frequency:**
- Member CRUD operations
- CustomFieldValue updates
- Token validation

**Low Frequency:**
- CustomField management
- User-Member linking
- Bulk operations

### Optimization Tips

1. **Use indexes:** All critical query paths have indexes
2. **Preload relationships:** Use Ash's `load` to avoid N+1
3. **Pagination:** Use keyset pagination (configured by default)
4. **GIN indexes:** Full-text search and fuzzy search on multiple fields
5. **Search optimization:** Full-text search via tsvector, not LIKE

## Visualization

### Using dbdiagram.io

1. Visit [https://dbdiagram.io](https://dbdiagram.io)
2. Click "Import" → "From file"
3. Upload `database_schema.dbml`
4. View interactive diagram with relationships

### Using dbdocs.io

1. Install dbdocs CLI: `npm install -g dbdocs`
2. Generate docs: `dbdocs build database_schema.dbml`
3. View generated documentation

### VS Code Extension

Install "DBML Language" extension to view/edit DBML files with:
- Syntax highlighting
- Inline documentation
- Error checking

## Security Considerations

### Sensitive Data

**Encrypted:**
- `users.hashed_password` (bcrypt)

**Should Not Log:**
- hashed_password
- tokens (jti, purpose, extra_data)

**Personal Data (GDPR):**
- All member fields (name, email, address)
- User email
- Token subject

### Access Control

- Implement through Ash policies
- Row-level security considerations for future
- Audit logging for sensitive operations

## Backup Recommendations

### Critical Tables (Priority 1)
- `members` - Core business data
- `users` - Authentication data
- `custom_fields` - Schema definitions

### Important Tables (Priority 2)
- `custom_field_values` - Member custom data
- `tokens` - Can be regenerated but good to backup

### Backup Strategy
```bash
# Full database backup
pg_dump -Fc mv_prod > backup_$(date +%Y%m%d).dump

# Restore
pg_restore -d mv_prod backup_20251110.dump
```

## Testing

### Test Database
- Separate test database: `mv_test`
- Sandbox mode via Ecto.Adapters.SQL.Sandbox
- Reset between tests

### Seed Data
```bash
# Load seed data
mix run priv/repo/seeds.exs
```

## Future Considerations

### Potential Additions

1. **Audit Log Table**
   - Track changes to members
   - Compliance and history tracking

2. **Payment Tracking**
   - Payment history table
   - Transaction records
   - Fee calculation

3. **Document Storage**
   - Member documents/attachments
   - File metadata table

4. **Email Queue**
   - Outbound email tracking
   - Delivery status

5. **Roles & Permissions**
   - User roles (admin, treasurer, member)
   - Permission management

## Resources

- **Ash Framework:** [https://hexdocs.pm/ash](https://hexdocs.pm/ash)
- **AshPostgres:** [https://hexdocs.pm/ash_postgres](https://hexdocs.pm/ash_postgres)
- **DBML Specification:** [https://dbml.dbdiagram.io](https://dbml.dbdiagram.io)
- **PostgreSQL Docs:** [https://www.postgresql.org/docs/](https://www.postgresql.org/docs/)

---

**Last Updated:** 2026-01-27  
**Schema Version:** 1.5  
**Database:** PostgreSQL 17.6 (dev) / 16 (prod)

