# PostgreSQL Migration Testing Methodology

## Overview
This document outlines the systematic approach for testing and refining the SQLite to PostgreSQL migration process before production deployment.

## 🔄 Iterative Testing Cycle

### Phase 1: Discovery Testing
**Goal**: Identify all migration issues without fixing them

```bash
# Run discovery cycle
./test_migration_workflow.sh > migration_test_$(date +%Y%m%d_%H%M%S).log 2>&1
```

**Process**:
1. Reset PostgreSQL database
2. Run migration attempt
3. **Document ALL errors** (don't fix immediately)
4. Categorize issues by type
5. Assess impact and priority

### Phase 2: Systematic Issue Resolution
**Goal**: Fix issues one category at a time

**Priority Order**:
1. **Schema Issues** (data types, constraints)
2. **Data Integrity** (NULL values, foreign keys)
3. **Data Quality** (string lengths, integer ranges)
4. **Missing Dependencies** (table existence)
5. **Performance Issues** (batch sizes, indexing)

### Phase 3: Validation Testing
**Goal**: Verify fixes and ensure no regressions

```bash
# Run validation cycle
./test_migration_workflow.sh
python validate_migration.py
```

### Phase 4: Production Readiness
**Goal**: Final verification before production

```bash
# Final comprehensive test
./production_readiness_check.sh
```

## 📊 Issue Tracking System

### Issue Categories

#### 1. Schema Compatibility
- **NULL Constraints**: Fields that require values in PostgreSQL
- **Data Types**: Type mismatches (BigInt, Varchar limits)
- **Constraints**: Unique, foreign key, check constraints

#### 2. Data Integrity  
- **Foreign Key Violations**: Missing parent records
- **Orphaned Records**: Child records without parents
- **Referential Integrity**: Cross-table consistency

#### 3. Data Quality
- **String Length**: Values exceeding column limits
- **Number Range**: Values outside PostgreSQL type ranges
- **Date/Time Format**: Incompatible date representations

#### 4. Migration Logic
- **Table Dependencies**: Incorrect migration order
- **Batch Processing**: Memory/performance issues
- **Transaction Handling**: Rollback scenarios

## 🎯 Testing Success Criteria

### ✅ Complete Success
- All tables migrated: **100%**
- All record counts match: **100%** 
- Data validation passes: **100%**
- Performance acceptable: **< 2x SQLite query time**

### ⚠️ Partial Success  
- Core tables migrated: **≥ 90%**
- Critical data intact: **≥ 95%**
- Documented workarounds for remaining issues

### ❌ Failure
- Core tables failed: **> 10%**
- Data corruption detected
- Performance degradation: **> 5x SQLite**

## 📈 Progress Tracking

### Test Run Template
```
Date: YYYY-MM-DD HH:MM
Test Run #: X
Previous Issues: X resolved, Y remaining
New Issues Found: Z

Results:
- Tables Migrated: X/Y (Z%)
- Records Migrated: X,XXX,XXX total
- Validation Status: PASS/FAIL
- Test Duration: X minutes

Issues Resolved This Run:
1. [CATEGORY] Description - Fix applied
2. [CATEGORY] Description - Fix applied

New Issues Found:
1. [CATEGORY] Description - Priority: HIGH/MED/LOW
2. [CATEGORY] Description - Priority: HIGH/MED/LOW

Next Actions:
- [ ] Fix issue #1
- [ ] Test scenario X
- [ ] Validate table Y
```

## 🔧 Development Workflow

### Before Each Test Run
```bash
# 1. Document current state
git status
git add -A
git commit -m "Pre-test state: $(date)"

# 2. Reset environment  
python reset_postgres.py

# 3. Run test with logging
./test_migration_workflow.sh | tee "logs/test_run_$(date +%Y%m%d_%H%M%S).log"
```

### After Each Test Run
```bash
# 1. Document results
cp migration_issues.md migration_issues_$(date +%Y%m%d).md

# 2. Update issue tracker
echo "## Test Run $(date)" >> migration_progress.md

# 3. Commit progress
git add -A  
git commit -m "Test run $(date): X issues resolved, Y remaining"
```

## 🚨 Critical Guidelines

### DO NOT Skip Steps
- Always reset database between tests
- Always run full validation after fixes
- Always document issues before fixing

### DO NOT Batch Fix Issues
- Fix one category at a time
- Test after each category of fixes
- Verify no regressions introduced

### DO NOT Ignore "Minor" Issues
- All data discrepancies must be documented
- Even successful migrations need validation
- Performance issues compound in production

## 📋 Pre-Production Checklist

### Data Verification
- [ ] All table counts match exactly
- [ ] Sample data integrity verified
- [ ] Foreign key relationships intact
- [ ] No data truncation occurred
- [ ] Character encoding preserved

### Performance Verification
- [ ] Migration completes within time window
- [ ] Query performance acceptable
- [ ] Index creation successful
- [ ] Connection pooling tested

### Operational Verification
- [ ] Backup/restore procedures tested
- [ ] Rollback plan verified
- [ ] Monitoring alerts configured
- [ ] Documentation updated

### Security Verification
- [ ] Access controls migrated
- [ ] Connection security verified
- [ ] Audit trail preserved
- [ ] Compliance requirements met

## 🎯 Success Metrics

### Quantitative
- **Data Accuracy**: 100% record count match
- **Data Quality**: 0 corruption events
- **Performance**: ≤ 2x query time vs SQLite
- **Availability**: < 1 hour downtime

### Qualitative  
- **Confidence Level**: High team confidence
- **Documentation**: Complete and accurate
- **Rollback Plan**: Tested and verified
- **Team Training**: Staff ready for operations

---

*This methodology ensures systematic, repeatable testing that builds confidence for production migration.*