Historian Module (Reference) provides comprehensive time-series data collection, storage, and retrieval capabilities for FrameworX solutions.
Key Concepts:
- Historian Tag: Individual data points mapped for archiving
- Historian Table: Logical grouping of tags
- Storage Location: Data repository
- Historian Engine: Data collection engine
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Historian Module Configuration
Designer UI Section
Configuration Sections
| Section | Path | Purpose |
|---|---|---|
| Storage Locations | Historian → Storage Locations | Define data repositories |
| Historian Tables | Historian → Historian Tables | Configure archiving groups |
| Historian Tags | Historian → Historian Tags | Map tags to tables |
| Historian Monitor | Historian → Historian Monitor | Runtime status and trends |
Configuration Workflow
| Step | Action | Purpose |
|---|---|---|
| 1. Define Storage | Configure default database | Set primary repository |
| 2. Add Locations | Configure external historians | Multiple storage targets |
| 3. Create Tables | Define historian tables | Group tags logically |
| 4. Map Tags | Assign tags to tables | Configure collection |
| 5. Set Triggers | Configure archiving events | Control data collection |
Storage Options
SQL Databases |
|---|
Dataset.DB.TagHistorian
|
TagProvider Storage Service |
|---|
External historian integration:
|
ScriptClass Custom Storage |
|---|
For specialized requirements:
|
Runtime Architecture
Process Execution
The Historian Module runs as an isolated server process:
- Event detection and triggering
- Data archiving operations
- Store and Forward management
- Query response handling
- Synchronization tasks
Control Operations
Access via Runtime → Runtime Diagnostics:
- Run/Pause/Stop execution
- Monitor performance metrics
- View error messages
- Check module status
Archiving Control
Trigger-Based
Event-driven collection:
- Time triggers (Server.Minute)
- Tag triggers (value change)
- Expression triggers
- Batch/process events
SaveOnChange
Continuous monitoring:
- Individual tag tracking
- Value change detection
- Deadband filtering
- Asynchronous storage
TimeDeadband
Minimum interval control:
- Prevents excessive writes
- Reduces storage requirements
- Maintains data integrity
Display Integration
TrendChart Control
Built-in visualization:
- Real-time trending
- Historical analysis
- Multiple pen support
- Zoom and pan features
Historian Monitor
Runtime monitoring interface:
- Table status display
- Error tracking
- Performance metrics
- Remote web access
Performance Optimization
Table Design
- Group by update frequency
- Limit tags per table (50-100)
- Match process dynamics
- Consider query patterns
Storage Strategy
- Choose appropriate schema
- Set retention policies
- Enable compression
- Plan capacity
Deadband Configuration
- Value deadbands for noise
- Time deadbands for frequency
- Deviation for exceptions
- Rate of change for upsets
Common Configurations
High-Speed Data
Storage: Local SQLite
Schema: Normalized
Trigger: SaveOnChange
TimeDeadband: 1 second
Retention: 30 daysProduction Records
Storage: SQL Server
Schema: Standard
Trigger: Batch events
SaveQuality: True
Retention: 365 daysCompliance Data
Storage: CanaryLabs
Store&Forward: True
SaveQuality: True
Retention: 7 years
Audit: EnabledBest Practices Checklist
Design
- Plan storage architecture - Match technology to requirements
- Group tags logically - Similar rates and relationships
- Size tables appropriately - Balance performance
- Configure deadbands - Optimize storage
- Set retention policies - Manage growth
Operations
- Monitor regularly - Check error counts
- Test failover - Verify Store and Forward
- Archive old data - Maintain performance
- Document configuration - Track changes
- Backup settings - Protect configuration
Performance
- Optimize queries - Use appropriate time ranges
- Index databases - Improve retrieval
- Cache frequently - Reduce database load
- Batch operations - Minimize transactions
Troubleshooting
Data Not Storing
- Verify trigger configuration
- Check table assignment
- Confirm database connection
- Review error messages
Incomplete Data
- Check module started status
- Verify tag quality
- Review deadband settings
- Examine triggers
Slow Retrieval
- Enable caching
- Optimize query ranges
- Check database indexes
- Review network latency
Store and Forward Issues
- Verify feature enabled
- Check local disk space
- Monitor buffer size
- Review sync status
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