Datasets → Tutorial | Concept | How-to Guide | Reference

Overview

The Dataset Engine orchestrates:

• Synchronous and asynchronous database operations
• Connection pooling and thread management
• Client/server domain tag mapping
• Query execution through TServer services
• Result set propagation
• Multi-database coordination

Understanding the engine helps when:

• Optimizing database performance
• Managing concurrent operations
• Implementing client-specific data
• Troubleshooting connection issues

Architecture

Process Separation

The Dataset Module runs as TRunModule.exe (Dataset):

• Reads all dataset configurations
• Does NOT directly connect to databases
• Consumes TServer database services
• Manages tag mapping and updates

TServer provides:

• Actual database connections
• SQL execution services
• Connection pooling
• Transaction management

Connection Management

Single Thread per DB

• Each DB configuration creates ONE connection
• Single execution thread per database
• Sequential command execution

Parallel Execution

For concurrent operations to same database:

DB1 → Production Database (Thread 1)
DB2 → Production Database (Thread 2)
DB3 → Production Database (Thread 3)

Create multiple DB connections to same database for parallelism.

Execution Methods

Asynchronous Execution (Default)

Trigger: Property changes (Select, Insert, Update, Delete)

Flow:

1. Property triggered (screen/script)
2. Request propagated to server
3. Dataset Module receives request
4. TServer executes database operation
5. Results returned to Dataset Module
6. Tags mapped and updated
7. Execution continues in parallel

Advantages:

• Non-blocking operation
• Better performance
• Prevents UI freezing
• Allows parallel operations

Use Cases:

• Display queries
• Background updates
• Report generation
• Real-time monitoring

Synchronous Execution

Trigger: Method calls (SelectCommand, ExecuteCommand)

Flow:

1. Method called
2. Execution PAUSES
3. Dataset Module calls TServer
4. Database operation completes
5. Results returned
6. Tags mapped
7. Execution RESUMES

Advantages:

• Guaranteed completion
• Sequential logic
• Immediate results
• Transaction support

Risks:

• Can freeze UI if called from screen
• Blocks thread execution
• Performance bottlenecks

Use Cases:

• Script tasks
• Sequential operations
• Transaction requirements
• Data validation

Tag Domain Mapping

Execution Context

Tag mapping occurs in the original call domain:

Client-Initiated Calls:

• From displays or client scripts
• Mapping uses client domain
• Results visible to specific client
• Isolated from other clients

Server-Initiated Calls:

• From server scripts or tasks
• Mapping uses server domain
• Results visible project-wide
• Shared across all clients

Domain Selection Strategy

Performance Optimization

Connection Pooling

• Reuse existing connections
• Minimize connection overhead
• Configure pool size appropriately

Query Optimization

sql

-- Use parameters to prevent recompilation
SELECT * FROM Table WHERE ID = @id

-- Limit result sets
SELECT TOP 100 * FROM LargeTable

-- Use appropriate indexes
CREATE INDEX idx_timestamp ON Data(Timestamp)

Asynchronous Patterns

csharp

// Good: Asynchronous from screen
@Dataset.Table.MyTable.SelectCommand = "SELECT * FROM Data";

// Bad: Synchronous from screen (blocks UI)
@Dataset.Table.MyTable.SelectCommandWithStatus();

Batch Operations

• Group multiple operations
• Use transactions for consistency
• Minimize round trips

Threading Model

Dataset Module Thread

• Main coordination thread
• Manages request queue
• Handles tag mapping

TServer Database Threads

• One per DB connection
• Sequential execution per thread
• Connection isolation

Client Request Threads

• Asynchronous request handling
• Non-blocking UI operations
• Parallel client support

Error Handling

Connection Failures

• Automatic retry logic
• Connection pooling recovery
• Error event propagation

Query Errors

• Exception capture in TServer
• Error property population
• Tag mapping skipped on error

Timeout Management

• Configurable command timeout
• Connection timeout settings
• Automatic cleanup

Best Practices Checklist 

• Prefer asynchronous - Use properties over methods
• Avoid UI blocking - No synchronous calls from screens
• Use appropriate domains - Client for user, Server for shared
• Pool connections - Reuse database connections
• Optimize queries - Index, parameterize, limit
• Handle errors - Check status properties
• Monitor performance - Track execution times

Troubleshooting

Slow queries:

• Check execution plan
• Add appropriate indexes
• Reduce result set size
• Use asynchronous execution

Connection issues:

• Verify TServer running
• Check connection string
• Review firewall rules
• Monitor connection pool

Tag mapping problems:

• Verify domain selection
• Check tag existence
• Review mapping configuration
• Confirm execution context

Thread blocking:

• Avoid synchronous in UI
• Use Script Tasks
• Implement async patterns
• Monitor thread pool

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