Running Workflows

Learn how to save and run designed pipelines, along with monitoring capabilities.

Save

You must save changes before running. Click the Save button on the top toolbar or use the shortcut Ctrl+S.

Validation

When saving, basic checks are performed for connection status and missing required settings. If there are errors, the save is blocked and problematic nodes are highlighted.

Manual Run

Batch Pipeline

1. Click the Run button (play icon) on the top toolbar.
2. When execution starts, the button changes to Stop, and the connection lines on the canvas display flow animations.
3. To stop the execution, click the Stop button.

Event Pipeline

1. Click the Register button on the top toolbar to register the event listener.
2. The pipeline transitions to a Listening state and will automatically execute when events are received.
3. To stop receiving events, click the Unregister button.

Scheduling

To run a pipeline periodically:

1. Click Settings (gear icon) on the top toolbar.
2. Set the frequency in the Schedule tab.
3. Once the settings are saved, a Schedule badge is displayed in the pipeline list.

For detailed scheduling configuration, refer to the Scheduling documentation.

Monitoring

[Screenshot] Workflow execution monitoring

Real-time Status

During execution, each node's status is indicated by a colored border.

Status	Color	Description
Running	Blue (animated)	Currently in execution
Success (ok/ready)	Green	Completed successfully
Failed (error)	Red	Execution failed
Pending	Yellow	Waiting (awaiting completion of dependency nodes)

Run History

The Run History Bar on the top toolbar provides an at-a-glance view of recent execution results. (Batch pipelines only)

• Each bar represents an individual execution run.
• Colors distinguish between success (green) and failure (red).
• Click a bar to view detailed information for that execution.

Batch Details

Clicking an execution run reveals the following information:

• Start/End Time: Execution duration
• Per-node Status: Execution result for each node
• Records Processed: Input/output data statistics
• Logs: Detailed execution logs

Error Handling

What to Check When Execution Fails

1. Click the red node: Select the failed node.
2. Inspector Panel: Review the error message and stack trace.
3. History Tab: Check the execution history and logs in the Code node's History tab.

Common Error Types

Error Type	Cause	Resolution
Connection Error	Failed to connect to data source	Check network, credentials
Schema Mismatch	Schema incompatibility	Verify input/output schema mapping
Code Error	Python/SQL code error	Fix code syntax and logic
Resource Limit	Insufficient resources	Reduce data size, adjust partitions
Timeout	Execution time exceeded	Optimize queries, adjust timeout settings