Return

Control Flow Pipeline

Synopsis

Finalizes processing and prevents further pipeline execution.

Schema

- return:
    description: <text>
    if: <script>
    ignore_failure: <boolean>
    ignore_missing: <boolean>
    on_failure: <processor[]>
    on_success: <processor[]>
    tag: <string>

Configuration

The following fields are used to define the processor:

Field	Required	Default	Description
description	N	-	Explanatory note
if	N	-	Condition to run
ignore_failure	N	false	Continue processing if operation fails
ignore_missing	N	false	Skip processing if referenced field doesn't exist
on_failure	N	-	See Handling Failures
on_success	N	-	See Handling Success
tag	N	-	Identifier

Details

Terminates pipeline execution immediately, preventing any subsequent processors from running. This processor is used to implement early termination logic, conditional exit points, and optimization paths that skip unnecessary processing.

When the return processor executes, it stops the current pipeline and marks the processing as complete. The data processed up to this point is preserved and passed to the next stage.

note

The return processor immediately stops pipeline execution. Any processors defined after a return statement will not be executed unless the return is conditional and the condition is not met.

This processor is commonly used for implementing business logic that requires early exit conditions, such as filtering logic, error handling, or optimization scenarios.

warning

Return processors with success/failure chains will execute those chains before terminating the pipeline. This allows for cleanup operations or additional processing before exit.

Examples

Basic Early Exit

Stopping pipeline execution early...	- set: field: processed value: true - return: description: "Exit after initial processing" - set: field: additional_processing value: true
skips remaining processors:	{ "processed": true }

Conditional Return

Exiting based on field conditions...	- return: if: "logEntry.skip_processing == true" description: "Skip processing when flag is set" - set: field: full_processing value: true - enrich: field: user_id target: user_details
returns early when condition matches:	{ "skip_processing": true }

Error Handling Return

Using return for error scenarios...	- validate: field: required_field exists: true on_failure: - set: field: error value: "Missing required field" - return: description: "Exit due to validation failure" - set: field: validation_passed value: true
exits pipeline on validation failure:	{ "error": "Missing required field" }

Return with Cleanup

Performing cleanup before exit...	- return: description: "Exit with cleanup operations" on_success: - set: field: exit_timestamp value: "{{now}}" - set: field: pipeline_status value: "completed_early"
executes cleanup before termination:	{ "exit_timestamp": "2024-01-15T10:30:00Z", "pipeline_status": "completed_early" }

Performance Optimization

Optimizing pipeline for specific data types...	- return: if: "logEntry.log_level == 'DEBUG' && logEntry.environment == 'production'" description: "Skip debug logs in production" on_success: - set: field: filtered_out value: true - enrich: field: log_data target: enriched_data - complex_analysis: field: enriched_data
skips expensive processing for debug logs:	{ "log_level": "DEBUG", "environment": "production", "filtered_out": true }

Multi-Path Exit Strategy

Different exit points for different scenarios...	- return: if: "logEntry.priority == 'low'" description: "Quick exit for low priority events" on_success: - set: field: processing_level value: "minimal" - return: if: "logEntry.priority == 'medium'" description: "Standard processing complete" on_success: - set: field: processing_level value: "standard" - set: field: processing_level value: "full" - advanced_processing: field: data
exits at different points based on priority:	{ "priority": "medium", "processing_level": "standard" }