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No configuration required: The Parallel Join node has zero configurable properties. It automatically pairs with the preceding Parallel Fork node by analysing the workflow graph structure. All behaviour — how long to wait, how many lanes to collect, and how to store results — is determined automatically.

Properties

Property Type Required Default Description
No properties — the Parallel Join node has no configuration.

Automatic Fork-Join Pairing

The BizFirstAI execution engine automatically determines which Parallel Fork a given Parallel Join is associated with by traversing the workflow graph backwards from the Join node. The first Parallel Fork found that has active parallel lanes is the associated Fork. This means:

Memory Written by Parallel Join

When all lanes complete, the Join node writes the following to the execution memory before firing its success port:

Memory Key Pattern Type Description
lane_N_* (e.g., lane_0_status) various All variables and outputs from lane N are written with a lane_N_ prefix. For example, if lane 1 produced a variable smsSent = true, the Join writes lane_1_smsSent = true. N is 0-based.
lane_outputs array of objects An ordered array where each element is the final execution context object of the corresponding lane. lane_outputs[0] is the full context of lane 0, lane_outputs[1] of lane 1, etc.
lane_success_count integer The number of lanes that completed without error.
lane_failure_count integer The number of lanes that completed with an error (relevant when fail_fast: false).
IsParallelExecutionActive boolean (false) Reset to false — signals that parallel execution has ended and normal sequential execution resumes.
Tip — Access lane results predictably: The lane index (0, 1, 2, ...) corresponds to the order in which the lanes were listed in the Parallel Fork's connections.success array. Document your Fork configuration clearly so you always know which lane index corresponds to which operation (e.g., lane 0 = email, lane 1 = SMS, lane 2 = Slack).