dag-result-aggregator

To merge parallel DAG outputs, the aggregator collects completed results from all branches, applies a selected merge strategy like union or deep merge, resolves conflicts with provenance tracking, and formats a single structured result.

Merge strategies for aggregating parallel outputs include union, intersection, priority, weighted, and deep merge. Each strategy defines how conflicting data points from multiple DAG branches are combined into the final coherent result.

Conflict resolution during result consolidation tracks the provenance of each output from parallel branches. This ensures you know exactly which branch contributed conflicting data points when the aggregator merges them into a single structured result.

You need to aggregate parallel DAG outputs when coordinating multiple parallel analyses. It is necessary when your workflow requires consolidating findings from concurrent branches and preparing a single structured output for downstream nodes.

Yes, the aggregation process includes validation hooks for downstream nodes. After applying the merge strategy and conflict resolution, the output is formatted and validated to ensure the final consolidated result meets downstream requirements.

The best way to consolidate parallel analyses is using an aggregator that collects all branch outputs, applies a deep merge or priority strategy, tracks provenance for conflicts, and validates the final structured result for downstream consumption.