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DEEP EXPLANATION

Map-Reduce Patterns in LangGraph Agent Workflows (ANSWERED)

Project BasedLangGraphMedium14 min read

**Pattern** Planner node outputs list of work items → map workers process each (possibly subgraph) → reducer synthesizes executive summary or ranked list.

TL;DR — Quick Answer

Map phase fans out work items to parallel nodes or dynamic sends; reduce node merges structured results with summarization or voting; enforce concurrency caps and handle stragglers.

The Interview Question

Implement map-reduce in LangGraph: parallel subtasks over items, then aggregate — e.g., analyze 50 PRs.

Deep Explanation

Pattern Planner node outputs list of work items → map workers process each (possibly subgraph) → reducer synthesizes executive summary or ranked list.

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LangGraphMap-ReduceParallelLangChainStartups

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Parallel Node Execution in LangGraph (EXPLAINED)

**Parallelism model** LangGraph can schedule independent nodes in same superstep concurrently — e.g., search three sources at once. Reducers combine outputs into unified state field.

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