[How to: summarize text through parallelization](https://python.langchain.com/docs/how_to/summarize_map_reduce): LLM should read this page when needing to summarize long text documents using parallelization, needing to optimize summarization for large volumes of text, and needing efficient summarization strategies. This page discusses using a map-reduce strategy to summarize text through parallelization, including breaking the text into subdocuments, generating summaries for each in parallel (map step), and then consolidating the summaries into a final summary (reduce step). It provides code examples using LangChain and LangGraph.

