Scaling Search and Retrieval for Contextual AI

Chapter 8. Coordinated Distributed Search

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Objective: Understand how search queries are distributed, merged, and made resilient across multiple nodes.

Chapter 7 established how retrieval systems scale beyond a single node by partitioning the index into shards, distributing ownership, and preserving segment locality wherever possible. These mechanisms define where data resides and how it evolves over time. However, partitioning alone does not generate results. After distributing the index, each query must be executed across the partitions, and the results combined into a single coherent response.

This introduces a fundamental shift in the execution model. In a single-node system, query evaluation occurs within a unified execution context where all segments are locally accessible, and results can be computed directly. In contrast, a distributed system lacks a single node that has a complete view of the index. Each shard evaluates only its own segments, producing partial results that require coordination, ...