Using the Milvus Vector Database for Real-Time Query

This post details the real-time query mechanism in Milvus 2.0. It explains how data is loaded to query nodes from log brokers (streaming) and object storage (historical), managed in sealed and growing segments, and how load balancing and failover are handled. It introduces the concept of flowgraphs for partition filtering of incremental data and the role of timeticks and tsafe values. The query message structure (msgID, collectionID, execPlan, service_ts, travel_ts, guarantee_ts) and the real-time query process, including handling of unsolved messages and the local/global reduce steps for query results, are elaborated.