Configure Qdrant's Optimizer for Predictable Search Latency

A Qdrant benchmark using 1.76 million 1024-dimensional Cohere-embedded MS MARCO passages on a single 14-core, 32GB node found that optimizer settings strongly affect search latency after bulk ingestion, as indexing, merging, and vacuuming compete with queries for CPU and I/O. Continuous indexing produced a roughly 11-minute recovery period with median search latency of 780 ms and p95 of 2 seconds, but delivered fast settled searches at 4.3 ms median, whereas disabling indexing avoided the backlog but left brute-force search at about 257 ms median. The experimental prevent_unoptimized option substantially reduced ingestion-period latency by deferring newly written points from search until optimized, but temporarily made recent writes unavailable to queries; it also requires asynchronous writes to avoid blocking. Segment configuration created a trade-off between recovery speed and final performance: a single segment achieved the fastest steady-state latency but took over an hour to optimize, while smaller or more numerous segments cleared much faster but increased settled query latency. Restricting optimizer threads made latency during loads smoother but extended backlog clearing, while raising the deletion threshold could avoid costly vacuum operations during active searches at the expense of retaining deleted data longer. The results caution that deferred indexing can create severe contention when later reenabled unless paired with prevent_unoptimized, and emphasize that measurements from the shared single-node environment are directional rather than universal performance guarantees.

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