mirror of
https://github.com/github/awesome-copilot.git
synced 2026-04-18 06:05:55 +00:00
23 lines
1.4 KiB
Markdown
23 lines
1.4 KiB
Markdown
---
|
|
name: qdrant-scaling-query-volume
|
|
description: "Guides Qdrant query volume scaling. Use when someone asks 'query returns too many results', 'scroll performance', 'large limit values', 'paginating search results', 'fetching many vectors', or 'high cardinality results'."
|
|
---
|
|
|
|
# Scaling for Query Volume
|
|
|
|
Problem: When a query has a large limit (e.g. 1000) and there are multiple shards (e.g. 10), naively each shard must return the full 1000 results — totaling 10,000 scored points transferred and merged. This is wasteful since data is randomly distributed across auto-shards.
|
|
|
|
## Core idea
|
|
|
|
Instead of asking every shard for the full limit, ask each shard for a smaller limit computed via Poisson distribution statistics, then merge. This is safe because auto-sharding guarantees random, independent data distribution.
|
|
|
|
## When it activates
|
|
|
|
- More than 1 shard
|
|
- Auto-sharding is in use (all queried shards share the same shard key)
|
|
- The request's limit + offset >= SHARD_QUERY_SUBSAMPLING_LIMIT (128)
|
|
- The query is not exact
|
|
|
|
## Key tradeoff
|
|
|
|
The strategy trades a small probability of slightly incomplete results for a large reduction in inter-shard data transfer, especially for high-limit queries across many shards. The 1.2x safety factor and the 99.9% Poisson threshold keep the error rate very low — comparable to inaccuracies already introduced by approximate vector indices like HNSW. |