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Document per-shard fusion in distributed collections

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Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Dylan Couzon
2026-07-12 12:01:31 -04:00
co-authored by Claude Opus 4.8
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qdrant-landing/content/documentation/search/hybrid-queries.md
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@@ -117,6 +117,12 @@ For a deeper breakdown of when to prefer each, see the [FAQ on RRF vs. DBSF](/do
<aside role="status">A common request is "alpha-weighted linear combination of dense and sparse scores." This is unreliable without first normalizing the scores: dense (cosine, bounded) and sparse (BM25, unbounded) scores live on different scales that also shift per query, so a fixed alpha over raw scores tends to be dominated by whichever retriever has larger raw magnitudes on a given query. RRF sidesteps this by using ranks. DBSF sidesteps it by normalizing distributions.</aside> <aside role="status">A common request is "alpha-weighted linear combination of dense and sparse scores." This is unreliable without first normalizing the scores: dense (cosine, bounded) and sparse (BM25, unbounded) scores live on different scales that also shift per query, so a fixed alpha over raw scores tends to be dominated by whichever retriever has larger raw magnitudes on a given query. RRF sidesteps this by using ranks. DBSF sidesteps it by normalizing distributions.</aside>
### Fusion in Distributed Collections
In a multi-shard collection, a fusion merges results across all shards only when it is the main query. A fusion nested inside a prefetch runs independently on each shard and fuses that shard's local results, so the ranking is per shard rather than global. A fusion is nested whenever the main query is something else, such as a formula query or an outer fusion.
To fuse across shards, make the fusion the main query, as in the [RRF](#reciprocal-rank-fusion-rrf) and [DBSF](#distribution-based-score-fusion-dbsf) examples above. A main query runs a single operation, so keeping a formula rescore over a fused result requires a single shard.
## Multi-Stage Queries ## Multi-Stage Queries
In general, larger vector representations give more accurate search results, but makes them more expensive to compute. In general, larger vector representations give more accurate search results, but makes them more expensive to compute.
@@ -163,6 +169,8 @@ A formula query lets you compose a final score from prefetch scores (`$score`),
The [Choosing a Fusion Method notebook](https://githubtocolab.com/qdrant/examples/blob/master/fusion-methods/Choosing_a_Fusion_Method.ipynb) shows this pattern end-to-end with exponential decay on a `published_at` payload field. For full formula query and decay function syntax, see the [Search Relevance reference](/documentation/search/search-relevance/). The [Choosing a Fusion Method notebook](https://githubtocolab.com/qdrant/examples/blob/master/fusion-methods/Choosing_a_Fusion_Method.ipynb) shows this pattern end-to-end with exponential decay on a `published_at` payload field. For full formula query and decay function syntax, see the [Search Relevance reference](/documentation/search/search-relevance/).
<aside role="status">Because this pattern puts the fusion inside a prefetch, multi-shard collections compute that fusion per shard, not globally. See <a href="#fusion-in-distributed-collections">Fusion in Distributed Collections</a>.</aside>
## Grouping ## Grouping
_Available as of v1.11.0_ _Available as of v1.11.0_