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nearest-neighbor-search-guide.html.md
# Vespa nearest neighbor search - a practical guide This guide is a practical introduction to using Vespa nearest neighbor search query operator and how to combine nearest neighbor search with othe...docs.vespa.ai/en/querying/nearest-neighbor-search-guide.html.mdRegistered: Fri Dec 12 05:07:54 UTC 2025 - Last Modified: Wed Dec 10 18:38:33 UTC 2025 - 69.1K bytes - Viewed (0) -
graceful-degradation.html.md
# Graceful Query Coverage Degradation Ideally you want to query all data indexed in a Vespa cluster within the specified timeout, but that might not always be possible: - The system might be overlo...docs.vespa.ai/en/performance/graceful-degradation.html.mdRegistered: Fri Dec 12 05:08:51 UTC 2025 - Last Modified: Wed Dec 10 18:38:33 UTC 2025 - 10.7K bytes - Viewed (0) -
sizing-search.html.md
# Vespa Serving Scaling Guide _Vespa can scale in multiple scaling dimensions:_ - Scale document volume and write volume - Scale query throughput - Scale serving latency to meet service level agree...docs.vespa.ai/en/performance/sizing-search.html.mdRegistered: Fri Dec 12 05:10:32 UTC 2025 - Last Modified: Wed Dec 10 18:38:33 UTC 2025 - 32.5K bytes - Viewed (0) -
query-rewriting.html.md
# Query Rewriting A search application can improve the quality by interpreting the intended meaning of the user queries. Once the meaning is guessed, the query can be rewritten to one that will sat...docs.vespa.ai/en/linguistics/query-rewriting.html.mdRegistered: Fri Dec 12 05:12:29 UTC 2025 - Last Modified: Wed Dec 10 18:38:33 UTC 2025 - 13.9K bytes - Viewed (0) -
tensor-examples.html.md
# Tensor Computation Examples Tensors can be used to express machine-learned models such as neural nets, but they can be used for much more than that. The tensor model in Vespa is powerful, since i...docs.vespa.ai/en/ranking/tensor-examples.html.mdRegistered: Fri Dec 12 05:09:34 UTC 2025 - Last Modified: Wed Dec 10 18:38:33 UTC 2025 - 20.6K bytes - Viewed (0) -
grouping.html.md
# Grouping and aggregation ## Grouping Interface Try running requests on the [grouping example data](https://github.com/vespa-engine/sample-apps/blob/master/examples/part-purchases-demo/ext/feed.js...docs.vespa.ai/en/querying/grouping.html.mdRegistered: Fri Dec 12 05:15:52 UTC 2025 - Last Modified: Wed Dec 10 18:38:33 UTC 2025 - 41.1K bytes - Viewed (0) -
searching-multivalue-fields.html.md
# Searching and ranking of multivalued fields This guide explains how to search and rank over structured multivalued fields. The examples in this guide use the [weightedset](../reference/schemas/sc...docs.vespa.ai/en/querying/searching-multivalue-fields.html.mdRegistered: Fri Dec 12 05:15:55 UTC 2025 - Last Modified: Wed Dec 10 18:38:33 UTC 2025 - 19.3K bytes - Viewed (0) -
lightgbm.html.md
# Ranking with LightGBM Models [LightGBM](https://github.com/microsoft/LightGBM) is a gradient boosting framework, similar to [XGBoost](xgboost). Among other[advantages](https://github.com/microsof...docs.vespa.ai/en/ranking/lightgbm.html.md Similar Results (1)Registered: Fri Dec 12 05:15:25 UTC 2025 - Last Modified: Wed Dec 10 18:38:33 UTC 2025 - 10.5K bytes - Viewed (0) -
approximate-nn-hnsw.html.md
# Approximate nearest neighbor search using HNSW index This document describes how to speed up searches for nearest neighbors in vector spaces by adding[HNSW index](../reference/schemas/schemas.htm...docs.vespa.ai/en/querying/approximate-nn-hnsw.html.mdRegistered: Fri Dec 12 05:13:45 UTC 2025 - Last Modified: Wed Dec 10 18:38:33 UTC 2025 - 15.5K bytes - Viewed (0) -
ranking-expressions.html.md
# Ranking Expressions This is a complete reference to the _ranking expressions_ used to configure application specific ranking functions. For examples and an overview of how to use ranking expressi...docs.vespa.ai/en/reference/ranking/ranking-expressions.html.mdRegistered: Fri Dec 12 05:18:36 UTC 2025 - Last Modified: Wed Dec 10 18:38:33 UTC 2025 - 24.5K bytes - Viewed (0)