content| docs.vespa.ai
Proton is Vespa's search core and runs on each content node as the vespa-proton-bin process.| docs.vespa.ai
Vespa can scale in multiple scaling dimensions:| docs.vespa.ai
Improvements made to triple the query performance of lexical search in Vespa.| Vespa Blog
Part one in a blog post series on billion-scale vector search. This post covers using nearest neighbor search with compact binary representations and bitwise hamming distance.| Vespa Blog
A schema defines a document type and what we want to compute over it, the| docs.vespa.ai
The Container is the home for all global processing of| docs.vespa.ai
The| docs.vespa.ai
numeric| docs.vespa.ai
Query features| docs.vespa.ai
Vespa ranks documents retrieved by a query by performing computations or inference that produces a score for each document. | docs.vespa.ai
Vespa uses a linguistics module to process text in queries and documents during indexing and searching.| docs.vespa.ai
expand all| docs.vespa.ai
expand all| docs.vespa.ai
expand all| docs.vespa.ai
Vespa allows expressing multi-phased retrieval and ranking of documents. The retrieval phase is done close to the data in the content nodes,| docs.vespa.ai
Follow @msmarco| microsoft.github.io
Refer to the Query API guide for API examples.| docs.vespa.ai