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:Search Relevance/VectorsVector searchVector searchenhancement"" muted="" aria-describedby="MDU6TGFiZWwyMzE3NA==-tooltip :R5b96b:">>enhancementTeam:Search RelevanceMeta label for the Search Relevance team in ElasticsearchMeta label for the Search Relevance team in Elasticsearch
Description
Description
Right now, for vectors stored as element_type: byte
we disallow scripting functions to be calculated with floating point query. However, if the user used some external quantization methodology, allowing the asymmetric distance calculation like this might be useful.
Since we already calculate magnitude for everything, the implementation will be fairly trivial.
The one aspect around this that might be "slow" is the actual vector ops. We have no SIMD optimized operations between float[], byte[]
for dot-product. But, that should be fairly simple to do.
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:Search Relevance/VectorsVector searchVector searchenhancement"" muted="" aria-describedby="MDU6TGFiZWwyMzE3NA==-tooltip :Ra5pmb:">>enhancementTeam:Search RelevanceMeta label for the Search Relevance team in ElasticsearchMeta label for the Search Relevance team in Elasticsearch