In some scenarios, I want to calculate the cosine similarity between M dense_vectors and all the stored dense_vectors. This can be achieved by calling the cosineSimilarity function for M times like this:
"script": {
"source": "cosineSimilarity(params.query_vector, doc['vector']) + 1",
"params": {
"query_vector": query_vector,
}
}
What I want to ask is:
1. Will it be faster to batch these M dense_vectors and then do matrix operations(like numpy in python) for only one time?
2. Does es support batch inference with cosineSimilarity ?
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