We have a custom solution for calculating similarities using feature vectors. Each document in Elasticsearch index can have multiple entities. Thus, for each document we have basically
long formatted data we would like to use to calculate distances. Such as this:
[ [378322298287171600,-9182346388506132000,-7884923301547995000,2954398850619687400,5792760765226170000,6941191355558596000,-9175934689997701000,2453767474651472000], [2395942447151390700,7206045950792974000,-6761273774897486000,648553841033347700,-4591414079501816000,3563632123683616000,288379928265751740,733693665263878500], ... ]
How should we define the mappings in order to access this data in Painless scripts in a performant way:
long vectors = doc['vectors'].value;
Thanks for all the tips!