Rank features field type

A rank_features field can index numeric feature vectors, so that they can later be used to boost documents in queries with a rank_feature query.

It is analogous to the rank_feature data type but is better suited when the list of features is sparse so that it wouldn’t be reasonable to add one field to the mappings for each of them.

  1. PUT my-index-000001
  2. {
  3.   "mappings": {
  4.     "properties": {
  5.       "topics": {
  6.         "type": "rank_features" 
  7.       }
  8.     }
  9.   }
  10. }
  12. PUT my-index-000001/_doc/1
  13. {
  14.   "topics": { 
  15.     "politics": 20,
  16.     "economics": 50.8
  17.   }
  18. }
  20. PUT my-index-000001/_doc/2
  21. {
  22.   "topics": {
  23.     "politics": 5.2,
  24.     "sports": 80.1
  25.   }
  26. }
  28. GET my-index-000001/_search
  29. {
  30.   "query": {
  31.     "rank_feature": {
  32.       "field": "topics.politics"
  33.     }
  34.   }
  35. }

Rank features fields must use the rank_features field type

Rank features fields must be a hash with string keys and strictly positive numeric values

rank_features fields only support single-valued features and strictly positive values. Multi-valued fields and zero or negative values will be rejected.

rank_features fields do not support sorting or aggregating and may only be queried using rank_feature queries.

rank_features fields only preserve 9 significant bits for the precision, which translates to a relative error of about 0.4%.