Scoring is a critical component of good search. Normal full-text searches automatically score a document based on how well it matches the query provided. However, sometimes you want certain documents to score better than they otherwise would. Boosting is a way to achieve this. There are three types of boost:
- Term Boost
- Document Boost
- Field Boost
Document & Field boost support was added in Haystack 1.1.
Despite all being types of boost, they take place at different times and have slightly different effects on scoring.
Term boost happens at query time (when the search query is run) and is based around increasing the score is a certain word/phrase is seen.
On the other hand, document & field boosts take place at indexing time (when the document is being added to the index). Document boost causes the relevance of the entire result to go up, where field boost causes only searches within that field to do better.
Term boosting is achieved by using
SearchQuerySet.boost. You provide it
the term you want to boost on & a floating point value (based around
as 100% - no boost).
# Slight increase in relevance for documents that include "banana". sqs = SearchQuerySet().boost('banana', 1.1) # Big decrease in relevance for documents that include "blueberry". sqs = SearchQuerySet().boost('blueberry', 0.8)
See the :doc:`searchqueryset_api` docs for more details on using this method.
Document boosting is done by adding a
boost field to the prepared data
SearchIndex creates. The best way to do this is to override
from haystack import indexes from notes.models import Note class NoteSearchIndex(indexes.SearchIndex, indexes.Indexable): # Your regular fields here then... def prepare(self, obj): data = super(NoteSearchIndex, self).prepare(obj) data['boost'] = 1.1 return data
Another approach might be to add a new field called
boost. However, this
can skew your schema and is not encouraged.
Field boosting is enabled by setting the
boost kwarg on the desired field.
An example of this might be increasing the significance of a
from haystack import indexes from notes.models import Note class NoteSearchIndex(indexes.SearchIndex, indexes.Indexable): text = indexes.CharField(document=True, use_template=True) title = indexes.CharField(model_attr='title', boost=1.125) def get_model(self): return Note