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 if 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.


Be warned that boost is very, very sensitive & can hurt overall search quality if over-zealously applied. Even very small adjustments can affect relevance in a big way.

Term Boost

Term boosting is achieved by using SearchQuerySet.boost. You provide it the term you want to boost on & a floating point value (based around 1.0 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 SearchQuerySet API docs for more details on using this method.

Document Boost

Document boosting is done by adding a boost field to the prepared data SearchIndex creates. The best way to do this is to override SearchIndex.prepare:

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 Boost

Field boosting is enabled by setting the boost kwarg on the desired field. An example of this might be increasing the significance of a title:

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


Field boosting only has an effect when the SearchQuerySet filters on the field which has been boosted. If you are using a default search view or form you will need override the search method or other include the field in your search query. This example CustomSearchForm searches the automatic content field and the title field which has been boosted:

from haystack.forms import SearchForm

class CustomSearchForm(SearchForm):

    def search(self):
        if not self.is_valid():
            return self.no_query_found()

        if not self.cleaned_data.get('q'):
            return self.no_query_found()

        q = self.cleaned_data['q']
        sqs = self.searchqueryset.filter(SQ(content=AutoQuery(q)) | SQ(title=AutoQuery(q)))

        if self.load_all:
            sqs = sqs.load_all()

        return sqs.highlight()