# Boost

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

Note

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.

Warning

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).

Example:

    # 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().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

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()