The new TrigramSimilarity feature of the django.contrib.postgres was great for a problem I had. I use it for a search bar to find hard to spell latin names. The problem is that there are over 2 million names, and the search takes longer then I want.
I'd like to create a index on the trigrams as descibed in the postgres documentation.
But I am not sure how to do this in a way that the Django API would make use of it. For the postgres text search there is a description on how to create an index, but not for the trigram similarity.
This is what I have right now:
class NCBI_names(models.Model):
tax_id = models.ForeignKey(NCBI_nodes, on_delete=models.CASCADE, default = 0)
name_txt = models.CharField(max_length=255, default = '')
name_class = models.CharField(max_length=32, db_index=True, default = '')
class Meta:
indexes = [GinIndex(fields=['name_txt'])]
In the view's get_queryset method:
class TaxonSearchListView(ListView):
#form_class=TaxonSearchForm
template_name='collectie/taxon_list.html'
paginate_by=20
model=NCBI_names
context_object_name = 'taxon_list'
def dispatch(self, request, *args, **kwargs):
query = request.GET.get('q')
if query:
try:
tax_id = self.model.objects.get(name_txt__iexact=query).tax_id.tax_id
return redirect('collectie:taxon_detail', tax_id)
except (self.model.DoesNotExist, self.model.MultipleObjectsReturned) as e:
return super(TaxonSearchListView, self).dispatch(request, *args, **kwargs)
else:
return super(TaxonSearchListView, self).dispatch(request, *args, **kwargs)
def get_queryset(self):
result = super(TaxonSearchListView, self).get_queryset()
#
query = self.request.GET.get('q')
if query:
result = result.exclude(name_txt__icontains = 'sp.')
result = result.annotate(similarity=TrigramSimilarity('name_txt', query)).filter(similarity__gt=0.3).order_by('-similarity')
return result
I found a 12/2020 article that uses the newest version of Django ORM as such:
class Author(models.Model):
first_name = models.CharField(max_length=100)
last_name = models.CharField(max_length=100)
class Meta:
indexes = [
GinIndex(
name='review_author_ln_gin_idx',
fields=['last_name'],
opclasses=['gin_trgm_ops'],
)
]
If, like the original poster, you were looking to create an index that works with icontains, you'll have to index the UPPER() of the column, which requires special handling from OpClass:
from django.db.models.functions import Upper
from django.contrib.postgres.indexes import GinIndex, OpClass
class Author(models.Model):
indexes = [
GinIndex(
OpClass(Upper('last_name'), name='gin_trgm_ops'),
name='review_author_ln_gin_idx',
)
]
To use it, you need to add 'django.contrib.postgres' in your INSTALLED_APPS.
Inspired from an old article on this subject, I landed to a current one which gives the following solution for a GistIndex:
Update: From Django-1.11 things seem to be simpler, as this answer and django docs sugest:
from django.contrib.postgres.indexes import GinIndex
class MyModel(models.Model):
the_field = models.CharField(max_length=512, db_index=True)
class Meta:
indexes = [GinIndex(fields=['the_field'])]
From Django-2.2, an attribute opclasses will be available in class Index(fields=(), name=None, db_tablespace=None, opclasses=()) for this purpose.
from django.contrib.postgres.indexes import GistIndex
class GistIndexTrgrmOps(GistIndex):
def create_sql(self, model, schema_editor):
# - this Statement is instantiated by the _create_index_sql()
# method of django.db.backends.base.schema.BaseDatabaseSchemaEditor.
# using sql_create_index template from
# django.db.backends.postgresql.schema.DatabaseSchemaEditor
# - the template has original value:
# "CREATE INDEX %(name)s ON %(table)s%(using)s (%(columns)s)%(extra)s"
statement = super().create_sql(model, schema_editor)
# - however, we want to use a GIST index to accelerate trigram
# matching, so we want to add the gist_trgm_ops index operator
# class
# - so we replace the template with:
# "CREATE INDEX %(name)s ON %(table)s%(using)s (%(columns)s gist_trgrm_ops)%(extra)s"
statement.template =\
"CREATE INDEX %(name)s ON %(table)s%(using)s (%(columns)s gist_trgm_ops)%(extra)s"
return statement
Which you can then use in your model class like this:
class YourModel(models.Model):
some_field = models.TextField(...)
class Meta:
indexes = [
GistIndexTrgrmOps(fields=['some_field'])
]