在序列化器字段中使用属性时如何优化 DRF 编号查询？

Question

I am working on a DRF API and I am not completely familiar with django properties.

The DB relationships are classic. Companies have different jobs to which candidates can apply. Each job has several matches, match being a joined table between a job and a candidate. Matches have different statuses representing different phases of an application process.

So here is the deal: I am using a drf viewset to get data from the api. This viewset uses a serializer to get specific fields, specifically the number of matches per status for a job. The simplified version of the serializer looks something like this.

class Team2AmBackofficeSerializer(Normal2JobSerializer):

    class Meta:
        model = Job
        fields = (    
            'pk',
            'name',
            'company',
            'company_name',
            'job__nb_matches_proposition',
            'job__nb_matches_preselection',
            'job__nb_matches_valides',
            'job__nb_matches_pitches',
            'job__nb_matches_entretiens',
            'job__nb_matches_offre',
        )

The job__xxx fields are using the decorator @property , for instance:

@property
def job__nb_matches_offre(self):
    return self.matches.filter(current_status__step_name='Offre').count()

The problem is each time I add one of these properties to my serializer's fields, the number of DB queries increases significantly. This is of course due to the fact that each property calls the DB multiple times. So here is my question:

Is there a way to optimize the number of queries made to the DB, either by changing something in the serializer or by getting the number of matches for a specific status in a different manner?

I have had a look at select_related and prefetch_related . This allows me to reduce the numbers of queries when getting information about the company but not really for the number of matches.

Any help is greatly appreciated:)

Answer 1

What you want is to annotate your queryset with these values which will result in the database doing all the counting in just one query. The result is significantly faster than your current solution.

Example:

from django.db.models import Count, Q

Job.objects.annotate(
    'nb_matches_offre'=Count(
        'pk',
        filter=Q(current_status__step_name='Offre')
    ),
    'nb_matches_entretiens'=Count(...)
).all()

The resulting queryset will contain Job objects that have the properties job_obj.nb_matches_offre and job_obj.nb_matches_entretiens with the count.

See also https://docs.djangoproject.com/en/3.0/topics/db/aggregation/