Optimizing Django Rest Framework - fix the n+1 problem!

Optimizing Django Rest Framework - fix the n+1 problem!

The N+1 problem is a common issue that can occur when using the Django REST framework serializer. It happens when the code makes multiple database queries to retrieve related data, instead of using a single query with a JOIN statement. This can significantly slow down the performance of your application.

One way to fix this issue is by using the select_related and prefetch_related methods on your queryset. These methods allow you to specify which related data should be fetched in a single database query, reducing the number of queries needed.

Here’s an example:

from django.db import models

class Author(models.Model):
    name = models.CharField(max_length=100)

class Book(models.Model):
    title = models.CharField(max_length=100)
    author = models.ForeignKey(Author, on_delete=models.CASCADE)

# Without select_related
books = Book.objects.all()
for book in books:
    print(book.author.name) # This will make a separate database query for each book

# With select_related
books = Book.objects.select_related('author').all()
for book in books:
    print(book.author.name) # This will make only one database query

In this example, we have two models: Author and Book. The Book model has a foreign key to the Author model. Without using select_related, retrieving the name of the author for each book would require a separate database query for each book. By using select_related, we can fetch all the related data in a single query.

select_related and prefetch_related

tl;dr
select_related is used for one-to-one and many-to-one relationships while prefetch_related is used for one-to-many and many-to-many relationships.

select_related and prefetch_related are two methods in Django’s ORM that can help reduce the number of database queries. select_related is used to retrieve related objects in a single query when you know you will be accessing the related objects. It works by creating a SQL join and including the fields of the related object in the SELECT statement.
On the other hand, prefetch_related does a separate lookup for each relationship and does the ‘joining’ in Python. This can be more efficient when dealing with many-to-many or many-to-one relationships.

select_related

select_related is a method you can use on a Django QuerySet to optimize database queries when retrieving related data. It works by creating a SQL JOIN statement to retrieve the related data in a single query, instead of making multiple queries.

select_related is useful when you have a foreign key or one-to-one relationship between two models. You can use it to specify which related fields should be fetched in the same query as the main model.

Here’s an example:

from django.db import models

class Author(models.Model):
    name = models.CharField(max_length=100)

class Book(models.Model):
    title = models.CharField(max_length=100)
    author = models.ForeignKey(Author, on_delete=models.CASCADE)

# Without select_related
books = Book.objects.all()
for book in books:
    print(book.author.name) # This will make a separate database query for each book

# With select_related
books = Book.objects.select_related('author').all()
for book in books:
    print(book.author.name) # This will make only one database query

In this example, we have two models: Author and Book. The Book model has a foreign key to the Author model. Without using select_related, retrieving the name of the author for each book would require a separate database query for each book. By using select_related, we can fetch all the related data in a single query.

prefetch_related

prefetch_related is another method you can use on a Django QuerySet to optimize database queries when retrieving related data. It works by fetching the related data in a separate query and then associating it with the main model in Python.

prefetch_related is useful when you have a many-to-many or reverse foreign key relationship between two models. You can use it to specify which related fields should be fetched in a separate query and then associated with the main model.

Here’s an example:

from django.db import models

class Author(models.Model):
    name = models.CharField(max_length=100)
    books = models.ManyToManyField('Book')

class Book(models.Model):
    title = models.CharField(max_length=100)

# Without prefetch_related
authors = Author.objects.all()
for author in authors:
    print(author.name)
    for book in author.books.all():
        print(book.title) # This will make a separate database query for each author

# With prefetch_related
authors = Author.objects.prefetch_related('books').all()
for author in authors:
    print(author.name)
    for book in author.books.all():
        print(book.title) # This will make only two database queries

In this example, we have two models: Author and Book, with a many-to-many relationship between them. Without using prefetch_related, retrieving the books for each author would require a separate database query for each author. By using prefetch_related, we can fetch all the related data in two queries: one for the authors and one for the books.

Use prefetch_related with reverse 1-Many relationship

Consider the following case where you have a Teacher model and each teacher has many Student

class Teacher(models.Model):
    name = models.CharField(max_length=100)

class Student(models.Model):
    name = models.CharField(max_length=100)
    teacher = models.ForeignKey(Teacher, on_delete=models.CASCADE, related_name='students')

to get a list of all teachers and their students if using `select_related` Django would try to fetch all the related students for all teachers in a single query. However, this approach can be less efficient since it may result in duplicate data being fetched

On the other hand, if you used `prefetch_related` Django will perform two queries

  • one to get all the teachers

  • another, get all the students for those teachers. The students will be cached in memory so that accessing them in the loop doesn't result in additional queries.