What's the difference between select_related and prefetch_related in Django ORM?
Your understanding is mostly correct. You use select_related
when the object that you're going to be selecting is a single object, so OneToOneField
or a ForeignKey
. You use prefetch_related
when you're going to get a "set" of things, so ManyToManyField
s as you stated or reverse ForeignKey
s. Just to clarify what I mean by "reverse ForeignKey
s" here's an example:
class ModelA(models.Model):
pass
class ModelB(models.Model):
a = ForeignKey(ModelA)
ModelB.objects.select_related('a').all() # Forward ForeignKey relationship
ModelA.objects.prefetch_related('modelb_set').all() # Reverse ForeignKey relationship
The difference is that select_related
does an SQL join and therefore gets the results back as part of the table from the SQL server. prefetch_related
on the other hand executes another query and therefore reduces the redundant columns in the original object (ModelA
in the above example). You may use prefetch_related
for anything that you can use select_related
for.
The tradeoffs are that prefetch_related
has to create and send a list of IDs to select back to the server, this can take a while. I'm not sure if there's a nice way of doing this in a transaction, but my understanding is that Django always just sends a list and says SELECT ... WHERE pk IN (...,...,...) basically. In this case if the prefetched data is sparse (let's say U.S. State objects linked to people's addresses) this can be very good, however if it's closer to one-to-one, this can waste a lot of communications. If in doubt, try both and see which performs better.
Everything discussed above is basically about the communications with the database. On the Python side however prefetch_related
has the extra benefit that a single object is used to represent each object in the database. With select_related
duplicate objects will be created in Python for each "parent" object. Since objects in Python have a decent bit of memory overhead this can also be a consideration.
Both methods achieve the same purpose, to forego unnecessary db queries. But they use different approaches for efficiency.
The only reason to use either of these methods is when a single large query is preferable to many small queries. Django uses the large query to create models in memory preemptively rather than performing on demand queries against the database.
select_related
performs a join with each lookup, but extends the select to include the columns of all joined tables. However this approach has a caveat.
Joins have the potential to multiply the number of rows in a query. When you perform a join over a foreign key or one-to-one field, the number of rows won't increase. However, many-to-many joins do not have this guarantee. So, Django restricts select_related
to relations that won't unexpectedly result in a massive join.
The "join in python" for prefetch_related
is a little more alarming then it should be. It creates a separate query for each table to be joined. It filters each of these table with a WHERE IN clause, like:
SELECT "credential"."id",
"credential"."uuid",
"credential"."identity_id"
FROM "credential"
WHERE "credential"."identity_id" IN
(84706, 48746, 871441, 84713, 76492, 84621, 51472);
Rather than performing a single join with potentially too many rows, each table is split into a separate query.
Gone through the already posted answers. Just thought it would be better if I add an answer with actual example.
Let' say you have 3 Django models which are related.
class M1(models.Model):
name = models.CharField(max_length=10)
class M2(models.Model):
name = models.CharField(max_length=10)
select_relation = models.ForeignKey(M1, on_delete=models.CASCADE)
prefetch_relation = models.ManyToManyField(to='M3')
class M3(models.Model):
name = models.CharField(max_length=10)
Here you can query M2
model and its relative M1
objects using select_relation
field and M3
objects using prefetch_relation
field.
However as we've mentioned M1
's relation from M2
is a ForeignKey
, it just returns only 1 record for any M2
object. Same thing applies for OneToOneField
as well.
But M3
's relation from M2
is a ManyToManyField
which might return any number of M1
objects.
Consider a case where you have 2 M2
objects m21
, m22
who have same 5 associated M3
objects with IDs 1,2,3,4,5
. When you fetch associated M3
objects for each of those M2
objects, if you use select related, this is how it's going to work.
Steps:
- Find
m21
object. - Query all the
M3
objects related tom21
object whose IDs are1,2,3,4,5
. - Repeat same thing for
m22
object and all otherM2
objects.
As we have same 1,2,3,4,5
IDs for both m21
, m22
objects, if we use select_related option, it's going to query the DB twice for the same IDs which were already fetched.
Instead if you use prefetch_related, when you try to get M2
objects, it will make a note of all the IDs that your objects returned (Note: only the IDs) while querying M2
table and as last step, Django is going to make a query to M3
table with the set of all IDs that your M2
objects have returned. and join them to M2
objects using Python instead of database.
This way you're querying all the M3
objects only once which improves performance.