The document discusses advanced techniques for optimizing Django's Object-Relational Mapping (ORM), focusing on model definitions, relationships, and how to reduce query counts. It covers strategies such as utilizing caching, implementing more efficient queries with methods like select_related, and addressing common pitfalls like repeated database queries. The author emphasizes the importance of understanding query sources, applying optimizations, and profiling application performance.

1. Advanced Django ORM
techniques
Daniel Roseman http://blog.roseman.org.uk

2. About Me
• Python user for five years
• Discovered Django four years ago
• Worked full-time with Python/Django since
2008.
• Top Django answerer on StackOverflow!
• Occasionally blog on Django, concentrating
on efficient use of the ORM.

3. Contents
• Behind the scenes: models and fields
• How model relationships work
• More efficient relationships
• Other optimising techniques

4. Django ORM
efficiency: a story

6. 414 queries!

7. How can you stop this
happening to you?
http://www.flickr.com/photos/m0n0/4479450696

8. Behind the scenes:
models and fields
http://www.flickr.com/photos/spacesuitcatalyst/847530840

9. Defining a model
• Model structure initialised via metaclass
• Called when model is first defined
• Resulting model class stored in cache to
use when instantiated

10. Fields
• Fields have contribute_to_class
• Adds methods, eg get_FOO_display()
• Enables use of descriptors for field access

11. Model metadata
• Model._meta
• .fields
• .get_field(fieldname)
• .get_all_related_objects()

12. Model instantiation
• Instance is populated from database initially
• Has no subsequent relationship with db
until save
• No identity between models

13. Querysets
• Model=manager returns a queryset:
foos Foo.objects.all()
• Queryset is an ordered list of instances
of a single model
• No database access yet
• Slice: foos[0]
• Iterate: {% for foo in foos %}

14. Where do all those
queries come from?
• Repeated queries
• Lack of caching
• Relational lookup
• Templates as well as views

15. Repeated queries
def get_absolute_url(self):
return "%s/%s" % (
self.category.slug,
self.slug
)
Same category, but query is
repeated for each article

16. Repeated queries
• Same link on every
page
• Dynamic, so can't
go in urlconf
• Could be cached
or memoized

17. Relationships
http://www.flickr.com/photos/katietegtmeyer/124315322

18. Relational lookups
• Forwards:
foo.bar.field
• Backwards:
bar.foo_set.all()

19. Example models
class Foo(models.Model):
name = models.CharField(max_length=10)
class Bar(models.Model):
name = models.CharField(max_length=10)
foo = models.ForeignKey(Foo)

20. Forwards relationship
>>> bar = Bar.objects.all()[0]
>>> bar.__dict__
{'id': 1, 'foo_id': 1, 'name': u'item1'}

21. Forwards relationship
>>> bar.foo.name
u'item1'
>>> bar.__dict__
{'_foo_cache': <Foo: Foo object>, 'id': 1,
'foo_id': 1, 'name': u'item1'}

22. Fowards relationships
• Relational access implemented via a
descriptor:
django.db.models.fields.related.
SingleRelatedObjectDescriptor
• __get__ tries to access _foo_cache
• If doesn't exist, does lookup and creates
cache

23. select_related
• Automatically follows foreign keys in SQL
query
• Prepopulates _foo_cache
• Doesn't follow null=True relationships by
default
• Makes query more expensive, so be sure
you need it

24. Backwards relationships
{% for foo in my_foos %}
{% for bar in foo.bar_set.all %}
{{ bar.name }}
{% endfor %}
{% endfor %}

25. Backwards relationships
• One query per foo
• If you iterate over foo_set again, you
generate a new set of db hits
• No _foo_cache
• select_related does not work here

26. Optimising backwards
relationships
• Get all related objects at once
• Sort by ID of parent object
• Then cache in hidden attribute as with
select_related

27. qs = Foo.objects.filter(criteria=whatever)
obj_dict = dict([(obj.id, obj)
for obj in qs])
objects = Bar.objects.filter(foo__in=qs)
relation_dict = {}
for obj in objects:
relation_dict.setdefault(
obj.foo_id, []).append(obj)
for id, related in relation_dict.items():
obj_dict[id]._related = related

28. qs = Foo.objects.filter(criteria=whatever)
obj_dict = dict([(obj.id, obj)
for obj in qs])
objects = Bar.objects.filter(foo__in=qs)
relation_dict = {}
for obj in objects:
relation_dict.setdefault(
obj.foo_id, []).append(obj)
for id, related in relation_dict.items():
obj_dict[id]._related = related

29. qs = Foo.objects.filter(criteria=whatever)
obj_dict = dict([(obj.id, obj)
for obj in qs])
objects = Bar.objects.filter(foo__in=qs)
relation_dict = {}
for obj in objects:
relation_dict.setdefault(
obj.foo_id, []).append(obj)
for id, related in relation_dict.items():
obj_dict[id]._related = related

30. qs = Foo.objects.filter(criteria=whatever)
obj_dict = dict([(obj.id, obj)
for obj in qs])
objects = Bar.objects.filter(foo__in=qs)
relation_dict = {}
for obj in objects:
relation_dict.setdefault(
obj.foo_id, []).append(obj)
for id, related in relation_dict.items():
obj_dict[id]._related = related

31. qs = Foo.objects.filter(criteria=whatever)
obj_dict = dict([(obj.id, obj)
for obj in qs])
objects = Bar.objects.filter(foo__in=qs)
relation_dict = {}
for obj in objects:
relation_dict.setdefault(
obj.foo_id, []).append(obj)
for id, related in relation_dict.items():
obj_dict[id]._related = related

32. qs = Foo.objects.filter(criteria=whatever)
obj_dict = dict([(obj.id, obj)
for obj in qs])
objects = Bar.objects.filter(foo__in=qs)
relation_dict = {}
for obj in objects:
relation_dict.setdefault(
obj.foo_id, []).append(obj)
for id, related in relation_dict.items():
obj_dict[id]._related = related

33. Optimising backwards
[{'time': '0.000', 'sql': u'SELECT
"foobar_foo"."id", "foobar_foo"."name" FROM
"foobar_foo"'},
{'time': '0.000', 'sql': u'SELECT
"foobar_bar"."id", "foobar_bar"."name",
"foobar_bar"."foo_id" FROM "foobar_bar"
WHERE "foobar_bar"."foo_id" IN (SELECT
U0."id" FROM "foobar_foo" U0)'}]

34. Optimising backwards
• Still quite expensive, as can mean large
dependent subquery – MySQL in particular
very bad at these
• But now just two queries instead of n
• Not automatic – need to remember to use
_related_items attribute

35. Generic relations
• Foreign key to ContentType, object_id
• Descriptor to enable direct access
• iterating through creates n+m
queries(n=number of source objects,
m=number of different content types)
• ContentType objects automatically cached
• Forwards relationship creates _foo_cache
• but select_related doesn't work

36. generics = {}
for item in queryset:
generics.setdefault(item.content_type_id,
set()).add(item.object_id)
content_types = ContentType.objects.in_bulk(
generics.keys())
relations = {}
for ct, fk_list in generics.items():
ct_model = content_types[ct].model_class()
relations[ct] = ct_model.objects.
in_bulk(list(fk_list))
for item in queryset:
setattr(item, '_content_object_cache',
relations[content_type_id][item.object_id]
)

37. generics = {}
for item in queryset:
generics.setdefault(item.content_type_id,
set()).add(item.object_id)
content_types = ContentType.objects.in_bulk(
generics.keys())
relations = {}
for ct, fk_list in generics.items():
ct_model = content_types[ct].model_class()
relations[ct] = ct_model.objects.
in_bulk(list(fk_list))
for item in queryset:
setattr(item, '_content_object_cache',
relations[content_type_id][item.object_id]
)

38. generics = {}
for item in queryset:
generics.setdefault(item.content_type_id,
set()).add(item.object_id)
content_types = ContentType.objects.in_bulk(
generics.keys())
relations = {}
for ct, fk_list in generics.items():
ct_model = content_types[ct].model_class()
relations[ct] = ct_model.objects.
in_bulk(list(fk_list))
for item in queryset:
setattr(item, '_content_object_cache',
relations[content_type_id][item.object_id]
)

39. generics = {}
for item in queryset:
generics.setdefault(item.content_type_id,
set()).add(item.object_id)
content_types = ContentType.objects.in_bulk(
generics.keys())
relations = {}
for ct, fk_list in generics.items():
ct_model = content_types[ct].model_class()
relations[ct] = ct_model.objects.
in_bulk(list(fk_list))
for item in queryset:
setattr(item, '_content_object_cache',
relations[content_type_id][item.object_id]
)

40. generics = {}
for item in queryset:
generics.setdefault(item.content_type_id,
set()).add(item.object_id)
content_types = ContentType.objects.in_bulk(
generics.keys())
relations = {}
for ct, fk_list in generics.items():
ct_model = content_types[ct].model_class()
relations[ct] = ct_model.objects.
in_bulk(list(fk_list))
for item in queryset:
setattr(item, '_content_object_cache',
relations[content_type_id][item.object_id]
)

41. generics = {}
for item in queryset:
generics.setdefault(item.content_type_id,
set()).add(item.object_id)
content_types = ContentType.objects.in_bulk(
generics.keys())
relations = {}
for ct, fk_list in generics.items():
ct_model = content_types[ct].model_class()
relations[ct] = ct_model.objects.
in_bulk(list(fk_list))
for item in queryset:
setattr(item, '_content_object_cache',
relations[content_type_id][item.object_id]
)

42. generics = {}
for item in queryset:
generics.setdefault(item.content_type_id,
set()).add(item.object_id)
content_types = ContentType.objects.in_bulk(
generics.keys())
relations = {}
for ct, fk_list in generics.items():
ct_model = content_types[ct].model_class()
relations[ct] = ct_model.objects.
in_bulk(list(fk_list))
for item in queryset:
setattr(item, '_content_object_cache',
relations[content_type_id][item.object_id]
)

43. generics = {}
for item in queryset:
generics.setdefault(item.content_type_id,
set()).add(item.object_id)
content_types = ContentType.objects.in_bulk(
generics.keys())
relations = {}
for ct, fk_list in generics.items():
ct_model = content_types[ct].model_class()
relations[ct] = ct_model.objects.
in_bulk(list(fk_list))
for item in queryset:
setattr(item, '_content_object_cache',
relations[content_type_id][item.object_id]
)

44. generics = {}
for item in queryset:
generics.setdefault(item.content_type_id,
set()).add(item.object_id)
content_types = ContentType.objects.in_bulk(
generics.keys())
relations = {}
for ct, fk_list in generics.items():
ct_model = content_types[ct].model_class()
relations[ct] = ct_model.objects.
in_bulk(list(fk_list))
for item in queryset:
setattr(item, '_content_object_cache',
relations[content_type_id][item.object_id]
)

45. Other optimising
techniques

46. Memoizing
• Cache property on first access
• Can cache within instance, if multiple
accesses within same request
def get_expensive_items(self):
if not hasattr(self, '_cache'):
self._cache = self.expensive_op()
return self._cache

47. DB Indexes
• Pay attention to slow query log and
debug toolbar output
• Add extra indexes where necessary -
especially for multiple-column lookup
• Use EXPLAIN

48. Outsourcing
• Does all the logic need to go in the web
app?
• Services - via eg Piston
• Message queues
• Distributed tasks, eg Celery

49. Summary
• Understand where queries are coming
from
• Optimise where necessary, within Django
or in the database
• and...

50. PROFILE

51. Daniel Roseman
http://blog.roseman.org.uk