Django2.0手册:Database access optimization

Django’s database layer provides various ways to help developers get the most
out of their databases. This document gathers together links to the relevant
documentation, and adds various tips, organized under a number of headings that
outline the steps to take when attempting to optimize your database usage.

Profile first¶

As general programming practice, this goes without saying. Find out what
queries you are doing and what they are costing you
. You may also want to use an external project like
django-debug-toolbar, or a tool that monitors your database directly.

Remember that you may be optimizing for speed or memory or both, depending on
your requirements. Sometimes optimizing for one will be detrimental to the
other, but sometimes they will help each other. Also, work that is done by the
database process might not have the same cost (to you) as the same amount of
work done in your Python process. It is up to you to decide what your
priorities are, where the balance must lie, and profile all of these as required
since this will depend on your application and server.

With everything that follows, remember to profile after every change to ensure
that the change is a benefit, and a big enough benefit given the decrease in
readability of your code. All of the suggestions below come with the caveat
that in your circumstances the general principle might not apply, or might even
be reversed.

Use standard DB optimization techniques¶


  • Indexes. This is a number one priority, after you have determined from
    profiling what indexes should be added. Use
    Field.db_index or
    Meta.index_together to add
    these from Django. Consider adding indexes to fields that you frequently
    query using filter(),
    order_by(), etc. as indexes may help
    to speed up lookups. Note that determining the best indexes is a complex
    database-dependent topic that will depend on your particular application.
    The overhead of maintaining an index may outweigh any gains in query speed.
  • Appropriate use of field types.

We will assume you have done the obvious things above. The rest of this document
focuses on how to use Django in such a way that you are not doing unnecessary
work. This document also does not address other optimization techniques that
apply to all expensive operations, such as general purpose caching.

Understand QuerySets¶

Understanding QuerySets is vital to getting good
performance with simple code. In particular:

Understand QuerySet evaluation¶

To avoid performance problems, it is important to understand:

Understand cached attributes¶

As well as caching of the whole QuerySet, there is caching of the result of
attributes on ORM objects. In general, attributes that are not callable will be
cached. For example, assuming the example Weblog models:

>>> entry = Entry.objects.get(id=1)
>>>   # Blog object is retrieved at this point
>>>   # cached version, no DB access

But in general, callable attributes cause DB lookups every time:

>>> entry = Entry.objects.get(id=1)
>>> entry.authors.all()   # query performed
>>> entry.authors.all()   # query performed again

Be careful when reading template code – the template system does not allow use
of parentheses, but will call callables automatically, hiding the above

Be careful with your own custom properties – it is up to you to implement
caching when required, for example using the
cached_property decorator.

Use the with template tag¶

To make use of the caching behavior of QuerySet, you may need to use the
with template tag.

Use iterator()¶

When you have a lot of objects, the caching behavior of the QuerySet can
cause a large amount of memory to be used. In this case,
iterator() may help.

Do database work in the database rather than in Python¶

For instance:

If these aren’t enough to generate the SQL you need:

Use RawSQL¶

A less portable but more powerful method is the
RawSQL expression, which allows some SQL
to be explicitly added to the query. If that still isn’t powerful enough:

Use raw SQL¶

Write your own custom SQL to retrieve data or populate models. Use django.db.connection.queries to find out what Django
is writing for you and start from there.

Retrieve individual objects using a unique, indexed column¶

There are two reasons to use a column with
unique or
db_index when using
get() to retrieve individual objects.
First, the query will be quicker because of the underlying database index.
Also, the query could run much slower if multiple objects match the lookup;
having a unique constraint on the column guarantees this will never happen.

So using the example Weblog models:

>>> entry = Entry.objects.get(id=10)

will be quicker than:

>>> entry = Entry.objects.get(headline="News Item Title")

because id is indexed by the database and is guaranteed to be unique.

Doing the following is potentially quite slow:

>>> entry = Entry.objects.get(headline__startswith="News")

First of all, headline is not indexed, which will make the underlying
database fetch slower.

Second, the lookup doesn’t guarantee that only one object will be returned.
If the query matches more than one object, it will retrieve and transfer all of
them from the database. This penalty could be substantial if hundreds or
thousands of records are returned. The penalty will be compounded if the
database lives on a separate server, where network overhead and latency also
play a factor.

Retrieve everything at once if you know you will need it¶

Hitting the database multiple times for different parts of a single ‘set’ of
data that you will need all parts of is, in general, less efficient than
retrieving it all in one query. This is particularly important if you have a
query that is executed in a loop, and could therefore end up doing many database
queries, when only one was needed. So:

Don’t retrieve things you don’t need¶

Use QuerySet.values() and values_list()¶

When you just want a dict or list of values, and don’t need ORM model
objects, make appropriate usage of
These can be useful for replacing model objects in template code – as long as
the dicts you supply have the same attributes as those used in the template,
you are fine.

使用 QuerySet.defer() 和 only()¶

Use defer() and
only() if there are database columns
you know that you won’t need (or won’t need in most cases) to avoid loading
them. Note that if you do use them, the ORM will have to go and get them in
a separate query, making this a pessimization if you use it inappropriately.

Also, be aware that there is some (small extra) overhead incurred inside
Django when constructing a model with deferred fields. Don’t be too aggressive
in deferring fields without profiling as the database has to read most of the
non-text, non-VARCHAR data from the disk for a single row in the results, even
if it ends up only using a few columns. The defer() and only() methods
are most useful when you can avoid loading a lot of text data or for fields
that might take a lot of processing to convert back to Python. As always,
profile first, then optimize.

使用 QuerySet.exists()¶

…if you only want the count, rather than doing len(queryset).

使用 QuerySet.exists()¶

…if you only want to find out if at least one result exists, rather than if


请不要过度使用 count() 和 exists()¶

If you are going to need other data from the QuerySet, just evaluate it.

For example, assuming an Email model that has a body attribute and a
many-to-many relation to User, the following template code is optimal:

{% if display_inbox %}
  {% with emails=user.emails.all %}
    {% if emails %}
      <p>You have {{ emails|length }} email(s)</p>
      {% for email in emails %}
        <p>{{ email.body }}</p>
      {% endfor %}
    {% else %}
      <p>No messages today.</p>
    {% endif %}
  {% endwith %}
{% endif %}

It is optimal because:

  1. Since QuerySets are lazy, this does no database queries if ‘display_inbox’
    is False.
  2. Use of with means that we store user.emails.all in a variable
    for later use, allowing its cache to be re-used.
  3. The line {% if emails %} causes QuerySet.__bool__() to be called,
    which causes the user.emails.all() query to be run on the database, and
    at the least the first line to be turned into an ORM object. If there aren’t
    any results, it will return False, otherwise True.
  4. The use of {{ emails|length }} calls QuerySet.__len__(), filling
    out the rest of the cache without doing another query.
  5. The for loop iterates over the already filled cache.

In total, this code does either one or zero database queries. The only
deliberate optimization performed is the use of the with tag. Using
QuerySet.exists() or QuerySet.count() at any point would cause
additional queries.

Use QuerySet.update() and delete()¶

Rather than retrieve a load of objects, set some values, and save them
individual, use a bulk SQL UPDATE statement, via QuerySet.update(). Similarly, do bulk deletes where possible.

Note, however, that these bulk update methods cannot call the save() or
delete() methods of individual instances, which means that any custom
behavior you have added for these methods will not be executed, including
anything driven from the normal database object signals.

Use foreign key values directly¶

If you only need a foreign key value, use the foreign key value that is already on
the object you’ve got, rather than getting the whole related object and taking
its primary key. i.e. do:



Don’t order results if you don’t care¶

Ordering is not free; each field to order by is an operation the database must
perform. If a model has a default ordering (Meta.ordering) and you don’t need it, remove
it on a QuerySet by calling
order_by() with no parameters.

Adding an index to your database may help to improve ordering performance.

Insert in bulk¶

When creating objects, where possible, use the
bulk_create() method to reduce the
number of SQL queries. For example:

    Entry(headline='This is a test'),
    Entry(headline='This is only a test'),

…is preferable to:

Entry.objects.create(headline='This is a test')
Entry.objects.create(headline='This is only a test')

Note that there are a number of caveats to this method, so make sure it’s appropriate
for your use case.

This also applies to ManyToManyFields, so doing:

my_band.members.add(me, my_friend)

…is preferable to:


…where Bands and Artists have a many-to-many relationship.