Allow adding joins to other querysets (or models) to a queryset with extra join conditions

[Debanshu Kundu]

In one of our project we had a need to join our sub-queries to our main query. As Django ORM doesn't support this we had to write SQL queries. But after some time those SQL queries became difficult to maintain and our project was under active development and we were doing additions/changes to models and query logic.

So we started to look for alternatives and found some ways to hack Django ORM using which we can add joins to queryset. I have created this gist with utility functions and related helper code which are we using to add join to another queryset (or model) to a queryset: ​https://gist.github.com/debanshuk/6fd9398cff0fab59e7093fe98b8a9152.

These functions are named join_to_queryset() and join_to_table() respectively. They also allow adding extra conditions to the join added by them using get_active_extra_restriction() helper function.

Following is an example showing use of join_to_queryset() function:

class Snake(models.Model):
    name = models.TextField()
    age = models.PositiveIntegerField()
    length = models.FloatField()
    sex = models.TextField()

class Egg(models.Model):
    snake = models.ForeignKey(Snake)

class Kill(models.Model):
    snake = models.ForeignKey(Snake)

queryset = Snake.objects.filter(pk__in=snake_pks)

queryset = join_to_queryset(
    table=Snake,
    subquery=Egg.objects.values('snake').annotate(egg_count=Count('pk')),
    table_field='id',
    subquery_field='snake_id',
    queryset=queryset,
    alias='SnakeEggAggr'
).extra(select={'egg_count': 'SnakeEggAggr.egg_count'})

queryset = join_to_queryset(
    table=Snake,
    subquery=Kill.objects.values('snake').annotate(kill_count=Count('pk')),
    table_field='id',
    subquery_field='snake_id',
    queryset=queryset,
    alias='SnakeKillAggr'
).extra(select={'kill_count': 'SnakeKillAggr.kill_count'})

print queryset.values('name', 'age', 'length', 'sex', 'egg_count', 'kill_count')

Output of above code would be something like:

[{'name': 'John', 'age': 5, 'length': 20.1, 'sex': 'male', 'egg_count': 10, 'kill_count': 5}, {'name': 'Jane', 'age': 8, 'length': 25.5, 'sex': 'female', 'egg_count': 5, 'kill_count': 1}, {'name': 'Jack', 'age': 2, 'length': 10.2, 'sex': 'hermaphrodite', 'egg_count': 0, 'kill_count': 0}]

Above result can also be obtained by doing following query:

print Snake.objects.filter(pk__in=snake_pks).annotate(egg_count=Count('egg__id'), kill_count=Count('kill__id')).values('name', 'age', 'length', 'sex', 'egg_count', 'kill_count''egg_count', 'kill_count')

But this query will take more time to execute than previous one as 'name', 'age', 'length' and 'sex' all four fields would be in the GROUP BY clause of SQL query and the time will increase more and more as the number of such fields increases (this is the vary reason due to which we had to use sub-queries for aggreagation).

It would be nice if such functionality can be added to the Django ORM itself. It seems doable to as we were able to hack the ORM to do the same.

[Tim Graham]

Duplicate of #26426 and/or #27332? If not, perhaps you can make a more specific API you're proposal.

[Debanshu Kundu]

@Tim, As I understood #27332 and #26426 both are only about specifying extra conditions in a join, which is a part of this ticket but isn't the main feature. The main feature here is to be able to join to sub-queries. The example query (using join_to_queryset() function) stated in the ticket will look something like following query in SQL:

SELECT name, age, length, sex, SnakeKillAggr.egg_count AS egg_count, SnakeKillAggr.kill_count AS kill_count
FROM snakes_snake
LEFT OUTER JOIN (
    SELECT snake_id, COUNT(id) AS egg_count
    FROM snakes_egg
    GROUP BY snake_id
) AS SnakeEggAggr ON (snakes_snake.id = SnakeEggAggr.snake_id)
LEFT OUTER JOIN (
    SELECT snake_id, COUNT(id) AS kill_count
    FROM snakes_kill
    GROUP BY snake_id
) AS SnakeKillAggr ON (snakes_snake.id = SnakeKillAggr.snake_id)

And if we want to add an extra condition in the second join such that a snake's kill count is only included if it's greater than it's age, we can do it as follows:

queryset = join_to_queryset(
    table=Snake,
    subquery=Kill.objects.values('snake').annotate(kill_count=Count('pk')),
    table_field='id',
    subquery_field='snake_id',
    queryset=queryset,
    alias='SnakeKillAggr',
    extra_restriction_func=lambda where_class, alias, related_alias: (
        where_class([ExtraWhere([f'{alias}.kill_count > {related_alias}.age'], ())])
    )
).extra(select={'kill_count': 'SnakeKillAggr.kill_count'})

About example code's API is not very clean as it was just a hack to make things work at the time, but it can be cleaned up and made a proper API. Following can be the API:

join_to_queryset() method for queryset with following arguments:

base_queryset_field: Field of base queryset which will be used in primary join condition.
subqueryset: Sub-queryset to join to.
subqueryset_field: Field of base sub-queryset which will be used in primary join condition.
extra_restrictions: List of extra restriction for the join (format of an object in this list needs to be decided).

And join_to_model() method for model with following argumets:

base_queryset_field: Field of base queryset which will be used in primary join condition.
model: Model to join to.
model_field: Field of base model which will be used in primary join condition.
extra_restrictions: List of extra restriction for the join (format of an object in this list needs to be decided).

So the example in the ticket will look something like (format of extra_restrictions needs to be decided):

queryset = queryset.join_to_queryset(
    base_queryset_field='id', subqueryset=Kill.objects.values('snake').annotate(kill_count=Count('pk')),
    subqueryset_field='snake_id',
    extra_restrictions=['{subqueryset}.kill_count > {base_queryset}.age']
)