I would like to write the following query in Postgresql using Django ORM:
SELECT t.id, t.field1 FROM mytable t JOIN ... JOIN ... WHERE .... GROUP BY id
Note that there is NO aggregate function (like SUM, COUNT etc.) in the SELECT part.
By the way, it's a perfectly legal SQL to GROUP BY primary key only in Postgresql.
How do I write it in Django ORM?
I saw workarounds like adding .annotate(dummy=Count('*')) to the queryset (but it slows down the execution) or introducing a dummy custom aggregate function (but it's a dirty hack). How to do it in a clean way?
I need to fetch the top performer for each month, here is the below MySql query which gives me the correct output.
select id,Name,totalPoints, createdDateTime
from userdetail
where app=4 and totalPoints in ( select
max(totalPoints)
FROM userdetail
where app=4
group by month(createdDateTime), year(createdDateTime))
order by totalPoints desc
I am new to Django ORM. I am not able to write an equivalent Django query which does the task. I have been struggling with this logic for 2 days. Any help would be highly appreciated.
While the GROUP BY clause in a subquery is slightly difficult to express with the ORM because aggregate() operations don't emit querysets, a similar effect can be achieved with a Window function:
UserDetail.objects.filter(total_points__in=UserDetail.objects.annotate(max_points=Window(
expression=Max('total_points'),
partition_by=[Trunc('created_datetime', 'month')]
)).values('max_points')
)
In general, this sort of pattern is implemented with Subquery expressions. In this case, I've implicitly used a subquery by passing a queryset to an __in predicate.
The Django documentation's notes on using aggregates within subqueries is are also relevant to this sort of query, since you want to use the results of an aggregate in a subquery (which I've avoided by using a window function).
However, I believe your query may not correctly capture what you want to do: as written it could return rows for users who weren't the best in a given month but did have the same score as another user who was the best in any month.
This is a bleeding-edge feature that I'm currently skewered upon and quickly bleeding out. I want to annotate a subquery-aggregate onto an existing queryset. Doing this before 1.11 either meant custom SQL or hammering the database. Here's the documentation for this, and the example from it:
from django.db.models import OuterRef, Subquery, Sum
comments = Comment.objects.filter(post=OuterRef('pk')).values('post')
total_comments = comments.annotate(total=Sum('length')).values('total')
Post.objects.filter(length__gt=Subquery(total_comments))
They're annotating on the aggregate, which seems weird to me, but whatever.
I'm struggling with this so I'm boiling it right back to the simplest real-world example I have data for. I have Carparks which contain many Spaces. Use Book→Author if that makes you happier but —for now— I just want to annotate on a count of the related model using Subquery*.
spaces = Space.objects.filter(carpark=OuterRef('pk')).values('carpark')
count_spaces = spaces.annotate(c=Count('*')).values('c')
Carpark.objects.annotate(space_count=Subquery(count_spaces))
This gives me a lovely ProgrammingError: more than one row returned by a subquery used as an expression and in my head, this error makes perfect sense. The subquery is returning a list of spaces with the annotated-on total.
The example suggested that some sort of magic would happen and I'd end up with a number I could use. But that's not happening here? How do I annotate on aggregate Subquery data?
Hmm, something's being added to my query's SQL...
I built a new Carpark/Space model and it worked. So the next step is working out what's poisoning my SQL. On Laurent's advice, I took a look at the SQL and tried to make it more like the version they posted in their answer. And this is where I found the real problem:
SELECT "bookings_carpark".*, (SELECT COUNT(U0."id") AS "c"
FROM "bookings_space" U0
WHERE U0."carpark_id" = ("bookings_carpark"."id")
GROUP BY U0."carpark_id", U0."space"
)
AS "space_count" FROM "bookings_carpark";
I've highlighted it but it's that subquery's GROUP BY ... U0."space". It's retuning both for some reason. Investigations continue.
Edit 2: Okay, just looking at the subquery SQL I can see that second group by coming through ☹
In [12]: print(Space.objects_standard.filter().values('carpark').annotate(c=Count('*')).values('c').query)
SELECT COUNT(*) AS "c" FROM "bookings_space" GROUP BY "bookings_space"."carpark_id", "bookings_space"."space" ORDER BY "bookings_space"."carpark_id" ASC, "bookings_space"."space" ASC
Edit 3: Okay! Both these models have sort orders. These are being carried through to the subquery. It's these orders that are bloating out my query and breaking it.
I guess this might be a bug in Django but short of removing the Meta-order_by on both these models, is there any way I can unsort a query at querytime?
*I know I could just annotate a Count for this example. My real purpose for using this is a much more complex filter-count but I can't even get this working.
Shazaam! Per my edits, an additional column was being output from my subquery. This was to facilitate ordering (which just isn't required in a COUNT).
I just needed to remove the prescribed meta-order from the model. You can do this by just adding an empty .order_by() to the subquery. In my code terms that meant:
from django.db.models import Count, OuterRef, Subquery
spaces = Space.objects.filter(carpark=OuterRef('pk')).order_by().values('carpark')
count_spaces = spaces.annotate(c=Count('*')).values('c')
Carpark.objects.annotate(space_count=Subquery(count_spaces))
And that works. Superbly. So annoying.
It's also possible to create a subclass of Subquery, that changes the SQL it outputs. For instance, you can use:
class SQCount(Subquery):
template = "(SELECT count(*) FROM (%(subquery)s) _count)"
output_field = models.IntegerField()
You then use this as you would the original Subquery class:
spaces = Space.objects.filter(carpark=OuterRef('pk')).values('pk')
Carpark.objects.annotate(space_count=SQCount(spaces))
You can use this trick (at least in postgres) with a range of aggregating functions: I often use it to build up an array of values, or sum them.
I just bumped into a VERY similar case, where I had to get seat reservations for events where the reservation status is not cancelled. After trying to figure the problem out for hours, here's what I've seen as the root cause of the problem:
Preface: this is MariaDB, Django 1.11.
When you annotate a query, it gets a GROUP BY clause with the fields you select (basically what's in your values() query selection). After investigating with the MariaDB command line tool why I'm getting NULLs or Nones on the query results, I've came to the conclusion that the GROUP BY clause will cause the COUNT() to return NULLs.
Then, I started diving into the QuerySet interface to see how can I manually, forcibly remove the GROUP BY from the DB queries, and came up with the following code:
from django.db.models.fields import PositiveIntegerField
reserved_seats_qs = SeatReservation.objects.filter(
performance=OuterRef(name='pk'), status__in=TAKEN_TYPES
).values('id').annotate(
count=Count('id')).values('count')
# Query workaround: remove GROUP BY from subquery. Test this
# vigorously!
reserved_seats_qs.query.group_by = []
performances_qs = Performance.objects.annotate(
reserved_seats=Subquery(
queryset=reserved_seats_qs,
output_field=PositiveIntegerField()))
print(performances_qs[0].reserved_seats)
So basically, you have to manually remove/update the group_by field on the subquery's queryset in order for it to not have a GROUP BY appended on it on execution time. Also, you'll have to specify what output field the subquery will have, as it seems that Django fails to recognize it automatically, and raises exceptions on the first evaluation of the queryset. Interestingly, the second evaluation succeeds without it.
I believe this is a Django bug, or an inefficiency in subqueries. I'll create a bug report about it.
Edit: the bug report is here.
Problem
The problem is that Django adds GROUP BY as soon as it sees using an aggregate function.
Solution
So you can just create your own aggregate function but so that Django thinks it is not aggregate. Just like this:
total_comments = Comment.objects.filter(
post=OuterRef('pk')
).order_by().annotate(
total=Func(F('length'), function='SUM')
).values('total')
Post.objects.filter(length__gt=Subquery(total_comments))
This way you get the SQL query like this:
SELECT "testapp_post"."id", "testapp_post"."length"
FROM "testapp_post"
WHERE "testapp_post"."length" > (SELECT SUM(U0."length") AS "total"
FROM "testapp_comment" U0
WHERE U0."post_id" = "testapp_post"."id")
So you can even use aggregate subqueries in aggregate functions.
Example
You can count the number of workdays between two dates, excluding weekends and holidays, and aggregate and summarize them by employee:
class NonWorkDay(models.Model):
date = DateField()
class WorkPeriod(models.Model):
employee = models.ForeignKey(User, on_delete=models.CASCADE)
start_date = DateField()
end_date = DateField()
number_of_non_work_days = NonWorkDay.objects.filter(
date__gte=OuterRef('start_date'),
date__lte=OuterRef('end_date'),
).annotate(
cnt=Func('id', function='COUNT')
).values('cnt')
WorkPeriod.objects.values('employee').order_by().annotate(
number_of_word_days=Sum(F('end_date__year') - F('start_date__year') - number_of_non_work_days)
)
Hope this will help!
A solution which would work for any general aggregation could be implemented using Window classes from Django 2.0. I have added this to the Django tracker ticket as well.
This allows the aggregation of annotated values by calculating the aggregate over partitions based on the outer query model (in the GROUP BY clause), then annotating that data to every row in the subquery queryset. The subquery can then use the aggregated data from the first row returned and ignore the other rows.
Performance.objects.annotate(
reserved_seats=Subquery(
SeatReservation.objects.filter(
performance=OuterRef(name='pk'),
status__in=TAKEN_TYPES,
).annotate(
reserved_seat_count=Window(
expression=Count('pk'),
partition_by=[F('performance')]
),
).values('reserved_seat_count')[:1],
output_field=FloatField()
)
)
If I understand correctly, you are trying to count Spaces available in a Carpark. Subquery seems overkill for this, the good old annotate alone should do the trick:
Carpark.objects.annotate(Count('spaces'))
This will include a spaces__count value in your results.
OK, I have seen your note...
I was also able to run your same query with other models I had at hand. The results are the same, so the query in your example seems to be OK (tested with Django 1.11b1):
activities = Activity.objects.filter(event=OuterRef('pk')).values('event')
count_activities = activities.annotate(c=Count('*')).values('c')
Event.objects.annotate(spaces__count=Subquery(count_activities))
Maybe your "simplest real-world example" is too simple... can you share the models or other information?
"works for me" doesn't help very much. But.
I tried your example on some models I had handy (the Book -> Author type), it works fine for me in django 1.11b1.
Are you sure you're running this in the right version of Django? Is this the actual code you're running? Are you actually testing this not on carpark but some more complex model?
Maybe try to print(thequery.query) to see what SQL it's trying to run in the database. Below is what I got with my models (edited to fit your question):
SELECT (SELECT COUNT(U0."id") AS "c"
FROM "carparks_spaces" U0
WHERE U0."carpark_id" = ("carparks_carpark"."id")
GROUP BY U0."carpark_id") AS "space_count" FROM "carparks_carpark"
Not really an answer, but hopefully it helps.
In one of the django apps we use two database engine A and B, both are the same database but with different schemas. We have a table called C in both schemas but using db routing it's always made to point to database B. We have formed a valuelist queryset from one of the models in A, tried to pass the same in table C using filter condition __in but it always fetches empty though there are matching records. When we convert valueslist queryset to a list and use it in table C using filter condition __in it works fine.
Not working
data = modelindbA.objects.values_list('somecolumn',flat=True)
info = C.objects.filter(somecolumn__in=data).values_list
Working
data = modelindbA.objects.values_list('somecolumn',flat=True)
data = list(data)
info = C.objects.filter(somecolumn__in=data).values_list
I have read django docs and other SO questions, couldn't find anything relative. My guess is that since both models are in different database schemas the above is not working. I need assistance on how to troubleshoot this issue.
When you use a queryset with __in, Django will construct a single SQL query that uses a subquery for the __in clause. Since the two tables are in different databases, no rows will match.
By contrast, if you convert the first queryset to a list, Django will go ahead and fetch the data from the first database. When you then pass that data to the second query, hitting the second database, it will work as expected.
See the documentation for the in field lookup for more details:
You can also use a queryset to dynamically evaluate the list of values instead of providing a list of literal values.... This queryset will be evaluated as subselect statement:
SELECT ... WHERE blog.id IN (SELECT id FROM ... WHERE NAME LIKE '%Cheddar%')
Because values_list method returns django.db.models.query.QuerySet, not a list.
When you use it with same schema the orm optimise it and should make just one query, but when schemas are different it fails.
Just use list().
I would even recommend to use it for one schema since it can decrease complexity of query and work better on big tables.
Is it possible to prevent multiple querys when i use django ORM ? Example:
product = Product.objects.get(name="Banana")
for provider in product.providers.all():
print provider.name
This code will make 2 SQL querys:
1 - SELECT ••• FROM stock_product WHERE stock_product.name = 'Banana'
2 - SELECT stock_provider.id, stock_provider.name FROM stock_provider INNER JOIN stock_product_reference ON (stock_provider.id = stock_product_reference.provider_id) WHERE stock_product_reference.product_id = 1
I confess, i use Doctrine (PHP) for some projects. With doctrine it's possible to specify joins when retrieve the object (relations are populated in object, so no need to query database again for get attribute relation value).
Is it possible to do the same with Django's ORM ?
PS: I hop my question is comprehensive, english is not my primary language.
In Django 1.4 or later, you can use prefetch_related. It's like select_related but allows M2M relations and such.
product = Product.objects.prefetch_related('providers').get(name="Banana")
You still get two queries, though. From the docs:
prefetch_related, on the other hand, does a separate lookup for each relationship, and does the ‘joining’ in Python.
As for packing this down into a single query, Django won't do it like Doctrine because it doesn't do that much post-processing of the result set (Django would have to remove all the redundant column data, since you'll get a row per provider and each of these rows will have a copy of all of product's fields).
So if you want to pack this down to one query, you're going to have to turn it around and run the query on the Provider table (I'm guessing at your schema):
providers = Provider.objects.filter(product__name="Banana").select_related('product')
This should pack it down to one query, but you won't get a single product ORM object out of it, instead needing to get the product fields via providers[k].product.
You can use prefetch_related, sometimes in combination with select_related, to get all related objects in a single query: https://docs.djangoproject.com/en/1.5/ref/models/querysets/#prefetch-related