How to group by AND aggregate with Django - django

I have a fairly simple query I'd like to make via the ORM, but can't figure that out..
I have three models:
Location (a place), Attribute (an attribute a place might have), and Rating (a M2M 'through' model that also contains a score field)
I want to pick some important attributes and be able to rank my locations by those attributes - i.e. higher total score over all selected attributes = better.
I can use the following SQL to get what I want:
select location_id, sum(score)
from locations_rating
where attribute_id in (1,2,3)
group by location_id order by sum desc;
which returns
location_id | sum
-------------+-----
21 | 12
3 | 11
The closest I can get with the ORM is:
Rating.objects.filter(
attribute__in=attributes).annotate(
acount=Count('location')).aggregate(Sum('score'))
Which returns
{'score__sum': 23}
i.e. the sum of all, not grouped by location.
Any way around this? I could execute the SQL manually, but would rather go via the ORM to keep things consistent.
Thanks

Try this:
Rating.objects.filter(attribute__in=attributes) \
.values('location') \
.annotate(score = Sum('score')) \
.order_by('-score')

Can you try this.
Rating.objects.values('location_id').filter(attribute__in=attributes).annotate(sum_score=Sum('score')).order_by('-score')

Related

Doctrine 2 How to do a Sum from a Join but Group by 2 columns

I am using Symfony and Doctrine Querybuilder to return a list of Orders with a count of all Products in each Order. That means I have a 1:n Relationship between Orders and OrderProducts the OrderProducts table stores the OrderID, and the quantity of each product. If I do a groupBy o.orderId then I get the correct Sum, but then I do not get the data for all the orderProducts belonging to the orderId so if there are 2 different Products in the orderproducts table then I get qty:2 but only the data for 1 product, so I need to group by oi.orderProductId but obviously as soon I add the second groupBy oi.orderProductId then the TotalCount is showing me the sum for each individual record. I am fully aware that this is the correct behaviour, but I just can not get my head around it if there is a way to achieve what I am trying to do. I assume I have to somehow use a subselect, but I am not sure if this is even possible to achieve. My 2 tables and my attemped so far
tbl order
orderId
dateCreated
tblorderProducts
orderProductid
orderId
qty
return $this->createQueryBuilder('o')
->select(array(
'o AS orderData',
'oi',
'sum(oi.qty)AS noOfItems'))
->join('o.orderItems', 'oi')
->groupBy('o.orderId')
->groupBy('oi.orderProductId')
->getQuery()
->execute();
I hope somebody can give me a hint how I could achieve it. Thank you very much in advance.
The groupBy() method always replaces the current group by clause. Use addGroupBy() method instead.

Django get all values Group By particular one field

I want to execute a simple query like:
select *,count('id') from menu_permission group by menu_id
In Django format I have tried:
MenuPermission.objects.all().values('menu_id').annotate(Count('id))
It selects only menu_id. The executed query is:
SELECT `menu_permission`.`menu_id`, COUNT(`menu_permission`.`id`) AS `id__count` FROM `menu_permission` GROUP BY `menu_permission`.`menu_id`
But I need other fields also. If I try:
MenuPermission.objects.all().values('id','menu_id').annotate(Count('id))
It adds 'id' in group by condition.
GROUP BY `menu_permission`.`id`
As a result I am not getting the expected result. How I can get all all fields in the output but group by a single one?
You can try subqueries to do what you need.
In my case I have two tables: Item and Transaction where item_id links to Item
First, I prepare Transaction subquery with group by item_id where I sum all amount fields and mark item_id as pk for outer query.
per_item_total=Transaction.objects.values('item_id').annotate(total=Sum('amount')).filter(item_id=OuterRef('pk'))
Then I select all rows from item plus subquery result as total filed.
items_with_total=Item.objects.annotate(total=Subquery(per_item_total.values('total')))
This produces the following SQL:
SELECT `item`.`id`, {all other item fields},
(SELECT SUM(U0.`amount`) AS `total` FROM `transaction` U0
WHERE U0.`item_id` = `item`.`id` GROUP BY U0.`item_id` ORDER BY NULL) AS `total` FROM `item`
You are trying to achieve this SQL:
select *, count('id') from menu_permission group by menu_id
But normally SQL requires that when a group by clause is used you only include those column names in the select that you are grouping by. This is not a django matter, but that's how SQL group by works.
The rows are grouped by those columns so those columns can be included in select and other columns can be aggregated if you want them to into a value. You can't include other columns directly as they may have more than one value (since the rows are grouped).
For example if you have a column called "permission_code", you could ask for an array of the values in the "permission_code" column when the rows are grouped by menu_id.
Depending on the SQL flavor you are using, this could be in PostgreSQL something like this:
select menu_id, array_agg(permission_code), count(id) from menu_permissions group by menu_id
Similary django queryset can be constructed for this.
Hopefully this helps, but if needed please share more about what you need to do and what your data models are.
The only way currently that it works as expected is to hve your query based on the model you want the GROUP BY to be based on.
In your case it looks like you have a Menu model (menu_id field foreign key) so doing this would give you what you want and will allow getting other aggregate information from your MenuPermission model but will only group by the Menu.id field:
Menu.objects.annotate(perm_count=Count('menupermission__id')).values('perm_count')
Of course there is no need for the "annotate" intermediate step if all you want is that single count.
query = MenuPermission.objects.values('menu_id').annotate(menu_id_count=Count('menu_id'))
You can check your SQL query by print(query.query)
This solution doesn't work, all fields end up in the group by clause, leaving it here because it may still be useful to someone.
model_fields = queryset.model._meta.get_fields()
queryset = queryset.values('menu_id') \
.annotate(
count=Count('id'),
**{field.name: F(field.name) for field in model_fields}
)
What i'm doing is getting the list of fields of our model, and set up a dictionary with the field name as key and an F instance with the field name as a parameter.
When unpacked (the **) it gets interpreted as named arguments passed into the annotate function.
For example, if we had a "name" field on our model, this annotate call would end up being equal to this:
queryset = queryset.values('menu_id') \
.annotate(
count=Count('id'),
name=F("name")
)
you can use the following code:
MenuPermission.objects.values('menu_id').annotate(Count('id)).values('field1', 'field2', 'field3'...)

Django ORM: Select items where latest status is `success`

I have this model.
class Item(models.Model):
name=models.CharField(max_length=128)
An Item gets transferred several times. A transfer can be successful or not.
class TransferLog(models.Model):
item=models.ForeignKey(Item)
timestamp=models.DateTimeField()
success=models.BooleanField(default=False)
How can I query for all Items which latest TransferLog was successful?
With "latest" I mean ordered by timestamp.
TransferLog Table
Here is a data sample. Here item1 should not be included, since the last transfer was not successful:
ID|item_id|timestamp |success
---------------------------------------
1 | item1 |2014-11-15 12:00:00 | False
2 | item1 |2014-11-15 14:00:00 | True
3 | item1 |2014-11-15 16:00:00 | False
I know how to solve this with a loop in python, but I would like to do the query in the database.
An efficient trick is possible if timestamps in the log are increasing, that is the end of transfer is logged as timestamp (not the start of transfer) or if you can expect ar least that the older transfer has ended before a newer one started. Than you can use the TransferLog object with the highest id instead of with the highest timestamp.
from django.db.models import Max
qs = TransferLog.objects.filter(id__in=TransferLog.objects.values('item')
.annotate(max_id=Max('id')).values('max_id'), success=True)
It makes groups by item_id in the subquery and sends the highest id for every group to the main query, where it is filtered by success of the latest row in the group.
You can see that it is compiled to the optimal possible one query directly by Django.
Verified how compiled to SQL: print(qs.query.get_compiler('default').as_sql())
SELECT L.id, L.item_id, L.timestamp, L.success FROM app_transferlog L
WHERE L.success = true AND L.id IN
( SELECT MAX(U0.id) AS max_id FROM app_transferlog U0 GROUP BY U0.item_id )
(I edited the example result compiled SQL for better readability by replacing many "app_transferlog"."field" by a short alias L.field, by substituting the True parameter directly into SQL and by editing whitespace and parentheses.)
It can be improved by adding some example filter and by selecting the related Item in the same query:
kwargs = {} # e.g. filter: kwargs = {'timestamp__gte': ..., 'timestamp__lt':...}
qs = TransferLog.objects.filter(
id__in=TransferLog.objects.filter(**kwargs).values('item')
.annotate(max_id=Max('id')).values('max_id'),
success=True).select_related('item')
Verified how compiled to SQL: print(qs.query.get_compiler('default').as_sql()[0])
SELECT L.id, L.item_id, L.timestamp, L.success, I.id, I.name
FROM app_transferlog L INNER JOIN app_item I ON ( L.item_id = I.id )
WHERE L.success = %s AND L.id IN
( SELECT MAX(U0.id) AS max_id FROM app_transferlog U0
WHERE U0.timestamp >= %s AND U0.timestamp < %s
GROUP BY U0.item_id )
print(qs.query.get_compiler('default').as_sql()[1])
# result
(True, <timestamp_start>, <timestamp_end>)
Useful fields of latest TransferLog and the related Items are acquired by one query:
for logitem in qs:
item = logitem.item # the item is still cached in the logitem
...
The query can be more optimized according to circumstances, e.g. if you are not interested in the timestamp any more and you work with big data...
Without assumption of increasing timestamps it is really more complicated than a plain Django ORM. My solutions can be found here.
EDIT after it has been accepted:
An exact solution for a non increasing dataset is possible by two queries:
Get a set of id of the last failed transfers. (Used fail list, because it is much smaller small than the list of successful tranfers.)
Iterate over the list of all last transfers. Exclude items found in the list of failed transfers.
This way can be be efficiently simulated queries that would otherwise require a custom SQL:
SELECT a_boolean_field_or_expression,
rank() OVER (PARTITION BY parent_id ORDER BY the_maximized_field DESC)
FROM ...
WHERE rank = 1 GROUP BY parent_object_id
I'm thinking about implementing an aggregation function (e.g. Rank(maximized_field) ) as an extension for Django with PostgresQL, how it would be useful.
try this
# your query
items_with_good_translogs = Item.objects.filter(id__in=
(x.item.id for x in TransferLog.objects.filter(success=True))
since you said "How can I query for all Items which latest TransferLog was successful?", it is logically easy to follow if you start the query with Item model.
I used the Q Object which can be useful in places like this. (negation, or, ...)
(x.item.id for x in TransferLog.objects.filter(success=True)
gives a list of TransferLogs where success=True is true.
You will probably have an easier time approaching this from the ItemLog thusly:
dataset = ItemLog.objects.order_by('item','-timestamp').distinct('item')
Sadly that does not weed out the False items and I can't find a way to apply the filter AFTER the distinct. You can however filter it after the fact with python listcomprehension:
dataset = [d.item for d in dataset if d.success]
If you are doing this for logfiles within a given timeperiod it's best to filter that before ordering and distinct-ing:
dataset = ItemLog.objects.filter(
timestamp__gt=start,
timestamp__lt=end
).order_by(
'item','-timestamp'
).distinct('item')
If you can modify your models, I actually think you'll have an easier time using ManyToMany relationship instead of explicit ForeignKey -- Django has some built-in convenience methods that will make your querying easier. Docs on ManyToMany are here. I suggest the following model:
class TransferLog(models.Model):
item=models.ManyToManyField(Item)
timestamp=models.DateTimeField()
success=models.BooleanField(default=False)
Then you could do (I know, not a nice, single-line of code, but I'm trying to be explicit to be clearer):
results = []
for item in Item.objects.all():
if item.transferlog__set.all().order_by('-timestamp')[0].success:
results.append(item)
Then your results array will have all the items whose latest transfer was successful. I know, it's still a loop in Python...but perhaps a cleaner loop.

Using .extra() on fields created by .annotate() in Django

I want to retrieve a sum of two fields (which are aggregations themselves) for each object in a table.
The following may describe a bit better what I'm after but results in an Unknown column in field list-Error:
items = MyModel.objects.annotate(
field1=Sum("relatedModel__someField"),
field2=Sum("relatedModel__someField")).extra(
select={"sum_field1_field2": "field1 + field2"})
I also tried using F() for the field lookups but that gives me an invalid sql statement.
Any ideas on how to solve this are much appreciated.
it this what you want?
items = MyModel.objects.extra(
select = {'sum_field1_field2': 'SUM(relatedModel__someField) + SUM(relatedModel__someField)'},
)
To make it work for many to many or for many to one (reverse) relations, you may use the following:
items = MyModel.objects.extra(
select = {'sum_field1_field2': 'SUM("relatedModel"."someField") + SUM("relatedModel"."someField")'},
)
But this will break also if you need another annotate, like for a count, because extra will add the statement to the GROUP BY clause, whereas aggregate functions are not allowed in there.

How do I get the related objects In an extra().values() call in Django?

Thank to this post I'm able to easily do count and group by queries in a Django view:
Django equivalent for count and group by
What I'm doing in my app is displaying a list of coin types and face values available in my database for a country, so coins from the UK might have a face value of "1 farthing" or "6 pence". The face_value is the 6, the currency_type is the "pence", stored in a related table.
I have the following code in my view that gets me 90% of the way there:
def coins_by_country(request, country_name):
country = Country.objects.get(name=country_name)
coin_values = Collectible.objects.filter(country=country.id, type=1).extra(select={'count': 'count(1)'},
order_by=['-count']).values('count', 'face_value', 'currency_type')
coin_values.query.group_by = ['currency_type_id', 'face_value']
return render_to_response('icollectit/coins_by_country.html', {'coin_values': coin_values, 'country': country } )
The currency_type_id comes across as the number stored in the foreign key field (i.e. 4). What I want to do is retrieve the actual object that it references as part of the query (the Currency model, so I can get the Currency.name field in my template).
What's the best way to do that?
You can't do it with values(). But there's no need to use that - you can just get the actual Collectible objects, and each one will have a currency_type attribute that will be the relevant linked object.
And as justinhamade suggests, using select_related() will help to cut down the number of database queries.
Putting it together, you get:
coin_values = Collectible.objects.filter(country=country.id,
type=1).extra(
select={'count': 'count(1)'},
order_by=['-count']
).select_related()
select_related() got me pretty close, but it wanted me to add every field that I've selected to the group_by clause.
So I tried appending values() after the select_related(). No go. Then I tried various permutations of each in different positions of the query. Close, but not quite.
I ended up "wimping out" and just using raw SQL, since I already knew how to write the SQL query.
def coins_by_country(request, country_name):
country = get_object_or_404(Country, name=country_name)
cursor = connection.cursor()
cursor.execute('SELECT count(*), face_value, collection_currency.name FROM collection_collectible, collection_currency WHERE collection_collectible.currency_type_id = collection_currency.id AND country_id=%s AND type=1 group by face_value, collection_currency.name', [country.id] )
coin_values = cursor.fetchall()
return render_to_response('icollectit/coins_by_country.html', {'coin_values': coin_values, 'country': country } )
If there's a way to phrase that exact query in the Django queryset language I'd be curious to know. I imagine that an SQL join with a count and grouping by two columns isn't super-rare, so I'd be surprised if there wasn't a clean way.
Have you tried select_related() http://docs.djangoproject.com/en/dev/ref/models/querysets/#id4
I use it a lot it seems to work well then you can go coin_values.currency.name.
Also I dont think you need to do country=country.id in your filter, just country=country but I am not sure what difference that makes other than less typing.