I have a queryset that returns a lot of data, it can be filtered by year which will return around 100k lines, or show all which will bring around 1 million lines.
The objective of this annotate is to generate a xlsx spreadsheet.
Models representation, RelatedModel is manytomany between Model and AnotherModel
Model:
id
field1
field2
field3
RelatedModel:
foreign_key_model (Model)
foreign_key_another (AnotherModel)
Queryset, if the relation exists it will annotate, this annotate is very slow and can take several minutes.
Model.objects.all().annotate(
related_exists=Exists(RelatedModel.objects.filter(foreign_key_model=OuterRef('id'))),
related_column=Case(
When(related_exists=True, then=Value('The relation exists!')),
When(related_exists=False, then=Value('The relation doesn't exist!')),
default=Value('This is the default value!'),
output_field=CharField(),
)
).values_list(
'related_column',
'field1',
'field2',
'field3'
)
If only thing needed is to change how True / False is displayed in xlsx - one option is to just have one related_exists BooleanField annotation and later customize how it will be converted when creating xlsx document - i.e. in serializer. Database should store raw / unformatted values, and app prepare them to be shown to user.
Other things to consider:
Indexes to speed-up filtering.
If you have millions of records after filtering, in one table - maybe table partitioning could be considered.
But let's look into raw sql of original query. It will be like this:
SELECT [model_fields],
EXISTS([CLIENT_SELECT]) AS related_exists,
CASE
WHEN EXISTS([CLIENT_SELECT]) = true THEN 'The relation exists!'
WHEN EXISTS([CLIENT_SELECT]) = true THEN 'The relation does not exist!'
ELSE 'The relation exists!'
END AS related_column
FROM model;
And right away we can see nested query for Exists CLIENT_SELECT is there 3 times. Even though it is exactly the same, it may be executed minimum 2 times and up to 3 times. Database may optimize it to be faster than 3x, but it still is not optimal as 1x.
First, EXISTS returns either True or False, we can leave just one check that it is True, making 'The relation does not exist!' the default value.
related_column=Case(
When(related_exists=True, then=Value('The relation exists!')),
default=Value('The relation does not exist!')
Why related_column performs same select again and not takes the value of related_exists?
Because we cannot reference calculated columns while calculating another columns - and this is database level constraint django knows about and duplicates expression.
Wait, then we actually do not need related_exists column, lets just leave related_column with CASE statement and 1 exists subquery.
Here comes Django - we cannot (till 3.0) use expressions in filters without annotating them first.
So, it our case it is like: in order to use Exist in When, we first need to add it as annotation, but it won't be used as a reference, but a full copy of expression.
Good news!
Since Django 3.0 we can use expressions that output BooleanField directly in QuerySet filters, without having to first annotate. Exists is one of such BooleaField expressions.
Model.objects.all().annotate(
related_column=Case(
When(
Exists(RelatedModel.objects.filter(foreign_key_model=OuterRef('id'))),
then=Value('The relation exists!'),
),
default=Value('The relation doesn't exist!'),
output_field=CharField(),
)
)
And only one nested select, and one annotated field.
Django 2.1, 2.2
Here's the commit that finalized allowance of boolean expressions although many pre-conditions for it were added earlier. One of them is presence of conditional attribute on expression object and check for this attribute.
So, although not recommended and not tested it seems quite working little hack for Django 2.1, 2.2 (before there was no conditional check, and it will require more intrusive changes):
create Exists expression instance
monkey patch it with conditional = True
use it as condition in When statement
related_model_exists = Exists(RelatedModel.objects.filter(foreign_key_model=OuterRef('id')))
setattr(related_model_exists, 'conditional', True)
Model.objects.all().annotate(
related_column=Case(
When(
relate_model_exists,
then=Value('The relation exists!'),
),
default=Value('The relation doesn't exist!'),
output_field=CharField(),
)
)
Related checks
relatedmodel_set__isnull=True check is not suitable for several reasons:
it performs LEFT OUTER JOIN - that is less efficient than EXISTS
it performs LEFT OUTER JOIN - it joins tables, this makes it ONLY suitable in filter() condition (not in annotate - When), and only for OneToOne or OneToMany (One is on relatedmodel side) relations
You can considerably simplify your query to:
from django.db.models import Count
Model.objects.all().annotate(
related_column=Case(
When(relatedmodel_set__isnull=True, then=Value("The relation doesn't exist!")),
default=Value("The relation exists!"),
output_field=CharField()
)
)
Where relatedmodel_set is the related_name on your foreign key.
Related
I have a filter which should return a queryset with 2 objects, and should have one different field. for example:
obj_1 = (name='John', age='23', is_fielder=True)
obj_2 = (name='John', age='23', is_fielder=False)
Both the objects are of same model, but different primary key. I tried usign the below filter:
qs = Model.objects.filter(name='John', age='23').annotate(is_fielder=F('plays__outdoor_game_role')=='Fielder')
I used annotate first time, but it gave me the below error:
TypeError: QuerySet.annotate() received non-expression(s): False.
I am new to Django, so what am I doing wrong, and what should be the annotate to get the required objects as shown above?
The solution by #ktowen works well, quite straightforward.
Here is another solution I am using, hope it is helpful too.
queryset = queryset.annotate(is_fielder=ExpressionWrapper(
Q(plays__outdoor_game_role='Fielder'),
output_field=BooleanField(),
),)
Here are some explanations for those who are not familiar with Django ORM:
Annotate make a new column/field on the fly, in this case, is_fielder. This means you do not have a field named is_fielder in your model while you can use it like plays.outdor_game_role.is_fielder after you add this 'annotation'. Annotate is extremely useful and flexible, can be combined with almost every other expression, should be a MUST-KNOWN method in Django ORM.
ExpressionWrapper basically gives you space to wrap a more complecated combination of conditions, use in a format like ExpressionWrapper(expression, output_field). It is useful when you are combining different types of fields or want to specify an output type since Django cannot tell automatically.
Q object is a frequently used expression to specify a condition, I think the most powerful part is that it is possible to chain the conditions:
AND (&): filter(Q(condition1) & Q(condition2))
OR (|): filter(Q(condition1) | Q(condition2))
Negative(~): filter(~Q(condition))
It is possible to use Q with normal conditions like below:
(Q(condition1)|id__in=[list])
The point is Q object must come to the first or it will not work.
Case When(then) can be simply explained as if con1 elif con2 elif con3 .... It is quite powerful and personally, I love to use this to customize an ordering object for a queryset.
For example, you need to return a queryset of watch history items, and those must be in an order of watching by the user. You can do it with for loop to keep the order but this will generate plenty of similar queries. A more elegant way with Case When would be:
item_ids = [list]
ordering = Case(*[When(pk=pk, then=pos)
for pos, pk in enumerate(item_ids)])
watch_history = Item.objects.filter(id__in=item_ids)\
.order_by(ordering)
As you can see, by using Case When(then) it is possible to bind those very concrete relations, which could be considered as 1) a pinpoint/precise condition expression and 2) especially useful in a sequential multiple conditions case.
You can use Case/When with annotate
from django.db.models import Case, BooleanField, Value, When
Model.objects.filter(name='John', age='23').annotate(
is_fielder=Case(
When(plays__outdoor_game_role='Fielder', then=Value(True)),
default=Value(False),
output_field=BooleanField(),
),
)
I have a queryset like this:
predicts = Prediction.objects.select_related('match').filter(match_id=pk)
I need to annotate this with a new field is_correct. I need to compare two string fields and the result should be annotated in this new field. the fields that I want to compare are:
predict from Prediction table
result from Match table (that has been joined through select_related)
I need to know what expression should I put inside my annotate function; below I have my current code which throughs a TypeError exception:
predicts = predicts.annotate(is_correct=(F('predict') == F('result')))
all help will be greatly appreciated.
UPDATE:
I found an alternative solution that does the job for me (filtering the Prediction based on Match result using filter and exclude), but I still like to know how to address this specific case where the new annotated field is the result of the comparison between two other fields of the queryset. For those who may need it, in Django 2.2 and later the Nullif database function does a comparison between two fields.
You can use the extra function, a hook for injecting specific clauses into the SQL.
First of all, we must know the names of the apps and the models, or the name of the tables in the database.
Assuming that in your case, the two tables are called "app_prediction" and "app_match".
The sentence would be as follows:
Prediction.objects.select_related('match').extra(
select={'is_correct': "app_prediction.predict = app_match.result"}
)
This will add a field called is_correct in your result,
in the database, the fields and tables must be called in the same way.
It would be best to see the models.
Django 1.10.6
Asset.objects.annotate(
coupon_saved=Count(
Q(coupons__device_id='8ae83c6fa52765061360f5459025cb85e6dc8905')
)
).all().query
produces the following query:
SELECT
"assets_asset"."id",
"assets_asset"."title",
"assets_asset"."description",
"assets_asset"."created",
"assets_asset"."modified",
"assets_asset"."uid",
"assets_asset"."org_id",
"assets_asset"."subtitle",
"assets_asset"."is_active",
"assets_asset"."is_generic",
"assets_asset"."file_standalone",
"assets_asset"."file_ios",
"assets_asset"."file_android",
"assets_asset"."file_preview",
"assets_asset"."json_metadata",
"assets_asset"."file_icon",
"assets_asset"."file_image",
"assets_asset"."video_mobile",
"assets_asset"."video_standalone",
"assets_asset"."file_coupon",
"assets_asset"."where_to_buy",
COUNT("games_coupon"."device_id" = 8ae83c6fa52765061360f5459025cb85e6dc8905) AS "coupon_saved"
FROM
"assets_asset"
LEFT OUTER JOIN
"games_coupon"
ON ("assets_asset"."id" = "games_coupon"."asset_id")
GROUP BY
"assets_asset"."id"
I need to get that device_id=X into LEFT OUTER JOIN definition below.
How to achieve?
TL;DR:
The condition should be in filter.
qs = (
Asset.objects
.filter(coupons__device_id='8ae83c6fa52765061360f5459025cb85e6dc8905')
.annotate(coupon_saved=Count('coupons'))
)
If you want only count > 0 then it can be filtered.
qs = qs.filter(coupon_saved__gt=0)
Footnotes: A one to many query is compiled to LEFT OUTER JOIN in order to be possible to get also base objects (Asset) with zero children. JOINs in Django are based every times on a ForeignKey to the primary key or similarly on OneToOne or ManyToMany, other conditions are compiled to WHERE.
Conditions in annotation (that you used) are possible e.g. as part of Conditional Expressions but it is more complicated to be used correctly and useful e.g. if you want to get many aggregations with many conditions by one query without subqueries and if a full scan is acceptable. This is probably not a subject of a question.
I have a model that has four fields. How do I remove duplicate objects from my database?
Daniel Roseman's answer to this question seems appropriate, but I'm not sure how to extend this to situation where there are four fields to compare per object.
Thanks,
W.
def remove_duplicated_records(model, fields):
"""
Removes records from `model` duplicated on `fields`
while leaving the most recent one (biggest `id`).
"""
duplicates = model.objects.values(*fields)
# override any model specific ordering (for `.annotate()`)
duplicates = duplicates.order_by()
# group by same values of `fields`; count how many rows are the same
duplicates = duplicates.annotate(
max_id=models.Max("id"), count_id=models.Count("id")
)
# leave out only the ones which are actually duplicated
duplicates = duplicates.filter(count_id__gt=1)
for duplicate in duplicates:
to_delete = model.objects.filter(**{x: duplicate[x] for x in fields})
# leave out the latest duplicated record
# you can use `Min` if you wish to leave out the first record
to_delete = to_delete.exclude(id=duplicate["max_id"])
to_delete.delete()
You shouldn't do it often. Use unique_together constraints on database instead.
This leaves the record with the biggest id in the DB. If you want to keep the original record (first one), modify the code a bit with models.Min. You can also use completely different field, like creation date or something.
Underlying SQL
When annotating django ORM uses GROUP BY statement on all model fields used in the query. Thus the use of .values() method. GROUP BY will group all records having those values identical. The duplicated ones (more than one id for unique_fields) are later filtered out in HAVING statement generated by .filter() on annotated QuerySet.
SELECT
field_1,
…
field_n,
MAX(id) as max_id,
COUNT(id) as count_id
FROM
app_mymodel
GROUP BY
field_1,
…
field_n
HAVING
count_id > 1
The duplicated records are later deleted in the for loop with an exception to the most frequent one for each group.
Empty .order_by()
Just to be sure, it's always wise to add an empty .order_by() call before aggregating a QuerySet.
The fields used for ordering the QuerySet are also included in GROUP BY statement. Empty .order_by() overrides columns declared in model's Meta and in result they're not included in the SQL query (e.g. default sorting by date can ruin the results).
You might not need to override it at the current moment, but someone might add default ordering later and therefore ruin your precious delete-duplicates code not even knowing that. Yes, I'm sure you have 100% test coverage…
Just add empty .order_by() to be safe. ;-)
https://docs.djangoproject.com/en/3.2/topics/db/aggregation/#interaction-with-default-ordering-or-order-by
Transaction
Of course you should consider doing it all in a single transaction.
https://docs.djangoproject.com/en/3.2/topics/db/transactions/#django.db.transaction.atomic
If you want to delete duplicates on single or multiple columns, you don't need to iterate over millions of records.
Fetch all unique columns (don't forget to include the primary key column)
fetch = Model.objects.all().values("id", "skuid", "review", "date_time")
Read the result using pandas (I did using pandas instead ORM query)
import pandas as pd
df = pd.DataFrame.from_dict(fetch)
Drop duplicates on unique columns
uniq_df = df.drop_duplicates(subset=["skuid", "review", "date_time"])
## Dont add primary key in subset you dumb
Now, you'll get the unique records from where you can pick the primary key
primary_keys = uniq_df["id"].tolist()
Finally, it's show time (exclude those id's from records and delete rest of the data)
records = Model.objects.all().exclude(pk__in=primary_keys).delete()
I have a two models:
class Category(models.Model):
pass
class Item(models.Model):
cat = models.ForeignKey(Category)
I am trying to return all Categories for which all of that category's items belong to a given subset of item ids (fixed thanks). For example, all categories for which all of the items associated with that category have ids in the set [1,3,5].
How could this be done using Django's query syntax (as of 1.1 beta)? Ideally, all the work should be done in the database.
Category.objects.filter(item__id__in=[1, 3, 5])
Django creates the reverse relation ship on the model without the foreign key. You can filter on it by using its related name (usually just the model name lowercase but it can be manually overwritten), two underscores, and the field name you want to query on.
lets say you require all items to be in the following set:
allowable_items = set([1,3,4])
one bruteforce solution would be to check the item_set for every category as so:
categories_with_allowable_items = [
category for category in
Category.objects.all() if
set([item.id for item in category.item_set.all()]) <= allowable_items
]
but we don't really have to check all categories, as categories_with_allowable_items is always going to be a subset of the categories related to all items with ids in allowable_items... so that's all we have to check (and this should be faster):
categories_with_allowable_items = set([
item.category for item in
Item.objects.select_related('category').filter(pk__in=allowable_items) if
set([siblingitem.id for siblingitem in item.category.item_set.all()]) <= allowable_items
])
if performance isn't really an issue, then the latter of these two (if not the former) should be fine. if these are very large tables, you might have to come up with a more sophisticated solution. also if you're using a particularly old version of python remember that you'll have to import the sets module
I've played around with this a bit. If QuerySet.extra() accepted a "having" parameter I think it would be possible to do it in the ORM with a bit of raw SQL in the HAVING clause. But it doesn't, so I think you'd have to write the whole query in raw SQL if you want the database doing the work.
EDIT:
This is the query that gets you part way there:
from django.db.models import Count
Category.objects.annotate(num_items=Count('item')).filter(num_items=...)
The problem is that for the query to work, "..." needs to be a correlated subquery that looks up, for each category, the number of its items in allowed_items. If .extra had a "having" argument, you'd do it like this:
Category.objects.annotate(num_items=Count('item')).extra(having="num_items=(SELECT COUNT(*) FROM app_item WHERE app_item.id in % AND app_item.cat_id = app_category.id)", having_params=[allowed_item_ids])