Hey all,
I'd like to suggest adding Common Table Expression (CTE) query generation
as a feature to Django.
I've been working on a project that required manipulation of many records
at once, and as with many ORMs found that this wasn't an ideal use-case in
Django. As the rest of our code base and related projects are in Django,
there was a strong preference to find a way to do it and keep to the same
model-is-the-truth design.
I first did this by writing some hackish functions using raw querysets and
generating my own CTE based queries, but it lacked ideal flexibility and
maintainability. So I've now written some modifications into my Django to
do this in a more Django-esque way and think that this functionality would
be beneficial within the project itself, but am unsure exactly where to
start the conversation about that.
*Why generate CTE based queries from querysets?*
By allowing querysets to be attached to each other, and setting appropriate
WHERE clauses, arbitrary and nested SQL queries can be generated. Where the
results of the queries are only necessary for the execution of following
queries this saves a very substantial amount of time and database work.
Once these features exist, other functionality can also transparently use
these to generate more efficient queries (such as large IN clauses).
This allows several powerful use cases I think Django would benefit from:
*Large 'IN' clauses*, can be implemented as CTEs reducing expensive lookups
to a single CTE INNER JOIN. For sets of thousands to match from tables of
millions of records this can be a very substantial gain.
*Composite 'IN' conditions,* where multiple fields must match and you're
matching against a large set of condition rows. In my usage this was "where
the md5/sha hashes match one of the million md5/sha tuples in my match
set". This is simply a CTE JOIN with two clauses in the WHERE.
*Nested data creation*, where the parent doesn't yet exist. Django doesn't
currently do this as the primary keys are needed, and this makes normalised
data structures unappealing. Using INSERTs as CTEs that supply those keys
to following statements means that entire nested data structures of new
information can be recreated in the database at once, efficiently and
atomically.
*Non-uniform UPDATE*s, such that a modified set of objects can all be
updated with different data at the same time by utilising a CTE values
statement JOINed to the UPDATE statement. As there's currently no way to do
this kind of bulk update the alternative is to update each instance
individually, and this doesn't scale well.
These could also be used with aggregations and other calculated fields to
create complex queries that aren't possible at the moment.
*What my PoC looks like*
With another mildly hackish PoC that creates a VALUEs set from a
dict/namedtuple which can be used to provide large input data, my present
modified version syntax looks a bit like this (not perfect queries):
class Hashes(models.Model):
md5 = models.UUIDField(verbose_name="MD5 hash (base16)", db_index=True)
sha2 = models.CharField(max_length=44, null=True, verbose_name="SHA256 hash
(base64)")
# Mock QuerySet of values
q_mo = Hashes.as_literal(input_hashes).values("md5", "sha2")
# A big IN query
q_in = Hashes.objects.attach(q_mo).filter(md5=q_mo.ref("md5"))
# Matched existing values with composite 'IN' (where md5 and sha2 match, or md5
matches and existing record lacks sha2)
q_ex =
Hashes.objects.attach(q_mo).filter(md5=q_mo.ref("md5")).filter(Q(sha160=q_mo.ref("sha160"))
| Q(sha160=None))
# Create new records that don't exist
q_cr = Hashes.objects.attach(q_mo,
q_ex).filter(md5=q_mo.ref("md5")).exclude(md5=q_ex.ref("md5")).values("md5",
"sha2").as_insert()
Returning the newly created records.
SQL can be generated that looks something like this:
WITH cte_1_0 (md5, sha2) AS (
VALUES ('00002d30243bfe9d06673765c432c2bd'::uuid,
'fsA8okuCuq9KybxqcAzNdjlIyAx1QJjTPdf1ZFK/hDI='::varchar(44)),
('0000f20a46e4e60338697948a0917423',
'6bVZgpYZtit1E32BlANWXoKnFFFDNierDSIi0SraND4=')),
cte_1 AS (
SELECT "hashes"."id", "hashes"."md5", "hashes"."sha2"
FROM "hashes" , "cte_1_0"
WHERE ("hashes"."md5" = (cte_1_0.md5) AND ("hashes"."sha2" =
(cte_1_0.sha2) OR "hashes"."sha2" IS NULL) ))
SELECT "hashes"."md5"
FROM "hashes" , "cte_1_0" , "cte_1"
WHERE ("hashes"."md5" = (cte_1_0.md5) AND NOT ("hashes"."md5" = (cte_1.md5)))
That is:
- A qs.as_insert() and qs.as_update() on queryset to create *lazy*
insert and update queries.
- A qs.attach() that allows querysets to be attached to other querysets,
and will generate them as CTE statements.
- A qs.ref() that returns an expression that when the query is compiled
will be a field reference on the CTE that represents that queryset.
- Additional compilers on the QuerySet subclasses that these return (so
no changes to base compilers meaning no functionality impact to existing
usage)
- Generation of WITH clauses for attached querysets, and RETURN clauses
for lazy UPDATE and INSERT querysets with fields requested (via values() in
this case)
As these can be attached to querysets that are attached to querysets, that
are... etc, many statements can be chained allowing substantial changes to
be performed without needing Django to have to receive, process, and resend
at every step.
I've had a read through the enhancement proposal docs etc, and I'm willing
to do what's needed to make this functionality solid, and put forth a
proposal to add it. But am first seeking feedback on it, and whether this
is a feature that will be considered.
Thanks,
- Ashley
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