Open simonw opened 7 years ago
simonw
commented
7 years ago I generated the list of SQL queries by adding the following configuration to swapi_graphene/settings.py
LOGGING = {
'version': 1,
'handlers': {
'console': {
'level': 'DEBUG',
'class': 'logging.StreamHandler',
},
},
'loggers': {
'django.db.backends': {
'level': 'DEBUG',
'handlers': ['console'],
},
},
}Even better: is it possible to detect the fields being requested and update the SELECT fields in those statements, using the Django .only() QuerySet method?
My ideal SQL queries for this GraphQL query would be either this (using prefetch_related):
SELECT COUNT(*) AS "__count" FROM "starwars_species";
SELECT "starwars_species"."id", "starwars_species"."name", "starwars_species"."homeworld_id",
FROM "starwars_species" LIMIT 37;
SELECT "starwars_planet"."name", "starwars_planet"."gravity"
FROM "starwars_planet"
WHERE "starwars_planet"."id" in (
9, 14, 23, 24, 28, 29, 31, 7, 33, 18, 8, 34,
35, 37, 38, 39, 40, 41, 43, 44, 45, 46, 47,
48, 49, 50, 11, 51, 54, 55, 10, 56, 57, 58, 59, 12
);Or this (using a select_related() join):
SELECT COUNT(*) AS "__count" FROM "starwars_species";
SELECT "starwars_species"."id", "starwars_species"."name", "starwars_species"."homeworld_id",
"starwars_planet"."name", "starwars_planet"."gravity"
FROM "starwars_species"
JOIN "starwars_planet" ON
"starwars_species"."homeworld_id" = "starwars_planet"."id"
LIMIT 37;On closer inspection of the docs, it looks like the solution here is to use a DataLoader - any chance of some example code for that? http://docs.graphene-python.org/en/latest/execution/dataloader/
simonw
commented
7 years ago I got this working using a dataloader: https://github.com/simonw/swapi-graphene/commit/cea04512abf01e929d50f050e3c690a2a7117565
Corresponding SQL:
(0.001) SELECT COUNT(*) AS "__count" FROM "starwars_species"; args=()
(0.001) SELECT "starwars_species"."id", "starwars_species"."created",
"starwars_species"."edited", "starwars_species"."name",
"starwars_species"."classification", "starwars_species"."designation",
"starwars_species"."average_height", "starwars_species"."skin_colors",
"starwars_species"."hair_colors", "starwars_species"."eye_colors",
"starwars_species"."average_lifespan", "starwars_species"."homeworld_id",
"starwars_species"."language" FROM "starwars_species" LIMIT 37; args=()
(0.002) SELECT "starwars_planet"."id", "starwars_planet"."created",
"starwars_planet"."edited", "starwars_planet"."name",
"starwars_planet"."rotation_period", "starwars_planet"."orbital_period",
"starwars_planet"."diameter", "starwars_planet"."climate",
"starwars_planet"."gravity", "starwars_planet"."terrain",
"starwars_planet"."surface_water", "starwars_planet"."population" FROM
"starwars_planet" WHERE "starwars_planet"."id" IN (9, 14, 23, 24, 28, 29,
31, 7, 33, 18, 8, 34, 35, 37, 38, 39, 40, 41, 43, 44, 45, 46, 47, 48, 49, 50,
11, 51, 54, 55, 10, 56, 57, 58, 59, 12); args=(9, 14, 23, 24, 28, 29, 31, 7,
33, 18, 8, 34, 35, 37, 38, 39, 40, 41, 43, 44, 45, 46, 47, 48, 49, 50, 11,
51, 54, 55, 10, 56, 57, 58, 59, 12)Oops, correct resolver on the Specie class looks like this:
def resolve_homeworld(self, *args):
if self.homeworld_id:
return planet_loader.load(self.homeworld_id)
else:
return NoneI think that's wrong too. The PlanetLoader batch_load_fn(keys) method needs to return objects for the keys in the same order that the keys were provided.
simonw
commented
7 years ago OK, I think this is the correct implementation of the DataLoader:
from promise import Promise
from promise.dataloader import DataLoader
class PlanetLoader(DataLoader):
def batch_load_fn(self, keys):
objects_by_key = {
o.pk: o
for o in models.Planet.objects.filter(pk__in=keys)
}
results = []
for key in keys:
results.append(objects_by_key.get(key, None))
return Promise.resolve(results)
planet_loader = PlanetLoader()
This query:
Executes 38 sql queries, looking something like this:
Full list here: https://gist.github.com/simonw/762a98de85a2f113d1d7ec6026f73ee4
Is it possible to detect this case and then use select_related() or prefetch_related() here to join against the relevant table and get everything done in just one or two queries?
If so, an example showing how to do that would be a fantastic illustration of a slightly more complex use-case for graphene-django (I tried myself and couldn't figure out how to do it).