I am trying to optimise the speed of a migration on a large table (250K objects). The goal is to add to each row a user field based on the user of an object related to this row:
I tried using an F expression but sadly django won't allow relations in them. Note that I am mostly a beginner in SQL :)
## models.py
class Band(models.Model):
user = models.ForeignKey(
settings.AUTH_USER_MODEL,
on_delete=models.CASCADE,
null=True,
default=None)
...
class Album(models.Model):
band = models.ForeignKey(
Band
on_delete=models.CASCADE,
null=True,
default=None)
user = models.ForeignKey(
settings.AUTH_USER_MODEL,
on_delete=models.CASCADE,
null=True,
default=None)
...
## 0035_album_add_user.py
def forwards_add_user(apps, schema_editor):
Album = apps.get_model('band', 'Album')
db_alias = schema_editor.connection.alias
albums = Album.objects \
.using(db_alias) \
.filter(band__isnull=False) \
.select_related('band', 'band__user')
for each in albums:
each.user = each.band.user
Album.objects \
.using(db_alias) \
.bulk_update(albums, ['user'])
class Migration(migrations.Migration):
dependencies = [ ... ]
operations = [
migrations.RunPython(forwards_add_user, reverse_add_user),
]
This migrations currently takes an hour on my local with 100% usage on the database for the whole duration. I have a better CPU thank my production database so this worries me a lot, downing the production database for an hour is not really an option.
I'm looking at two different solutions both of which I have no idea of how to accomplish : - Optimize more the python code to make it run faster - Throttle the database's CPU consummation during the migration so it stays available. Both being the best case scenario :)
I'm running Python3.6.9 with Django2.2.9 and PostgreSQL10.6 on RDS in production an in a Docker in local.
Thanks !