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Partial postgres db dumps for a Django app

Off late, I have been working with a large postgres database that is used by an app built in Django. I wanted a partial dump of the database to try out some experimental clean up scripts. I haven't really used databases before, and the last time I had to do this I did it in a pretty ad-hoc fashion. This time around, I tried to do it more methodically and to document it.

The Django Route

I looked around for tools that let you do this, and found django-fixture-magic. I first tried it out on my older partial dump (10% as large as the original db) and it turned out to be reasonably fast and worked well, after making a few changes to get it working with Python 3.x. Its kitchensink flag to the dump_object seemed like a promising option, but didn't really seem to get all the required tables for ManyToManyFields. I worked around it, by getting a dump of all the models which were related using Django's dumpdata.

Get a dump with objects of interest

The dump_object command lets you run commands to select the objects that you want to have in the dump, and that is quite a useful thing.

python manage.py dump_object dataset.Product -k --query '{"subcategory_id__in": [1886, ...]}' > products.json

Also, get a dump of related tables.

# Dump of related fields
python manage.py dumpdata dataset.Attribute > attributes.json

Create the new empty db

Next, create a new database where this fixture can be loaded!

# Create the db
sudo su - postgres
createdb mydb

# Create a user, if required
createuser -P

Grant access to the user

In the psql prompt type the following to grant the user permissions for the database.

GRANT ALL PRIVILEGES ON DATABASE mydb TO myuser;

Fix settings.py and create tables for the models.

Make changes to settings.py to use the newly created database, and then create the tables used by the app, and then load the data.

python manage.py syncdb
python manage.py loaddata products.json

Too slow!

This method worked and was reasonably fast when I was trying to get 20k rows from a table with about 200k rows, with all the dependencies.

But, when I tried to get a dump of about 200k rows from a table with 2M rows, it was way too slow to be of any use. There could've been a couple of reasons for this, which I didn't have the time to look into, and debug.

  • The web-server where the Django app was running, and the db server with the postgres database were on different machines in separate datacenters, which could've been adding a significant amount of latency.
  • Just the size of the database being much larger could be making it slower?

These are things I should be looking into and learning about, when I have more time at hand. For now, I needed a quicker way to get a dump. Even though the raw SQL route was more manual, it turned out to be much quicker.

Raw SQL dump route

Get a dump of the interesting tables

First, I had to get a dump of all the tables with the data I was interested in, one-by-one.

COPY (SELECT * FROM "dataset_product" WHERE ("dataset_product"."subcategory_id" IN (319557, 94589, 332, 406, 626, 1886) AND "dataset_product"."gender_id" = 1)) TO '/tmp/products.tsv'

COPY (SELECT * FROM "dataset_photo" WHERE "dataset_photo"."product_id" IN (SELECT U0."id" FROM "dataset_product" U0 WHERE (U0."subcategory_id" IN (319557, 94589, 332, 406, 626, 1886) AND U0."gender_id" = 1))) TO '/tmp/photos.tsv'

-- Copy a bunch of other tables!

Load the data from the dumps

-- syncdb
COPY dataset_product FROM '/tmp/products.tsv' ENCODING 'UTF8';
COPY dataset_photo FROM '/tmp/photos.tsv' ENCODING 'UTF8';
-- Copy a bunch of other tables!

Make tables writable

Some of the tables did not let me write anything to them, until I altered the sequence for these tables.

Automating

It would be pretty nice if all of this was automated – allow a user to enter exactly the same kind of a query that django-fixture-magic lets you run, and figure out the SQL copies that need to be done to get the requested dump. Its something that currently would qualify as yak-shaving, but may be a handy thing to have. Someone somewhere possibly already has something that does this.

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