Re: DB migration: Loading a massive fixture dump

Just for the follow-up, I ended up using pgloader and after some argument tweaking, it worked. Cheers.

On Wednesday, September 2, 2020 at 7:26:04 AM UTC+2 Fred Blaise wrote:

Hi Mike,

Thanks for the answer.

Yes, I was aware yet hopeful regarding the size.

Regarding the converter, I would be interested to take a look at your py3 work, if you could forward it along.

Thanks.

On Wed, Sep 2, 2020, 00:21 Fred Blaise <fred....@gmail.com> wrote:

Hi,

I have to migrate a database from mysql to postgresql. Unfortunately, there is quite a bit of data in there.

As a strategy, I thought of using Django's ORM feature, dump the data from my setup using mysql, and load the fixtures on the other setup using postgresql, such as:

# on mysql

$ docker exec -ti madchap_ddojo_uwsgi_1 bash -c 'python manage.py dumpdata --indent=4 -e sessions -e admin --natural-foreign --natural-primary -e contenttypes -e auth.permission -v2' > ~/Downloads/datadump_orm_dump_1.json

This yields a 4GB json file.

Reload on the other side, such as:

# on postgresql

$  docker exec -ti madchap_ddojo_uwsgi_1 bash -c 'python manage.py loaddata datadump_orm_dump_small.json'

I let the loaddata run for 4hours, and it eventually returns with no error -- but no success either. I actually now think that the message indicating "Installed x object(s) from 1 fixture(s)" does not show, I will see again.

Looking at the postgresql side, querying metatables such as:

SELECT nspname || '.' || relname AS "relation",

    pg_size_pretty(pg_total_relation_size(C.oid)) AS "total_size"

  FROM pg_class C

  LEFT JOIN pg_namespace N ON (N.oid = C.relnamespace)

  WHERE nspname NOT IN ('pg_catalog', 'information_schema')

    AND C.relkind <> 'i'

    AND nspname !~ '^pg_toast'

  ORDER BY pg_total_relation_size(C.oid) DESC

  LIMIT 5;

tells me loads of data gets in there. a "\d+" does not agree, however (weird, but I don't know enough to get the difference between the two). And yet, I cannot see anything through any SELECT statement (hinting to the transaction isolation).

All things equal, this strategy works fine when working with small json files. I just successfully did it with a file less than 1MB.

I am guessing I have a few questions, I am stuck here.

1. Are there any hidden args/switches to manage.py loaddata or else that I could look at?

2. Are there specific django configuration that could help me load the data?

3. Does a loaddata actually result in a massive single transaction? (looks like so, sounds crazy to me :))

4. Is there a better way to migrate my data?

Thanks a lot for any pointers!

Cheers.

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