4.4 KiB
TubeSync
Advanced usage guide - using other database backends
This is a new feature in v1.0 of TubeSync and later. It allows you to use a custom existing external database server instead of the default SQLite database. You may want to use this if you encounter performance issues with adding very large or a large number of channels and database write contention (as shown by errors in the log) become an issue.
Requirements
TubeSync supports SQLite (the automatic default) as well as PostgreSQL, MySQL and MariaDB. For MariaDB just follow the MySQL instructions as the driver is the same.
You should start with a blank install of TubeSync. Migrating to a new database will reset your database. If you are comfortable with Django you can export and re-import existing database data with:
$ docker exec -i tubesync python3 /app/manage.py dumpdata > some-file.json
Then change you database backend over, then use
$ cat some-file.json | docker exec -i tubesync python3 /app/manage.py loaddata - --format=json
As detailed in the Django documentation:
https://docs.djangoproject.com/en/3.1/ref/django-admin/#dumpdata
and:
https://docs.djangoproject.com/en/3.1/ref/django-admin/#loaddata
Further instructions are beyond the scope of TubeSync documenation and you should refer to Django documentation for more details.
If you are not comfortable with the above, then skip the dumpdata
steps, however
remember you will start again with a completely new database.
Steps
1. Create a database in your external database server
You need to create a database and a user with permissions to access the database in your chosen external database server. Steps vary between PostgreSQL, MySQL and MariaDB so this is up to you to work out.
2. Set the database connection string environment variable
You need to provide the database connection details to TubeSync via an environment
variable. The environment variable name is DATABASE_CONNECTION
and the format is the
standard URL-style string. Examples are:
postgresql://tubesync:password@localhost:5432/tubesync
and
mysql://tubesync:password@localhost:3306/tubesync
Important note: For MySQL databases make SURE you create the tubesync database with
utf8mb4
encoding, like:
CREATE DATABASE tubesync CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci;
Without utf8mb4
encoding things like emojis in video titles (or any extended UTF8
characters) can cause issues.
3. Start TubeSync and check the logs
Once you start TubeSync with the new database connection you should see the folling log entry in the container or stdout logs:
2021-04-04 22:42:17,912 [tubesync/INFO] Using database connection: django.db.backends.postgresql://tubesync:[hidden]@localhost:5432/tubesync
If you see a line similar to the above and the web interface loads, congratulations, you are now using an external database server for your TubeSync data!
Database Compression (For MariaDB)
With a lot of media files the sync_media
table grows in size quickly.
You can save space using column compression while using MariaDB
- Stop tubesync
- Execute
ALTER TABLE sync_source MODIFY metadata LONGTEXT COMPRESSED;
on database tubesync - Start tunesync and confirm the connection still works.
Docker Compose
If you're using Docker Compose and simply want to connect to another container with the DB for the performance benefits, a configuration like this would be enough:
tubesync-db:
image: postgres:15.2
container_name: tubesync-db
restart: unless-stopped
volumes:
- /<path/to>/init.sql:/docker-entrypoint-initdb.d/init.sql
- /<path/to>/tubesync-db:/var/lib/postgresql/data
environment:
- POSTGRES_USER=postgres
- POSTGRES_PASSWORD=testpassword
tubesync:
image: ghcr.io/meeb/tubesync:latest
container_name: tubesync
restart: unless-stopped
ports:
- 4848:4848
volumes:
- /<path/to>/tubesync/config:/config
- /<path/to>/YouTube:/downloads
environment:
- DATABASE_CONNECTION=postgresql://postgres:testpassword@tubesync-db:5432/tubesync
depends_on:
- tubesync-db
Note that an init.sql
file is needed to initialize the tubesync
database before it can be written to. This file should contain:
CREATE DATABASE tubesync;
Then it must be mapped to /docker-entrypoint-initdb.d/init.sql
for it
to be executed on first startup of the container. See the tubesync-db
volume mapping above for how to do this.