Table of contents
- Summary
- Initial server configuration
- Get doccano running
- Get doccano running simultaneaously with the Open Discourse database
- Retreive data
This repository contains files and documentation to set up an annotation pipeline for machine learning on the bwcloud OpenStack server.
Access information, credentials, and private key-file are stored on the S7 network storage /Projekte/BWCloudServer/
The annotation server hosts the doccano annotation tool (https://github.com/doccano/doccano) and a PostgreSQL database.
Doccano can be accessed via web browser under the known IP-adress. Database access is described in the readme.md in this repository in the folder ./scripts/.
To set up the annotation server from scratch, follow the subsequent steps... The basic useage of the bwCloud is described https://www.bw-cloud.org/de/erste_schritte and here https://uweremer.github.io/css_server_setup/.
Be aware: “With great power comes great responsibility”! You have root rights for your own instances. Everybody is responsible (and liable) for his/her own instance. The insatance is exposed in the internet, so take appropriate measures to secure your server!
Build an OpenStack instance, e.g., with the OpenSUSE Leap 15.3 JeOS image and login with ssh.
First, automate updates to receive security updates when necessary. Select at least weekly security updates.
sudo zypper install yast2-online-update-configuration
sudo yast2 online_update_configuration
As the JeOS (Just enough operating system) version of OpenSUSE is a minimal installation, we need to add some basic packages:
- nano
- tmux
- git
- docker
- docker-compose
sudo zypper install [package]
Start docker service:
sudo systemctl status docker
sudo systemctl start docker
Make docker service start on startup:
sudo systemctl enable docker.service
sudo systemctl enable containerd.service
For the comprehensive doccano documentation see https://doccano.github.io/doccano/
We use a docker container to deploy doccano on the server. First, clone the doccano repository from github with git.
git clone https://github.com/doccano/doccano.git
Next, we store our own configuration parameters in the .env file under path ./doccano/docker/ (by copying and customizing the .env.example)
cd doccano/docker/
cp .env.example .env
nano .env
The actual configuration of the productive environment is stored on the S7 network storage ./Projekte/BWCloudServer/.
Now, we can initialize the doccano container:
sudo docker-compose -f docker-compose.prod.yml --env-file .env up
Alternatively, if we use tmux, we can start the process in background shell session:
tmux new -s SESSIONNAME # starts new shell session
sudo docker-compose -f docker-compose.prod.yml --env-file .env up
Then press Ctrl + B d to leave session.
Now we can access the doccano annotation tools via web browser.
To stop the conatiner execute:
sudo docker-compose -f docker-compose.prod.yml down
To be able to use the Open Discourse database on parliamentary speeches of the German Bundestag together with the doccano server, we need to adapt the deployment process.
The Open Discourse database is available as prefilled PostgreSQL database docker container.
As doccano and the Open Discourse docker container both start postges as a service, we need to adapt the docker-compose yaml files. The goal is to arrive at a single PostgreSQL instance, which contains the OpenDiscourse database but also the doccano database.
The documentation on how to setup the Open Discourse database locally can be found here.
The docker image is provided via ghcr.io (github container registry). To access containers from ghcr.io, we need a github account and a personal github token with permisison to read:packages (see github documentation).
After generating this token, we store it in a .credentials file and use it to login to ghcr.io (don't forget to provide your USERNAME):
cd ~
nano .credentials # insert token ghp_...
cat .credentials | docker login ghcr.io -u USERNAME --password-stdin
Then we are able to pull the docker image:
docker pull ghcr.io/open-discourse/open-discourse/database:latest
If we were only interested in the database (without having a doccano environment), we could just follow the Open Discourse documentation and start the container:
docker run --env POSTGRES_USER=postgres --env POSTGRES_DB=postgres --env POSTGRES_PASSWORD=postgres -p 5432:5432 -d ghcr.io/open-discourse/open-discourse/database
Now we can explore the data (e.g. via pgAdmin or in R with the package RPostgreSQL (see section 'retreive data').
But if we want to have doccano and Open Discourse on the same postgres instance, we need to adapt the deployment procedure as follows:
We copy the customized docker yaml files from this repository /docker_yaml/ to the docker path of the doccano folders ./doccano/docker/.
cp ./annotation_pipeline/docker_yaml/* ./doccano/docker/
cd doccano/docker/
First, we need do start the Open Discourse container, as it provides also a PostgreSQL service within the image. The corresponding yaml file is /docker_yaml/docker-compose.od_db.yml.
Additionaly, we need to provide the .env file (already mentioned above).
sudo docker-compose -f docker-compose.od_db.yml --env-file .env up
Now we can access the PostgreSQL Server via pgAdmin, or R, or Python...
To properly shut down the service:
sudo docker-compose -f docker-compose.od_db.yml down
Before we can star the doccano container, we have to initialize the doccano database, so that the docker-compse command for the doccano container finds a database that is ready to be populated. For now, I just create the doccano database via the pgAdmin on the database server we just created.
Then we start the doccano container with docker-compose:
sudo docker-compose -f docker-compose.doccano.yml --env-file .env up
#sudo docker-compose -f docker-compose.doccano.yml --env-file .env down
To have a clean setup, make sure that the persistent docker volumes are newly initialized. But be aware: do not prune the volumes if they already contain productive data. Make sure to hava a backup of the data!
Hard reset of docker:
sudo systemctl restart docker
docker system prune -a
docker volume prune
See how to retreive data from the database with R and the packages DBI RPostgres:
# Install dependencies
install.packages("DBI")
library(DBI)
install.packages("RPostgres")
library(RPostgres)
Now we can create a connection to the database (remember to connect to the university network via VPN).
Please get the credentials from the .env file.
#dbname 'next' contains the opendiscourse data
con <- dbConnect(Postgres(),dbname = 'next',
host = '$HOST_IP',
port = 5432,
user = '$POSTGRES_USER',
password = 'POSTGRES_PASSWORD',
options='-c search_path=open_discourse')
Now we can display the existing tables for this connected database:
dbListTables(con)
Or display the existing fields for a specific table in the database:
dbListFields(con, "speeches")
And we can download the whole table from the database into a dataframe:
# Do not run! 920000 rows, 13 cols
#wahlen <- dbReadTable(con, "speeches")
Of course we could do SQL queries...
query <- dbSendQuery(con, "SELECT * FROM speeches WHERE
speeches.last_name = 'merkel' ")
df_neu <- dbFetch(query)
head(df_neu)
dbClearResult(query)