Example application in Django using Elasticsearch DSL for search.

It uses data from StackExchange dumps (https://archive.org/details/stackexchange) - download the torrent and just point the load_dump command to an unpacked data directory for a stack exchange server.

To install:

# install requirements
pip install -r requirements.txt

# create database
python manage.py migrate

# load SE dump into the DB
python manage.py load_dump DIR

# index all data into elasticsearch
python manage.py index_data

To perform search just go to http://localhost:8000/search/?tags=flavor&tags=beans&q=bitterness.

To develop on this project make sure you Docker an Docker Compose installed.

To get started just run:

docker-compose up -d

wait till the elastic cluster is healthy:

$ docker ps
CONTAINER ID        IMAGE                       COMMAND                  CREATED             STATUS                 PORTS                       NAMES
d25832cf31db        e62bf4ebda11                "python manage.py ..."   About an hour ago   Up About an hour       0.0.0.0:80->80/tcp          esdjangoexample_web_1
98a60d2d200c        fxdgear/elasticsearch:5.4   "/docker-entrypoin..."   2 hours ago         Up 2 hours (healthy)   9200/tcp, 9300/tcp          esdjangoexample_elasticsearch_1

Once healthy you can access the web container by running:

docker exec --it esdjangoexample_web_1 ash

Then you can create the database by running:

python manage.py migrate

Then you can load the SE dump into the data base:

python manage.py load_dump DIR

Then you can index the data:

python manage.py index_data

Now you can naviaget to http://localhost

Build and push the image to the repository:

docker-compose build
docker-compose push

To deploy this with docker swarm. Make sure you have access to a swarm cluster and simply run:

docker stack deploy --compose-file docker-compose.prod.yml es-django-example