This project loads automatically information about world cup games into Elastcsearch.
It sets up elasticsearch and kibana docker containers which are ready for your analysis.
When you deploy the stack, a python script downloads the current status (updates every minute!) and load it instantly to elasticsearch!
- Make sure you have docker swarm!
- Clone the project by running:
git clone https://github.com/eeddaann/ElastiCup.git
-
Build the Docker images:
-
Kibana's image:
docker build ./kibana -t kibana-canvas
This can take few minutes because of the installation of canvas..
-
ETL (extract - transforom - load) image:
docker build ./etl -t elasticup-etl
-
-
Deploy the docker stack:
docker stack deploy -c docker-compose.yml elasticup
- Now open kibana on:
http://127.0.0.1:5601
- Click on "Canvas" in the side menu
- Load the workpad by clicking on "workpads" button at the bottom menu
- Drag and drop matches.json
The data is imported from: https://worldcup.sfg.io/matches
To analyze this data efficiently with Elasticsearch I decomposed the data about each match to three elasticsearch's documents. Each kind of documented is loaded into dedicated index:
