{"id":17110798,"url":"https://github.com/eeddaann/elasticup","last_synced_at":"2025-03-23T22:18:39.748Z","repository":{"id":97229613,"uuid":"138799811","full_name":"eeddaann/ElastiCup","owner":"eeddaann","description":"Analyze 2018 FIFA World Cup with the ELK stack!","archived":false,"fork":false,"pushed_at":"2018-07-19T22:08:05.000Z","size":308,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-01-29T05:28:27.324Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/eeddaann.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-06-26T22:19:29.000Z","updated_at":"2018-08-08T13:13:08.000Z","dependencies_parsed_at":null,"dependency_job_id":"1eaad0c5-5d05-409d-977e-3058e59a6b5b","html_url":"https://github.com/eeddaann/ElastiCup","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eeddaann%2FElastiCup","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eeddaann%2FElastiCup/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eeddaann%2FElastiCup/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eeddaann%2FElastiCup/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/eeddaann","download_url":"https://codeload.github.com/eeddaann/ElastiCup/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245175572,"owners_count":20572802,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-14T16:46:25.245Z","updated_at":"2025-03-23T22:18:39.726Z","avatar_url":"https://github.com/eeddaann.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ElastiCup \n\n## Analyze 2018 FIFA World Cup with the ELK stack!\n\nThis project loads automatically information about world cup games into Elastcsearch.\n\nIt sets up elasticsearch and kibana docker containers which are ready for your analysis. \n\nWhen you deploy the stack, a python script downloads the current status (updates every minute!) and load it instantly to elasticsearch!\n\n## Getting Started\n\n1. Make sure you have docker swarm!\n2. Clone the project by running:\n\n```git clone https://github.com/eeddaann/ElastiCup.git```\n\n3. Build the Docker images:\n\n   - Kibana's image:\n\n     ``` bash\n     docker build ./kibana -t kibana-canvas\n     ```\n\n     *This can take few minutes because of the installation of canvas..* \n\n   - ETL (extract - transforom - load) image:\n\n     ```bash\n     docker build ./etl -t elasticup-etl\n     ```\n\n4. Deploy the docker stack:\n\n``` docker stack deploy -c docker-compose.yml elasticup``` \n\n5. Now open kibana on:\n\n```http://127.0.0.1:5601``` \n\n6. Click on \"Canvas\" in the side menu \n7. Load the workpad by clicking on \"workpads\" button at the bottom menu\n8. Drag and drop matches.json\n\n## Screenshots\n\n![](./images/1.png)\n\n![](./images/2.png)\n\n![](./images/3.png)\n\n## data\n\nThe data is imported from: https://worldcup.sfg.io/matches\n\nTo 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:\n\n### matches\n\n![](./images/matches.png)\n\n## team-stats\n\n![](./images/team-stats.png)\n\n## events\n\n![](./images/events.png)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feeddaann%2Felasticup","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Feeddaann%2Felasticup","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feeddaann%2Felasticup/lists"}