##Overview The purpose of this demo is to show the multi-model capabilities of DataStax Enterprise. This application uses graph and search functionality in the same schema.
##Data The data used in this demo is largely from 538, source GitHub. Application uses graph to explore relationships between players/countries and the World Cup tournaments in which they've participated.
- Install DSE single-node instance, options and instructions can be found on the DataStax website. Highly recommend using a container install method such as docker.
- (Optional) Install DataStax studio for running CQL and grelmin queries. Also available on docker.
- (Optional) To use the web UI pieces of this repo, the following components are required:
If you are using the development Next.js app, you will need to create an .env.local file to store your connection information.
(sample)
DSE_CONTACT_POINTS: YOUR_SERVER_DNS_NAME
DSE_KEYSPACE = 'WORLD_CUP'
DSE_LOCAL_DATA_CENTER = 'dc1'##Load Data Within the data directory there are data files you can use to load the graph schema. The goal of this data is provide a comparison of performances in World Cup play since 1966 and was created by the team at 538. Original source can be found within their github repository.
To load data, strongly recommend using the [dsbulk tool] (https://docs.datastax.com/en/dsbulk/doc/dsbulk/dsbulkRef.html). In terms of order, as long as the player, country, and tournament tables are loaded first there will be no issues.
Also included in the data directory is a .tar file export of DataStax Studio notebook that can be used as starting point for understanding some basic gremlin and CQL queries.