Hazelcast Jet Demo Applications
The following are demonstration applications using Hazelcast Jet. Each is a full application and demonstrates how you can use Jet to solve real-world problems.
For smaller, feature specific samples see Hazelcast Jet Code Samples.
- Git Large File Storage: Installation Guide some of the demo applications include machine learning models in their use cases. Since some models’ size exceeds GitHub’s 100MB file storage limit this repository uses Git LFS.
- Java Development Kit 8+: Installation Guide
- Apache Maven: Installation Guide
Real-Time Image Recognition
Recognizes images present in the webcam video input with a model trained with CIFAR-10 dataset.
Twitter Cryptocurrency Sentiment Analysis
Twitter and Reddit content is analyzed with sentiment analysis in real time to calculate a cryptocurrency aggregated sentiment score.
Real-Time Road Traffic Analysis and Prediction
Continuously computes linear regression models from current traffic. Uses the trend from week ago to predict traffic now.
Real-Time Sports Betting Engine
This is a simple example of a sports book and is a good introduction to the Pipeline API. It also uses Hazelcast IMDG as an in-memory data store.
Reads a stream of telemetry data from ADB-S on all commercial aircraft flying anywhere in the world.
Market Data Ingest
Uploads a stream of stock market data (prices) from a Kafka topic into an IMDG map.