https://github.com/thkwag/spring-cloud-dataflow-quartz-scheduler
Spring Cloud Data Flow Quartz Scheduler
https://github.com/thkwag/spring-cloud-dataflow-quartz-scheduler
quartz quartz-scheduler spring-batch spring-cloud-data-flow spring-cloud-dataflow spring-integration
Last synced: 12 months ago
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Spring Cloud Data Flow Quartz Scheduler
- Host: GitHub
- URL: https://github.com/thkwag/spring-cloud-dataflow-quartz-scheduler
- Owner: thkwag
- License: mit
- Created: 2025-02-23T09:39:00.000Z (12 months ago)
- Default Branch: master
- Last Pushed: 2025-02-23T09:56:17.000Z (12 months ago)
- Last Synced: 2025-02-23T10:26:50.530Z (12 months ago)
- Topics: quartz, quartz-scheduler, spring-batch, spring-cloud-data-flow, spring-cloud-dataflow, spring-integration
- Language: Java
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Spring Cloud Data Flow Quartz Scheduler
> ⚠️ **Warning**: This project is currently under development and not ready for production use. Testing and validation are still in progress.
A scheduling solution for Spring Cloud Data Flow that works in any environment - local, VM, or Kubernetes.
## Why This Project?
Spring Cloud Data Flow only supports scheduling in Kubernetes environments. According to the [official documentation](https://dataflow.spring.io/docs/feature-guides/batch/scheduling/#scheduling-a-batch-job):
> "Spring Cloud Data Flow does not offer an out-of-the-box solution for scheduling task launches on the local platform."
This project provides a complete scheduling solution that:
- Works in any environment (local, VM, cloud) without Kubernetes
- Integrates seamlessly with Spring Cloud Data Flow
- Uses Quartz for reliable and flexible scheduling
## Features
- **Simple Setup**: Easy to run in any environment
- **Full Integration**: Works with existing Spring Cloud Data Flow tasks
- **Flexible Scheduling**: Supports cron expressions and various triggers
- **Dashboard**: Includes UI for schedule management
- **High Availability**: Supports clustered environments
- **Job History**: Tracks all task executions
## Quick Start
### Prerequisites
- JDK 17+
- Spring Cloud Data Flow Server
- MySQL/PostgreSQL
### Run with Docker
```bash
docker-compose up -d
```
### Run with Gradle
```bash
./gradlew bootRun
```
## Documentation
- [Spring Cloud Data Flow](https://dataflow.spring.io/docs/feature-guides/batch/scheduling/)
- [Quartz Scheduler](http://www.quartz-scheduler.org/documentation/)
## License
MIT License - see the [LICENSE](LICENSE) file for details.