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- Interactive Flink based data exploration in Jupyter
- Plaform libraries support for common operations
- Savepoints
- Triggering, Listing & Resuming & Disposing savepoints from Deployment Manager for a given application.
- Example applications
- Illustrate how to build and deploy Flink applications with PNDA (in Java, Scala & Python)
- executing batch job similar to spark-batch-python
- executing streaming job similar to spark-streaming-python
- Illustrate how to use Flink Accumulators, application metrics
- Use stateful continuous processing (non-batch mode) making it a different case from Spark streaming examples
- Illustrate how to build and deploy Flink applications with PNDA (in Java, Scala & Python)
- Metrics
- configure Graphite as a default metrics reporter in flink.
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