DataFibers (DF) - A pure streaming processing application on Kafka and Flink. The DF processor has two components defined to deal with stream ETL (Extract, Transform, and Load).

• Connects is to leverage Kafka Connect REST API on Confluent to landing or publishing data in or out of Apache Kafka.
• Transforms is to leverage streaming processing engine, such as Apache Flink, for data transformation.

You build the project using:

mvn clean package

The application is tested using vertx-unit.

The application is packaged as a fat jar, using the Maven Shade Plugin.

Once packaged, just launch the fat jar as follows ways

• Default with no parameters to launch standalone mode with web ui.

java -jar df-data-service-<version>-SNAPSHOT-fat.jar

• For more running features checking help option

java -jar df-data-service-<version>-SNAPSHOT-fat.jar -h

http://localhost:8000/ or http://localhost:8000/dfa/

https://datafibers-community.gitbooks.io/datafibers-complete-guide/content/

• Fetch all installed connectors/plugins in regularly frequency
• Need to report connector or job status
• Need an initial method to import all available|paused|running connectors from kafka connect
• Add Flink Table API engine
• Add memory LKP
• Add Connects, Transforms Logging URL
• Add to generic function to do connector validation before creation
• Add submit other job actions, such as start, hold, etc
• Add Spark Structure Streaming
• Topic visualization
• Launch 3rd party jar
• Job level control, schedule, and metrics