Fault-Tolerant Streaming with Flink

This is a demo to show how Flink can deal with stateful streaming jobs and fault-tolerance. The idea is to have an analysis job with a stateful counter. The job is started on a cluster with two TaskManagers, then the TaskManagers are shot down to see how Flink reacts.

These are the steps to take:

1. Build Flink 0.10-SNAPSHOT: This is required to get the latest checkpoint/recovery code. If you have a checkout of the Flink repository a quick mvn clean install -DskipTests should do the trick.

2. Follow the Hello Samza example from here: hello samza. We use this to get Kafka up and running and also to parse the wikipedia edit stream and put it into a Kafka topic.

3. Package the example using mvn package.

4. Start local Flink cluster with two TaskManagers. This can be done using:

   bin/start-cluster-streaming.sh
   rm /tmp/my-taskmanager.pid && bin/taskmanager.sh start streaming

5. Start the example job on the Flink cluster:

   bin/flink run -c com.dataartisans.streamexample.ScalaJobCheatSheet /path/to/example.jar

6. Get PIDs of running TaskManagers using jps. Shoot down one TaskManager. The job fails and recovers you hit the right one, if not, start another TaskManager using the earlier command and repeat with the other TaskManager PID.

   jps
   kill -KILL <taskmanager-pid>