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:
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 -DskipTestsshould do the trick.
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.
Package the example using
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
Start the example job on the Flink cluster:
bin/flink run -c com.dataartisans.streamexample.ScalaJobCheatSheet /path/to/example.jar
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>