Hazelcast Jet is a powerful distributed data processing engine that allows developers to build high-performance, fault-tolerant stream processing applications. In this blog post, we will explore some of the key fault tolerance mechanisms provided by Hazelcast Jet and how to leverage them in your Java applications.

1. Checkpointing

Checkpointing is a fundamental mechanism in fault-tolerant stream processing systems. It allows the system to create snapshots of the application’s state, which can be used for recovery in case of failures. Hazelcast Jet uses a distributed snapshotting technique called “distributed snapshots” to ensure a consistent and fault-tolerant processing of data.

To enable checkpointing in a Jet application, you need to configure a few properties. You can use the StreamStage#snapshot() method to define when and how often you want to take snapshots of your application’s state.

 Pipeline.create()
  .readFrom(source)
  .apply(transformations)
  .snapshot(SnapshotMode.EXACTLY_ONCE)
  .writeTo(sink);

By specifying SnapshotMode.EXACTLY_ONCE, you ensure that the snapshots are taken precisely once for each batch of data processed.

2. Job Restarting

In addition to checkpointing, Hazelcast Jet provides a built-in job restarting mechanism that automatically recovers the job from the latest successful snapshot in case of failure. This allows for seamless recovery from failures without any manual intervention.

When a Jet job is started, it creates a snapshot of the initial state. In case of a failure, the system automatically restarts the job from the latest successful snapshot, ensuring exactly-once processing semantics.

To enable job restarting, you need to set the JetConfig#setEnabled(true) property in your configuration:

Config config = new Config();
JetConfig jetConfig = config.getJetConfig();
jetConfig.setEnabled(true);

Once enabled, Hazelcast Jet will automatically restart the job in case of a failure.

Conclusion

In this blog post, we explored the fault tolerance mechanisms provided by Hazelcast Jet in Java applications. We learned about checkpointing, which allows for creating snapshots of the application’s state, and how to enable job restarting for seamless recovery from failures.

By leveraging these fault tolerance mechanisms, developers can build robust and reliable stream processing applications with Hazelcast Jet.

#HazelcastJet #FaultTolerance #Java