#HazelcastJet #Java

Hazelcast Jet is a powerful distributed computing platform that allows you to perform high-speed data processing and analysis. One of its key features is windowing, which allows you to perform computations on sliding or tumbling intervals of data. In this blog post, we will explore how to use windowing in Hazelcast Jet with Java applications.

Windowing Basics

Windowing is a technique used to group data based on time or count intervals. Hazelcast Jet provides two types of windows:

1. Tumbling Windows: These windows are non-overlapping and have a fixed size. For example, if you have a tumbling window of 5 seconds, it will contain data for the past 5 seconds only.
2. Sliding Windows: These windows are overlapping and can have a fixed or variable size. For example, if you have a sliding window of 5 seconds with a slide of 1 second, it means that every 1 second, a new window of the past 5 seconds will be created.

Windowing with Hazelcast Jet

To use windowing in Hazelcast Jet, you need to define a pipeline that includes a source, windowing transformation, and a sink. Let’s look at an example of sliding windowing.

import com.hazelcast.jet.Jet;
import com.hazelcast.jet.JetInstance;
import com.hazelcast.jet.pipeline.Pipeline;
import com.hazelcast.jet.pipeline.SlidingWindowDefinition;
import com.hazelcast.jet.pipeline.WindowDefinition;
import com.hazelcast.jet.pipeline.WindowGroupAggregateBuilder;

public class WindowingExample {

    public static void main(String[] args) {
        JetInstance jet = Jet.newJetInstance();

        Pipeline pipeline = Pipeline.create();

        pipeline.drawFrom(/* your source */)
                .groupingKey(k -> k)
                .window(WindowDefinition.sliding(5000, 1000))
                .aggregate(/* your aggregate function */)
                .drainTo(/* your sink */);

        jet.newJob(pipeline).join();
    }
}

In the above example, we create a Hazelcast Jet instance and define a pipeline. We draw data from a source, group it by a key, specify a sliding window of 5000 milliseconds with a slide of 1000 milliseconds, apply an aggregate function, and finally drain the results to a sink.

Conclusion

Hazelcast Jet provides powerful windowing capabilities that enable you to efficiently process and analyze data in a distributed environment. In this blog post, we explored how to use windowing in Hazelcast Jet with Java applications. By using windowing, you can perform computations on sliding or tumbling intervals of data, allowing you to gain insights and make real-time decisions based on time or count-based windows.

#HazelcastJet #Java