This document is for an old version of the former Hazelcast IMDG product.

We've combined the in-memory storage of IMDG with the stream processing power of Jet to bring you an all new platform: Hazelcast 5.0

Use the following links to try it:

In this section we'll get you started using Hazelcast Jet. We'll show you how to set up a Java project with the proper dependencies and a quick Hello World example to verify your setup.

Requirements

In the good tradition of Hazelcast products, Jet is distributed as a JAR with no other dependencies. It requires JRE version 8 or higher to run.

Using Maven and Gradle

The easiest way to start using Hazelcast Jet is to add it as a dependency to your project.

Hazelcast Jet is published on the Maven repositories. Add the following lines to your pom.xml:

<dependencies>
  <dependency>
    <groupId>com.hazelcast.jet</groupId>
    <artifactId>hazelcast-jet</artifactId>
    <version>0.5</version>
  </dependency>
</dependencies>

If you prefer to use Gradle, execute the following command:

compile 'com.hazelcast.jet:hazelcast-jet:0.5'

Downloading

Alternatively you can download the latest distribution package of Hazelcast Jet and add the hazelcast-jet-<version>.jar file to your classpath.

Distribution Package

The distribution package contains the following scripts to help you get started with Hazelcast Jet:

  • bin/start-jet.sh and bin/start-jet.bat start a new Jet member in the current directory.
  • bin/stop-jet.sh and bin/stop-jet.bat stop the member started in the current directory.
  • bin/submit-jet.sh and bin/submit-jet.bat submit a Jet computation job that was packaged in a self-contained JAR file.
  • bin/cluster.sh provides basic functionality for Hazelcast cluster manager, such as changing the cluster state, shutting down the cluster or forcing the cluster to clean its persisted data.

Verify Your Setup

You can verify your setup by running this simple program. It processes the contents of a Hazelcast IList that contains lines of text, finds the number of occurrences of each word in it, and stores its results in a Hazelcast IMap. In a distributed computation job the input and output cannot be simple in-memory structures like a Java List; they must reside in the cluster so any member can access them. This is why we use Hazelcast structures.

import com.hazelcast.jet.Jet;
import com.hazelcast.jet.JetInstance;
import com.hazelcast.jet.Pipeline;
import com.hazelcast.jet.Sinks;
import com.hazelcast.jet.Sources;

import java.util.List;
import java.util.Map;

import static com.hazelcast.jet.Traversers.traverseArray;
import static com.hazelcast.jet.aggregate.AggregateOperations.counting;
import static com.hazelcast.jet.function.DistributedFunctions.wholeItem;

public class HelloWorld {
    public static void main(String[] args) throws Exception {
        // Create the specification of the computation pipeline. Note that it is
        // a pure POJO: no instance of Jet is needed to create it.
        Pipeline p = Pipeline.create();
        p.drawFrom(Sources.<String>list("text"))
         .flatMap(word -> traverseArray(word.toLowerCase().split("\\W+")))
         .filter(word -> !word.isEmpty())
         .groupBy(wholeItem(), counting())
         .drainTo(Sinks.map("counts"));

        // Start Jet, populate the input list
        JetInstance jet = Jet.newJetInstance();
        try {
            List<String> text = jet.getList("text");
            text.add("hello world hello hello world");
            text.add("world world hello world");

            // Perform the computation
            jet.newJob(p).join();

            // Check the results
            Map<String, Long> counts = jet.getMap("counts");
            System.out.println("Count of hello: " + counts.get("hello"));
            System.out.println("Count of world: " + counts.get("world"));
        } finally {
            Jet.shutdownAll();
        }
    }
}

You should expect to see a lot of logging output from Jet (sent to stderr) and two lines on stdout:

Count of hello: 4
Count of world: 5