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HDF > Hadoop for Data Scientists & Analysts > Real World Examples

Superset in Trucking IoT on HDF

Deploying the Topology

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Deploying the Topology


Now that we know how to develop a Storm topology, let’s go over how to package it up into a JAR file and deploy it onto a cluster.


Packaging a JAR

In a terminal, navigate to where the Storm project root is located and run:

sbt assembly

This produces an uber jar, housing your topology and all of its dependencies. The jar is saved to /trucking-iot-demo-2/target/scala-2.11/truckingIot-assembly-0.3.2.jar. This gets uploaded to the cluster for deployment to Storm.

Note: Storm 1.1.0 enhances the way topologies are deployed, providing alternatives to using uber jars. Check out the Storm 1.1.0 release notes for more information.

Deploying to Storm

Note: If the jar from the previous section was built on your computer, you’ll have to copy it onto your cluster before running the next command.

On your cluster, run the following command:

storm jar trucking-iot-demo-2/target/scala-2.11/truckingIot-assembly-0.3.2.jar  com.orendainx.hortonworks.storm.topologies.KafkaToKafka

storm jar will submit the jar to the cluster. After uploading the jar, storm jar calls the main function of the class we specified (com.orendainx.hortonworks.storm.topologies.KafkaToKafka), which deploys the topology by way of the StormSubmitter class.


Congratulations! You now know about the role that Storm plays in a real-time data pipeline and how to create and deploy a topology from scratch.