A Java source-to-image application skeleton for using Apache Spark and Kafka on OpenShift.
This application will simply read messages from a Kafka topic, and the write those messages back out to a second topic. It will achieve this using Spark's streaming utilities for Kafka.
-
OpenShift - this application is designed for use on OpenShift, you can find great documentation and starter guides on their website.
-
Apache Kafka - because this application requires a Kafka broker to read from and write to, you will need to a broker deployed and a source of information. The Strimzi project provides some great documentation and manifests for running Kafka on OpenShift.
To help accelerate work with Kafka, here are a few applications to help:
-
Emitter - this is a skeleton to publish text information on a Kafka topic.
-
Listener - this is a skeleton to log all messages from a Kafka topic.
As this project utilizes Spark, it will be easiest to consume on OpenShift by using the RADanalytics tooling. The source-to-image nature of this application will require that a Spark cluster is available. The shortest path to making that connection is to use the automatically spawned Spark clusters that are created by the Oshinko project source-to-image utilities. Please see that documentation for more information about this process.
-
see the radanalytics.io Get Started page for instructions on installing that tooling
-
launch the skeleton with the following command:
oc new-app --template oshinko-java-spark-build-dc \ -p APPLICATION_NAME=skeleton \ -p GIT_URI=https://github.com/bones-brigade/kafka-spark-java \ -p APP_MAIN_CLASS=org.bonesbrigade.skeletons.kafkasparkopenshift.App \ -p SPARK_OPTIONS='--packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.3.0 --conf spark.jars.ivy=/tmp/.ivy2' \ -e KAFKA_BROKERS=kafka:9092 \ -e KAFKA_IN_TOPIC=topic1 \ -e KAFKA_OUT_TOPIC=topic2
In this example, our application will subscribe to messages on the Kafka topic
topic1
, and it will publish messages on the topic topic2
using the broker
at kafka:9092
.