SCALA-SPARK.md

Introduction

This section will show how you can use your scala Spark application and run it in CDAP. The procedure is the same when compared to what was done for Java.

Getting Started

• Package

  cd sparkpi-scala
  mvn clean package

• Deploy sparkpi-1.0.0.jar in CDAP as a plugin.

  curl -w"\n" -X POST "localhost:11015/v3/namespaces/default/artifacts/sparkpi-program" \
    -H 'Artifact-Plugins: [ { "name": "SparkPi", "type": "sparkprogram", "className": "com.example.spark.SparkPi" }]' \
    -H "Artifact-Version: 1.0.0" \
    -H "Artifact-Extends: system:cdap-notifiable-workflow[1.0.0, 1.0.0]" \
    --data-binary @/PATH/TO/sparkpi-1.0.0.jar

• Create CDAP Application with the plugin just deployed.

  curl -v "localhost:11015/v3/namespaces/default/apps/SparkPiApp" -X PUT -d @app.json

where app.json contains the configurations which are used to configure the applications.

  {
    "artifact": {
      "name": "cdap-notifiable-workflow",
      "version": "1.0.0",
      "scope": "system"
    },
    "config": {
      "plugin": {
        "name": "SparkPi",
        "type": "sparkprogram",
        "artifact": {
          "name": "sparkpi-program",
          "scope": "user",
          "version": "1.0.0"
        }
      },

      "notificationEmailSender": "sender@example.domain.com",
      "notificationEmailIds": ["recipient@example.domain.com"],
      "notificationEmailSubject": "[Critical] Workflow execution failed.",
      "notificationEmailBody": "Execution of Workflow running the SparkPi program failed."
    }
  }

At this point SparkPiApp application should be created in CDAP.

• Run the NotifiableWorkflow program in the SparkPiApp. main method of the SparkPi program expects number of slices as an input argument. This argument can be supplied to the NotifiableWorkflow program through program.args runtime argument as

  curl -w"\n" -X POST "localhost:11015/v3/namespaces/default/apps/SparkPiApp/workflows/NotifiableWorkflow/start" \
    -d '{"program.args": "3"}'

• Similar to WordCount, NotifiableWorkflow in SparkPiApp can be scheduled to run at a desired interval.