open-nomad/website/source/guides/analytical-workloads/spark/customizing.html.md

layout	page_title	sidebar_current	description
guides	Apache Spark Integration - Customizing Applications	guides-analytical-workloads-spark-customizing	Learn how to customize the Nomad job that is created to run a Spark application.

Customizing Applications

There are two ways to customize the Nomad job that Spark creates to run an application:

• Use the default job template and set configuration properties
• Use a custom job template

Using the Default Job Template

The Spark integration will use a generic job template by default. The template includes groups and tasks for the driver, executors and (optionally) the shuffle service. The job itself and the tasks that are created have the spark.nomad.role meta value defined accordingly:

job "structure" {
  meta {
    "spark.nomad.role" = "application"
  }

  # A driver group is only added in cluster mode
  group "driver" {
    task "driver" {
      meta {
        "spark.nomad.role" = "driver"
      }
    }
  }

  group "executors" {
    count = 2
    task "executor" {
      meta {
        "spark.nomad.role" = "executor"
      }
    }

    # Shuffle service tasks are only added when enabled (as it must be when
    # using dynamic allocation)
    task "shuffle-service" {
      meta {
        "spark.nomad.role" = "shuffle"
      }
    }
  }
}

The default template can be customized indirectly by explicitly setting configuration properties.

Using a Custom Job Template

An alternative to using the default template is to set the spark.nomad.job.template configuration property to the path of a file containing a custom job template. There are two important considerations:

• The template must use the JSON format. You can convert an HCL jobspec to JSON by running nomad job run -output <job.nomad>.

• spark.nomad.job.template should be set to a path on the submitting machine, not to a URL (even in cluster mode). The template does not need to be accessible to the driver or executors.

Using a job template you can override Spark’s default resource utilization, add additional metadata or constraints, set environment variables, add sidecar tasks and utilize the Consul and Vault integration. The template does not need to be a complete Nomad job specification, since Spark will add everything necessary to run your the application. For example, your template might set job metadata, but not contain any task groups, making it an incomplete Nomad job specification but still a valid template to use with Spark.

To customize the driver task group, include a task group in your template that has a task that contains a spark.nomad.role meta value set to driver.

To customize the executor task group, include a task group in your template that has a task that contains a spark.nomad.role meta value set to executor or shuffle.

The following template adds a meta value at the job level and an environment variable to the executor task group:

job "template" {

  meta {
    "foo" = "bar"
  }

  group "executor-group-name" {

    task "executor-task-name" {
      meta {
        "spark.nomad.role" = "executor"
      }

      env {
        BAZ = "something"
      }
    }
  }
}

Order of Precedence

The order of precedence for customized settings is as follows:

1. Explicitly set configuration properties.
2. Settings in the job template (if provided).
3. Default values of the configuration properties.

Next Steps

Learn how to allocate resources for your Spark applications.