Caught some typos. Made units separate from the numbers 1GHz -> 1 GHz after talking to Nick about questions of style (this has the side effect of making future spell checking easier).
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guides | Apache Spark Integration - Customizing Applications | guides-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 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:
- Explicitly set configuration properties.
- Settings in the job template (if provided).
- Default values of the configuration properties.
Next Steps
Learn how to allocate resources for your Spark applications.