3cff38ff94
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).
127 lines
3.6 KiB
Markdown
127 lines
3.6 KiB
Markdown
---
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layout: "guides"
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page_title: "Apache Spark Integration - Customizing Applications"
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sidebar_current: "guides-spark-customizing"
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description: |-
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Learn how to customize the Nomad job that is created to run a Spark
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application.
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---
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# Customizing Applications
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There are two ways to customize the Nomad job that Spark creates to run an
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application:
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- Use the default job template and set configuration properties
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- Use a custom job template
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## Using the Default Job Template
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The Spark integration will use a generic job template by default. The template
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includes groups and tasks for the driver, executors and (optionally) the
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[shuffle service](/guides/spark/dynamic.html). The job itself and the tasks that
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are created have the `spark.nomad.role` meta value defined accordingly:
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```hcl
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job "structure" {
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meta {
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"spark.nomad.role" = "application"
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}
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# A driver group is only added in cluster mode
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group "driver" {
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task "driver" {
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meta {
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"spark.nomad.role" = "driver"
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}
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}
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}
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group "executors" {
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count = 2
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task "executor" {
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meta {
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"spark.nomad.role" = "executor"
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}
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}
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# Shuffle service tasks are only added when enabled (as it must be when
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# using dynamic allocation)
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task "shuffle-service" {
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meta {
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"spark.nomad.role" = "shuffle"
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}
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}
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}
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}
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```
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The default template can be customized indirectly by explicitly [setting
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configuration properties](/guides/spark/configuration.html).
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## Using a Custom Job Template
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An alternative to using the default template is to set the
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`spark.nomad.job.template` configuration property to the path of a file
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containing a custom job template. There are two important considerations:
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* The template must use the JSON format. You can convert an HCL jobspec to
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JSON by running `nomad run -output <job.nomad>`.
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* `spark.nomad.job.template` should be set to a path on the submitting
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machine, not to a URL (even in cluster mode). The template does not need to
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be accessible to the driver or executors.
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Using a job template you can override Spark’s default resource utilization, add
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additional metadata or constraints, set environment variables, add sidecar
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tasks and utilize the Consul and Vault integration. The template does
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not need to be a complete Nomad job specification, since Spark will add
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everything necessary to run your the application. For example, your template
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might set `job` metadata, but not contain any task groups, making it an
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incomplete Nomad job specification but still a valid template to use with Spark.
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To customize the driver task group, include a task group in your template that
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has a task that contains a `spark.nomad.role` meta value set to `driver`.
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To customize the executor task group, include a task group in your template that
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has a task that contains a `spark.nomad.role` meta value set to `executor` or
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`shuffle`.
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The following template adds a `meta` value at the job level and an environment
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variable to the executor task group:
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```hcl
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job "template" {
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meta {
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"foo" = "bar"
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}
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group "executor-group-name" {
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task "executor-task-name" {
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meta {
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"spark.nomad.role" = "executor"
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}
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env {
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BAZ = "something"
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}
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}
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}
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}
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```
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## Order of Precedence
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The order of precedence for customized settings is as follows:
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1. Explicitly set configuration properties.
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2. Settings in the job template (if provided).
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3. Default values of the configuration properties.
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## Next Steps
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Learn how to [allocate resources](/guides/spark/resource.html) for your Spark
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applications.
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