README.md

layout	title
global	Spark on Kubernetes Development

Kubernetes is a framework for easily deploying, scaling, and managing containerized applications. It would be useful for a user to run their Spark jobs on a Kubernetes cluster alongside their other Kubernetes-managed applications. For more about the motivations for adding this feature, see the umbrella JIRA ticket that tracks this project: SPARK-18278.

This submodule is an initial implementation of allowing Kubernetes to be a supported cluster manager for Spark, along with Mesos, Hadoop YARN, and Standalone. This document provides a summary of important matters to keep in mind when developing this feature.

Building Spark with Kubernetes Support

To build Spark with Kubernetes support, use the kubernetes profile when invoking Maven. For example, to simply compile the Kubernetes core implementation module along with its dependencies:

build/mvn compile -Pkubernetes -pl resource-managers/kubernetes/core -am -DskipTests

If this is the first time you compile the Kubernetes core implementation module, run the following command to install the dependencies and compile:

build/mvn install -Pkubernetes -pl resource-managers/kubernetes/core -am -DskipTests

To build a distribution of Spark with Kubernetes support, use the dev/make-distribution.sh script, and add the kubernetes profile as part of the build arguments. Any other build arguments can be specified as one would expect when building Spark normally. For example, to build Spark against Hadoop 2.7 and Kubernetes:

dev/make-distribution.sh --tgz -Phadoop-2.7 -Pkubernetes

Kubernetes Code Modules

Below is a list of the submodules for this cluster manager and what they do.

• core: Implementation of the Kubernetes cluster manager support.
• integration-tests: Integration tests for the project.
• docker-minimal-bundle: Base Dockerfiles for the driver and the executors. The Dockerfiles are used for integration tests as well as being provided in packaged distributions of Spark.
• integration-tests-spark-jobs: Spark jobs that are only used in integration tests.
• integration-tests-spark-jobs-helpers: Dependencies for the spark jobs used in integration tests. These dependencies are separated out to facilitate testing the shipping of jars to drivers running on Kubernetes clusters.

Running the Kubernetes Integration Tests

Note that the integration test framework is currently being heavily revised and is subject to change.

Note that currently the integration tests only run with Java 8.

Running any of the integration tests requires including kubernetes-integration-tests profile in the build command. In order to prepare the environment for running the integration tests, the pre-integration-test step must be run in Maven on the resource-managers/kubernetes/integration-tests module:

build/mvn pre-integration-test -Pkubernetes -Pkubernetes-integration-tests -pl resource-managers/kubernetes/integration-tests -am -DskipTests

Afterwards, the integration tests can be executed with Maven or your IDE. Note that when running tests from an IDE, the pre-integration-test phase must be run every time the Spark main code changes. When running tests from the command line, the pre-integration-test phase should automatically be invoked if the integration-test phase is run.

After the above step, the integration test can be run using the following command:

build/mvn integration-test \
    -Pkubernetes -Pkubernetes-integration-tests \
    -pl resource-managers/kubernetes/integration-tests -am

Running against an arbitrary cluster

In order to run against any cluster, use the following:

build/mvn integration-test \
    -Pkubernetes -Pkubernetes-integration-tests \
    -pl resource-managers/kubernetes/integration-tests -am
    -DextraScalaTestArgs="-Dspark.kubernetes.test.master=k8s://https://<master> -Dspark.docker.test.driverImage=<driver-image> -Dspark.docker.test.executorImage=<executor-image>"

Preserve the Minikube VM

The integration tests make use of Minikube, which fires up a virtual machine and setup a single-node kubernetes cluster within it. By default the vm is destroyed after the tests are finished. If you want to preserve the vm, e.g. to reduce the running time of tests during development, you can pass the property spark.docker.test.persistMinikube to the test process:

build/mvn integration-test \
    -Pkubernetes -Pkubernetes-integration-tests \
    -pl resource-managers/kubernetes/integration-tests -am \
    -DextraScalaTestArgs=-Dspark.docker.test.persistMinikube=true

Usage Guide

See the usage guide for more information.