radanalyticsio/openshift-spark repository overview

⁠Apache Spark images for OpenShift

This repository contains several files for building Apache Spark⁠ focused container images, targeted for usage on OpenShift Origin⁠.

By default, it will build the following images into your local Docker registry:

• openshift-spark, Apache Spark, Python 2.7
• openshift-spark-py36, Apache Spark, Python 3.6

For Spark versions, please see the image.yaml file.

⁠Instructions

⁠Build

⁠Prerequisites

• concreate tool from the cekit project⁠, this can be installed from pypi⁠.

⁠Procedure

Create all images and save them in the local Docker registry.

make

⁠Push

Tag and push the images to the designated reference.

make push SPARK_IMAGE=[REGISTRY_HOST[:REGISTRY_PORT]/]NAME[:TAG]

⁠Customization

There are several ways to customize the construction and build process. This project uses the GNU Make tool⁠ for the build workflow, see the Makefile for more information. For container specification and construction, the Container image creation tool concreate⁠ is used as the primary point of investigation, see the image.yaml file for more information.

⁠Partial images without an Apache Spark distribution installed

This repository also supports building 'incomplete' versions of the images which contain tooling for OpenShift but lack an actual Spark distribution. An s2i workflow can be used with these partial images to install a Spark distribution of a user's choosing. This gives users an alternative to checking out the repository and modifying build files if they want to run a custom Spark distribution. By default, the partial images built will be

• openshift-spark-inc, Apache Spark, Python 2.7
• openshift-spark-inc-py36, Apache Spark, Python 3.6

⁠Build

To build the partial images, use make with Makefile.inc

make -f Makefile.inc

⁠Push

Tag and push the images to the designated reference.

make -f Makefile.inc push SPARK_IMAGE=[REGISTRY_HOST[:REGISTRY_PORT]/]NAME[:TAG]

⁠Image Completion

To produce a final image, a source-to-image build must be performed which takes a Spark distribution as input. This can be done in OpenShift or locally using the s2i tool⁠ if it's installed. The final images created can be used just like the openshfit-spark and openshift-spark-py36 images described above.

To complete the Python 2.7 image using the s2i tool⁠

$ mkdir build_input
$ wget https://archive.apache.org/dist/spark/spark-2.3.0/spark-2.3.0-bin-hadoop2.7.tgz -O build_input/spark-2.3.0-bin-hadoop2.7.tgz
$ wget https://archive.apache.org/dist/spark/spark-2.3.0/spark-2.3.0-bin-hadoop2.7.tgz.md5 -O build_input/spark-2.3.0-bin-hadoop2.7.tgz.md5
$ s2i build build_input radanalyticsio/openshift-spark-inc openshift-spark

To complete the Python 2.7 image using OpenShift, for example:

$ oc new-build --name=openshift-spark --docker-image=radanalyticsio/openshift-spark-inc --binary
$ oc start-build openshift-spark --from-file=https://archive.apache.org/dist/spark/spark-2.3.0/spark-2.3.0-bin-hadoop2.7.tgz

(note that the value of `--from-file` could also be the `build_input` directory from the s2i example above)

This will write the completed image to an imagestream called openshift-spark in the current project

⁠A 'usage' command for all images

Note that all of the images described here will respond to a 'usage' command for reference. For example

$ docker run --rm openshift-spark:latest usage