intelsdi-x/openshift-spark

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This project will no longer be maintained by Intel.

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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.

Build inputs

The OpenShift method can take either local files or a URL as build input. For the s2i method, local files are required. Here is an example which downloads an Apache Spark distribution to a local 'build-input' directory (including the sha512 file is optional).

$ mkdir build-input
$ wget https://archive.apache.org/dist/spark/spark-2.4.0/spark-2.4.0-bin-hadoop2.7.tgz -O build-input/spark-2.4.0-bin-hadoop2.7.tgz
$ wget https://archive.apache.org/dist/spark/spark-2.4.0/spark-2.4.0-bin-hadoop2.7.tgz.sha512 -O build-input/spark-2.4.0-bin-hadoop2.7.tgz.sha512

Optionally, your build-input directory may contain a modify-spark directory. The structure of this directory should be parallel to the structure of the top-level directory in the Spark distribution tarball. During the installation, the contents of this directory will be copied to the Spark installation using rsync, allowing you to add or overwrite files. To add my.jar to Spark, for example, put it in build-input/modify-spark/jars/my.jar

Running the image completion

To complete the Python 2.7 image using the s2i tool

$ 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-2.4.0/spark-2.4.0-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