This is a fork of Radanaytics openshift-spark. This has python 3.8 instead of 3.6.
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 3.8
For Spark versions, please see the image.yaml
file.
cekit
version 3.7.0 from the cekit project
Create all images and save them in the local Docker registry.
make
Tag and push the images to the designated reference.
make push SPARK_IMAGE=[REGISTRY_HOST[:REGISTRY_PORT]/]NAME[:TAG]
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 Evolution Kit cekit
is
used as the primary point of investigation, see the image.yaml
file for
more information.
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 3.8
To build the partial images, use make with Makefile.inc
make -f Makefile.inc
Tag and push the images to the designated reference.
make -f Makefile.inc push SPARK_IMAGE=[REGISTRY_HOST[:REGISTRY_PORT]/]NAME[:TAG]
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
image
described above.
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-3.0.0/spark-3.0.0-bin-hadoop3.2.tgz -O build-input/spark-3.0.0-bin-hadoop3.2.tgz
$ wget https://archive.apache.org/dist/spark/spark-3.0.0/spark-3.0.0-bin-hadoop3.2.tgz.sha512 -O build-input/spark-3.0.0-bin-hadoop3.2.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
To complete the image using the s2i tool
$ s2i build build-input radanalyticsio/openshift-spark-inc openshift-spark
To complete the 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-3.0.0/spark-3.0.0-bin-hadoop3.2.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
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