Pandas on OpenShift v3

Question

Now that OpenShift Online V2 has announced its end of service, I am looking to migrate my Python application to OpenShift Online V3, aka OpenShift NextGen. Pandas is a requi

Answer 1

It is going to be one of two things.

Either compiling Pandas is a huge memory hog, possibly caused by the compiler hitting some pathological case. Or, the size of the generated image at that point exceeds an internal limit and so runs out of disk space allocated.

If it was memory, you would need to increase the memory allocated to the build pod. By default in Online this is 512Mi.

To increase the limit you will need to edit the YAML/JSON for the build configuration from the web console, or from the command line using oc edit.

For YAML, you need to add the following:

  resources:
    limits:
      memory: 1Gi

This is setting the field:

$ oc explain bc.spec.resources.limits FIELD: limits <object>

DESCRIPTION:
     Limits describes the maximum amount of compute resources allowed. More
     info: http://kubernetes.io/docs/user-guide/compute-resources/

The maximum is 1Gi. It appears an increase to this value does allow the build to complete, where as increasing it to 768Mi wasn't enough.

Do be aware that this takes memory away from the quota for compute-resources-timebound when running and since it is using it all during the build, other things you try and do at the same time could be held up.

FWIW, the image size on a local build, not in Online, only produced:

172.30.1.1:5000/mysite/osv3test              latest               f323d9b036f6        About an hour ago   910MB

Thus unless intermediary space used before things were cleaned up was an issue, it isn't an issue.

So increasing memory used for the build appears to be the answer.