Hi Ricardo,
I am leaning towards option #2. We already do that with jupyterhub
images. @Landon
LaSmith <llasmith(a)redhat.com> and @Václav Pavlín <vasek(a)redhat.com> do you
have a preference?
Juana
On Mon, Aug 19, 2019 at 8:33 AM Ricardo Martinelli de Oliveira <
rmartine(a)redhat.com> wrote:
 Hi,
 I'm integrating Spark SQL Thrift server into ODH operator and I need to
 use a custom spark image (other than the RADAnalytics image) with
 additional jars to access Ceph/S3 buckets. Actually, both thrift server and
 the spark cluster will need this custom spark image in order to access the
 buckets.
 With that being said, I'd like to discuss some options to get this done. I
 am thinking about these options:
 1) Let the customer specify the custom image in the yaml file (this is
 already possible)
 2) Create that custom spark image and publish on quay.io opendarahub
 organization
 3) Add a buildconfig object and make operator create the custom build and
 set the image location into the deploymentconfig objects
 Although the third option automate everything and deliver the whole set
 with the custom image, there's this thing about supporting custom images
 within operators. We'd need to add a spark_version variable where the build
 could download the spark distribution corresponding to that version and the
 artifacts related and run the build. In the first option, we simply don't
 create the build objects and document that in order to use Thrift server in
 ODH operator, both spark cluster and thrift must use a custom spark image
 containing the jars needed to access Ceph/S3. At last, the middle term
 between both is option two, so we don't need to worry about delegate this
 task to the user or the operator.
 What do you think? What could be the best option for this scenario?
 --
 Ricardo Martinelli De Oliveira
 Data Engineer, AI CoE
 Red Hat Brazil <
https://www.redhat.com/>
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