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/>
Av. Brigadeiro Faria Lima, 3900
8th floor
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