question regarding adding a pipeline in datahub. W...
# ingestion
s
question regarding adding a pipeline in datahub. We have a pipeline which consists of AWS Kinesis, S3, Lamdba, redis channels, python processing applications etc. Probably a few more things. I was thinking of documenting this pipeline through adding the lineage in datahub. I think the following would be required • some way to represent redis channels • some way to represent Kinesis streams • some way to represent generic processors - currently only airflow seems to be shown in pipelines. I was thinking we can model redis channels and kinesis streams as datasets. Is there any limitation currently in the model to represent generic processors - like AWS lambda or python apps? I was thinking these could be tasks in datahub. Has anyone tried representing processing jobs outside airflow in datahub? Any feedback of how that went would be helpful.
plus1 4
h
There is also the
DataProcess
which is not bound to a flow in the same way as datajobs.
Aha, it seems to be "deprecated".
But for example Kafka connectors are modeled as jobs (check the
metadata-ingestion
source)
But I feel it's a bit artificial to force a "flow" on that. The generic DataProcess would have been good for cases like this.
b
I feel like Data Process should represent a specific instance of a Task
Which would need a flow nonetheless
It's a bit unfortunate that we've forced Data Tasks to be associated with a parent flow..
One thing we were considering is an "urn v2" which would address this issue (among others) in our urns
s
Seems like a feature request then. I will add it in the relevant channel for everyone's reference