kubeflow / kubeflow/spark-operator
Define update semantics for SparkApplication and SparkConnect specs
Open
- Dominant language
- Python
- Stars
- 3.2k
- Forks
- 1.5k
- Avg merge
- 5d 10h
- Merged PRs (30d)
- 13
Description
The goal of this issue is to define the update semantics for the SparkApplication and SparkConnect specs as they handle updates inconsistently at this time.
SparkApplication does a full restart for spec updates whereas SparkConnect does not have any such behavior.
Contributor guide
Research direction
Start by comparing how SparkApplication and SparkConnect currently handle spec updates. Define the expected update semantics, including whether spec changes should trigger a full restart, and document the consistent behavior that both resources should follow.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- kubernetes, spark
- Domain
- backend-api-design, devops, distributed-systems
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100