stackabletech / stackabletech/spark-k8s-operator
Add support for deploying stand alone Spark clusters
Open
Nobody has claimed this yet.
type/feature-new
- Dominant language
- Rust
- Stars
- 72
- Forks
- 4
- Avg merge
- 2d 15h
- Merged PRs (30d)
- 15
Description
Description
Jupyter notebooks can connect to stand alone clusters. This allows for much better scalability when analyzing big data with Pyspark notebooks.
Acceptance
- A new custom resource describes stand alone clusters
- Stand alone clusters can be are provisioned with external dependencies
- Stand alone clusters can be connected with history servers
- ...
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files or tests are named. Start by reviewing the existing Spark operator resources and deployment flow; done means a standalone-cluster custom resource supports provisioning with external dependencies and connections to history servers.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- kubernetes, rust, spark
- Domain
- data-engineering, distributed-systems, infrastructure
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100