stackabletech / stackabletech/spark-k8s-operator
Investigate hardware accelerated Spark
Open
Nobody has claimed this yet.
epic
- Dominant language
- Rust
- Stars
- 72
- Forks
- 4
- Avg merge
- 2d 15h
- Merged PRs (30d)
- 15
Description
Intel AVX instruction set
Intel OEP - Optimized Analytics Package
https://github.com/oap-project
https://github.com/oap-project/gazelle_plugin/blob/master/docs/User-Guide.md
NVidia RAPIDS
https://nvidia.github.io/spark-rapids/
Cloud how-to
- Google Kubernetes Engine (GKE)
- Amazon Elastic Kubernetes Service (EKS)
- Azure Kubernetes Service (AKS)
Articles
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
The issue names no source files, entry points, or tests. Start by reviewing the linked OAP, NVIDIA RAPIDS, and cloud GPU guides, then determine the operator changes and supported hardware-acceleration path required. Done would need a defined implementation scope and validation criteria, which the issue does not currently provide.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, azure, gcp, kubernetes, spark
- Domain
- cloud, data-engineering, distributed-systems, infrastructure, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 18/100