distributed-computing
bydominodatalab· 23 skills
Work with distributed computing frameworks in Domino including Apache Spark, Ray, and Dask clusters. Covers cluster configuration, on-demand clusters, choosing between frameworks, PySpark usage, and scaling workloads. Use when processing large datasets, parallel ML training, or running distributed compute jobs.
How to install distributed-computing?
dominodatalab/domino-claude-plugin/distributed-computing
$npx -y skills add dominodatalab/domino-claude-plugin --skill distributed-computingInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/dominodatalab/domino-claude-plugin" --skill "dominodatalab/domino-claude-plugin/distributed-computing"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/dominodatalab/domino-claude-plugin" that are relevant to the current task. Run `npx skills add "https://github.com/dominodatalab/domino-claude-plugin"` and select the relevant skills, then follow their instructions.
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