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domino-distributed-computing

Skill

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 c

0Machine Learning

Install

git clone https://github.com/dominodatalab/domino-claude-plugin.git ~/.claude/skills/domino-distributed-computing

What is domino-distributed-computing?

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.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~78 tokens of context used while enabled, before you invoke anything

Documentation

README · ~4 min read

Domino Distributed Computing Skill

Description

This skill helps users work with distributed computing frameworks in Domino - Spark, Ray, and Dask clusters for scaling compute-intensive workloads.

Activation

Activate this skill when users want to:

  • Run Spark, Ray, or Dask clusters in Domino
  • Scale data processing or ML training
  • Configure distributed cluster settings
  • Understand when to use each framework

Supported Frameworks

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