working-with-large-data
OfficialProcess large data on HPC without memory limits.
Authoryale-som-hpc
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Process data too large to fit in memory on the Yale SOM HPC cluster by using columnar formats, lazy evaluation, and on-disk processing with Parquet, DuckDB, Polars, and Arrow.
Core Features & Use Cases
- Out-of-core processing: operate on datasets larger than RAM by streaming and chunking.
- Format-agnostic pipelines: leverage Parquet, Arrow, and DuckDB for efficient data workflows.
- Scalable HPC workflows: integrate with Slurm-backed clusters to run chunked data pipelines.
Quick Start
Launch a Slurm job to read Parquet data and process it efficiently with DuckDB or Polars in chunked steps.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
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Please help me install this Skill: Name: working-with-large-data Download link: https://github.com/yale-som-hpc/claude-code-marketplace/archive/main.zip#working-with-large-data Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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