---
title: "Apache Spark DataFrame ETL Pipeline"
description: "Automates PySpark DataFrame transformations including schema inference, partition pruning, and Delta Lake merge operations. Integrates with AWS Glue Data Catalog and Apache Iceberg table formats for lakehouse architectures."
verification: "security_reviewed"
source: "https://github.com/apache/spark"
category:
  - "Data Extraction & Transformation"
framework:
  - "OpenClaw"
tool_ecosystem:
  github_repo: "apache/spark"
  github_stars: 43117
---

# Apache Spark DataFrame ETL Pipeline

Automates PySpark DataFrame transformations including schema inference, partition pruning, and Delta Lake merge operations. Integrates with AWS Glue Data Catalog and Apache Iceberg table formats for lakehouse architectures.

## Installation

Choose whichever fits your setup:

1. Copy this skill folder into your local skills directory.
2. Clone the repo and symlink or copy the skill into your agent workspace.
3. Add the repo as a git submodule if you manage shared skills centrally.
4. Install it through your internal provisioning or packaging workflow.
5. Download the folder directly from GitHub and place it in your skills collection.

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/spark-dataframe-etl-pipeline/)