Apache Spark Data Processing
Processes large datasets efficiently using Apache Spark for data transformation, analysis, and machine learning tasks.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add apache-spark-data-processing npx -- -y @trustedskills/apache-spark-data-processing
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"apache-spark-data-processing": {
"command": "npx",
"args": [
"-y",
"@trustedskills/apache-spark-data-processing"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill enables AI agents to perform data processing tasks using Apache Spark, a distributed computing framework for large-scale data analytics. It allows agents to execute transformations, aggregations, and computations on structured datasets across distributed systems.
When to use it
- Processing large datasets that exceed single-machine memory capacity
- Performing ETL (Extract, Transform, Load) operations on distributed clusters
- Running parallelized computations across multiple nodes for efficiency
- Analyzing petabyte-scale data warehouses or data lakes
Key capabilities
- Distributed data processing and computation
- Large-scale dataset manipulation and transformation
- Cluster-based analytics execution
- Integration with Apache Spark ecosystem components
Example prompts
- "Process this CSV file using Apache Spark to calculate aggregate statistics"
- "Transform the distributed dataset by filtering records where revenue exceeds threshold"
- "Run a Spark SQL query to join multiple tables for customer analysis"
Tips & gotchas
Ensure you have access to a Spark cluster or environment before attempting large-scale data operations. This skill
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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