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spark-troubleshooting

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UpdatedApril 6, 2026 at 09:22

Troubleshoot Spark applications on AWS EMR, Glue, and SageMaker - analyze failures, identify bottlenecks, get code recommendations. Use when mentioning Spark, EMR, PySpark, Glue Spark, or Spark troubleshooting.

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whchoi98

whchoi98/aws-skills-for-claude-code

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Related occupationsSOC

Based on SOC occupation classification

Software DevelopersComputer and Mathematical Occupations·SOC 15-1252

SKILL.md

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name	spark-troubleshooting
description	Troubleshoot Spark applications on AWS EMR, Glue, and SageMaker - analyze failures, identify bottlenecks, get code recommendations. Use when mentioning Spark, EMR, PySpark, Glue Spark, or Spark troubleshooting.

Spark Troubleshooting Agent

Key Capabilities

Failure analysis for PySpark and Scala jobs
Root cause identification via telemetry correlation
Performance diagnostics and bottleneck detection
Code recommendations and optimizations
Supports EMR EC2, EMR Serverless, Glue, SageMaker

MCP Servers

sagemaker-unified-studio-mcp-troubleshooting — Failure analysis
sagemaker-unified-studio-mcp-code-rec — Code recommendations

Best Practices

Provide specific identifiers (cluster ID, application ID, job ID)
Describe symptoms clearly (observed vs expected)
Include exact error messages
Specify platform (EMR EC2, EMR Serverless, Glue, SageMaker)

Setup

Requires CloudFormation stack deployment for IAM role. See AWS docs for setup.

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name	spark-troubleshooting
description	Troubleshoot Spark applications on AWS EMR, Glue, and SageMaker - analyze failures, identify bottlenecks, get code recommendations. Use when mentioning Spark, EMR, PySpark, Glue Spark, or Spark troubleshooting.

Spark Troubleshooting Agent

Key Capabilities

Failure analysis for PySpark and Scala jobs
Root cause identification via telemetry correlation
Performance diagnostics and bottleneck detection
Code recommendations and optimizations
Supports EMR EC2, EMR Serverless, Glue, SageMaker

MCP Servers

sagemaker-unified-studio-mcp-troubleshooting — Failure analysis
sagemaker-unified-studio-mcp-code-rec — Code recommendations

Best Practices

Provide specific identifiers (cluster ID, application ID, job ID)
Describe symptoms clearly (observed vs expected)
Include exact error messages
Specify platform (EMR EC2, EMR Serverless, Glue, SageMaker)

Setup

Requires CloudFormation stack deployment for IAM role. See AWS docs for setup.