Agent skill · Data & Analytics

spark-optimization

Optimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.

Nick44,414★ · +328/wk · 1 repos on radarProfile →
claude-codecodexcursorMIT
Install
npx skills add sickn33/agentic-awesome-skills --skill spark-optimization --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 13 KB
Bundled scripts: none
Path: skills/spark-optimization/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 44,414 · +328 this week
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Apache Spark Optimization Production patterns for optimizing Apache Spark jobs including partitioning strategies, memory management, shuffle optimization, and performance tuning. ## Do not use this skill when - The task is unrelated to apache spark optimization - You need a different domain or tool outside this scope ## Instructions - Clarify goals, constraints, and required inputs. - Apply relevant best practices and validate outcomes. - Provide actionable steps and verification. - If detailed examples are required, open `resources/implementation-playbook.md`. ## Use this skill when - Optimizing slow Spark jobs - Tuning memory and executor configuration - Implementing efficient partitioning strategies - Debugging Spark performance issues - Scaling Spark pipelines for large datasets - Reducing shuffle and data skew ## Core Concepts ### 1. Spark Execution Model ``` Driver Program ↓ Job (triggered by action) ↓ Stages (separated by shuffles) ↓ Tasks (one per partition) ``` ### 2. Key Performance Factors | Factor | Impact | Solution | |--------|--------|----------| | **Shuffle** | Network I/O, disk I/O | Minimize wide transformations | | **Data Skew** | Uneven task duration | Salting

What's inside
Steps it walks through
  1. Do not use this skill when
  2. Instructions
  3. Use this skill when
  4. Core Concepts
  5. 1. Spark Execution Model
  6. 2. Key Performance Factors
  7. Quick Start
  8. Patterns
  9. Pattern 1: Optimal Partitioning
  10. Pattern 2: Join Optimization
  11. Pattern 3: Caching and Persistence
  12. Pattern 4: Memory Tuning
  13. Pattern 5: Shuffle Optimization
  14. Pattern 6: Data Format Optimization
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About this skill
What does the spark-optimization skill do?

Optimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.

How do I install it?

Run `npx skills add sickn33/agentic-awesome-skills --skill spark-optimization --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From sickn33/agentic-awesome-skills, a repository with 44,414 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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