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Use this skill when writing PySpark code. Provides PySpark best practices for manageability, testability, and performance including DataFrame patterns, caching strategies, testing approaches, and deployment configurations.
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SOC 職業分類に基づく
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| name | pyspark-coding |
| description | Use this skill when writing PySpark code. Provides PySpark best practices for manageability, testability, and performance including DataFrame patterns, caching strategies, testing approaches, and deployment configurations. |
| version | 1.0.0 |
Comprehensive PySpark development practices for manageability, testability, and high performance.
Use this skill when:
| Reference | Read when you need to… |
|---|---|
fundamentals.md | Start a new PySpark project — DataFrame vs RDD decision, code structure, testability patterns, SparkSession management |
performance.md | Optimize PySpark jobs — caching/persistence strategies, join optimization, partitioning, file format choices, I/O patterns |
testing-and-deployment.md | Set up PySpark testing — local dev vs cluster configs, parallelism tuning, executor settings, deployment practices |
