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catalyst-optimizer

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An experimental investigation into Apache Spark's Catalyst optimizer, exploring when it optimizes effectively, what defeats it, and when optimization itself adds overhead. Through six controlled experiments, we analyzed predicate pushdown, join reordering, rule criticality, and algebraic equivalence, using PySpark in Google Colab.

  • Updated Jul 23, 2026
  • Jupyter Notebook

A comprehensive learning repository for Apache Spark and PySpark, covering core architecture, Catalyst optimizer, DataFrame operations, window functions, and performance optimization. Includes hands-on examples and real analytical projects.

  • Updated Oct 1, 2026

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