PySpark RDD Operations – Practice Notebook

This repository contains a Jupyter Notebook that demonstrates basic operations using Apache Spark RDDs (Resilient Distributed Datasets).
It covers the creation of RDDs, basic actions, and transformations to help understand Spark’s distributed data processing model.

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📑 Contents

🔹 Spark Initialization

• Creating a SparkSession and SparkContext.

🔹 RDD Creation

• Generating an RDD from a NumPy array of numbers (1–49).

🔹 Basic RDD Actions

• Sum
• Average
• Count
• Minimum
• Maximum

🔹 RDD Transformations

• Filtering even numbers.
• Mapping values (e.g., doubling numbers).
• Collecting results for inspection.

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🎯 Learning Goals

• Understand how Spark RDDs are created and manipulated.
• Practice fundamental RDD operations (actions vs transformations).
• Build intuition for distributed data processing.