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It includes my notes and experiments while exploring **core Spark concepts, transformations, actions, DataFrame API, and more**.\n\n---\n\n## 🚀 What is PySpark?\n\n**PySpark** is the Python API for **Apache Spark**, a powerful open-source distributed computing engine used for large-scale data processing and analytics. PySpark allows you to leverage the power of distributed computing using Python.\n\n---\n\n## 📘 Topics Covered\n\n- ✅ Introduction to Spark \u0026 PySpark  \n- ✅ SparkContext \u0026 SparkSession  \n- ✅ RDDs (Resilient Distributed Datasets)  \n- ✅ DataFrames \u0026 Datasets  \n- ✅ Transformations vs Actions  \n- ✅ Reading/Writing: JSON, CSV, Parquet  \n- ✅ PySpark SQL \u0026 Queries  \n- ✅ GroupBy, Aggregations, Joins  \n- ✅ Handling Nulls \u0026 Missing Data  \n- ✅ User-Defined Functions (UDFs)  \n- ✅ Window Functions  \n- ✅ Data Partitioning \u0026 Performance Optimization  \n- ✅ Intro to MLlib (Optional)\n\n---\n\n## ✍️ How I Learn\nI follow a \"Learn by Doing\" approach.\nEach notebook contains:\n\n✅ Detailed explanations\n\n🧪 Hands-on code examples\n\n📌 Real-world case studies\n\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fneha-dev-dot%2Fpyspark-tutorial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fneha-dev-dot%2Fpyspark-tutorial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fneha-dev-dot%2Fpyspark-tutorial/lists"}