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In this video, we dive deep into the Architecture of Apache Spark, one of the most powerful open-source data processing frameworks used in Big Data and Machine Learning. 🚀

You’ll learn:
✅ What is Apache Spark?
✅ Key components of Spark architecture — Driver, Executors, Cluster Manager, and SparkContext
✅ How Spark works internally (Job → Stage → Task flow)
✅ Difference between RDD, DataFrame, and Dataset
✅ Real-world use cases of Apache Spark

Whether you’re a Data Engineer, Data Analyst, or Big Data enthusiast, this video will help you understand how Spark processes data efficiently in distributed environments.

📊 Topics Covered:
00:00 – Introduction
01:30 – What is Apache Spark?
03:10 – Spark Architecture Overview
06:00 – Components of Spark
09:00 – Spark Execution Flow
12:00 – Real-time Examples
14:00 – Summary

💡 Tools & Technologies:
Apache Spark | Hadoop | Scala | Python | Big Data | Cluster Computing

📚 Hashtags:
#ApacheSpark #BigData #DataEngineering #SparkArchitecture #Hadoop #DataAnalytics #MachineLearning