Process 10 TB in 10 Minutes with Apache Spark! | spark-submit Tuning Guide for Massive Datasets

🚀 Want to learn how to process 10 Terabytes of data in under 10 minutes using Apache Spark? In this video, I walk you through an end-to-end Spark tuning strategy—perfect for big data engineers, data scientists, and cloud architects. You’ll learn: How Spark handles large files with 128 MB partitions How to calculate executor memory, cores, and number of executors How to use spark-submit to optimize for performance How to estimate required CPU and RAM Whether it's really possible to meet a strict 10-minute SLA 📌 Whether you're working with AWS EMR, Databricks, or on-premise clusters, this tutorial will give you practical, real-world insight into Apache Spark performance tuning. ✅ Don't forget to LIKE, SUBSCRIBE, and SHARE if you find this helpful! 🔔 Stay tuned for more big data tips and tutorials every week! 📧 For collaborations or project consulting, reach out at: [email protected] #ApacheSpark #BigData #SparkSubmit #DataEngineering #SparkOptimization #Databricks #AWSGlue #DataPipeline #BigDataEngineering #PerformanceTuning #PySpark #CloudComputing #DataEngineer #SparkTips #SparkJob