Apache Spark Processing with AWS EMR | Data Engineering Project

In this comprehensive guide, we dive into the powerful world of AWS, focusing on how data engineers like you can harness the robust compute capabilities of Amazon Elastic Map Reduce (EMR). Whether you're new to cloud computing or looking to enhance your skills, this video is your one-stop resource for mastering EMR. Timestamps: 0:00 - Introduction 1:26 - Setting up EMR on AWS 13:59 - Setting up Cloud9 on AWS 23:00 - Setting Up a Spark Job with S3 24:30 - Submitting Jobs to EMR 31:08 - Visualizing the Process on EMR Spark and Hadoop UI 35:00 - Submitting to the Cluster with EMR Steps 37:45 - Results 🔔 Don't forget to subscribe and hit the bell icon to stay updated on our latest videos in cloud computing, data engineering, and more! Hashtags: #AWS #EMR #DataEngineering #CloudComputing #BigData #Spark #YarnCluster #AWSLearning #TechTutorial Tags: AWS, Amazon Web Services, EMR, Elastic Map Reduce, Data Engineering, Cloud Computing, Big Data, Spark, Yarn, AWS Tutorial, Data Processing, Cloud Technology, AWS Certification, Data Visualization 👍 Like, Share, and Comment: Your support means a lot! If you found this video helpful, please like, share, and comment below with your thoughts or any questions you might have. Resources EMR Documentation: https://docs.aws.amazon.com/emr/ Github: https://github.com/airscholar/EMR-for-data-engineers Stay Connected: 🌐 Visit our Website: datamasterylab.com 📸 Follow us on Instagram: https://www.instagram.com/airscholar/ 🐦 Tweet us on Twitter: https://twitter.com/datamasterylab 🔗 Connect with us on LinkedIn: https://www.linkedin.com/in/yusuf-ganiyu-b90140107