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Description:
In this video, we continue to learn about Spark Notebooks in Microsoft Fabric. We review the capabilities of Apache Spark within a Lakehouse using a sample dataset. Notebooks are a great tool for large-scale SQL, batch processing, streaming analytics, and machine-learning. The key advantage of Apache Spark is its speed, scalability, and performance. 📚 What you will learn in this video: - Read multiple files from a Lakehouse folder using PySpark. - Create a custom schema for data types. - Transform and analyze data using PySpark. 🕒 Timecodes: 00:00 - Introduction. 01:19 - Create a new Spark Notebook from the Lakehouse interface. 02:40 - Count a number of rows in a file. 03:08 - Read multiple files from a folder using PySpark. 04:20 - Create a custom schema for data types. 07:10 - Transform and analyze data to uncover top spending customers. 🔗 Useful links and resources: Sample files used in the video: https://buy.stripe.com/28EbJ2fjB4aG62H7Px8g23K Documentation: https://learn.microsoft.com/en-us/fabric/data-engineering/how-to-use-notebook 🤝 Let's Connect: LinkedIn: https://www.linkedin.com/company/centida/ Website: https://centida.com/ Centida GmbH 34 Kernenhofstrasse, Oberkirch 77704, Germany Email: info@centida.com 👍 If you found this video helpful, please give it a thumbs up, and consider subscribing to stay updated with our series. Your engagement helps us create more valuable content for the community.
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