#️⃣ #databricks #DataEngineering #AzureDataFactory
In this video, we dive deep into User Defined Functions (UDFs) in Databricks and learn how to extend PySpark with custom logic. You’ll understand:
✅ What is a UDF in Databricks & when to use it
✅ Difference between UDF, Pandas UDF, and built-in functions
✅ Step-by-step coding examples in PySpark
✅ Performance considerations & best practices
✅ Real-world use cases (data cleaning, transformations, custom business rules)
👉 Perfect for Data Engineers & Spark developers preparing for projects or interviews!
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📽️ Chapters
⏱️ 0:00 - Introduction
📚 Playlists You’ll Love:
1️⃣ AWS Data Engineer:
🔗 • AWS DATA ENGINEER
2️⃣ Azure Data Engineer Playlist:
🔗 • Complete azure data engineer Course | azur...
3️⃣ SQL Playlist:
🔗 • SQL Playlist
6️⃣ PySpark Playlist:
🔗 • Pyspark Tutorial
5️⃣ Azure Data Factory Playlist:
🔗 • Azure Data Factory
4️⃣ Python Playlist:
🔗 • Python Tutorial
7️⃣ Azure Data Engineer Projects:
🔗 • Data Engineer Project
8️⃣ Data Engineer Interview Prep:
🔗 • Data Engineer Interview Playlist
📣 Connect with Me:
💬 Join the conversation on Telegram:
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🙏 Hope you enjoyed the video and learned something valuable!
📺 See you in the next one — until then, Bye-Bye 👋
🔖 Tags:
#dataengineer #azuredataengineer #awsdataengineer #pyspark #databricks #adf #azuredatafactory #cloudcomputing #etl #datascience
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