🚀 Let's dive into some crucial concepts from Week 6 Spark Dataframe Transformations from Sumit Mittal sir’s ULTIMATE BIG DATA MASTER PROGRAM! 🚀
🔹 Schema Enforcement: Ensuring data consistency and quality by enforcing predefined schemas (Schema ddl & StructType).
🔹 Different Types of Read Modes in DataFrame: Managing how Spark handles corrupt or malformed records with PERMISSIVE, DROPMALFORMED, and FAILFAST modes.
🔹 DataFrame Creation: Techniques for creating and manipulating DataFrames efficiently.
🔹 Concept of Nested Schema: Handling complex data structures within DataFrames to maintain data integrity using Schema Enforcement.
🔹 Select vs SelectExpr: Exploring the differences and use cases for select and selectExpr for data transformations.
Thank you to my mentor, Sumit Mittal, and the amazing TrendyTech team for their unwavering support and guidance. Here’s to more learning and growth in the world of big data! 🌟
#DataEngineering #BigData #ApacheSpark #DataFrames #DataQuality #SchemaEnforcement #ETL #DataScience #LearningJourney #TrendyTech