Data Transformations with Spark SQL focus on processing, querying, and reshaping large datasets using SQL-based operations in Apache Spark. Spark SQL provides a powerful interface for handling structured and semi-structured data in distributed environments. This training explains how to perform filtering, aggregation, joins, sorting, and column transformations using SQL queries and DataFrames. It also covers working with temporary views, functions, and optimization techniques for efficient large-scale data processing. You will learn how to build scalable transformation workflows that support analytics, ETL pipelines, and reporting systems. The course also highlights best practices for improving query performance and managing data transformations in big data environments.
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