Snowflake - Build and Architect Data Pipelines Using AWS - What Is Pushdown in Spark 3.1?

The video tutorial discusses executing scripts on AWS Glue and the challenges of data movement between Snowflake and AWS. It highlights the inefficiencies of using Python for large data sets and introduces Spark as a powerful tool for big data transformations. The concept of pushdown optimization in Spark 3.1 is explained, which allows for efficient data handling by minimizing data movement. The tutorial emphasizes the importance of enabling pushdown to let Spark automatically translate transformations into SQL, optimizing performance.

What are the advantages of using Spark for data transformations within Snowflake?

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Describe the lazy evaluation feature of Spark and its impact on data processing.

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