PySpark and AWS: Master Big Data with PySpark and AWS - Running Spark Code Locally

This video tutorial demonstrates how to run PySpark code on both Databricks and local machines. It covers exporting code from Databricks, handling Python version conflicts, resolving file path errors, and understanding the output and logs generated during execution. The tutorial aims to make viewers comfortable with writing and executing Spark code in different environments.

How can you specify which Python version to use with PySpark?

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What does the error 'Python 3 is not recognized' indicate?

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What should you do if the input path does not exist when running your code?

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What is the expected output format when running Spark code locally compared to Databricks?

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