Spark Programming in Python for Beginners with Apache Spark 3 - DataFrame Rows and Unit Testing

Spark Programming in Python for Beginners with Apache Spark 3 - DataFrame Rows and Unit Testing

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video tutorial covers scenarios for working with row objects in Spark, converting notebook code to a Spark project, and creating unit tests using Python. It explains setting up a Spark session, creating a schema, and manually creating a DataFrame. The tutorial demonstrates how to validate data types and data in test cases, and how to collect and assert data using the collect method. The video concludes with running tests and confirming their success.

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5 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the purpose of converting the function to an automated unit test?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the steps involved in setting up a test case using the Python unit test framework.

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain how you would assert the data type of a column in a DataFrame.

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

How do you validate the data returned by a DataFrame in Spark?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the significance of the collect method in validating DataFrames?

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