Spark Programming in Python for Beginners with Apache Spark 3 - Spark DataFrameReader API

Spark Programming in Python for Beginners with Apache Spark 3 - Spark DataFrameReader API

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Hard

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This video tutorial introduces the basics of using Spark Data Frame Reader API to read data from various sources. It covers the supported formats, options, and read modes, including permissive, drop malformed, and fail fast. The tutorial also explains schema inference and the importance of following standard practices over shortcuts for better code maintainability.

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7 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the primary purpose of the Spark Data Frame Reader API?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

List the four main things you can specify when using the Data Frame Reader.

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the three read modes available in Spark when encountering a malformed record?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain the permissive read mode in Spark Data Frame Reader.

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

Why might you not need to specify a schema when using the Data Frame Reader?

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6.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the significance of the load method in the Data Frame Reader API?

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7.

OPEN ENDED QUESTION

3 mins • 1 pt

Discuss the importance of following standard practices when using the Data Frame Reader API.

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