Apache Spark 3 for Data Engineering and Analytics with Python - DataFrame Reader and Writer

Apache Spark 3 for Data Engineering and Analytics with Python - DataFrame Reader and Writer

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

This tutorial covers the use of DataFrame reader and writer APIs in Spark. It explains how to read CSV files, set options, and infer schemas. The tutorial also demonstrates selecting and displaying data, and writing data to Parquet format. Key concepts include the ability to handle big data file types and the use of distributed file systems.

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3 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

How does Spark infer the schema of a CSV file?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the role of the Dataframe writer in saving data?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

Discuss the importance of distributed file systems in big data storage.

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