Spark Programming in Python for Beginners with Apache Spark 3 - Writing Your Data and Managing Layout

Spark Programming in Python for Beginners with Apache Spark 3 - Writing Your Data and Managing Layout

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

This video tutorial explains the use of Dataframe Writer in Spark, focusing on creating Avro outputs. It covers configuring Spark to handle Avro files, using the Dataframe Writer API, understanding partitions, and optimizing file sizes. The tutorial demonstrates how to partition data by specific columns and control file sizes using the max records per file option, providing insights into parallel processing and partition elimination.

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4 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the two types of benefits mentioned for partitioning data?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

In what scenarios would you want to partition your data for specific columns?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

How can you control the size of the output files when writing a DataFrame?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the expected outcome when applying the max records per file option?

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