PySpark and AWS: Master Big Data with PySpark and AWS - ETL Pipeline Flow

PySpark and AWS: Master Big Data with PySpark and AWS - ETL Pipeline Flow

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

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FREE Resource

This video tutorial introduces a simple ETL pipeline using Databricks and AWS. It covers the basics of using CSV files in DBFS, processing data with PySpark, and loading it into a Postgres database on AWS RDS. The tutorial is designed for beginners, emphasizing the importance of mastering these foundational concepts before tackling more complex scenarios. The instructor encourages viewers to familiarize themselves with AWS due to its high demand in the market.

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5 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the main purpose of the pipeline discussed in the text?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the significance of understanding the basic pipeline concept according to the text?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What type of file is used as the source in the pipeline?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

What database is the data loaded into after transformations?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

Which cloud service is recommended for working with PySpark in the pipeline?

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