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You're reading from  Distributed Data Systems with Azure Databricks

Product typeBook
Published inMay 2021
Reading LevelBeginner
PublisherPackt
ISBN-139781838647216
Edition1st Edition
Languages
Python
Tools
Azure Functions
Concepts
Data Science
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Author (1)
Alan Bernardo Palacio
Alan Bernardo Palacio
author image
Alan Bernardo Palacio

Alan Bernardo Palacio is a data scientist and an engineer with vast experience in different engineering fields. His focus has been the development and application of state-of-the-art data products and algorithms in several industries. He has worked for companies such as Ernst and Young, Globant, and now holds a data engineer position at Ebiquity Media helping the company to create a scalable data pipeline. Alan graduated with a Mechanical Engineering degree from the National University of Tucuman in 2015, participated as the founder in startups, and later on earned a Master's degree from the faculty of Mathematics in the Autonomous University of Barcelona in 2017. Originally from Argentina, he now works and resides in the Netherlands.
Read more about Alan Bernardo Palacio

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Orchestrating jobs with Azure Databricks

Until now, we have been able to use data stored in either an S3 bucket or Azure Blob storage, transform it using PySpark or SQL, and then persist the transformed data into a table. Now, the question is: Which methods do we have to integrate this into a complete ETL? One of the options that we have is to use ADF to integrate our Azure Databricks notebook as one of the steps in our data architecture.

In the next example, we will use ADF in order to trigger our notebook by directly passing the name of the file that contains the data we want to process and use this to update our voting turnout table. For this, you will require the following:

  • An Azure subscription
  • An Azure Databricks notebook attached to a running container
  • The Voting_Turnout_US_2020 dataset loaded into a Spark dataframe

ADF

ADF is the Azure cloud platform for the integration of serverless data transformation and aggregation processes. It can integrate...

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Distributed Data Systems with Azure Databricks
Published in: May 2021Publisher: PacktISBN-13: 9781838647216
© 2021 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Alan Bernardo Palacio

Alan Bernardo Palacio is a data scientist and an engineer with vast experience in different engineering fields. His focus has been the development and application of state-of-the-art data products and algorithms in several industries. He has worked for companies such as Ernst and Young, Globant, and now holds a data engineer position at Ebiquity Media helping the company to create a scalable data pipeline. Alan graduated with a Mechanical Engineering degree from the National University of Tucuman in 2015, participated as the founder in startups, and later on earned a Master's degree from the faculty of Mathematics in the Autonomous University of Barcelona in 2017. Originally from Argentina, he now works and resides in the Netherlands.
Read more about Alan Bernardo Palacio

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