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You're reading from  Azure Data Engineer Associate Certification Guide

Product typeBook
Published inFeb 2022
PublisherPackt
ISBN-139781801816069
Edition1st Edition
Tools
Azure
Concepts
Big Data
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Author (1)
Newton Alex
Newton Alex
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Newton Alex

Newton Alex leads several Azure Data Analytics teams in Microsoft, India. His team contributes to technologies including Azure Synapse, Azure Databricks, Azure HDInsight, and many open source technologies, including Apache YARN, Apache Spark, and Apache Hive. He started using Hadoop while at Yahoo, USA, where he helped build the first batch processing pipelines for Yahoo's ad serving team. After Yahoo, he became the leader of the big data team at Pivotal Inc., USA, where he was responsible for the entire open source stack of Pivotal Inc. He later moved to Microsoft and started the Azure Data team in India. He has worked with several Fortune 500 companies to help build their data systems on Azure.
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Scaling resources

Scaling refers to the process of increasing or decreasing the compute, storage, or network resources to improve the performance of jobs or reduce expenses. There are two types of scaling: Manual and Automatic. As might be obvious, with manual scaling, we decide on the size beforehand. With automatic scaling, the service dynamically decides on the size of the resources based on various factors, such as the load on the cluster, the cost of running the cluster, time constraints, and more.

Let's explore the scaling options available in Azure Batch and then quickly glance at the options available in Spark and SQL too.

Azure Batch

Azure Batch provides one of the most flexible autoscale options. It lets you specify your own autoscale formula. Azure Batch will then use your formula to decide how many resources to scale up or down to.

A scaling formula can be written based on the following:

  • Time metrics: Using application stats collected at 5-minute...
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Azure Data Engineer Associate Certification Guide
Published in: Feb 2022Publisher: PacktISBN-13: 9781801816069
© 2022 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Newton Alex

Newton Alex leads several Azure Data Analytics teams in Microsoft, India. His team contributes to technologies including Azure Synapse, Azure Databricks, Azure HDInsight, and many open source technologies, including Apache YARN, Apache Spark, and Apache Hive. He started using Hadoop while at Yahoo, USA, where he helped build the first batch processing pipelines for Yahoo's ad serving team. After Yahoo, he became the leader of the big data team at Pivotal Inc., USA, where he was responsible for the entire open source stack of Pivotal Inc. He later moved to Microsoft and started the Azure Data team in India. He has worked with several Fortune 500 companies to help build their data systems on Azure.
Read more about Newton Alex

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