Book Image

Cloud Scale Analytics with Azure Data Services

By : Patrik Borosch
Book Image

Cloud Scale Analytics with Azure Data Services

By: Patrik Borosch

Overview of this book

Azure Data Lake, the modern data warehouse architecture, and related data services on Azure enable organizations to build their own customized analytical platform to fit any analytical requirements in terms of volume, speed, and quality. This book is your guide to learning all the features and capabilities of Azure data services for storing, processing, and analyzing data (structured, unstructured, and semi-structured) of any size. You will explore key techniques for ingesting and storing data and perform batch, streaming, and interactive analytics. The book also shows you how to overcome various challenges and complexities relating to productivity and scaling. Next, you will be able to develop and run massive data workloads to perform different actions. Using a cloud-based big data-modern data warehouse-analytics setup, you will also be able to build secure, scalable data estates for enterprises. Finally, you will not only learn how to develop a data warehouse but also understand how to create enterprise-grade security and auditing big data programs. By the end of this Azure book, you will have learned how to develop a powerful and efficient analytical platform to meet enterprise needs.
Table of Contents (20 chapters)
1
Section 1: Data Warehousing and Considerations Regarding Cloud Computing
4
Section 2: The Storage Layer
7
Section 3: Cloud-Scale Data Integration and Data Transformation
14
Section 4: Data Presentation, Dashboarding, and Distribution

Setting up a Synapse Spark pool

Now, let's examine the basic steps to spin up a Synapse Spark pool in this section.

This task is very easy to handle in a Synapse workspace:

  1. Please navigate to the Management pane and there, in the Analytics pools section, select Apache Spark pools.
  2. In the Details pane, click + New. The configuration blade for a new Apache Spark pool is displayed:

    Figure 6.1 – Create Apache Spark pool – The Basics blade

  3. Here you will name your new Spark pool and configure the node size value, enable Autoscale, and set the lower and upper boundaries for the autoscaling feature, if enabled. The last row in this view shows the potential cost of the lowest and the highest autoscaling setting. Click Next: Additional settings.
  4. In the upper area of the Additional settings blade, you can now configure Auto-pause and Number of minutes idle, which sets the amount of idle time that will elapse before the cluster pauses. In the Component...