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Azure Synapse Analytics Cookbook

You're reading from   Azure Synapse Analytics Cookbook Implement a limitless analytical platform using effective recipes for Azure Synapse

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781803231501
Length 238 pages
Edition 1st Edition
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Authors (2):
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Gaurav Agarwal(BLR) Gaurav Agarwal(BLR)
Author Profile Icon Gaurav Agarwal(BLR)
Gaurav Agarwal(BLR)
Meenakshi Muralidharan Meenakshi Muralidharan
Author Profile Icon Meenakshi Muralidharan
Meenakshi Muralidharan
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Table of Contents (11) Chapters Close

Preface 1. Chapter 1: Choosing the Optimal Method for Loading Data to Synapse 2. Chapter 2: Creating Robust Data Pipelines and Data Transformation FREE CHAPTER 3. Chapter 3: Processing Data Optimally across Multiple Nodes 4. Chapter 4: Engineering Real-Time Analytics with Azure Synapse Link Using Cosmos DB 5. Chapter 5: Data Transformation and Processing with Synapse Notebooks 6. Chapter 6: Enriching Data Using the Azure ML AutoML Regression Model 7. Chapter 7: Visualizing and Reporting Petabytes of Data 8. Chapter 8: Data Cataloging and Governance 9. Chapter 9: MPP Platform Migration to Synapse 10. Other Books You May Enjoy

Achieving parallelism in data loading using PolyBase

PolyBase is the one of best data loading methods when it comes to performance after the COPY Into command. So, it's recommended to use PolyBase where it's supported or possible when it comes to parallelism.

How it achieves parallelism is similar to what a parallel data warehouse system does. There will be a control node, followed by multiple compute nodes, which are then linked to multiple data nodes. The data nodes will consist of the actual data, which will get the process by the compute nodes in parallel, and all these operations and instructions are governed by the control node.

In the following architecture diagrams, each Hadoop Distributed File System (HDFS) bridge of the service from every compute node can connect to an external resource, such as Azure Blob storage, and then bidirectionally transfer data between a SQL data warehouse and the external resource. This is fully scalable and highly robust: as you...

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