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Distributed Data Systems with Azure Databricks

You're reading from   Distributed Data Systems with Azure Databricks Create, deploy, and manage enterprise data pipelines

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Product type Paperback
Published in May 2021
Publisher Packt
ISBN-13 9781838647216
Length 414 pages
Edition 1st Edition
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Author (1):
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Alan Bernardo Palacio Alan Bernardo Palacio
Author Profile Icon Alan Bernardo Palacio
Alan Bernardo Palacio
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Introducing Databricks
2. Chapter 1: Introduction to Azure Databricks FREE CHAPTER 3. Chapter 2: Creating an Azure Databricks Workspace 4. Section 2: Data Pipelines with Databricks
5. Chapter 3: Creating ETL Operations with Azure Databricks 6. Chapter 4: Delta Lake with Azure Databricks 7. Chapter 5: Introducing Delta Engine 8. Chapter 6: Introducing Structured Streaming 9. Section 3: Machine and Deep Learning with Databricks
10. Chapter 7: Using Python Libraries in Azure Databricks 11. Chapter 8: Databricks Runtime for Machine Learning 12. Chapter 9: Databricks Runtime for Deep Learning 13. Chapter 10: Model Tracking and Tuning in Azure Databricks 14. Chapter 11: Managing and Serving Models with MLflow and MLeap 15. Chapter 12: Distributed Deep Learning in Azure Databricks 16. Other Books You May Enjoy

Optimizing file management with Delta Engine

Delta Engine allows improved management of files in Delta Lake, yielding better query speed, thanks to optimization in the layout of the stored data. Delta Lake does this by using two types of algorithms: bin-packing and Z-Ordering. The first algorithm is useful when merging small files into larger ones and is more efficient in handling the larger ones. The second algorithm is borrowed from mathematical analysis and is applied to the underlying structure of the data to map multiple dimensions into one dimension while preserving the locality of the data points.

In this section, we will learn how these algorithms work, see how to implement them using commands that act on our data, and how to handle snapshots of data thanks to the time travel feature.

It is good to remember that although there are automatic optimizations that take place when we use Delta Lake, most of these optimizations do not occur automatically, and some of them must...

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