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Optimizing Databricks Workloads

You're reading from   Optimizing Databricks Workloads Harness the power of Apache Spark in Azure and maximize the performance of modern big data workloads

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Product type Paperback
Published in Dec 2021
Publisher Packt
ISBN-13 9781801819077
Length 230 pages
Edition 1st Edition
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Authors (3):
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Anshul Bhatnagar Anshul Bhatnagar
Author Profile Icon Anshul Bhatnagar
Anshul Bhatnagar
Sarthak Sarbahi Sarthak Sarbahi
Author Profile Icon Sarthak Sarbahi
Sarthak Sarbahi
Anirudh Kala Anirudh Kala
Author Profile Icon Anirudh Kala
Anirudh Kala
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Toc

Table of Contents (13) Chapters Close

Preface 1. Section 1: Introduction to Azure Databricks
2. Chapter 1: Discovering Databricks FREE CHAPTER 3. Chapter 2: Batch and Real-Time Processing in Databricks 4. Chapter 3: Learning about Machine Learning and Graph Processing in Databricks 5. Section 2: Optimization Techniques
6. Chapter 4: Managing Spark Clusters 7. Chapter 5: Big Data Analytics 8. Chapter 6: Databricks Delta Lake 9. Chapter 7: Spark Core 10. Section 3: Real-World Scenarios
11. Chapter 8: Case Studies 12. Other Books You May Enjoy

Chapter 6: Databricks Delta Lake

Delta Lake is an open source storage layer that provides functionalities to data in the data lake that only exist in data warehouses. When combined with cloud storage, Databricks and Delta Lake lead to the formation of a Lakehouse. A Lakehouse simply provides the best of both worlds – data lakes and data warehouses. In today's world, a Lakehouse provides the same set of capabilities as a traditional data warehouse and at a much lower cost. This is made possible due to cheap cloud storage such as Azure Data Lake, Spark as the processing engine, and data being stored in the Delta Lake format. In this chapter, we will learn about various Delta Lake optimizations that help us build a more performant Lakehouse.

In this chapter, we will cover the following topics:

  • Working with the OPTIMIZE and ZORDER commands
  • Using AUTO OPTIMIZE
  • Learning about delta caching
  • Learning about dynamic partition pruning
  • Understanding bloom...
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