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Optimizing Databricks Workloads

You're reading from  Optimizing Databricks Workloads

Product type Book
Published in Dec 2021
Publisher Packt
ISBN-13 9781801819077
Pages 230 pages
Edition 1st Edition
Languages
Authors (3):
Anirudh Kala Anirudh Kala
Profile icon Anirudh Kala
Anshul Bhatnagar Anshul Bhatnagar
Profile icon Anshul Bhatnagar
Sarthak Sarbahi Sarthak Sarbahi
Profile icon Sarthak Sarbahi
View More author details

Table of Contents (13) Chapters

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

Summary

In this chapter, we learned about the fundamentals of Spark, got an introduction to Databricks, and explored Delta Lake. We were introduced to Azure Databricks and the important workspace components. We learned how to create an Azure Databricks instance, a notebook in the Databricks workspace, Spark clusters, and Databricks jobs. We also learned about the important big data file formats such as Parquet, Avro, and ORC. We also learned about the fundamentals of Delta Lake and went through a worked-out example.

In the next chapter, we will dive deeper into the concepts of batch and stream processing in Azure Databricks. We'll also see more examples in the chapter to practice working hands-on in a Databricks environment.

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Optimizing Databricks Workloads
Published in: Dec 2021 Publisher: Packt ISBN-13: 9781801819077
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