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Business Intelligence with Databricks SQL

You're reading from   Business Intelligence with Databricks SQL Concepts, tools, and techniques for scaling business intelligence on the data lakehouse

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803235332
Length 348 pages
Edition 1st Edition
Languages
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Author (1):
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Vihag Gupta Vihag Gupta
Author Profile Icon Vihag Gupta
Vihag Gupta
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Databricks SQL on the Lakehouse
2. Chapter 1: Introduction to Databricks FREE CHAPTER 3. Chapter 2: The Databricks Product Suite – A Visual Tour 4. Chapter 3: The Data Catalog 5. Chapter 4: The Security Model 6. Chapter 5: The Workbench 7. Chapter 6: The SQL Warehouses 8. Chapter 7: Using Business Intelligence Tools with Databricks SQL 9. Part 2: Internals of Databricks SQL
10. Chapter 8: The Delta Lake 11. Chapter 9: The Photon Engine 12. Chapter 10: Warehouse on the Lakehouse 13. Part 3: Databricks SQL Commands
14. Chapter 11: SQL Commands – Part 1 15. Chapter 12: SQL Commands – Part 2 16. Part 4: TPC-DS, Experiments, and Frequently Asked Questions
17. Chapter 13: Playing with the TPC-DS Dataset 18. Chapter 14: Ask Me Anything 19. Index 20. Other Books You May Enjoy

Using Serverless SQL

It would be remiss not to introduce the Serverless SQL offering in Databricks SQL. SQL Warehouses – the classic SQL Warehouses that we have discussed so far – reside in your cloud account. That is, the workers of the warehouses are VMs in your cloud account. This has two implications:

  • You incur the cost of Databricks and the cost of the VMs that Databricks uses to power the SQL Warehouses.
  • You incur some latency in cluster cold starts and upscaling events.

Databricks SQL offers Serverless SQL to circumvent this. In Serverless SQL, the SQL Warehouses are provisioned in Databricks’s account from a pool of pre-provisioned compute resources. This solves both the aforementioned implications:

  • The cost of Databricks SQL Warehouses includes the VM costs, and you pay for only one line item
  • Since Databricks uses a pool of pre-provisioned compute, no latency is incurred in cold starts, as well as when upscaling events
  • ...
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