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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

Experimenting with TPC-DS in Databricks SQL

Now that we have the TPC-DS data generated and ready to query, you are free to experiment and validate everything that we’ve learned in the previous chapters – especially Chapter 8, The Delta Lake.

If you intend to use the TPC-DS benchmarking queries themselves, please note that you will have to import the Databricks versions of the queries into Databricks SQL manually. See Figure 13.11 to learn how to obtain the queries. Otherwise, you can refer to the TPC-DS specification on the ER diagram and row counts to craft your own queries of varying complexity that test the features you want to test.

Keep the metrics you want to measure in mind. A measure such as speed requires that you keep the cluster configuration constant and account for the fact that Databricks SQL will cache table data and query results. Depending on the test, data skipping effectiveness might be a better metric to measure.

As we saw in the Generating...

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