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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

Understanding the SQL Warehouse architecture

The official documentation for SQL Warehouses (https://docs.databricks.com/sql/admin/sql-endpoints.html) defines a SQL Warehouse as a computation resource that lets you run SQL commands on data objects within Databricks SQL.

In practice, this computation resource manifests as a logical/virtual grouping of one or more physical clusters. The physical clusters are Apache Spark clusters, as provisioned by Databricks.

A single physical cluster follows the core architecture of Apache Spark, as shown in the following diagram:

Figure 6.1 – Physical cluster topology

As shown in the preceding diagram, two distinct processes make a cluster:

  • Driver process: Think of this process as the brain of the cluster. It is responsible for accepting users’ queries, parsing them, planning them, and coordinating their distributed execution across the worker processes available in the cluster. The driver process...
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