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Snowflake Cookbook

You're reading from Snowflake Cookbook

Product type Book

Published in Feb 2021

Publisher Packt

ISBN-13 9781800560611

Pages 330 pages

Edition 1st Edition

Languages

Concepts

Authors (2):

Hamid Mahmood Qureshi

Hammad Sharif

View More author details

Table of Contents (12) Chapters

Preface

Chapter 1: Getting Started with Snowflake

Chapter 2: Managing the Data Life Cycle

Chapter 3: Loading and Extracting Data into and out of Snowflake

Chapter 4: Building Data Pipelines in Snowflake

Chapter 5: Data Protection and Security in Snowflake

Chapter 6: Performance and Cost Optimization

Chapter 7: Secure Data Sharing

Chapter 8: Back to the Future with Time Travel

Chapter 9: Advanced SQL Techniques

Chapter 10: Extending Snowflake Capabilities

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Optimizing virtual warehouse scale

This recipe will explore how we can expand the number of concurrent queries that a virtual warehouse can process and identify the optimal sizing for your virtual warehouses. This entails analyzing query usage for each virtual warehouse and identifying whether the warehouse can process an additional load of queries concurrently or is limited. If it is struggling to match the demand from the workload, we will see how we can resize the cluster or virtual warehouse to an optimal size from a processing and billing perspective.

Getting ready

In this recipe, we will use Snowflake's web UI to show how to use different tools to put a load on the warehouse. We intend to use benchmarking queries in this case, which are available with Snowflake. Secondly, we shall be exploring analytics provided within the web UI to help understand the workload and actions that we can take based on the analysis.

How to do it…

Let's start with the...

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Authors (2)

Hamid Mahmood Qureshi

Hamid Qureshi is a senior cloud and data warehouse professional with almost two decades of total experience, having architected, designed, and led the implementation of several data warehouse and business intelligence solutions. He has extensive experience and certifications across various data analytics platforms, ranging from Teradata, Oracle, and Hadoop to modern, cloud-based tools such as Snowflake. Having worked extensively with traditional technologies, combined with his knowledge of modern platforms, he has accumulated substantial practical expertise in data warehousing and analytics in Snowflake, which he has subsequently captured in his publications.

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See other products by Hamid Mahmood Qureshi

Hammad Sharif

Hammad Sharif is an experienced data architect with more than a decade of experience in the information domain, covering governance, warehousing, data lakes, streaming data, and machine learning. He has worked with a leading data warehouse vendor for a decade as part of a professional services organization, advising customers in telco, retail, life sciences, and financial industries located in Asia, Europe, and Australia during presales and post-sales implementation cycles. Hammad holds an MSc. in computer science and has published conference papers in the domains of machine learning, sensor networks, software engineering, and remote sensing.

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