Book Image

Snowflake Cookbook

By : Hamid Mahmood Qureshi, Hammad Sharif
5 (1)
Book Image

Snowflake Cookbook

5 (1)
By: Hamid Mahmood Qureshi, Hammad Sharif

Overview of this book

Snowflake is a unique cloud-based data warehousing platform built from scratch to perform data management on the cloud. This book introduces you to Snowflake's unique architecture, which places it at the forefront of cloud data warehouses. You'll explore the compute model available with Snowflake, and find out how Snowflake allows extensive scaling through the virtual warehouses. You will then learn how to configure a virtual warehouse for optimizing cost and performance. Moving on, you'll get to grips with the data ecosystem and discover how Snowflake integrates with other technologies for staging and loading data. As you progress through the chapters, you will leverage Snowflake's capabilities to process a series of SQL statements using tasks to build data pipelines and find out how you can create modern data solutions and pipelines designed to provide high performance and scalability. You will also get to grips with creating role hierarchies, adding custom roles, and setting default roles for users before covering advanced topics such as data sharing, cloning, and performance optimization. By the end of this Snowflake book, you will be well-versed in Snowflake's architecture for building modern analytical solutions and understand best practices for solving commonly faced problems using practical recipes.
Table of Contents (12 chapters)

Projections in Snowflake for performance

Snowflake offers the concept of MVs for optimizing different access patterns. MVs allow disconnecting the table design from evolving access paths. This recipe shall provide you with guidance on using MVs, their limitations, and their implications.

Getting ready

This recipe shows how Snowflake MVs can be constructed from a table and how query latency can be reduced. Note that these steps can be run in either the Snowflake web UI or the SnowSQL command-line client.

How to do it…

Let's start by creating a table in a database, followed by generating a large dataset to demonstrate how MVs improve efficiency. The steps for this recipe are as follows:

  1. We will start by creating a new database:

    The database should be created successfully.

  2. Moreover, we shall execute a configuration change for the following steps so that Snowflake does not use caching:
  3. ...