Book Image

Snowflake Cookbook

By : Hamid Mahmood Qureshi, Hammad Sharif
Book Image

Snowflake Cookbook

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)

Using Apache Spark to prepare data for storage on Snowflake

This recipe provides you with an example of how Apache Spark and Snowflake partner to utilize the two systems' strengths. The recipe shows a scenario involving reading data from Snowflake into a Spark DataFrame and writing data back to Snowflake from a Spark DataFrame.

Getting ready

You will need to be connected to your Snowflake instance via the Web UI or the SnowSQL client to execute this recipe.

It is assumed that you have already configured the Snowflake Connector for Spark and can connect to the Snowflake instance successfully through Spark.

How to do it

We will be reading data from Snowflake sample tables and transforming the data before writing it back to Snowflake in a new table. The following code in the various steps should be added into a single scala file called snowflake_transform.scala since we will be calling that file from within spark-shell:

  1. Let's start by creating a new database...