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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 Hamid Mahmood Qureshi
Profile icon Hamid Mahmood Qureshi
LinkedIn
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.
See other products by Hamid Mahmood Qureshi
Hammad Sharif Hammad Sharif
Profile icon Hammad Sharif
LinkedIn
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.
See other products by Hammad Sharif
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Table of Contents (12) Chapters

Preface 1. Chapter 1: Getting Started with Snowflake 2. Chapter 2: Managing the Data Life Cycle 3. Chapter 3: Loading and Extracting Data into and out of Snowflake 4. Chapter 4: Building Data Pipelines in Snowflake 5. Chapter 5: Data Protection and Security in Snowflake 6. Chapter 6: Performance and Cost Optimization 7. Chapter 7: Secure Data Sharing 8. Chapter 8: Back to the Future with Time Travel 9. Chapter 9: Advanced SQL Techniques 10. Chapter 10: Extending Snowflake Capabilities 11. Other Books You May Enjoy

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...
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Authors (2)

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Profile icon Hamid Mahmood Qureshi
LinkedIn
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.
Read more
See other products by Hamid Mahmood Qureshi
Profile icon Hammad Sharif
LinkedIn
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.
Read more
See other products by Hammad Sharif
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