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Snowflake Cookbook

You're reading from Snowflake Cookbook Techniques for building modern cloud data warehousing solutions

Product type Paperback

Published in Feb 2021

Publisher Packt

ISBN-13 9781800560611

Length 330 pages

Edition 1st Edition

Languages

Python

Tools

Cloud Foundry

Concepts

Data Science

Authors (2):

Hamid Mahmood Qureshi

Hammad Sharif

View More author details

Table of Contents (12) Chapters

Preface

1. Chapter 1: Getting Started with Snowflake

2. Chapter 2: Managing the Data Life Cycle FREE CHAPTER

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

Chapter 10: Extending Snowflake Capabilities

This chapter provides techniques for extending Snowflake capabilities and integrating a Snowflake-based data warehouse to work with other technologies. The chapter guides you through the creation of User-Defined Functions (UDFs), which can help introduce functionality that may currently be missing in Snowflake. It also talks about the two different languages that UDFs support and the two different modes in which UDFs can exist, and offers a guide on connecting Snowflake with Apache Spark for data exchanges between Snowflake and Spark. Then, the chapter explores scenarios involving externalizing data processing to a Spark engine, which could help support existing Spark pipelines in the customer's ecosystem or as a cost optimization technique for ETL.

The following recipes will be covered in this chapter:

Creating a Scalar user-defined function using SQL
Creating a Table user-defined function using SQL
Creating a Scalar...

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Authors (2)

Hamid Mahmood Qureshi

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.

See other products by Hamid Mahmood Qureshi

Hammad Sharif

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.

See other products by Hammad Sharif

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