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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

Connecting to Snowflake with JDBC

The previous recipe talked about using SnowSQL to connect to Snowflake, which provides more control over how a user can interact with Snowflake. SnowSQL can be used with the Linux shell to automate code execution. But if applications have to be supported with Snowflake serving as a data tier, it will require more granular control over connecting and executing SQL. This recipe demonstrates how to install Snowflake's Java Database Connectivity (JDBC) driver and how to use that in a Java application to connect to a Snowflake instance. This functionality is captured in a Java app.

Getting ready

Ubuntu Linux 64-bit has been used for this recipe. The JDBC driver will be downloaded in the home directory of the sfuser user on a 64-bit Linux host called sfchost. These names have no significance and are abbreviations of the Snowflake user and Snowflake client host. Any Linux shell commands shown will be preceded by a sfcuser@sfchost:~$, prompt, though...

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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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