Book description
Develop modern solutions with Snowflake's unique architecture and integration capabilities; process bulk and real-time data into a data lake; and leverage time travel, cloning, and data-sharing features to optimize data operations
Key Features
- Build and scale modern data solutions using the all-in-one Snowflake platform
- Perform advanced cloud analytics for implementing big data and data science solutions
- Make quicker and better-informed business decisions by uncovering key insights from your data
Book Description
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.
What you will learn
- Get to grips with data warehousing techniques aligned with Snowflake's cloud architecture
- Broaden your skills as a data warehouse designer to cover the Snowflake ecosystem
- Transfer skills from on-premise data warehousing to the Snowflake cloud analytics platform
- Optimize performance and costs associated with a Snowflake solution
- Stage data on object stores and load it into Snowflake
- Secure data and share it efficiently for access
- Manage transactions and extend Snowflake using stored procedures
- Extend cloud data applications using Spark Connector
Who this book is for
This book is for data warehouse developers, data analysts, database administrators, and anyone involved in designing, implementing, and optimizing a Snowflake data warehouse. Knowledge of data warehousing and database and cloud concepts will be useful. Basic familiarity with Snowflake is beneficial, but not necessary.
Table of contents
- Snowflake Cookbook
- Contributors
- About the authors
- About the reviewers
- Preface
- Chapter 1: Getting Started with Snowflake
- Chapter 2: Managing the Data Life Cycle
-
Chapter 3: Loading and Extracting Data into and out of Snowflake
- Technical requirements
- Configuring Snowflake access to private S3 buckets
- Loading delimited bulk data into Snowflake from cloud storage
- Loading delimited bulk data into Snowflake from your local machine
- Loading Parquet files into Snowflake
- Making sense of JSON semi-structured data and transforming to a relational view
- Processing newline-delimited JSON (or NDJSON) into a Snowflake table
- Processing near real-time data into a Snowflake table using Snowpipe
- Extracting data from Snowflake
-
Chapter 4: Building Data Pipelines in Snowflake
- Technical requirements
- Creating and scheduling a task
- Conjugating pipelines through a task tree
- Querying and viewing the task history
- Exploring the concept of streams to capture table-level changes
- Combining the concept of streams and tasks to build pipelines that process changed data on a schedule
- Converting data types and Snowflake's failure management
- Managing context using different utility functions
-
Chapter 5: Data Protection and Security in Snowflake
- Technical requirements
- Setting up custom roles and completing the role hierarchy
- Configuring and assigning a default role to a user
- Delineating user management from security and role management
- Configuring custom roles for managing access to highly secure data
- Setting up development, testing, pre-production, and production database hierarchies and roles
- Safeguarding the ACCOUNTADMIN role and users in the ACCOUNTADMIN role
-
Chapter 6: Performance and Cost Optimization
- Technical requirements
- Examining table schemas and deriving an optimal structure for a table
- Identifying query plans and bottlenecks
- Weeding out inefficient queries through analysis
- Identifying and reducing unnecessary Fail-safe and Time Travel storage usage
- Projections in Snowflake for performance
- Reviewing query plans to modify table clustering
- Optimizing virtual warehouse scale
-
Chapter 7: Secure Data Sharing
- Technical requirements
- Sharing a table with another Snowflake account
- Sharing data through a view with another Snowflake account
- Sharing a complete database with another Snowflake account and setting up future objects to be shareable
- Creating reader accounts and configuring them for non-Snowflake sharing
- Keeping costs in check when sharing data with non-Snowflake users
-
Chapter 8: Back to the Future with Time Travel
- Technical requirements
- Using Time Travel to return to the state of data at a particular time
- Using Time Travel to recover from the accidental loss of table data
- Identifying dropped databases, tables, and other objects and restoring them using Time Travel
- Using Time Travel in conjunction with cloning to improve debugging
- Using cloning to set up new environments based on the production environment rapidly
- Chapter 9: Advanced SQL Techniques
-
Chapter 10: Extending Snowflake Capabilities
- Technical requirements
- Creating a Scalar user-defined function using SQL
- Creating a Table user-defined function using SQL
- Creating a Scalar user-defined function using JavaScript
- Creating a Table user-defined function using JavaScript
- Connecting Snowflake with Apache Spark
- Using Apache Spark to prepare data for storage on Snowflake
- Why subscribe?
- Other Books You May Enjoy
Product information
- Title: Snowflake Cookbook
- Author(s):
- Release date: February 2021
- Publisher(s): Packt Publishing
- ISBN: 9781800560611
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