Apache Polaris: The Definitive Guide

Part III. Hands-on with Apache Polaris

In the first two sections of this book, we laid the groundwork of exploring the core concepts of lakehouses, Apache Iceberg, and Apache Polaris. We delved into the architecture, the principles of open table formats, and how Polaris serves as a cutting-edge catalog solution for managing metadata at scale. With this foundational knowledge in place, it’s time to roll up our sleeves and put these concepts into action.

Part III focuses on the practical application of Apache Polaris and its integration with modern data tools. We’ll start by learning how to deploy Polaris locally, enabling you to get hands-on experience with its open source version. From there, we’ll explore how Polaris interacts with powerful tools such as Apache Spark, Snowflake, and Dremio. Each chapter will provide step-by-step guides to configure, query, and manage catalogs, helping you connect the theoretical concepts covered earlier to real-world workflows.

By the end of this section, you’ll not only have deployed Polaris but also integrated it into a broader data ecosystem, giving you a comprehensive understanding of how lakehouse architectures operate in practice. Whether you’re building an on-premise lakehouse, experimenting with open table formats, or evaluating Polaris for production use, these chapters will equip you with the skills and insights to confidently manage your data landscape.

Let’s begin by setting up Polaris in your local environment and gaining a firsthand ...