Apache Iceberg: The Definitive Guide: Data Lakehouse Functionality, Performance, and Scalability on the Data LakeКНИГИ » ОС И БД
Название: Apache Iceberg: The Definitive Guide: Data Lakehouse Functionality, Performance, and Scalability on the Data Lake Автор: Tomer Shiran, Jason Hughes, Alex Merced Издательство: O’Reilly Media, Inc. Год: 2024 Страниц: 479 Язык: английский Формат: pdf, epub (true) Размер: 14.0 MB
Traditional data architecture patterns are severely limited. To use these patterns, you have to ETL data into each tool—a cost-prohibitive process for making warehouse features available to all of your data. The lack of flexibility with these patterns requires you to lock into a set of priority tools and formats, which creates data silos and data drift. This practical book shows you a better way.
Apache Iceberg provides the capabilities, performance, scalability, and savings that fulfill the promise of an open data lakehouse. By following the lessons in this book, you'll be able to achieve interactive, batch, Machine Learning, and streaming analytics with this high-performance open source format. Authors Tomer Shiran, Jason Hughes, and Alex Merced from Dremio show you how to get started with Iceberg.
In these pages, you’ll learn what Apache Iceberg is, why it exists, how it works, and how to harness its power. Designed for data engineers, architects, scientists, and analysts working with large datasets across various use cases from BI dashboards to AI/ML, this book explores the core concepts, inner workings, and practical applications of Apache Iceberg. By the time you reach the end, you will have grasped the essentials and possess the practical knowledge to implement Apache Iceberg effectively in your data projects. Whether you are a newcomer or an experienced practitioner, Apache Iceberg: The Definitive Guide will be your trusted companion on this enlightening journey into Apache Iceberg.
The Part II of the book will delve into the practical aspects of using Apache Iceberg with some widely used compute engines and standalone APIs, including Apache Spark, Dremio’s SQL Engine, AWS Glue, Apache Flink, and PyIceberg. For a bonus chapter on the Iceberg Java/Python APIs, visit this supplemental repository. The primary focus is to provide in-depth explanations and code examples to demonstrate how Apache Iceberg works with various compute engines so that you can apply and build on the theoretical concepts discussed in the previous chapters. Visit the book’s GitHub repository to learn how to create a data lakehouse environment on your computer with Docker and to get hands-on with tools such as Apache Spark, Apache Flink, and Dremio.
With this book, you'll learn: • The architecture of Apache Iceberg tables • What happens under the hood when you perform operations on Iceberg tables • How to further optimize Iceberg tables for maximum performance • How to use Iceberg with popular data engines such as Apache Spark, Apache Flink, and Dremio
Discover why Apache Iceberg is a foundational technology for implementing an open data lakehouse.
Preface I. Fundamentals of Apache Iceberg 1. Introduction to Apache Iceberg 2. The Architecture of Apache Iceberg 3. Lifecycle of Write and Read Queries 4. Optimizing the Performance of Iceberg Tables 5. Iceberg Catalogs II. Hands-on with Apache Iceberg 6. Apache Spark 7. Dremio’s SQL Query Engine 8. AWS Glue 9. Apache Flink III. Apache Iceberg in Practice 10. Apache Iceberg in Production 11. Streaming with Apache Iceberg 12. Governance and Security 13. Migrating to Apache Iceberg 14. Real-World Use Cases of Apache Iceberg Index
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Apache Iceberg: The Definitive Guide: Data Lakehouse Functionality, Performance, and Scalability on the Data Lake 
