Alex Merced – författare

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.

With this book, you''ll learn:

The architecture of Apache Iceberg tablesWhat happens under the hood when you perform operations on Iceberg tablesHow to further optimize Iceberg tables for maximum performanceHow 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.

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.

With this book, you''ll learn:

The architecture of Apache Iceberg tablesWhat happens under the hood when you perform operations on Iceberg tablesHow to further optimize Iceberg tables for maximum performanceHow 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.

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. This lack of flexibility forces you to adjust your workflow to the tool your data is locked in, which creates data silos and data drift. This 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 lakehouse. Authors Tomer Shiran, Jason Hughes, Alex Merced, and Dipankar Mazumdar from Dremio guide you through the process.With this book, you'll learn:The architecture of Apache Iceberg tablesWhat happens under the hood when you perform operations on Iceberg tablesHow to further optimize Apache Iceberg tables for maximum performanceHow to use Apache Iceberg with popular data engines such as Apache Spark, Apache Flink, and Dremio SonarHow Apache Iceberg can be used in streaming and batch ingestionDiscover why Apache Iceberg is a foundational technology for implementing an open data lakehouse.

Building a data platform can be difficult, and many systems are expensive to run. When you rely on one vendor, it can be hard to change or improve your setup later. A modern data platform should be reliable, able to grow with your needs, and not tied to costly licences. Open-source tools give you more control over how your platform works and how much you spend. This book shows a clear way to build a complete data platform using Apache Iceberg. 

Learn how to create a modular and scalable Iceberg Lakehouse architecture.  Understand where Spark, Flink, Dremio, and Polaris fit into your design.  Build reliable batch and streaming ingestion pipelines for your data.  Apply strategies for governance, security, and performance at scale.  Connect architectural theory with practical implementation through hands-on examples. 

Architecting an Apache Iceberg Lakehouse is a practical guide to designing a complete data platform. The book carefully guides you through each layer of the architecture, from storage and ingestion to governance and security. It uses hands-on examples, such as ingesting data with Apache Spark and building dashboards in Apache Superset, to illustrate key concepts. 

After reading this book, you will understand how to design and build a data platform that can grow with your needs. It explains the key choices you need to make when working with large amounts of data in real projects. 

This book is written for data architects who already know the basics of data Lakehouses and are planning a new system or moving from an existing one. 

Revolutionize your understanding of modern data management with Apache Polaris (incubating), the open source catalog designed for data lakehouse industry standard Apache Iceberg. This comprehensive guide takes you on a journey through the intricacies of Apache Iceberg data lakehouses, highlighting the pivotal role of Iceberg catalogs.Authors Alex Merced, Andrew Madson, and Tomer Shiran explore Apache Polaris's architecture and features in detail, equipping you with the knowledge needed to leverage its full potential. Data engineers, data architects, data scientists, and data analysts will learn how to seamlessly integrate Apache Polaris with popular data tools like Apache Spark, Snowflake, and Dremio to enhance data management capabilities, optimize workflows, and secure datasets.Get a comprehensive introduction to Iceberg data lakehousesUnderstand how catalogs facilitate efficient data management and querying in IcebergExplore Apache Polaris's unique architecture and its powerful featuresDeploy Apache Polaris locally, and deploy managed Apache Polaris from Snowflake and DremioPerform basic table operations on Apache Spark, Snowflake, and Dremio

Revolutionize your understanding of modern data management with Apache Polaris (incubating), the open source catalog designed for data lakehouse industry standard Apache Iceberg. This comprehensive guide takes you on a journey through the intricacies of Apache Iceberg data lakehouses, highlighting the pivotal role of Iceberg catalogs.Authors Alex Merced, Andrew Madson, and Tomer Shiran explore Apache Polaris's architecture and features in detail, equipping you with the knowledge needed to leverage its full potential. Data engineers, data architects, data scientists, and data analysts will learn how to seamlessly integrate Apache Polaris with popular data tools like Apache Spark, Snowflake, and Dremio to enhance data management capabilities, optimize workflows, and secure datasets.Get a comprehensive introduction to Iceberg data lakehousesUnderstand how catalogs facilitate efficient data management and querying in IcebergExplore Apache Polaris's unique architecture and its powerful featuresDeploy Apache Polaris locally, and deploy managed Apache Polaris from Snowflake and DremioPerform basic table operations on Apache Spark, Snowflake, and Dremio