Discover the origin and benefits of Apache Iceberg, a format for managing big data tables efficiently. Learn about Iceberg's collaboration with industry giants like Apple, Airbnb, and Lyft. Dive into the challenges of data migration and schema evolution in the realm of data management with Iceberg.
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Quick takeaways
Apache Iceberg simplifies big data analysis by enabling SQL tables usage with Spark and Hive concurrently.
Iceberg ensures correctness and efficiency by providing atomic operations for schema management and file layout enhancements.
Deep dives
Overview of Apache Iceberg and its Origins
Apache Iceberg is an open-source high-performance format for huge data tables born out of Netflix by Ryan Blue and Dan Weeks. It facilitates SQL table use for big data, enabling engines like Spark and Hive to work safely with the same tables concurrently. Since being open-sourced, companies like Airbnb, Apple, and Lyft have adopted Iceberg.
Functionality of Iceberg as a Table Format
Iceberg operates as a layer atop data storage mechanisms like S3, providing database-type capabilities. It addresses challenges like schema management by offering a layer of metadata to handle schema, file layouts, and enhance query performance. Iceberg simplifies data analysis by creating a manageable table abstraction.
Evolution from Hive to Iceberg
Iceberg contrasts with Hive's simplistic table model that lacks atomic operations when managing large-scale changes. Iceberg enhances correctness by enabling operations like file replacements atomically and safely, a feature absent in Hive. It elevates schema evolution by providing fully SQL-compatible schema updates.
Transactional Guarantees and Migration Challenges
Iceberg provides single table transactions ensuring atomic changes through manageable mechanisms like pointer adjustments for version transitions. Migrating to Iceberg involves building metadata around existing files and transitioning Spark and Trino queries to use Iceberg metadata. For rollbacks post-migration, solutions entail segregation of new data files and maintaining oversight through S3 access logs.
Apache Iceberg is an open source high-performance format for huge data tables. Iceberg enables the use of SQL tables for big data, while making it possible for engines like Spark and Hive to safely work with the same tables, at the same time.
Iceberg was started at Netflix by Ryan Blue and Dan Weeks, and was open-sourced and donated to the Apache Software Foundation in November 2018. It has now been adopted at many other companies including Airbnb, Apple, and Lyft.
Ryan Blue joins the podcast to describe the origins of Iceberg, how it works, the problems it solves, collaborating with Apple and others to open-source it, and more.
This episode is hosted by Lee Atchison. Lee Atchison is a software architect, author, and thought leader on cloud computing and application modernization. His best-selling book, Architecting for Scale (O’Reilly Media), is an essential resource for technical teams looking to maintain high availability and manage risk in their cloud environments.
Lee is the host of his podcast, Modern Digital Business, an engaging and informative podcast produced for people looking to build and grow their digital business with the help of modern applications and processes developed for today’s fast-moving business environment. Listen at mdb.fm. Follow Lee at softwarearchitectureinsights.com, and see all his content at leeatchison.com.