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Learn how to optimize Apache Iceberg performance for data warehouse workloads in this 24-minute conference talk from a San Francisco meetup. Discover technical optimizations that enable low-latency, high-concurrency queries on Apache Iceberg while maintaining data openness and accessibility. Explore the key factors that impact query performance when working with Iceberg, including challenges with position and equality delete tables, metadata parsing bottlenecks, and distributed query execution. Examine proven best practices and query engine optimizations that significantly improve response times, with real-world case studies from enterprises successfully implementing these techniques at scale. Gain actionable insights for handling distributed metadata parsing, managing delete operations efficiently, and implementing query engine enhancements that transform your Iceberg lakehouse into a high-performance analytical platform.
Syllabus
​[SF Meetup] Achieving Data Warehouse Performance on Apache Iceberg
Taught by
Altinity