More Than Just The Tip Of The Iceberg
summary
Hands-on workshop that sets up a local Apache Iceberg environment with Docker Compose stack, MinIO object storage, LakeKeeper REST catalog, PySpark, pyiceberg, Polars and DuckDB and Jupyter notebooks. Demonstrates creating tables, changing partition specs (years → hash buckets), inserting three commits (six rows), tagging a snapshot, expiring a snapshot, and querying metadata tables. Covers time travel and branching, copy‑on‑write vs merge‑on‑read, compaction, bloom filters, and isolation levels with practical commands and working examples.
AI-written summary · about
chapters (12)
- 0:00Introduction and agenda
- 1:05Speaker introduction
- 9:17Apache Iceberg basics
- 15:55Setting up Iceberg environment
- 28:05Partitioning optimization
- 41:28Snapshot management
- 46:46Querying Iceberg with libraries
- 52:01Copy-on-write vs merge-on-read
- 57:16Compaction and metadata
- 1:00:54Isolation levels
- 1:04:12Bloom filters
- 1:06:24Q&A and closing
related talks
46mTake the Polar Plunge: A Fearless Introduction to Apache Iceberg™
41mTip of the Iceberg
31mHow Apache Iceberg Enables Multi-Engine Data Platforms
52mApache Iceberg - An Architectural Look Under the Covers
13mExploring the Depths of Apache Iceberg's Metadata Capabilities
45mBuilding an Open Data Lakehouse using Apache Spark, Apache Iceberg and Dremio
49mHow Apache Iceberg Really Works
52mSetting Up Iceberg Tables in Snowflake