From the trenches: Managing Apache Iceberg metadata for near-real-time workloads
Blog post from Onehouse
The blog discusses the challenges and solutions related to managing Apache Iceberg snapshots for data pipelines that require frequent writes for near-real-time ingest latencies. Apache Iceberg, a popular open table format, allows for schema evolution and time travel but faces difficulties in metadata management and scaling with frequent writes. Onehouse, described as the "Open Lakehouse Company," utilizes Apache Hudi and Apache XTable to manage metadata for large production tables, addressing issues such as slow snapshot expiration and orphan file deletion. The solutions include implementing a custom FileCleanupStrategy to skip scanning data files, using Hudi's cleaning table service for efficient file management, and leveraging Hudi's write markers to track and clean partial write operations. These strategies aim to maintain data freshness SLAs without resorting to costly daily or weekly maintenance operations. By asynchronously running table optimizations and maintenance services, Onehouse ensures continuous ingestion without impacting data freshness, supporting their vision of a Universal Data Lakehouse.
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