yihua opened a new pull request, #20172: URL: https://github.com/apache/hudi/pull/20172
### Describe the issue this Pull Request addresses issue: #20169 Teams already writing Iceberg tables from Spark, Flink or Kafka Connect cannot adopt the pluggable table format without moving their pipelines to Hudi's entry points, which is a rewrite rather than a switch. ### Summary and Changelog Adds RFC-115, which proposes an Iceberg-side plugin that occupies Iceberg's own pluggable seams so that a user adds a jar and one Spark config and keeps writing to the same Iceberg table: a wrapper catalog as the commit fence, a `SparkTable` subclass whose writes go through `HoodieSparkSqlWriter`, session extensions routing row-level commands to Hudi, maintenance procedures redirected to Hudi table services, and adopt and eject through a table property. The RFC lists the Hudi-side prerequisites (table format settings persistence, foreign data files in the file-system view, catalog configuration threading, metadata table coexistence, SPI types) and the phasing. The Iceberg-to-Hudi behavior mapping, the Spark-specific mechanics and the proof-of-concept status are in appendices. A proof of concept exists in Apache XTable and covers batch writes, row-level commands, maintenance procedures, adopt and eject, merge-on-read with deletion vectors and Structured Streaming on Spark 3.4. ### Impact Documentation only. ### Risk Level none ### Documentation Update none ### Contributor's checklist - [x] Read through [contributor's guide](https://hudi.apache.org/contribute/how-to-contribute) - [x] Enough context is provided in the sections above - [ ] Adequate tests were added if applicable -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
