Hi everyone,

I'd like to start a discussion about releasing Apache Paimon C++ 0.2.3. This 
would be the first Apache release of Paimon C++.


Paimon C++ was originally developed in the [Alibaba Paimon C++ 
repository](https://github.com/alibaba/paimon-cpp) and was subsequently 
contributed to and migrated into the [Apache Paimon community 
repository](https://github.com/apache/paimon-cpp). The 0.2.3 version continues 
the 0.2 release line from the original repository and includes the migration 
work and subsequent development completed in the Apache community.

Before the migration, the project had received contributions from approximately 
30 contributors in the Alibaba repository. Together with the migration and 
continued development in Apache, the project now provides the following major 
capabilities:

- A native C++ SDK for accessing Apache Paimon tables without JVM dependencies

- Catalog, schema, snapshot, manifest, tag management, scan, read, write, and 
commit support

- Append table and primary key table read/write support, including compaction, 
merge-on-read, and deletion vectors


- Parquet, ORC, Avro, and Blob file format support, with Apache Arrow 
integration

- Local and Jindo file system support

- B-tree, Lumina vector, and Lucene full-text global indexes

- Row tracking and data evolution support

- Interoperability with Apache Paimon Java metadata and serialization formats, 
including manifests, snapshots, commit messages, and data splits


It is exciting to see Paimon C++ move from its original repository into the 
Apache Paimon community. Many thanks to all contributors who worked on the 
project in the Alibaba repository, as well as everyone who helped with the 
migration, review, and continued development in Apache.

I would like to volunteer as the release manager for this release.

Please share any concerns, blockers, or changes that should be included before 
the release. If the community reaches consensus and no blockers are identified, 
I plan to begin preparing the first release candidate in the next few days.


Best regards,

Xinyu Liu

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