[GitHub] [beam] damccorm opened a new issue, #21657: Native implementation for serialized Rows to/from Arrow

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damccorm opened a new issue, #21657:
URL: https://github.com/apache/beam/issues/21657

   With https://s.apache.org/batched-dofns (BEAM-14213), we want to encourage users to develop pipelines that process arrow data within the Python SDK, but communicating batches of data across SDKs or from SDK to Runner is left as future work. So when Arrow data is processed in the SDK, it must be converted to/from Rows for transmission over the Fn API. So the current ideal Python execution looks like:
   
   1. read row oriented data over the Fn API, deserialize  with SchemaCoder 
   2. Buffer rows and construct an arrow RecordBatch/Table object
   3. Perform user computation(s)
   4. Explode output RecordBatch/Table into rows
   5. Serialize rows with SchemaCoder and write out over the Fn API
   
   Note that (1,2) and (4,5) will exist in every stage of the user's pipeline, and they'll also exist when Python transforms (e.g. dataframe read_csv) are used in other SDKs. We should improve performance for this hot path by making a native (cythonized) implementation for (1,2) and (4,5).
   
   Imported from Jira [BEAM-14540](https://issues.apache.org/jira/browse/BEAM-14540). Original Jira may contain additional context.
   Reported by: bhulette.


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