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. -- 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]
