WeichenXu123 edited a comment on issue #24734: [SPARK-27870][SQL][PySpark] Flush each batch for pandas UDF (for improving pandas UDFs pipeline) URL: https://github.com/apache/spark/pull/24734#issuecomment-497634309 @BryanCutler But python side write buffer size is hardcoded... and I doubt Scala side `spark.buffer.size` used in spark widely in other buffers config. Another issue is that user is hard to estimate the accurate batch size in bytes. In contrast, per batch flushing is more accurate, only when one batch generated we need flushed it. We can discuss in two case: 1) In most cases, we always use default batch size (`spark.sql.execution.arrow.maxRecordsPerBatch`=10000), this case one batch in bytes is large, so per batch flushing will only influence performance slightly. 2) In some cases such as ML realtime inference case, we make `spark.sql.execution.arrow.maxRecordsPerBatch` small, this case per batch flushing show its performance advantage (See above discussion)
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