viirya commented on code in PR #55552:
URL: https://github.com/apache/spark/pull/55552#discussion_r3191694232
##########
core/src/main/scala/org/apache/spark/internal/config/Python.scala:
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@@ -150,4 +150,28 @@ private[spark] object Python {
.version("4.1.0")
.booleanConf
.createWithDefault(true)
+
+ val PYTHON_UDF_PIPELINED_EXECUTION =
+ ConfigBuilder("spark.python.udf.pipelined.enabled")
+ .doc("When true, enables pipelined (asynchronous) data transfer between
JVM and Python " +
+ "UDF workers. In pipelined mode, input serialization runs in a
separate writer thread " +
+ "while the main task thread reads output from the Python worker,
allowing the two " +
+ "directions to overlap for improved throughput. " +
+ "This is particularly beneficial for compute-heavy UDFs (e.g., ML
inference).")
+ .version("4.2.0")
Review Comment:
Yes. Thanks!
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