holdenk commented on code in PR #52679:
URL: https://github.com/apache/spark/pull/52679#discussion_r2482828853
##########
core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala:
##########
@@ -38,7 +38,9 @@ import
org.apache.spark.internal.config.Python.PYTHON_FACTORY_IDLE_WORKER_MAX_PO
import org.apache.spark.security.SocketAuthHelper
import org.apache.spark.util.{RedirectThread, Utils}
-case class PythonWorker(channel: SocketChannel) {
+case class PythonWorker(
+ channel: SocketChannel,
+ extraChannel: Option[SocketChannel] = None) {
Review Comment:
Let's call this profile data channel or something?
##########
python/pyspark/worker.py:
##########
@@ -3167,7 +3170,28 @@ def func(_, it):
return func, None, ser, ser
+def write_profile(outfile):
+ import yappi
+
+ while True:
+ stats = []
+ for thread in yappi.get_thread_stats():
+ data = list(yappi.get_func_stats(ctx_id=thread.id))
+ stats.extend([{str(k): str(v) for k, v in d.items()} for d in
data])
+ pickled = pickle.dumps(stats)
Review Comment:
While pickle? Would JSON maybe make more sense so we can interpert more
easily in say the Spark UI in the future?
##########
python/pyspark/worker.py:
##########
@@ -3167,7 +3170,28 @@ def func(_, it):
return func, None, ser, ser
+def write_profile(outfile):
+ import yappi
+
+ while True:
+ stats = []
+ for thread in yappi.get_thread_stats():
+ data = list(yappi.get_func_stats(ctx_id=thread.id))
+ stats.extend([{str(k): str(v) for k, v in d.items()} for d in
data])
+ pickled = pickle.dumps(stats)
+ write_with_length(pickled, outfile)
+ outfile.flush()
+ time.sleep(1)
+
+
def main(infile, outfile):
Review Comment:
Maybe rename to outputs
##########
python/pyspark/worker.py:
##########
@@ -3167,7 +3170,28 @@ def func(_, it):
return func, None, ser, ser
+def write_profile(outfile):
+ import yappi
+
+ while True:
+ stats = []
+ for thread in yappi.get_thread_stats():
+ data = list(yappi.get_func_stats(ctx_id=thread.id))
+ stats.extend([{str(k): str(v) for k, v in d.items()} for d in
data])
+ pickled = pickle.dumps(stats)
+ write_with_length(pickled, outfile)
+ outfile.flush()
+ time.sleep(1)
Review Comment:
I know yappi says it's fast but 1 second busy loop seems maybe overkill or
should be configurable?
##########
core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala:
##########
@@ -281,6 +281,7 @@ private[spark] abstract class BasePythonRunner[IN, OUT](
}
// allow the user to set the batch size for the BatchedSerializer on UDFs
envVars.put("PYTHON_UDF_BATCH_SIZE", batchSizeForPythonUDF.toString)
+ envVars.put("PYSPARK_RUNTIME_PROFILE", true.toString)
Review Comment:
obviously make configurable later
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