You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@spark.apache.org by da...@apache.org on 2016/01/05 22:48:51 UTC
spark git commit: [SPARK-12511] [PYSPARK] [STREAMING] Make sure
PythonDStream.registerSerializer is called only once
Repository: spark
Updated Branches:
refs/heads/master c26d17426 -> 6cfe341ee
[SPARK-12511] [PYSPARK] [STREAMING] Make sure PythonDStream.registerSerializer is called only once
There is an issue that Py4J's PythonProxyHandler.finalize blocks forever. (https://github.com/bartdag/py4j/pull/184)
Py4j will create a PythonProxyHandler in Java for "transformer_serializer" when calling "registerSerializer". If we call "registerSerializer" twice, the second PythonProxyHandler will override the first one, then the first one will be GCed and trigger "PythonProxyHandler.finalize". To avoid that, we should not call"registerSerializer" more than once, so that "PythonProxyHandler" in Java side won't be GCed.
Author: Shixiong Zhu <sh...@databricks.com>
Closes #10514 from zsxwing/SPARK-12511.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/6cfe341e
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/6cfe341e
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/6cfe341e
Branch: refs/heads/master
Commit: 6cfe341ee89baa952929e91d33b9ecbca73a3ea0
Parents: c26d174
Author: Shixiong Zhu <sh...@databricks.com>
Authored: Tue Jan 5 13:48:47 2016 -0800
Committer: Davies Liu <da...@gmail.com>
Committed: Tue Jan 5 13:48:47 2016 -0800
----------------------------------------------------------------------
python/pyspark/streaming/context.py | 33 +++++++++++++++-----
python/pyspark/streaming/util.py | 3 +-
.../spark/streaming/StreamingContext.scala | 12 +++++++
3 files changed, 38 insertions(+), 10 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/spark/blob/6cfe341e/python/pyspark/streaming/context.py
----------------------------------------------------------------------
diff --git a/python/pyspark/streaming/context.py b/python/pyspark/streaming/context.py
index 3deed52..5cc4bbd 100644
--- a/python/pyspark/streaming/context.py
+++ b/python/pyspark/streaming/context.py
@@ -98,8 +98,28 @@ class StreamingContext(object):
# register serializer for TransformFunction
# it happens before creating SparkContext when loading from checkpointing
- cls._transformerSerializer = TransformFunctionSerializer(
- SparkContext._active_spark_context, CloudPickleSerializer(), gw)
+ if cls._transformerSerializer is None:
+ transformer_serializer = TransformFunctionSerializer()
+ transformer_serializer.init(
+ SparkContext._active_spark_context, CloudPickleSerializer(), gw)
+ # SPARK-12511 streaming driver with checkpointing unable to finalize leading to OOM
+ # There is an issue that Py4J's PythonProxyHandler.finalize blocks forever.
+ # (https://github.com/bartdag/py4j/pull/184)
+ #
+ # Py4j will create a PythonProxyHandler in Java for "transformer_serializer" when
+ # calling "registerSerializer". If we call "registerSerializer" twice, the second
+ # PythonProxyHandler will override the first one, then the first one will be GCed and
+ # trigger "PythonProxyHandler.finalize". To avoid that, we should not call
+ # "registerSerializer" more than once, so that "PythonProxyHandler" in Java side won't
+ # be GCed.
+ #
+ # TODO Once Py4J fixes this issue, we should upgrade Py4j to the latest version.
+ transformer_serializer.gateway.jvm.PythonDStream.registerSerializer(
+ transformer_serializer)
+ cls._transformerSerializer = transformer_serializer
+ else:
+ cls._transformerSerializer.init(
+ SparkContext._active_spark_context, CloudPickleSerializer(), gw)
@classmethod
def getOrCreate(cls, checkpointPath, setupFunc):
@@ -116,16 +136,13 @@ class StreamingContext(object):
gw = SparkContext._gateway
# Check whether valid checkpoint information exists in the given path
- if gw.jvm.CheckpointReader.read(checkpointPath).isEmpty():
+ ssc_option = gw.jvm.StreamingContextPythonHelper().tryRecoverFromCheckpoint(checkpointPath)
+ if ssc_option.isEmpty():
ssc = setupFunc()
ssc.checkpoint(checkpointPath)
return ssc
- try:
- jssc = gw.jvm.JavaStreamingContext(checkpointPath)
- except Exception:
- print("failed to load StreamingContext from checkpoint", file=sys.stderr)
- raise
+ jssc = gw.jvm.JavaStreamingContext(ssc_option.get())
# If there is already an active instance of Python SparkContext use it, or create a new one
if not SparkContext._active_spark_context:
http://git-wip-us.apache.org/repos/asf/spark/blob/6cfe341e/python/pyspark/streaming/util.py
----------------------------------------------------------------------
diff --git a/python/pyspark/streaming/util.py b/python/pyspark/streaming/util.py
index abbbf6e..e617fc9 100644
--- a/python/pyspark/streaming/util.py
+++ b/python/pyspark/streaming/util.py
@@ -89,11 +89,10 @@ class TransformFunctionSerializer(object):
it uses this class to invoke Python, which returns the serialized function
as a byte array.
"""
- def __init__(self, ctx, serializer, gateway=None):
+ def init(self, ctx, serializer, gateway=None):
self.ctx = ctx
self.serializer = serializer
self.gateway = gateway or self.ctx._gateway
- self.gateway.jvm.PythonDStream.registerSerializer(self)
self.failure = None
def dumps(self, id):
http://git-wip-us.apache.org/repos/asf/spark/blob/6cfe341e/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala
----------------------------------------------------------------------
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala b/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala
index c4a10aa..a5ab666 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala
@@ -902,3 +902,15 @@ object StreamingContext extends Logging {
result
}
}
+
+private class StreamingContextPythonHelper {
+
+ /**
+ * This is a private method only for Python to implement `getOrCreate`.
+ */
+ def tryRecoverFromCheckpoint(checkpointPath: String): Option[StreamingContext] = {
+ val checkpointOption = CheckpointReader.read(
+ checkpointPath, new SparkConf(), SparkHadoopUtil.get.conf, false)
+ checkpointOption.map(new StreamingContext(null, _, null))
+ }
+}
---------------------------------------------------------------------
To unsubscribe, e-mail: commits-unsubscribe@spark.apache.org
For additional commands, e-mail: commits-help@spark.apache.org