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author | Shixiong Zhu <shixiong@databricks.com> | 2016-01-05 13:48:47 -0800 |
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committer | Davies Liu <davies.liu@gmail.com> | 2016-01-05 13:48:47 -0800 |
commit | 6cfe341ee89baa952929e91d33b9ecbca73a3ea0 (patch) | |
tree | c578445bdd6b5610875b189d6e4a8e7cc2efc20f /streaming/src/main | |
parent | c26d174265f6b4682210fcc406e6603b4f7dc784 (diff) | |
download | spark-6cfe341ee89baa952929e91d33b9ecbca73a3ea0.tar.gz spark-6cfe341ee89baa952929e91d33b9ecbca73a3ea0.tar.bz2 spark-6cfe341ee89baa952929e91d33b9ecbca73a3ea0.zip |
[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 <shixiong@databricks.com>
Closes #10514 from zsxwing/SPARK-12511.
Diffstat (limited to 'streaming/src/main')
-rw-r--r-- | streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala | 12 |
1 files changed, 12 insertions, 0 deletions
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 c4a10aa2dd..a5ab666975 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)) + } +} |