Major Description
I am reasonably sure there is some issue here in Streaming and that I'm not missing something basic, but not 100%. I went ahead and posted it as a JIRA to track, since it's come up a few times before without resolution, and right now I can't get checkpointing to work at all.
When Spark Streaming checkpointing is enabled, I see a NotSerializableException thrown for a Hadoop Configuration object, and it seems like it is not one from my user code.
Before I post my particular instance see http://mail-archives.apache.org/mod_mbox/spark-user/201408.mbox/%3C1408135046777-12202.post@n3.nabble.com%3E for another occurrence.
I was also on customer site last week debugging an identical issue with checkpointing in a Scala-based program and they also could not enable checkpointing without hitting exactly this error.
The essence of my code is:
final JavaSparkContext sparkContext = new JavaSparkContext(sparkConf); JavaStreamingContextFactory streamingContextFactory = new JavaStreamingContextFactory() { @Override public JavaStreamingContext create() { return new JavaStreamingContext(sparkContext, new Duration(batchDurationMS)); } }; streamingContext = JavaStreamingContext.getOrCreate( checkpointDirString, sparkContext.hadoopConfiguration(), streamingContextFactory, false); streamingContext.checkpoint(checkpointDirString);
It yields:
2014-10-31 14:29:00,211 ERROR OneForOneStrategy:66 org.apache.hadoop.conf.Configuration - field (class "org.apache.spark.streaming.dstream.PairDStreamFunctions$$anonfun$9", name: "conf$2", type: "class org.apache.hadoop.conf.Configuration") - object (class "org.apache.spark.streaming.dstream.PairDStreamFunctions$$anonfun$9", <function2>) - field (class "org.apache.spark.streaming.dstream.ForEachDStream", name: "org$apache$spark$streaming$dstream$ForEachDStream$$foreachFunc", type: "interface scala.Function2") - object (class "org.apache.spark.streaming.dstream.ForEachDStream", org.apache.spark.streaming.dstream.ForEachDStream@cb8016a) ...
This looks like it's due to PairRDDFunctions, as this saveFunc seems
to be org.apache.spark.streaming.dstream.PairDStreamFunctions$$anonfun$9
:
def saveAsNewAPIHadoopFiles(
prefix: String,
suffix: String,
keyClass: Class[_],
valueClass: Class[_],
outputFormatClass: Class[_ <: NewOutputFormat[_, _]],
conf: Configuration = new Configuration
) {
val saveFunc = (rdd: RDD[(K, V)], time: Time) => {
val file = rddToFileName(prefix, suffix, time)
rdd.saveAsNewAPIHadoopFile(file, keyClass, valueClass,
outputFormatClass, conf)
}
self.foreachRDD(saveFunc)
}
Is that not a problem? but then I don't know how it would ever work in Spark. But then again I don't see why this is an issue and only when checkpointing is enabled.
Long-shot, but I wonder if it is related to closure issues like https://issues.apache.org/jira/browse/SPARK-1866
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