I'm having trouble loading a streaming job from a checkpoint when a
broadcast variable is defined. I've seen the solution by TD in Scala (
https://issues.apache.org/jira/browse/SPARK-5206) that uses a singleton to
get/create an accumulator, but I can't seem to get it to work in PySpark
with a broadcast variable.
A simplified code snippet:
broadcastHelper = {}
class StreamingJob(object):
def transform_function(self):
def transform_function_inner(t, rdd):
if 'bar' not in broadcastHelper:
broadcastHelper['bar'] =
rdd.context.broadcast(broadcastHelper['foo'])
return rdd.filter(lambda event: event['id'] not in
broadcastHelper['bar'].value)
return transform_function_inner
def createContext(self):
dstream = self.getKafkaStream()
dstream = dstream.transform(self.transform_function())
dstream.foreachRdd(lambda rdd:
rdd.foreachPartition(self.send_partition))
def run(self):
broadcastHelper['foo'] = {1, 2, 3}
ssc = StreamingContext.getOrCreate(self.checkpoint_path,
self.createContext)
ssc.start()
ssc.awaitTermination()
The error I inevitably get when restoring from the checkpoint is:
Exception: (Exception("Broadcast variable '3' not loaded!",), <function
_from_id at 0x1089a1230>, (3L,))
Has anyone had any luck checkpointing in PySpark with a broadcast variable?
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