I have made some progress - the partitioning is very uneven, and everything
goes to one partition. I see that spark partitions by key, so I tried this:
//partitioning is done like partitionIdx = f(key) % numPartitions
//we use random keys to get even partitioning
val uniform = other_stream.transform(rdd => {
rdd.map({ kv =>
val k = kv._1
val v = kv._2
(UUID.randomUUID().toString, v)
})
})
uniform.foreachRDD(rdd => {
rdd.forEachPartition(partition => {
...
As you can see, I'm using random keys. Even in this case, when running with
2 nodes, i verified that one partition is completely empty, and the other
contains all the records.
What is going wrong with the partitioning here?
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