d information. Since the RDD is already
> partitioned, there is no need to worry about repartitioning.
>
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Thanks Daniel for the detailed information. Since the RDD is already
partitioned, there is no need to worry about repartitioning.
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tions?
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Thanks, will give that a try.
I see the number of partitions requested is 8 (through HashPartitioner(8)).
If I have a 40 node cluster, whats the recommended number of partitions?
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(pfUser(0) -> pfUser(1))})
.partitionBy(new
org.apache.spark.HashPartitioner(8))
You have a kvRdd with pageName as Key and UserID as Value.
Thanks
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Forgot to mention, I'm using Spark 1.0.0 and running against 40 node
yarn-cluster.
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