Github user mridulm commented on a diff in the pull request: https://github.com/apache/spark/pull/44#discussion_r10242223 --- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala --- @@ -847,6 +847,8 @@ class SparkContext( partitions: Seq[Int], allowLocal: Boolean, resultHandler: (Int, U) => Unit) { + val partitionRange = (0 until rdd.partitions.size) + require(partitions.forall(partitionRange.contains(_)), "partition index out of range") --- End diff -- Take a look at use of PartitionPruningRDD .. On Mar 4, 2014 9:33 AM, "LiGuoqiang" <notificati...@github.com> wrote: > In core/src/main/scala/org/apache/spark/SparkContext.scala: > > > @@ -847,6 +847,8 @@ class SparkContext( > > partitions: Seq[Int], > > allowLocal: Boolean, > > resultHandler: (Int, U) => Unit) { > > + val partitionRange = (0 until rdd.partitions.size) > > + require(partitions.forall(partitionRange.contains(_)), "partition index out of range") > > > 1. > > Can be changed > > require(partitions.toSet.diff(rdd.partitions.map(_.index).toSet).isEmpty, "partition index out of range") > > 2. > > Custom Partitioner causing a lot of problems > > val partitioner = new Partitioner { > override def numPartitions: Int = 2 > override def getPartition(key: Any): Int = key.hashCode() % 2 > } > > val pairs = sc.parallelize(Array((1, 2), (3, 4), (5, 6), (-1, 7))) > val shuffled = pairs.partitionBy(partitioner) > shuffled.count > > > -- > Reply to this email directly or view it on GitHub<https://github.com/apache/spark/pull/44/files#r10242185> > . >
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