Choose a partitioner to use for a cogroup-like operation between a number of RDDs.
If any of the RDDs already has a partitioner, choose that one.
Otherwise, we use a default HashPartitioner. For the number of partitions, if
spark.default.parallelism is set, then we'll use the value from SparkContext
defaultParallelism, otherwise we'll use the max number of upstream partitions.
Unless spark.default.parallelism is set, the number of partitions will be the
same as the number of partitions in the largest upstream RDD, as this should
be least likely to cause out-of-memory errors.
We use two method parameters (rdd, others) to enforce callers passing at least 1 RDD.