[SPARK-13021][CORE] Fail fast when custom RDDs violate RDD.partition's API contract

Spark's `Partition` and `RDD.partitions` APIs have a contract which requires custom implementations of `RDD.partitions` to ensure that for all `x`, `rdd.partitions(x).index == x`; in other words, the `index` reported by a repartition needs to match its position in the partitions array.

If a custom RDD implementation violates this contract, then Spark has the potential to become stuck in an infinite recomputation loop when recomputing a subset of an RDD's partitions, since the tasks that are actually run will not correspond to the missing output partitions that triggered the recomputation. Here's a link to a notebook which demonstrates this problem: https://rawgit.com/JoshRosen/e520fb9a64c1c97ec985/raw/5e8a5aa8d2a18910a1607f0aa4190104adda3424/Violating%2520RDD.partitions%2520contract.html

In order to guard against this infinite loop behavior, this patch modifies Spark so that it fails fast and refuses to compute RDDs' whose `partitions` violate the API contract.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #10932 from JoshRosen/SPARK-13021.