[SPARK-1777] Prevent OOMs from single partitions

**Problem.** When caching, we currently unroll the entire RDD partition before making sure we have enough free memory. This is a common cause for OOMs especially when (1) the BlockManager has little free space left in memory, and (2) the partition is large.

**Solution.** We maintain a global memory pool of `M` bytes shared across all threads, similar to the way we currently manage memory for shuffle aggregation. Then, while we unroll each partition, periodically check if there is enough space to continue. If not, drop enough RDD blocks to ensure we have at least `M` bytes to work with, then try again. If we still don't have enough space to unroll the partition, give up and drop the block to disk directly if applicable.

**New configurations.**
- `spark.storage.bufferFraction` - the value of `M` as a fraction of the storage memory. (default: 0.2)
- `spark.storage.safetyFraction` - a margin of safety in case size estimation is slightly off. This is the equivalent of the existing `spark.shuffle.safetyFraction`. (default 0.9)

For more detail, see the [design document](https://issues.apache.org/jira/secure/attachment/12651793/spark-1777-design-doc.pdf). Tests pending for performance and memory usage patterns.

Instead of trying to ensureFreeSpace on all of the globalUnrollMemory at once, let's maybe ensure only enough for the amount we want to request.

If you change ensureFreeSpace to not do accounting differently when we're unrolling (as per my comment below), I think this will become something like this:
```
val maxWeCanFree = globalUnrollMemory - unrollMemory // (the sum of your map)
if (maxWeCanFree > extraAmountWeNeed) {
  ensureFreeSpace(blockId, extraAmountWeNeed)
}
```
Basically this means we can only request extra space until 20% of the memory pool is allocated to unrolling. If we can fit our next request within that 20%, we go ahead and do it. Otherwise we don't.