Optimizations to CPU usage of external spilling code

In the external spilling code in ExternalAppendOnlyMap and CoGroupedRDD, there are a few opportunities for optimization:

• There are lots of uses of pattern-matching on Tuple2 (e.g. val (k, v) = pair), which we found to be much slower than accessing fields directly
• Hash codes for each element are computed many times in StreamBuffer.minKeyHash, which will be expensive for some data types
• Uses of buffer.remove() may be expensive if there are lots of hash collisions (better to swap in the last element into that position)
• More objects are allocated than is probably necessary, e.g. ArrayBuffers and pairs
• Because ExternalAppendOnlyMap is only given one key-value pair at a time, it allocates a new update function on each one, unlike the way we pass a single update function to AppendOnlyMap in Aggregator

These should help because situations where we're spilling are also ones where there is presumably a lot of GC pressure in the new generation.