Optimize queries on time-series collections which request the most recent value

There are a couple ways to write a similar query by flipping the sort and $first/$last, but consider this example:

db.my_timeseries.aggregate([

  {$sort: {ts: 1}},

  {$group: {_id: "$meta.x", most_recent_foo: {$last: "$foo"}}}

])

This is the same pattern as described in SERVER-9507, and we should be able to have this query do something like a DISTINCT_SCAN if one of the following indexes exist:

{ts: +/-1, meta: +/-1}

{meta: +/-1, ts: +/-1}

{_id: +/-1, meta: +/-1}

{meta: +/-1, _id: +/-1}

The last two would probably be pretty challenging to implement and would have to do some similar analysis to SERVER-55106 in order to translate the "ts" predicate/scan into something on _id. It may not even be possible.

We could also instead consider transforming the query not into a distinct scan but into a reverse _id scan to ensure whatever we find is most recent, and performing a streaming $group implementation (SERVER-4507). This is generally a hard operation to perform, but within the context of a time-series collection it might be easier to prove that the optimization is correct.