use a shadow table for faster rowgroup pruning

[cldellow]

See discussion in #34.

ATM we prune row groups by doing a linear scan over the row group statistics. For ~10-20K row groups, this takes ~20ms. Where possible, it'd be nice to do this pruning via a faster mechanism. This could make some parquet-backed tables almost competitive with SQLite itself for needle in a haystack queries. eg I think this is possible:

• sqlite: 0.1ms
• parquet w/fast rowgroup pruning: 1-2ms
• parquet w/linear rowgroup pruning: 20ms

Option 1: SQLite shadow table

Perhaps on table connect we could populate a shadow table with the statistics, then use that at query time to generate an array of row group IDs to traverse.

I'm not as sure that this is a slamdunk. SQLite doesn't support using more than 1 index in a query, so it will often end up doing a table scan.

Option 2: our own indexing

We could do the indexing ourself in C. I'm not enthused about this.

I guess we could sort the ranges by their lower bound into some array arr.

Then binary search arr for lower bound < our lowest value (order by lo desc limit 1) and lower bound > our highest value (order by low asc limit 1), which gives us the bounds to search.

Actually, I guess we could translate that into a series of SQLite calls.

Option 3: constrain the problem

We could support it only for monotonically increasing values -- then we could do 2 binary searches to determine the lower and upper bounds of the row groups to search. We could either do the search in C, or delegate it to SQLite.