This drops the `= 'Dawson Creek'` query from 210ms to 145ms.
Maybe inlining would have been an option here? I'm not familiar enough
with g++ to know. :(
Now the `== 'Dawson Creek'` query is ~210ms, which is approx the
same as a `count(*)` query. This seems maybe OK, since the row group
filter is only excluding 30% of records.
This gets the census `== 'Dawson Creek'` query down to ~410ms from
~650ms.
That still seems much slower than it should be. Am I accidentally
doing a copy? Now to go learn how to profile C++ code...
For the statscan census set filtering on `== 'Dawson Creek'`, the query
goes from 980ms to 660ms.
This is expected, since the data isn't sorted by that column.
I'll try adding some scaffolding to do filtering at the row level, too.
We could also try unpacking the dictionary and testing the individual
values, although we may want some heuristics to decide whether it's
worth doing -- eg if < 10% of the rows have a unique value.
Ideally, this should be like a ~1ms query.
- "fixed_size_binary" -> "binary_10"
- make null parquet use rowgroups of sie 10: first rowgroup
has no nulls, 2nd has all null, 3rd-10th have alternating
nulls
This is prep for making a Postgres layer to use as an oracle
for generating test cases so that we have good coverage before
implementing advanced `xBestIndex` and `xFilter` modes.
