WIP: Support constaints on distance column in KNN queries, for pagination and range queries

[asg017]

refs #165

.load dist/vec0
create virtual table vec_items using vec0(
vector float[1]
);
insert into vec_items(rowid, vector)
select value, json_array(value) from generate_series(1, 100);
select vec_to_json(vector), distance
from vec_items
where vector match '[1]'and k =5;
/*┌─────────────────────┬──────────┐│ vec_to_json(vector) │ distance │├─────────────────────┼──────────┤│ '[1.000000]' │ 0.0 ││ '[2.000000]' │ 1.0 ││ '[3.000000]' │ 2.0 ││ '[4.000000]' │ 3.0 ││ '[5.000000]' │ 4.0 │└─────────────────────┴──────────┘*/select vec_to_json(vector), distance
from vec_items
where vector match '[1]'and k =5-- the new magicand distance >4.0;
/*┌─────────────────────┬──────────┐│ vec_to_json(vector) │ distance │├─────────────────────┼──────────┤│ '[6.000000]' │ 5.0 ││ '[7.000000]' │ 6.0 ││ '[8.000000]' │ 7.0 ││ '[9.000000]' │ 8.0 ││ '[10.000000]' │ 9.0 │└─────────────────────┴──────────┘*/

TODO

• tests
• docs
• edge cases - when multiple items have same distance calculations
• should distances be f64?