Create a shadow table. For `stats`, it'd be `_stats_rowgroups`.
It contains three columns:
- the clause (eg `city = 'Dawson Creek'`)
- the initial estimate, as a bitmap of rowgroups based on stats
- the actual observed rowgroups, as a bitmap
This papers over poorly sorted parquet files, at the cost of some disk
space. It makes interactive queries much more natural -- drilldown style
queries are much faster, as they can leverage work done by previous
queries.
eg 'SELECT * FROM stats WHERE city = 'Dawson Creek' and question_id >= 1935 and question_id <= 1940`
takes ~584ms on first run, but 9ms on subsequent runs.
We only create entries when the estimates don't match the actual
results.
Fixes#6
- "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.
Colin Dellow