Shaheed Haque <shaheedhaque@xxxxxxxxx> writes:
> Unfortunately, the real query which I think should behave very
> similarly is still at the several-seconds level despite using the
> index. ...
> -> Bitmap Heap Scan on paiyroll_payrun (cost=26.88..30.91 rows=1
> width=4) (actual time=32.488..2258.891 rows=62 loops=1)
> Recheck Cond: ((company_id = 173) AND ((snapshot ->
> 'employee'::text) ? '16376'::text))
> Filter: (((snapshot #>
> '{employee,16376,last_run_of_employment}'::text[]) <> 'true'::jsonb)
> OR ((snapshot #> '{employee,16376,pay_graph}'::text[]) <> '0'::jsonb)
> OR ((snapshot #> '{employee,16376,state,employment,-1,2}'::text[]) <=
> '0'::jsonb))
> Heap Blocks: exact=5
> -> BitmapAnd (cost=26.88..26.88 rows=1 width=0) (actual
> time=0.038..0.039 rows=0 loops=1)
> -> Bitmap Index Scan on paiyroll_payrun_company_id_ce341888
> (cost=0.00..6.56 rows=304 width=0) (actual time=0.016..0.016 rows=304
> loops=1)
> Index Cond: (company_id = 173)
> -> Bitmap Index Scan on idx1 (cost=0.00..20.07 rows=9
> width=0) (actual time=0.021..0.021 rows=62 loops=1)
> Index Cond: ((snapshot -> 'employee'::text) ? '16376'::text)
> IIUC, at the bottom, the indices are doing their thing, but a couple
> of layers up, the "Bitmap Heap Scan" jumps from ~30ms to 2200ms. But I
> cannot quite see why.
I suppose it's the execution of that "Filter" condition, which will
require perhaps as many as three fetches of the "snapshot" column.
You really need to rethink that data structure. Sure, you can store tons
of unorganized data in a jsonb column, but you pay for that convenience
with slow access. Normalizing the bits you need frequently into a more
traditional relational schema is the route to better-performing queries.
regards, tom lane
