Re: querying with index on jsonb slower than standard column. Why?

Tim Dudgeon <tdudgeon(dot)ml(at)gmail(dot)com> writes:
> The index created is not a gin index. Its a standard btree index on the
> data extracted from the json. So the indexes on the standard columns and
> the ones on the 'fields' extracted from the json seem to be equivalent.
> But perform differently.

I don't see any particular difference ...

regression=# explain analyze select count(*) from json_test where (data->>'assay1_ic50')::float > 90
and (data->>'assay2_ic50')::float < 10;
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Aggregate (cost=341613.79..341613.80 rows=1 width=0) (actual time=901.207..901.208 rows=1 loops=1)
-> Bitmap Heap Scan on json_test (cost=123684.69..338836.02 rows=1111111 width=0) (actual time=497.982..887.128 rows=100690 loops=1)
Recheck Cond: ((((data ->> 'assay2_ic50'::text))::double precision < 10::double precision) AND (((data ->> 'assay1_ic50'::text))::double precision > 90::double precision))
Heap Blocks: exact=77578
-> BitmapAnd (cost=123684.69..123684.69 rows=1111111 width=0) (actual time=476.585..476.585 rows=0 loops=1)
-> Bitmap Index Scan on idx_data_json_assay2_ic50 (cost=0.00..61564.44 rows=3333333 width=0) (actual time=219.287..219.287 rows=999795 loops=1)
Index Cond: (((data ->> 'assay2_ic50'::text))::double precision < 10::double precision)
-> Bitmap Index Scan on idx_data_json_assay1_ic50 (cost=0.00..61564.44 rows=3333333 width=0) (actual time=208.197..208.197 rows=1000231 loops=1)
Index Cond: (((data ->> 'assay1_ic50'::text))::double precision > 90::double precision)
Planning time: 0.128 ms
Execution time: 904.196 ms
(11 rows)

regression=# explain analyze select count(*) from json_test where assay1_ic50 > 90 and assay2_ic50 < 10;
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------
Aggregate (cost=197251.24..197251.25 rows=1 width=0) (actual time=895.238..895.238 rows=1 loops=1)
-> Bitmap Heap Scan on json_test (cost=36847.25..197003.24 rows=99197 width=0) (actual time=495.427..881.033 rows=100690 loops=1)
Recheck Cond: ((assay2_ic50 < 10::double precision) AND (assay1_ic50 > 90::double precision))
Heap Blocks: exact=77578
-> BitmapAnd (cost=36847.25..36847.25 rows=99197 width=0) (actual time=474.201..474.201 rows=0 loops=1)
-> Bitmap Index Scan on idx_data_col_assay2_ic50 (cost=0.00..18203.19 rows=985434 width=0) (actual time=219.060..219.060 rows=999795 loops=1)
Index Cond: (assay2_ic50 < 10::double precision)
-> Bitmap Index Scan on idx_data_col_assay1_ic50 (cost=0.00..18594.21 rows=1006637 width=0) (actual time=206.066..206.066 rows=1000231 loops=1)
Index Cond: (assay1_ic50 > 90::double precision)
Planning time: 0.129 ms
Execution time: 898.237 ms
(11 rows)

regression=# \timing
Timing is on.
regression=# select count(*) from json_test where (data->>'assay1_ic50')::float > 90
and (data->>'assay2_ic50')::float < 10;
count
--------
100690
(1 row)

Time: 882.607 ms
regression=# select count(*) from json_test where assay1_ic50 > 90 and assay2_ic50 < 10;
count
--------
100690
(1 row)

Time: 881.071 ms

regards, tom lane