The below query basically gives the result by maintaining the order of the sizes in the list. explain analyze select "price_levels"."name", "price_levels"."size" from "price_levels" join unnest(array['M', 'L', 'XL', '2XL', '3XL', '4XL', '5XL', '6XL', 'S']) with ordinality t(size, ord) using (size) order by t.size I have a Btree index on the size column. Explain output is: Merge Join (cost=4.61..5165.38 rows=60000 width=46) (actual time=0.157..57.872 rows=60000 loops=1) Merge Cond: ((price_levels.size)::text = t.size) -> Index Scan using price_levels_size_idx on price_levels (cost=0.29..4111.05 rows=60000 width=14) (actual time=0.044..25.941 rows=60000 loops=1) -> Sort (cost=4.32..4.57 rows=100 width=32) (actual time=0.108..3.946 rows=53289 loops=1) Sort Key: t.size Sort Method: quicksort Memory: 25kB -> Function Scan on unnest t (cost=0.00..1.00 rows=100 width=32) (actual time=0.030..0.033 rows=9 loops=1) Planning time: 0.667 ms Execution time: 62.846 ms |
