> On Sep 13, 2018, at 12:17 PM, Arup Rakshit <a...@zeit.io> wrote:
>
> 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
>
>
>
> Thanks,
>
> Arup Rakshit
> a...@zeit.io <mailto:a...@zeit.io>
>
>
There are not value of size fit it to be a worthwhile key.
>
