Re: Can I add Index to make a query faster which involves joins on unnest ?

Hello Rob,

So how do I improve this query speed?

Thanks,

Arup Rakshit
ar(at)zeit(dot)io

> On 14-Sep-2018, at 12:27 AM, Rob Sargent <robjsargent(at)gmail(dot)com> wrote:
>
>
>
>> On Sep 13, 2018, at 12:17 PM, Arup Rakshit <ar(at)zeit(dot)io <mailto:ar(at)zeit(dot)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
>> ar(at)zeit(dot)io <mailto:ar(at)zeit(dot)io>
>>
>>
> There are not value of size fit it to be a worthwhile key.
>>
>