On 27/12/17 18:02, Jean Baro wrote:
Sorry guys,

The performance problem is not caused by PG.

'Index Scan using idx_user_country on public.old_card  (cost=0.57..1854.66 rows=460 width=922) (actual time=3.442..76.606 rows=200 loops=1)' '  Output: id, user_id, user_country, user_channel, user_role, created_by_system_key, created_by_username, created_at, last_modified_at, date_start, date_end, payload, tags, menu, deleted, campaign, correlation_id' '  Index Cond: (((old_card.user_id)::text = '1234'::text) AND (old_card.user_country = 'BR'::bpchar))'
'  Buffers: shared hit=11 read=138 written=35'
'Planning time: 7.748 ms'
'Execution time: 76.755 ms'

77ms on an 8GB database with 167MM rows and almost 500GB in size is amazing!!

    gp2 disks are of *variable* performance. Once you exhaust the I/O credits, you are capped to a baseline IOPS that are proportional to the size. I guess you would experience low performance in this scenario since your disk is not big. And actually performance numbers with gp2 disks are unreliable as you don't know in which credit status you are.

    Benchmark with provisioned iops to get a right picture of the desired performance.




Alvaro Hernandez


Now we are investigating other bottlenecks, is it the creation of a new connection to PG  (no connection poller at the moment, like PGBouncer), is it the Lambda start up time? Is it the network performance  between PG and Lambda?

I am sorry for wasting your time guys, it helped us to find the problem though, even if it wasn't a PG problem.

BTW, what a performance! I am impressed.

Thanks PG community!

Em 27 de dez de 2017 14:34, "Jean Baro" <jfb...@gmail.com <mailto:jfb...@gmail.com>> escreveu:

    Thanks Jeremy,

    We will provide a more complete EXPLAIN as other people have

    I am glad we might end up with a much better performance
    (currently each query takes around 2 seconds!).


    Em 27 de dez de 2017 14:02, "Jeremy Finzel" <finz...@gmail.com
    <mailto:finz...@gmail.com>> escreveu:

            The EXPLAIN

            'Index Scan using idx_user_country on card
            (cost=0.57..1854.66 rows=460 width=922)'
            '  Index Cond: (((user_id)::text = '4684'::text) AND
            (user_country = 'BR'::bpchar))'

        Show 3 runs of the full explain analyze plan on given
        condition so that we can also see cold vs warm cache performance.

        There is definitely something wrong as there is no way a query
        like that should take 500ms.  Your instinct is correct there.

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