Hi again,
Thanks for the suggestions.
- I increased work_mem to 64M, which caused disk-based sorting to be
replaced with quicksort and resulted in a modest speedup. However I
have to admit I didn't understand why more work_mem speeds up the heap
scan.
- the suggestion regarding "create statistics on group by" is awesome,
to get rid of sorting is probably the best that could happen to the
query.
- ARMv8 instead of ARMv6 could have a positive impact
I'll mirate to a containerized postgresql-version running on raspbian
os 64-bit as I find some time to spare and report back.
Thanks again, Clemens
Am So., 16. Apr. 2023 um 22:50 Uhr schrieb David Rowley <dgrowleyml@gmail.com>:
>
> On Mon, 17 Apr 2023 at 05:00, Clemens Eisserer <linuxhippy@gmail.com> wrote:
> > Example:
> > table smartmeter with non-null column ts (timestamp with time zone)
> > and brinc index on ts, no pk to avoid a btree index.
> > Sensor values are stored every 5s, so for 1 month there are about 370k
> > rows - and in total the table currently holds about 3M rows.
> > The query to display the values for 1 month takes ~3s, with the bitmap
> > heap scan as well as aggregation taking up most of the time, with
> > sorting in between.
>
> I know you likely don't have much RAM to spare here, but more work_mem
> might help, even just 16MBs might be enough. This would help the Sort
> and to a lesser extent the Bitmap Heap Scan too.
>
> Also, if you'd opted to use PostgreSQL 14 or 15, then you could have
> performed CREATE STATISTICS on your GROUP BY clause expression and
> then run ANALYZE. That might cause the planner to flip to a Hash
> Aggregate which would eliminate the Sort before aggregation. You'd
> only need to sort 236 rows after the Hash Aggregate for the ORDER BY.
>
> Plus, what Justin said.
>
> David
