Hi Danilo, following my experience now SSD or RAM Disk is the only way to
speed up queries. It depends on your storage occupation of your 41M docs.
If you don't have Enterprise SSD you can add consumer SSD as a fast cache
(linux caching modules "flashcache / bcache" are able to use cheap SSD as a
data cache and have your data safe stored on SATA Disks).

I don't think you can increase performances without changing technology on
the storage system.

Regards.
Dario

Il giorno lun 22 feb 2021 alle ore 08:52 Danilo Tomasoni <tomas...@cosbi.eu>
ha scritto:

> Hello all,
> we are running a solr instance with around 41 MLN documents on a SATA
> class 10 disk with around 10.000 rpm.
> We are experiencing very slow query responses (in the order of hours..)
> with an average of 205 segments.
> We made a test with a normal pc and an SSD disk, and there the same solr
> instance with the same data and the same number of segments was around 45
> times faster.
> Force optimize was also tried to improve the performances, but it was very
> slow, so we abandoned it.
>
> Since we still don't have enterprise server ssd disks, we are now
> wondering if in the meanwhile defragmenting the solrdata folder can help.
> The idea is that due to many updates, each segment file is fragmented
> across different phisical blocks.
> Put in another way, each segment file is non-contiguous on disk, and this
> can slow-down the solr response.
>
> What do you suggest?
> Is this somewhat equivalent to force-optimize or it can be faster?
>
> Thank you.
> Danilo
>
> Danilo Tomasoni
>
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> Computational and Systems Biology (COSBI)
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