Re: scaling postgres

On Mon, Aug 3, 2015 at 8:22 AM, Chris Withers <chris(at)simplistix(dot)co(dot)uk>
wrote:

> On 03/08/2015 08:15, Jony Cohen wrote:
>
>> SSD disks are cheep these days but they don't like repeated
>> writes/deletes so it might cause problems down the line (hence my first RAM
>> recommendation)
>>
>> as for keeping the raw data - you could easily do it if you use
>> partitions, if you have daily partitions inheriting from a master table you
>> can quickly access the last day (or even several days)
>> but do take note that a full table scan takes time and you'll need to
>> manage writing to the right partition yourself (not that hard - simply
>> insert to <tablename>_<date>)
>>
>> if you can write the data daily, keeping it will not add any real load (a
>> little on parse times for queries that access the master table)
>>
>
> Interesting, you seem a lot less fussed by these numbers than I am, which
> is good to hear!
>
> At what point does postgres stop scaling?
> What happens when the computational load no longer fits on one machine?
> What are the options then?

I think it is hard to come up with blanket responses to generic questions
such as "What happens when the computational load no longer fits on one
machine?"
I'd say consider a scaling strategy that may be able to make use of your
domain model first, if that is possible of course.

I work in healthcare and patient centric records let me consider multiple
servers for lots and lots of patients. The engineering team from instagram
has been sharing their experience with postgres, which is possible due to
their domain model.

So my humble suggestion is: start from the simplest scenario, ask yourself
if you can use multiple, independent postgres installations, if your domain
model and its data model allow you to do this. If not, you may still have
other options, but it all depends on your access patterns etc.

All the best
Seref

>
> cheers,
>
> Chris
>
>
>
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