Re: [SPAM] Re: [SPAM] Re: Best practices to manage custom statistics

On 11/24/2016 09:59 AM, Moreno Andreo wrote:
> Hi Adrian,
>     First of all: now I've seen that not all fields touched by WHERE

>>
>> Aah, I get it now. You are refreshing forms every 60 seconds over 350
>> users each with their own database. Actually worse then that as there
>> is user overlap over databases(up to 10 per user), so the same
>> database can be hit multiple times at a given refresh. Seems physics
>> is at work here as you have already pointed out. Namely fetching all
>> that data at regular intervals taxes the bandwith as well as the
>> CPU/storage.
> Exactly. At the moment the bottleneck is I/O (running on a VM over a
> RAID-5 with 15kRPM SAS), in the next weeks I'm up to prepare a test
> server with SSDs ("attached SSD" on Google Cloud Platform), that's
> pretty much expensive, but data sheets point out a very good IOPS rate
> (rising as size, and price, rises). CPU is not a problem (almost never
> over 70-80%, average is about 40% over a 4 core server)
>>
>> High levels solutions that come to mind to spread the load out:
>>
>> 1) Replication to spread data across multiple machines.
>> Or just split the databases over multiple non-replicated Postgres
>> instances on separate machines
> Already in place, but only for owner's database. Other databases can't
> be "downloaded" essentially for privacy matters.

Not sure I follow, a user can see their database and up to 9 other users
databases. Not seeing how replication would be any less 'private' then
that, especially if the databases are replicated to machines the company
owns.

>>
>> 2) Caching results from each individual database so subsequent calls
>> for the information do not touch the database. You already touched on
>> this with your counter table.
> Yes, and I'm all ears on suggestions on what to be done and if there are
> hidden caveats...

The usual I would guess:

Storage for the cached data.
Maintaining the cache.
"There are only two hard things in Computer Science: cache invalidation
and naming things."

     -- Phil Karlton

> I heard that stored procedures (and triggers, I suppose) are faster to
> execute than the same "operation" coming from outside because the
> backend has not to translate it, and in this case can be executed only
> when needed

Well that and that less data has to flow back and forth across a
network. In your case you said bandwidth is less of on an issue then
disk I/0 on the server. In-database procedures are still going to
require I/O on the server.

>>
>> 3) Spreading out the refresh interval. Not sure if the 60 second
>> interval is synced across users. Still maybe setting different refresh
>> intervals and/or changing it on the fly when load increases. A back
>> off equation so to speak.
> I'm afraid that if we have a moment when load is extremely high (I
> experienced top measuring 45 (5-minutes basis) on a 4-core machine, it
> was even hard to type in putty console!!), we won't have any upgrade.

Is there a predictability(even a rough one) about when the load spikes
occur? Something you could use to spread the load out.

> Yes, in these conditions we're still not having upgrades, but my goal is
> to find a way to reduce overall query load to have a good (V-)hardware
> design so I can have better performance with lower cost.
> "Pushing" data would be the best way... but I need to have a look to
> LISTEN/NOTIFY, and what it means with Npgsql and JDBC (one thing I
> didn't specify is that between user and database we have a web server,
> in LAN with PgSQL server, hosting web services for the user to interact

?
http://www.memcached.org/
http://redis.io/

> with database. Maybe web server can "proxy" connections (keep them open)
> and the listen/notify method can be achieved (yes, it's a bit of hard
> work to rewrite all connection policies, but if it's necessary...)
>
> I think that a combination of the last two should be the best.
> Tell me what you think.....

I think there are a lot of moving parts to this and more pop up with
each post:) I would not even know how to start to compose a useful
answer to what is a complex problem that also looks to be in the process
of fairly major hardware changes. All I can suggest is that you create a
test setup and start doing some incremental changes, using some of the
suggestions already provided, with tests to measure whether the changes
actually are a benefit.

>
>>
>>>>
>>>> Except when they are wrong:) Still been there.
>>> Don't tell me.... :-)
>>>>
>>
>>>>>>>
>>>>>>> Thanks in advance and sorry for the long message (but I had to
>>>>>>> explain
>>>>>>> such a complex thing)
>>>>>>> Moreno.-
>>
>>
>>
>
>
>
>


--
Adrian Klaver
adrian.klaver@aklaver.com