From: | Kenneth Marshall <ktm(at)rice(dot)edu> |
---|---|
To: | Ivan Voras <ivoras(at)freebsd(dot)org> |
Cc: | Heikki Linnakangas <heikki(dot)linnakangas(at)enterprisedb(dot)com>, pgsql-performance(at)postgresql(dot)org |
Subject: | Re: Storing sensor data |
Date: | 2009-05-28 15:01:02 |
Message-ID: | 20090528150102.GF18879@it.is.rice.edu |
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Lists: | pgsql-performance |
On Thu, May 28, 2009 at 04:55:34PM +0200, Ivan Voras wrote:
> 2009/5/28 Heikki Linnakangas <heikki(dot)linnakangas(at)enterprisedb(dot)com>:
> > Ivan Voras wrote:
> >>
> >> I need to store data about sensor readings. There is a known (but
> >> configurable) number of sensors which can send update data at any time.
> >> The "current" state needs to be kept but also all historical records.
> >> I'm trying to decide between these two designs:
> >>
> >> 1) create a table for "current" data, one record for each sensor, update
> >> this table when a sensor reading arrives, create a trigger that would
> >> transfer old record data to a history table (of basically the same
> >> structure)
> >> 2) write only to the history table, use relatively complex queries or
> >> outside-the-database magic to determine what the "current" values of the
> >> sensors are.
> >
> > 3) write only to the history table, but have an INSERT trigger to update the
> > table with "current" data. This has the same performance characteristics as
> > 1, but let's you design your application like 2.
>
> Excellent idea!
>
> > I think I'd choose this approach (or 2), since it can handle out-of-order or
> > delayed arrival of sensor readings gracefully (assuming they are timestamped
> > at source).
>
> It seems like your approach is currently the winner.
>
> > If you go with 2, I'd recommend to still create a view to encapsulate the
> > complex query for the current values, to make the application development
> > simpler. And if it gets slow, you can easily swap the view with a table,
> > updated with triggers or periodically, without changing the application.
> >
> >> The volume of sensor data is potentially huge, on the order of 500,000
> >> updates per hour. Sensor data is few numeric(15,5) numbers.
> >
> > Whichever design you choose, you should also consider partitioning the data.
>
> I'll look into it, but we'll first see if we can get away with
> limiting the time the data needs to be available.
>
Mr. Voras,
One big benefit of partitioning is that you can prune old data with
minimal impact to the running system. Doing a large bulk delete would
be extremely I/O impacting without partion support. We use this for
a DB log system and it allows us to simply truncate a day table instead
of a delete -- much, much faster.
Regards,
Ken
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