I've had a reporting database with just about a billion rows. Each row
was horribly large because the legacy schema had problems. We partitioned
it out by month and it ran about 30 million rows a month. With a reasonably
large box you can get that kind of data into memory and indexes are
almost unnecessary. So long as you have constraint exclusion and a good
partition scheme you should be fine. Throw in a well designed schema and
you'll be cooking well into the tens of billions of rows.
We ran self joins of that table reasonably consistently by the way:
SELECT lhs.id, rhs.id
FROM bigtable lhs, bigtable rhs
WHERE lhs.id > rhs.id
AND '' > lhs.timestamp AND lhs.timestamp >= ''
AND '' > rhs.timestamp AND rhs.timestamp >= ''
AND lhs.timestamp = rhs.timestamp
AND lhs.foo = rhs.foo
AND lhs.bar = rhs.bar
This really liked the timestamp index and we had to be careful to only do it
for a few days at a time. It took a few minutes each go but it was
definitely doable.
Once you get this large you do have to be careful with a few things though:
*It's somewhat easy to write super long queries or updates. This can lots
of dead rows in your tables. Limit your longest running queries to a day or
so. Note that queries are unlikely to take that long but updates with
massive date ranges could. SELECT COUNT(*) FROM bigtable too about 30
minutes when the server wasn't under heavy load.
*You sometimes get bad plans because:
**You don't or can't get enough statistics about a column.
**PostgreSQL doesn't capture statistics about two columns together.
PostgreSQL has no way of knowing that columnA = 'foo' implies columnB =
'bar' about 30% of the time.
Nik
On Thu, May 27, 2010 at 5:58 AM, Massa, Harald Armin <c...@ghum.de> wrote:
> Dann,
>
> There really are domains that big, so that there is no more normalization
>> or other processes to mitigate the problem.
>>
>> Examples:
>> Microsoft's registered customers database (all MS products bought by any
>> customer, including operating systems)
>> Tolls taken on the New Jersey road system for FY 2009
>> DNA data from the Human Genome Project
>>
>> .....
>
> please also think of ouer most risk exposed users, the ones using Poker /
> Roulette simulation and analyzing software with an PostgrSQL database below.
> There are so many rounds of Poker to play .... :)
>
> Harald
>
>
> --
> GHUM Harald Massa
> persuadere et programmare
> Harald Armin Massa
> Spielberger Straße 49
> 70435 Stuttgart
> 0173/9409607
> no fx, no carrier pigeon
> -
> Using PostgreSQL is mostly about sleeping well at night.
>
