[Haskell-cafe] Storing big datasets

David Turner dct25-561bs at mythic-beasts.com
Sat May 7 14:42:23 UTC 2016


On 7 May 2016 13:45, "Joachim Durchholz" <jo at durchholz.org> wrote:
>
> Am 07.05.2016 um 12:48 schrieb David Turner:
>>
>> Btrees are good for storing data on disk. And something like postgres is
an
>> extremely efficient implementation of a btree supporting atomic updates
and
>> the like. I'd use that!
>
>
> The original question was about standard hardware (i.e. still including
rotating rust) and ~50 updates/second.
> I'd assume that that's doable with an ACID-compliant DB on standard
hardware, though it does not leave room for inefficiencies so you need to
know what you're doing in SQL.
>
> On a later update, he corrected the specs to 1,000-2,000 updates/second,
and I believe that it's impossible to do that on a standard single-HDD. I
don't know whether Mikhail considers SSDs standard configuration.
>
> Now transaction rates aren't the same as write rates. If he can batch
multiple writes in one transaction, Postgresql or any other RDBMS might
actually work.

Thousands of transactions per second is getting into
needs-clever-optimisation territory if it can't be done in RAM, but it's
not that tricky. Postgres will batch transactions for you: see for instance
http://pgeoghegan.blogspot.co.uk/2012/06/towards-14000-write-transactions-on-my.html?m=1

Cheers,

>
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