Hi and thanks for your answer,

I do agree that it is a large volume of data, but as H2 is great in
every other aspect, I was just trying to make sure that I didn't miss
anything.
I tried playing with the cache_size, and it seems that if you specify
a cache_size (I tried 4G for instance), as the index creation process
doesn't have enough memory, it exists with an "out of memory" error
message.

On a sidenote, as the indexes will only be used to access the data
directly (where id2= , and not where id>...), I'l trying to create a
hash index to check if the performance is any better.

Steph.

On Jun 23, 4:14 pm, Chris Schanck <[email protected]> wrote:
> An embedded database storage engine with 100 million rows? That's ...
> bigger than what I would think is the sweet spot for an embedded db.
>
> Either way, I would look into changing the page size and the cache
> size; both can be specified in the connection url, I think, and the
> page size can't be changed after the db is created.
>
> Chris
>
> On Thu, Jun 23, 2011 at 2:53 AM, Stephane Geney
>
>
>
>
>
>
>
>
>
> <[email protected]> wrote:
> > Hi,
>
> > I've just started using H2 for my application as an embedded database
> > storage engine and it's really working great except for one part :
>
> > I have a table with 3 columns : id1 char(8), id2 char(8), value float.
> > I need indexes on the first two columns separately as I'll do a lot of
> > (select..where id1=...) and (select... where id2=...).
>
> > The table as more than 100 millions rows, and the index creation is
> > just too long. Creation of index on column id2 took more than 10
> > hours.
>
> > Is there a workaround ? should I try to create the indexes first and
> > then only import data in the table by splitting in in smaller chunks ?
>
> > Thank you for your answers.
>
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> --
> C. Schanck

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