> I'm confused : don't range queries such as the ones we've been
> > discussing require using an orderedpartitionner ?
>
> Alright, so distribution depends on your choice of token.
>
Ah yes, I get it now : with a naive orderedpartitioner, the key is
associated with the node whose token is the clos
On Tue, 2010-04-13 at 16:05 +0200, Philippe wrote:
> I'm confused : don't range queries such as the ones we've been
> discussing require using an orderedpartitionner ?
Alright, so distribution depends on your choice of token.
--
Eric Evans
eev...@rackspace.com
I'm confused : don't range queries such as the ones we've been discussing
require using an orderedpartitionner ?
Le 13 avr. 2010 15:58, "Eric Evans" a écrit :
On Tue, 2010-04-13 at 08:57 +0200, Philippe wrote:
> Okay so if i switch columns and super columns i...
Sure.
> Assuming this is all co
On Tue, 2010-04-13 at 08:57 +0200, Philippe wrote:
> Okay so if i switch columns and super columns in my model i get what i
> want
> don't i?
>
> Super column = x
> Column = time frame
> Now i can get 2d range extracts from the grid and every cell will
> contain all time frame data. Is this correc
Okay so if i switch columns and super columns in my model i get what i want
don't i?
Super column = x
Column = time frame
Now i can get 2d range extracts from the grid and every cell will contain
all time frame data. Is this correct ?
I suppose that if that becomes too much data to retrieve, i can
