thanks Hoss,
once again.
-umar
On Sat, Jun 14, 2008 at 4:06 AM, Chris Hostetter <[EMAIL PROTECTED]>
wrote:
>
> : I am using a servlet filter to alter the query parms sent to the solr ,
> : now I have a problem where I want to take some extra action (like drop
> some
> : query terms or filters
Hi.
We as well use md5 as the uid.
I guess by saying each 1/16th is because the md5 is hex, right? (0-f).
Thinking about md5 sharding.
1 shard: 0-f
2 shards: 0-7:8-f
3 shards: problem!
4 shards: 0-3
This technique would require that you double the amount of shards each time
you split right ?
Hmmm distributed BDB brrr :)
On Fri, Jun 13, 2008 at 3:21 AM, Otis Gospodnetic <
[EMAIL PROTECTED]> wrote:
> Or, if you want to go with something older/more stable, go with BDB. :)
>
>
> Otis --
> Sematext -- http://sematext.com/ -- Lucene - Solr - Nutch
>
>
> - Original Message
> > From
Hi users,
I´m going to create a big index of 300gb in a SAN where i have 4TB. I read
many entries in the mail list talking about using multiple index with
multicore. I would like to know what kind of benefit can i have
using multiple index instead of one big index if i dont have problems with
the
Roberto,
Here is some food for thought...
Multiple smaller indices you can split them across several servers, but you
can't do that with a monolithic index.
With multiple smaller indices you can choose to search only a subset of them,
should that make sense for your app.
How much does it cost
Hi Otis,
Thanks for your fast answer.
I understand perfectly your points. I will explain my limitations ...
--Multiple smaller indices you can split them across several servers, but
you can't do that with a monolithic index.
The index will be allocated in a SAN that is not under my election. I c
Hi Roberto,
SAN is a fine choice, if that's what you were worried about. There is no way
to tell exactly how fast your searches will be, as that depends on a lot of
factors -- benchmarking with your own data and hardware and queries is the best
way to go.
As for the cost of multiple smaller m