Hi Ganesh, I'd suggest, if you have a particular dimension/field on which you could shard your data such that the query/data breakup gets predictable, that would be a good way to scale out e.g. if you have users which are equally active/searched then you may want to split their data on a simple mod of some numeric (auto increment) userid. This works well under normal cases unless your partitioning is not predictable.
-- Anshum Gupta http://ai-cafe.blogspot.com On Fri, Jan 21, 2011 at 10:52 AM, Ganesh <emailg...@yahoo.co.in> wrote: > Hello all, > > Could you any one guide me what all the various ways we could scale out? > > 1. Index: Add data to the nodes in round-robin. > Search: Query all the nodes and cluster the results using carrot2. > > 2.Horizontal partitioning and No shared architecture, > Index: Split the data based on userid and index few set of users data > in each node. > Search: Have a mapper kind of application which could tell which userid > is mapped to node, redirect the search traffic to corresponding node. > > Which one is best? Did you guys tried any of these approach. Please share > your thoughts. > > Regards > Ganesh > Send free SMS to your Friends on Mobile from your Yahoo! Messenger. > Download Now! http://messenger.yahoo.com/download.php > > --------------------------------------------------------------------- > To unsubscribe, e-mail: java-user-unsubscr...@lucene.apache.org > For additional commands, e-mail: java-user-h...@lucene.apache.org > >
