> > In this case, I'd say that if you have a reliable, scalable queueing system > for > getting indexing events distributed to all of your servers, then indexing > on > all replicas simultaneously can be the best way to have maximally realtime > search, either using the very new feature of "near realtime search" in > Lucene 2.9, by using something home-brewed which indexes in memory > and on disk simultaneously, or using Zoie ( http://zoie.googlecode.com ), > an open-source realtime search library built on top of Lucene which we at > LinkedIn built and have been using in production for serving tens of > millions of queries a day in real time (meaning milliseconds, even under > fairly high indexing load) for the past year.
Zoie looks very close to what I'm after, however my whole app is written in Python and uses PyLucene, so there is a non-trivial amount of work to make things work with Zoie. I'm currently experiencing a bottleneck when optimising my index. How is this handled / solved with Zoie? Cheers, Chris
