We are doing the same exacting thing. We didn't test with so many documents. The most we tested till now 3 million documents with 3GB file size.
I would be interested in seeing how you maintained replicated indices that r in sync. The way we did was, run the indexer on each server independently. I the data changes, one server will know the change. That server updates lucene index and notifies other servers (using multicast).


Glad to know someone else is doing the similar thing and more happy to know that the solution works even for 100 millions documents. I was little worried if the index size goes higher and higher but it looks like we should not have to worry anymore :)

Thanks
Praveen
----- Original Message ----- From: "Bryan McCormick" <[EMAIL PROTECTED]>
To: "Chris D" <[EMAIL PROTECTED]>
Cc: <lucene-user@jakarta.apache.org>
Sent: Friday, February 18, 2005 3:45 PM
Subject: Re: Scalability of Lucene indexes



Hi chris,

I'm responsible for the webshots.com search index and we've had very
good results with lucene. It currently indexes over 100 Million
documents and performs 4 Million searches / day.

We initially tested running multiple small copies and using a
MultiSearcher and then merging results as compared to running a very
large single index. We actually found that the single large instance
performed better. To improve load handling we clustered multiple
identical copies together, then session bind a user to particular server
and cache the results, but each server is running a single index.

Bryan McCormick


On Fri, 2005-02-18 at 08:01, Chris D wrote:
Hi all,

I have a question about scaling lucene across a cluster, and good ways
of breaking up the work.

We have a very large index and searches sometimes take more time than
they're allowed. What we have been doing is during indexing we index
into 256 seperate indexes (depending on the md5sum) then distribute
the indexes to the search machines. So if a machine has 128 indexes it
would have to do 128 searches. I gave parallelMultiSearcher a try and
it was significantly slower than simply iterating through the indexes
one at a time.

Our new plan is to somehow have only one index per search machine and
a larger main index stored on the master.

What I'm interested to know is whether having one extremely large
index for the master then splitting the index into several smaller
indexes (if this is possible) would be better than having several
smaller indexes and merging them on the search machines into one
index.

I would also be interested to know how others have divided up search
work across a cluster.

Thanks,
Chris

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