Can anyone speculate as to how any of these distributed caches actually
perform though? I'm wondering how much overhead the network communication
between cluster participants introduces and whether a many-to-one
(slide-to-filesystem) design using an NFS mounted filesystem wouldn't be
just as fast as a many-to-many design where each slide has its own
filesystem.

Warwick


> -----Original Message-----
> From: Richard Emberson [mailto:[EMAIL PROTECTED] 
> Sent: Wednesday, November 24, 2004 11:40 AM
> To: Slide Users Mailing List
> Subject: Re: slide clustering support question
> 
> 
> Build your own or use whats out there. For Slide to have 
> top-grade clustering either Slide must invest the time and 
> effort to develop such a system or just use existing 
> libraries that provide such capabilities. I would think that 
> the correct approach is to build on whats out there, 
> specifically, JGroups which has a distinguished academic 
> pedigree, rich computer science heritage and significant 
> usage. JGroups has distributed hashtables, distributed lock 
> management, and, very appealing, group membership can be 
> determined dynamically - one does not have to know every 
> member of the group when the whole cluster starts.
> 
> Slide might have to be refactored some so that the clustering 
> implementation is an addon and the main Slide code can 
> compile and run without the JGroups jar file. But for those 
> who wish to use Slide where clustering is a must, either for 
> performance or failover, then the clustering implementation 
> with its dependence on JGroups would have to be compiled and loaded.
> 
> Example usages:
> JBoss uses JGroups.
> CJDBC uses JGroups.
> 
> Richard
> 
> 
> Warwick Burrows wrote:
> > We've implemented that configuration: a jdbc nodestore with tx 
> > filesystem store much like you've outlined with a HTTP load 
> balancer 
> > between our DAV clients and Slide servers. It is untested in this 
> > target (load balanced) configuration but we have tested in 
> a simpler 
> > configuration that shares the jdbc store and the content 
> (using NFS) 
> > between two Slide servers.
> > 
> > Unfortunately the clustering implementation is untested in terms of 
> > how locking will work. Ie. when a lock is taken by one client a 
> > notification is sent to the other servers in the cluster to 
> let them 
> > know that this object has changed. But its not certain what will 
> > happen if two requests for the lock come in at exactly the 
> same time 
> > as they would both take the lock and send a notification off to the 
> > other clustered servers. I believe that there's no code to resolve 
> > this issue.
> > 
> > So for our deployment we've gone with disabling the cache for the 
> > nodestore altogether so that updates for locks and other 
> metadata are 
> > written directly to the db. The content store also has its cache 
> > disabled right now as it seems that caching for both node 
> and content 
> > stores is controlled from the encompassing <store> definition.
> > 
> > So far we think it will meet our particular performance 
> requirements 
> > even with the caches disabled. A fully distributed cache (and so 
> > lock-safe) cache would be great but the question is would 
> it be more 
> > performant than just writing directly to the db?... 
> particularly when 
> > you consider that any negotiation for the lock that would need to 
> > occur between cluster caches would be over the network and 
> subject to 
> > network latency. Anyone have any ideas as to how distributed caches 
> > actually perform in the real world?
> > 
> > Warwick
> > 
> > 
> > 
> >>-----Original Message-----
> >>From: Alessandro Apostoli [mailto:[EMAIL PROTECTED]
> >>Sent: Wednesday, November 24, 2004 5:28 AM
> >>To: Slide Users Mailing List
> >>Subject: slide clustering support question
> >>
> >>
> >>I have a couple questions about the clustering features of
> >>slide, suppose a scenario where you have a distributed 
> >>replicated filesystem such as coda and a replicated db 
> >>running on each node. Each node has the same data both on 
> >>filesystem and db, the nodes are part of a big wan with links 
> >>speed around 2 Mbit. The idea would be to use slide tx store 
> >>for resources and revisions whilst using a jdbc store for 
> >>properties, users, groups, roles and security
> >>1) In such a scenario how would the locks on the filesystem 
> >>behave, I guess that the transaction support in the 
> >>commons.transaction.file package would be broken for there 
> >>would be two or more instances of FileResourceManager 
> >>accessing the same directory or am I missing something ?
> >>2) For ideal clustering support would I be confined to the 
> JDBC store?
> >>3) If the Tx Store still works in this configuration how does slide 
> >>solve the
> >>above distributed transaction problem?
> >>
> >>Alessandro
> >>
> >>
> >>
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> > 
> > 
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