Half of those indexes max out at about 1.3G, the other half will always stay 
very small < 5m total. We keep an index for “raw” data and another index for 
events and “trended” data. Possible design changes may make this number go up 
to 4-5G per index, but definitely no more than that. 

We’re indexing streaming patient vitals data from many different devices 
simultaneously, hence the high number of necessary indices. There are also 
constraints on patient identity confirmation, which requires that multiple 
indices are created to keep unconfirmed patient data separate from confirmed 
data. 

Also, we’re not using Solr, only raw lucene. The indices remain open until the 
streaming data has stopped and a user has removed the related session from the 
UI. 

Yes, it’s a necessary kind of scary… 

-Brian

On Nov 7, 2014, at 4:20 PM, Erick Erickson <erickerick...@gmail.com> wrote:

> bq: Our server runs many hundreds (soon to be thousands) of indexes
> simultaneously
> 
> This is actually kind of scary. How do you expect to fit "many
> thousands" of indexes into
> memory? Raising per-process virtual memory to unlimited still doesn't handle 
> the
> amount of RAM the Solr process needs. It holds things like caches,
> (top-level and
> per-segment), sort lists, all that. How many G of indexes are we
> talking here? Note
> that this is not a great guide to RAM requirements, but I'm just
> trying to get a handle
> on the scale you're at. You're not, for instance, going to handle
> terabyte-scale indexes
> on a single machine satisfactorily IMO.
> 
> If your usage pattern is a user signs on, works with their index for a
> while then
> signs off, you might get some joy out of the LotsOfCores option. That said, 
> this
> option has NOT been validated on cloud setups, where I expect it'll
> have problems.
> 
> FWIW,
> Erick
> 
> On Fri, Nov 7, 2014 at 2:24 PM, Uwe Schindler <u...@thetaphi.de> wrote:
>> Hi,
>> 
>>> That error can also be thrown when the number of open files exceeds the
>>> given limit. "OutOfMemory" should really have been named
>>> "OutOfResources".
>> 
>> This was changed already. Lucene no longer prints OOM (it removes the OOM 
>> from stack trace). It also adds useful information. So I think the version 
>> of Lucene that produced this exception is older (before 4.9): 
>> https://issues.apache.org/jira/browse/LUCENE-5673
>> 
>> Uwe
>> 
>> 
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