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From Erick Erickson <>
Subject Re: Scaling to large Number of Collections
Date Sun, 31 Aug 2014 16:04:20 GMT
What is your access pattern? By that I mean do all the cores need to be
searched at the same time or is it reasonable for them to be loaded on
demand? This latter would impose the penalty of the first time a collection
was accessed there would be a delay while the core loaded. I suppose I'm
asking "how many customers are using the system simultaneously?". One way
around that is to fire a dummy query behind the scenes when a user logs on
but before she actually executes a search.

Why I'm asking:

See this page: It was intended for
the multi-tenancy case in which you could count on a subset of users being
logged on at once.

WARNING! LotsOfCores is NOT supported in SolrCloud at this point! There has
been some talk of extending support for SolrCloud, but no action as it's
one of those cases that has lots of implications particularly around
 ZooKeeper knowing the state of all the cores, cores going into recovery in
a cascading fashionetc. It's not at all clear that it _can_ be extended to
SolrCloud for that matter without doing great violence to the code.

With the LotsOfCores approach (and assuming somebody volunteers to code it
up), the number of cores hosted on a particular node can be many thousands.
The limits will come from how many of them have to be up and running
simultaneously. The limits would come from two places:
1> The time it takes to recursively walk your SOLR_HOME directory and
discover the cores (I see about 1,000 cores/second discovered on my laptop,
admittedly an SSD, and there has been no optimization done to this process).
2> having to keep a table of all the cores and their information (home
directory and the like) in memory, but practically I don't think this is a
problem. I haven't actually measured, but the size of each entry is almost
certainly less than 1K and probably closer to 0.5K.

But it really does bring us back to the question of whether all these cores
are necessary or not. The "usual" technique for handling this with the
LotsOfCores option is to combine the records into a number of smaller
cores. Without knowing your requirements in detail, something like a
customers core and a products core where, say, each product has a field
with tokens indicating what users had access or vice versa, and (possibly)
using pseudo joins. In one view, this is an ACL problem which has several
solutions, each with drawbacks of course.

Or just de-normalizing your data entirely and just have a core per customer
with _all_ the products indexed in to it.

Like I said, I don't know enough details to have a clue whether the data
would explode unacceptably.

Anyway, enough on a Sunday morning!


On Sun, Aug 31, 2014 at 8:18 AM, Shawn Heisey <> wrote:

> On 8/31/2014 8:58 AM, Joseph Obernberger wrote:
> > Could you add another field(s) to your application and use that instead
> of
> > creating collections/cores?  When you execute a search, instead of
> picking
> > a core, just search a single large core but add in a field which contains
> > some core ID.
> This is a nice idea.  Have one big collection in your cloud and use an
> additional field in your queries to filter down to a specific user's data.
> It'd be really nice to write a custom search component that ensures
> there is a filter query for that specific field, and if it's not
> present, change the search results to include a document that informs
> the caller that they're not doing it right.
> (That URL probably won't work correctly on mobile browsers)
> Thanks,
> Shawn

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