Hi Jorg,
  We're storing each application in it's own Index so we can manage it 
independently of others.  There's not set load or usage on our 
applications.  Some will be very small, a few hundred documents.  Others 
will be quite large, in the billions.  We have no way of knowing what the 
usage profile is.  Rather, we're initially thinking that expansion will 
occur using a combination of additional indexes and aliases referencing 
those indexes.  This allows us to automate the management of the aliases 
and indexes, and in turn allows us to scale them to the needs of the 
application without over allocating unused capacity.   For instance, with 
write heavy applications we can allocate more shards (via alias), for read 
heavy application we can allocate more replicas.



We're not running our cluster on a single node.  Our cluster is small to 
begin with, it's 6 nodes in our current POC.  Ultimately I expect us to 
grow each cluster we stand up to 20 or so nodes.  We'll expand as necessary 
to support the number of shards and replicas and keep our performance up. 
 I'm not particularly worried about our ability to scale horizontally with 
our hardware.  

Rather, I'm concerned with how far can we scale on our number of indexes, 
and how does that relate to the number of machines?  When we keep adding 
hardware, does this increase the upper bounds of the number of indexes we 
can have?  Not the physical shards and replicas, but the routing 
information for the master of the shards and location of the replicas. 
 I've done distributed data storage for many years, and none of the 
documentation on ES makes it clear if this becomes an issue operationally. 
 I'm leery to just assume it will "just work".  When implementing something 
like this, you either have to do a distributed tree for your meta data to 
get the partitioning you need to scale infinitely, or every node must store 
every shard's master information.   How does it work in ES?


Thanks,
Todd



On Friday, September 26, 2014 4:29:53 PM UTC-6, Jörg Prante wrote:
>
> Why do you want to create huge number of indexes on just a single node? 
>
> There are smarter methods to scale. Use over-allocation of shards. This is 
> explained by kimchy in this thread
>
>
> http://elasticsearch-users.115913.n3.nabble.com/Over-allocation-of-shards-td3673978.html
>  
> <http://www.google.com/url?q=http%3A%2F%2Felasticsearch-users.115913.n3.nabble.com%2FOver-allocation-of-shards-td3673978.html&sa=D&sntz=1&usg=AFQjCNEk7KTtpuEot3JtBBmMRMpH25vLDA>
>
> TL;DR you can create many thousands of aliases on a single (or few) 
> indices with just a few shards. There is no limit defined by ES, when your 
> configuration / hardware capacity is exceeded, you will see the node 
> getting sluggish.
>
> Jörg
>
> On Fri, Sep 26, 2014 at 11:23 PM, Todd Nine <[email protected] 
> <javascript:>> wrote:
>
>> Hey guys.  We’re building a Multi tenant application, where users create 
>> applications within our single server.    For our current ES scheme, we're 
>> building an index per application.  Are there any stress tests or 
>> documentation on the upper bounds of the number of indexes a cluster can 
>> handle?  From my current understanding of meta data and routing, ever node 
>> caches the meta data of all the indexes and shards for routing.  At some 
>> point, this will obviously overwhelm the node.  Is my current understanding 
>> correct, or is this information partitioned across the cluster as well?
>>
>>
>> Thanks,
>>
>> Todd
>>
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