Hi Shawn,
I expect that indexing is a little bit slower with replication but in my
case is 3 times worst. I don't explain this.
The monitored consumption of resources is:
All the test have point out an I/O utilization of 100MB/s during
loading data on disk cache, disk cache utilization of 20GB and core
utilization of 100% (all 8 cores)
so it seems that the bottleneck are cores and not RAM. I don't expect a
performance improvement increasing RAM. Am I wrong?
Thanks,
Luca
On Fri, Jan 8, 2016 at 4:40 PM, Shawn Heisey <apa...@elyograg.org> wrote:
> On 1/8/2016 7:55 AM, Luca Quarello wrote:
> > I used solr5.3.1 and I sincerely expected response times with replica
> > configuration near to response times without replica configuration.
> >
> > Do you agree with me?
> >
> > I read here
> >
> http://lucene.472066.n3.nabble.com/Solr-Cloud-Query-Scaling-td4110516.html
> > that "Queries do not need to be routed to leaders; they can be handled by
> > any replica in a shard. Leaders are only needed for handling update
> > requests. "
> >
> > I haven't found this behaviour. In my case CONF2 e CONF3 have all
> replicas
> > on VM2 but analyzing core utilization during a request is 100% on both
> > machines. Why?
>
> Indexing is a little bit slower with replication -- the update must
> happen on all replicas.
>
> If your index is sharded (which I believe you did indicate in your
> initial message), you may find that all replicas get used even for
> queries. It is entirely possible that some of the shard subqueries will
> be processed on one replica and some of them will be processed on other
> replicas. I do not know if this commonly happens, but I would not be
> surprised if it does. If the machines are sized appropriately for the
> index, this separation should speed up queries, because you have the
> resources of multiple machines handling one query.
>
> That phrase "sized appropriately" is very important. Your initial
> message indicated that you have a 90GB index, and that you are running
> in virtual machines. Typically VMs have fairly small memory sizes. It
> is very possible that you simply don't have enough memory in the VM for
> good performance with an index that large. With 90GB of index data on
> one machine, I would hope for at least 64GB of RAM, and I would prefer
> to have 128GB. If there is more than 90GB of data on one machine, then
> even more memory would be needed.
>
> Thanks,
> Shawn
>
>
