High sustainable bulk indexing is very stable here.

I have 3x HP DL165 G7 32 core machines and can index for hours at same
speed with this settings

https://gist.github.com/jprante/10666960

Jörg


On Wed, Apr 23, 2014 at 5:52 PM, John Smith <[email protected]> wrote:

> Ok so I decided to skip in-memory for now just to test bassic
> functionality.
>
> I'm running elastic search with defaults as
>
> ./elasticsearch -Xms32g -Xmx32g
>
> I also got bigdesk installed.
>
> Either I'm not getting something... But why as I write more documents to
> the index the
>
> Indexing requests per second (Δ)
>
> goes down and the
>
> Indexing time per second (Δ)
>
> Is going up
>
> So basically it's getting slower and slower.
>
> Is their any sensible tuning parameters. I would expect that the insertion
> should be stable and not getting slower.
>
> It's a 32 core machine and enough ram, standard drives though. There has
> to be a way to setup buffers and queues to alliviate the issue of disks
> "being slow"
>
>
> On Wednesday, April 23, 2014 10:42:37 AM UTC-4, John Smith wrote:
>>
>> On a 32 core machine? Plus I think 1.7_51 uses G1
>>
>> I have tested another "indexing" api up to 190GB or so with 30,000,000
>> objects and my latency was 3ms overall including network and app logic.
>>
>> And I haven't tested that many records with elastic search yet ;)
>>
>>
>> On Wednesday, 23 April 2014 10:20:20 UTC-4, Jörg Prante wrote:
>>>
>>> The ES "memory" or "ram" store (Lucene RAMDirectory) puts enormous
>>> pressure on JVM garbage collection.
>>>
>>> You can not expect that standard JVM with CMS GC can give the best
>>> performance.
>>>
>>> More info in this great article by Mike McCandless
>>>
>>> http://blog.mikemccandless.com/2012/07/lucene-index-in-
>>> ram-with-azuls-zing-jvm.html
>>>
>>> Maybe Java 8 with G1 GC is giving slightly better numbers. But do not
>>> expect too much.
>>>
>>> Jörg
>>>
>>>
>>>
>>>
>>>
>>> On Wed, Apr 23, 2014 at 3:19 PM, John Smith <[email protected]> wrote:
>>>
>>>> 1.7_51 but i dont see how their could be a limitation.
>>>>
>>>> I used java up to 200GB easily and with no issues either...
>>>>
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