So I got my server with SAS

It's an HP DL 380P G7
2 x6 (Hyperthreaded) 24 cores 72GB RAM and 5 Intel 530 SSDs (RAID 10)

These are the stats while JMeter is pushing 3,500 indexing operations/sec 
Average documents size is 2,500 bytes.

Indexing - Index:1.98msIndexing - Delete:0msSearch - Query:9.81msSearch - 
Fetch:0.62msGet - Total:0msGet - Exists:0msGet - Missing:0msRefresh:215.91ms
Flush:532.62ms



On Friday, 11 July 2014 19:29:17 UTC-4, Mark Walkom wrote:
>
> You could setup a hot and cold based allocation system, put your highly 
> accessed (hot) indexes on the SSDs and then the rest on the spinning disk.
>
> Regards,
> Mark Walkom
>
> Infrastructure Engineer
> Campaign Monitor
> email: [email protected] <javascript:>
> web: www.campaignmonitor.com
>  
>
> On 11 July 2014 23:35, John Smith <[email protected] <javascript:>> 
> wrote:
>
>> Right now I have 4 boxes...
>>
>> 2x 32 cores 200GB RAM with RAID10 SATA1 + the Fusion IO
>>
>> 2x 24 cores 96GB RAM with RAID10 SAS but regular mechanical drives.
>>
>> I only test them as pairs. So it's clusters of 2
>>
>> On the surface all searches seem to perform quite close to each other. 
>> Only when looking at the stats in HQ and Marvel the true story is told. For 
>> instance most warnings with Fusion IO are yellow at best. While with the 
>> SAS Raid 10 (Regular SATA Drives) they reach red.
>>
>> I'm hopping I can get some regular SSDs to put on the SAS boxes and see 
>> if it's better.
>>
>>
>>
>>
>> On Thursday, 10 July 2014 18:00:11 UTC-4, Jörg Prante wrote:
>>>
>>>  Did you consider SSD with RAID0 (Linux, ext4, noatime) and SAS2 (6g/s) 
>>> or SAS3 (12g/s) controller?
>>>
>>> I have for personal use at home LSI SAS 2008 of 4x128g SSD RAID0 with 
>>> sustained 800 MB/s write and 950 MB/s read, on a commodity dual AMD C32 
>>> socket server mainboard. I do not test with JMeter but on this single node 
>>> hardware alone I observe 15k bulk index operations per second, and 
>>> scan/scroll over 45m docs takes less than 70 min.
>>>
>>> I'm waiting until SAS3 is affordable for me. For the future I have on my 
>>> list: LSI SAS 3008 HBA and SAS3 SSDs. For personal home use, Fusion IO is 
>>> too heavy for my wallet. Even for commercial purpose I do not consider it 
>>> as a cost effective solution.
>>>
>>> Just a note: if you want spend your money to accelerate ES, buy RAM. You 
>>> will get more performance than from drives. Reason is the lower latency. 
>>> Low latency will speed up applications like ES more than the fastest I/O 
>>> drive is able to. That reminds me that I'm waiting since ages for DDR4 
>>> RAM...
>>>
>>> Jörg
>>>
>>>
>>> On Thu, Jul 10, 2014 at 10:13 PM, John Smith <[email protected]> 
>>> wrote:
>>>
>>>> Using 1.2.1
>>>>
>>>> I know each system and functionality is different but just curious when 
>>>> people say buy SSDs for ES, what types of SSDs are they buying?
>>>>
>>>> Fortunately for me I had some Fusion IO cards to test with, but just 
>>>> wondering if it's worth the price and if I should look into off the shelf 
>>>> SSDs like Samsung EVOs using SAS instead of pure SATA.
>>>>
>>>> So far from my testing it seems that all search operation regardless of 
>>>> the drive type seem to return in the same amount of time. So I suppose 
>>>> caching is playing a huge part here.
>>>>
>>>>  Though when looking at the HQ indexing stats like query time, fetch 
>>>> time, refresh time etc... The Fusion IO fares a bit better then regular 
>>>> SSDs using SATA.
>>>>
>>>> For instance refresh time for Fusion IO is 250ms while for regular SSDs 
>>>> (SATA NOT SAS, will test SAS when I get a chance) it's just above 1 second.
>>>> Even with fusion IO I do see some warnings on the index stats, but 
>>>> slightly better then regular SSDs
>>>>
>>>> Some strategies I picked for my indexes...
>>>> - New index per day, plus routing by "user"
>>>> - New index per day for monster users.
>>>>
>>>> Using JMeter to test...
>>>> - Achieved 3,500 index operations per second (Not bulk) avg document 
>>>> size 2,500 bytes (Fusion IO seemed to perform a bit better)
>>>> - Created a total of 25 indexes totaling over 100,000,000 documents 
>>>> anywhere between 3,000,000 to 5,000,000 documents per index.
>>>> - Scroll query to retrieve 15,000,000 documents out of the 100,000,000 
>>>> (all indexes) took 25 minutes regardless of drive type.
>>>>
>>>> P.s: I want to index 2,000,000,000 documents per year so about 
>>>> 4,000,000 per day. So you can see why Fusion IO could be expensive :)
>>>>
>>>> Thanks
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
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