On Mon, Jun 27, 2016 at 8:03 PM, Seshika Fernando <[email protected]> wrote:

> Iranga,
> The optimization applies to siddhi queries that were written for IS
> analytics. Other product analytics would have different queries so this is
> not applicable there.
> This is not a siddhi level change, rather an optimization of the
> previously written queries.
>
Yes, above per-second and per-minute design is applied to some other
analytics product as well but it is not generic and too specific for the
usecase and query as mentioned by Seshi..

Thanks,
Mohan


> Seshi
> On 27 Jun 2016 16:48, "Iranga Muthuthanthri" <[email protected]> wrote:
>
>>
>>
>> On Mon, Jun 27, 2016 at 4:35 PM, Mohanadarshan Vivekanandalingam <
>> [email protected]> wrote:
>>
>>>
>>>
>>> On Mon, Jun 27, 2016 at 4:30 PM, Seshika Fernando <[email protected]>
>>> wrote:
>>>
>>>> Hey saith,
>>>>
>>>> This is great. So when you removed the duplicate windows, there were no
>>>> OOM issues?
>>>>
>>> Yes, we have introduced per-second windows and eventually per-minute
>>> event count get reduced. Then, there will not be an OOM..
>>>
>>
>> is this specific for IS-Analytics or common to all other 'product
>> analytics'.
>>
>>
>>> Latest number is also seems good.. SajithR, can share those numbers..
>>>
>>> Thanks,
>>> Mohan
>>>
>>>
>>>> Seshi
>>>> On 24 Jun 2016 14:28, "Sajith Ravindra" <[email protected]> wrote:
>>>>
>>>>> Hi Malith,
>>>>>
>>>>> Thanks for the explanation.
>>>>>>
>>>>>> I would expect some variation in the throughput. The aim should be
>>>>>> minimize the variation in the throughput (while maintaining the 
>>>>>> throughput
>>>>>> at its highest level).
>>>>>>
>>>>>  Agreed. Actually, our expectation is to minimize the fluctuation and
>>>>> to increase the throughput.
>>>>>
>>>>>>
>>>>>> It is possible to measure the latency as well?
>>>>>>
>>>>> In IS-Analytics we don't generate any output events or alerts
>>>>> currently. Therefore, we don't calculate the latency. What we do is
>>>>> summarize events using siddhi queries and persist them in a DB and further
>>>>> summarize persisted data using Spark and then displayed through
>>>>> dashbaords.
>>>>>
>>>>>
>>>>> Thanks
>>>>> *,Sajith Ravindra*
>>>>> Senior Software Engineer
>>>>> WSO2 Inc.; http://wso2.com
>>>>> lean.enterprise.middleware
>>>>>
>>>>> mobile: +94 77 2273550
>>>>> blog: http://sajithr.blogspot.com/
>>>>> <http://lk.linkedin.com/pub/shani-ranasinghe/34/111/ab>
>>>>>
>>>>> On Fri, Jun 24, 2016 at 1:57 PM, Malith Jayasinghe <[email protected]>
>>>>> wrote:
>>>>>
>>>>>> Hi Sajith,
>>>>>>
>>>>>> Thanks for the explanation.
>>>>>>
>>>>>> I would expect some variation in the throughput. The aim should be
>>>>>> minimize the variation in the throughput (while maintaining the 
>>>>>> throughput
>>>>>> at its highest level).
>>>>>>
>>>>>> It is possible to measure the latency as well?
>>>>>>
>>>>>> regards
>>>>>>
>>>>>> Malith
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Thu, Jun 23, 2016 at 11:13 PM, Sajith Ravindra <[email protected]>
>>>>>> wrote:
>>>>>>
>>>>>>> Hi Malith,
>>>>>>>
>>>>>>> The deployment is just a standalone DAS server, and we are planning
>>>>>>> to do a test for HA deployment in recent future.
>>>>>>>
>>>>>>> The workload is generated by a .csv data file which has 100K sample
>>>>>>> events, 10M events are generated by iterating through the same data set 
>>>>>>> 100
>>>>>>> times. But we keep increasing the timestamp. A simple thrift client is 
>>>>>>> used
>>>>>>> to publish data.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Thanks
>>>>>>> *,Sajith Ravindra*
>>>>>>> Senior Software Engineer
>>>>>>> WSO2 Inc.; http://wso2.com
>>>>>>> lean.enterprise.middleware
>>>>>>>
>>>>>>> mobile: +94 77 2273550
>>>>>>> blog: http://sajithr.blogspot.com/
>>>>>>> <http://lk.linkedin.com/pub/shani-ranasinghe/34/111/ab>
>>>>>>>
>>>>>>> On Fri, Jun 24, 2016 at 10:34 AM, Malith Jayasinghe <
>>>>>>> [email protected]> wrote:
>>>>>>>
>>>>>>>> Hi Sajith,
>>>>>>>>
>>>>>>>> Could you please provide some details about how you are actually
>>>>>>>> doing these performance tests. For example, what is deployment model?  
>>>>>>>> How
>>>>>>>> are you generating these workloads/events?
>>>>>>>>
>>>>>>>> Thanks
>>>>>>>>
>>>>>>>> Malith
>>>>>>>>
>>>>>>>> On Thu, Jun 23, 2016 at 11:28 AM, Sajith Ravindra <[email protected]
>>>>>>>> > wrote:
>>>>>>>>
>>>>>>>>> Hi all,
>>>>>>>>>
>>>>>>>>> This is to give an update on the performance study we conducted on
>>>>>>>>> is-analytics server on last. The idea of this test round was to 
>>>>>>>>> evaluate
>>>>>>>>> the performance of Siddhi queries used for is-analytics, therefore we
>>>>>>>>> disabled event stream persistence and spark for this test.
>>>>>>>>>
>>>>>>>>> This test was conducted on a standalone DAS server with Xms2g and
>>>>>>>>> Xmx4g.
>>>>>>>>>
>>>>>>>>> On the initial round when input TPS reaches ~20K, the server went
>>>>>>>>> OOM after consuming around 1M events. The reason for this was the 
>>>>>>>>> events
>>>>>>>>> accumulated inside 7 1min time batch windows used inside.  To 
>>>>>>>>> overcome this
>>>>>>>>> we implemented an extension to siddhi which allows us to avoid 
>>>>>>>>> duplicating
>>>>>>>>> the window.
>>>>>>>>>
>>>>>>>>> After removing duplicate windows the server was able to consume
>>>>>>>>> events at a rate of ~22K, but there were fluctuations (see the graph
>>>>>>>>> bellow) of the throughput. With analysis, we found that intense GC 
>>>>>>>>> causes
>>>>>>>>> this. We suspect that this intense GC  is caused when expiring a large
>>>>>>>>> number of events accumulated inside 1-minute window. To  overcome 
>>>>>>>>> this we
>>>>>>>>> are planning to batch events in 1-second windows and then accumulate
>>>>>>>>> 1second batches in 1 min window in order to stop accumulating a large
>>>>>>>>> number of events.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> As the next steps, we are planning to test the performance with
>>>>>>>>> event stream persistence and then move on to check the performance in 
>>>>>>>>> DAS
>>>>>>>>> minimum HA mode.
>>>>>>>>>
>>>>>>>>> We will keep updating this thread with our findings.
>>>>>>>>>
>>>>>>>>> Please share your thought, suggestions on this.
>>>>>>>>>
>>>>>>>>> Thanks
>>>>>>>>> *,Sajith Ravindra*
>>>>>>>>> Senior Software Engineer
>>>>>>>>> WSO2 Inc.; http://wso2.com
>>>>>>>>> lean.enterprise.middleware
>>>>>>>>>
>>>>>>>>> mobile: +94 77 2273550
>>>>>>>>> blog: http://sajithr.blogspot.com/
>>>>>>>>> <http://lk.linkedin.com/pub/shani-ranasinghe/34/111/ab>
>>>>>>>>>
>>>>>>>>> _______________________________________________
>>>>>>>>> Architecture mailing list
>>>>>>>>> [email protected]
>>>>>>>>> https://mail.wso2.org/cgi-bin/mailman/listinfo/architecture
>>>>>>>>>
>>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> --
>>>>>>>> Malith Jayasinghe
>>>>>>>>
>>>>>>>>
>>>>>>>> WSO2, Inc. (http://wso2.com)
>>>>>>>> Email   : [email protected]
>>>>>>>> Mobile : 0770704040
>>>>>>>> Lean . Enterprise . Middleware
>>>>>>>>
>>>>>>>> _______________________________________________
>>>>>>>> Architecture mailing list
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>>>>>>>> https://mail.wso2.org/cgi-bin/mailman/listinfo/architecture
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>> _______________________________________________
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>>>>>>>
>>>>>>>
>>>>>>
>>>>>>
>>>>>> --
>>>>>> Malith Jayasinghe
>>>>>>
>>>>>>
>>>>>> WSO2, Inc. (http://wso2.com)
>>>>>> Email   : [email protected]
>>>>>> Mobile : 0770704040
>>>>>> Lean . Enterprise . Middleware
>>>>>>
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>>>>>>
>>>>>>
>>>>>
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>>>>>
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>>>
>>>
>>> --
>>> *V. Mohanadarshan*
>>> *Associate Tech Lead,*
>>> *Data Technologies Team,*
>>> *WSO2, Inc. http://wso2.com <http://wso2.com> *
>>> *lean.enterprise.middleware.*
>>>
>>> email: [email protected]
>>> phone:(+94) 771117673
>>>
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>>
>>
>> --
>> Thanks & Regards
>>
>> Iranga Muthuthanthri
>> (M) -0777-255773
>> Team Product Management
>>
>>
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>


-- 
*V. Mohanadarshan*
*Associate Tech Lead,*
*Data Technologies Team,*
*WSO2, Inc. http://wso2.com <http://wso2.com> *
*lean.enterprise.middleware.*

email: [email protected]
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