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From Lahiru Gunathilake <glah...@gmail.com>
Subject Re: Profiling the current Airavata registry
Date Tue, 12 Aug 2014 12:54:34 GMT
Hi Sachith,

How did you test this ? What database did you use ?

I think 1000 experiments is a very low number. I think most important part
is when there are large number of experiments, how expensive is the search
and how expensive is a single experiment retrieval.

If we support to get defined number of experiments in the API (I think this
is the practical scenario, among 10k experiments get 100) we have to test
the performance of that too.

Regards
Lahiru


On Tue, Aug 12, 2014 at 4:59 PM, Sachith Withana <swsachith@gmail.com>
wrote:

> Hi all,
>
> I'm testing the registry with 10,1000,10,000 Experiments and I've tested
> the database performance executing the getAllExperiments method.
> I'll post the complete analysis.
>
> What are the other methods that I should test using?
>
> getExperiment(experiment_id)
> searchExperiment
>
> Any pointers?
>
>
>
> On Wed, Jul 23, 2014 at 6:07 PM, Marlon Pierce <marpierc@iu.edu> wrote:
>
>> Thanks, Sachith. Did you look at scaling also?  That is, will the
>> operations below still be the slowest if the DB is 10x, 100x, 1000x bigger?
>>
>> Marlon
>>
>>
>> On 7/23/14, 8:22 AM, Sachith Withana wrote:
>>
>>> Hi all,
>>>
>>> I'm profiling the current registry in few different aspects.
>>>
>>> I looked into the database operations and I've listed the operations that
>>> take the most amount of time.
>>>
>>> 1. Getting the Status of an Experiment (takes around 10% of the overall
>>> time spent)
>>>      Has to go through the hierarchy of the datamodel to get to the
>>> actual
>>> experiment status ( node,     tasks ...etc)
>>>
>>> 2. Dealing with the Application Inputs
>>>      Strangely it takes a long time for the queries regarding the
>>> ApplicationInputs to complete.
>>>      This is a part of the new Application Catalog
>>>
>>> 3. Getting all the Experiments ( using the * wild card)
>>>      This takes the maximum amount of time when queried at first. But
>>> thanks
>>> to the OpenJPA        caching, it flattens out as we keep querying.
>>>
>>> To reduce the first issue, I would suggest to have a different table for
>>> Experiment Summaries,
>>> where the status ( both the state and the state update time) would be the
>>> only varying entity, and use that to improve the query time for
>>> Experiment
>>> summaries.
>>>
>>> It would also help improve the performance for getting all the
>>> Experiments
>>> ( experiment summaries)
>>>
>>> WDYT?
>>>
>>> ToDos :  Look into memory consumption ( in terms of memory leakage
>>> ...etc)
>>>
>>>
>>> Any more suggestions?
>>>
>>
>>
>
>
> --
> Thanks,
> Sachith Withana
>
>


-- 
System Analyst Programmer
PTI Lab
Indiana University

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