Re: Queueing Theory in Oracle

From: Ls Cheng <exriscer_at_gmail.com>
Date: Tue, 11 Mar 2014 21:52:46 +0100
Message-ID: <CAJ2-Qb_BzqWoM3bzPHcR4WFxfztWVy173QzC3p30Cb+-eL9MXg_at_mail.gmail.com>

But the transaction rate I got was from v$sysmetric, that does differentiate the 5 different application transactions

On Tue, Mar 11, 2014 at 9:51 PM, Ls Cheng <exriscer_at_gmail.com> wrote:

> Hi
>
> The TPC test runs 5 different type of transactions,
>
>
> 1. *New Order Transaction*
> 2. *Payment Tansaction*
> 3. *Order Status Transaction*
> 4. *Delivery Transaction*
> 5. *Stock Level Transaction*
>
>
> From the results Payment had an avg of 5ms service time, New Order 13ms,
> Delivery 15ms, Stock-Level 30ms and finally order status 261ms
>
>
>
>
>
> On Tue, Mar 11, 2014 at 9:36 PM, Jonathan Lewis <
> jonathan_at_jlcomp.demon.co.uk> wrote:
>
>>
>> I was thinking more of the way the data might introduce variability in
>> the time required to execute queries - for example in an order placing
>> system a "product pick" query that supplies 20 full names and product IDs
>> for the user to choose from will take longer than a query that supplies
>> only one option. Was there enough variation in the required service time
>> to allow a non-normal distribution ?
>>
>>
>> Regards
>> Jonathan Lewis
>> http://jonathanlewis.wordpress.com
>> _at_jloracle
>> ------------------------------
>> *From:* Ls Cheng [exriscer_at_gmail.com]
>> *Sent:* 11 March 2014 20:23
>> *To:* Jonathan Lewis
>> *Cc:* Oracle Mailinglist
>>
>> *Subject:* Re: Queueing Theory in Oracle
>>
>> Hi
>>
>> I thought the reasons of getting normal data distribution was probably
>> how the test is run. Since it's a constant 300/420 users running probably
>> 30 or 40 different SQL statements ( I dont know how many are there in a TPC
>> test), the server was only 18% loaded, the database metric I used were
>> gathered from v$sysmetrc (so I have metric rates in per second unit
>> gathered every minute), all mix together the distribution I got was normal,
>> I even took the sample data and used Cary's mdist.pl to see if the data
>> was exponentially distributed and all were rejected. After checking that
>> and think a bit then I think the normal data distribution is expected, if I
>> am running 16 TPC transactions per second and there are few in the lower
>> side a few in the higher side and most were in the middle then of course
>> it's a normal data distribution, why should I expect it to be exponentially
>> distributed?
>>
>> I used TPS as arrival rate and little's law to get the service time
>> (used host cpu as utilization)
>>
>> system utilization = (arrival rate * service time) / number of servers
>>
>> The service time was normal distributed as well
>>
>> So using the TPC test sample data, the formulas I could find (I have
>> downloaded probably 20 PPT from 7 or 8 universities statistics courses)
>> they just dont "glue" together in an Oracle Database and that is why I am
>> asking if anyone has successfully used queueing theory in Oracle so at
>> least I can get some points and see what I am dong wrong :-)
>>
>>
>> Thanks
>>
>>
>>
>>
>>
>>
>> On Tue, Mar 11, 2014 at 9:07 PM, Jonathan Lewis <
>> jonathan_at_jlcomp.demon.co.uk> wrote:
>>
>>>
>>>
>>> That's an interesting observation - but (viewed from the outside) I
>>> would be a little suspicious that the normal distribution was an artifact
>>> of the data generation mechanism and the test mechanism.
>>>
>>>
>>>
>>> Regards
>>> Jonathan Lewis
>>> http://jonathanlewis.wordpress.com
>>> _at_jloracle
>>> ------------------------------
>>> *From:* Ls Cheng [exriscer_at_gmail.com]
>>> *Sent:* 11 March 2014 20:01
>>> *To:* Karl Arao
>>> *Cc:* Jonathan Lewis; Oracle Mailinglist
>>>
>>> *Subject:* Re: Queueing Theory in Oracle
>>>
>>>
>>> I ran last week a couple of TPC load with 300 and 420 users then I
>>> used both transaction per second and logical reads per second metric and
>>> both showed normal data distribution and that is why I have doubts of how
>>> to use queueing theory in Oracle.
>>>
>>> From your paper was you able to predict the change from v1 to x2
>>> without run the actual test? Then run the test and validate the prediction?
>>>
>>>
>>
>

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Received on Tue Mar 11 2014 - 21:52:46 CET