Raj, Imesh and i had a discussion on an improvement to window size we accumulate the stats. Currently we get 1 min window and run the execution plan 1 min by 1 min. We can improve the sample by increasing the window to 10 mins and running it 1 min by 1 min.
I will incorporate this with the curve fitting change. On Fri, Nov 7, 2014 at 12:47 AM, Akila Ravihansa Perera <raviha...@wso2.com> wrote: > Hi, > > On Nov 6, 2014 11:37 AM, "Imesh Gunaratne" <im...@apache.org> wrote: > > > > Thanks for your response Nirmal, please see my thoughts below: > > > > On Thu, Nov 6, 2014 at 7:38 PM, Nirmal Fernando <nirmal070...@gmail.com > > wrote: > >> > >> AFAIU if it is statistics, it's all about random data, samples and > normalization. You don't use all values to do estimations. And this is an > estimation for gradient per say! > > > > > > True, however the random data needs to be accurate as much as possible. > >>> > >>> > >> Well, statistics we are calculating is for a cluster as a whole not > member wise. Since, we autoscale a cluster. > > > > > > Yes for autoscaling a cluster the aggregated statistics should be > calculated against the cluster. However I do not think that we can mix each > statistic accorss members when calculating differences. Different members > of a cluster might be running at different resource usage levels at a given > point of time. Therefore aggregation might needed to be done at the member > level first and then on the cluster level. WDYT? > > +1 > > We need to sample stats and aggregate them on fixed intervals before > calculating the gradients. > > Thanks. > > > > > > > -- > > Imesh Gunaratne > > > > Technical Lead, WSO2 > > Committer & PMC Member, Apache Stratos > -- -- Lahiru Sandaruwan Committer and PMC member, Apache Stratos, Senior Software Engineer, WSO2 Inc., http://wso2.com lean.enterprise.middleware email: lahi...@wso2.com blog: http://lahiruwrites.blogspot.com/ linked-in: http://lk.linkedin.com/pub/lahiru-sandaruwan/16/153/146
