Hi Folks,I need some input/help here to get me unblocked and moving: 1) I need to reuse/extend the DistributedContext inside the runtime perf measurement module as all algorithms inside math-scala need this, I was trying to mimic some of the H2O code and saw that they had their own engine, I am wondering what the best way is to extend DistributedContext and get the benefit of an already existing engine without needing to tie into h2o or flink, or is the only way to add an engine to point to one of those back ends, ideally I want to build the runtime perf module in a backend agnostic way and currently I dont see a way around this, thoughts?2) I also tried to reuse some of the logic inside math-scala but in digging into this code it seems that this code is strongly tied to scala test utilities
Net-Net: I just need access to the DistributedContext without linking in any test utilities or backends. Would love some advice on ways to move forward to maximize reuse.Thanks in advance. > From: [email protected] > To: [email protected] > Subject: RE: [Discuss--A proposal for building an application in mahout to > measure runtime performance of algorithms in mahout] > Date: Thu, 9 Jun 2016 21:45:13 -0700 > > Andrew et al,So I've finally been able to over the past few days got a self > contained module compiling that leverages the DistributedContext, for > starters I copied the NaiveBayes test code, ripped out the test > infrastructure code around it and then added some timers, next steps will be > to dump to csv and eventually to zeppelin, some questions before I get too > far ahead: > 1) I made the design decision to create my own trait and encapsulate the > context within that, I am wondering if I should instead leverage the context > that is already defined in math-scala ,, this however brings its own > complications in that it brings in the MahoutSuite which I'm not sure I > really need, thoughts on this > 2) I need some infrastructure to run the perf framework , I can use an azure > ubuntu vm for now but is there an AWS instance or some other vm I can > eventually use, I would really like to avoid using my mac laptop as a runtime > perf testing environment > > Thanks, I'll update JIRA as I make more headway. > > > From: [email protected] > > To: [email protected] > > Subject: RE: [Discuss--A proposal for building an application in mahout to > > measure runtime performance of algorithms in mahout] > > Date: Mon, 6 Jun 2016 08:58:49 -0700 > > > > Andrew,Thanks for the input, I will shift gears a bit and just get some > > lightweight code going that calls into mahout algorithms and does a csv > > dump out. Note that I think akka could be a good use for this as you could > > make an async call and get back a notification when the csv dump is > > finished. Also I am indeed not focusing on mapreduce algorithms and will > > be tackling the algorithms in the math-scala library. What do you think of > > making this a lightweight web based workbench using spray that committers > > can run outside of mahout through curl or something, this was my initial > > vision in using spray and its good that I'm getting early feedback. > > > > On zeppelin do you think its worthwhile that I incorporate Trevor's efforts > > to take that csv and turn that into one or two visualizations. I'm trying > > to understand how that effort may(or may not) intersect with what I'm > > trying to accomplish. > > Also point taken on the small data sets. > > Thanks > > > > > From: [email protected] > > > To: [email protected] > > > Subject: Re: [Discuss--A proposal for building an application in mahout > > > to measure runtime performance of algorithms in mahout] > > > Date: Mon, 6 Jun 2016 15:50:16 +0000 > > > > > > Saikat, > > > > > > If you're going to pursue this there is a few things that I would > > > suggest. First, keep it light weight. We don't want to bring a a lot of > > > extra dependencies or data into the distribution. I'm not sure what this > > > means as far as spray/akka, but those seem like overkill in my opinion. > > > This should be able to be kept down to a simple csv dump I think. > > > > > > Second, use Data that can be either randomly generated with a seeded RNG, > > > or a function like Mackey-Glass or downloaded (probably best), and only > > > use a small very small sample in the tests- since they're pretty long > > > currently. The main point being that we don't want to ship any large test > > > datasets with the distro. > > > > > > Third, we're not using MapReduce anymore, so focus on algorithms in the > > > math-scala library (eg. dssvd, thinqr, dals, etc.) as well as Matrix > > > algebra operations. That is where i see this being useful, so that we > > > may compare changes and optimizations going forward. > > > > > > Thanks, > > > > > > Andy > > > > > > ________________________________________ > > > From: Saikat Kanjilal <[email protected]> > > > Sent: Friday, June 3, 2016 12:35:54 AM > > > To: [email protected] > > > Subject: RE: [Discuss--A proposal for building an application in mahout > > > to measure runtime performance of algorithms in mahout] > > > > > > Hi All,Created a JIRA ticket and have moved the discussion for the > > > runtime performance framework there: > > > https://issues.apache.org/jira/browse/MAHOUT-1869 > > > @AndrewP & Trevor I would like to integrate zeppelin into the runtime > > > performance measurement framework to output some measurement related data > > > for some of the algorithms. > > > Should I wait till the zeppelin integration is completely working before > > > I incorporate this piece? > > > Also would really some feedback either on the JIRA ticket or in response > > > to this thread.Regards > > > > > > > From: [email protected] > > > > To: [email protected] > > > > Subject: [Discuss--A proposal for building an application in mahout to > > > > measure runtime performance of algorithms in mahout] > > > > Date: Thu, 19 May 2016 21:31:05 -0700 > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > This proposal will outline a runtime performance module used to measure > > > > the performance of various algorithms in mahout in the three major > > > > areas, clustering, regression and classification. The module will be a > > > > spray/scala/akka application which will be run by any current or new > > > > algorithm in mahout and will display a csv file and a set of zeppelin > > > > plots outlining the various criteria for performance. The goal of > > > > releasing any new build in mahout will be to run a set of tests for > > > > each of the algorithms to compare and contrast some benchmarks from one > > > > release to another. > > > > > > > > > > > > Architecture > > > > The run time performance application will run on top of spray/scala and > > > > akka and will make async api calls into the various mahout algorithms > > > > to generate a cvs file containing data representing the run time > > > > performance measurement calculations for each algorithm of interest as > > > > well as a set of zeppelin plots for displaying some of these results. > > > > The spray scala architecture will leverage the zeppelin server to > > > > create the visualizations. The discussion below centers around two > > > > types of algorithms to be addressed by the application. > > > > > > > > > > > > Clustering > > > > The application will consist of a set of rest APIs to do the following: > > > > > > > > > > > > a) A method to load and execute the run time perf module and takes as > > > > inputs the name of the algorithm (kmeans, fuzzy kmeans) and a location > > > > of a set of files containing various sizes of data sets > > > > > > > > > > > > /algorithm=clustering/fileLocation=/path/to/files/of/different/datasets/clusters=12,20,30,40 > > > > and finally a set of values for the number of clusters to use for each > > > > of the different sizes of the datasets > > > > > > > > > > > > The above API call will return a runId which the client program can > > > > then use to monitor the module > > > > > > > > > > > > > > > > > > > > b) A method to monitor the application to ensure that its making > > > > progress towards generating the zeppelin plots > > > > /monitor/runId=456 > > > > > > > > > > > > > > > > > > > > The above method will execute asynchronously by calling into the mahout > > > > kmeans (fuzzy kmeans) clustering implementations and will generate > > > > zeppelin plots showing the normalized time on the y axis and the number > > > > of clusters in the x axis. The spray/scala akka framework will allow > > > > the client application to receive a callback when the run time > > > > performance calculations are actually completed. For now the > > > > calculations for measuring run time performance will contain: a) the > > > > ratio of the number of points clustered correctly to the total number > > > > of points b) the total time taken for the algorithm to run . These > > > > items will be represented in separate zeppelin plots. > > > > > > > > > > > > > > > > > > > > Regression > > > > a) The runtime performance module will run the likelihood ratio test > > > > with a different set of features in every run . We will introduce a > > > > rest API to run the likelihood ratio test and return the results, this > > > > will once again be an sync call through the spray/akka stack. > > > > > > > > > > > > > > > > > > > > > > > > > > > > b) The run time performance module will contain the following metrics > > > > for every algorithm: 1) cpu usage 2) memory usage 3) time taken for > > > > algorithm to converge and run to completion. These metrics will be > > > > reported on top of the zeppelin graphs for both the regression and the > > > > different clustering algorithms mentioned above. > > > > > > > > How does the application get runThe run time performance measuring > > > > application will get invoked from the command line, eventually it would > > > > be worthwhile to hook this into some sort of integration test suite to > > > > certify the different mahout releases. > > > > > > > > > > > > I will add more thoughts around this and create a JIRA ticket only once > > > > there's enough consensus between the committers that this is headed in > > > > the right direction. I will also add some more thoughts on measuring > > > > run time performance of some of the other algorithms after some more > > > > research. > > > > Would love feedback or additional things to consider that I might have > > > > missed. If its more appropriate I can move the discussion to a jira > > > > ticket as well so please let me know.Thanks in advance. > > >
