Yep, a subproject would be the alternative. In this case we would give you PMC and committer rights so you can actively work on that. However this would make the mapreduce part more or less useless, so if you want to go the hybrid way, feel free to submit an incubation request.
2012/9/7 Suraj Menon <[email protected]> > I think Thomas has a point. How about making it a sub-module/sub-project of > Hama for now? If/When it gains enough community support to make it a top > level project, you can fork it as a separate project. > I am not completely aware of the procedures and requirements for getting > external project as sub-project. > We can look into it if you are ready to take this route. > > > Could you please send me a link for setting up an open-source Apache > project? > If I am right this is what you are looking for - > http://incubator.apache.org/guides/proposal.html > http://incubator.apache.org/sitemap.html > > Good luck, > Suraj > > On Fri, Sep 7, 2012 at 11:40 AM, Thomas Jungblut > <[email protected]>wrote: > > > Although I think this is a great project, I think that you will not meet > > the requirements. > > You need a community and a charter to get it into the incubation. > > > > What about hosting it on Github? > > > > 2012/9/7 Leonidas Fegaras <[email protected]> > > > > > Yes, this is a great idea. I have used GIT on my own server but I don't > > > know how to do this for ASF. Could you please send me a link for > setting > > up > > > an open-source Apache project? > > > > > > > > > On 09/05/2012 10:51 AM, Edward J. Yoon wrote: > > > > > >> If you can open source this then I'm sure the ASF community can help > > >> you and make this software better. > > >> > > >> Pls feel free to ask us if you need any assistance donating source > > >> code to the ASF or contributing to the Hama project in the future. > > >> > > >> On Thu, Aug 30, 2012 at 11:40 PM, Leonidas Fegaras< > [email protected]> > > >> wrote: > > >> > > >>> Yes sure. I have fixed the bug with the repeat stopping condition > but I > > >>> have > > >>> only tested pagerank on my small cluster. I still need to fix the > > k-means > > >>> clustering (it's a special case because you improve a fixed number of > > >>> points). > > >>> Leonidas > > >>> > > >>> > > >>> On Aug 30, 2012, at 9:02 AM, Edward J. Yoon wrote: > > >>> > > >>> Shall we work together? > > >>>> > > >>>> On Fri, Aug 24, 2012 at 9:01 PM, Leonidas Fegaras< > [email protected] > > > > > >>>> wrote: > > >>>> > > >>>>> Thank you very much for your interest and for testing my system. > > >>>>> It seems that my release was premature: It worked for some random > > data > > >>>>> but > > >>>>> didn't for some others. It's a minor logical error that I will try > to > > >>>>> fix > > >>>>> in > > >>>>> the next few days. The problem is with the stopping condition of > the > > >>>>> repeat > > >>>>> expression that calculates the new pagerank from the old. It must > > stop > > >>>>> if > > >>>>> ALL peers reach the specified precision. This is done by having > > those > > >>>>> peers > > >>>>> that need to continue send a message to others to continue. It > seems > > >>>>> that > > >>>>> now when all peers agree at the same time, the program works fine. > > But > > >>>>> if > > >>>>> one finishes sooner, instead of continuing the repeat loop, it runs > > >>>>> away > > >>>>> to > > >>>>> the next BSP step that follows the repeat, then exits prematurely > and > > >>>>> the > > >>>>> system hangs. The casting errors are due to the run-away peers > > >>>>> executing > > >>>>> the > > >>>>> wrong BSP steps reading wrong messages. Queries without repeat > though > > >>>>> are > > >>>>> OK. > > >>>>> By the way, I had a problem exchanging large amount of data during > > sync > > >>>>> (I > > >>>>> discussed this with Thomas). My solution was to to break a BSP > > >>>>> superstep > > >>>>> into multiple substeps so that each substep can handle a max number > > of > > >>>>> messages. Of course my program has to collect all messages in a > > vector > > >>>>> in > > >>>>> memory. When the vector is too big, it is spilled in a local file. > > This > > >>>>> moved the problem from the Hama side to my side and allowed me to > > >>>>> handle > > >>>>> larger data, especially in joins. I think this problem of > exchanging > > >>>>> large > > >>>>> amount of data during a superstep is currently a weakness of Hama. > > >>>>> Leonidas > > >>>>> > > >>>>> > > >>>>> > > >>>>> On 08/24/2012 04:15 AM, Thomas Jungblut wrote: > > >>>>> > > >>>>>> > > >>>>>> BTW, should we feature this on our website? > > >>>>>> > > >>>>>> 2012/8/24 Thomas Jungblut<thomas.jungblut@**gmail.com< > > [email protected]> > > >>>>>> > > > >>>>>> > > >>>>>> Hi Leonidas! > > >>>>>>> > > >>>>>>> I have to admit that I have known what is going on (and had to > keep > > >>>>>>> silent), but I have to say: Thank you very much! > > >>>>>>> This will help many people writing BSPs in a more easier way. > > >>>>>>> > > >>>>>>> Of course this is not as fast as the native BSP code, Hive and > Pig > > >>>>>>> suffer > > >>>>>>> from the same problems in MR. > > >>>>>>> But it gives people the opportunity to develop faster and get > their > > >>>>>>> code > > >>>>>>> in production with just a minor time expense. > > >>>>>>> > > >>>>>>> And I think, that we will help you gladly on improving the BSP > part > > >>>>>>> of > > >>>>>>> your framework. At least I would do ;) > > >>>>>>> > > >>>>>>> Thanks! > > >>>>>>> > > >>>>>>> 2012/8/24 Edward J. Yoon<[email protected]> > > >>>>>>> > > >>>>>>> Here's my few test results on Oracle BDA (40G/s infiniband > > network). > > >>>>>>> > > >>>>>>>> > > >>>>>>>> It seems slow than our PageRank example. > > >>>>>>>> > > >>>>>>>> P.S., There are some errors so I couldn't test large-scale. > > >>>>>>>> (java.lang.ClassCastException: hadoop.mrql.MR_int cannot be cast > > to > > >>>>>>>> hadoop.mrql.Inv and java.lang.Error: Cannot clear a > > non-materialized > > >>>>>>>> sequence ..., etc.) > > >>>>>>>> > > >>>>>>>> > > >>>>>>>> > > >>>>>>>> == 100K nodes and 1M edges == > > >>>>>>>> > > >>>>>>>> *** Using 10 BSP tasks (out of a max 10). Each task will handle > > >>>>>>>> about > > >>>>>>>> 2383611 bytes of input data. > > >>>>>>>> > > >>>>>>>> Run time: 30.384 secs > > >>>>>>>> > > >>>>>>>> *** Using 20 BSP tasks (out of a max 20). Each task will handle > > >>>>>>>> about > > >>>>>>>> 1191805 bytes of input data. > > >>>>>>>> > > >>>>>>>> Run time: 24.412 secs > > >>>>>>>> > > >>>>>>>> On Fri, Aug 24, 2012 at 9:36 AM, Edward J. Yoon > > >>>>>>>> <[email protected]> > > >>>>>>>> wrote: > > >>>>>>>> > > >>>>>>>>> > > >>>>>>>>> Wow, very interesting. I'm going to install and test on my > large > > >>>>>>>>> > > >>>>>>>> > > >>>>>>>> cluster. > > >>>>>>>> > > >>>>>>>>> > > >>>>>>>>> On Fri, Aug 24, 2012 at 4:41 AM, Leonidas Fegaras > > >>>>>>>>> <[email protected]> > > >>>>>>>>> > > >>>>>>>> > > >>>>>>>> wrote: > > >>>>>>>> > > >>>>>>>>> > > >>>>>>>>>> Dear Hama users, > > >>>>>>>>>> I am pleased to announce that the MRQL query processing system > > can > > >>>>>>>>>> now > > >>>>>>>>>> evaluate SQL-like queries on a Hama cluster. MRQL is available > > at: > > >>>>>>>>>> > > >>>>>>>>>> http://lambda.uta.edu/mrql/ > > >>>>>>>>>> > > >>>>>>>>>> MRQL (the Map-Reduce Query Language) is an SQL-like query > > language > > >>>>>>>>>> for > > >>>>>>>>>> large-scale, distributed data analysis. MRQL is powerful > enough > > to > > >>>>>>>>>> express most common data analysis tasks over many different > > kinds > > >>>>>>>>>> of > > >>>>>>>>>> raw data, including hierarchical data and nested collections, > > such > > >>>>>>>>>> as > > >>>>>>>>>> XML data. MRQL can run in two modes: in MR (Map-Reduce) mode > > using > > >>>>>>>>>> Apache Hadoop and in BSP (Bulk Synchronous Parallel) mode > using > > >>>>>>>>>> Apache > > >>>>>>>>>> Hama. Both modes use Apache's HDFS to read and write their > data. > > >>>>>>>>>> > > >>>>>>>>>> Note that, the BSP mode is currently experimental (not > > fine-tuned > > >>>>>>>>>> yet) > > >>>>>>>>>> and lacks any fault-tolerance (if an error occurs, the entire > > job > > >>>>>>>>>> must > > >>>>>>>>>> be restarted). Due to our limited resources, MRQL has only > been > > >>>>>>>>>> tested > > >>>>>>>>>> on a small cluster (7-nodes/28-cores). We compared the BSP > mode > > >>>>>>>>>> with > > >>>>>>>>>> the MR mode by evaluating a pagerank query over a small graph > > >>>>>>>>>> (100K > > >>>>>>>>>> nodes, 1M edges) and found that BSP mode is about 4.5 times > > faster > > >>>>>>>>>> than the MR mode. Please let me know if you'd like to > contribute > > >>>>>>>>>> to > > >>>>>>>>>> this project by testing MRQL on a larger cluster. > > >>>>>>>>>> Best regards, > > >>>>>>>>>> Leonidas Fegaras > > >>>>>>>>>> University of Texas at Arlington > > >>>>>>>>>> > > >>>>>>>>>> > > >>>>>>>>> -- > > >>>>>>>>> Best Regards, Edward J. Yoon > > >>>>>>>>> @eddieyoon > > >>>>>>>>> > > >>>>>>>> > > >>>>>>>> > > >>>>>>>> > > >>>>>>>> -- > > >>>>>>>> Best Regards, Edward J. Yoon > > >>>>>>>> @eddieyoon > > >>>>>>>> > > >>>>>>>> . > > >>>>>> > > >>>>>> > > >>>> > > >>>> -- > > >>>> Best Regards, Edward J. Yoon > > >>>> @eddieyoon > > >>>> > > >>> > > >>> > > >> > > >> > > > > > >
