PartitioningRunner rewrites (converted to VertexWritable) records to particular partition files. and then, GraphJobRunner reads just VertexWritable.
To Hama devs, BTW, I hadn't really thought about 'Range Partitioning' and 'integration with NoSQLs' until just now. And I just found my old opinion[1] on record converter. I didn't like 'Record converter'. 1. http://markmail.org/message/ol32pp2ixfazcxfc On Sat, May 4, 2013 at 7:36 AM, Jiwon Seo <[email protected]> wrote: > Edward, thanks for your reply. > > Right, I checked that PartitioningRunner is the only place that calls the > convertRecord method. > > However, it is not clear how that class is related to the GraphJobRunner > class. > The loadVertices() method in the GraphJobRunner does not call the > convertRecord method as in PartitioningRunner::bsp(). > > Is the GraphJobRunner::loadVertices() not used for loading vertices? > If it is used, how is it related to PartitioningRunner::bsp()? It would be > helpful to know the (rough) call stack from PartitioningRunner to > GraphJobRunner (or vice versa). > > Thanks, > > -Jiwon > >> Hi Mr.Seo, >> >> Please look at VertexInputReader.convertRecord() method. see also >> PartitioningRunner and RecordConverter classes[1]. >> >> 1. > http://svn.apache.org/repos/asf/hama/trunk/core/src/main/java/org/apache/hama/bsp/PartitioningRunner >> >>On Fri, May 3, 2013 at 5:49 PM, Jiwon Seo <[email protected]> wrote: >>> Hi, >>> >>> I'm trying to understand how vertex loading is done in hama. >>> >>> The part that I don't understand is, the relation between > VertexInputReader >>> and InputFormat. >>> >>> As far as I understand, VertexInputReader.parseVertex is the method to >>> initialize each vertex, but it is not clear where the function is called > in >>> Hama 0.6.1. >>> In Hama 0.6.0, the parseVertex function is explicitly called inside >>> GraphJobRunner::loadVertices, but in Hama 0.6.1, it is replaced with >>> peer.readNext(vertex, NullWritable.get()), and parseVertex does not seem > to >>> get called. Where is the function called? >>> >>> Thanks, >>> >>> -Jiwon -- Best Regards, Edward J. Yoon @eddieyoon
