Hi Martin, thanks a lot for sharing! This is a very useful tool. I only had a quick look, but if we merge label and payload inside a Tuple2, then it should also be Gelly-compatible :)
Cheers, Vasia. On 6 October 2015 at 10:03, Martin Junghanns <m.jungha...@mailbox.org> wrote: > Hi all, > > For our benchmarks with Flink, we are using a data generator provided by > the LDBC project (Linked Data Benchmark Council) [1][2]. The generator uses > MapReduce to create directed, labeled, attributed graphs that mimic > properties of real online social networks (e.g, degree distribution, > diameter). The output is stored in several files either local or in HDFS. > Each file represents a vertex, edge or multi-valued property class. > > I wrote a little tool, that parses and transforms the LDBC output into two > datasets representing vertices and edges. Each vertex has a unique id, a > label and payload according to the LDBC schema. Each edge has a unique id, > a label, source and target vertex IDs and also payload according to the > schema. > > I thought this may be useful for others so I put it on GitHub [2]. It > currently uses Flink 0.10-SNAPSHOT as it depends on some fixes made in > there. > > Best, > Martin > > [1] http://ldbcouncil.org/ > [2] https://github.com/ldbc/ldbc_snb_datagen > [3] https://github.com/s1ck/ldbc-flink-import >
