Absolutely spot on - between FlashGraph and Frank McSherry's COST work, the two have really pushed the envelope on efficient large scale graph analysis.
Frank McSherry wrote a "call to arms" for the broader graph community at [1]. The main point of interest is that academia generally compared their work with existing distributed graph processing systems, celebrating when any achievements were made, yet not aware of the significant overheads brought on by the distributed approach. Both Frank's work (run on a single laptop) and FlashGraph (run on a single powerful machine) run far faster than the distributed approach and have very few disadvantages.
Note: I'm a data scientist at Common Crawl and Frank's graph computation discussion article was a guest post at our blog.
Frank McSherry wrote a "call to arms" for the broader graph community at [1]. The main point of interest is that academia generally compared their work with existing distributed graph processing systems, celebrating when any achievements were made, yet not aware of the significant overheads brought on by the distributed approach. Both Frank's work (run on a single laptop) and FlashGraph (run on a single powerful machine) run far faster than the distributed approach and have very few disadvantages.
Note: I'm a data scientist at Common Crawl and Frank's graph computation discussion article was a guest post at our blog.
[1]: http://blog.commoncrawl.org/2015/04/evaluating-graph-computa...