Hi all, we're considering different libraries and approaches for the construction of large sized graphs (using Twitter data) - upon construction graph algorithms will be evaluated, so the purpose is more for knowledge discovery rather than visualization.
Currently, it takes 4 hours to generate a graph for a twitter data set that has 21 days worth of twitter data.
1. Which would you recommend, Node4J or Jung, for this purpose?
2. Would HaDoop be a good choice to spread the construction task across different machines in order to save time?
3. How can we store a very large graph in memory , and how can it be made persistent?