What is a good design pattern/structure to represent Direct Acyclic Graph in Java?

Question

I need to store a reasonably large Direct Acyclic Graph in Java (order of 100,000 nodes, depth between 7 and 20, irregular shaped, average depth 13).

What would be the best-performing data structure(s) to store it if the predominant operation I need after building the data structure is:

• 99% operations: Find a full set of accendant paths (from the root down to a given node)
• 1% operations: Find all children, or more often, all ancestors, of a given node.

As can be obvious, I'd like the first operation to be O(1) if possible, as opposed to O(Average-Depth)

Please note that for the purposes of this question, the data structure is write-once: after I build it from a list of nodes and vertices, the graph topology will never change .

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My naive implementation would be to store it as a combination of:

HashMap<Integer, Integer[]> childrenPerParent;
HashMap<Integer, Integer[]> ascendantPaths; 

Eg I store, for each node: a list of children of that node; and separately, a set of paths to the root from that node.

Downside: This seems very wasteful as far as space (we basically store each of the inner graph nodes multiples of multiples of times in the ascendantPaths - eg given size estimates, we would store extra 100,000 * 13 = 1,3Million node copies in ascendantPaths , each of which is an object to be created and stored )

Answer 1

I would recommend using Neo4J . It's a graph database implemented in Java with a lot of low-level optimizations (eg, node and edge attributes are stored in their own blocks so that node identities and their edges can be packed), and it mmaps the on-disk database. Following an edge is independent of the number of nodes in the graph or edges on the origin.