Eventually, every node of the graph has been visited. If there are no more unvisited nodes at the current depth, nodes at a higher depth are traversed. The breadth-first search algorithm starts at a root node and traverses every node with depth one. Data stored in RAM using memory-efficient custom data structures On-disk persistence Tabular result sets Uses the popular graph query language openCypher. The measure of performance for an external memory algorithm is the number of I/Os it performs.Įxternal memory breadth-first search M is the size of the internal memory, B is the block size of a disk and D is the number of parallel disks.

A machine is specified by three parameters: M, B and D.

Since accessing the disk is magnitudes slower than accessing internal memory, the need for efficient traversal of external memory exists.įor external memory algorithms the external memory model by Aggarwal and Vitter is used for analysis. This view neglects the fact, that for huge instances part of the graph resides on disk rather than internal memory. Graph traversal algorithms, like breadth-first search and depth-first search, are analyzed using the von Neumann model, which assumes uniform memory access cost. External memory graph traversal is a type of graph traversal optimized for accessing externally stored memory. The goal of a graph traversal algorithm is to visit (and / or process) every node of a graph. Graph traversal is a subroutine in most graph algorithms.

Memory on disk graph