The compression process is a pipeline implemented for the most part on top of the WebGraph framework and ecosystem libraries. The compression pipeline consists of the following steps:
Each of these steps is briefly described below. For more details see the following paper:
Paolo Boldi, Antoine Pietri, Sebastiano Vigna, Stefano Zacchiroli. Ultra-Large-Scale Repository Analysis via Graph Compression. In proceedings of SANER 2020: The 27th IEEE International Conference on Software Analysis, Evolution and Reengineering. IEEE 2020.
In order to practically perform graph compression, install the
module and use the
swh graph compress command line interface of the
compression driver, that will conduct the various steps in the right order.
swh graph compress --help for usage details.
Mapping between the strings and longs ids is needed before compressing the graph. From the Sux4J utility tool, we use the GOVMinimalPerfectHashFunction class, mapping with no collisions N keys to N consecutive integers.
The step produces a
.mph file (MPH stands for Minimal Perfect
Hash-function) storing the hash function taking as input a string and returning
a unique integer.
2. BV compress¶
This is the first actual compression step, building a compressed version of the input graph using WebGraph techniques presented in the framework paper. We use the ScatteredArcsASCIIGraph class, from WebGraph.
The resulting BV graph is stored as a set of files:
.graph: the compressed graph in the BV format
.offsets: offsets values to read the bit stream graph file
.obl: offsets cache to load the graph faster
.properties: entries used to correctly decode graph and offset files
In the LLP paper, authors propose an empirical analysis linking node ordering and high compression ratio: it is important to use an ordering of nodes ids such that vertices from the same host are close to one another.
The resulting ordering is stored in the
.order file, listing nodes ids in
order of traversal.
Once the order is computed (BFS or another ordering technique), the final compressed graph is created based on the initial BV compress result, and using the new node order mapping. The permutation uses the Transform class from WebGraph framework.
The final compressed graph is only stored in the resulting
Compute various statistics on the final compressed graph:
.stats: entries such as number of nodes, edges, avg/min/max degree, average locality, etc.
.indegree: graph indegree distribution
.outdegree: graph outdegree distribution
This step uses the Stats class from WebGraph.