The Graphalytics benchmark is an industrial-grade benchmark for graph analysis platforms such as Giraph. It consists of six core algorithms, standard datasets, synthetic dataset generators, and reference outputs, enabling the objective comparison of graph analysis platforms.
The design of the benchmark process takes into account that graph-processing is impeded by three dimensions of diversity: platform, algorithms and dataset.
The benchmark harness consists of a core component, which is extendable by a driver for each different platform implementation. The choice of the six algorithms:
- breadth-first search,
- weakly connected components,
- community detection using label propagation,
- local clustering coefficient, and
- single-source shortest paths
was carefully motivated, using the LDBC TUC and extensive literature surveys to ensure good coverage of scenarios. The standard datasets include both real and synthetic datasets, which are classified into intuitive “T-shirt” sizes (e.g., S, M, L, XL).
Each experiment set in Graphalytics consists of multiple platform runs (a platform executes an algorithm on a dataset), and diverse set of experiments are carried out to evaluate different performance characteristics of a system-under-test.
All completed benchmarks must go through a strict validation process to ensure the integrity of the performance results.
The Graphalytics benchmarking process is made future-proof, through a renewal process that takes place regularly to ensure that the benchmark process meets the state-of-the-art development in the field of graph analytics.
To enhance the depth of the benchmark process, Graphalytics also facilitates a plugin-architecture, which allows external software tools to be added to the benchmark harness. For instance, it is possible to also use SNB datagen (the data generator of the LDBC Social Network Benchmark), an advanced synthetic dataset generator to create synthetic graphs for custom test scenarios, or to use Granula, a fine-grained performance evaluation tool to obtain enriched performance results.
The development of Graphalytics is supported by many active vendors in the field of large-scale graph analytics. Currently, Graphalytics already facilitates benchmark for a large number of graph analytics platforms, such as Giraph, GraphX, GraphMat, OpenG, and PGXD, allowing comparison of the state-of-the-art system performance of both community-driven and industrial-driven platforms. To get started, the details of the Graphalyics documentation and its software components are described on the Graphalytics developer page.