Three partition refinement algorithms
SIAM Journal on Computing
Index Structures for Path Expressions
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Exploiting Local Similarity for Indexing Paths in Graph-Structured Data
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
An efficient algorithm for computing bisimulation equivalence
Theoretical Computer Science
A distributed algorithm for strong bisimulation reduction of state spaces
International Journal on Software Tools for Technology Transfer (STTT) - Special section on parallel and distributed model checking
Path queries on compressed XML
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
MapReduce: simplified data processing on large clusters
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Graph Twiddling in a MapReduce World
Computing in Science and Engineering
Power-Law Distributions in Empirical Data
SIAM Review
Design patterns for efficient graph algorithms in MapReduce
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Data-Intensive Text Processing with MapReduce
Data-Intensive Text Processing with MapReduce
LEEN: Locality/Fairness-Aware Key Partitioning for MapReduce in the Cloud
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
Advanced Topics in Bisimulation and Coinduction
Advanced Topics in Bisimulation and Coinduction
Query preserving graph compression
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Adaptive MapReduce using situation-aware mappers
Proceedings of the 15th International Conference on Extending Database Technology
Graph pattern matching revised for social network analysis
Proceedings of the 15th International Conference on Database Theory
Load Balancing in MapReduce Based on Scalable Cardinality Estimates
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
A structural approach to indexing triples
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
External memory K-bisimulation reduction of big graphs
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Efficiency and precision trade-offs in graph summary algorithms
Proceedings of the 17th International Database Engineering & Applications Symposium
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Computing the bisimulation partition of a graph is a fundamental problem which plays a key role in a wide range of basic applications. Intuitively, two nodes in a graph are bisimilar if they share basic structural properties such as labeling and neighborhood topology. In data management, reducing a graph under bisimulation equivalence is a crucial step, e.g., for indexing the graph for efficient query processing. Often, graphs of interest in the real world are massive; examples include social networks and linked open data. For analytics on such graphs, it is becoming increasingly infeasible to rely on in-memory or even I/O-efficient solutions. Hence, a trend in Big Data analytics is the use of distributed computing frameworks such as MapReduce. While there are both internal and external memory solutions for efficiently computing bisimulation, there is, to our knowledge, no effective MapReduce-based solution for bisimulation. Motivated by these observations we propose in this paper the first efficient MapReduce-based algorithm for computing the bisimulation partition of massive graphs. We also detail several optimizations for handling the data skew which often arises in real-world graphs. The results of an extensive empirical study are presented which demonstrate the effectiveness and scalability of our solution.