Borealis-R: a replication-transparent stream processing system for wide-area monitoring applications
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Challenges in dependable internet-scale stream processing
Proceedings of the 2nd workshop on Dependable distributed data management
Out-of-order processing: a new architecture for high-performance stream systems
Proceedings of the VLDB Endowment
Detouring and replication for fast and reliable internet-scale stream processing
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Proceedings of the Fourteenth International Database Engineering & Applications Symposium
Proceedings of the VLDB Endowment
Decentralized management of bi-modal network resources in a distributed stream processing platform
Journal of Parallel and Distributed Computing
Fault injection-based assessment of partial fault tolerance in stream processing applications
Proceedings of the 5th ACM international conference on Distributed event-based system
Pollux: towards scalable distributed real-time search on microblogs
Proceedings of the 16th International Conference on Extending Database Technology
Rollback-recovery without checkpoints in distributed event processing systems
Proceedings of the 7th ACM international conference on Distributed event-based systems
Hi-index | 0.00 |
We present a replication-based approach that realizes both fast and highly-available stream processing over wide area networks. In our approach, multiple operator replicas send outputs to each downstream replica so that it can use whichever data arrives first. To further expedite the data flow, replicas run independently, possibly processing data in different orders. Despite this complication, our approach always delivers what non-replicated processing would produce without failures. We call this guarantee replication transparency. In this paper, we first discuss semantic issues for replication transparency and extend stream-processing primitives accordingly. Next, we develop an algorithm that manages replicas at geographically dispersed servers. This algorithm strives to achieve the best latency guarantee, relative to the cost of replication. Finally, we substantiate the utility of our work through experiments on PlanetLab servers as well as simulations based on real network traces.