Continuous analytics on graph data streams using WSO2 complex event processor
| Autor: | Miyuru Dayarathna, Anoukh Jayawardena, Bhagya Rupasinghe, Sriskandarajah Suhothayan, Malith Jayasinghe, Isuru Perera, Srinath Perera |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Data stream mining
Computer science business.industry Real-time computing Complex event processing 02 engineering and technology Linked data computer.software_genre Open source Virtual machine Analytics 020204 information systems 0202 electrical engineering electronic engineering information engineering Graph (abstract data type) 020201 artificial intelligence & image processing Latency (engineering) business computer |
| Zdroj: | DEBS |
| DOI: | 10.1145/2933267.2933508 |
| Popis: | The ACM DEBS Grand Challenge 2016 focuses on analysing the properties of a time evolving social-network graph generated using LDBC (Linked Data Benchmark Council) Social Network Benchmark. In this paper we present how we used WSO2 CEP, an open source, commercially available Complex Event Processing Engine, to solve the problem. On a 4-core/8 GB virtual machine, our solution processed 90,000 events per second with a mean latency of 6 ms for query 1. For query 2 it processed 210,000 events per second with a mean latency of only 0.3 ms. The paper describes the solution we propose, the experiments' results, and presents how we optimized the performance of our solution. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|