{"title":"基于查询重写的分布式复杂事件处理","authors":"T. Dilrukshi, Surangika Ranathunga","doi":"10.1109/MERCon52712.2021.9525778","DOIUrl":null,"url":null,"abstract":"This paper presents the STHITHIKA distributed Complex Event Processing (CEP) system, which is focused on the problem of optimally processing a large number of different event streams using a large number of CEP queries in a distributed manner. Optimization is done in two levels: individual query optimization using query rewriting, and optimization of query distribution across multiple nodes. Cost of individual queries, number of events streams common to queries, CPU and memory utilization of nodes that run CEP queries, type of queries, and the number of queries in each node are the factors considered in the query distribution algorithm. Experiments show that with these optimizations, compared to existing systems, STHITHIKA is capable of providing a higher system throughput, without making an adverse impact on event duplication or load variance across processing nodes. It is also more robust to event bursts.","PeriodicalId":6855,"journal":{"name":"2021 Moratuwa Engineering Research Conference (MERCon)","volume":"11 1","pages":"705-710"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"STHITHIKA: Distributed Complex Event Processing with Query Rewriting\",\"authors\":\"T. Dilrukshi, Surangika Ranathunga\",\"doi\":\"10.1109/MERCon52712.2021.9525778\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the STHITHIKA distributed Complex Event Processing (CEP) system, which is focused on the problem of optimally processing a large number of different event streams using a large number of CEP queries in a distributed manner. Optimization is done in two levels: individual query optimization using query rewriting, and optimization of query distribution across multiple nodes. Cost of individual queries, number of events streams common to queries, CPU and memory utilization of nodes that run CEP queries, type of queries, and the number of queries in each node are the factors considered in the query distribution algorithm. Experiments show that with these optimizations, compared to existing systems, STHITHIKA is capable of providing a higher system throughput, without making an adverse impact on event duplication or load variance across processing nodes. It is also more robust to event bursts.\",\"PeriodicalId\":6855,\"journal\":{\"name\":\"2021 Moratuwa Engineering Research Conference (MERCon)\",\"volume\":\"11 1\",\"pages\":\"705-710\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Moratuwa Engineering Research Conference (MERCon)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MERCon52712.2021.9525778\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Moratuwa Engineering Research Conference (MERCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MERCon52712.2021.9525778","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
STHITHIKA: Distributed Complex Event Processing with Query Rewriting
This paper presents the STHITHIKA distributed Complex Event Processing (CEP) system, which is focused on the problem of optimally processing a large number of different event streams using a large number of CEP queries in a distributed manner. Optimization is done in two levels: individual query optimization using query rewriting, and optimization of query distribution across multiple nodes. Cost of individual queries, number of events streams common to queries, CPU and memory utilization of nodes that run CEP queries, type of queries, and the number of queries in each node are the factors considered in the query distribution algorithm. Experiments show that with these optimizations, compared to existing systems, STHITHIKA is capable of providing a higher system throughput, without making an adverse impact on event duplication or load variance across processing nodes. It is also more robust to event bursts.