{"title":"集中与分布式环境下XML查询处理的性能评价","authors":"S. Subramaniam, S. Haw, Lay-Ki Soon","doi":"10.1145/3372422.3372431","DOIUrl":null,"url":null,"abstract":"eXtensible Markup Language (XML) has been used to transfer data among a wide variety of systems. The increasing usage of XML data and increase in query workloads makes XML unrealisable for centralized storage. Therefore, a distributed query evaluation strategy is well-suited to access these types of collections without having to ship large volumes of irrelevant data across the network. A centralized planning and distributed execution strategy can be used in processing XML queries in distributed manner. In this paper, a technique that processes query in distributed environment is presented, with a pruning technique in local distributed servers and the central server federates the results sent by the distributed servers. A series of evaluations were that compares the performance of centralized and distributed techniques using same set of queries on two different datasets. The results show that the proposed technique, D-DGReLab+ outperformed other centralized techniques, TwigStack and QTwig.","PeriodicalId":118684,"journal":{"name":"Proceedings of the 2019 2nd International Conference on Computational Intelligence and Intelligent Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Performance Evaluation of XML Query Processing in Centralized and Distributed Environment\",\"authors\":\"S. Subramaniam, S. Haw, Lay-Ki Soon\",\"doi\":\"10.1145/3372422.3372431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"eXtensible Markup Language (XML) has been used to transfer data among a wide variety of systems. The increasing usage of XML data and increase in query workloads makes XML unrealisable for centralized storage. Therefore, a distributed query evaluation strategy is well-suited to access these types of collections without having to ship large volumes of irrelevant data across the network. A centralized planning and distributed execution strategy can be used in processing XML queries in distributed manner. In this paper, a technique that processes query in distributed environment is presented, with a pruning technique in local distributed servers and the central server federates the results sent by the distributed servers. A series of evaluations were that compares the performance of centralized and distributed techniques using same set of queries on two different datasets. The results show that the proposed technique, D-DGReLab+ outperformed other centralized techniques, TwigStack and QTwig.\",\"PeriodicalId\":118684,\"journal\":{\"name\":\"Proceedings of the 2019 2nd International Conference on Computational Intelligence and Intelligent Systems\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 2nd International Conference on Computational Intelligence and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3372422.3372431\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 2nd International Conference on Computational Intelligence and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3372422.3372431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance Evaluation of XML Query Processing in Centralized and Distributed Environment
eXtensible Markup Language (XML) has been used to transfer data among a wide variety of systems. The increasing usage of XML data and increase in query workloads makes XML unrealisable for centralized storage. Therefore, a distributed query evaluation strategy is well-suited to access these types of collections without having to ship large volumes of irrelevant data across the network. A centralized planning and distributed execution strategy can be used in processing XML queries in distributed manner. In this paper, a technique that processes query in distributed environment is presented, with a pruning technique in local distributed servers and the central server federates the results sent by the distributed servers. A series of evaluations were that compares the performance of centralized and distributed techniques using same set of queries on two different datasets. The results show that the proposed technique, D-DGReLab+ outperformed other centralized techniques, TwigStack and QTwig.