{"title":"可伸缩的基于对等的RDF管理","authors":"Christoph Böhm, Daniel Hefenbrock, Felix Naumann","doi":"10.1145/2362499.2362523","DOIUrl":null,"url":null,"abstract":"Handling web-scale RDF data requires sophisticated data management that scales easily and integrates seamlessly into existing analysis workflows. We present Hdrs-- a scalable storage infrastructure that enables online-analysis of very large RDF data sets. Hdrs combines state-of-the-art data management techniques to organize triples in indexes that are sharded and stored in a peer-to-peer system. The store is open source and integrates well with Hadoop MapReduce or any other client application.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Scalable peer-to-peer-based RDF management\",\"authors\":\"Christoph Böhm, Daniel Hefenbrock, Felix Naumann\",\"doi\":\"10.1145/2362499.2362523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Handling web-scale RDF data requires sophisticated data management that scales easily and integrates seamlessly into existing analysis workflows. We present Hdrs-- a scalable storage infrastructure that enables online-analysis of very large RDF data sets. Hdrs combines state-of-the-art data management techniques to organize triples in indexes that are sharded and stored in a peer-to-peer system. The store is open source and integrates well with Hadoop MapReduce or any other client application.\",\"PeriodicalId\":275036,\"journal\":{\"name\":\"International Conference on Semantic Systems\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Semantic Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2362499.2362523\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Semantic Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2362499.2362523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Handling web-scale RDF data requires sophisticated data management that scales easily and integrates seamlessly into existing analysis workflows. We present Hdrs-- a scalable storage infrastructure that enables online-analysis of very large RDF data sets. Hdrs combines state-of-the-art data management techniques to organize triples in indexes that are sharded and stored in a peer-to-peer system. The store is open source and integrates well with Hadoop MapReduce or any other client application.
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