{"title":"DISCO:分布式计算即服务","authors":"Balázs Mészáros, P. Harsh, T. Bohnert","doi":"10.1145/3147213.3149216","DOIUrl":null,"url":null,"abstract":"The setup of distributed computing clusters and the installation of data analysis frameworks can be cumbersome and requires a great deal of knowledge in a plenitude of fields. We have developed DISCO, a service which is alleviating the data scientist from these hurdles. This paper shows up the competitiveness of DISCO with an existing solution.","PeriodicalId":341011,"journal":{"name":"Proceedings of the10th International Conference on Utility and Cloud Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DISCO: Distributed Computing as a Service\",\"authors\":\"Balázs Mészáros, P. Harsh, T. Bohnert\",\"doi\":\"10.1145/3147213.3149216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The setup of distributed computing clusters and the installation of data analysis frameworks can be cumbersome and requires a great deal of knowledge in a plenitude of fields. We have developed DISCO, a service which is alleviating the data scientist from these hurdles. This paper shows up the competitiveness of DISCO with an existing solution.\",\"PeriodicalId\":341011,\"journal\":{\"name\":\"Proceedings of the10th International Conference on Utility and Cloud Computing\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the10th International Conference on Utility and Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3147213.3149216\",\"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 the10th International Conference on Utility and Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3147213.3149216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The setup of distributed computing clusters and the installation of data analysis frameworks can be cumbersome and requires a great deal of knowledge in a plenitude of fields. We have developed DISCO, a service which is alleviating the data scientist from these hurdles. This paper shows up the competitiveness of DISCO with an existing solution.
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