{"title":"MM-infer:一个多模型图式推断工具","authors":"P. Koupil, Sebastián Hricko, I. Holubová","doi":"10.48786/edbt.2022.52","DOIUrl":null,"url":null,"abstract":"The variety feature of Big Data, represented by multi-model data, has brought a new dimension of complexity to data management. The need to process a set of distinct but interlinked models is a challenging task. In our demonstration, we present our prototype implementation MM-infer that ensures inference of a common schema of multi-model data. It supports popular data models and all three types of their mutual combinations, i.e., inter-model references, the embedding of models, and cross-model redundancy. Following the current trends, the implementation can efficiently process large amounts of data. To the best of our knowledge, ours is the first tool addressing schema inference in the world of multi-model databases.","PeriodicalId":88813,"journal":{"name":"Advances in database technology : proceedings. International Conference on Extending Database Technology","volume":"31 1","pages":"2:566-2:569"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"MM-infer: A Tool for Inference of Multi-Model Schemas\",\"authors\":\"P. Koupil, Sebastián Hricko, I. Holubová\",\"doi\":\"10.48786/edbt.2022.52\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The variety feature of Big Data, represented by multi-model data, has brought a new dimension of complexity to data management. The need to process a set of distinct but interlinked models is a challenging task. In our demonstration, we present our prototype implementation MM-infer that ensures inference of a common schema of multi-model data. It supports popular data models and all three types of their mutual combinations, i.e., inter-model references, the embedding of models, and cross-model redundancy. Following the current trends, the implementation can efficiently process large amounts of data. To the best of our knowledge, ours is the first tool addressing schema inference in the world of multi-model databases.\",\"PeriodicalId\":88813,\"journal\":{\"name\":\"Advances in database technology : proceedings. International Conference on Extending Database Technology\",\"volume\":\"31 1\",\"pages\":\"2:566-2:569\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in database technology : proceedings. International Conference on Extending Database Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.48786/edbt.2022.52\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in database technology : proceedings. International Conference on Extending Database Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48786/edbt.2022.52","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MM-infer: A Tool for Inference of Multi-Model Schemas
The variety feature of Big Data, represented by multi-model data, has brought a new dimension of complexity to data management. The need to process a set of distinct but interlinked models is a challenging task. In our demonstration, we present our prototype implementation MM-infer that ensures inference of a common schema of multi-model data. It supports popular data models and all three types of their mutual combinations, i.e., inter-model references, the embedding of models, and cross-model redundancy. Following the current trends, the implementation can efficiently process large amounts of data. To the best of our knowledge, ours is the first tool addressing schema inference in the world of multi-model databases.